How to cite this paper
Chienwattanasook, K., Tancho, N., Onputtha, S., Boonrattanakittibhumi, C., Sriyakul, T & Waiyawuththanapoom, P. (2022). The role of industry 4.0 in supply chain sustainability: Evidence from the rubber industry.Uncertain Supply Chain Management, 10(4), 1243-1252.
Refrences
Arunachalam, D., Kumar, N., & Kawalek, J. (2018). Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice. Transportation Research Part E: Logistics and Transportation Review, 114, 416-436.
Aydin, D., & Şenoğlu, B. (2018). Estimating the Missing Value in One-Way ANOVA Under Long-Tailed Symmetric Error Distributions. Sigma: Journal of Engineering & Natural Sciences, 36(2), 523-538.
Baykasoğlu, A., Subulan, K., Güçdemir, H., Dudaklı, N., & Eren Akyol, D. (2020). Revenue management for make-to-order manufacturing systems with a real-life application. The Engineering Economist, 65(1), 27-65.
Bowling, A., Bond, M., Jenkinson, C., & Lamping, D. (1999). Short Form 36 (SF-36) Health Survey questionnaire: which normative data should be used? Comparisons between the norms provided by the Omnibus Survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey. Journal of Public Health, 21(3), 255-270.
Chanchaichujit, J., Saavedra-Rosas, J., & Kaur, A. (2017). Analysing the impact of restructuring transportation, production and distribution on costs and environment–a case from the Thai Rubber industry. International Journal of Logistics Research and Applications, 20(3), 237-253.
Chienwattanasook, K., & Onputtha, S. (2022). The Impact of Inspirational Leadership on Green Supply Chain Management and Organizational Performance of Food and Beverage Companies. Asian Administration and Management Review, 5(1), 29-40.
Chin, W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Chinachoti, P. (2018). The Readiness of Human Resource Management for Industrial Business Sector towards Industrial 4.0 in Thailand. Asian Administration and Management Review, 1(2), 123-131.
Crawford, J., Gasparis, A., Almeida, J., Elias, S., Wakefield, T., Lal, B. Osborne, N., Amery, S., & Labropoulos, N. (2019). A review of United States endovenous ablation practice trends from the Medicare Data Utilization and Payment Database. Journal of Vascular Surgery: Venous and Lymphatic Disorders, 7(4), 471-479.
De, D., Chowdhury, S., Dey, P., & Ghosh, S. (2020). Impact of lean and sustainability oriented innovation on sustainability performance of small and medium sized enterprises: a data envelopment analysis-based framework. International Journal of Production Economics, 219, 416-430.
Dey, P., Malesios, C., De, D., Chowdhury, S., & Abdelaziz, F. (2019). Could lean practices and process innovation enhance supply chain sustainability of small and medium‐sized enterprises?. Business Strategy and the Environment, 28(4), 582-598.
Dubey, R., Gunasekaran, A., Childe, S., Luo, Z., Wamba, S., Roubaud, D., & Foropon, C. (2018). Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour. Journal of Cleaner Production, 196, 1508-1521.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 18(3), 382-388.
Hair, J., Hollingsworth, C., Randolph, A., & Chong, A. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
Hair, J., Sarstedt, M., Pieper, T., & Ringle, C. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long range planning, 45(5-6), 320-340.
Hair Jr, J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
Haseeb, M., Hussain, H., Slusarczyk, B., & Jermsittiparsert, K. (2019). Industry 4.0: A Solution towards Technology Challenges of Sustainable Business Performance. Social Sciences, 8(5), 184.
Hameed, W., Nadeem, S., Azeem, M., Aljumah, A., & Adeyemi, R. (2018). Determinants of E-Logistic Customer Satisfaction: A Mediating Role of Information and Communication Technology (ICT). International Journal of Supply Chain Management, 7(1), 105-111.
Henseler, J., & Chin, W. (2010). A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling. Structural Equation Modeling, 17(1), 82-109.
Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing,” in New challenges to international marketing (pp. 277-319), Bingley: Emerald Group Publishing Limited.
Iqbal, J., & Kousar, S. (2018). Antecedents of Sustainable Social Entrepreneurship Initiatives in Pakistan and Outcomes: Collaboration between Quadruple Helix Sectors. Sustainability, 10(12), 4539.
Jermsittiparsert, K., & Boonratanakittiphumi, C. (2019). The Supply Chain Management, Enterprise Resource Planning Systems and the Organisational Performance of Thai Manufacturing Firms: Does the Application of Industry 4.0 Matter?. International Journal of Innovation, Creativity and Change, 8(8), 82-102.
Jiang, P., Hong, C., & Agrawal, G. (2020). A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. Paper presented at the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, California, USA.
Jittimanee, U. (2014). The Supply Chain Management of Khaotangkwa Pomeloin Chainat. Journal of Interdisciplinary Research: Graduate Studies, 3(1), 68-88.
Kaur, A., Patil, G., Shirk, S., & Taillie, C. (1996). Environmental sampling with a concomitant variable: a comparison between ranked set sampling and stratified simple random sampling. Journal of applied statistics, 23(2-3), 231-256.
Khamhaeng, S., Kotikul, K., Jinachan, K., Morasin, C., & Phonsongkram, P. (2015). The Study of the Development Process for the Logistics Ability and the Supply Chain of the Nutmeg Products, Nakhonsithammarat. Journal of Interdisciplinary Research: Graduate Studies, 4(2), 20-26.
Kusworo, T., Aryanti, N., Utomo, D., & Nurmala, E. (2020). Performance Evaluation of PES-ZnO nanohybrid using a combination of UV Irradiation and Cross-linking for Wastewater Treatment of the Rubber Industry to Clean Water. Journal of Membrane Science and Research, 7(1), 4-13.
Lim, M., Tseng, M., Tan, K., & Bui, T. (2017). Knowledge management in sustainable supply chain management: Improving performance through an interpretive structural modelling approach. Journal of Cleaner Production, 162, 806-816.
Liu, Y., Peng, J., & Yu, Z. (2018). Big Data Platform Architecture under the Background of Financial Technology: In the Insurance Industry as an Example. Paper presented at the 2018 International Conference on Big Data Engineering and Technology, Chengdu, China.
Malyavkina, L., Savina, A., & Parshutina, I. (2019). Blockchain technology as the basis for digital transformation of the supply chain management system: benefits and implementation challenges. Paper presented at the 1st International Scientific Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth”, Ekaterinburg, Russia.
Marimin, M., Wibisono, A., & Darmawan, M. (2017). Decision support system for natural rubber supply chain management performance measurement: a sustainable balanced scorecard approach. International Journal of Supply Chain Management, 6(2), 60-74.
Mastos, T., Nizamis, A., Vafeiadis, T., Alexopoulos, N., Ntinas, C., Gkortzis, D., Papadopoulos, A., Ioannidis, D., & Tzovaras, D. (2020). Industry 4.0 sustainable supply chains: An application of an IoT enabled scrap metal management solution. Journal of Cleaner Production, 269, 122377.
Preacher, K., & Hayes, A. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, instruments, & computers, 36(4), 717-731.
Preacher, K., & Hayes, A. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
Qiao, H., Chao, M., Hui, D., Liu, J., Zheng, J., Lei, W., Zhou, X., Wang, R., & Zhang, L. (2017). Enhanced interfacial interaction and excellent performance of silica/epoxy group-functionalized styrene-butadiene rubber (SBR) nanocomposites without any coupling agent. Composites Part B: Engineering, 114, 356-364.
Roy, V., Schoenherr, T., & Charan, P. (2020). Toward an organizational understanding of the transformation needed for sustainable supply chain management: The concepts of force-field and differential efforts. Journal of purchasing and supply management, 26(3), 100612.
Sirisuwat, P., & Jindabot, T. (2012). The Rubber Export Industry in Thailand: An Analysis of Export Performance. PSAKU International Journal of Interdisciplinary Research, 1(1), 195-202.
Sukriket, P., Sriyakul, T., Jermsittiparsert, K., & Chienwattanasook, K. (2022). Food Supply Chain Quality Management Practices Impact on Quality Safety Performance in Thailand. International Journal of eBusiness and eGovernment Studies, 14(1), 134-149.
Tongkum, S., & Sasananan, M. (2014). Supply Chain of Organic Vegetables: A Case Study of Food Safety Program in Hospital. Journal of Interdisciplinary Research: Graduate Studies, 3(2), 23-34.
Tortorella, G., Vergara, A., Garza-Reyes, J., & Sawhney, R. (2020). Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers. International Journal of Production Economics, 219, 284-294.
Ul-Hameed, W., Mohammad, H., & Shahar, H. (2018). Microfinance institute’s non-financial services and women-empowerment: The role of vulnerability. Management Science Letters, 8(10), 1103-1116.
Waiyawuththanapoom, P., Thammaboosadee, S., Tirastittam, P., Jermsittiparsert, K., Wongsanguan, C., Sirikamonsin, P., & Aunyawong, W. (2022). The role of human resource management and supply chain process in sustainable business performance. Uncertain Supply Chain Management, 10(2), 517-526. DOI: 10.5267/j.uscm.2021.11.011.
Xu, T., Li, H., Zhang, H., & Zhang, X. (2019). Improve Data Utilization with Two-stage Learning in CNN-LSTM-based Voice Activity Detection. Paper presented at the 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Lanzhou, China.
Zhong, R., Newman, S., Huang, G., & Lan, S. (2016). Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives. Computers & Industrial Engineering, 101, 572-591.
Aydin, D., & Şenoğlu, B. (2018). Estimating the Missing Value in One-Way ANOVA Under Long-Tailed Symmetric Error Distributions. Sigma: Journal of Engineering & Natural Sciences, 36(2), 523-538.
Baykasoğlu, A., Subulan, K., Güçdemir, H., Dudaklı, N., & Eren Akyol, D. (2020). Revenue management for make-to-order manufacturing systems with a real-life application. The Engineering Economist, 65(1), 27-65.
Bowling, A., Bond, M., Jenkinson, C., & Lamping, D. (1999). Short Form 36 (SF-36) Health Survey questionnaire: which normative data should be used? Comparisons between the norms provided by the Omnibus Survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey. Journal of Public Health, 21(3), 255-270.
Chanchaichujit, J., Saavedra-Rosas, J., & Kaur, A. (2017). Analysing the impact of restructuring transportation, production and distribution on costs and environment–a case from the Thai Rubber industry. International Journal of Logistics Research and Applications, 20(3), 237-253.
Chienwattanasook, K., & Onputtha, S. (2022). The Impact of Inspirational Leadership on Green Supply Chain Management and Organizational Performance of Food and Beverage Companies. Asian Administration and Management Review, 5(1), 29-40.
Chin, W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Chinachoti, P. (2018). The Readiness of Human Resource Management for Industrial Business Sector towards Industrial 4.0 in Thailand. Asian Administration and Management Review, 1(2), 123-131.
Crawford, J., Gasparis, A., Almeida, J., Elias, S., Wakefield, T., Lal, B. Osborne, N., Amery, S., & Labropoulos, N. (2019). A review of United States endovenous ablation practice trends from the Medicare Data Utilization and Payment Database. Journal of Vascular Surgery: Venous and Lymphatic Disorders, 7(4), 471-479.
De, D., Chowdhury, S., Dey, P., & Ghosh, S. (2020). Impact of lean and sustainability oriented innovation on sustainability performance of small and medium sized enterprises: a data envelopment analysis-based framework. International Journal of Production Economics, 219, 416-430.
Dey, P., Malesios, C., De, D., Chowdhury, S., & Abdelaziz, F. (2019). Could lean practices and process innovation enhance supply chain sustainability of small and medium‐sized enterprises?. Business Strategy and the Environment, 28(4), 582-598.
Dubey, R., Gunasekaran, A., Childe, S., Luo, Z., Wamba, S., Roubaud, D., & Foropon, C. (2018). Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour. Journal of Cleaner Production, 196, 1508-1521.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 18(3), 382-388.
Hair, J., Hollingsworth, C., Randolph, A., & Chong, A. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
Hair, J., Sarstedt, M., Pieper, T., & Ringle, C. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long range planning, 45(5-6), 320-340.
Hair Jr, J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
Haseeb, M., Hussain, H., Slusarczyk, B., & Jermsittiparsert, K. (2019). Industry 4.0: A Solution towards Technology Challenges of Sustainable Business Performance. Social Sciences, 8(5), 184.
Hameed, W., Nadeem, S., Azeem, M., Aljumah, A., & Adeyemi, R. (2018). Determinants of E-Logistic Customer Satisfaction: A Mediating Role of Information and Communication Technology (ICT). International Journal of Supply Chain Management, 7(1), 105-111.
Henseler, J., & Chin, W. (2010). A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling. Structural Equation Modeling, 17(1), 82-109.
Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing,” in New challenges to international marketing (pp. 277-319), Bingley: Emerald Group Publishing Limited.
Iqbal, J., & Kousar, S. (2018). Antecedents of Sustainable Social Entrepreneurship Initiatives in Pakistan and Outcomes: Collaboration between Quadruple Helix Sectors. Sustainability, 10(12), 4539.
Jermsittiparsert, K., & Boonratanakittiphumi, C. (2019). The Supply Chain Management, Enterprise Resource Planning Systems and the Organisational Performance of Thai Manufacturing Firms: Does the Application of Industry 4.0 Matter?. International Journal of Innovation, Creativity and Change, 8(8), 82-102.
Jiang, P., Hong, C., & Agrawal, G. (2020). A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. Paper presented at the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, California, USA.
Jittimanee, U. (2014). The Supply Chain Management of Khaotangkwa Pomeloin Chainat. Journal of Interdisciplinary Research: Graduate Studies, 3(1), 68-88.
Kaur, A., Patil, G., Shirk, S., & Taillie, C. (1996). Environmental sampling with a concomitant variable: a comparison between ranked set sampling and stratified simple random sampling. Journal of applied statistics, 23(2-3), 231-256.
Khamhaeng, S., Kotikul, K., Jinachan, K., Morasin, C., & Phonsongkram, P. (2015). The Study of the Development Process for the Logistics Ability and the Supply Chain of the Nutmeg Products, Nakhonsithammarat. Journal of Interdisciplinary Research: Graduate Studies, 4(2), 20-26.
Kusworo, T., Aryanti, N., Utomo, D., & Nurmala, E. (2020). Performance Evaluation of PES-ZnO nanohybrid using a combination of UV Irradiation and Cross-linking for Wastewater Treatment of the Rubber Industry to Clean Water. Journal of Membrane Science and Research, 7(1), 4-13.
Lim, M., Tseng, M., Tan, K., & Bui, T. (2017). Knowledge management in sustainable supply chain management: Improving performance through an interpretive structural modelling approach. Journal of Cleaner Production, 162, 806-816.
Liu, Y., Peng, J., & Yu, Z. (2018). Big Data Platform Architecture under the Background of Financial Technology: In the Insurance Industry as an Example. Paper presented at the 2018 International Conference on Big Data Engineering and Technology, Chengdu, China.
Malyavkina, L., Savina, A., & Parshutina, I. (2019). Blockchain technology as the basis for digital transformation of the supply chain management system: benefits and implementation challenges. Paper presented at the 1st International Scientific Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth”, Ekaterinburg, Russia.
Marimin, M., Wibisono, A., & Darmawan, M. (2017). Decision support system for natural rubber supply chain management performance measurement: a sustainable balanced scorecard approach. International Journal of Supply Chain Management, 6(2), 60-74.
Mastos, T., Nizamis, A., Vafeiadis, T., Alexopoulos, N., Ntinas, C., Gkortzis, D., Papadopoulos, A., Ioannidis, D., & Tzovaras, D. (2020). Industry 4.0 sustainable supply chains: An application of an IoT enabled scrap metal management solution. Journal of Cleaner Production, 269, 122377.
Preacher, K., & Hayes, A. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, instruments, & computers, 36(4), 717-731.
Preacher, K., & Hayes, A. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
Qiao, H., Chao, M., Hui, D., Liu, J., Zheng, J., Lei, W., Zhou, X., Wang, R., & Zhang, L. (2017). Enhanced interfacial interaction and excellent performance of silica/epoxy group-functionalized styrene-butadiene rubber (SBR) nanocomposites without any coupling agent. Composites Part B: Engineering, 114, 356-364.
Roy, V., Schoenherr, T., & Charan, P. (2020). Toward an organizational understanding of the transformation needed for sustainable supply chain management: The concepts of force-field and differential efforts. Journal of purchasing and supply management, 26(3), 100612.
Sirisuwat, P., & Jindabot, T. (2012). The Rubber Export Industry in Thailand: An Analysis of Export Performance. PSAKU International Journal of Interdisciplinary Research, 1(1), 195-202.
Sukriket, P., Sriyakul, T., Jermsittiparsert, K., & Chienwattanasook, K. (2022). Food Supply Chain Quality Management Practices Impact on Quality Safety Performance in Thailand. International Journal of eBusiness and eGovernment Studies, 14(1), 134-149.
Tongkum, S., & Sasananan, M. (2014). Supply Chain of Organic Vegetables: A Case Study of Food Safety Program in Hospital. Journal of Interdisciplinary Research: Graduate Studies, 3(2), 23-34.
Tortorella, G., Vergara, A., Garza-Reyes, J., & Sawhney, R. (2020). Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers. International Journal of Production Economics, 219, 284-294.
Ul-Hameed, W., Mohammad, H., & Shahar, H. (2018). Microfinance institute’s non-financial services and women-empowerment: The role of vulnerability. Management Science Letters, 8(10), 1103-1116.
Waiyawuththanapoom, P., Thammaboosadee, S., Tirastittam, P., Jermsittiparsert, K., Wongsanguan, C., Sirikamonsin, P., & Aunyawong, W. (2022). The role of human resource management and supply chain process in sustainable business performance. Uncertain Supply Chain Management, 10(2), 517-526. DOI: 10.5267/j.uscm.2021.11.011.
Xu, T., Li, H., Zhang, H., & Zhang, X. (2019). Improve Data Utilization with Two-stage Learning in CNN-LSTM-based Voice Activity Detection. Paper presented at the 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Lanzhou, China.
Zhong, R., Newman, S., Huang, G., & Lan, S. (2016). Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives. Computers & Industrial Engineering, 101, 572-591.