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An introduction to the application of (case 1) best–worst scaling in marketing research

Citations

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  1. Tiganis, Antonios & Chrysochou, Polymeros & Mitkidis, Panagiotis & Krystallis, Athanasios, 2025. "Social order or social justice? The relationship of political ideology with consumer preferences for Corporate Social Responsibility," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
  2. Anastasio J. Villanueva & Melania Salazar‐Ordóñez & Rubén Granado‐Díaz, 2025. "Consumer preferences toward new circular bioeconomy agri‐food products," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(2), pages 2614-2633, April.
  3. Davis, Katrina J & Burton, Michael & Kragt, Marit E, "undated". "Discrete choice models: scale heterogeneity and why it matters," Working Papers 235373, University of Western Australia, School of Agricultural and Resource Economics.
  4. 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.
  5. 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.
  6. Joshua Benjamin Schramm & Marcel Lichters, 2025. "Incentive alignment in anchored MaxDiff yields superior predictive validity," Marketing Letters, Springer, vol. 36(1), pages 1-16, March.
  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. Zander, Kerstin K., 2020. "Unrealised opportunities for residential solar panels in Australia," Energy Policy, Elsevier, vol. 142(C).
  9. 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.
  10. Hammerle, Mara & White, Lee V. & Sturmberg, Bjorn, 2023. "Solar for renters: Investigating investor perspectives of barriers and policies," Energy Policy, Elsevier, vol. 174(C).
  11. 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.
  12. Marco A. Palma, 2017. "Improving the prediction of ranking data," Empirical Economics, Springer, vol. 53(4), pages 1681-1710, December.
  13. White, Mark H., 2021. "bwsTools: An R package for case 1 best-worst scaling," Journal of choice modelling, Elsevier, vol. 39(C).
  14. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
  15. 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.
  16. 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).
  17. Huang, Wenli & Pan, Xiaofeng & Peng, You & Lu, Yuan, 2024. "Senior tourists’ acceptance for tourism-related mobile apps: An integrated model based on BWS case 1 and ordered choice data," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
  18. 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.
  19. 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.
  20. 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.
  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. Jinhua Li & Fang Zhang & Shiwei Sun, 2019. "Building Consumer-Oriented CSR Differentiation Strategy," Sustainability, MDPI, vol. 11(3), pages 1-14, January.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. David A. Hensher & Chinh Ho, 2016. "Identifying a behaviourally relevant choice set from stated choice data," Transportation, Springer, vol. 43(2), pages 197-217, March.
  29. Lipovetsky, Stan & Conklin, Michael, 2014. "Best-Worst Scaling in analytical closed-form solution," Journal of choice modelling, Elsevier, vol. 10(C), pages 60-68.
  30. 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.
  31. 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.
  32. Lipovetsky, Stan & Conklin, Michael, 2014. "Finding items cannibalization and synergy by BWS data," Journal of choice modelling, Elsevier, vol. 12(C), pages 1-9.
  33. 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.
  34. 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.
  35. 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.
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