How to cite this paper
Chatchawanchanchanakij, P., Jermsittiparsert, K., Chankoson, T & Waiyawuththanapoom, P. (2023). The role of industry 4.0 in sustainable supply chain: Evidence from the textile industry.Uncertain Supply Chain Management, 11(1), 1-10.
Refrences
Albassami, A. M., Hameed, W. U., Naveed, R. T., & Moshfegyan, M. (2019). Does Knowledge Management Expedite SMEs Performance through Organizational Innovation? An Empirical Evidence from Small and Medium-sized enterprises (SMEs). Pacific Business Review International, 12(1), 11-22.
Asch, M., Moore, T., Badia, R., Beck, M., Beckman, P., Bidot, T., Bodin, F., Cappello, F., Choudhary, A., de Supinski, B., Deelman, E., Dongarra, J., Dubey, A., Fox, G., Fu, H., Girona, S., Gropp, W., Heroux, M., Ishikawa, Y., Keahey, K., Keyes, D., Kramer, W., Lavignon, J., Lu, Y., Matsuoka, S., Mohr, B., Reed, D., Requena, S., Saltz, J., Schulthess, T., Stevens, R., Swany, M., Szalay, A., Tang, W., Varoquaux, G., Vilotte, J., Wisniewski, R., Xu, Z., & Zacharov, I. (2018). Big data and extreme-scale computing: Pathways to convergence-toward a shaping strategy for a future software and data ecosystem for scientific inquiry. The International Journal of High Performance Computing Applications, 32(4), 435-479.
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.
Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 Perspective. International journal of mechanical, industrial science and engineering, 8(1), 37-44.
Dal Corso, L., De Carlo, A., Carluccio, F., Girardi, D., & Falco, A. (2019). An Opportunity to Grow or a Label? Performance Appraisal Justice and Performance Appraisal Satisfaction to Increase Teachers' Well-Being. Frontiers in psychology, 10, 2361-2361.
Dolgui, A., Ivanov, D., Sethi, S. P., & Sokolov, B. (2019). Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications. International journal of production research, 57(2), 411-432.
Fernández-Caramés, T. M., Blanco-Novoa, O., Froiz-Míguez, I., & Fraga-Lamas, P. (2019). Towards an autonomous industry 4.0 warehouse: A UAV and blockchain-based system for inventory and traceability applications in big data-driven supply chain management. Sensors, 19(10), 2394.
Fernando, Y., Jabbour, C. J. C., & Wah, W.-X. (2019). Pursuing green growth in technology firms through the connections between environmental innovation and sustainable business performance: Does service capability matter? Resources, Conservation and Recycling, 141, 8-20.
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.
Guazzi, M., Adams, V., Conraads, V., Halle, M., Mezzani, A., Vanhees, L., Arena, R., Fletcher, G., Forman, D., Kitzman, D., Lavie, C., & Myers, J. (2012). EACPR/AHA Scientific Statement. Clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. Circulation, 126(18), 2261-2274.
Guazzi, M., Arena, R., Halle, M., Piepoli, M. F., Myers, J., & Lavie, C. J. (2018). 2016 focused update: clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. European heart journal, 39(14), 1144-1161.
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., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. doi: https://ssrn.com/abstract=2233795
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., Hult, G., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM), California: Sage Publications, 2016.
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.
Hameed, W. U., Basheer, M. F., Iqbal, J., Anwar, A., & Ahmad, H. K. (2018). Determinants of Firm’s open innovation performance and the role of R & D department: an empirical evidence from Malaysian SME’s. Journal of Global Entrepreneurship Research, 8(1), 29. doi:https://doi.org/10.1186/s40497-018-0112-8
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. DOI: 10.3390/socsci8050154.
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., & Fassott, G. (2010). Testing moderating effects in PLS path models: An illustration of available procedures Handbook of partial least squares (pp. 713-735): Springer.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. in New challenges to international marketing, Bingley: Emerald Group Publishing Limited, pp. 277-319.
Jeble, S., Dubey, R., Childe, S. J., Papadopoulos, T., Roubaud, D., & Prakash, A. (2018). Impact of big data and predictive analytics capability on supply chain sustainability. The International Journal of Logistics Management, 29(2), 513-538.
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.
Jermsittiparsert, K., Kraimak, S., & Boonratanakittiphumi, C. (2019). Does the Industry 4.0 Have Any Impact on the Relationship between Agile Strategic Supply Chain and the Supply Chain Partners Performance. International Journal of Innovation, Creativity and Change, 8(8), 122-141.
Jubaedah, J., Yulivan, I., & Hadi, A. R. A. (2016). The Influence of Financial Performance, Capital Structure and Macroeconomic Factors on Firm’s Value–Evidence from Textile Companies at Indonesia Stock Exchange. Applied Finance and Accounting, 2(2), 18-29.
Li, Z., Guo, H., Barenji, A. V., Wang, W. M., Guan, Y., & Huang, G. Q. (2020). A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network. International Journal of Production Research, 58(24), 7399-7419.
Maghsoodi, A. I., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(1), 2.
Mason, C., & Harrison, R. (2004). Does investing in technology-based firms involve higher risk? An exploratory study of the performance of technology and non-technology investments by business angels. Venture Capital: An international journal of entrepreneurial finance, 6(4), 313-332.
Moktadir, M. A., Ali, S. M., Kusi-Sarpong, S., & Shaikh, M. A. A. (2018). Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process Safety and Environmental Protection, 117, 730-741.
Mosallaeipour, S., Shavarani, S. M., Steens, C., & Eros, A. (2019). A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era. Journal of Corporate Real Estate.
Naveed, R. T., Hameed, W. U., Albassami, A. M., & Moshfegyan, M. (2019). Online Tax System (OTS) in Pakistan: The role of Tax Service Quality (TSQ) and Information Communication Technology (ICT). Pacific Business Review International, 11(12), 78-86.
Pacaiova, H., Turisova, R., Nagyova, A., & Oravec, M. (2020). Safety Management in Accordance with Industry 4.0 Requirements: Analysis and Evaluation of the Level of Digitalization in the Slovak Companies. Paper presented at the International Conference on Applied Human Factors and Ergonomics.
Prasetyani, D., Abidin, A. Z., Purusa, N. A., & Sandra, F. A. (2020). The Prospects and The Competitiveness of Textile Commodities and Indonesian Textile Product in the Global Market. ETIKONOMI, 19(1), 1-18.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
Räisänen, P., Hedman, L., Andersson, M., Stridsman, C., Lindberg, A., Lundbäck, B., Rönmark, E., & Backman, H. (2020). Non-response did not affect prevalence estimates of asthma and respiratory symptoms-results from a postal questionnaire survey of the general population. Respiratory Medicine, 106017.
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A. B. L., & Rajak, S. (2020). Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, 107546.
Rane, S. B., & Narvel, Y. A. M. (2021). Re-designing the business organization using disruptive innovations based on blockchain-IoT integrated architecture for improving agility in future Industry 4.0. Benchmarking: An International Journal, 28(5), 1883-1908.
Sahal, R., Breslin, J. G., & Ali, M. I. (2020). Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case. Journal of Manufacturing Systems, 54, 138-151.
Sergis, S., Sampson, D. G., Rodríguez-Triana, M. J., Gillet, D., Pelliccione, L., & de Jong, T. (2019). Using educational data from teaching and learning to inform teachers’ reflective educational design in inquiry-based STEM education. Computers in human behavior, 92, 724-738.
Tortorella, G., Miorando, R., Caiado, R., Nascimento, D., & Portioli Staudacher, A. (2021). The mediating effect of employees’ involvement on the relationship between Industry 4.0 and operational performance improvement. Total Quality Management & Business Excellence, 32(1-2), 119-133.
Ul-Hameed, W., Mohammad, H., Shahar, H., Aljumah, A., & Azizan, S. (2019). The effect of integration between audit and leadership on supply chain performance: Evidence from UK based supply chain companies. Uncertain Supply Chain Management, 7(2), 311-328. doi:https://doi.org/10.5267/j.uscm.2018.8.001
van der Kamp, R. (1997). Technology and Human Resources in the Indonesian Textile Industry–The Role of Technological Progress, Education and HRD in Economic Performance. Masters thesis, Eindhoven University of Technology.
Yadav, G., Luthra, S., Jakhar, S. K., Mangla, S. K., & Rai, D. P. (2020). A framework to overcome SSC challenges through solution measures of industry 4.0 and circular economy: An automotive case. Journal of Cleaner Production, 254, 120112.
Asch, M., Moore, T., Badia, R., Beck, M., Beckman, P., Bidot, T., Bodin, F., Cappello, F., Choudhary, A., de Supinski, B., Deelman, E., Dongarra, J., Dubey, A., Fox, G., Fu, H., Girona, S., Gropp, W., Heroux, M., Ishikawa, Y., Keahey, K., Keyes, D., Kramer, W., Lavignon, J., Lu, Y., Matsuoka, S., Mohr, B., Reed, D., Requena, S., Saltz, J., Schulthess, T., Stevens, R., Swany, M., Szalay, A., Tang, W., Varoquaux, G., Vilotte, J., Wisniewski, R., Xu, Z., & Zacharov, I. (2018). Big data and extreme-scale computing: Pathways to convergence-toward a shaping strategy for a future software and data ecosystem for scientific inquiry. The International Journal of High Performance Computing Applications, 32(4), 435-479.
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.
Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 Perspective. International journal of mechanical, industrial science and engineering, 8(1), 37-44.
Dal Corso, L., De Carlo, A., Carluccio, F., Girardi, D., & Falco, A. (2019). An Opportunity to Grow or a Label? Performance Appraisal Justice and Performance Appraisal Satisfaction to Increase Teachers' Well-Being. Frontiers in psychology, 10, 2361-2361.
Dolgui, A., Ivanov, D., Sethi, S. P., & Sokolov, B. (2019). Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications. International journal of production research, 57(2), 411-432.
Fernández-Caramés, T. M., Blanco-Novoa, O., Froiz-Míguez, I., & Fraga-Lamas, P. (2019). Towards an autonomous industry 4.0 warehouse: A UAV and blockchain-based system for inventory and traceability applications in big data-driven supply chain management. Sensors, 19(10), 2394.
Fernando, Y., Jabbour, C. J. C., & Wah, W.-X. (2019). Pursuing green growth in technology firms through the connections between environmental innovation and sustainable business performance: Does service capability matter? Resources, Conservation and Recycling, 141, 8-20.
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.
Guazzi, M., Adams, V., Conraads, V., Halle, M., Mezzani, A., Vanhees, L., Arena, R., Fletcher, G., Forman, D., Kitzman, D., Lavie, C., & Myers, J. (2012). EACPR/AHA Scientific Statement. Clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. Circulation, 126(18), 2261-2274.
Guazzi, M., Arena, R., Halle, M., Piepoli, M. F., Myers, J., & Lavie, C. J. (2018). 2016 focused update: clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. European heart journal, 39(14), 1144-1161.
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., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. doi: https://ssrn.com/abstract=2233795
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., Hult, G., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM), California: Sage Publications, 2016.
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.
Hameed, W. U., Basheer, M. F., Iqbal, J., Anwar, A., & Ahmad, H. K. (2018). Determinants of Firm’s open innovation performance and the role of R & D department: an empirical evidence from Malaysian SME’s. Journal of Global Entrepreneurship Research, 8(1), 29. doi:https://doi.org/10.1186/s40497-018-0112-8
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. DOI: 10.3390/socsci8050154.
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., & Fassott, G. (2010). Testing moderating effects in PLS path models: An illustration of available procedures Handbook of partial least squares (pp. 713-735): Springer.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. in New challenges to international marketing, Bingley: Emerald Group Publishing Limited, pp. 277-319.
Jeble, S., Dubey, R., Childe, S. J., Papadopoulos, T., Roubaud, D., & Prakash, A. (2018). Impact of big data and predictive analytics capability on supply chain sustainability. The International Journal of Logistics Management, 29(2), 513-538.
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.
Jermsittiparsert, K., Kraimak, S., & Boonratanakittiphumi, C. (2019). Does the Industry 4.0 Have Any Impact on the Relationship between Agile Strategic Supply Chain and the Supply Chain Partners Performance. International Journal of Innovation, Creativity and Change, 8(8), 122-141.
Jubaedah, J., Yulivan, I., & Hadi, A. R. A. (2016). The Influence of Financial Performance, Capital Structure and Macroeconomic Factors on Firm’s Value–Evidence from Textile Companies at Indonesia Stock Exchange. Applied Finance and Accounting, 2(2), 18-29.
Li, Z., Guo, H., Barenji, A. V., Wang, W. M., Guan, Y., & Huang, G. Q. (2020). A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network. International Journal of Production Research, 58(24), 7399-7419.
Maghsoodi, A. I., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(1), 2.
Mason, C., & Harrison, R. (2004). Does investing in technology-based firms involve higher risk? An exploratory study of the performance of technology and non-technology investments by business angels. Venture Capital: An international journal of entrepreneurial finance, 6(4), 313-332.
Moktadir, M. A., Ali, S. M., Kusi-Sarpong, S., & Shaikh, M. A. A. (2018). Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process Safety and Environmental Protection, 117, 730-741.
Mosallaeipour, S., Shavarani, S. M., Steens, C., & Eros, A. (2019). A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era. Journal of Corporate Real Estate.
Naveed, R. T., Hameed, W. U., Albassami, A. M., & Moshfegyan, M. (2019). Online Tax System (OTS) in Pakistan: The role of Tax Service Quality (TSQ) and Information Communication Technology (ICT). Pacific Business Review International, 11(12), 78-86.
Pacaiova, H., Turisova, R., Nagyova, A., & Oravec, M. (2020). Safety Management in Accordance with Industry 4.0 Requirements: Analysis and Evaluation of the Level of Digitalization in the Slovak Companies. Paper presented at the International Conference on Applied Human Factors and Ergonomics.
Prasetyani, D., Abidin, A. Z., Purusa, N. A., & Sandra, F. A. (2020). The Prospects and The Competitiveness of Textile Commodities and Indonesian Textile Product in the Global Market. ETIKONOMI, 19(1), 1-18.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
Räisänen, P., Hedman, L., Andersson, M., Stridsman, C., Lindberg, A., Lundbäck, B., Rönmark, E., & Backman, H. (2020). Non-response did not affect prevalence estimates of asthma and respiratory symptoms-results from a postal questionnaire survey of the general population. Respiratory Medicine, 106017.
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A. B. L., & Rajak, S. (2020). Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, 107546.
Rane, S. B., & Narvel, Y. A. M. (2021). Re-designing the business organization using disruptive innovations based on blockchain-IoT integrated architecture for improving agility in future Industry 4.0. Benchmarking: An International Journal, 28(5), 1883-1908.
Sahal, R., Breslin, J. G., & Ali, M. I. (2020). Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case. Journal of Manufacturing Systems, 54, 138-151.
Sergis, S., Sampson, D. G., Rodríguez-Triana, M. J., Gillet, D., Pelliccione, L., & de Jong, T. (2019). Using educational data from teaching and learning to inform teachers’ reflective educational design in inquiry-based STEM education. Computers in human behavior, 92, 724-738.
Tortorella, G., Miorando, R., Caiado, R., Nascimento, D., & Portioli Staudacher, A. (2021). The mediating effect of employees’ involvement on the relationship between Industry 4.0 and operational performance improvement. Total Quality Management & Business Excellence, 32(1-2), 119-133.
Ul-Hameed, W., Mohammad, H., Shahar, H., Aljumah, A., & Azizan, S. (2019). The effect of integration between audit and leadership on supply chain performance: Evidence from UK based supply chain companies. Uncertain Supply Chain Management, 7(2), 311-328. doi:https://doi.org/10.5267/j.uscm.2018.8.001
van der Kamp, R. (1997). Technology and Human Resources in the Indonesian Textile Industry–The Role of Technological Progress, Education and HRD in Economic Performance. Masters thesis, Eindhoven University of Technology.
Yadav, G., Luthra, S., Jakhar, S. K., Mangla, S. K., & Rai, D. P. (2020). A framework to overcome SSC challenges through solution measures of industry 4.0 and circular economy: An automotive case. Journal of Cleaner Production, 254, 120112.