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Investigating causal relationships of factors influencing eco-innovation capability: an integrated approach of regression analysis and DEMATEL

Yıl 2025, Cilt: 40 Sayı: 3, 2013 - 2028, 21.08.2025
https://doi.org/10.17341/gazimmfd.1563324
https://izlik.org/JA74PR79PM

Öz

Today, in line with the increasing environmental awareness and sustainability demands, eco-innovation has become a critical element that provides both competitive advantage and supports long-term success for manufacturing companies. The eco-innovation capabilities of companies are developed and shaped under the influence of various internal factors, from organizational culture to strategic orientations. In this context, this study aims to determine the internal factors affecting the eco-innovation capabilities of manufacturing companies and to analyze the complex causal relationships between these factors in detail. For this purpose, firstly, a total of 12 factors affecting eco-innovation capabilities were identified through a systematic literature review and interviews with experts. In the study, an innovative approach in which regression analysis and the DEMATEL method were integrated was employed to investigate the relationships between the factors. This approach significantly reduces the evaluation burden of experts, especially in studies involving a high number of factors, and provides an effective solution in determining the direct effects of factors on each other by combining expert opinions. As a result of the analyses, strategic management capability, technological innovation capability and R&D capability were revealed as the most critical factors that have a driving force on other factors, respectively. In addition, it was found that organizational management capability, learning capability and process/production capability factors are among the core factors. The findings obtained from this study provide a comprehensive guide for the development of applicable strategies to improve the eco-innovation capabilities of manufacturing companies and achieve sustainability goals.

Etik Beyan

The authors declare that there is no conflict of interest with any individual or institution during the conduct and publication of this study.

Kaynakça

  • 1. Doran, J., Ryan, G., The importance of the diverse drivers and types of environmental innovation for firm performance, Business Strategy and the Environment, 25 (2), 102-119, 2016.
  • 2. Arranz, N., Arroyabe M.F., Agustin M, Arroyabe, J.C.F., Incentives and inhibiting factors of eco-innovation in the Spanish firms, J. Cleaner Prod., 220, 1-28, 2019.
  • 3. Benkraiem R., Dubocage E., Lelong Y., Shuwaikh, F., The effects of environmental performance and green innovation on corporate venture capital, Ecological Economics, 210, 1-57, 2023.
  • 4. Rodríguez-Rebés, L, Ibar-Alonso, R., Gomez, L.M.R., Navío-Marco, J., The use and drivers of organizational eco-innovation in European SMEs, Research in International Business and Finance, 70, 1-18, 2024.
  • 5. Salim, N., Ab Rahman, M.N., Abd Wahab, D., A systematic literature review of internal capabilities for enhancing eco-innovation performance of manufacturing firms, Journal of Cleaner Production, 209, 1445-1460, 2019.
  • 6. Xie, X., Huo, J., Qi, G., Zhu, K.X., Green process innovation and financial performance in emerging economies: Moderating effects of absorptive capacity and green subsidies, IEEE Transactions on Engineering Management, 67 (3), 760-772, 2019.
  • 7. Testa, F., Annunziata, E., Iraldo, F., Frey, M., Drawbacks and opportunities of green public procurement: an effective tool for sustainable production, Journal of Cleaner Production, 216, 144-152, 2019.
  • 8. Borghesi, S., Cainelli, G., Mazzanti, M., Linking emission trading to environmental innovation: Evidence from the Italian manufacturing industry, Research Policy, 44 (3), 669-683, 2015.
  • 9. Rennings, K., Redefining innovation-eco-innovation research and the contribution from ecological economics, Ecological Economics, 32 (2), 319-332, 2000.
  • 10. Roostaie, S., Nawari, N., The DEMATEL approach for integrating resilience indicators into building sustainability assessment frameworks, Building and Environment, 207, 108113, 2022.
  • 11. Kabra, G., Mukerjee, H.S., Analyzing barriers to design thinking adoption within organizations: a DEMATEL approach. International Journal of Productivity and Performance Management, 2024.
  • 12. Chen, J., Cheng J., Dai, S., Regional eco-innovation in China: An analysis of eco-innovation levels and influencing factors, Journal of Cleaner Production, 153, 1-14, 2017.
  • 13. Cai, W., Zhou, X., On the drivers of eco-innovation: empirical evidence from China, Journal of Cleaner Production, 79 (15), 2014.
  • 14. Mady, K, Halim M., Omar, K., Environmental pressures and eco-innovation in manufacturing SMEs: the mediating effect of environmental capabilities, International Journal of Innovation Studies, 16 (3), 501-526, 2024.
  • 15. Shahin, A., Imanipour N, Shahin, A., Wood, L., C., An integrative approach for structuring and prioritizing eco-innovation determinants with a survey in knowledge-based companies, Journal of Manufacturing Technology Management, 31 (4), 799, 824, 2020.
  • 16. Horbach, J., Determinants of environmental innovation—New evidence from German panel data sources, Research Policy, 37(1), 163-173, 2008.
  • 17. Peyravi, B., Jakubavičius, A., Drivers in the Eco-Innovation Road to the Circular Economy: Organizational Capabilities and Exploitative Strategies, Sustainability, 14(17), 10748, 2022.
  • 18. Qalati, S.A., Barbosa, B., Ibrahim, B., Factors influencing employees’ eco-friendly innovation capabilities and behavior: the role of green culture and employees’ motivations, Environment, Development and Sustainability, 10, 1-22, 2023.
  • 19. Al Halbusi, H., Klobas, J.E., Ramayah, T. Green core competence and firm performance in a post‐conflict country, Iraq. Business Strategy and the Environment, 1-13, 2023.
  • 20. Albort-Morant, G., Leal-Millan, A., Cepeda-Carrion G., The antecedents of green innovation performance: A model of learning and capabilities, Journal of Business Research, 69 (11), 4912-4917, 2016.
  • 21. Pham D.D.T., Paille, P., Halilem, N., Systematic review on environmental innovativeness: A knowledge-based resource view, Journal of Cleaner Production 211, 1088-1099, 2019.
  • 22. Qu, X., Khan, A., Yahya, S., Zafar, A.U., Shahzad, M., Green core competencies to prompt green absorptive capacity and bolster green innovation: the moderating role of organization’s green culture. Journal of Environmental Planning and Management, 65 (3), 536-561, 2022.
  • 23. El-Kassar A., Singh S.K., Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices, Technological Forecasting and Social Change, 144, 483-498, 2019.
  • 24. Passaro, R., Quinto, I., Scandurra, G., Thomas, A., The drivers of eco-innovations in small and medium-sized enterprises: A systematic literature review and research directions, Business Strategy and the Environment, 32 (4), 1432-1450, 2023.
  • 25. Srisathan, W.A., Ketkaew, C., Phonthanukitithaworn, C., Naruetharadhol, P., Driving policy support for open eco-innovation enterprises in Thailand: A probit regression model, Journal of Open Innovation: Technology, Market and Complexity, 9 (3), 2023.
  • 26. Bittencourt, B.A., Galuk, M.B., Daniel, V.M., Zen, A.C., Cluster Innovation Capability: A Systematic review, International Journal of Innovation, 7 (1), 26-44, 2018.
  • 27. Vasconcelos-Garcia, M, Carrilho-Nunes, I., Internationalisation and digitalisation as drivers for eco-innovation in the European Union, Structural Change and Economic Dynamics 70, 245-256, 2024.
  • 28. Pichlak, M., The drivers of technological eco-innovation-Dynamic capabilities and leadership, Sustainability, 13 (10), 5354, 2021.
  • 29. Özgül, B., KOBİ’lerde yeşil süreç inovasyonunu teşvik etmek için yeşil dönüşümcü liderliğin ve yeşil temel yeteneklerin etkilerinin incelenmesi, Business & Management Studies: An International Journal, 11 (1), 48-65, 2023.
  • 30. Akman, G., Boyacı, A.İ., Evaluating the Challenges Encountered in the White Goods Industry in the Adaptation Process to Industry 4.0 via a Hybrid MCDM Model, Politeknik Dergisi, 27 (3), 1197-1212, 2024.
  • 31. Wu, W.W., Lan, L.W., Lee, Y.T., Exploring decisive factors affecting an organization's SaaS adoption: A case study, International Journal of Information Management, 31 (6), 556-563, 2011.
  • 32. Braga, I.F., Ferreira, F.A., Ferreira, J.J., Correia, R.J., Pereira, L.F., Falcão, P.F., A DEMATEL analysis of smart city determinants, Technology in Society, 66, 101687, 2021.
  • 33. Akman, G., Yörür, B., Boyacı, A.I., Chiu, M.C., Assessing innovation capabilities of manufacturing companies by combination of unsupervised and supervised machine learning approaches, Applied Soft Computing, 147, 110735, 2023.
  • 34. Del Río, P., Peñasco, C., Romero-Jordán, D., What drives eco-innovators? A critical review of the empirical literature based on econometric methods, Journal of Cleaner Production, 112, 2158-2170, 2016.
  • 35. Hojnik, J., Ruzzier, M., What drives eco-innovation? A review of an emerging literature, Environmental Innovation and Societal Transitions, 19, 31-41, 2016.
  • 36. Zhang, Y., Sun, J., Yang, Z., Li, S., Organizational Learning and Green Innovation: Does Environmental Proactivity Matter?, Sustainability, 10 (10), 3737, 2018.
  • 37. Sadiq, I.Z., Usman, A., Muhammad, A., Ahmad, K.H., Sample Size Calculation in Biomedical, Clinical and Biological Sciences Research. Journal of Umm Al-Qura University for Applied Sciences, 2024.
  • 38. Şanlı, S., Sampling Methods and Appropriate Sample Size Determination: A Concise Overview, Pamukkale University Journal of Social Sciences Institute, 56, 357-375. 2023.
  • 39. Singh, A.S., Masuku, M.B., Sampling Techniques & Determination of Sample Size in Applied Statistics Research: An Overview, International Journal of Economics, Commerce, and Management, 2 (11), 1-22, 2014.
  • 40. Datlıca, M.T., Çakıt, E., Estimation of clustering parameters and anomaly detection in tracking devices with changeable position time, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (1), 373-394, 2021.
  • 41. Boyacı, A.İ., Baynal, K., Optimisation of elastomeric bearings’ vulcanisation process using response surface methodology and desirability function approach, Journal of Rubber Research, 22 (4), 187-193, 2019.
  • 42. Göğen, E., Güney, S., Machine learning-based weather prediction with radiosonde observations, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (4), 2317-2328, 2024.
  • 43. Akyüz, B., Karatay, S., Erken, F., Comparison of the Performance of the Regression Models in GPS-Total Electron Content Prediction, Politeknik Dergisi, 26 (1), 321-328, 2023.
  • 44. Yurtcu, Ş., Özocak, A., Prediction of compression index of fine-grained soils using statistical and artificial intelligence methods, Journal of the Faculty of Engineering and Architecture of Gazi University, 31 (3), 597-608, 2016.
  • 45. Adıyaman, O., Regression Modeling of the effect of chip slenderness ratio and cutting parameters on vibration, Gazi University Journal of Science Part C: Design and Technology, 9 (4), 661-678, 2021.
  • 46. Cardoso, R.A., Oliveira, G.A.B., Almeida, G.M.J., Araújo, J.A., A simple linear regression strategy for fretting fatigue life estimates, Tribology International, 109852, 2024.
  • 47. Maulud, D., Abdulazeez, A.M., A review on linear regression comprehensive in machine learning, Journal of Applied Science and Technology Trends, 1 (2), 140-147, 2020.
  • 48. Yardımcı, R., Boğar, E., A trend-residual decomposition-based modeling approach for Türkiye's total healthcare expenditure forecasting, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (4), 2539-2550, 2024.
  • 49. Akbulut, U., Çifçi, M.A., İşler, B., Aslan, Z., Comparison of different machine learning techniques in river flow prediction, Journal of the Faculty of Engineering and Architecture of Gazi University, 40 (1), 467-486, 2024. 50. Montgomery, D.C., Peck, E.A., Vining, G.G., Introduction to Linear Regression Analysis, John Wiley & Sons, New York, A.B.D., 2012.
  • 51. Prodanova, H., Nedkov, S., Petrov, G., GIS-based modeling of landscape patterns in mountain areas using climate indices and regression analysis, Environmental Modelling & Software, 180, 106160, 2024.
  • 52. Yılmaz, A., Prediction of base and subbase resilient modulus (Mr) using regression methodology, Journal of the Faculty of Engineering and Architecture of Gazi University, 35 (1), 507-517, 2020.
  • 53. Akman, G., Boyacı, A.İ., Kurnaz, S., Selecting the suitable e-commerce marketplace with neutrosophic Fuzzy AHP and EDAS methods from seller's perspective in the context of Covid-19, International Journal of the Analytic Hierarchy Process, 14 (3), 2022.
  • 54. Kumar, R., Singh, R.K., Dwivedi, Y.K., Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges, Journal of Cleaner Production, 275, 124063, 2020.
  • 55. Si, S.L., You, X.Y., Liu, H.C., Zhang, P., DEMATEL technique: a systematic review of the state‐of‐the‐art literature on methodologies and applications, Mathematical Problems in Engineering, 1, 3696457, 2018.
  • 56. Klewitz, J., Hansen, E.G., Sustainability-oriented innovation of SMEs: A systematic review, Journal of Cleaner Production, 65, 57-75, 2014.
  • 57. Dangelico, R.M., Pujari, D., Mainstreaming green product innovation: Why and how companies integrate environmental sustainability, Journal of Business Ethics, 95 (3), 471-486, 2010.
  • 58. Zheng, L., Iatridis, K., Friends or foes? A systematic literature review and meta-analysis of the relationship between eco-innovation and firm performance, Business Strategy and the Environment, 31 (4), 1838-1855, 2022.

Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım

Yıl 2025, Cilt: 40 Sayı: 3, 2013 - 2028, 21.08.2025
https://doi.org/10.17341/gazimmfd.1563324
https://izlik.org/JA74PR79PM

Öz

Günümüzde artan çevresel bilinç ve sürdürülebilirlik talepleri doğrultusunda, eko-inovasyon (Eİ), üretim firmaları için hem rekabet avantajı sağlayan hem de uzun vadeli başarıyı destekleyen kritik bir unsur haline gelmiştir. Firmaların Eİ yetenekleri, organizasyonel kültürden stratejik yönelimlere kadar çeşitli içsel faktörlerin etkisi altında gelişmekte ve şekillenmektedir. Bu bağlamda bu çalışmada üretim firmaların Eİ yeteneklerini etkileyen içsel faktörlerin belirlenmesi ve bu faktörler arasındaki karmaşık nedensellik ilişkilerinin detaylı bir şekilde analiz edilmesi amaçlanmaktadır. Bu amaçla öncelikle sistematik bir literatür taraması ve uzmanlarla yapılan görüşmeler sonucunda Eİ yeteneğini etkileyen toplamda 12 faktör tanımlanmıştır. Çalışmada faktörler arasındaki ilişkilerin araştırılması amacıyla Regresyon analizi ve DEMATEL yönteminin entegre edildiği yenilikçi bir yaklaşım kullanılmıştır. Bu yaklaşım özellikle yüksek sayıda faktör içeren çalışmalarda uzmanların değerlendirme yükünü önemli ölçüde azaltmakta ve uzman görüşlerinin birleştirilerek faktörlerin birbirleri üzerindeki doğrudan etkilerinin belirlenmesinde etkili bir çözüm sunmaktadır. Analizler sonucunda sırasıyla stratejik yönetim yeteneği, teknolojik yenilik yeteneği ve Ar-Ge yeteneği diğer faktörler üzerinde itici gücü olan en kritik faktörler olarak elde edilmiştir. Ek olarak örgütsel yönetim yeteneği, öğrenme yeteneği ve proses/üretim yeteneği faktörlerinin de çekirdek faktörler arasında olduğu anlaşılmaktadır. Bu çalışmadan elde edilen bulgular, üretim firmalarının Eİ süreçlerini iyileştirmek ve sürdürülebilirlik hedeflerine ulaşmak için uygulanabilir stratejilerin geliştirilmesinde kapsamlı bir rehber niteliği taşımaktadır.

Etik Beyan

Yazarlar, bu çalışmanın yürütülmesi ve yayımlanması sürecinde herhangi bir kişi ya da kurumla çıkar çatışması içerisinde olmadığını beyan eder.

Kaynakça

  • 1. Doran, J., Ryan, G., The importance of the diverse drivers and types of environmental innovation for firm performance, Business Strategy and the Environment, 25 (2), 102-119, 2016.
  • 2. Arranz, N., Arroyabe M.F., Agustin M, Arroyabe, J.C.F., Incentives and inhibiting factors of eco-innovation in the Spanish firms, J. Cleaner Prod., 220, 1-28, 2019.
  • 3. Benkraiem R., Dubocage E., Lelong Y., Shuwaikh, F., The effects of environmental performance and green innovation on corporate venture capital, Ecological Economics, 210, 1-57, 2023.
  • 4. Rodríguez-Rebés, L, Ibar-Alonso, R., Gomez, L.M.R., Navío-Marco, J., The use and drivers of organizational eco-innovation in European SMEs, Research in International Business and Finance, 70, 1-18, 2024.
  • 5. Salim, N., Ab Rahman, M.N., Abd Wahab, D., A systematic literature review of internal capabilities for enhancing eco-innovation performance of manufacturing firms, Journal of Cleaner Production, 209, 1445-1460, 2019.
  • 6. Xie, X., Huo, J., Qi, G., Zhu, K.X., Green process innovation and financial performance in emerging economies: Moderating effects of absorptive capacity and green subsidies, IEEE Transactions on Engineering Management, 67 (3), 760-772, 2019.
  • 7. Testa, F., Annunziata, E., Iraldo, F., Frey, M., Drawbacks and opportunities of green public procurement: an effective tool for sustainable production, Journal of Cleaner Production, 216, 144-152, 2019.
  • 8. Borghesi, S., Cainelli, G., Mazzanti, M., Linking emission trading to environmental innovation: Evidence from the Italian manufacturing industry, Research Policy, 44 (3), 669-683, 2015.
  • 9. Rennings, K., Redefining innovation-eco-innovation research and the contribution from ecological economics, Ecological Economics, 32 (2), 319-332, 2000.
  • 10. Roostaie, S., Nawari, N., The DEMATEL approach for integrating resilience indicators into building sustainability assessment frameworks, Building and Environment, 207, 108113, 2022.
  • 11. Kabra, G., Mukerjee, H.S., Analyzing barriers to design thinking adoption within organizations: a DEMATEL approach. International Journal of Productivity and Performance Management, 2024.
  • 12. Chen, J., Cheng J., Dai, S., Regional eco-innovation in China: An analysis of eco-innovation levels and influencing factors, Journal of Cleaner Production, 153, 1-14, 2017.
  • 13. Cai, W., Zhou, X., On the drivers of eco-innovation: empirical evidence from China, Journal of Cleaner Production, 79 (15), 2014.
  • 14. Mady, K, Halim M., Omar, K., Environmental pressures and eco-innovation in manufacturing SMEs: the mediating effect of environmental capabilities, International Journal of Innovation Studies, 16 (3), 501-526, 2024.
  • 15. Shahin, A., Imanipour N, Shahin, A., Wood, L., C., An integrative approach for structuring and prioritizing eco-innovation determinants with a survey in knowledge-based companies, Journal of Manufacturing Technology Management, 31 (4), 799, 824, 2020.
  • 16. Horbach, J., Determinants of environmental innovation—New evidence from German panel data sources, Research Policy, 37(1), 163-173, 2008.
  • 17. Peyravi, B., Jakubavičius, A., Drivers in the Eco-Innovation Road to the Circular Economy: Organizational Capabilities and Exploitative Strategies, Sustainability, 14(17), 10748, 2022.
  • 18. Qalati, S.A., Barbosa, B., Ibrahim, B., Factors influencing employees’ eco-friendly innovation capabilities and behavior: the role of green culture and employees’ motivations, Environment, Development and Sustainability, 10, 1-22, 2023.
  • 19. Al Halbusi, H., Klobas, J.E., Ramayah, T. Green core competence and firm performance in a post‐conflict country, Iraq. Business Strategy and the Environment, 1-13, 2023.
  • 20. Albort-Morant, G., Leal-Millan, A., Cepeda-Carrion G., The antecedents of green innovation performance: A model of learning and capabilities, Journal of Business Research, 69 (11), 4912-4917, 2016.
  • 21. Pham D.D.T., Paille, P., Halilem, N., Systematic review on environmental innovativeness: A knowledge-based resource view, Journal of Cleaner Production 211, 1088-1099, 2019.
  • 22. Qu, X., Khan, A., Yahya, S., Zafar, A.U., Shahzad, M., Green core competencies to prompt green absorptive capacity and bolster green innovation: the moderating role of organization’s green culture. Journal of Environmental Planning and Management, 65 (3), 536-561, 2022.
  • 23. El-Kassar A., Singh S.K., Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices, Technological Forecasting and Social Change, 144, 483-498, 2019.
  • 24. Passaro, R., Quinto, I., Scandurra, G., Thomas, A., The drivers of eco-innovations in small and medium-sized enterprises: A systematic literature review and research directions, Business Strategy and the Environment, 32 (4), 1432-1450, 2023.
  • 25. Srisathan, W.A., Ketkaew, C., Phonthanukitithaworn, C., Naruetharadhol, P., Driving policy support for open eco-innovation enterprises in Thailand: A probit regression model, Journal of Open Innovation: Technology, Market and Complexity, 9 (3), 2023.
  • 26. Bittencourt, B.A., Galuk, M.B., Daniel, V.M., Zen, A.C., Cluster Innovation Capability: A Systematic review, International Journal of Innovation, 7 (1), 26-44, 2018.
  • 27. Vasconcelos-Garcia, M, Carrilho-Nunes, I., Internationalisation and digitalisation as drivers for eco-innovation in the European Union, Structural Change and Economic Dynamics 70, 245-256, 2024.
  • 28. Pichlak, M., The drivers of technological eco-innovation-Dynamic capabilities and leadership, Sustainability, 13 (10), 5354, 2021.
  • 29. Özgül, B., KOBİ’lerde yeşil süreç inovasyonunu teşvik etmek için yeşil dönüşümcü liderliğin ve yeşil temel yeteneklerin etkilerinin incelenmesi, Business & Management Studies: An International Journal, 11 (1), 48-65, 2023.
  • 30. Akman, G., Boyacı, A.İ., Evaluating the Challenges Encountered in the White Goods Industry in the Adaptation Process to Industry 4.0 via a Hybrid MCDM Model, Politeknik Dergisi, 27 (3), 1197-1212, 2024.
  • 31. Wu, W.W., Lan, L.W., Lee, Y.T., Exploring decisive factors affecting an organization's SaaS adoption: A case study, International Journal of Information Management, 31 (6), 556-563, 2011.
  • 32. Braga, I.F., Ferreira, F.A., Ferreira, J.J., Correia, R.J., Pereira, L.F., Falcão, P.F., A DEMATEL analysis of smart city determinants, Technology in Society, 66, 101687, 2021.
  • 33. Akman, G., Yörür, B., Boyacı, A.I., Chiu, M.C., Assessing innovation capabilities of manufacturing companies by combination of unsupervised and supervised machine learning approaches, Applied Soft Computing, 147, 110735, 2023.
  • 34. Del Río, P., Peñasco, C., Romero-Jordán, D., What drives eco-innovators? A critical review of the empirical literature based on econometric methods, Journal of Cleaner Production, 112, 2158-2170, 2016.
  • 35. Hojnik, J., Ruzzier, M., What drives eco-innovation? A review of an emerging literature, Environmental Innovation and Societal Transitions, 19, 31-41, 2016.
  • 36. Zhang, Y., Sun, J., Yang, Z., Li, S., Organizational Learning and Green Innovation: Does Environmental Proactivity Matter?, Sustainability, 10 (10), 3737, 2018.
  • 37. Sadiq, I.Z., Usman, A., Muhammad, A., Ahmad, K.H., Sample Size Calculation in Biomedical, Clinical and Biological Sciences Research. Journal of Umm Al-Qura University for Applied Sciences, 2024.
  • 38. Şanlı, S., Sampling Methods and Appropriate Sample Size Determination: A Concise Overview, Pamukkale University Journal of Social Sciences Institute, 56, 357-375. 2023.
  • 39. Singh, A.S., Masuku, M.B., Sampling Techniques & Determination of Sample Size in Applied Statistics Research: An Overview, International Journal of Economics, Commerce, and Management, 2 (11), 1-22, 2014.
  • 40. Datlıca, M.T., Çakıt, E., Estimation of clustering parameters and anomaly detection in tracking devices with changeable position time, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (1), 373-394, 2021.
  • 41. Boyacı, A.İ., Baynal, K., Optimisation of elastomeric bearings’ vulcanisation process using response surface methodology and desirability function approach, Journal of Rubber Research, 22 (4), 187-193, 2019.
  • 42. Göğen, E., Güney, S., Machine learning-based weather prediction with radiosonde observations, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (4), 2317-2328, 2024.
  • 43. Akyüz, B., Karatay, S., Erken, F., Comparison of the Performance of the Regression Models in GPS-Total Electron Content Prediction, Politeknik Dergisi, 26 (1), 321-328, 2023.
  • 44. Yurtcu, Ş., Özocak, A., Prediction of compression index of fine-grained soils using statistical and artificial intelligence methods, Journal of the Faculty of Engineering and Architecture of Gazi University, 31 (3), 597-608, 2016.
  • 45. Adıyaman, O., Regression Modeling of the effect of chip slenderness ratio and cutting parameters on vibration, Gazi University Journal of Science Part C: Design and Technology, 9 (4), 661-678, 2021.
  • 46. Cardoso, R.A., Oliveira, G.A.B., Almeida, G.M.J., Araújo, J.A., A simple linear regression strategy for fretting fatigue life estimates, Tribology International, 109852, 2024.
  • 47. Maulud, D., Abdulazeez, A.M., A review on linear regression comprehensive in machine learning, Journal of Applied Science and Technology Trends, 1 (2), 140-147, 2020.
  • 48. Yardımcı, R., Boğar, E., A trend-residual decomposition-based modeling approach for Türkiye's total healthcare expenditure forecasting, Journal of the Faculty of Engineering and Architecture of Gazi University, 39 (4), 2539-2550, 2024.
  • 49. Akbulut, U., Çifçi, M.A., İşler, B., Aslan, Z., Comparison of different machine learning techniques in river flow prediction, Journal of the Faculty of Engineering and Architecture of Gazi University, 40 (1), 467-486, 2024. 50. Montgomery, D.C., Peck, E.A., Vining, G.G., Introduction to Linear Regression Analysis, John Wiley & Sons, New York, A.B.D., 2012.
  • 51. Prodanova, H., Nedkov, S., Petrov, G., GIS-based modeling of landscape patterns in mountain areas using climate indices and regression analysis, Environmental Modelling & Software, 180, 106160, 2024.
  • 52. Yılmaz, A., Prediction of base and subbase resilient modulus (Mr) using regression methodology, Journal of the Faculty of Engineering and Architecture of Gazi University, 35 (1), 507-517, 2020.
  • 53. Akman, G., Boyacı, A.İ., Kurnaz, S., Selecting the suitable e-commerce marketplace with neutrosophic Fuzzy AHP and EDAS methods from seller's perspective in the context of Covid-19, International Journal of the Analytic Hierarchy Process, 14 (3), 2022.
  • 54. Kumar, R., Singh, R.K., Dwivedi, Y.K., Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges, Journal of Cleaner Production, 275, 124063, 2020.
  • 55. Si, S.L., You, X.Y., Liu, H.C., Zhang, P., DEMATEL technique: a systematic review of the state‐of‐the‐art literature on methodologies and applications, Mathematical Problems in Engineering, 1, 3696457, 2018.
  • 56. Klewitz, J., Hansen, E.G., Sustainability-oriented innovation of SMEs: A systematic review, Journal of Cleaner Production, 65, 57-75, 2014.
  • 57. Dangelico, R.M., Pujari, D., Mainstreaming green product innovation: Why and how companies integrate environmental sustainability, Journal of Business Ethics, 95 (3), 471-486, 2010.
  • 58. Zheng, L., Iatridis, K., Friends or foes? A systematic literature review and meta-analysis of the relationship between eco-innovation and firm performance, Business Strategy and the Environment, 31 (4), 1838-1855, 2022.
Toplam 57 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Endüstri Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Ali İhsan Boyacı 0000-0003-3656-6164

Gulsen Akman 0000-0002-5696-2423

Çağın Karabıçak 0000-0002-6520-7374

Gönderilme Tarihi 8 Ekim 2024
Kabul Tarihi 8 Mart 2025
Erken Görünüm Tarihi 8 Ağustos 2025
Yayımlanma Tarihi 21 Ağustos 2025
DOI https://doi.org/10.17341/gazimmfd.1563324
IZ https://izlik.org/JA74PR79PM
Yayımlandığı Sayı Yıl 2025 Cilt: 40 Sayı: 3

Kaynak Göster

APA Boyacı, A. İ., Akman, G., & Karabıçak, Ç. (2025). Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 40(3), 2013-2028. https://doi.org/10.17341/gazimmfd.1563324
AMA 1.Boyacı Aİ, Akman G, Karabıçak Ç. Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım. GUMMFD. 2025;40(3):2013-2028. doi:10.17341/gazimmfd.1563324
Chicago Boyacı, Ali İhsan, Gulsen Akman, ve Çağın Karabıçak. 2025. “Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40 (3): 2013-28. https://doi.org/10.17341/gazimmfd.1563324.
EndNote Boyacı Aİ, Akman G, Karabıçak Ç (01 Ağustos 2025) Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40 3 2013–2028.
IEEE [1]A. İ. Boyacı, G. Akman, ve Ç. Karabıçak, “Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım”, GUMMFD, c. 40, sy 3, ss. 2013–2028, Ağu. 2025, doi: 10.17341/gazimmfd.1563324.
ISNAD Boyacı, Ali İhsan - Akman, Gulsen - Karabıçak, Çağın. “Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 40/3 (01 Ağustos 2025): 2013-2028. https://doi.org/10.17341/gazimmfd.1563324.
JAMA 1.Boyacı Aİ, Akman G, Karabıçak Ç. Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım. GUMMFD. 2025;40:2013–2028.
MLA Boyacı, Ali İhsan, vd. “Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 40, sy 3, Ağustos 2025, ss. 2013-28, doi:10.17341/gazimmfd.1563324.
Vancouver 1.Ali İhsan Boyacı, Gulsen Akman, Çağın Karabıçak. Eko-inovasyon yeteneğini etkileyen faktörlerin nedensellik ilişkilerinin araştırılması: Regresyon analizi ve DEMATEL tabanlı entegre bir yaklaşım. GUMMFD. 01 Ağustos 2025;40(3):2013-28. doi:10.17341/gazimmfd.1563324