IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v172y2021ics0040162521004728.html
   My bibliography  Save this article

Innovation, environmental sustainability and economic development: DEA-Bootstrap and multilevel analysis to compare two regions

Author

Listed:
  • Bresciani, Stefano
  • Puertas, Rosa
  • Ferraris, Alberto
  • Santoro, Gabriele

Abstract

Innovation and environmental sustainability are key elements in countries' development and essential to ensure their continuing competitiveness in an increasingly globalised market. Similarly, at the regional level, these elements mark the difference between higher/lower growth; as such, the evaluation of innovation processes is very useful to orient innovation policies towards those regions that need additional strategies to develop potential improvements. This study proposes the use, in the first stage, of DEA-Bootstrap and the Malmquist Index to analyse the innovation efficiency level in Spanish and Italian regions during the period 2004-2012. In the second stage, multilevel regression is used to analyse the relationship between efficiency, environmental sustainability and economic development. The results show great differences between the territories of the two countries analysed, confirming the need to establish differentiated policies that encourage the adoption of innovation practices in regions whose efficiency scores have shown a lack of rigour in the use of their resources, i.e. southern Italian and Spanish regions. Furthermore, we demonstrated that the stringency of environmental policies positively affects innovation efficiency, with a positive relationship identified among development, innovation, and environmental sustainability.

Suggested Citation

  • Bresciani, Stefano & Puertas, Rosa & Ferraris, Alberto & Santoro, Gabriele, 2021. "Innovation, environmental sustainability and economic development: DEA-Bootstrap and multilevel analysis to compare two regions," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004728
    DOI: 10.1016/j.techfore.2021.121040
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521004728
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.121040?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Alberto Marzucchi & Sandro Montresor, 2013. "The Multi-Dimensional Additionality of Innovation Policies: A Multi-Level Application to Italy and Spain," SPRU Working Paper Series 2013-04, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Kekoura Sakouvogui, 2020. "A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1787-1810, May.
    5. Kontolaimou, Alexandra & Giotopoulos, Ioannis & Tsakanikas, Aggelos, 2016. "A typology of European countries based on innovation efficiency and technology gaps: The role of early-stage entrepreneurship," Economic Modelling, Elsevier, vol. 52(PB), pages 477-484.
    6. Arun T. M. & Puneet Kaur & Stefano Bresciani & Amandeep Dhir, 2021. "What drives the adoption and consumption of green hotel products and services? A systematic literature review of past achievement and future promises," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2637-2655, July.
    7. Zhongju Liao & Yan Liu & Mengsha Li, 2020. "Is environmental innovation contagious? A study on the mechanism of individual firms' environmental innovation affecting the industry," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(6), pages 1787-1795, November.
    8. Wang, Ya & Pan, Jiao-feng & Pei, Rui-min & Yi, Bo-Wen & Yang, Guo-liang, 2020. "Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    9. Guan, Jiancheng & Chen, Kaihua, 2012. "Modeling the relative efficiency of national innovation systems," Research Policy, Elsevier, vol. 41(1), pages 102-115.
    10. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    11. Olfat, Laya & Amiri, Maghsoud & Bamdad Soufi, Jahanyar & Pishdar, Mahsa, 2016. "A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 272-290.
    12. Lee, Hyoungsuk & Choi, Yongrok & Seo, Hyungjun, 2020. "Comparative analysis of the R&D investment performance of Korean local governments," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    13. Janger, Jürgen & Schubert, Torben & Andries, Petra & Rammer, Christian & Hoskens, Machteld, 2017. "The EU 2020 innovation indicator: A step forward in measuring innovation outputs and outcomes?," Research Policy, Elsevier, vol. 46(1), pages 30-42.
    14. Herrera, Santiago & Pang, Gaobo, 2005. "Efficiency of public spending in developing countries : an efficiency frontier approach," Policy Research Working Paper Series 3645, The World Bank.
    15. Yu, Anyu & Shi, Yu & You, Jianxin & Zhu, Joe, 2021. "Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 292(1), pages 199-212.
    16. Tan, Xiujie & Choi, Yongrok & Wang, Banban & Huang, Xiaoqi, 2020. "Does China's carbon regulatory policy improve total factor carbon efficiency? A fixed-effect panel stochastic frontier analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    17. Hille, Erik & Althammer, Wilhelm & Diederich, Henning, 2020. "Environmental regulation and innovation in renewable energy technologies: Does the policy instrument matter?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    18. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    19. Alexander Berman & Alba Marino & Ram Mudambi, 2020. "The global connectivity of regional innovation systems in Italy: a core–periphery perspective," Regional Studies, Taylor & Francis Journals, vol. 54(5), pages 677-691, May.
    20. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    21. Enrico Botta & Tomasz Koźluk, 2014. "Measuring Environmental Policy Stringency in OECD Countries: A Composite Index Approach," OECD Economics Department Working Papers 1177, OECD Publishing.
    22. Hauser, Christoph & Siller, Matthias & Schatzer, Thomas & Walde, Janette & Tappeiner, Gottfried, 2018. "Measuring regional innovation: A critical inspection of the ability of single indicators to shape technological change," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 43-55.
    23. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    24. Karen Palmer & Wallace E. Oates & Paul R. Portney & Karen Palmer & Wallace E. Oates & Paul R. Portney, 2004. "Tightening Environmental Standards: The Benefit-Cost or the No-Cost Paradigm?," Chapters, in: Environmental Policy and Fiscal Federalism, chapter 3, pages 53-66, Edward Elgar Publishing.
    25. Jon Mikel Zabala-Iturriagagoitia & Fernando Jiménez-Sáez & Elena Castro-Martínez & Antonio Gutiérrez-Gracia, 2007. "What indicators do (or do not) tell us about Regional Innovation Systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 85-106, January.
    26. Thijs ten Raa & William H. Greene (ed.), 2019. "The Palgrave Handbook of Economic Performance Analysis," Springer Books, Springer, number 978-3-030-23727-1, November.
    27. Kiani Mavi, Reza & Kiani Mavi, Neda, 2021. "National eco-innovation analysis with big data: A common-weights model for dynamic DEA," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    28. Munshi Naser Ibne Afzal, 2014. "An empirical investigation of the National Innovation System (NIS) using Data Envelopment Analysis (DEA) and the TOBIT model," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(4), pages 507-523, July.
    29. Erik Hille & Patrick Möbius, 2019. "Environmental Policy, Innovation, and Productivity Growth: Controlling the Effects of Regulation and Endogeneity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1315-1355, August.
    30. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Does innovation respond to climate change? Empirical evidence from patents and greenhouse gas emissions," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 49-62.
    31. Silva, Thiago Christiano & Tabak, Benjamin Miranda & Cajueiro, Daniel Oliveira & Dias, Marina Villas Boas, 2017. "A comparison of DEA and SFA using micro- and macro-level perspectives: Efficiency of Chinese local banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 216-223.
    32. Martínez-Zarzoso, Inmaculada & Bengochea-Morancho, Aurelia & Morales-Lage, Rafael, 2019. "Does environmental policy stringency foster innovation and productivity in OECD countries?," Energy Policy, Elsevier, vol. 134(C).
    33. Ferreira, João J.M. & Fernandes, Cristina I. & Ferreira, Fernando A.F., 2020. "Technology transfer, climate change mitigation, and environmental patent impact on sustainability and economic growth: A comparison of European countries," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    34. Juying Zeng & Domingo Ribeiro-Soriano & Jun Ren, 2021. "Innovation efficiency: a bibliometric review and future research agenda," Asia Pacific Business Review, Taylor & Francis Journals, vol. 27(2), pages 209-228, March.
    35. Baumann, Julian & Kritikos, Alexander S., 2016. "The link between R&D, innovation and productivity: Are micro firms different?," Research Policy, Elsevier, vol. 45(6), pages 1263-1274.
    36. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    37. Andreas Schibany & Gerhard Streicher, 2008. "The European Innovation Scoreboard: drowning by numbers?," Science and Public Policy, Oxford University Press, vol. 35(10), pages 717-732, December.
    38. Yang, Zhenbing & Shao, Shuai & Li, Chengyu & Yang, Lili, 2020. "Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    39. Jaeho Shin & Changhee Kim & Hongsuk Yang, 2018. "The Effect of Sustainability as Innovation Objectives on Innovation Efficiency," Sustainability, MDPI, vol. 10(6), pages 1-13, June.
    40. Brown, Rayna, 2006. "Mismanagement or mismeasurement? Pitfalls and protocols for DEA studies in the financial services sector," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1100-1116, October.
    41. Fu, Xiaolan & Mohnen, Pierre & Zanello, Giacomo, 2018. "Innovation and productivity in formal and informal firms in Ghana," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 315-325.
    42. Roberta Capello & Camilla Lenzi, 2013. "Territorial patterns of innovation: a taxonomy of innovative regions in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(1), pages 119-154, August.
    43. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    44. Christoph Hauser & Gottfried Tappeiner & Janette Walde, 2007. "The Learning Region: The Impact of Social Capital and Weak Ties on Innovation," Regional Studies, Taylor & Francis Journals, vol. 41(1), pages 75-88.
    45. 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.
    46. Namazi, Mehdi & Mohammadi, Emran, 2018. "Natural resource dependence and economic growth: A TOPSIS/DEA analysis of innovation efficiency," Resources Policy, Elsevier, vol. 59(C), pages 544-552.
    47. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    48. Huangxin Chen & Hang Lin & Wenjie Zou, 2020. "Research on the Regional Differences and Influencing Factors of the Innovation Efficiency of China’s High-Tech Industries: Based on a Shared Inputs Two-Stage Network DEA," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
    49. Peng Xu & Fan Luo & Ziyue Zhang & Hongyi Xu, 2020. "Research on Innovation Efficiency of Listed Companies in Development Zone Based on the Three-Stage DEA-Tobit Model: A Case Study of Hubei Province," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, July.
    50. Glyptis, Loukas & Christofi, Michael & Vrontis, Demetris & Giudice, Manlio Del & Dimitriou, Salomi & Michael, Panayiota, 2020. "E-Government implementation challenges in small countries: The project manager's perspective," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    51. Di Cagno, Daniela & Fabrizi, Andrea & Meliciani, Valentina & Wanzenböck, Iris, 2016. "The impact of relational spillovers from joint research projects on knowledge creation across European regions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 83-94.
    52. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    53. Min, Sujin & Kim, Juseong & Sawng, Yeong-Wha, 2020. "The effect of innovation network size and public R&D investment on regional innovation efficiency," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    54. Nichola J. Lowe & Laura Wolf-Powers, 2018. "Who works in a working region? Inclusive innovation in the new manufacturing economy," Regional Studies, Taylor & Francis Journals, vol. 52(6), pages 828-839, June.
    55. Hugo Pinto, 2009. "The Diversity of Innovation in the European Union: Mapping Latent Dimensions and Regional Profiles," European Planning Studies, Taylor & Francis Journals, vol. 17(2), pages 303-326, February.
    56. Pegkas, Panagiotis & Staikouras, Christos & Tsamadias, Constantinos, 2019. "Does research and development expenditure impact innovation? Evidence from the European Union countries," Journal of Policy Modeling, Elsevier, vol. 41(5), pages 1005-1025.
    57. Albrizio, Silvia & Kozluk, Tomasz & Zipperer, Vera, 2017. "Environmental policies and productivity growth: Evidence across industries and firms," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 209-226.
    58. Yu, Liping & Duan, Yunlong & Fan, Tianting, 2020. "Innovation performance of new products in China's high-technology industry," International Journal of Production Economics, Elsevier, vol. 219(C), pages 204-215.
    59. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    60. Jianqing Zhang & Song Wang & Peilei Yang & Fei Fan & Xueli Wang, 2020. "Analysis of Scale Factors on China’s Sustainable Development Efficiency Based on Three-Stage DEA and a Double Threshold Test," Sustainability, MDPI, vol. 12(6), pages 1-26, March.
    61. Jiancheng Guan & Kaihua Chen, 2010. "Modeling macro-R&D production frontier performance: an application to Chinese province-level R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 165-173, January.
    62. Abdelaziz Hakimi & Roula Inglesi-Lotz, 2020. "Examining the differences in the impact of climate change on innovation between developed and developing countries: evidence from a panel system GMM analysis," Applied Economics, Taylor & Francis Journals, vol. 52(22), pages 2353-2365, May.
    63. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    64. John Bryden & Stig S. Gezelius, 2017. "Innovation as if people mattered: the ethics of innovation for sustainable development," Innovation and Development, Taylor & Francis Journals, vol. 7(1), pages 101-118, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nadia Yusuf & Miltiadis D. Lytras, 2023. "Competitive Sustainability of Saudi Companies through Digitalization and the Circular Carbon Economy Model: A Bold Contribution to the Vision 2030 Agenda in Saudi Arabia," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    2. Ahmad, Najid & Youjin, Liu & Žiković, Saša & Belyaeva, Zhanna, 2023. "The effects of technological innovation on sustainable development and environmental degradation: Evidence from China," Technology in Society, Elsevier, vol. 72(C).
    3. Puertas, Rosa & Guaita-Martinez, José M. & Carracedo, Patricia & Ribeiro-Soriano, Domingo, 2022. "Analysis of European environmental policies: Improving decision making through eco-efficiency," Technology in Society, Elsevier, vol. 70(C).
    4. Chen, Hao, 2022. "Industrial production evaluation with the consideration of technology accumulation," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 72-84.
    5. Xin Nie & Jianxian Wu & Han Wang & Lihua Li & Chengdao Huang & Weijuan Li & Zhuxia Wei, 2022. "Booster or Stumbling Block? The Role of Environmental Regulation in the Coupling Path of Regional Innovation under the Porter Hypothesis," Sustainability, MDPI, vol. 14(5), pages 1-20, March.
    6. Puertas, Rosa & Carracedo, Patricia & Garcia−Mollá, Marta & Vega, Virginia, 2022. "Analysis of the determinants of market capitalisation: Innovation, climate change policies and business context," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    7. Santos-Arteaga, Francisco J. & Di Caprio, Debora & Tavana, Madjid, 2023. "A combinatorial data envelopment analysis with uncertain interval data with application to ICT evaluation," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Jiang, Zihao & Liu, Zhiying, 2022. "Policies and exploitative and exploratory innovations of the wind power industry in China: The role of technological path dependence," Technological Forecasting and Social Change, Elsevier, vol. 177(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Puertas, Rosa & Marti, Luisa & Guaita-Martinez, José M., 2020. "Innovation, lifestyle, policy and socioeconomic factors: An analysis of European quality of life," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    2. Xiangyu Guo & Canhui Deng & Dan Wang & Xu Du & Jiali Li & Bowen Wan, 2021. "International Comparison of the Efficiency of Agricultural Science, Technology, and Innovation: A Case Study of G20 Countries," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    3. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    4. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    5. Wang, Qian & Ren, Shuming, 2022. "Evaluation of green technology innovation efficiency in a regional context: A dynamic network slacks-based measuring approach," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    6. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
    7. Zhang, Dan & Zheng, Mingbo & Feng, Gen-Fu & Chang, Chun-Ping, 2022. "Does an environmental policy bring to green innovation in renewable energy?," Renewable Energy, Elsevier, vol. 195(C), pages 1113-1124.
    8. Prokop, Viktor & Hajek, Petr & Stejskal, Jan, 2021. "Configuration Paths to Efficient National Innovation Ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    9. Chen Kaihua & Kou Mingting, 2014. "Staged efficiency and its determinants of regional innovation systems: a two-step analytical procedure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 627-657, March.
    10. Hauser, Christoph & Siller, Matthias & Schatzer, Thomas & Walde, Janette & Tappeiner, Gottfried, 2018. "Measuring regional innovation: A critical inspection of the ability of single indicators to shape technological change," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 43-55.
    11. Siran Fang & Xiaoshan Xue & Ge Yin & Hong Fang & Jialin Li & Yongnian Zhang, 2020. "Evaluation and Improvement of Technological Innovation Efficiency of New Energy Vehicle Enterprises in China Based on DEA-Tobit Model," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    12. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    13. Jaeho Shin & Changhee Kim & Hongsuk Yang, 2019. "Does Reduction of Material and Energy Consumption Affect to Innovation Efficiency? The Case of Manufacturing Industry in South Korea," Energies, MDPI, vol. 12(6), pages 1-14, March.
    14. Barbero, Javier & Zabala-Iturriagagoitia, Jon Mikel & Zofío, José L., 2021. "Is more always better? On the relevance of decreasing returns to scale on innovation," Technovation, Elsevier, vol. 107(C).
    15. Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    16. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    17. Svetlana V. Ratner & Svetlana A. Balashova & Andrey V. Lychev, 2022. "The Efficiency of National Innovation Systems in Post-Soviet Countries: DEA-Based Approach," Mathematics, MDPI, vol. 10(19), pages 1-23, October.
    18. Puertas, Rosa & Carracedo, Patricia & Garcia−Mollá, Marta & Vega, Virginia, 2022. "Analysis of the determinants of market capitalisation: Innovation, climate change policies and business context," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    19. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    20. Irena Lacka & Lukasz Brzezicki, 2021. "The Efficiency and Productivity Evaluation of National Innovation Systems in Europe," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 471-496.

    More about this item

    Keywords

    Innovation; Development; Sustainability; DEA; Multilevel regression;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004728. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.