How to cite this paper
Alshurideh, M., Kurdi, B., Yasin, S., Damra, Y., Al-Gasaymeh, A., Alzoubi, H., Hamadneh, S., Alzboun, N & Alquqa, E. (2024). Exploring the impact of metaverse adoption on supply chain effectiveness: A pathway to competitive advantage.Uncertain Supply Chain Management, 12(2), 883-892.
Refrences
Aćimović, S., Mijušković, V., Marković, D., & Spasenić, A. T. (2022). The relationship between logistics and organizational performance in a supply chain context. Serbian Journal of Management, 17(2), 333-349.
AlHamad, A. Q., Alomari, K. M., Alshurideh, M., Al Kurdi, B., Salloum, S., & Al-Hamad, A. Q. (2022, November). The adoption of metaverse systems: a hybrid SEM-ML method. In 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (pp. 1-5). IEEE.
Alshurideh, M. T., Al Kurdi, B., Saleh, S., Massoud, K., & Osama, A. (2023a). IoT Applications in Business and Marketing During the Coronavirus Pandemic. In The Effect of Information Technology on Business and Marketing Intelligence Systems (pp. 2541-2551). Cham: Springer International Publishing.
Alshurideh, M. T., Akour, I. A., Al Kurdi, B., Hamadneh, S., & Alzoubi, H. M. (2023b). Impact of Metaverse and Marketing Innovation on Digital Transformation. In 2023 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1-5). IEEE.
Al-Zabidi, A., Rehman, A. U., & Alkahtani, M. (2021). An approach to assess sustainable supply chain agility for a manufacturing organization. Sustainability, 13(4), 1752.
Bai, P., & Bisht, C. (2023). Decentralized Identity Management: Prerequisiteof Web3 Identity Model. TechRxiv.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption and use as an Illustration.
Barhmi, A. (2023). Risk management, robustness and resilience: mechanisms for stabilizing and improving agility performance. Production, 33, e20220119.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588–606.
Cheah, I., & Shimul, A. S. (2023). Marketing in the metaverse: Moving forward–What’s next?. Journal of Global Scholars of Marketing Science, 33(1), 1-10.
Chen, Z. (2022). Metaverse and Stock Market—A Study Based on Fama-French Model. In Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology, 11, 725-734. Atlantis Press.
Cherian, T. M., Mathivathanan, D., Arun SJ, C. J., Ramasubramaniam, M., & Alathur, S. (2023). Influence of supply chain resilience, information technology capabilities and agility on cost and delivery performance in construction supply chains: an Indian perspective. The International Journal of Logistics Management, 34(4), 1050-1076.
Chinie, C., Oancea, M., & Todea, S. (2022). The adoption of the metaverse concepts in Romania. Management & Marketing, 17(3), 328-340.
Christopher, M., Lowson, R., & Peck, H. (2004). Creating agile supply chains in the fashion industry. International Journal of Retail & Distribution Management, 32(8), 367-376.
Cohen, J., (1988). Statistical Power Analysis for the Behavioral Sciences, second ed. Routledge, New York. Routledge.
Cristina, A. P. I. (2021). Opportunities for the digital transformation of the banana sector supply chain based on software with artificial intelligence. Metaverse, 2(1), 13.
Cui, W., Fan, K., & Ci, D. (2022). Research on the Development of Metaverse Marketing in the Context of Digitization: Illustrate by the Case of BlueFocus. BCP Business & Management, 20, 1093-1102.
Daneshvar, M., Razavi Hajiagha, S. H., Tupėnaitė, L., Khoshkheslat, F., (2020). Effective factors of implementing efficient supply chain strategy on supply chain performance. Technological and Economic Development of Economy, 26(4), 947-969
De Felice, F., Petrillo, A., Iovine, G., Salzano, C., & Baffo, I. (2023). How Does the Metaverse Shape Education? A Systematic Literature Review. Applied Sciences, 13(9), 5682.
De Giovanni, P. (2023). Sustainability of the Metaverse: A transition to Industry 5.0. Sustainability, 15(7), 6079.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational statistics & data analysis, 81, 10-23.
Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., ... & Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66, 102542.
Fadlianto, A., & Sulistyowati, N. (2022). E-farming implementation effect on supply chain performance of sugar cane commodities in a plantation company. Journal of Economics, Management, Entrepreneurship, and Business, 2(2), 74-85.
Firmansyah, H. S., & Siagian, H. (2022). The Impact of Information Sharing on Supply Chain Performance through Supplier Quality Management, Supply Chain Agility, and Supply Chain Innovation. Petra International Journal of Business Studies, 5(2), 119-131.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Goodhue, D. L., Lewis, W., & Thompson, R. L. (2017). A multicollinearity and measurement error statistical blind spot: Correcting for excessive false positives in regression and PLS. MIS Quarterly, 41(3), 667–684.
Gupta, P. (2023). Understanding Consumer Behavior in Virtual Ecosystems: Adoption of Immersive Technologies in Metaverse Among Consumers. In Handbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World,130-152. IGI Global.
Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110.
Hair Jr, J., Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hair, J. F., Black, W. C., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New Jersey: Prentice Hall.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458.
Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 3(4), 424–453.
Huang, Y., Li, K., & Zhang, Z. (2023). Valuation Analysis of Metaverse Industry. BCP Business & Management, 38, 672-681.
Koohang, A., Nord, J. H., Ooi, K. B., Tan, G. W. H., Al-Emran, M., Aw, E. C. X., ... & Wong, L. W. (2023). Shaping the metaverse into reality: a holistic multidisciplinary understanding of opportunities, challenges, and avenues for future investigation. Journal of Computer Information Systems, 63(3), 735-765.
Lohmoller, J. -B. (1989). Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag
Luo, X., Wang, Z., Lu, L., & Guan, Y. (2020). Supply chain flexibility evaluation based on matter-element extension. Complexity, 2020, 1-12.
Maden, A. (2022). Evaluation of Metaverse Risks for Supply Chain Sustainability Using Spherical Fuzzy AHP. Proceedings of the International Symposium of the Analytic Hierarchy Process 2022 Web Conference.
Mirabi, M., Hatami, A. S., & Karamad, S. (2018). Impact of supply chain management and agile supply chain on customer satisfaction and competitive advantage. International Journal of Engineering and Technology, 10(4), 995-1004.
Momtaz, P. P. (2022). Some very simple economics of web3 and the metaverse. FinTech, 1(3), 225-234.
Mukhsin, M., Taufik, H., Ridwan, A., & Suryanto, T. (2022). The mediation role of supply chain agility on supply chain orientation-supply chain performance link. Uncertain Supply Chain Management, 10(1), 197-204.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory New York. NY: McGraw-Hill.
Potnis, T., Lau, Y. Y., & Yip, T. L. (2023). Roles of Blockchain Technology in Supply Chain Capability and Flexibility. Sustainability, 15(9), 7460.
Queiroz, M. M., Wamba, S. F., Pereira, S. C. F., & Jabbour, C. J. C. (2023). The metaverse as a breakthrough for operations and supply chain management: Implications and call for action. International Journal of Operations & Production Management, 43(10), 1539-1553.
Rehman Khan, S. A., & Yu, Z. (2021). Assessing the eco-environmental performance: an PLS-SEM approach with practice-based view. International Journal of Logistics Research and Applications, 24(3), 303-321.
Şahin, E., Çemberci, M., Civelek, M. E., & Uca, N. (2017). The role of agility in the effect of trust in supply chain on firm performance. Management Studies, 5(4), 336–345.
Salloum, S., Al Marzouqi, A., Alderbashi, K. Y., Shwedeh, F., Aburayya, A., Al Saidat, M. R., & Al-Maroof, R. S. (2023). Sustainability Model for the Continuous Intention to Use Metaverse Technology in Higher Education: A Case Study from Oman. Sustainability, 15(6), 5257.
Sebastian, S. R., & Babu, B. P. (2022). Are we Cyber aware? A cross sectional study on the prevailing Cyber practices among adults from Thiruvalla, Kerala. International Journal of Community Medicine and Public Health, 10(1), 235–239.
SONG, L., & WANG, J. (2023). Investigation and Research on Public Cognition and Attitude Towards “Metaverse” in Digital Age. Digitalization and Management Innovation: Proceedings of DMI 2022, 367, 331.
Spieske, A., & Birkel, H. (2021). Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic. Computers & Industrial Engineering, 158, 107452.
Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: scale development and model testing. Journal of Operations management, 24(2), 170-188.
Trivedi, S., & Negi, S. (2023). The Metaverse in Supply Chain Management: Application and Benefits. International Journal of Advanced Virtual Reality, 1(1), 36-43.
Tukamuhabwa, B. R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: definition, review and theoretical foundations for further study. International journal of production research, 53(18), 5592-5623.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5-40.
Xiao, R., Yu, T., & Gong, X. (2012). Modeling and simulation of ant colony's labor division with constraints for task allocation of resilient supply chains. International Journal on Artificial Intelligence Tools, 21(03), 1240014.
Yan, H. (2023). Future Trend of Supply Chain Being Exposed to the Metaverse. Highlights in Business, Economics and Management, 11, 149-154.
Yemenici, A. D. (2022). Entrepreneurship in the world of metaverse: virtual or real?. Journal of Metaverse, 2(2), 71-82.
Yi, C. Y., Ngai, E. W. T., & Moon, K. L. (2011). Supply chain flexibility in an uncertain environment: exploratory findings from five case studies. Supply Chain Management: An International Journal, 16(4), 271-283.
Yusuf, Y. Y., Gunasekaran, A., Musa, A., Dauda, M., El-Berishy, N. M., & Cang, S. (2014). A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry. International Journal of Production Economics, 147, 531-543.
Zhang, H., & Okoroafo, S. C. (2015). Third-party logistics (3PL) and supply chain performance in the Chinese market: a conceptual framework. Engineering Management Research, 4(1), 38-48.
Zhang, Z., & Sharifi, H. (2000). A methodology for achieving agility in manufacturing organisations. International journal of operations & production management, 20(4), 496-513.
Zheng, D., Luo, Q., & Ritchie, B. W. (2021). Afraid to travel after COVID-19? Self-protection, coping and resilience against pandemic ‘travel fear’. Tourism Management, 83, 104261.
AlHamad, A. Q., Alomari, K. M., Alshurideh, M., Al Kurdi, B., Salloum, S., & Al-Hamad, A. Q. (2022, November). The adoption of metaverse systems: a hybrid SEM-ML method. In 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (pp. 1-5). IEEE.
Alshurideh, M. T., Al Kurdi, B., Saleh, S., Massoud, K., & Osama, A. (2023a). IoT Applications in Business and Marketing During the Coronavirus Pandemic. In The Effect of Information Technology on Business and Marketing Intelligence Systems (pp. 2541-2551). Cham: Springer International Publishing.
Alshurideh, M. T., Akour, I. A., Al Kurdi, B., Hamadneh, S., & Alzoubi, H. M. (2023b). Impact of Metaverse and Marketing Innovation on Digital Transformation. In 2023 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1-5). IEEE.
Al-Zabidi, A., Rehman, A. U., & Alkahtani, M. (2021). An approach to assess sustainable supply chain agility for a manufacturing organization. Sustainability, 13(4), 1752.
Bai, P., & Bisht, C. (2023). Decentralized Identity Management: Prerequisiteof Web3 Identity Model. TechRxiv.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption and use as an Illustration.
Barhmi, A. (2023). Risk management, robustness and resilience: mechanisms for stabilizing and improving agility performance. Production, 33, e20220119.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588–606.
Cheah, I., & Shimul, A. S. (2023). Marketing in the metaverse: Moving forward–What’s next?. Journal of Global Scholars of Marketing Science, 33(1), 1-10.
Chen, Z. (2022). Metaverse and Stock Market—A Study Based on Fama-French Model. In Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology, 11, 725-734. Atlantis Press.
Cherian, T. M., Mathivathanan, D., Arun SJ, C. J., Ramasubramaniam, M., & Alathur, S. (2023). Influence of supply chain resilience, information technology capabilities and agility on cost and delivery performance in construction supply chains: an Indian perspective. The International Journal of Logistics Management, 34(4), 1050-1076.
Chinie, C., Oancea, M., & Todea, S. (2022). The adoption of the metaverse concepts in Romania. Management & Marketing, 17(3), 328-340.
Christopher, M., Lowson, R., & Peck, H. (2004). Creating agile supply chains in the fashion industry. International Journal of Retail & Distribution Management, 32(8), 367-376.
Cohen, J., (1988). Statistical Power Analysis for the Behavioral Sciences, second ed. Routledge, New York. Routledge.
Cristina, A. P. I. (2021). Opportunities for the digital transformation of the banana sector supply chain based on software with artificial intelligence. Metaverse, 2(1), 13.
Cui, W., Fan, K., & Ci, D. (2022). Research on the Development of Metaverse Marketing in the Context of Digitization: Illustrate by the Case of BlueFocus. BCP Business & Management, 20, 1093-1102.
Daneshvar, M., Razavi Hajiagha, S. H., Tupėnaitė, L., Khoshkheslat, F., (2020). Effective factors of implementing efficient supply chain strategy on supply chain performance. Technological and Economic Development of Economy, 26(4), 947-969
De Felice, F., Petrillo, A., Iovine, G., Salzano, C., & Baffo, I. (2023). How Does the Metaverse Shape Education? A Systematic Literature Review. Applied Sciences, 13(9), 5682.
De Giovanni, P. (2023). Sustainability of the Metaverse: A transition to Industry 5.0. Sustainability, 15(7), 6079.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational statistics & data analysis, 81, 10-23.
Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., ... & Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66, 102542.
Fadlianto, A., & Sulistyowati, N. (2022). E-farming implementation effect on supply chain performance of sugar cane commodities in a plantation company. Journal of Economics, Management, Entrepreneurship, and Business, 2(2), 74-85.
Firmansyah, H. S., & Siagian, H. (2022). The Impact of Information Sharing on Supply Chain Performance through Supplier Quality Management, Supply Chain Agility, and Supply Chain Innovation. Petra International Journal of Business Studies, 5(2), 119-131.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Goodhue, D. L., Lewis, W., & Thompson, R. L. (2017). A multicollinearity and measurement error statistical blind spot: Correcting for excessive false positives in regression and PLS. MIS Quarterly, 41(3), 667–684.
Gupta, P. (2023). Understanding Consumer Behavior in Virtual Ecosystems: Adoption of Immersive Technologies in Metaverse Among Consumers. In Handbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World,130-152. IGI Global.
Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110.
Hair Jr, J., Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hair, J. F., Black, W. C., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New Jersey: Prentice Hall.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458.
Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 3(4), 424–453.
Huang, Y., Li, K., & Zhang, Z. (2023). Valuation Analysis of Metaverse Industry. BCP Business & Management, 38, 672-681.
Koohang, A., Nord, J. H., Ooi, K. B., Tan, G. W. H., Al-Emran, M., Aw, E. C. X., ... & Wong, L. W. (2023). Shaping the metaverse into reality: a holistic multidisciplinary understanding of opportunities, challenges, and avenues for future investigation. Journal of Computer Information Systems, 63(3), 735-765.
Lohmoller, J. -B. (1989). Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag
Luo, X., Wang, Z., Lu, L., & Guan, Y. (2020). Supply chain flexibility evaluation based on matter-element extension. Complexity, 2020, 1-12.
Maden, A. (2022). Evaluation of Metaverse Risks for Supply Chain Sustainability Using Spherical Fuzzy AHP. Proceedings of the International Symposium of the Analytic Hierarchy Process 2022 Web Conference.
Mirabi, M., Hatami, A. S., & Karamad, S. (2018). Impact of supply chain management and agile supply chain on customer satisfaction and competitive advantage. International Journal of Engineering and Technology, 10(4), 995-1004.
Momtaz, P. P. (2022). Some very simple economics of web3 and the metaverse. FinTech, 1(3), 225-234.
Mukhsin, M., Taufik, H., Ridwan, A., & Suryanto, T. (2022). The mediation role of supply chain agility on supply chain orientation-supply chain performance link. Uncertain Supply Chain Management, 10(1), 197-204.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory New York. NY: McGraw-Hill.
Potnis, T., Lau, Y. Y., & Yip, T. L. (2023). Roles of Blockchain Technology in Supply Chain Capability and Flexibility. Sustainability, 15(9), 7460.
Queiroz, M. M., Wamba, S. F., Pereira, S. C. F., & Jabbour, C. J. C. (2023). The metaverse as a breakthrough for operations and supply chain management: Implications and call for action. International Journal of Operations & Production Management, 43(10), 1539-1553.
Rehman Khan, S. A., & Yu, Z. (2021). Assessing the eco-environmental performance: an PLS-SEM approach with practice-based view. International Journal of Logistics Research and Applications, 24(3), 303-321.
Şahin, E., Çemberci, M., Civelek, M. E., & Uca, N. (2017). The role of agility in the effect of trust in supply chain on firm performance. Management Studies, 5(4), 336–345.
Salloum, S., Al Marzouqi, A., Alderbashi, K. Y., Shwedeh, F., Aburayya, A., Al Saidat, M. R., & Al-Maroof, R. S. (2023). Sustainability Model for the Continuous Intention to Use Metaverse Technology in Higher Education: A Case Study from Oman. Sustainability, 15(6), 5257.
Sebastian, S. R., & Babu, B. P. (2022). Are we Cyber aware? A cross sectional study on the prevailing Cyber practices among adults from Thiruvalla, Kerala. International Journal of Community Medicine and Public Health, 10(1), 235–239.
SONG, L., & WANG, J. (2023). Investigation and Research on Public Cognition and Attitude Towards “Metaverse” in Digital Age. Digitalization and Management Innovation: Proceedings of DMI 2022, 367, 331.
Spieske, A., & Birkel, H. (2021). Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic. Computers & Industrial Engineering, 158, 107452.
Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: scale development and model testing. Journal of Operations management, 24(2), 170-188.
Trivedi, S., & Negi, S. (2023). The Metaverse in Supply Chain Management: Application and Benefits. International Journal of Advanced Virtual Reality, 1(1), 36-43.
Tukamuhabwa, B. R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: definition, review and theoretical foundations for further study. International journal of production research, 53(18), 5592-5623.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5-40.
Xiao, R., Yu, T., & Gong, X. (2012). Modeling and simulation of ant colony's labor division with constraints for task allocation of resilient supply chains. International Journal on Artificial Intelligence Tools, 21(03), 1240014.
Yan, H. (2023). Future Trend of Supply Chain Being Exposed to the Metaverse. Highlights in Business, Economics and Management, 11, 149-154.
Yemenici, A. D. (2022). Entrepreneurship in the world of metaverse: virtual or real?. Journal of Metaverse, 2(2), 71-82.
Yi, C. Y., Ngai, E. W. T., & Moon, K. L. (2011). Supply chain flexibility in an uncertain environment: exploratory findings from five case studies. Supply Chain Management: An International Journal, 16(4), 271-283.
Yusuf, Y. Y., Gunasekaran, A., Musa, A., Dauda, M., El-Berishy, N. M., & Cang, S. (2014). A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry. International Journal of Production Economics, 147, 531-543.
Zhang, H., & Okoroafo, S. C. (2015). Third-party logistics (3PL) and supply chain performance in the Chinese market: a conceptual framework. Engineering Management Research, 4(1), 38-48.
Zhang, Z., & Sharifi, H. (2000). A methodology for achieving agility in manufacturing organisations. International journal of operations & production management, 20(4), 496-513.
Zheng, D., Luo, Q., & Ritchie, B. W. (2021). Afraid to travel after COVID-19? Self-protection, coping and resilience against pandemic ‘travel fear’. Tourism Management, 83, 104261.