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Towhidul Islam

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Meade, Nigel & Islam, Towhidul, 2021. "Modelling and forecasting national introduction times for successive generations of mobile telephony," Telecommunications Policy, Elsevier, vol. 45(3).

    Cited by:

    1. Lund, Henrik & Østergaard, Poul Alberg & Nielsen, Tore Bach & Werner, Sven & Thorsen, Jan Eric & Gudmundsson, Oddgeir & Arabkoohsar, Ahmad & Mathiesen, Brian Vad, 2021. "Perspectives on fourth and fifth generation district heating," Energy, Elsevier, vol. 227(C).

  2. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).

    Cited by:

    1. Rodrigues Teixeira, Ana Carolina & Machado, Pedro Gerber & Borges, Raquel Rocha & Felipe Brito, Thiago Luis & Moutinho dos Santos, Edmilson & Mouette, Dominique, 2021. "The use of liquefied natural gas as an alternative fuel in freight transport – Evidence from a driver's point of view," Energy Policy, Elsevier, vol. 149(C).
    2. Nilsa Duarte da Silva Lima & Irenilza de Alencar Nääs & João Gilberto Mendes dos Reis & Raquel Baracat Tosi Rodrigues da Silva, 2020. "Classifying the Level of Energy-Environmental Efficiency Rating of Brazilian Ethanol," Energies, MDPI, vol. 13(8), pages 1-16, April.
    3. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries," Energies, MDPI, vol. 13(16), pages 1-20, August.
    4. Ioana Ancuta Iancu & Patrick Hendrick & Dan Doru Micu & Denisa Stet & Levente Czumbil & Stefan Dragos Cirstea, 2023. "The Influence of Cultural Factors on Choosing Low-Emission Passenger Cars," Sustainability, MDPI, vol. 15(8), pages 1-18, April.

  3. Islam, Towhidul & Meade, Nigel, 2018. "The direct and indirect effects of economic wealth on time to take-off," International Journal of Research in Marketing, Elsevier, vol. 35(2), pages 305-318.

    Cited by:

    1. V. Kumar & Nandini Nim & Amit Agarwal, 2021. "Platform-based mobile payments adoption in emerging and developed countries: Role of country-level heterogeneity and network effects," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(8), pages 1529-1558, October.
    2. Yingying Zhang Zhang & Sylvia Rohlfer, 2023. "Cultural Configurations for International Innovativeness: A review and theoretical proposal," Working Papers EMS_2023_05, Research Institute, International University of Japan.
    3. Meade, Nigel & Islam, Towhidul, 2021. "Modelling and forecasting national introduction times for successive generations of mobile telephony," Telecommunications Policy, Elsevier, vol. 45(3).

  4. Marley, A.A.J. & Islam, T. & Hawkins, G.E., 2016. "A formal and empirical comparison of two score measures for best–worst scaling," Journal of choice modelling, Elsevier, vol. 21(C), pages 15-24.

    Cited by:

    1. White, Mark H., 2021. "bwsTools: An R package for case 1 best-worst scaling," Journal of choice modelling, Elsevier, vol. 39(C).
    2. Lipovetsky, Stan, 2018. "Quantum paradigm of probability amplitude and complex utility in entangled discrete choice modeling," Journal of choice modelling, Elsevier, vol. 27(C), pages 62-73.
    3. Chrzan, Keith & Peitz, Megan, 2019. "Best-Worst Scaling with many items," Journal of choice modelling, Elsevier, vol. 30(C), pages 61-72.
    4. Amanda Working & Mohammed Alqawba & Norou Diawara, 2020. "Dynamic Attribute-Level Best Worst Discrete Choice Experiments," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 11(2), pages 1-1, March.
    5. Alexandre Brouste & Christophe Dutang & Tom Rohmer, 2022. "A Closed-form Alternative Estimator for GLM with Categorical Explanatory Variables," Post-Print hal-03689206, HAL.
    6. Echaniz, Eneko & Ho, Chinh Q. & Rodriguez, Andres & dell'Olio, Luigi, 2019. "Comparing best-worst and ordered logit approaches for user satisfaction in transit services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 752-769.

  5. Huybers, Twan & Louviere, Jordan & Islam, Towhidul, 2015. "What determines student satisfaction with university subjects? A choice-based approach," Journal of choice modelling, Elsevier, vol. 17(C), pages 52-65.

    Cited by:

    1. Anita Kéri & Erzsébet Hetesi, 2022. "Is it only the university they are satisfied with? – Foreign student satisfaction and its effect on loyalty," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 19(3), pages 601-622, September.

  6. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

    Cited by:

    1. Aggelos Skoufis & Georgios Chatzithanasis & Georgia Dede & Evangelia Filiopoulou & Thomas Kamalakis & Christos Michalakelis, 2023. "Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 211-227, February.
    2. Hoeschele, Thomas & Dietzel, Christoph & Kopp, Daniel & Fitzek, Frank H.P. & Reisslein, Martin, 2021. "Importance of Internet Exchange Point (IXP) infrastructure for 5G: Estimating the impact of 5G use cases," Telecommunications Policy, Elsevier, vol. 45(3).
    3. Elias Aravantinos & Dimitris Varoutas, 2022. "A revisit of fixed and mobile broadband diffusion in the OECD: a new classification," Netnomics, Springer, vol. 22(2), pages 71-84, October.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Yunrong Li & Ricardo Mora, 2022. "On the use of social networking services and the ability to socialize: evidence from Chinese children aged 10 to 15," Applied Economics, Taylor & Francis Journals, vol. 54(49), pages 5639-5654, October.
    6. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Predicting diffusion dynamics and launch time strategy for mobile telecommunication services: an empirical analysis," Information Technology and Management, Springer, vol. 22(1), pages 33-51, March.
    7. Aravantinos, Elias & Petre, Konstantin & Katsianis, Dimitris & Varoutas, Dimitris, 2021. "Determinants of FTTH tariffs evolution in EU: A panel data analysis," Telecommunications Policy, Elsevier, vol. 45(10).
    8. Katsikopoulos, Konstantinos V. & Durbach, Ian N. & Stewart, Theodor J., 2018. "When should we use simple decision models? A synthesis of various research strands," Omega, Elsevier, vol. 81(C), pages 17-25.
    9. João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
    10. Kim, Gabjo & Bae, Jinwoo, 2017. "A novel approach to forecast promising technology through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 228-237.
    11. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.

  7. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.

    Cited by:

    1. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    2. Edward Oughton, 2017. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04, Cambridge Judge Business School, University of Cambridge.
    3. Meade, Nigel & Islam, Towhidul, 2021. "Modelling and forecasting national introduction times for successive generations of mobile telephony," Telecommunications Policy, Elsevier, vol. 45(3).
    4. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.

  8. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.

    Cited by:

    1. Bessi, Alessandro & Guidolin, Mariangela & Manfredi, Piero, 2021. "The role of gas on future perspectives of renewable energy diffusion: Bridging technology or lock-in?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Tolliver, Clarence & Keeley, Alexander Ryota & Managi, Shunsuke, 2020. "Policy targets behind green bonds for renewable energy: Do climate commitments matter?," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    4. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    5. Furlan, Claudia & Guidolin, Mariangela & Guseo, Renato, 2016. "Has the Fukushima accident influenced short-term consumption in the evolution of nuclear energy? An analysis of the world and seven leading countries," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 37-49.
    6. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    7. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    8. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    9. Khalid Zaman, 2015. "Determinants of Nuclear Energy Consumption in South Asia: Economic and Energy Security Issues," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 822-827.
    10. Scholten, Daniel & Bosman, Rick, 2016. "The geopolitics of renewables; exploring the political implications of renewable energy systems," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 273-283.
    11. Kobos, Peter H. & Malczynski, Leonard A. & Walker, La Tonya N. & Borns, David J. & Klise, Geoffrey T., 2018. "Timing is everything: A technology transition framework for regulatory and market readiness levels," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 211-225.
    12. Dincer, Hasan & Yuksel, Serhat, 2019. "Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach," Energy, Elsevier, vol. 175(C), pages 1259-1270.
    13. Bunea, Anita M. & Della Posta, Pompeo & Guidolin, Mariangela & Manfredi, Piero, 2020. "What do adoption patterns of solar panels observed so far tell about governments’ incentive? Insights from diffusion models," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    14. Guidolin, Mariangela & Alpcan, Tansu, 2019. "Transition to sustainable energy generation in Australia: Interplay between coal, gas and renewables," Renewable Energy, Elsevier, vol. 139(C), pages 359-367.
    15. Can Şener, Şerife Elif & Sharp, Julia L. & Anctil, Annick, 2018. "Factors impacting diverging paths of renewable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2335-2342.
    16. Cuce, Erdem, 2016. "Toward multi-functional PV glazing technologies in low/zero carbon buildings: Heat insulation solar glass – Latest developments and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1286-1301.
    17. Liobikienė, Genovaitė & Butkus, Mindaugas, 2017. "The European Union possibilities to achieve targets of Europe 2020 and Paris agreement climate policy," Renewable Energy, Elsevier, vol. 106(C), pages 298-309.
    18. Valdés Lucas, Javier Noel & Escribano Francés, Gonzalo & San Martín González, Enrique, 2016. "Energy security and renewable energy deployment in the EU: Liaisons Dangereuses or Virtuous Circle?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1032-1046.

  9. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.

    Cited by:

    1. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    2. Irfan, Mohd & Yadav, Sarvendra & Shaw, Krishnendu, 2021. "The adoption of solar photovoltaic technology among Indian households: Examining the influence of entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Eslami, Hossein & Krishnan, Trichy, 2023. "New sustainable product adoption: The role of economic and social factors," Energy Policy, Elsevier, vol. 183(C).
    4. McCoy, Daire & Curtice, John, 2018. "Exploring the spatial and temporal determinants of gas central heating adoption," LSE Research Online Documents on Economics 86625, London School of Economics and Political Science, LSE Library.
    5. Braito, Michael & Flint, Courtney & Muhar, Andreas & Penker, Marianne & Vogel, Stefan, 2017. "Individual and collective socio-psychological patterns of photovoltaic investment under diverging policy regimes of Austria and Italy," Energy Policy, Elsevier, vol. 109(C), pages 141-153.
    6. Carattini, Stefano & Levin, Simon & Tavoni, Alessandro, 2019. "Cooperation in the climate commons," LSE Research Online Documents on Economics 100784, London School of Economics and Political Science, LSE Library.
    7. Henningsen, Geraldine & Wiese, Catharina, 2019. "Do Household Characteristics Really Matter? A Meta-Analysis on the Determinants of Households’ Energy-Efficiency Investments," MPRA Paper 101701, University Library of Munich, Germany.
    8. Wang, Jianjun & Liu, Fang & Li, Li & Zhang, Jian, 2022. "More than innovativeness: Comparing residents’ motivations for participating renewable energy communities in different innovation segments," Renewable Energy, Elsevier, vol. 197(C), pages 552-563.
    9. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment," Renewable Energy, Elsevier, vol. 180(C), pages 516-535.
    10. McCoy, Daire & Curtis, John, 2018. "Exploring the spatial and temporal determinants of gas central heating adoption," Resource and Energy Economics, Elsevier, vol. 52(C), pages 64-86.
    11. Bertsch, Valentin & Di Cosmo, Valeria, 2018. "Are Renewables Profitable in 2030? A Comparison between Wind and Solar across Europe," ESP: Energy Scenarios and Policy 276178, Fondazione Eni Enrico Mattei (FEEM).
    12. Lan, Haifeng & Gou, Zhonghua & Yang, Linchuan, 2020. "House price premium associated with residential solar photovoltaics and the effect from feed-in tariffs: A case study of Southport in Queensland, Australia," Renewable Energy, Elsevier, vol. 161(C), pages 907-916.
    13. Jimenez, Maritza & Franco, Carlos J. & Dyner, Isaac, 2016. "Diffusion of renewable energy technologies: The need for policy in Colombia," Energy, Elsevier, vol. 111(C), pages 818-829.
    14. Bartiaux, Françoise & Schmidt, Luísa & Horta, Ana & Correia, Augusta, 2016. "Social diffusion of energy-related practices and representations: Patterns and policies in Portugal and Belgium," Energy Policy, Elsevier, vol. 88(C), pages 413-421.
    15. Marley, A.A.J. & Islam, T. & Hawkins, G.E., 2016. "A formal and empirical comparison of two score measures for best–worst scaling," Journal of choice modelling, Elsevier, vol. 21(C), pages 15-24.
    16. Hackbarth, André & Löbbe, Sabine, 2020. "Attitudes, preferences, and intentions of German households concerning participation in peer-to-peer electricity trading," Energy Policy, Elsevier, vol. 138(C).
    17. Selvakkumaran, Sujeetha & Ahlgren, Erik O., 2019. "Determining the factors of household energy transitions: A multi-domain study," Technology in Society, Elsevier, vol. 57(C), pages 54-75.
    18. Nakada, Tatsuhiro & Shin, Kongjoo & Managi, Shunsuke, 2016. "The effect of demand response on purchase intention of distributed generation: Evidence from Japan," Energy Policy, Elsevier, vol. 94(C), pages 307-316.
    19. Rúa, Diego & Castaneda, Monica & Zapata, Sebastian & Dyner, Isaac, 2020. "Simulating the efficient diffusion of photovoltaics in Bogotá: An urban metabolism approach," Energy, Elsevier, vol. 195(C).
    20. Conradie, Peter D. & De Ruyck, Olivia & Saldien, Jelle & Ponnet, Koen, 2021. "Who wants to join a renewable energy community in Flanders? Applying an extended model of Theory of Planned Behaviour to understand intent to participate," Energy Policy, Elsevier, vol. 151(C).
    21. Bondio, Steven & Shahnazari, Mahdi & McHugh, Adam, 2018. "The technology of the middle class: Understanding the fulfilment of adoption intentions in Queensland's rapid uptake residential solar photovoltaics market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 642-651.
    22. Tibebu, Tiruwork B. & Hittinger, Eric & Miao, Qing & Williams, Eric, 2022. "Roles of diffusion patterns, technological progress, and environmental benefits in determining optimal renewable subsidies in the US," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    23. Wang, Ge & Zhang, Qi & Li, Yan & Li, Hailong, 2018. "Policy simulation for promoting residential PV considering anecdotal information exchanges based on social network modelling," Applied Energy, Elsevier, vol. 223(C), pages 1-10.
    24. Petrovich, Beatrice & Carattini, Stefano & Wüstenhagen, Rolf, 2021. "The price of risk in residential solar investments," LSE Research Online Documents on Economics 108405, London School of Economics and Political Science, LSE Library.
    25. Rohan Best & Paul J Burke & Shuhei Nishitateno, 2019. "Understanding the determinants of rooftop solar installation: evidence from household surveys in Australia," CCEP Working Papers 1902, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    26. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    27. Johannes Rode & Sven Müller, 2016. "Spatio-temporal variation in peer effects - The case of rooftop photovoltaic systems in Germany," ERSA conference papers ersa16p579, European Regional Science Association.
    28. Woo, JongRoul & Moon, Sungho & Choi, Hyunhong, 2022. "Economic value and acceptability of advanced solar power systems for multi-unit residential buildings: The case of South Korea," Applied Energy, Elsevier, vol. 324(C).
    29. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    30. Anita M. Bunea & Pietro Manfredi & Pompeo Della Posta & Mariangela Guidolin, 2019. "What do adoption patterns of solar panels observed so far tell about governments' incentive? insight from diffusion models," Papers 1909.10017, arXiv.org.
    31. Gu, Gaofeng & Feng, Tao, 2020. "Heterogeneous choice of home renewable energy equipment conditioning on the choice of electric vehicles," Renewable Energy, Elsevier, vol. 154(C), pages 394-403.
    32. Lan, Haifeng & Gou, Zhonghua & Lu, Yi, 2021. "Machine learning approach to understand regional disparity of residential solar adoption in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    33. Petrovich, Beatrice & Hille, Stefanie Lena & Wüstenhagen, Rolf, 2019. "Beauty and the budget: A segmentation of residential solar adopters," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    34. Gui, Xuechen & Gou, Zhonghua, 2022. "Household energy technologies in New South Wales, Australia: Regional differences and renewables adoption rates," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    35. Alina Ștefania Chenic & Alin Ioan Cretu & Adrian Burlacu & Nicolae Moroianu & Daniela Vîrjan & Dragos Huru & Mihaela Roberta Stanef-Puica & Vladimir Enachescu, 2022. "Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint," Sustainability, MDPI, vol. 14(14), pages 1-30, July.
    36. Williams, Eric & Carvalho, Rexon & Hittinger, Eric & Ronnenberg, Matthew, 2020. "Empirical development of parsimonious model for international diffusion of residential solar," Renewable Energy, Elsevier, vol. 150(C), pages 570-577.
    37. Gaofeng Gu & Xiaofeng Pan, 2023. "A Study on the Interdependence in Sustainable Mobility Tools and Home Energy Equipment Choices," Energies, MDPI, vol. 16(3), pages 1-16, January.
    38. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    39. Baharoon, Dhyia Aidroos & Rahman, Hasimah Abdul & Fadhl, Saeed Obaid, 2016. "Personal and psychological factors affecting the successful development of solar energy use in Yemen power sector: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 516-535.
    40. Tsantopoulos, Georgios & Arabatzis, Garyfallos & Tampakis, Stilianos, 2014. "Public attitudes towards photovoltaic developments: Case study from Greece," Energy Policy, Elsevier, vol. 71(C), pages 94-106.
    41. Manning, Dale T. & Rad, Mani Rouhi & Suter, Jordan F. & Goemans, Christopher & Xiang, Zaichen & Bailey, Ryan, 2020. "Non-market valuation in integrated assessment modeling: The benefits of water right retirement," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    42. Zander, Kerstin K., 2020. "Unrealised opportunities for residential solar panels in Australia," Energy Policy, Elsevier, vol. 142(C).
    43. Mishra, Pulak & Behera, Bhagirath, 2016. "Socio-economic and environmental implications of solar electrification: Experience of rural Odisha," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 953-964.
    44. Chul-Yong Lee & Min-Kyu Lee, 2017. "Demand Forecasting in the Early Stage of the Technology’s Life Cycle Using a Bayesian Update," Sustainability, MDPI, vol. 9(8), pages 1-15, August.
    45. Bertsch, Valentin & Di Cosmo, Valeria, 2020. "Are renewables profitable in 2030 and do they reduce carbon emissions effectively? A comparison across Europe," MPRA Paper 101822, University Library of Munich, Germany.
    46. Klingler, Anna-Lena, 2017. "Self-consumption with PV+Battery systems: A market diffusion model considering individual consumer behaviour and preferences," Applied Energy, Elsevier, vol. 205(C), pages 1560-1570.
    47. van Blommestein, Kevin & Daim, Tugrul U. & Cho, Yonghee & Sklar, Paul, 2018. "Structuring financial incentives for residential solar electric systems," Renewable Energy, Elsevier, vol. 115(C), pages 28-40.
    48. Sachs, Julia & Meng, Yiming & Giarola, Sara & Hawkes, Adam, 2019. "An agent-based model for energy investment decisions in the residential sector," Energy, Elsevier, vol. 172(C), pages 752-768.
    49. Sanghamitra Mukherjee, 2021. "A Framework to Measure Regional Disparities in Battery Electric Vehicle Diffusion in Ireland," Working Papers 202119, School of Economics, University College Dublin.
    50. Heike I. Brugger & Adam Douglas Henry, 2019. "Equity of Incentives: Agent-Based Explorations of How Social Networks Influence the Efficacy of Programs to Promote Solar Adoption," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    51. Michael Chesser & Jim Hanly & Damien Cassells & Nikolaos Apergis, 2019. "Household Energy Consumption: A Study of Micro Renewable Energy Systems in Ireland," The Economic and Social Review, Economic and Social Studies, vol. 50(2), pages 265-280.
    52. Davis, Katrina J & Burton, Michael & Kragt, Marit E, 2016. "Discrete choice models: scale heterogeneity and why it matters," Working Papers 235373, University of Western Australia, School of Agricultural and Resource Economics.
    53. Bunea, Anita M. & Della Posta, Pompeo & Guidolin, Mariangela & Manfredi, Piero, 2020. "What do adoption patterns of solar panels observed so far tell about governments’ incentive? Insights from diffusion models," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    54. Lim, Sesil & Huh, Sung-Yoon & Shin, Jungwoo & Lee, Jongsu & Lee, Yong-Gil, 2019. "Enhancing public acceptance of renewable heat obligation policies in South Korea: Consumer preferences and policy implications," Energy Economics, Elsevier, vol. 81(C), pages 1167-1177.
    55. Friebe, Christian A. & von Flotow, Paschen & Täube, Florian A., 2014. "Exploring technology diffusion in emerging markets – the role of public policy for wind energy," Energy Policy, Elsevier, vol. 70(C), pages 217-226.
    56. Tibebu, Tiruwork B. & Hittinger, Eric & Miao, Qing & Williams, Eric, 2021. "What is the optimal subsidy for residential solar?," Energy Policy, Elsevier, vol. 155(C).
    57. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    58. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    59. Simpson, Genevieve & Clifton, Julian, 2015. "The emperor and the cowboys: The role of government policy and industry in the adoption of domestic solar microgeneration systems," Energy Policy, Elsevier, vol. 81(C), pages 141-151.
    60. Henry Muyingo, 2015. "Organizational Challenges in the Adoption of Building Applied Photovoltaics in the Swedish Tenant-Owner Housing Sector," Sustainability, MDPI, vol. 7(4), pages 1-28, March.
    61. Londo, Marc & Matton, Robin & Usmani, Omar & van Klaveren, Marieke & Tigchelaar, Casper & Brunsting, Suzanne, 2020. "Alternatives for current net metering policy for solar PV in the Netherlands: A comparison of impacts on business case and purchasing behaviour of private homeowners, and on governmental costs," Renewable Energy, Elsevier, vol. 147(P1), pages 903-915.
    62. Wilson, C. & Pettifor, H. & Chryssochoidis, G., 2018. "Quantitative modelling of why and how homeowners decide to renovate energy efficiently," Applied Energy, Elsevier, vol. 212(C), pages 1333-1344.
    63. Seo-Hoon Kim & SungJin Lee & Seol-Yee Han & Jong-Hun Kim, 2020. "Scenario Analysis for GHG Emission Reduction Potential of the Building Sector for New City in South Korea," Energies, MDPI, vol. 13(20), pages 1-19, October.
    64. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).
    65. Wichsinee Wibulpolprasert & Umnouy Ponsukcharoen & Siripha Junlakarn & Sopitsuda Tongsopit, 2021. "Preliminarily Screening Geographical Hotspots for New Rooftop PV Installation: A Case Study in Thailand," Energies, MDPI, vol. 14(11), pages 1-30, June.
    66. Huybers, Twan & Louviere, Jordan & Islam, Towhidul, 2015. "What determines student satisfaction with university subjects? A choice-based approach," Journal of choice modelling, Elsevier, vol. 17(C), pages 52-65.
    67. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2020. "Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    68. Ramin Shabanpour & Ali Shamshiripour & Abolfazl Mohammadian, 2018. "Modeling adoption timing of autonomous vehicles: innovation diffusion approach," Transportation, Springer, vol. 45(6), pages 1607-1621, November.
    69. Palm, Jenny, 2018. "Household installation of solar panels – Motives and barriers in a 10-year perspective," Energy Policy, Elsevier, vol. 113(C), pages 1-8.
    70. Garlet, Taís Bisognin & Ribeiro, José Luis Duarte & de Souza Savian, Fernando & Mairesse Siluk, Julio Cezar, 2019. "Paths and barriers to the diffusion of distributed generation of photovoltaic energy in southern Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 157-169.
    71. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    72. Hackbarth, André, 2018. "Attitudes, preferences, and intentions of German households concerning participation in peer-to-peer electricity trading," Reutlingen Working Papers on Marketing & Management 2019-2, Reutlingen University, ESB Business School.
    73. Kardooni, Roozbeh & Yusoff, Sumiani Binti & Kari, Fatimah Binti & Moeenizadeh, Leila, 2018. "Public opinion on renewable energy technologies and climate change in Peninsular Malaysia," Renewable Energy, Elsevier, vol. 116(PA), pages 659-668.
    74. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    75. Felipe Moraes do Nascimento & Julio Cezar Mairesse Siluk & Fernando de Souza Savian & Taís Bisognin Garlet & José Renes Pinheiro & Carlos Ramos, 2020. "Factors for Measuring Photovoltaic Adoption from the Perspective of Operators," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
    76. dos Santos, L.L.C. & Canha, L.N. & Bernardon, D.P., 2018. "Projection of the diffusion of photovoltaic systems in residential low voltage consumers," Renewable Energy, Elsevier, vol. 116(PA), pages 384-401.

  10. Islam, Towhidul & Meade, Nigel, 2013. "The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation," Energy Policy, Elsevier, vol. 55(C), pages 521-530.

    Cited by:

    1. Irfan, Mohd & Yadav, Sarvendra & Shaw, Krishnendu, 2021. "The adoption of solar photovoltaic technology among Indian households: Examining the influence of entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Ryszard Kata & Rafał Pitera, 2023. "Local Authority Investments in the Field of Energy Transition and Their Determinants (on the Example of South-Eastern Poland)," Energies, MDPI, vol. 16(2), pages 1-20, January.
    3. Pedro I. Hancevic & Hector M. Nunez & Juan Rosellón, 2017. "Distributed Photovoltaic Power Generation: Possibilities, Benefits, and Challenges for a Widespread Application in the Mexican Residential Sector," Discussion Papers of DIW Berlin 1663, DIW Berlin, German Institute for Economic Research.
    4. Alipour, Mohammad & Taghikhah, Firouzeh & Irannezhad, Elnaz & Stewart, Rodney A. & Sahin, Oz, 2022. "How the decision to accept or reject PV affects the behaviour of residential battery system adopters," Applied Energy, Elsevier, vol. 318(C).
    5. Bao, Qifang & Sinitskaya, Ekaterina & Gomez, Kelley J. & MacDonald, Erin F. & Yang, Maria C., 2020. "A human-centered design approach to evaluating factors in residential solar PV adoption: A survey of homeowners in California and Massachusetts," Renewable Energy, Elsevier, vol. 151(C), pages 503-513.
    6. Heymann, Fabian & Miranda, Vladimiro & Soares, Filipe Joel & Duenas, Pablo & Perez Arriaga, Ignacio & Prata, Ricardo, 2019. "Orchestrating incentive designs to reduce adverse system-level effects of large-scale EV/PV adoption – The case of Portugal," Applied Energy, Elsevier, vol. 256(C).
    7. Hackbarth, André & Löbbe, Sabine, 2020. "Attitudes, preferences, and intentions of German households concerning participation in peer-to-peer electricity trading," Energy Policy, Elsevier, vol. 138(C).
    8. Bondio, Steven & Shahnazari, Mahdi & McHugh, Adam, 2018. "The technology of the middle class: Understanding the fulfilment of adoption intentions in Queensland's rapid uptake residential solar photovoltaics market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 642-651.
    9. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.
    10. Lukanov, Boris R. & Krieger, Elena M., 2019. "Distributed solar and environmental justice: Exploring the demographic and socio-economic trends of residential PV adoption in California," Energy Policy, Elsevier, vol. 134(C).
    11. Shuai Wang & Yao Li & Junjun Jia, 2022. "How to promote sustainable adoption of residential distributed photovoltaic generation in China? An employment of incentive and punitive policies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(2), pages 1-26, February.
    12. Woo, JongRoul & Moon, Sungho & Choi, Hyunhong, 2022. "Economic value and acceptability of advanced solar power systems for multi-unit residential buildings: The case of South Korea," Applied Energy, Elsevier, vol. 324(C).
    13. Romano, A.A. & Scandurra, G. & Carfora, A., 2015. "Probabilities to adopt feed in tariff conditioned to economic transition: A scenario analysis," Renewable Energy, Elsevier, vol. 83(C), pages 988-997.
    14. Bao, Qifang & Honda, Tomonori & El Ferik, Sami & Shaukat, Mian Mobeen & Yang, Maria C., 2017. "Understanding the role of visual appeal in consumer preference for residential solar panels," Renewable Energy, Elsevier, vol. 113(C), pages 1569-1579.
    15. Karakaya, Emrah & Hidalgo, Antonio & Nuur, Cali, 2015. "Motivators for adoption of photovoltaic systems at grid parity: A case study from Southern Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1090-1098.
    16. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    17. Kirsi Kotilainen & Ulla A. Saari, 2018. "Policy Influence on Consumers’ Evolution into Prosumers—Empirical Findings from an Exploratory Survey in Europe," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    18. Elena Stolyarova & Hélène Le Cadre, MINES ParisTech, PSL Research University, Centre for Applied Mathematics & Dominique Osso, EDF R&D, ENERgie dans les BAtiments et les Territoires & Benoit Allibe, 2015. "Stated Preferences for Space Heating Investment," EcoMod2015 8579, EcoMod.
    19. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    20. Acaroğlu, Hakan & Baykul, M. Celalettin, 2016. "Economic analysis of flat-plate solar collectors (FPSCs): A solution to the unemployment problem in the city of Eskisehir," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 607-617.
    21. George Adwek & Shen Boxiong & Paul O. Ndolo & Zachary O. Siagi & Chebet Chepsaigutt & Cicilia M. Kemunto & Moses Arowo & John Shimmon & Patrobers Simiyu & Abel C. Yabo, 2020. "The solar energy access in Kenya: a review focusing on Pay-As-You-Go solar home system," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 3897-3938, June.
    22. Alderete Peralta, Ali & Balta-Ozkan, Nazmiye & Longhurst, Philip, 2022. "Spatio-temporal modelling of solar photovoltaic adoption: An integrated neural networks and agent-based modelling approach," Applied Energy, Elsevier, vol. 305(C).
    23. Ruokamo, Enni, 2016. "Household preferences of hybrid home heating systems – A choice experiment application," Energy Policy, Elsevier, vol. 95(C), pages 224-237.
    24. Ryszard Kata & Kazimierz Cyran & Sławomir Dybka & Małgorzata Lechwar & Rafał Pitera, 2021. "Economic and Social Aspects of Using Energy from PV and Solar Installations in Farmers’ Households in the Podkarpackie Region," Energies, MDPI, vol. 14(11), pages 1-21, May.
    25. Lim, Sesil & Huh, Sung-Yoon & Shin, Jungwoo & Lee, Jongsu & Lee, Yong-Gil, 2019. "Enhancing public acceptance of renewable heat obligation policies in South Korea: Consumer preferences and policy implications," Energy Economics, Elsevier, vol. 81(C), pages 1167-1177.
    26. Karakaya, Emrah & Sriwannawit, Pranpreya, 2015. "Barriers to the adoption of photovoltaic systems: The state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 60-66.
    27. Higgins, Andrew & McNamara, Cheryl & Foliente, Greg, 2014. "Modelling future uptake of solar photo-voltaics and water heaters under different government incentives," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 142-155.
    28. Sanghamitra Mukherjee & Tensay Meles & L. (Lisa B.) Ryan & Séin Healy & Robert Mooney & Lindsay Sharpe & Paul Hayes, 2020. "Attitudes to Renewable Energy Technologies: Driving Change in Early Adopter Markets," Working Papers 202026, School of Economics, University College Dublin.
    29. Spyridon Karytsas & Ioannis Vardopoulos & Eleni Theodoropoulou, 2019. "Factors Affecting Sustainable Market Acceptance of Residential Microgeneration Technologies. A Two Time Period Comparative Analysis," Energies, MDPI, vol. 12(17), pages 1-20, August.
    30. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    31. Henry Muyingo, 2015. "Organizational Challenges in the Adoption of Building Applied Photovoltaics in the Swedish Tenant-Owner Housing Sector," Sustainability, MDPI, vol. 7(4), pages 1-28, March.
    32. Londo, Marc & Matton, Robin & Usmani, Omar & van Klaveren, Marieke & Tigchelaar, Casper & Brunsting, Suzanne, 2020. "Alternatives for current net metering policy for solar PV in the Netherlands: A comparison of impacts on business case and purchasing behaviour of private homeowners, and on governmental costs," Renewable Energy, Elsevier, vol. 147(P1), pages 903-915.
    33. Chen, Kee Kuo, 2014. "Assessing the effects of customer innovativeness, environmental value and ecological lifestyles on residential solar power systems install intention," Energy Policy, Elsevier, vol. 67(C), pages 951-961.
    34. Best, Rohan & Chareunsy, Andrea, 2022. "The impact of income on household solar panel uptake: Exploring diverse results using Australian data," Energy Economics, Elsevier, vol. 112(C).
    35. Jeong, Gicheol, 2013. "Assessment of government support for the household adoption of micro-generation systems in Korea," Energy Policy, Elsevier, vol. 62(C), pages 573-581.
    36. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    37. Vinay Virupaksha & Mary Harty & Kevin McDonnell, 2019. "Microgeneration of Electricity Using a Solar Photovoltaic System in Ireland," Energies, MDPI, vol. 12(23), pages 1-26, December.
    38. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2020. "Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    39. Garlet, Taís Bisognin & Ribeiro, José Luis Duarte & de Souza Savian, Fernando & Mairesse Siluk, Julio Cezar, 2019. "Paths and barriers to the diffusion of distributed generation of photovoltaic energy in southern Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 157-169.
    40. Hackbarth, André, 2018. "Attitudes, preferences, and intentions of German households concerning participation in peer-to-peer electricity trading," Reutlingen Working Papers on Marketing & Management 2019-2, Reutlingen University, ESB Business School.
    41. Ryszard Kata & Kazimierz Cyran & Sławomir Dybka & Małgorzata Lechwar & Rafał Pitera, 2022. "The Role of Local Government in Implementing Renewable Energy Sources in Households (Podkarpacie Case Study)," Energies, MDPI, vol. 15(9), pages 1-22, April.
    42. Khuong, Phuong M. & Scheller, Fabian & McKenna, Russell & Keles, Dogan & Fichtner, Wolf, 2020. "Willingness to pay for residential PV: Reconciling gaps between acceptance and adoption," Working Paper Series in Production and Energy 46, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    43. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    44. Wiggins, Seth, 2016. "It’s All Local? How Sub-State Policies Affect Western US Residential Solar Adoption," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235667, Agricultural and Applied Economics Association.

  11. Louviere, Jordan & Lings, Ian & Islam, Towhidul & Gudergan, Siegfried & Flynn, Terry, 2013. "An introduction to the application of (case 1) best–worst scaling in marketing research," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 292-303.

    Cited by:

    1. Suellen Tapsall & Geoffrey N Soutar & Wendy A Elliott & Tim Mazzarol & Jennifer Holland, 2022. "COVID-19’s impact on the perceived risk of ocean cruising: A best-worst scaling study of Australian consumers," Tourism Economics, , vol. 28(1), pages 248-271, February.
    2. Christian Wankmüller & Maximilian Kunovjanek & Robert Gennaro Sposato & Gerald Reiner, 2020. "Selecting E-Mobility Transport Solutions for Mountain Rescue Operations," Energies, MDPI, vol. 13(24), pages 1-19, December.
    3. Agnew, Scott & Dargusch, Paul, 2017. "Consumer preferences for household-level battery energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 609-617.
    4. White, Mark H., 2021. "bwsTools: An R package for case 1 best-worst scaling," Journal of choice modelling, Elsevier, vol. 39(C).
    5. Suprehatin, By & Umberger, Wendy J. & Yi, Dale & Stringer, Randy & Minot, Nicholas, 2015. "Can Understanding Indonesian Farmers’ Preferences for Crop Attributes Encourage their Adoption of High Value Crops?," 2015 Conference, August 9-14, 2015, Milan, Italy 212057, International Association of Agricultural Economists.
    6. Roberto Sañudo & Eneko Echaniz & Borja Alonso & Rubén Cordera, 2019. "Addressing the Importance of Service Attributes in Railways," Sustainability, MDPI, vol. 11(12), pages 1-20, June.
    7. Ákos Münnich & Emese Vargáné Karsai & Jenő Nagy, 2022. "A real-time network-based approach for analysing best–worst data types," SN Business & Economics, Springer, vol. 2(1), pages 1-24, January.
    8. Katja Woelfl & Lutz Kaufmann & Craig R. Carter, 2023. "In the eye of the beholder: A configurational exploration of perceived deceptive supplier behavior in negotiations," Journal of Supply Chain Management, Institute for Supply Management, vol. 59(2), pages 33-61, April.
    9. Glenk, Klaus & Eory, Vera & Colombo, Sergio & Barnes, Andrew, 2014. "Adoption of greenhouse gas mitigation in agriculture: An analysis of dairy farmers' perceptions and adoption behaviour," Ecological Economics, Elsevier, vol. 108(C), pages 49-58.
    10. Qingmeng Tong & Lu Zhang & Junbiao Zhang, 2017. "Evaluation of GHG Mitigation Measures in Rice Cropping and Effects of Farmer’s Characteristics: Evidence from Hubei, China," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    11. Lipovetsky, Stan & Conklin, Michael, 2014. "Finding items cannibalization and synergy by BWS data," Journal of choice modelling, Elsevier, vol. 12(C), pages 1-9.
    12. Lipovetsky, Stan & Conklin, Michael, 2014. "Best-Worst Scaling in analytical closed-form solution," Journal of choice modelling, Elsevier, vol. 10(C), pages 60-68.
    13. Zander, Kerstin K., 2020. "Unrealised opportunities for residential solar panels in Australia," Energy Policy, Elsevier, vol. 142(C).
    14. Jinhua Li & Fang Zhang & Shiwei Sun, 2019. "Building Consumer-Oriented CSR Differentiation Strategy," Sustainability, MDPI, vol. 11(3), pages 1-14, January.
    15. PK Sarma, 2020. "Investigating Consumers Preference on Fresh Vegetables in Bangladesh: Best-Worst Scaling Approach," Agricultural Research & Technology: Open Access Journal, Juniper Publishers Inc., vol. 24(1), pages 15-23, March.
    16. Huang, Lijuan & Mou, Jian & See-To, Eric W.K. & Kim, Jongki, 2019. "Consumer perceived value preferences for mobile marketing in China: A mixed method approach," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 70-86.
    17. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    18. Ochieng’, Brian J. & Hobbs, Jill E., 2016. "Incentives for cattle producers to adopt an E. Coli vaccine: An application of best–worst scaling," Food Policy, Elsevier, vol. 59(C), pages 78-87.
    19. Davis, Katrina J & Burton, Michael & Kragt, Marit E, 2016. "Discrete choice models: scale heterogeneity and why it matters," Working Papers 235373, University of Western Australia, School of Agricultural and Resource Economics.
    20. Van Wyngaarden, Sarah & Anders, Sven M., 2021. "Canadian Farmer Policy and Agency Preferences in Agri-Environmental Best Management Practice Adoption," 2021 Annual Meeting, August 1-3, Austin, Texas 313851, Agricultural and Applied Economics Association.
    21. Shehely Parvin & Paul Wang & Jashim Uddin, 2016. "Using best-worst scaling method to examine consumers’ value preferences: A multidimensional perspective," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1199110-119, December.
    22. Lin Jia & Yuting Tan & Feiyu Han & Yi Zhou & Chu Zhang & Yufei Zhang, 2019. "Factors Affecting Chinese Young Adults’ Acceptance of Connected Health," Sustainability, MDPI, vol. 11(8), pages 1-22, April.
    23. Arias, Juan F. & Bachmann, Chris, 2022. "Quantifying the relative importance of rapid transit implementation barriers: Evidence from ecuador," Journal of Transport Geography, Elsevier, vol. 100(C).
    24. Rasch, Carsten & Louviere, Jordan J. & Teichert, Thorsten, 2015. "Using facial EMG and eye tracking to study integral affect in discrete choice experiments," Journal of choice modelling, Elsevier, vol. 14(C), pages 32-47.
    25. Balcombe, Paul & Rigby, Dan & Azapagic, Adisa, 2014. "Investigating the importance of motivations and barriers related to microgeneration uptake in the UK," Applied Energy, Elsevier, vol. 130(C), pages 403-418.
    26. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
    27. Cooper, Bethany & Crase, Lin & Rose, John M., 2018. "Cost-reflective pricing: empirical insights into irrigators’ preferences for water tariffs," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.
    28. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    29. Hammerle, Mara & White, Lee V. & Sturmberg, Bjorn, 2023. "Solar for renters: Investigating investor perspectives of barriers and policies," Energy Policy, Elsevier, vol. 174(C).
    30. Marco A. Palma, 2017. "Improving the prediction of ranking data," Empirical Economics, Springer, vol. 53(4), pages 1681-1710, December.

  12. T. Islam & Z. Chik & M. M. Mustafa & H. Sanusi, 2012. "Estimation of Soil Electrical Properties in a Multilayer Earth Model with Boundary Element Formulation," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-13, August.

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    1. Min-Jae Kang & Chang-Jin Boo & Byeong-Chan Han & Ho-Chan Kim, 2023. "Kernel Function-Based Inverting Algorithm for Structure Parameters of Horizontal Multilayer Soil," Energies, MDPI, vol. 16(4), pages 1-17, February.

  13. Eckert, Christine & Louviere, Jordan J. & Islam, Towhidul, 2012. "Seeing the forest despite the trees: Brand effects on choice uncertainty," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 256-264.

    Cited by:

    1. Julie V. Stanton & Deirdre T. Guion, 2013. "Taking Advantage of a Vulnerable Group? Emotional Cues in Ads Targeting Parents," Journal of Consumer Affairs, Wiley Blackwell, vol. 47(3), pages 485-517, November.
    2. Francesca Gerini & Frode Alfnes & Alexander Schjøll, 2016. "Organic- and Animal Welfare-labelled Eggs: Competing for the Same Consumers?," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(2), pages 471-490, June.
    3. Mario Farsky & Oliver Schnittka & Henrik Sattler & Björn Höfer & Carina Lorth, 2017. "Brand-anchored discrete choice experiment (BDCE) vs. direct attribute rating (DAR): An empirical comparison of predictive validity," Marketing Letters, Springer, vol. 28(2), pages 231-240, June.

  14. Islam, Towhidul & Meade, Nigel, 2012. "The impact of competition, and economic globalization on the multinational diffusion of 3G mobile phones," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 843-850.

    Cited by:

    1. Simplice A. Asongu & Jacinta C. Nwachukwu, 2017. "Educational Quality Thresholds in the Diffusion of Knowledge with Mobile Phones for Inclusive Human Development in Sub-Saharan Africa," Research Africa Network Working Papers 17/057, Research Africa Network (RAN).
    2. Simplice A. Asongu, 2017. "Mobile Phone Innovation and Technology-driven Exports in Sub-Saharan Africa," Research Africa Network Working Papers 17/042, Research Africa Network (RAN).
    3. ., 2014. "Restructuring among mobile service providers: a ten-year perspective," Chapters, in: Mobile Telecommunications Networks, chapter 1, pages 1-25, Edward Elgar Publishing.
    4. Simplice A. Asongu & Jacinta C. Nwachukwu, 2016. "The Role of Governance in Mobile Phones for Inclusive Human Development in Sub-Saharan Africa," Research Africa Network Working Papers 16/007, Research Africa Network (RAN).
    5. Uchenna Efobi & Belmondo Tanankem & Simplice Asongu, 2016. "Technological Advancement and the Evolving Gender Identities: A Focus on the Level of Female Economic Participation in Sub-Saharan Africa," Working Papers of the African Governance and Development Institute. 16/045, African Governance and Development Institute..
    6. Simplice A. Asongu & Nicholas Biekpe, 2017. "Mobile Phone Innovation and Entrepreneurship in Sub-Saharan Africa," Research Africa Network Working Papers 17/023, Research Africa Network (RAN).
    7. Gerpott, Torsten J. & Ahmadi, Nima, 2015. "Determinants of willingness to look for separate international roaming services—An empirical study of mobile communication customers in Germany," International Journal of Information Management, Elsevier, vol. 35(2), pages 192-203.
    8. Simplice A. Asongu & Sara le Roux, 2016. "Enhancing ICT for Inclusive Human Development in Sub-Saharan Africa," Research Africa Network Working Papers 16/029, Research Africa Network (RAN).
    9. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    10. Simplice A. Asongu, 2023. "Mobile Phone Innovation and Doing Business in Sub-Saharan Africa," Journal of Entrepreneurship and Innovation in Emerging Economies, Entrepreneurship Development Institute of India, vol. 9(2), pages 238-269, July.
    11. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    12. Giovannetti, Emanuele & Hamoudia, Mohsen, 2018. "Understanding the different pre and post peak adoption drivers in the process of Mobile Social Networking diffusion," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190422, International Telecommunications Society (ITS).
    13. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    14. Simplice A. Asongu & John C. Anyanwu & Vanessa S. Tchamyou, 2017. "Technology-driven information sharing and conditional financial development in Africa," Research Africa Network Working Papers 17/010, Research Africa Network (RAN).
    15. Bera, Subhasis, 2019. "Club convergence and drivers of digitalization across Indian states," Telecommunications Policy, Elsevier, vol. 43(8), pages 1-1.
    16. Simplice Asongu & Jacinta C. Nwachukwu, 2016. "Mobile phones, Institutional Quality and Entrepreneurship in Sub-Saharan Africa," Working Papers of the African Governance and Development Institute. 16/044, African Governance and Development Institute..
    17. Asimakopoulos, Grigorios & Whalley, Jason, 2017. "Market leadership, technological progress and relative performance in the mobile telecommunications industry," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 57-67.
    18. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
    19. Simplice A. Asongu & Ndemaze Asongu, 2019. "The Role of Mobile Phones in Governance-Driven Technology Exports in Sub-Saharan Africa," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 849-867, June.
    20. Gupta, Sunita & Jain, Megha & Nagpal, Aishwarya, 2019. "An Empirical Investigation on associated linkage between Human Development and ICT: A South Asian Perspective," MPRA Paper 96167, University Library of Munich, Germany.
    21. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    22. Ramin Shabanpour & Ali Shamshiripour & Abolfazl Mohammadian, 2018. "Modeling adoption timing of autonomous vehicles: innovation diffusion approach," Transportation, Springer, vol. 45(6), pages 1607-1621, November.
    23. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    24. Swinerd, Chris & McNaught, Ken R., 2015. "Comparing a simulation model with various analytic models of the international diffusion of consumer technology," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 330-343.
    25. Rabah Arezki & Vianney Dequiedt & Rachel Yuting Fan & Carlo Maria Rossotto, 2021. "Working Paper 352 - Liberalization, Technology Adoption, and Stock Returns: Evidence from Telecom," Working Paper Series 2478, African Development Bank.
    26. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    27. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.
    28. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.

  15. Towhidul Islam & Nigel Meade, 2011. "Detecting the impact of market factors on sales takeoff times of analog cellular telephones," Marketing Letters, Springer, vol. 22(2), pages 197-212, June.

    Cited by:

    1. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    2. Islam, Towhidul & Meade, Nigel, 2013. "The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation," Energy Policy, Elsevier, vol. 55(C), pages 521-530.
    3. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

  16. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.

    Cited by:

    1. Banciu, M. & Ødegaard, F., 2016. "Optimal product bundling with dependent valuations: The price of independence," European Journal of Operational Research, Elsevier, vol. 255(2), pages 481-495.
    2. Riikonen, Antti & Smura, Timo & Töyli, Juuso, 2016. "The effects of price, popularity, and technological sophistication on mobile handset replacement and unit lifetime," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 313-323.
    3. Glady, Nicolas & Lemmens, Aurélie & Croux, Christophe, 2015. "Unveiling the relationship between the transaction timing, spending and dropout behavior of customers," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 78-93.
    4. Mayukh Dass & Masoud Moradi & Fereshteh Zihagh, 2023. "Forecasting purchase rates of new products introduced in existing categories," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 385-408, September.
    5. Calabrese, Raffaella & Degl’Innocenti, Marta & Osmetti, Silvia Angela, 2017. "The effectiveness of TARP-CPP on the US banking industry: A new copula-based approach," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1029-1037.
    6. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    7. Dimitrova, Dimitrina S. & Kaishev, Vladimir K. & Zhao, Shouqi, 2015. "On finite-time ruin probabilities in a generalized dual risk model with dependence," European Journal of Operational Research, Elsevier, vol. 242(1), pages 134-148.
    8. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

  17. José Blandon & Spencer Henson & Towhidul Islam, 2010. "The Importance of Assessing Marketing Preferences of Small-scale Farmers: A Latent Segment Approach," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 22(4), pages 494-509, September.

    Cited by:

    1. Oreoluwa Ola & Luisa Menapace, 2020. "Revisiting constraints to smallholder participation in high‐value markets: A best‐worst scaling approach," Agricultural Economics, International Association of Agricultural Economists, vol. 51(4), pages 595-608, July.
    2. Katharine Tröger & Margareta Amy Lelea & Brigitte Kaufmann, 2018. "The Fine Line between Trusting and Cheating: Exploring Relationships between Actors in Ugandan Pineapple Value Chains," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(5), pages 823-841, December.
    3. Mengshuai Zhu & Chen Shen & Yajun Tian & Jianzhai Wu & Yueying Mu, 2022. "Factors Affecting Smallholder Farmers’ Marketing Channel Choice in China with Multivariate Logit Model," Agriculture, MDPI, vol. 12(9), pages 1-11, September.
    4. Ola, Oreoluwa & Menapace, Luisa, 2020. "Smallholders' perceptions and preferences for market attributes promoting sustained participation in modern agricultural value chains," Food Policy, Elsevier, vol. 97(C).

  18. Jose Blandon & Spencer Henson & Towhidul Islam, 2009. "Marketing preferences of small-scale farmers in the context of new agrifood systems: a stated choice model," Agribusiness, John Wiley & Sons, Ltd., vol. 25(2), pages 251-267.

    Cited by:

    1. Stefano Ciliberti & Simone Del Sarto & Angelo Frascarelli & Giulia Pastorelli & Gaetano Martino, 2020. "Contracts to Govern the Transition towards Sustainable Production: Evidence from a Discrete Choice Analysis in the Durum Wheat Sector in Italy," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    2. Schipmann, Christin & Qaim, Matin, 2011. "Supply chain differentiation, contract agriculture, and farmers’ marketing preferences: The case of sweet pepper in Thailand," Food Policy, Elsevier, vol. 36(5), pages 667-677.
    3. Schipmann, Christin & Qaim, Matin, 2011. "Supply chain differentiation, contract agriculture, and farmers’ marketing preferences: the case of sweet pepper in Thailand," GlobalFood Discussion Papers 108349, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    4. Viet Hoang, 2021. "Impact of Contract Farming on Farmers’ Income in the Food Value Chain: A Theoretical Analysis and Empirical Study in Vietnam," Agriculture, MDPI, vol. 11(8), pages 1-16, August.
    5. Susanne Väth & Simone Gobien, 2014. "Life Satisfaction, Contract Farming and Property Rights: Evidence from Ghana," MAGKS Papers on Economics 201415, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Arouna, Aminou & Adegbola, Patrice Y. & Raphael, Babatunde & Diagne, Aliou, 2015. "Contract farming preferences by smallholder rice producers in Africa: a stated choice model using mixed logic," 2015 Conference, August 9-14, 2015, Milan, Italy 210957, International Association of Agricultural Economists.
    7. Susanne Väth & Michael Kirk, 2014. "Do property rights and contract farming matter for rural development? Evidence from a large-scale investment in Ghana," MAGKS Papers on Economics 201416, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Ochieng, Dennis O. & Veettil, Prakashan C. & Qaim, Matin, 2017. "Farmers’ preferences for supermarket contracts in Kenya," Food Policy, Elsevier, vol. 68(C), pages 100-111.
    9. Schuster, Monica & Maertens, Miet, 2013. "Do private standards create exclusive supply chains? New evidence from the Peruvian asparagus export sector," Food Policy, Elsevier, vol. 43(C), pages 291-305.
    10. Michelson, Hope & Reardon, Thomas & Perez, Francisco Jose, 2010. "Small Farmers and Big Retail: trade-offs of supplying supermarkets in Nicaragua," Staff Paper Series 62124, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    11. Michelson, Hope C., 2012. "Small farmers, NGOs, and a Walmart World: Welfare effects of supermarkets operating in Nicaragua," MPRA Paper 42458, University Library of Munich, Germany.
    12. Ma, Wanglin & Abdulai, Awudu, 2015. "Linking apple farmers to markets: Determinants and impacts of marketing contracts in China," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 202719, Agricultural and Applied Economics Association.
    13. Alim Setiawan Slamet & Akira Nakayasu & Masahiro Ichikawa, 2017. "Small-Scale Vegetable Farmers’ Participation in Modern Retail Market Channels in Indonesia: The Determinants of and Effects on Their Income," Agriculture, MDPI, vol. 7(2), pages 1-16, February.
    14. Viet Hoang & Vinh Nguyen, 2023. "Determinants of small farmers' participation in contract farming in developing countries: A study in Vietnam," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 836-853, July.
    15. Banterle, Alessandro & Carraresi, Laura & Cavaliere, Alessia, 2011. "Price Setting in Food SMEs: Which Role for Marketing Capability? An Empirical Analysis in Italy," 2011 International European Forum, February 14-18, 2011, Innsbruck-Igls, Austria 122000, International European Forum on System Dynamics and Innovation in Food Networks.
    16. Fischer, Sabine & Wollni, Meike, 2018. "The role of farmers’ trust, risk and time preferences for contract choices: Experimental evidence from the Ghanaian pineapple sector," Food Policy, Elsevier, vol. 81(C), pages 67-81.
    17. Mailu, Stephen & Wachira, Ann, 2009. "The influence of prices on market participation decisions of indigenous poultry farmers in four districts of Eastern Province, Kenya," MPRA Paper 21312, University Library of Munich, Germany.
    18. Fanny Widadie & Jos Bijman & Jacques Trienekens, 2021. "Farmer preferences in contracting with modern retail in Indonesia: A choice experiment," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 371-392, April.
    19. Surendran Arumugam & Ramu Govindasamy & James E. Simon & Emil Wyk & Burhan Ozkan, 2022. "Market outlet choices for African Indigenous Vegetables (AIVs): a socio-economic analysis of farmers in Zambia," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-13, December.
    20. Marino Davide & Giannelli Agostino & Mazzocchi Giampiero & Mastronardi Luigi & Giaccio Vincenzo, 2018. "Territorialisation dynamics for Italian farms adhering to Alternative Food Networks," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 40(40), pages 113-131, June.
    21. Rattiya Suddeephong Lippe & Ulrike Grote, 2017. "Determinants Affecting Adoption of GLOBALG.A.P. Standards: A Choice Experiment in Thai Horticulture," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 242-256, April.
    22. Sekabira, Haruna & Qaim, Matin, 2016. "Mobile Phone Technologies, Agricultural Production Patterns, and Market access in Uganda," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246310, African Association of Agricultural Economists (AAAE).
    23. Bensemann, Jessica & Shadbolt, Nicola, 2015. "Farmers’ Choice of Marketing Strategy: A Study of New Zealand Lamb Producers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 18(3), pages 1-33, September.
    24. Thai Thuy Pham & Ludwig Theuvsen & Verena Otter, 2019. "Determinants of Smallholder Farmers' Marketing Channel Choice: Evidence from the Vietnamese Rice Sector," Asian Economic Journal, East Asian Economic Association, vol. 33(3), pages 281-300, September.
    25. Hanna Ihli & Ronja Seegers & Etti Winter & Brian Chiputwa & Anja Gassner, 2022. "Preferences for tree fruit market attributes among smallholder farmers in Eastern Rwanda," Agricultural Economics, International Association of Agricultural Economists, vol. 53(1), pages 5-21, January.
    26. Gelaw, Fekadu & Speelman, Stijn & Van Huylenbroeck, Guido, 2016. "Farmers’ marketing preferences in local coffee markets: Evidence from a choice experiment in Ethiopia," Food Policy, Elsevier, vol. 61(C), pages 92-102.
    27. Islam, Towhidul & Meade, Nigel, 2013. "The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation," Energy Policy, Elsevier, vol. 55(C), pages 521-530.
    28. Atiş, Ela & Miran, Bulent & Bektaȿ, Zerrin & Ciftci, Kenan & Karabat, Selcuk, 2013. "An Analysis of Marketing Preferences of Sultana Producers in Turkey in Terms of Sustainable Market Power," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152136, Australian Agricultural and Resource Economics Society.
    29. Vlaeminck, Pieter & Vranken, Liesbet & Van Den Broeck, Goedele & Vande Velde, Katrien & Raymaekers, Karen & Maertens, Miet, 2015. "Farmers’ preferences for Fair Trade contracting in Benin," Working Papers 225931, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    30. Sekabira, Haruna & Qaim, Matin, 2016. "Mobile Money, Agricultural Marketing, and Off-Farm Income in Uganda," GlobalFood Discussion Papers 234998, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    31. Hailong Yu & H. Holly Wang & Binglong Li, 2018. "Production system innovation to ensure raw milk safety in small holder economies: the case of dairy complex in China," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 787-797, November.
    32. Ogoudélé S. Codjo & Denis Acclassato & Rose Fiamohe & Sylvain Kpenavoun & Gauthier Biaou, 2020. "Comparative analysis of the preference of producers and processors for domestic rice production contracts in Benin," Agribusiness, John Wiley & Sons, Ltd., vol. 36(2), pages 242-258, April.

  19. Jordan J. Louviere & Towhidul Islam & Nada Wasi & Deborah Street & Leonie Burgess, 2008. "Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(2), pages 360-375, March.

    Cited by:

    1. Peter Boxall & W. L. (Vic) Adamowicz & Amanda Moon, 2009. "Complexity in choice experiments: choice of the status quo alternative and implications for welfare measurement ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(4), pages 503-519, October.
    2. Jürgen Meyerhoff & Malte Oehlmann & Priska Weller, 2015. "The Influence of Design Dimensions on Stated Choices in an Environmental Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(3), pages 385-407, July.
    3. Regier, Dean A. & Watson, Verity & Burnett, Heather & Ungar, Wendy J., 2014. "Task complexity and response certainty in discrete choice experiments: An application to drug treatments for juvenile idiopathic arthritis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 50(C), pages 40-49.
    4. Yang, Jui-Chen & Johnson, F. Reed & Kilambi, Vikram & Mohamed, Ateesha F., 2015. "Sample size and utility-difference precision in discrete-choice experiments: A meta-simulation approach," Journal of choice modelling, Elsevier, vol. 16(C), pages 50-57.
    5. Esther W. Bekker-Grob & Bas Donkers & Jorien Veldwijk & Marcel F. Jonker & Sylvia Buis & Jan Huisman & Patrick Bindels, 2021. "What Factors Influence Non-Participation Most in Colorectal Cancer Screening? A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(2), pages 269-281, March.
    6. Pires Gonçalves, Ricardo, 2008. "Consumer Behavior: Product Characteristics and Quality Perception," MPRA Paper 11142, University Library of Munich, Germany.
    7. Chandoevwit, Worawan & Wasi, Nada, 2020. "Incorporating discrete choice experiments into policy decisions: Case of designing public long-term care insurance," Social Science & Medicine, Elsevier, vol. 258(C).
    8. Hasan-Basri, Bakti & Yahya, Nurul & Musa, Rusmani, 2013. "Status Quo Effect and Preferences Uncertainty: A Heteroscedastic Extreme Value (HEV) Model," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 47(1), pages 163-172.
    9. Ailawadi, Kusum L. & Gedenk, Karen & Langer, Tobias & Ma, Yu & Neslin, Scott A., 2014. "Consumer response to uncertain promotions: An empirical analysis of conditional rebates," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 94-106.
    10. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    11. Mulatu, Dawit W. & van der Veen, Anne & van Oel, Pieter R., 2014. "Farm households' preferences for collective and individual actions to improve water-related ecosystem services: The Lake Naivasha basin, Kenya," Ecosystem Services, Elsevier, vol. 7(C), pages 22-33.
    12. Richard Norman & Benjamin M. Craig & Paul Hansen & Marcel F. Jonker & John Rose & Deborah J. Street & Brendan Mulhern, 2019. "Issues in the Design of Discrete Choice Experiments," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(3), pages 281-285, June.
    13. Gökçe Esenduran & James A. Hill & In Joon Noh, 2020. "Understanding the Choice of Online Resale Channel for Used Electronics," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1188-1211, May.
    14. Mandy Ryan & Karen Gerard & Gillian Currie, 2012. "Using Discrete Choice Experiments in Health Economics," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 41, Edward Elgar Publishing.
    15. Joseph Cooper & Daniel Hellerstein, 2009. "Do Government Economists Value AAEA Conferences?," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(4), pages 914-930.
    16. Danne, Michael & Mußhoff, Oliver & Schulte, Michael, 2018. "Analysing the importance of glyphosate as part of agricultural srategies: A discrete choice experiment," DARE Discussion Papers 1802, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    17. Bliemer, Michiel C.J. & Collins, Andrew T., 2016. "On determining priors for the generation of efficient stated choice experimental designs," Journal of choice modelling, Elsevier, vol. 21(C), pages 10-14.
    18. Meise, Jan Niklas & Rudolph, Thomas & Kenning, Peter & Phillips, Diane M., 2014. "Feed them facts: Value perceptions and consumer use of sustainability-related product information," Journal of Retailing and Consumer Services, Elsevier, vol. 21(4), pages 510-519.
    19. H. Holly Wang & Yu Jiang & Shaosheng Jin & Qiujie Zheng, 2022. "New online market connecting Chinese consumers and small farms to improve food safety and environment," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(4), pages 305-324, December.
    20. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
    21. Araña, Jorge E. & León, Carmelo J., 2013. "Dynamic hypothetical bias in discrete choice experiments: Evidence from measuring the impact of corporate social responsibility on consumers demand," Ecological Economics, Elsevier, vol. 87(C), pages 53-61.
    22. van Cranenburgh, Sander & Collins, Andrew T., 2019. "New software tools for creating stated choice experimental designs efficient for regret minimisation and utility maximisation decision rules," Journal of choice modelling, Elsevier, vol. 31(C), pages 104-123.
    23. Moser, Riccarda & Raffaelli, Roberta, 2014. "Does attribute cut-off elicitation affect choice consistency? Contrasting hypothetical and real-money choice experiments," Journal of choice modelling, Elsevier, vol. 11(C), pages 16-29.
    24. Olynk Widmar, Nicole J. & Ortega, David L., 2014. "Comparing Consumer Preferences for Livestock Production Process Attributes Across Products, Species, and Modeling Methods," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 46(3), pages 1-17, August.
    25. Hein, Maren & Kurz, Peter & Steiner, Winfried J., 2019. "On the effect of HB covariance matrix prior settings: A simulation study," Journal of choice modelling, Elsevier, vol. 31(C), pages 51-72.
    26. Vardges Hovhannisyan & Hayk Khachatryan, 2017. "Ornamental Plants in the United States: An Econometric Analysis of a Household‐Level Demand System," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 226-241, April.
    27. Jui-Chen Yang & Shelby D. Reed & Steve Hass & Mark B. Skeen & F. Reed Johnson, 2021. "Is Easier Better Than Harder? An Experiment on Choice Experiments for Benefit-Risk Tradeoff Preferences," Medical Decision Making, , vol. 41(2), pages 222-232, February.
    28. Samare P. I. Huls & Emily Lancsar & Bas Donkers & Jemimah Ride, 2022. "Two for the price of one: If moving beyond traditional single‐best discrete choice experiments, should we use best‐worst, best‐best or ranking for preference elicitation?," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2630-2647, December.
    29. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    30. Schumacher, Tucker & Schroeder, Ted C. & Tonsor, Glynn T., 2012. "Willingness-to-Pay for Calf Health Programs and Certification Agents," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 44(2), pages 1-12, May.
    31. Sever, Ivan & Verbič, Miroslav & Klarić Sever, Eva, 2019. "Cost attribute in health care DCEs: Just adding another attribute or a trigger of change in the stated preferences?," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    32. Roy Brouwer & Ivana Logar & Oleg Sheremet, 2017. "Choice Consistency and Preference Stability in Test-Retests of Discrete Choice Experiment and Open-Ended Willingness to Pay Elicitation Formats," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(3), pages 729-751, November.
    33. Kaenzig, Josef & Heinzle, Stefanie Lena & Wüstenhagen, Rolf, 2013. "Whatever the customer wants, the customer gets? Exploring the gap between consumer preferences and default electricity products in Germany," Energy Policy, Elsevier, vol. 53(C), pages 311-322.
    34. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    35. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    36. Michaels-Igbokwe, Christine & Lagarde, Mylene & Cairns, John & Terris-Prestholt, Fern, 2014. "Using decision mapping to inform the development of a stated choice survey to elicit youth preferences for sexual and reproductive health and HIV services in rural Malawi," Social Science & Medicine, Elsevier, vol. 105(C), pages 93-102.
    37. McKendree, Melissa G.S. & Olynk Widmar, Nicole & Ortega, David L. & Foster, Kenneth A., 2013. "Consumer Preferences for Verified Pork-Rearing Practices in the Production of Ham Products," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(3), pages 1-21.
    38. Fecke, Wilm & Danne, Michael & Mußhoff, Oliver, 2018. "Online-Einkauf von Pflanzenschutzmitteln: Ein Discrete Choice Experiment mit landwirtschaftlichen Unternehmern in Deutschland," DARE Discussion Papers 1811, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    39. Lijia Shi & Jing Xie & Zhifeng Gao, 2018. "The impact of deal†proneness on WTP estimates in incentive†aligned value elicitation methods," Agricultural Economics, International Association of Agricultural Economists, vol. 49(3), pages 353-362, May.
    40. Marcel F. Jonker & Arthur E. Attema & Bas Donkers & Elly A. Stolk & Matthijs M. Versteegh, 2017. "Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self‐assessed Health and an Efficient Discrete Choice Experiment," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1534-1547, December.
    41. Ndebele, Tom & Marsh, Dan & Scarpa, Riccardo, 2019. "Consumer switching in retail electricity markets: Is price all that matters?," Energy Economics, Elsevier, vol. 83(C), pages 88-103.
    42. David L. Ortega & H. Holly Wang & Nicole J. Olynk Widmar, 2014. "Aquaculture imports from Asia: an analysis of U.S. consumer demand for select food quality attributes," Agricultural Economics, International Association of Agricultural Economists, vol. 45(5), pages 625-634, September.
    43. Glynn T. Tonsor & Ted C. Schroeder & Joost M. E. Pennings, 2009. "Factors Impacting Food Safety Risk Perceptions," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(3), pages 625-644, September.
    44. Tadesse, Tewodros & Berhane, Tsegay & Mulatu, Dawit W. & Rannestad, Meley Mekonen, 2021. "Willingness to accept compensation for afromontane forest ecosystems conservation," Land Use Policy, Elsevier, vol. 105(C).
    45. Dudinskaya, Emilia Cubero & Naspetti, Simona & Zanoli, Raffaele, 2020. "Using eye-tracking as an aid to design on-screen choice experiments," Journal of choice modelling, Elsevier, vol. 36(C).
    46. Maya Durvasula & Stephen W. Pan & Jason J. Ong & Weiming Tang & Bolin Cao & Chuncheng Liu & Fern Terris-Prestholt & Joseph D. Tucker, 2019. "Enhancing Public Health Messaging: Discrete-Choice Experiment Evidence on the Design of HIV Testing Messages in China," Medical Decision Making, , vol. 39(5), pages 568-582, July.
    47. McKendree, Melissa G.S. & Ortega, David L. & Widmar, Nicole Olynk & Wang, H. Holly, 2013. "Consumer Perceptions of Seafood Industries in the Wake of the Deepwater Horizon Oil Spill and Fukushima Daiichi Nuclear Disaster," Staff Paper Series 155582, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    48. Axel Christian Mühlbacher & Anika Kaczynski, 2021. "The Impact of Gastrointestinal Symptoms on Patients’ Well-Being: Best–Worst Scaling (BWS) to Prioritize Symptoms of the Gastrointestinal Symptom Score (GIS)," IJERPH, MDPI, vol. 18(21), pages 1-13, November.
    49. Stéphane Luchini & Verity Watson, 2014. "Are choice experiments reliable? Evidence from the lab," Post-Print hal-01463113, HAL.
    50. Stephane Hess & John Rose, 2012. "Can scale and coefficient heterogeneity be separated in random coefficients models?," Transportation, Springer, vol. 39(6), pages 1225-1239, November.
    51. Han, Qi & Dellaert, Benedict G.C. & Raaij, W. Fred van & Timmermans, Harry J.P., 2014. "Publicly announced access recommendations and consumers' service time choices with uncertain congestion," Journal of choice modelling, Elsevier, vol. 10(C), pages 1-10.
    52. Nicolas Krucien & Nathalie Pelletier-Fleury & Amiram Gafni, 2019. "Measuring Public Preferences for Health Outcomes and Expenditures in a Context of Healthcare Resource Re-Allocation," PharmacoEconomics, Springer, vol. 37(3), pages 407-417, March.
    53. Keith Finlay & Charles Stoecker & Scott Cunningham, 2015. "Willingness-To-Accept Pharmaceutical Retail Inconvenience: Evidence from a Contingent Choice Experiment," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-10, May.
    54. Jara-Diaz, Sergio & Monzon, Andres & Cascajo, Rocio & Garcia-Martinez, Andres, 2022. "An international time equivalency of the pure transfer penalty in urban transit trips: Closing the gap," Transport Policy, Elsevier, vol. 125(C), pages 48-55.
    55. Tonsor, Glynn T., 2010. "Consumer Food Safety Perceptions: Do they Differ across Products, Species, and Specific Risks?," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61044, Agricultural and Applied Economics Association.
    56. Ndebele, Tom & Marsh, Dan, 2014. "Environmental attitude and the demand for green electricity in the context of supplier choice: A case study of the New Zealand retail electricity market," 2014 Conference, August 28-29, 2014, Nelson, New Zealand 188376, New Zealand Agricultural and Resource Economics Society.
    57. Khachatryan, Hayk & Joireman, Jeff & Casavant, Kenneth L., 2013. "The Effects of Intertemporal Considerations on Consumer Preferences for Biofuels," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150334, Agricultural and Applied Economics Association.
    58. Marcel F. Jonker & Bas Donkers & Esther de Bekker‐Grob & Elly A. Stolk, 2019. "Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 350-363, March.
    59. Que, Sisi & Awuah-Offei, Kwame & Weidner, Nathan & Wang, Yumin, 2017. "Discrete choice experiment validation: A resource project case study," Journal of choice modelling, Elsevier, vol. 22(C), pages 39-50.
    60. Tonsor, Glynn T. & Wolf, Christopher & Olynk, Nicole, 2009. "Consumer voting and demand behavior regarding swine gestation crates," Food Policy, Elsevier, vol. 34(6), pages 492-498, December.
    61. Shiwen Quan & Yinchu Zeng & Xiaohua Yu & Te Bao, 2018. "WTP for baby milk formula in China: Using attribute nonattendance as a priori information to select attributes in choice experiment," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 300-320, March.
    62. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 27, pages 661-674, Edward Elgar Publishing.
    63. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    64. Gensler, Sonja & Hinz, Oliver & Skiera, Bernd & Theysohn, Sven, 2012. "Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs," European Journal of Operational Research, Elsevier, vol. 219(2), pages 368-378.
    65. Elizabeth Kinter & Thomas Prior & Christopher Carswell & John Bridges, 2012. "A Comparison of Two Experimental Design Approaches in Applying Conjoint Analysis in Patient-Centered Outcomes Research," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 5(4), pages 279-294, December.
    66. Jordan Louviere & Joffre Swait, 2010. "—Discussion of “Alleviating the Constant Stochastic Variance Assumption in Decision Research: Theory, Measurement, and Experimental Test”," Marketing Science, INFORMS, vol. 29(1), pages 18-22, 01-02.
    67. Xinxin Lv & Mingxue Zhang & Dongqing Li, 2022. "Eliciting Herders’ Willingness to Accept Grassland Conservation: A Choice Experiment Design in Pastoral Regions of China," Land, MDPI, vol. 11(9), pages 1-16, September.
    68. Tinessa, Fiore, 2021. "Closed-form random utility models with mixture distributions of random utilities: Exploring finite mixtures of qGEV models," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 262-288.
    69. Tonsor, Glynn T. & Wolf, Christopher A., 2011. "On mandatory labeling of animal welfare attributes," Food Policy, Elsevier, vol. 36(3), pages 430-437, June.
    70. Tobias Börger & Oliver Frör & Sören Weiß, 2017. "The relationship between perceived difficulty and randomness in discrete choice experiments: Investigating reasons for and consequences of difficulty," Discussion Papers in Environment and Development Economics 2017-03, University of St. Andrews, School of Geography and Sustainable Development.
    71. David Boto-García & Petr Mariel & José Baños Pino & Antonio Alvarez, 2022. "Tourists’ willingness to pay for holiday trip characteristics: A Discrete Choice Experiment," Tourism Economics, , vol. 28(2), pages 349-370, March.
    72. Thao Thai & Michiel Bliemer & Gang Chen & Jean Spinks & Sonja de New & Emily Lancsar, 2023. "Comparison of a full and partial choice set design in a labeled discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1284-1304, June.
    73. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    74. Jeroen Luyten & Sandy Tubeuf & Roselinde Kessels, 2022. "Rationing of a scarce life‐saving resource: Public preferences for prioritizing COVID‐19 vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 342-362, February.
    75. Kar H. Lim & Wuyang Hu, 2016. "How Local Is Local? A Reflection on Canadian Local Food Labeling Policy from Consumer Preference," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(1), pages 71-88, March.
    76. Marsh, Dan & Phillips, Yvonne, 2012. "Difficult Choices: What Influences the Error Variance in a Choice Experiment," 2012 Conference, August 31, 2012, Nelson, New Zealand 139651, New Zealand Agricultural and Resource Economics Society.
    77. Wolf, Christopher A. & Tonsor, Glynn T., 2017. "Cow Welfare in the U.S. Dairy Industry: Willingness-to-Pay and Willingness-to-Supply," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(2), May.
    78. Regier, Dean A. & Sicsic, Jonathan & Watson, Verity, 2019. "Choice certainty and deliberative thinking in discrete choice experiments. A theoretical and empirical investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 235-255.
    79. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    80. Jorien Veldwijk & Mattijs S Lambooij & Esther W de Bekker-Grob & Henriëtte A Smit & G Ardine de Wit, 2014. "The Effect of Including an Opt-Out Option in Discrete Choice Experiments," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    81. Schoon, Rebecca & Chi, Chunhuei & Liu, Tsai-Ching, 2022. "Quantifying public preferences for healthcare priorities in Taiwan through an integrated citizens jury and discrete choice experiment," Social Science & Medicine, Elsevier, vol. 315(C).
    82. Ebenezer Kwabena Tetteh & Steve Morris & Nigel Titcheneker-Hooker, 2017. "Discrete-choice modelling of patient preferences for modes of drug administration," Health Economics Review, Springer, vol. 7(1), pages 1-14, December.
    83. John Bridges & Elizabeth Kinter & Annette Schmeding & Ina Rudolph & Axel Mühlbacher, 2011. "Can Patients Diagnosed with Schizophrenia Complete Choice-Based Conjoint Analysis Tasks?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 4(4), pages 267-275, December.
    84. Nina Hampl & Moritz Loock, 2013. "Sustainable Development in Retailing: What is the Impact on Store Choice?," Business Strategy and the Environment, Wiley Blackwell, vol. 22(3), pages 202-216, March.
    85. J. DeShazo & Trudy Cameron & Manrique Saenz, 2009. "The Effect of Consumers’ Real-World Choice Sets on Inferences from Stated Preference Surveys," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 319-343, March.
    86. Bremer, Lucas & Heitmann, Mark & Schreiner, Thomas F., 2017. "When and how to infer heuristic consideration set rules of consumers," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 516-535.

  20. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.

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    1. Sigurdsson, Valdimar & Larsen, Nils Magne & Alemu, Mohammed Hussen & Gallogly, Joseph Karlton & Menon, R. G. Vishnu & Fagerstrøm, Asle, 2020. "Assisting sustainable food consumption: The effects of quality signals stemming from consumers and stores in online and physical grocery retailing," Journal of Business Research, Elsevier, vol. 112(C), pages 458-471.
    2. Nicole Stein & Stefan Spinler & Helga Vanthournout & Vered Blass, 2020. "Consumer Perception of Online Attributes in Circular Economy Activities," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
    3. Hristov, Hristov & Kuhar, Ales, 2013. "Young Urban Adults' Preferences for Wine Attributes: An Exploratory Study of the Republic of Macedonia Wine Market Applying the Best-Worst Scaling," 2013 Conference: Tools for decision support in agriculture and rural development, April 18-19, 2013, Krško, Slovenia 183907, Slovenian Association of Agricultural Economists (DAES).
    4. Christian Wankmüller & Maximilian Kunovjanek & Robert Gennaro Sposato & Gerald Reiner, 2020. "Selecting E-Mobility Transport Solutions for Mountain Rescue Operations," Energies, MDPI, vol. 13(24), pages 1-19, December.
    5. Christian Schlereth & Fabian Schulz, 2014. "Schnelle und einfache Messung von Bedeutungsgewichten mit der Restricted-Click-Stream Analyse: Ein Vergleich mit etablierten Präferenzmessmethoden," Schmalenbach Journal of Business Research, Springer, vol. 66(8), pages 630-657, December.
    6. Suk, Kwanho & Yoon, Song-Oh, 2012. "The moderating role of decision task goals in attribute weight convergence," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(1), pages 37-45.
    7. John Rose & David Hensher, 2014. "Tollroads are only part of the overall trip: the error of our ways in past willingness to pay studies," Transportation, Springer, vol. 41(4), pages 819-837, July.
    8. Enav, Friedmann & Daphna, Brueller, 2018. "Is stereotypical gender targeting effective for increasing service choice?," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 35-44.
    9. Soto, Jose R. & Adams, Damian C., 2012. "Estimating the Supply of Forest Carbon Offsets: A Comparison of Best- Worst and Discrete Choice Valuation Methods," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124830, Agricultural and Applied Economics Association.
    10. Viengkham, Doris & Baumann, Chris & Winzar, Hume & Dahana, Wirawan Dony, 2022. "Toward understanding Convergence and Divergence: Inter-ocular testing of traditional philosophies, economic orientation, and religiosity/spirituality," Journal of Business Research, Elsevier, vol. 139(C), pages 1335-1352.
    11. Stephanie A. Knox & Rosalie C. Viney & Deborah J. Street & Marion R. Haas & Denzil G. Fiebig & Edith Weisberg & Deborah Bateson, 2012. "What’s Good and Bad About Contraceptive Products?," PharmacoEconomics, Springer, vol. 30(12), pages 1187-1202, December.
    12. Joeri Hofmans & Etienne Mullet, 2013. "Towards unveiling individual differences in different stages of information processing: a clustering-based approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 455-464, January.
    13. Minh T. H. Le, 2023. "Does brand love lead to brand addiction?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(1), pages 57-68, March.
    14. Zhang, Jing & Reed Johnson, F. & Mohamed, Ateesha F. & Hauber, A. Brett, 2015. "Too many attributes: A test of the validity of combining discrete-choice and best–worst scaling data," Journal of choice modelling, Elsevier, vol. 15(C), pages 1-13.
    15. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    16. Heo, Cindy Yoonjoung & Kim, Bona & Park, Kwangsoo & Back, Robin M., 2022. "A comparison of Best-Worst Scaling and Likert Scale methods on peer-to-peer accommodation attributes," Journal of Business Research, Elsevier, vol. 148(C), pages 368-377.
    17. Greiner, Romy, 2014. "Willingness of north Australian pastoralists and graziers to participate in contractual biodiversity conservation," 2014 Conference (58th), February 4-7, 2014, Port Macquarie, Australia 165839, Australian Agricultural and Resource Economics Society.
    18. Ronny Baierl, 2018. "Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis," SAGE Open, , vol. 8(2), pages 21582440187, May.
    19. Eline Jongmans & Alain Jolibert & Julie Irwin, 2014. "Estimation du poids d'un attribut environnemental : influence et effet des mesures d'évaluation," Post-Print halshs-01185772, HAL.
    20. Meise, Jan Niklas & Rudolph, Thomas & Kenning, Peter & Phillips, Diane M., 2014. "Feed them facts: Value perceptions and consumer use of sustainability-related product information," Journal of Retailing and Consumer Services, Elsevier, vol. 21(4), pages 510-519.
    21. Marco Lerro & Giuseppe Marotta & Concetta Nazzaro, 2020. "Measuring consumers’ preferences for craft beer attributes through Best-Worst Scaling," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-13, December.
    22. Soto, José & Escobedo, Francisco & Adams, Damian, 2016. "Public and Private Preferences for Urban Forest Ecosystem Services," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236232, Agricultural and Applied Economics Association.
    23. Lagerkvist, C.J. & Edenbrandt, A.K. & Tibbelin, I. & Wahlstedt, Y., 2020. "Preferences for sustainable and responsible equity funds - A choice experiment with Swedish private investors," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    24. Steven D. Silver, 2018. "Multivariate methodology for discriminating market segments in urban commuting," Public Transport, Springer, vol. 10(1), pages 63-89, May.
    25. Kreye, Melissa M. & Adams, Damian C. & Escobedo, Francisco J. & Soto, José R., 2016. "Does policy process influence public values for forest-water resource protection in Florida?," Ecological Economics, Elsevier, vol. 129(C), pages 122-131.
    26. Dumbrell, Nikki P. & Wheeler, Sarah Ann & Zuo, Alec & Adamson, David, 2022. "Public willingness to make trade-offs in the development of a hydrogen industry in Australia," Energy Policy, Elsevier, vol. 165(C).
    27. Soto, José R. & Adams, Damian C. & Escobedo, Francisco J., 2016. "Landowner attitudes and willingness to accept compensation from forest carbon offsets: Application of best–worst choice modeling in Florida USA," Forest Policy and Economics, Elsevier, vol. 63(C), pages 35-42.
    28. Paolo Delle Site & Karim Kilani & Valerio Gatta & Edoardo Marcucci & André de Palma, 2018. "Estimation of Logit and Probit models using best, worst and best-worst choices," Working Papers hal-01953581, HAL.
    29. Graves, Rose A. & Nielsen-Pincus, Max & Haugo, Ryan D. & Holz, Andrés, 2022. "Forest carbon incentive programs for non-industrial private forests in Oregon (USA): Impacts of program design on willingness to enroll and landscape-scale program outcomes," Forest Policy and Economics, Elsevier, vol. 141(C).
    30. Claudia Symmank, 2019. "Extrinsic and intrinsic food product attributes in consumer and sensory research: literature review and quantification of the findings," Management Review Quarterly, Springer, vol. 69(1), pages 39-74, February.
    31. Feucht, Yvonne & Zander, Katrin, 2017. "Consumers’ attitudes on carbon footprint labelling. Results of the SUSDIET project," Thünen Working Paper 266396, Johann Heinrich von Thünen-Institut (vTI), Federal Research Institute for Rural Areas, Forestry and Fisheries.
    32. Xuan, Bui Bich & Ngoc, Quach Thi Khanh & Börger, Tobias, 2022. "Fisher preferences for marine litter interventions in Vietnam," Ecological Economics, Elsevier, vol. 200(C).
    33. Swinton, Scott M., 2021. "Learning about Consumer Demand from Student Surveys," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 3(3), September.
    34. Palma, David & Dios Ortuzar, Juan de & Casaubon, Gerard & Rizzi, Luis I. & Agosin, Eduardo, 2013. "Measuring consumer preferences using hybrid discrete choice models," Working Papers 164855, American Association of Wine Economists.
    35. Schlereth, Christian & Eckert, Christine & Schaaf, René & Skiera, Bernd, 2014. "Measurement of preferences with self-explicated approaches: A classification and merge of trade-off- and non-trade-off-based evaluation types," European Journal of Operational Research, Elsevier, vol. 238(1), pages 185-198.
    36. Huang, Lijuan & Mou, Jian & See-To, Eric W.K. & Kim, Jongki, 2019. "Consumer perceived value preferences for mobile marketing in China: A mixed method approach," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 70-86.
    37. Paolo Delle Site & Karim Kilani & Valerio Gatta & Edoardo Marcucci & André de Palma, 2019. "Estimation of consistent Logit and Probit models using best, worst and best–worst choices," Post-Print hal-03719022, HAL.
    38. Soto, José R. & Escobedo, Francisco J. & Khachatryan, Hayk & Adams, Damian C., 2018. "Consumer demand for urban forest ecosystem services and disservices: Examining trade-offs using choice experiments and best-worst scaling," Ecosystem Services, Elsevier, vol. 29(PA), pages 31-39.
    39. Katharina Keller & Christian Schlereth & Oliver Hinz, 2021. "Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time," Journal of the Academy of Marketing Science, Springer, vol. 49(3), pages 482-500, May.
    40. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    41. Ana Margarita Larranaga & Julián Arellana & Luis Ignacio Rizzi & Orlando Strambi & Helena Beatriz Bettella Cybis, 2019. "Using best–worst scaling to identify barriers to walkability: a study of Porto Alegre, Brazil," Transportation, Springer, vol. 46(6), pages 2347-2379, December.
    42. Riera, Pere & Signorello, Giovanni & Thiene, Mara & Mahieu, Pierre-Alexandre & Navrud, Ståle & Kaval, Pamela & Rulleau, Benedicte & Mavsar, Robert & Madureira, Lívia & Meyerhoff, Jürgen & Elsasser, Pe, 2012. "Non-market valuation of forest goods and services: Good practice guidelines," Journal of Forest Economics, Elsevier, vol. 18(4), pages 259-270.
    43. Janssen, Meike & Hamm, Ulrich, 2014. "Governmental and private certification labels for organic food: Consumer attitudes and preferences in Germany," Food Policy, Elsevier, vol. 49(P2), pages 437-448.
    44. Oliver Meixner & Felix Katt, 2020. "Assessing the Impact of COVID-19 on Consumer Food Safety Perceptions—A Choice-Based Willingness to Pay Study," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    45. Sung-Kwon Hong & Ju-Mi Kim & Hyun-Kil Jo & Sang-Woo Lee, 2018. "Monetary Valuation of Urban Forest Attributes in Highly Developed Urban Environments: An Experimental Study Using a Conjoint Choice Model," Sustainability, MDPI, vol. 10(7), pages 1-22, July.
    46. Axel C. Mühlbacher & Peter Zweifel & Anika Kaczynski & F. Reed Johnson, 2016. "Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues," Health Economics Review, Springer, vol. 6(1), pages 1-12, December.
    47. Sandra Notaro & Maria De Salvo & Roberta Raffaelli, 2022. "Estimating Willingness to Pay for Alpine Pastures: A Discrete Choice Experiment Accounting for Attribute Non-Attendance," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    48. Murray Rudd, 2011. "An Exploratory Analysis of Societal Preferences for Research-Driven Quality of Life Improvements in Canada," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 101(1), pages 127-153, March.
    49. Rubino, Elena C. & Pienaar, Elizabeth F. & Soto, José R., 2018. "Structuring Legal Trade in Rhino Horn to Incentivize the Participation of South African Private Landowners," Ecological Economics, Elsevier, vol. 154(C), pages 306-316.
    50. Stefanie Heinzle, 2012. "Disclosure of Energy Operating Cost Information: A Silver Bullet for Overcoming the Energy-Efficiency Gap?," Journal of Consumer Policy, Springer, vol. 35(1), pages 43-64, March.
    51. Mueller, Simone C. & Umberger, Wendy J., 2010. "“Pick the Tick” The Impact of Health Endorsements on Consumers’ Food Choices," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116436, European Association of Agricultural Economists.
    52. Simone Mueller & Larry Lockshin & Jordan Louviere, 2010. "What you see may not be what you get: Asking consumers what matters may not reflect what they choose," Marketing Letters, Springer, vol. 21(4), pages 335-350, December.
    53. Macea, Luis F. & Cantillo, Victor & Arellana, Julian, 2018. "Influence of attitudes and perceptions on deprivation cost functions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 125-141.
    54. Fernando, Angeline Gautami & Aw, Eugene Cheng-Xi, 2023. "What do consumers want? A methodological framework to identify determinant product attributes from consumers’ online questions," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    55. Erdem, Seda & Rigby, Dan, 2011. "Using Best Worst Scaling To Investigate Perceptions Of Control & Concern Over Food And Non-Food Risks," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108790, Agricultural Economics Society.
    56. Kreye, Melissa M. & Adams, Damian C. & Ober, Holly K., 2018. "Protecting Imperiled Wildlife Species on Private Lands: Forest Owner Values and Response to Government Interventions," Ecological Economics, Elsevier, vol. 149(C), pages 254-264.
    57. Nikolina Dukić Samaržija, 2019. "Determining the Marginal Willingness to Pay for the Cervical Cancer Screening Program in Croatia: A Best-Worst Scaling Approach," Society and Economy, Akadémiai Kiadó, Hungary, vol. 41(4), pages 433-447, December.
    58. Kei Long Cheung & Ben F. M. Wijnen & Ilene L. Hollin & Ellen M. Janssen & John F. Bridges & Silvia M. A. A. Evers & Mickael Hiligsmann, 2016. "Using Best–Worst Scaling to Investigate Preferences in Health Care," PharmacoEconomics, Springer, vol. 34(12), pages 1195-1209, December.
    59. David Quarfoot & Douglas Kohorn & Kevin Slavin & Rory Sutherland & David Goldstein & Ellen Konar, 2017. "Quadratic voting in the wild: real people, real votes," Public Choice, Springer, vol. 172(1), pages 283-303, July.
    60. Galassi, Veronica & Madlener, Reinhard, 2014. "Identifying Business Models for Photovoltaic Systems with Storage in the Italian Market: A Discrete Choice Experiment," FCN Working Papers 19/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    61. Scarpa, Riccardo & Notaro, Sandra & Raffaelli, Roberta & Louviere, Jordan, 2011. "Modelling attribute non-attendance in best-worst rank ordered choice data to estimate tourism benefits from Alpine pasture heritage," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115990, European Association of Agricultural Economists.
    62. Franke, Melanie & Nadler, Claudia, 2019. "Energy efficiency in the German residential housing market: Its influence on tenants and owners," Energy Policy, Elsevier, vol. 128(C), pages 879-890.
    63. Luis Pérez y Pérez & Azucena Gracia, 2023. "Consumer Preferences for Olive Oil in Spain: A Best-Worst Scaling Approach," Sustainability, MDPI, vol. 15(14), pages 1-14, July.
    64. Jarvis, Wade & Mueller, Simone & Chiong, Kathleen, 2010. "A latent analysis of images and words in wine choice," Australasian marketing journal, Elsevier, vol. 18(3), pages 138-144.

  21. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.

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    1. Theologos Dergiades & Apostolos Dasilas, 2010. "Modelling and forecasting mobile telecommunication services: the case of Greece," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1823-1828.
    2. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    3. Baburin, Vyacheslav & Zemtsov, Stepan, 2014. "Diffussion of ICT-products and "five Russias"," MPRA Paper 68926, University Library of Munich, Germany, revised 10 May 2014.
    4. Cristian Giovanni Colombo & Fabio Borghetti & Michela Longo & Federica Foiadelli, 2023. "Electrification of Motorway Network: A Methodological Approach to Define Location of Charging Infrastructure for EV," Sustainability, MDPI, vol. 15(23), pages 1-21, November.
    5. José Antonio Moya, 2016. "A Natural Analogy to the Diffusion of Energy-Efficient Technologies," Energies, MDPI, vol. 9(6), pages 1-14, June.
    6. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    7. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
    8. Hong, Zhaofu & Li, Mengfan & Han, Xiaoya & He, Xuhuai, 2020. "Innovative green product diffusion through word of mouth," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    9. Adarsh Anand & Richie Aggarwal & Ompal Singh, 2019. "Using Weibull Distribution for Modeling Bimodal Diffusion Curves: A Naive Framework to Study Product Life Cycle," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(07), pages 1-17, November.
    10. Adrien Bernard Bonache & Marc Filser, 2013. "Comment améliorer la prévision des ventes pour le marketing ? Les apports de la théorie du chaos," Post-Print hal-03822792, HAL.
    11. Karakaya, Emrah, 2016. "Finite Element Method for forecasting the diffusion of photovoltaic systems: Why and how?," Applied Energy, Elsevier, vol. 163(C), pages 464-475.
    12. Truschkin, Eugen & Elbert, Ralf, 2013. "Horizontal transshipment technologies as enablers of combined transport: Impact of transport policies on the modal split," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 91-109.
    13. Elias Aravantinos & Dimitris Varoutas, 2022. "A revisit of fixed and mobile broadband diffusion in the OECD: a new classification," Netnomics, Springer, vol. 22(2), pages 71-84, October.
    14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    15. Mesak, Hani I. & Bari, Abdullahel & Babin, Barry J. & Birou, Laura M. & Jurkus, Anthony, 2011. "Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers' disadoption," European Journal of Operational Research, Elsevier, vol. 211(3), pages 642-649, June.
    16. Marinakis, Yorgos D., 2012. "Forecasting technology diffusion with the Richards model," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 172-179.
    17. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    18. David G. Green, 2023. "Emergence in complex networks of simple agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 419-462, July.
    19. Plötz, Patrick & Gnann, Till & Wietschel, Martin, 2014. "Modelling market diffusion of electric vehicles with real world driving data — Part I: Model structure and validation," Ecological Economics, Elsevier, vol. 107(C), pages 411-421.
    20. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    21. Mikko Myrskylä & Joshua R. Goldstein, 2010. "Probabilistic forecasting using stochastic diffusion models, with applications to cohort processes of marriage and fertility," MPIDR Working Papers WP-2010-013, Max Planck Institute for Demographic Research, Rostock, Germany.
    22. Giovanni Modanese, 2023. "The Network Bass Model with Behavioral Compartments," Stats, MDPI, vol. 6(2), pages 1-13, March.
    23. José de Castro Vieira, Samuel & Tapia Carpio, Lucio Guido, 2020. "The economic impact on residential fees associated with the expansion of grid-connected solar photovoltaic generators in Brazil," Renewable Energy, Elsevier, vol. 159(C), pages 1084-1098.
    24. James Waters, 2017. "Determinants of initial technology adoption and intensification: evidence from Latin America and the Caribbean," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(4), pages 334-352, May.
    25. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    26. Kaldasch, Joachim, 2011. "Evolutionary model of an anonymous consumer durable market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(14), pages 2692-2715.
    27. Agner, Joy & Barile, John P. & Chandler, Susan M. & Berry, Marianne, 2020. "Innovation in child welfare: Factors affecting adoption of empirically supported interventions," Children and Youth Services Review, Elsevier, vol. 119(C).
    28. Furlan, Claudia & Guidolin, Mariangela & Guseo, Renato, 2016. "Has the Fukushima accident influenced short-term consumption in the evolution of nuclear energy? An analysis of the world and seven leading countries," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 37-49.
    29. Roberts, Ruby & Flin, Rhona & Millar, David & Corradi, Luca, 2021. "Psychological factors influencing technology adoption: A case study from the oil and gas industry," Technovation, Elsevier, vol. 102(C).
    30. Guseo, Renato & Mortarino, Cinzia, 2012. "Sequential market entries and competition modelling in multi-innovation diffusions," European Journal of Operational Research, Elsevier, vol. 216(3), pages 658-667.
    31. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    32. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    33. Wang, Juite & Lai, Jung-Yu & Chang, Chih-Hsin, 2016. "Modeling and analysis for mobile application services: The perspective of mobile network operators," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 146-163.
    34. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    35. Riikonen, Antti & Smura, Timo & Töyli, Juuso, 2016. "The effects of price, popularity, and technological sophistication on mobile handset replacement and unit lifetime," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 313-323.
    36. Bodo, Peter, 2016. "MADness in the method: On the volatility and irregularity of technology diffusion," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 2-11.
    37. Jessica Schoner & Greg Lindsey & David Levinson, 2015. "Is Bicycling Contagious? Effects of Bike Share Stations and Activity on System Membership and General Population Cycling," Working Papers 000137, University of Minnesota: Nexus Research Group.
    38. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    39. Nathalia Granja & Pedro Domingues & Mónica Cabecinhas & Dominik Zimon & Paulo Sampaio, 2021. "ISO 22000 Certification: Diffusion in Europe," Resources, MDPI, vol. 10(10), pages 1-16, September.
    40. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Predicting diffusion dynamics and launch time strategy for mobile telecommunication services: an empirical analysis," Information Technology and Management, Springer, vol. 22(1), pages 33-51, March.
    41. Foster, John, 2021. "In search of a suitable heuristic for evolutionary economics: from generalized Darwinism to economic self-organisation," MPRA Paper 106146, University Library of Munich, Germany.
    42. Chien, Chen-Fu & Chen, Yun-Ju & Peng, Jin-Tang, 2010. "Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle," International Journal of Production Economics, Elsevier, vol. 128(2), pages 496-509, December.
    43. Huang, Lizhen & Bohne, Rolf André & Lohne, Jardar, 2015. "Shelter and residential building energy consumption within the 450 ppm CO2eq constraints in different climate zones," Energy, Elsevier, vol. 90(P1), pages 965-979.
    44. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Technology diffusion model with change in adoption rate and repeat purchases: a case of consumer balking," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(1), pages 29-36, February.
    45. Hingley, Peter & Park, Walter G., 2017. "Do business cycles affect patenting? Evidence from European Patent Office filings," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 76-86.
    46. Marius F. Niculescu & Hyoduk Shin & Seungjin Whang, 2012. "Underlying Consumer Heterogeneity in Markets for Subscription-Based IT Services with Network Effects," Information Systems Research, INFORMS, vol. 23(4), pages 1322-1341, December.
    47. Park, Sang Yong & Kim, Jong Wook & Lee, Duk Hee, 2011. "Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects," Energy Policy, Elsevier, vol. 39(6), pages 3307-3315, June.
    48. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    49. Tarek Ben Rhouma & Georges Zaccour, 2018. "Optimal Marketing Strategies for the Acquisition and Retention of Service Subscriber," Management Science, INFORMS, vol. 64(6), pages 2609-2627, June.
    50. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    51. Kobos, Peter H. & Malczynski, Leonard A. & Walker, La Tonya N. & Borns, David J. & Klise, Geoffrey T., 2018. "Timing is everything: A technology transition framework for regulatory and market readiness levels," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 211-225.
    52. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    53. Yamakawa, Peter & Rees, Gareth H. & Manuel Salas, José & Alva, Nikolai, 2013. "The diffusion of mobile telephones: An empirical analysis for Peru," Telecommunications Policy, Elsevier, vol. 37(6), pages 594-606.
    54. Laciana, C.E. & Gual, G. & Kalmus, D. & Oteiza-Aguirre, N. & Rovere, S.L., 2014. "Diffusion of two brands in competition: Cross-brand effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 104-115.
    55. Dong, Andy & Sarkar, Somwrita, 2015. "Forecasting technological progress potential based on the complexity of product knowledge," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 599-610.
    56. Claudia Furlan & Cinzia Mortarino & Mohammad Salim Zahangir, 2021. "Interaction among three substitute products: an extended innovation diffusion model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 269-293, March.
    57. Naveed, Kashif & Watanabe, Chihiro & Neittaanmäki, Pekka, 2017. "Co-evolution between streaming and live music leads a way to the sustainable growth of music industry – Lessons from the US experiences," Technology in Society, Elsevier, vol. 50(C), pages 1-19.
    58. Duan, Hong-Bo & Zhu, Lei & Fan, Ying, 2014. "A cross-country study on the relationship between diffusion of wind and photovoltaic solar technology," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 156-169.
    59. Islam, Towhidul & Meade, Nigel & Carson, Richard T. & Louviere, Jordan J. & Wang, Juan, 2022. "The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures," Journal of Business Research, Elsevier, vol. 151(C), pages 324-338.
    60. Winkler, Kay, 2014. "Potential Effects of New Zealand's Policy on Next Generation High-Speed Access Networks," Working Paper Series 19308, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    61. Dong, Changgui & Sigrin, Benjamin & Brinkman, Gregory, 2017. "Forecasting residential solar photovoltaic deployment in California," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 251-265.
    62. Franklin M. Lartey, 2020. "Predicting Product Uptake Using Bass, Gompertz, and Logistic Diffusion Models: Application to a Broadband Product," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 9(2), pages 1-5, October.
    63. Xiao, Yu & Han, Jingti, 2016. "Forecasting new product diffusion with agent-based models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 167-178.
    64. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    65. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    66. Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
    67. Rządkowski Grzegorz & Sobczak Lidia, 2020. "A Generalized Logistic Function and its Applications," Foundations of Management, Sciendo, vol. 12(1), pages 85-92, January.
    68. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    69. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    70. Waters, James, 2015. "Determinants of initial technology adoption and intensification: evidence from Latin America and the Caribbean," MPRA Paper 61473, University Library of Munich, Germany.
    71. Bin Shen & Hau-Ling Chan, 2017. "Forecast Information Sharing for Managing Supply Chains in the Big Data Era: Recent Development and Future Research," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-26, February.
    72. Jos? ?ngel Gimeno & Eva Llera Sastresa & Sabina Scarpellini, 2020. "Determinants and barriers of PV self-consumption in Spain from the perception of the installers for the promotion of distributed energy systems," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 0(1), pages 153-169.
    73. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    74. Bary S.R. Pradelski, 2015. "The Dynamics of Social Influence," Economics Series Working Papers 742, University of Oxford, Department of Economics.
    75. Renato Guseo & Mariangela Guidolin, 2008. "Cellular automata and Riccati equation models for diffusion of innovations," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 291-308, July.
    76. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
    77. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    78. Lu, Louis Y.Y. & Hsieh, Chih-Hung & Liu, John S., 2016. "Development trajectory and research themes of foresight," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 347-356.
    79. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.
    80. Ganglmair-Wooliscroft, Alexandra & Wooliscroft, Ben, 2016. "Diffusion of innovation: The case of ethical tourism behavior," Journal of Business Research, Elsevier, vol. 69(8), pages 2711-2720.
    81. Bin Hu & Zhankun Sun, 2022. "Managing Self-Replicating Innovative Goods," Management Science, INFORMS, vol. 68(1), pages 399-419, January.
    82. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    83. R. Gutiérrez & R. Gutiérrez‐Sánchez & A. Nafidi, 2009. "Modelling and forecasting vehicle stocks using the trends of stochastic Gompertz diffusion models: The case of Spain," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 385-405, May.
    84. Ding, Fei & Liu, Yun, 2009. "A decision theoretical approach for diffusion promotion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3572-3580.
    85. Carlos Pablo Sigüenza & Bernhard Steubing & Arnold Tukker & Glenn A. Aguilar‐Hernández, 2021. "The environmental and material implications of circular transitions: A diffusion and product‐life‐cycle‐based modeling framework," Journal of Industrial Ecology, Yale University, vol. 25(3), pages 563-579, June.
    86. Vahideh Sadat Abedi & Oded Berman & Fred M. Feinberg & Dmitry Krass, 2022. "Strategic new product media planning under emergent channel substitution and synergy," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2143-2166, May.
    87. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    88. Klingler, Anna-Lena, 2017. "Self-consumption with PV+Battery systems: A market diffusion model considering individual consumer behaviour and preferences," Applied Energy, Elsevier, vol. 205(C), pages 1560-1570.
    89. Xu, Jiuping & Li, Li & Zheng, Bobo, 2016. "Wind energy generation technological paradigm diffusion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 436-449.
    90. van Blommestein, Kevin & Daim, Tugrul U. & Cho, Yonghee & Sklar, Paul, 2018. "Structuring financial incentives for residential solar electric systems," Renewable Energy, Elsevier, vol. 115(C), pages 28-40.
    91. Qian, Lixian & Soopramanien, Didier, 2014. "Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market," Journal of Business Research, Elsevier, vol. 67(6), pages 1226-1232.
    92. Xenikos, D.G. & Constantoudis, V., 2023. "Weibull dynamics and power-law diffusion of epidemics in small world 2D networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    93. Javaid, Aneeque & Janssen, Marco A. & Reuter, Hauke & Schlüter, Achim, 2017. "When Patience Leads to Destruction: The Curious Case of Individual Time Preferences and the Adoption of Destructive Fishing Gears," Ecological Economics, Elsevier, vol. 142(C), pages 91-103.
    94. Meihan He & Jongsu Lee, 2020. "Social culture and innovation diffusion: a theoretically founded agent-based model," Journal of Evolutionary Economics, Springer, vol. 30(4), pages 1109-1149, September.
    95. Petre, Konstantin & Varoutas, Dimitris, 2022. "On the application of Machine Learning in telecommunications forecasting: A comparison," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265665, International Telecommunications Society (ITS).
    96. Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
    97. Hongyi Chen & Turuna Seecharan & Chen Feng, 2024. "Promoting the Diffusion of Sustainable Innovations through Customer Education—A Case of the Cosmetic Industry," Sustainability, MDPI, vol. 16(6), pages 1-17, March.
    98. Guseo, Renato & Guidolin, Mariangela, 2015. "Heterogeneity in diffusion of innovations modelling: A few fundamental types," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 514-524.
    99. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    100. Hultman, Nathan E. & Malone, Elizabeth L. & Runci, Paul & Carlock, Gregory & Anderson, Kate L., 2012. "Factors in low-carbon energy transformations: Comparing nuclear and bioenergy in Brazil, Sweden, and the United States," Energy Policy, Elsevier, vol. 40(C), pages 131-146.
    101. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2019. "Modeling Technological Substitution by Incorporating Dynamic Adoption Rate," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-24, February.
    102. Il-Horn Hann & Byungwan Koh & Marius F. Niculescu, 2016. "The Double-Edged Sword of Backward Compatibility: The Adoption of Multigenerational Platforms in the Presence of Intergenerational Services," Information Systems Research, INFORMS, vol. 27(1), pages 112-130, March.
    103. Nandakumar, Karthik & Funk, Jeffrey L., 2015. "Understanding the timing of economic feasibility: The case of input interfaces for human-computer interaction," Technology in Society, Elsevier, vol. 43(C), pages 33-49.
    104. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    105. Oliver Schaer & Nikolaos Kourentzes & Robert Fildes, 2022. "Predictive competitive intelligence with prerelease online search traffic," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3823-3839, October.
    106. Meeran, Sheik & Jahanbin, Semco & Goodwin, Paul & Quariguasi Frota Neto, Joao, 2017. "When do changes in consumer preferences make forecasts from choice-based conjoint models unreliable?," European Journal of Operational Research, Elsevier, vol. 258(2), pages 512-524.
    107. Wildauer, Rafael & Heck, Ines & Kapeller, Jakob, 2023. "Was Pareto right? Is the distribution of wealth thick-tailed?," Greenwich Papers in Political Economy 38597, University of Greenwich, Greenwich Political Economy Research Centre.
    108. Hongmin Li, 2020. "Optimal Pricing Under Diffusion-Choice Models," Operations Research, INFORMS, vol. 68(1), pages 115-133, January.
    109. Singh, Shiwangi & Dhir, Sanjay & Das, V. Mukunda & Sharma, Anuj, 2020. "Bibliometric overview of the Technological Forecasting and Social Change journal: Analysis from 1970 to 2018," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    110. Ye Li & Clemens Kool & Peter-Jan Engelen, 2020. "Analyzing the Business Case for Hydrogen-Fuel Infrastructure Investments with Endogenous Demand in The Netherlands: A Real Options Approach," Sustainability, MDPI, vol. 12(13), pages 1-22, July.
    111. Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    112. Singh, Rhythm, 2018. "Energy sufficiency aspirations of India and the role of renewable resources: Scenarios for future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2783-2795.
    113. Ryszard Kata & Kazimierz Cyran & Sławomir Dybka & Małgorzata Lechwar & Rafał Pitera, 2021. "Economic and Social Aspects of Using Energy from PV and Solar Installations in Farmers’ Households in the Podkarpackie Region," Energies, MDPI, vol. 14(11), pages 1-21, May.
    114. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2020. "Modeling technology diffusion: a study based on market coverage and advertising efforts," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 154-162, July.
    115. Nguyen, Hong-Trang & Skitmore, Martin & Gray, Matthew & Zhang, Xiaoling & Olanipekun, Ayokunle Olubunmi, 2017. "Will green building development take off? An exploratory study of barriers to green building in Vietnam," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 8-20.
    116. Mikko Myrskylä & Joshua Goldstein, 2013. "Probabilistic Forecasting Using Stochastic Diffusion Models, With Applications to Cohort Processes of Marriage and Fertility," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 237-260, February.
    117. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    118. Seebauer, Sebastian, 2015. "Why early adopters engage in interpersonal diffusion of technological innovations: An empirical study on electric bicycles and electric scooters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 146-160.
    119. Simpson, Jesse R. & Mishra, Sabyasachee & Talebian, Ahmadreza & Golias, Mihalis M., 2019. "An estimation of the future adoption rate of autonomous trucks by freight organizations," Research in Transportation Economics, Elsevier, vol. 76(C).
    120. Boateng, Mark K. & Awuah-Offei, Kwame, 2017. "Agent-based modeling framework for modeling the effect of information diffusion on community acceptance of mining," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 1-11.
    121. Shi, Xiaohui & Li, Feng & Bigdeli, Ali Ziaee, 2016. "An examination of NPD models in the context of business models," Journal of Business Research, Elsevier, vol. 69(7), pages 2541-2550.
    122. Heinz, B. & Graeber, M. & Praktiknjo, A.J., 2013. "The diffusion process of stationary fuel cells in a two-sided market economy," Energy Policy, Elsevier, vol. 61(C), pages 1556-1567.
    123. Benseny, Jaume & Lahteenmaki, Jarno & Toyli, Juuso & Hammainen, Heikki, 2023. "Urban wireless traffic evolution: The role of new devices and the effect of policy," Telecommunications Policy, Elsevier, vol. 47(7).
    124. José Antonio Moya, 2017. "Where Diffusion of Clean Technologies and Barriers to Innovation Clash: Application to the Global Diffusion of the Electrical Arc Furnace," Energies, MDPI, vol. 10(1), pages 1-22, January.
    125. Sabina Scarpellini & José Ángel Gimeno & Pilar Portillo-Tarragona & Eva Llera-Sastresa, 2021. "Financial Resources for the Investments in Renewable Self-Consumption in a Circular Economy Framework," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    126. Bary Pradelski, 2019. "Control by social influence: durables vs. non-durables," Post-Print hal-03100218, HAL.
    127. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
    128. Avila, Luz Angelica Pirir & Lee, Deok-Joo & Kim, Taegu, 2018. "Diffusion and competitive relationship of mobile telephone service in Guatemala: An empirical analysis," Telecommunications Policy, Elsevier, vol. 42(2), pages 116-126.
    129. Harijan, Khanji & Uqaili, Mohammad A. & Memon, Mujeebuddin & Mirza, Umar K., 2011. "Forecasting the diffusion of wind power in Pakistan," Energy, Elsevier, vol. 36(10), pages 6068-6073.
    130. Dragan Lazarević & Libor Švadlenka & Valentina Radojičić & Momčilo Dobrodolac, 2020. "New Express Delivery Service and Its Impact on CO 2 Emissions," Sustainability, MDPI, vol. 12(2), pages 1-29, January.
    131. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    132. Xu, Mei & Xie, Pu & Xie, Bai-Chen, 2020. "Study of China's optimal solar photovoltaic power development path to 2050," Resources Policy, Elsevier, vol. 65(C).
    133. Hongmin Li & Dieter Armbruster & Karl G. Kempf, 2013. "A Population-Growth Model for Multiple Generations of Technology Products," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 343-360, July.
    134. Shagun Srivastava & Madhvendra Misra, 2014. "Developing Evaluation Matrix for Critical Success Factors in Technology Forecasting," Global Business Review, International Management Institute, vol. 15(2), pages 363-380, June.
    135. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2012. "Exploring the determinants of the OSS market potential: The case of the Apache web server," Telecommunications Policy, Elsevier, vol. 36(1), pages 51-68.
    136. Fernández-Durán, J.J., 2014. "Modeling seasonal effects in the Bass Forecasting Diffusion Model," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 251-264.
    137. Yi-Hui Chiang & Yiming Li & Chih-Young Hung, 2007. "A Dynamic Growth Model for Flows of Foreign Direct Investment," DEGIT Conference Papers c012_047, DEGIT, Dynamics, Economic Growth, and International Trade.
    138. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    139. Casey Olechnowicz & Jessica Leahy & Tian Guo & Emily Silver Huff & Cecilia Danks & Maura Adams, 2021. "Industry Leaders’ Perceptions of Residential Wood Pellet Technology Diffusion in the Northeastern U.S," Sustainability, MDPI, vol. 13(8), pages 1-15, April.
    140. Jonathan R B Fisher & Jensen Montambault & Kyle P Burford & Trisha Gopalakrishna & Yuta J Masuda & Sheila M W Reddy & Kaitlin Torphy & Andrea I Salcedo, 2018. "Knowledge diffusion within a large conservation organization and beyond," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-24, March.
    141. Yoon Seong Kim & Eun Jin Han & So Young Sohn, 2017. "Demand Forecasting for Heavy-Duty Diesel Engines Considering Emission Regulations," Sustainability, MDPI, vol. 9(2), pages 1-16, January.
    142. Schmidthuber, Lisa & Maresch, Daniela & Ginner, Michael, 2020. "Disruptive technologies and abundance in the service sector - toward a refined technology acceptance model," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    143. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    144. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
    145. Hunecke, C. & Meyer, S. & Brummer, B., 2018. "Technology Diffusion through Networks - Adoption of automatic milking systems in Germany," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277543, International Association of Agricultural Economists.
    146. Liu-Thompkins, Yuping & Rogerson, Michelle, 2012. "Rising to Stardom: An Empirical Investigation of the Diffusion of User-generated Content," Journal of Interactive Marketing, Elsevier, vol. 26(2), pages 71-82.
    147. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    148. Tadeusz Skoczkowski & Sławomir Bielecki & Joanna Wojtyńska, 2019. "Long-Term Projection of Renewable Energy Technology Diffusion," Energies, MDPI, vol. 12(22), pages 1-24, November.
    149. B Aytac & S D Wu, 2011. "Modelling high-tech product life cycles with short-term demand information: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 425-432, March.
    150. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    151. Christine Roxanne Hung & Paul Kishimoto & Volker Krey & Anders Hammer Strømman & Guillaume Majeau‐Bettez, 2022. "ECOPT2: An adaptable life cycle assessment model for the environmentally constrained optimization of prospective technology transitions," Journal of Industrial Ecology, Yale University, vol. 26(5), pages 1616-1630, October.
    152. Almaz Mustafin & Aliya Kantarbayeva, 2021. "Resource competition and technological diversity," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-37, November.
    153. P. Ding & M. D. Gerst & G. Bang & M. E. Borsuk, 2015. "An Application of Automated Mediation to International Climate Treaty Negotiation," Group Decision and Negotiation, Springer, vol. 24(5), pages 885-903, September.
    154. Velickovic, Stevan & Radojicic, Valentina & Bakmaz, Bojan, 2016. "The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 130-140.
    155. Islam, Towhidul & Meade, Nigel, 2013. "The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation," Energy Policy, Elsevier, vol. 55(C), pages 521-530.
    156. Semra Gunduc, 2021. "Diffusion of Innovation In Competitive Markets-A Study on the Global Smartphone Diffusion," Papers 2103.07707, arXiv.org.
    157. S. P. Zemtsov & V. L. Baburin, 2020. "COVID-19: Spatial Dynamics and Diffusion Factors across Russian Regions," Regional Research of Russia, Springer, vol. 10(3), pages 273-290, July.
    158. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    159. Rządkowski Grzegorz & Głażewska Iwona & Sawińska Katarzyna, 2014. "Logistic Function as a Tool of Planning," Foundations of Management, Sciendo, vol. 6(1), pages 57-70, June.
    160. Christ, Katherine L. & Burritt, Roger L., 2016. "ISO 14051: A new era for MFCA implementation and research," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 1-9.
    161. Pranpreya Sriwannawit & Ulf Sandström, 2015. "Large-scale bibliometric review of diffusion research," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1615-1645, February.
    162. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Determination of Electricity Demand by Personal Light Electric Vehicles (PLEVs): An Example of e-Motor Scooters in the Context of Large City Management in Poland," Energies, MDPI, vol. 13(1), pages 1-18, January.
    163. Stepan Zemtsov & Vyacheslav Baburin, 2013. "Innovation potential of regions in Northern Eurasia," ERSA conference papers ersa13p546, European Regional Science Association.
    164. Pradelski, Bary S.R., 2023. "Social influence: The Usage History heuristic," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 105-113.
    165. Chung, Wenming & Talluri, Srinivas & Narasimhan, Ram, 2015. "Optimal pricing and inventory strategies with multiple price markdowns over time," European Journal of Operational Research, Elsevier, vol. 243(1), pages 130-141.
    166. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    167. Wasilewski, Adam & Floriańczyk, Zbigniew & Wigier, Marek, 2013. "Governance of Internet development in rural areas in the context of territorial competitiveness: the case of Poland," Rural Areas and Development, European Rural Development Network (ERDN), vol. 10, pages 1-17.
    168. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries," Energies, MDPI, vol. 13(16), pages 1-20, August.
    169. Hélène Dernis & Mariagrazia Squicciarini & Roberto Pinho, 2016. "Detecting the emergence of technologies and the evolution and co-development trajectories in science (DETECTS): a ‘burst’ analysis-based approach," The Journal of Technology Transfer, Springer, vol. 41(5), pages 930-960, October.
    170. Ding, Fei & Liu, Yun & Shen, Bo & Si, Xia-Meng, 2010. "An evolutionary game theory model of binary opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1745-1752.
    171. José Ángel Gimeno & Eva Llera & Sabina Scarpellini, 2018. "Investment Determinants in Self-Consumption Facilities: Characterization and Qualitative Analysis in Spain," Energies, MDPI, vol. 11(8), pages 1-24, August.
    172. Strong, Derek Ryan, 2017. "The Early Diffusion of Smart Meters in the US Electric Power Industry," Thesis Commons 7zprk, Center for Open Science.
    173. Ramin Shabanpour & Ali Shamshiripour & Abolfazl Mohammadian, 2018. "Modeling adoption timing of autonomous vehicles: innovation diffusion approach," Transportation, Springer, vol. 45(6), pages 1607-1621, November.
    174. Lee, Jongsu & Cho, Youngsang, 2009. "Demand forecasting of diesel passenger car considering consumer preference and government regulation in South Korea," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 420-429, May.
    175. Si, Xia-Meng & Liu, Yun & Xiong, Fei & Zhang, Yan-Chao & Ding, Fei & Cheng, Hui, 2010. "Effects of selective attention on continuous opinions and discrete decisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3711-3719.
    176. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    177. Christos Michalakelis & Georgia Dede & Dimitris Varoutas & Thomas Sphicopoulos, 2010. "Estimating diffusion and price elasticity with application to telecommunications," Netnomics, Springer, vol. 11(3), pages 221-242, October.
    178. Le Vine, Scott & Polak, John, 2019. "The impact of free-floating carsharing on car ownership: Early-stage findings from London," Transport Policy, Elsevier, vol. 75(C), pages 119-127.
    179. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    180. Karakaya, Emrah, 2014. "Finite Element Model of the Innovation Diffusion: An Application to Photovoltaic Systems," INDEK Working Paper Series 2014/6, Royal Institute of Technology, Department of Industrial Economics and Management.
    181. Liao, Shuangqing & Seifert, Ralf W., 2015. "On the optimal frequency of multiple generation product introductions," European Journal of Operational Research, Elsevier, vol. 245(3), pages 805-814.
    182. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    183. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    184. Bertotti, M.L. & Brunner, J. & Modanese, G., 2016. "The Bass diffusion model on networks with correlations and inhomogeneous advertising," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 55-63.
    185. Bonnin Roca, Jaime, 2022. "Teaching technological forecasting to undergraduate students: a reflection on challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    186. Chang, Shuhua & Zhang, Zhaowei & Wang, Xinyu & Dong, Yan, 2020. "Optimal acquisition and retention strategies in a duopoly model of competition," European Journal of Operational Research, Elsevier, vol. 282(2), pages 677-695.
    187. Susanne Linder, 2011. "Spatial diffusion of electric vehicles in the German metropolitan region of Stuttgart," ERSA conference papers ersa11p557, European Regional Science Association.
    188. Kaldasch, Joachim, 2015. "Dynamic Model of Markets of Successive Product Generations," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(3), pages 1-15.
    189. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    190. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    191. Ellero, Andrea & Fasano, Giovanni & Sorato, Annamaria, 2009. "A modified Galam’s model for word-of-mouth information exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3901-3910.
    192. Plötz, Patrick & Gnann, Till & Wietschel, Martin, 2014. "Modelling market diffusion of electric vehicles with real world driving data. Part I: Model structure and validation," Working Papers "Sustainability and Innovation" S4/2014, Fraunhofer Institute for Systems and Innovation Research (ISI).
    193. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.
    194. Derbyshire, James & Giovannetti, Emanuele, 2017. "Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 334-344.
    195. Ashish Sood & Gareth M. James & Gerard J. Tellis & Ji Zhu, 2012. "Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder," Marketing Science, INFORMS, vol. 31(6), pages 964-979, November.
    196. Samuel Bjork & Avner Offer & Gabriel Söderberg, 2014. "Time series citation data: the Nobel Prize in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 185-196, January.
    197. Feng, Guangchao Charles, 2015. "Determinants of Internet diffusion: A focus on China," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 176-185.

  22. Robert Bartels & Towhidul Islam, 2002. "Supply Restricted Telecommunications Markets: The Effect of Technical Efficiency on Waiting Times," Journal of Productivity Analysis, Springer, vol. 18(2), pages 161-169, September.

    Cited by:

    1. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    2. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

  23. Islam, Towhidul & Fiebig, Denzil G. & Meade, Nigel, 2002. "Modelling multinational telecommunications demand with limited data," International Journal of Forecasting, Elsevier, vol. 18(4), pages 605-624.

    Cited by:

    1. Russel Cooper & Gary Madden, 2010. "Estimating components of ICT expenditure: a model-based approach with applicability to short time-series," Applied Economics, Taylor & Francis Journals, vol. 42(1), pages 87-96.
    2. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
    3. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    4. Ding, Song & Tao, Zui & Zhang, Huahan & Li, Yao, 2022. "Forecasting nuclear energy consumption in China and America: An optimized structure-adaptative grey model," Energy, Elsevier, vol. 239(PA).
    5. D’Ignazio, Alessio & Giovannetti, Emanuele, 2015. "Predicting internet commercial connectivity wars: The impact of trust and operators’ asymmetry," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1127-1137.
    6. Aravantinos, Elias & Petre, Konstantin & Katsianis, Dimitris & Varoutas, Dimitris, 2021. "Determinants of FTTH tariffs evolution in EU: A panel data analysis," Telecommunications Policy, Elsevier, vol. 45(10).
    7. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    8. Mouchart, Michel & Rombouts, Jeroen V.K., 2005. "Clustered panel data models: an efficient approach for nowcasting from poor data," International Journal of Forecasting, Elsevier, vol. 21(3), pages 577-594.
    9. Dalla Valle, Alessandra & Furlan, Claudia, 2014. "Diffusion of nuclear energy in some developing countries," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 143-153.
    10. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    11. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    12. Towhidul Islam & Nigel Meade, 2011. "Detecting the impact of market factors on sales takeoff times of analog cellular telephones," Marketing Letters, Springer, vol. 22(2), pages 197-212, June.
    13. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    14. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    15. Jongsu Lee & Minkyu Lee, 2009. "Analysis on the growth of telecommunication services: a global comparison of diffusion patterns," Applied Economics, Taylor & Francis Journals, vol. 41(24), pages 3143-3150.
    16. Ding, Song & Li, Ruojin & Wu, Shu & Zhou, Weijie, 2021. "Application of a novel structure-adaptative grey model with adjustable time power item for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 298(C).
    17. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2012. "Exploring the determinants of the OSS market potential: The case of the Apache web server," Telecommunications Policy, Elsevier, vol. 36(1), pages 51-68.
    18. Edward Oughton, 2017. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04, Cambridge Judge Business School, University of Cambridge.
    19. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    20. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    21. Ashutosh Jha & Debashis Saha, 2022. "Mobile Broadband for Inclusive Connectivity: What Deters the High-Capacity Deployment of 4G-LTE Innovation in India?," Information Systems Frontiers, Springer, vol. 24(4), pages 1305-1329, August.
    22. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    23. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    24. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    25. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.

  24. Islam, Towhidul & Fiebig, Denzil G, 2001. "Modelling the Development of Supply-Restricted Telecommunications Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(4), pages 249-264, July.

    Cited by:

    1. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    2. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    3. Tarek Ben Rhouma & Georges Zaccour, 2018. "Optimal Marketing Strategies for the Acquisition and Retention of Service Subscriber," Management Science, INFORMS, vol. 64(6), pages 2609-2627, June.
    4. Bo Tan & Zhiguo Zhu & Pan Jiang & Xiening Wang, 2023. "Modeling Multi-Generation Product Diffusion in the Context of Dual-Brand Competition and Sustainable Improvement," Sustainability, MDPI, vol. 15(17), pages 1-22, August.
    5. Dalla Valle, Alessandra & Furlan, Claudia, 2014. "Diffusion of nuclear energy in some developing countries," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 143-153.
    6. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    7. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    8. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    9. Robert Bartels & Towhidul Islam, 2002. "Supply Restricted Telecommunications Markets: The Effect of Technical Efficiency on Waiting Times," Journal of Productivity Analysis, Springer, vol. 18(2), pages 161-169, September.
    10. Abualkhair, Ayman, 2007. "Electricity sector in the Palestinian territories: Which priorities for development and peace?," Energy Policy, Elsevier, vol. 35(4), pages 2209-2230, April.
    11. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    12. Chang, Shuhua & Zhang, Zhaowei & Wang, Xinyu & Dong, Yan, 2020. "Optimal acquisition and retention strategies in a duopoly model of competition," European Journal of Operational Research, Elsevier, vol. 282(2), pages 677-695.
    13. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

  25. Islam, Towhidul & Meade, Nigel, 2000. "Modelling diffusion and replacement," European Journal of Operational Research, Elsevier, vol. 125(3), pages 551-570, September.

    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Franses, Ph.H.B.F. & Hernández-Mireles, C., 2006. "When Should Nintendo Launch its Wii? Insights From a Bivariate Successive Generation Model," ERIM Report Series Research in Management ERS-2006-032-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Kito, Minami, 2021. "Impact of aircraft lifetime change on lifecycle CO2 emissions and costs in Japan," Ecological Economics, Elsevier, vol. 188(C).
    4. Riikonen, Antti & Smura, Timo & Töyli, Juuso, 2016. "The effects of price, popularity, and technological sophistication on mobile handset replacement and unit lifetime," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 313-323.
    5. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    6. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    7. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    8. Chun, Young H., 2012. "Monte Carlo analysis of estimation methods for the prediction of customer response patterns in direct marketing," European Journal of Operational Research, Elsevier, vol. 217(3), pages 673-678.
    9. Higgins, Andrew & Syme, Mike & McGregor, James & Marquez, Leorey & Seo, Seongwon, 2014. "Forecasting uptake of retrofit packages in office building stock under government incentives," Energy Policy, Elsevier, vol. 65(C), pages 501-511.
    10. Hernández-Mireles, C. & Franses, Ph.H.B.F., 2010. "The Launch Timing of New and Dominant Multigeneration Technologies," ERIM Report Series Research in Management ERS-2010-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Kim, T.Y. & Dekker, R. & Heij, C., 2016. "Spare part demand forecasting for consumer goods using installed base information," Econometric Institute Research Papers EI2016-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.

  26. Nigel Meade & Towhidul Islam, 1998. "Technological Forecasting---Model Selection, Model Stability, and Combining Models," Management Science, INFORMS, vol. 44(8), pages 1115-1130, August.

    Cited by:

    1. Hongmin Li & Woonghee Tim Huh, 2012. "Optimal pricing for a short life‐cycle product when customer price‐sensitivity varies over time," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(7), pages 552-576, October.
    2. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
    3. Karakaya, Emrah, 2016. "Finite Element Method for forecasting the diffusion of photovoltaic systems: Why and how?," Applied Energy, Elsevier, vol. 163(C), pages 464-475.
    4. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    5. Madden, Gary & Coble-Neal, Grant & Dalzell, Brian, 2004. "A dynamic model of mobile telephony subscription incorporating a network effect," Telecommunications Policy, Elsevier, vol. 28(2), pages 133-144, March.
    6. Marina V. Evseeva, 2020. "Technological differentiation in the development of the Ural macroregion’s subjects," Journal of New Economy, Ural State University of Economics, vol. 21(3), pages 132-157, October.
    7. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    8. Chang, Suk-Gwon, 2015. "A structured scenario approach to multi-screen ecosystem forecasting in Korean communications market," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 1-20.
    9. Heidary Dahooie, Jalil & Mohammadi, Navid & Daim, Tugrul & Vanaki, Amir Salar & Zavadskas, Edmundas Kazimieras, 2021. "Matching of technological forecasting technique to a technology using fuzzy multi-attribute decision-making methods: Case study from the aerospace industry," Technology in Society, Elsevier, vol. 67(C).
    10. Dewenter, Ralf & Kruse, Jörn, 2010. "Calling party pays or receiving party pays? The diffusion of mobile telephony with endogenous regulation," DICE Discussion Papers 10, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    11. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    12. Fok, Dennis & Franses, Philip Hans, 2007. "Modeling the diffusion of scientific publications," Journal of Econometrics, Elsevier, vol. 139(2), pages 376-390, August.
    13. Sanjay Kumar SINGH & Vijay Lakshmi SINGH, 2023. "Internet diffusion in India: A study based on Growth Curve modelling," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 15(2), pages 29-42, June.
    14. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    15. Yuan, Xiaodong & Cai, Yuchen, 2021. "Forecasting the development trend of low emission vehicle technologies: Based on patent data," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    16. Xiao, Yu & Han, Jingti, 2016. "Forecasting new product diffusion with agent-based models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 167-178.
    17. J Mingers, 2008. "Exploring the dynamics of journal citations: Modelling with s-curves," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1013-1025, August.
    18. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
    19. H Shore & D Benson-Karhi, 2007. "Forecasting S-shaped diffusion processes via response modelling methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 720-728, June.
    20. Mandal, A. & Huang, W.T. & Bhandari, S.K. & Basu, A., 2011. "Goodness-of-fit testing in growth curve models: A general approach based on finite differences," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1086-1098, February.
    21. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    22. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    23. Singh, Sanjay Kumar, 2006. "Future mobility in India: Implications for energy demand and CO2 emission," Transport Policy, Elsevier, vol. 13(5), pages 398-412, September.
    24. Riikonen, Antti & Smura, Timo & Kivi, Antero & Töyli, Juuso, 2013. "Diffusion of mobile handset features: Analysis of turning points and stages," Telecommunications Policy, Elsevier, vol. 37(6), pages 563-572.
    25. J. J. Winnink & Robert J. W. Tijssen, 2015. "Early stage identification of breakthroughs at the interface of science and technology: lessons drawn from a landmark publication," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 113-134, January.
    26. Islam, Towhidul & Fiebig, Denzil G. & Meade, Nigel, 2002. "Modelling multinational telecommunications demand with limited data," International Journal of Forecasting, Elsevier, vol. 18(4), pages 605-624.
    27. S. David Wu & Karl G. Kempf & Mehmet O. Atan & Berrin Aytac & Shamin A. Shirodkar & Asima Mishra, 2010. "Improving New-Product Forecasting at Intel Corporation," Interfaces, INFORMS, vol. 40(5), pages 385-396, October.
    28. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    29. Hong, Jungsik & Koo, Hoonyoung & Kim, Taegu, 2016. "Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS," European Journal of Operational Research, Elsevier, vol. 248(2), pages 681-690.
    30. Apostolos Giovanis & Christos Skiadas, 2007. "A new modeling approach investigating the diffusion speed of mobile telecommunication services in EU-15," Computational Economics, Springer;Society for Computational Economics, vol. 29(2), pages 97-106, March.
    31. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    32. B Aytac & S D Wu, 2011. "Modelling high-tech product life cycles with short-term demand information: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 425-432, March.
    33. Øverby, Harald & Audestad, Jan A. & Szalkowski, Gabriel Andy, 2023. "Compartmental market models in the digital economy—extension of the Bass model to complex economic systems," Telecommunications Policy, Elsevier, vol. 47(1).
    34. Bewley, Ronald & Griffiths, William E., 2003. "The penetration of CDs in the sound recording market: issues in specification, model selection and forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 111-121.
    35. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    36. Guanglu Zhang & Douglas Allaire & Venkatesh Shankar & Daniel A McAdams, 2019. "A case against the trickle-down effect in technology ecosystems," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-7, June.
    37. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    38. Karakaya, Emrah, 2014. "Finite Element Model of the Innovation Diffusion: An Application to Photovoltaic Systems," INDEK Working Paper Series 2014/6, Royal Institute of Technology, Department of Industrial Economics and Management.
    39. Kumar, V. & Nagpal, Anish & Venkatesan, Rajkumar, 2002. "Forecasting category sales and market share for wireless telephone subscribers: a combined approach," International Journal of Forecasting, Elsevier, vol. 18(4), pages 583-603.
    40. Zhang, Guanglu & McAdams, Daniel A. & Shankar, Venkatesh & Darani, Milad Mohammadi, 2017. "Modeling the evolution of system technology performance when component and system technology performances interact: Commensalism and amensalism," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 116-124.
    41. Islam, M.R. & Mekhilef, S. & Saidur, R., 2013. "Progress and recent trends of wind energy technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 456-468.
    42. Ashish Sood & Gareth M. James & Gerard J. Tellis & Ji Zhu, 2012. "Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder," Marketing Science, INFORMS, vol. 31(6), pages 964-979, November.

  27. Meade, Nigel & Islam, Towhidul, 1995. "Forecasting with growth curves: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 11(2), pages 199-215, June.

    Cited by:

    1. Dale Jorgenson & Eric Yip, 2001. "Whatever Happened to Productivity Growth?," NBER Chapters, in: New Developments in Productivity Analysis, pages 509-540, National Bureau of Economic Research, Inc.
    2. Snellman, Jussi & Vesala, Jukka, 1999. "Forecasting the electronification of payments with learning curves: The case of Finland," Bank of Finland Research Discussion Papers 8/1999, Bank of Finland.
    3. Satoh, Daisuke, 2021. "Discrete Gompertz equation and model selection between Gompertz and logistic models," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1192-1211.
    4. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    5. Daniel, Betty C. & Gao, Si, 2015. "Implications of productive government spending for fiscal policy," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 148-175.
    6. David Humphrey & Lawrence Pulley & Jukka Vesala, 2000. "The Check's in the Mail: Why the United States Lags in the Adoption of Cost-Saving Electronic Payments," Journal of Financial Services Research, Springer;Western Finance Association, vol. 17(1), pages 17-39, February.
    7. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    8. To, W.M. & Lai, T.M. & Chung, W.L., 2011. "Fuel life cycle emissions for electricity consumption in the world’s gaming center–Macao SAR, China," Energy, Elsevier, vol. 36(8), pages 5162-5168.
    9. Tseng, Fang-Mei & Wang, Shenq-Yuan & Hsieh, Chih-Hung & Guo, Aifang, 2014. "An integrated model for analyzing the development of the 4G telecommunications market in Taiwan," Telecommunications Policy, Elsevier, vol. 38(1), pages 14-31.
    10. Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
    11. Zeki Murat Çınar & Qasim Zeeshan & Orhan Korhan, 2021. "A Framework for Industry 4.0 Readiness and Maturity of Smart Manufacturing Enterprises: A Case Study," Sustainability, MDPI, vol. 13(12), pages 1-32, June.
    12. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
    13. Nathalia Granja & Pedro Domingues & Mónica Cabecinhas & Dominik Zimon & Paulo Sampaio, 2021. "ISO 22000 Certification: Diffusion in Europe," Resources, MDPI, vol. 10(10), pages 1-16, September.
    14. Huang, Lizhen & Bohne, Rolf André & Lohne, Jardar, 2015. "Shelter and residential building energy consumption within the 450 ppm CO2eq constraints in different climate zones," Energy, Elsevier, vol. 90(P1), pages 965-979.
    15. Sanjay Kumar SINGH & Vijay Lakshmi SINGH, 2023. "Internet diffusion in India: A study based on Growth Curve modelling," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 15(2), pages 29-42, June.
    16. Joost M.E. Pennings & Philip Garcia, 2009. "The informational content of the shape of utility functions: financial strategic behavior," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 83-90.
    17. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    18. Dalla Valle, Alessandra & Furlan, Claudia, 2014. "Diffusion of nuclear energy in some developing countries," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 143-153.
    19. Franklin M. Lartey, 2020. "Predicting Product Uptake Using Bass, Gompertz, and Logistic Diffusion Models: Application to a Broadband Product," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 9(2), pages 1-5, October.
    20. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
    21. Chang, Byeong-Yun & Li, Xu & Kim, Yun Bae, 2014. "Performance comparison of two diffusion models in a saturated mobile phone market," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 41-48.
    22. Mr. Tanai Khiaonarong & David Humphrey, 2019. "Cash Use Across Countries and the Demand for Central Bank Digital Currency," IMF Working Papers 2019/046, International Monetary Fund.
    23. Qian, Lixian & Soopramanien, Didier, 2014. "Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market," Journal of Business Research, Elsevier, vol. 67(6), pages 1226-1232.
    24. Petre, Konstantin & Varoutas, Dimitris, 2022. "On the application of Machine Learning in telecommunications forecasting: A comparison," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265665, International Telecommunications Society (ITS).
    25. Bewley, Ronald, 1997. "The forecast process and academic research," International Journal of Forecasting, Elsevier, vol. 13(4), pages 433-437, December.
    26. Jussi Snellman & Jukka Vesala & David Humphrey, 2001. "Substitution of Noncash Payment Instruments for Cash in Europe," Journal of Financial Services Research, Springer;Western Finance Association, vol. 19(2), pages 131-145, April.
    27. F-M Tseng, 2008. "Quadratic interval innovation diffusion models for new product sales forecasting," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1120-1127, August.
    28. Singh, Sanjay Kumar, 2006. "Future mobility in India: Implications for energy demand and CO2 emission," Transport Policy, Elsevier, vol. 13(5), pages 398-412, September.
    29. Steven M. Shugan, 2007. "—It's the Findings, Stupid, Not the Assumptions," Marketing Science, INFORMS, vol. 26(4), pages 449-459, 07-08.
    30. Singh, Rhythm, 2018. "Energy sufficiency aspirations of India and the role of renewable resources: Scenarios for future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2783-2795.
    31. Islam, Towhidul & Fiebig, Denzil G. & Meade, Nigel, 2002. "Modelling multinational telecommunications demand with limited data," International Journal of Forecasting, Elsevier, vol. 18(4), pages 605-624.
    32. Gardebroek, Cornelis, 2008. "Evaluating Different Growth Scenarios for Organic Farming Using Bayesian Techniques," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44211, European Association of Agricultural Economists.
    33. Humphrey, David & Kaloudis, Aris & Owre, Grete, 2004. "The future of cash: falling legal use and implications for government policy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(3), pages 221-233, July.
    34. Wilko Bolt & David B. Humphrey & Roland Uittenbogaard, 2005. "The effect of transaction pricing on the adoption of electronic payments: a cross-country comparison," Working Papers 05-28, Federal Reserve Bank of Philadelphia.
    35. Jongsu Lee & Minkyu Lee, 2009. "Analysis on the growth of telecommunication services: a global comparison of diffusion patterns," Applied Economics, Taylor & Francis Journals, vol. 41(24), pages 3143-3150.
    36. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    37. Forouzanfar, Mehdi & Doustmohammadi, Ali & Menhaj, M. Bagher & Hasanzadeh, Samira, 2010. "Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran," Applied Energy, Elsevier, vol. 87(1), pages 268-274, January.
    38. Lee, Minkyu & Heshmati, Almas, 2006. "A Dynamic Flexible Partial-Adjustment Model of International Diffusion of the Internet," Ratio Working Papers 99, The Ratio Institute.
    39. Bewley, Ronald & Griffiths, William E., 2003. "The penetration of CDs in the sound recording market: issues in specification, model selection and forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 111-121.
    40. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    41. Xiaoxia Fu & Ping Zhang & Juzhi Zhang, 2017. "Forecasting and Analyzing Internet Users of China with Lotka–Volterra Model," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-18, February.
    42. Ashish Sood & Gareth M. James & Gerard J. Tellis & Ji Zhu, 2012. "Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder," Marketing Science, INFORMS, vol. 31(6), pages 964-979, November.
    43. Wankmüller, Christian & Pulsfort, Johannes & Kunovjanek, Maximilian & Polt, Romana & Craß, Stefan & Reiner, Gerald, 2023. "Blockchain-based tokenization and its impact on plastic bottle supply chains," International Journal of Production Economics, Elsevier, vol. 257(C).
    44. Wooseok Jang & Heeyeul Kwon & Yongtae Park & Hakyeon Lee, 2018. "Predicting the degree of interdisciplinarity in academic fields: the case of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 231-254, July.
    45. Dmitry Kucharavy & Eric Schenk & Roland de Guio, 2009. "Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge," Post-Print halshs-00440438, HAL.

Chapters

  1. Nigel Meade & Towhidul Islam, 2010. "Modeling and Forecasting Diffusion," World Scientific Book Chapters, in: Joe Tidd (ed.), Gaining Momentum Managing the Diffusion of Innovations, chapter 12, pages 373-426, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. S. Mahmuda & T. Sigler & E. Knight & J. Corcoran, 2020. "Sectoral evolution and shifting service delivery models in the sharing economy," Business Research, Springer;German Academic Association for Business Research, vol. 13(2), pages 663-684, July.

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