Abstract
The shift between companies from competition based on products to competition between supply chains has also forced companies to shift in the technology used in managing and sharing supply chain data. Therefore, the current study aims to create a conceptual framework on supply chain management practices (SCMP), big data analytics capabilities (BDAC), and sustainable performance (SP) from a metaverse perspective. The methodology used in the current conceptual study includes a wide review of the research literature and previous studies related to the research variables. On the basis of such review, model links were created and supported by the dynamic capability theory and the natural resource-based view (NRBV) theory. Accordingly, some implications were presented to academics and practitioners, and some future studies were also suggested.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aboelmaged, M.: The drivers of sustainable manufacturing practices in Egyptian SMEs and their impact on competitive capabilities: a PLS-SEM model. J. Clean. Prod. 175, 207–221 (2018). https://doi.org/10.1016/j.jclepro.2017.12.053
Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R., Childe, S.J.: How to improve firm performance using big data analytics capability and business strategy alignment? Int. J. Prod. Econ. 182, 113–131 (2016). https://doi.org/10.1016/j.ijpe.2016.08.018
Al-Abrrow, H., Fayez, A.S., Abdullah, H., Khaw, K.W., Alnoor, A., Rexhepi, G.: Effect of open-mindedness and humble behavior on innovation: mediator role of learning. Int. J. Emerg. Market. (2021)
Albahri, A.S., et al.: Based on the multi-assessment model: towards a new context of combining the artificial neural network and structural equation modelling: a review. Chaos Solitons Fractals 153, 111445 (2021)
Albergaria, M., Jabbour, C.J.C.: The role of big data analytics capabilities (BDAC) in understanding the challenges of service information and operations management in the sharing economy: evidence of peer effects in libraries. Int. J. Inf. Manag. 51, 102023 (2020)
AL-Fatlawey, M.H., Brias, A.K., Atiyah, A.G.: The role of Strategic Behavior in achievement the Organizational Excellence “Analytical research of the manager’s views of Ur State Company at Thi-Qar Governorate”. J. Administ. Econ. 10(37) (2021)
Alnoor, A., et al.: How positive and negative electronic word of mouth (eWOM) affects customers’ intention to use social commerce? A dual-stage multi group-SEM and ANN analysis. Int. J. Hum. Comput. Interact. 1–30 (2022)
Alsalem, M.A., et al.: Rise of multiattribute decision-making in combating COVID-19: a systematic review of the state-of-the-art literature. Int. J. Intell. Syst. 37(6), 3514–3624 (2022)
Amin, S.H., Zhang, G.: Closed-loop supply chain network configuration by a multi-objective mathematical model. Int. J. Bus. Perform. Supply Chain Model. 6(1), 1–15 (2014)
Arunachalam, D., Kumar, N., Kawalek, J.P.: Understanding big data analytics capabilities in supply chain management: unravelling the issues, challenges and implications for practice. Transport. Res. Part E: Logist. Transport. Rev. 114, 416–436 (2018). https://doi.org/10.1016/j.tre.2017.04.001
Ataseven, C., Nair, A.: Assessment of supply chain integration and performance relationships: a meta-analytic investigation of the literature. Int. J. Prod. Econ. 185, 252–265 (2017)
Atiyah, A.G.: The effect of the dimensions of strategic change on organizational performance level. PalArch’s J. Archaeol. Egypt/Egyptol. 17(8), 1269–1282 (2020)
Atiyah, A.G. Strategic Network and Psychological Contract Breach: The Mediating Effect of Role Ambiguity (2023)
Atiyah, A.G., Zaidan, R.A.: Barriers to using social commerce. In: Artificial Neural Networks and Structural Equation Modeling: Marketing and Consumer Research Applications, pp. 115–130. Springer Nature Singapore, Singapore (2020)
Bag, S., Wood, L.C., Xu, L., Dhamija, P., Kayikci, Y.: Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resour. Conserv. Recycl. 153, 104559 (2020). https://doi.org/10.1016/j.resconrec.2019.104559
Bag, S., Yadav, G., Wood, L.C., Dhamija, P., Joshi, S.: Industry 4.0 and the circular economy: resource melioration in logistics. Resources Policy 68 (2020)
Ballou, R.A.: Business Logistics Management. Prentice Hall (1992)
Bansal, P., Roth, K.: Why companies go green: a model of ecological responsiveness. Acad. Manag. J. 43(4), 717–736 (2000). https://doi.org/10.5465/1556363
Barbeito-Caamaño, A., Chalmeta, R.: Using big data to evaluate corporate social responsibility and sustainable development practices. Corp. Soc. Responsib. Environ. Manag. 27(6), 2831–2848 (2020)
Barney, J.: Firm resources and sustained competitive advantage. J. Manag. 17(1), 99–120 (1991). https://doi.org/10.1177/014920639101700108
Barney, J., Wright, M., Ketchen, D.J.: The resource-based view of the firm: ten years after 1991. J. Manag. 27(6), 625–641 (2001). https://doi.org/10.1177/014920630102700601
Baumgartner, R.J.: Managing corporate sustainability and CSR: a conceptual framework combining values, strategies, and instruments contributing to sustainable development. Corp. Soc. Responsib. Environ. Manag. 21, 258–271 (2014)
Belhadi, A., Kamble, S.S., Zkik, K., Cherrafi, A., Touriki, F.E.: The integrated effect of big data analytics, lean six sigma, and green manufacturing on the environmental performance of manufacturing companies: the case of North Africa. J. Clean. Prod. 252, 119903 (2020)
Beske, P.: NOFOMA dynamic capabilities and sustainable supply chain management. Int. J. Phys. Distrib. Logist. Manag. 42(4), 5–25 (2012)
Buhalis, D., Leung, D., Lin, M.: Metaverse as a disruptive technology revolutionising tourism management and marketing. Tour. Manage. 97, 104724 (2023)
Chandra, C., Kumar, S.: Supply chain management in theory and practice: a passing fad or a fundamental change? Indust. Manag. Data Syst. 100(3), 100–113 (2000)
Charkha, P.G., Jaju, S.B.: Supply chain performance measurement system: an overview. Int. J. Bus. Perform. Supply Chain Model. 6(1), 40–60 (2014)
Chopra, S., Meindl, P.: Supply Chain Management. Prentice-Hall (2001)
Chow, W.S., Madu, C.N., Kuei, C., Lu, M.H., Lin, C., Tseng, H.: Supply chain management in the US and Taiwan: an empirical study. Omega 36(5), 565–579 (2008)
Clegg, N.: Making the metaverse: what it is, how it will be built, and why it matters (2022)
Corbett, C.J.: How sustainable is big data. Prod. Oper. Manag. 27(9), 1685–1695 (2018)
Davenport, T.H.: Competing on analytics [WWW Document]. Harvard Business Review (2006). https://hbr.org/2006/01/competing-on-analytics. Accessed 2 Feb 2016
Davenport, T.H., Harris, J.G.: Competing on Analytics: The New Science of Winning. Harvard Business School Press (2007)
Dawe, R.L.: An investigation of the pace and determination of information technology use in the manufacturing materials logistics system. J. Bus. Logist. 15(1), 229–258 (1994)
Dezi, L., Santoro, G., Gabteni, H., Pellicelli, A.C.: The role of big data in shaping ambidextrous business process management: Case studies from the service industry. Bus. Process. Manag. J. 24(5), 1163–1175 (2018). https://doi.org/10.1108/BPMJ-07-2017-0215
Dierickx, I., Cool, K.: Asset stock accumulation and sustainability of competitive advantage. Manage. Sci. 35(12), 1504–1511 (1989). https://doi.org/10.1287/mnsc.35.12.1504
Dolgui, A., Ivanov, D.: Metaverse supply chain and operations management. Int. J. Prod. Res. (2023). https://doi.org/10.1080/00207543.2023.2240900
Dubey, R., et al.: Can big data and predictive analytics improve social and environmental sustainability? Technol. Forecast. Soc. Chang. 144, 534–545 (2019). https://doi.org/10.1016/j.techfore.2017.06.020
Dwivedi, Y.K., et al.: Metaverse beyond the hype: multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manage. 66, 102542 (2022). https://doi.org/10.1016/j.ijinfomgt.2022.102542
Dwivedi, Y., et al.: How metaverse will change the future of marketing: implications for research and practice. Psychol. Mark. (2023). https://doi.org/10.1002/mar.21767
Fadhil, S.S., Ismail, R., Alnoor, A.: The influence of soft skills on employability: a case study on technology industry sector in Malaysia. Interdiscip. J. Inf. Knowl. Manag. 16, 255 (2021)
Fantini, P., Pinzone, M., Taisch, M.: Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems. Comp. Indust. Eng. (2018)
Ferraris, A., Mazzoleni, A., Devalle, A., Couturier, J.: Big data analytics capabilities and knowledge management: impact on firm performance. Manag. Decis. 57(8), 1923–1936 (2019). https://doi.org/10.1108/MD-07-2018-0825
Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage. 35(2), 137–144 (2015). https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Gartner. Gartner Says Worldwide IT Spending on Pace to Grow 3.2 Percent in 2014 (2014)
Gatea, A.A., Marina, V.: Higher education funding in Iraq in terms of the experience of particular developed countries. Int. J. Adv. Stud. 6(1), 8–17 (2016)
George, G., Haas, M.R., Pentland, A.: Big data and management. Acad. Manag. J. 27, 321–326 (2014)
Gharajeh, M.S.: Biological big data analytics. In: Advances in Computers, vol. 109, pp. 321–355. Elsevier, Amsterdam (2018). ISBN 9780128137864
Giddings, B., Hopwood, B., O’Brien, G.: Environment, economy, and society: fitting them together into sustainable development. Sustain. Dev. 10, 187–196 (2002)
Gobble, M.M.: Big data: the next big thing in innovation. Res. Technol. Manag. 56, 64–66 (2013)
Gobbo, S.C.D.O., Fusco, J.P.A., Junior, J.A.G.: An analysis of embeddedness in the value creation in interorganizational networks: an illustrative example in Brazil. Int. J. Adv. Oper. Manag. 6(2), 178–198 (2014)
Goes, P.B.: Big data and IS research. MIS Q. 38, 3–8 (2014)
Govindan, K., Azevedo, S.G., Carvalho, H., Cruz-Machado, V.: Impact of supply chain management practices on sustainability. J. Clean. Prod. 85, 212–225 (2014). https://doi.org/10.1016/j.jclepro.2014.05.068
Grant, R.M.: The resource-based theory of competitive advantage: implications for strategy formulation. Calif. Manage. Rev. 33(3), 114–135 (1991). https://doi.org/10.2307/41166664
Grover, V., Chiang, R.H.L., Liang, T., Zhang, D.: Creating strategic business value from big data analytics: a research framework. J. Manag. Inf. Syst. 35(2), 388–423 (2018). https://doi.org/10.1080/07421222.2018.1451951
Hamid, R.A., et al.: How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management. Comp. Sci. Rev. 39, 100337 (2021)
Hart, S.L.: A natural-resource-based view of the firm. Acad. Manag. Rev. 20(4), 986–1014 (1995). https://doi.org/10.5465/amr.1995.9512280033
Hart, S.L., Dowell, G.: Invited editorial: a natural-resource-based view of the firm: fifteen years after. J. Manag. 37(5), 1464–1479 (2011). https://doi.org/10.1177/0149206310390219
Hart, S.L., Milstein, M.B.: Creating sustainable value. Acad. Manag. Perspect. 17(2), 56–67 (2003). https://doi.org/10.5465/ame.2003.10025194
Hitt, M.A., Xu, K., Carnes, C.M.: Resource based theory in operations management research. J. Oper. Manag. 41, 77–94 (2016). https://doi.org/10.1016/j.jom.2015.11.002
Hoskisson, R.E., Wan, W.P., Yiu, D., Hitt, M.A.: Theory and research in strategic management: swings of a pendulum. J. Manag. 25(3), 417–456 (1999). https://doi.org/10.1016/S0149-2063(99)00008-2
Huo, B., Gu, M., Wang, Z.: Green or lean? A supply chain approach to sustainable performance. J. Clean. Prod. 216, 152–166 (2019). https://doi.org/10.1016/j.jclepro.2019.01.141
Ibrahim, Y.M., Hami, N., Othman, S.N.: Integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework. Int. J. Energy Econ. Policy 9(4), 30–39 (2019). https://doi.org/10.32479/ijeep.7709
Ivanov, D., Dolgui, A.: A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Prod. Plan. Control (2020)
Junaid, M., Zhang, Q., Syed, M.W.: Effects of sustainable supply chain integration on green innovation and firm performance. Sustain. Prod. Consump. 30, 145–157 (2022)
Kache, F., Seuring, S.: Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. Int. J. Oper. Prod. Manag. 37(1), 10–36 (2017)
Kamble, S.S., Gunasekaran, A.: Big data-driven supply chain performance measurement system: a review and framework for implementation. Int. J. Prod. Res. 58(1), 65–86 (2020)
Kamble, S.S., Gunasekaran, A., Gawankar, S.A.: Achieving sustainable performance in a data-driven agriculture supply chain: a review for research and applications. Int. J. Prod. Econ. 219, 179–194 (2020)
Karim, S., Mitchell, W.: Path-dependent and path-breaking change: reconfiguring business resources following acquisitions in the U.S. medical sector, 1978–1995. Strateg. Manag. J. 21(10–11), 1061–1081 (2000). https://doi.org/10.1002/1097-0266(200010/11)21:10/11%3c1061::AID-SMJ116%3e3.0.CO;2-G
Kauffman, R.J., Srivastava, J., Vayghan, J.: Business and data analytics: new innovations for the management of e-commerce. Electron. Commer. Res. Appl. 11, 85–88 (2012)
Khan, S.A.R., Kamble, S.S., Zkik, K., Belhadi, A., Touriki, F.E.: Evaluating barriers and solutions for social sustainability adoption in multi-tier supply chains. Int. J. Prod. Res. (2021). https://doi.org/10.1080/00207543.2021.1876271
Khaw, K.W., et al.: Modelling and evaluating trust in mobile commerce: a hybrid three stage Fuzzy Delphi, structural equation modeling, and neural network approach. Int. J. Hum. Comput. Interact. 38(16), 1529–1545 (2022)
Kiron, D., Prentice, P.K., Ferguson, R.B.: The analytics mandate. MIT Sloan Manag. Rev. 55, 1–25 (2014)
Kumar, V., Chibuzo, E.N., Garza-Reyes, J.A., Kumari, A., Rocha-Lona, L., Lopez-Torres, G.C.: The impact of supply chain integration on performance: evidence from the UK food sector. Procedia Manufact. 11, 814–821 (2017)
Lee, J.G., Kang, M.: Geospatial big data: challenges and opportunities. Big Data Research 2, 74–81 (2015)
Lehrer, C., Wieneke, A., Brocke, J., Jung, R., et al.: How big data analytics enables service innovation: materiality, affordance, and the individualization of service. J. Manag. Inf. Syst. 35(2), 424–460 (2018). https://doi.org/10.1080/07421222.2018.1451953
Lenny Koh, S.C., Demirbag, M., Bayraktar, E., Tatoglu, E., Zaim, S.: The impact of supply chain management practices on performance of SMEs. Indust. Manag. Data Syst. 107(1), 103–124 (2007). https://doi.org/10.1108/02635570710719089
Li, S., Rao, S.S., Ragu-Nathan, T.S., Ragu-Nathan, B.: Development and validation of a measurement instrument for studying supply chain management practices. J. Oper. Manag. 23(6), 618–641 (2005). https://doi.org/10.1016/j.jom.2005.01.002
Liu, Y., Zhu, Q., Seuring, S.: Linking capabilities to green operations strategies: the moderating role of corporate environmental proactivity. Int. J. Prod. Econ. 187, 182–195 (2017)
Lopes de Sousa Jabbour, A.B., Gomes Alves Filho, A., Backx Noronha Viana, A., José Chiappetta Jabbour, C.: Measuring supply chain management practices. Measur. Bus. Excell. 15(2), 18–31 (2011). https://doi.org/10.1108/13683041111131592
Lunden, I.: Forrester: $2.1 Trillion Will Go Into IT Spend in 2013; Apps and the U.S. Lead the Charge (2013)
Lundmark, P.: The real future of the metaverse is not for consumers (2022). https://www.ft.com/content/af0c9de8-d36e-485b-9db5-5ee1e57716cb
Mangla, S.K., Kusi-Sarpong, S., Luthra, S., Bai, C., Jakhar, S.K., Khan, S.A.: Operational excellence for improving sustainable supply chain performance. Resour. Conserv. Recycling 162 (2020). https://doi.org/10.1016/j.resconrec.2020.105025
Manhal, M., Al-khalidi, A., Hamad, Z.: Strategic network: managerial myopia point of view. Manag. Sci. Lett. 13(3), 211–218 (2023)
Martens, D., Provost, F., Clark, J.: Mining massive fine-grained behavior data to improve predictive analytics. MIS Q., 40(4), 869–888 (2016). https://doi.org/10.25300/MISQ/2016/40.4.04
McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harv. Bus. Rev. 60–66(68), 128 (2012)
Menguc, B., Ozanne, L.K.: Challenges of the “green imperative”: a natural resource-based approach to the environmental orientation–business performance relationship. J. Bus. Res. 58(4), 430–438 (2005). https://doi.org/10.1016/j.jbusres.2003.09.002
Minelli, M., Chambers, M., Dhiraj, A.: Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses. Wiley (2013)
Moktadir, M.A., Ali, S.M., Paul, S.K., Shukla, N.: Barriers to big data analytics in manufacturing supply chains: a case study from Bangladesh. Comp. Indust. Eng. 128, 1063–1075 (2019). https://doi.org/10.1016/j.cie.2018.04.013
Müller, O., Fay, M., Brocke, J.: The effect of big data and analytics on firm performance: an econometric analysis considering industry characteristics. J. Manag. Inf. Syst. 35(2), 488–509 (2018). https://doi.org/10.1080/07421222.2018.1451955
Narasimhan, R.: Strategic supply management: a total quality management imperative. Adv. Manag. Organ. Quality 2, 39–86 (1997)
Nidumolu, R., Prahalad, C.K., Rangaswami, M.R.: Why sustainability is now the key driver of innovation. Harv. Bus. Rev. 87(9), 56–64 (2009)
Nilsson, F., Göransson, M.: Critical factors for the realization of sustainable supply chain innovations—model development based on a systematic literature review. J. Clean. Prod. 296, 126471 (2021)
Olszak, C.M.: Towards an understanding business intelligence. A dynamic capability-based framework for Business Intelligence. In: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems (FedCSIS 2014), Warsaw, 7–10 September 2014 (2014)
Ou, C.S., Liu, F.C., Hung, Y.C., Yen, D.C.: A structural model of supply chain management on firm performance. Int. J. Oper. Prod. Manag. 30(5), 526–545 (2010)
Penrose, E.T.: The Theory of the Growth of the Firm. Oxford University Press (2009)
Queiroz, M.M., Fosso Wamba, S., Pereira, S.C.F., Chiappetta Jabbour, C.J.: The metaverse as a breakthrough for operations and supply chain management: implications and call for action. Int. J. Oper. Prod. Manag. 43(10), 1539–1553 (2023). https://doi.org/10.1108/IJOPM-01-2023-0006
Retrieved from https://nickclegg.medium.com/making-the-metaverse-what-it-is-how-it-will-be-built-and-why-it-matters-3710f7570b04
Sarkis, J., Gonzalez-Torre, P., Adenso-Diaz, B.: Stakeholder pressure and the adoption of environmental practices: the mediating effect of training. J. Oper. Manag. 28(2), 163–176 (2010). https://doi.org/10.1016/j.jom.2009.10.001
Schoenherr, T., Speier-Pero, C.: Data science, predictive analytics, and big data in supply chain management: current state and future potential. J. Bus. Logist. 36(1), 120–132 (2015)
Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D., Tufano, P.P.: Analytics: The Real-World Use of Big Data. IBM Institute for Business Value, New York (2012)
Seuring, S.A.: Assessing the rigor of case study research in supply chain management. Supply Chain Manag. Int. J. 13(2), 128–137 (2008)
Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., Luqman, A., Zahid, R.: Impact of big data analytics on sales performance in pharmaceutical organizations: the role of customer relationship management capabilities. PLoS ONE 16, e0250229 (2021)
Shamim, S., Zeng, J., Khan, Z., Zia, N.U.: Big data analytics capability and decision-making performance in emerging market firms: the role of contractual and relational governance mechanisms. Technol. Forecast. Soc. Chang. 161, 120315 (2020)
Sharma, K., Giannakos, M.: Multimodal data capabilities for learning: what can multimodal data tell us about learning? Br. J. Edu. Technol. 51(5), 1450–1484 (2020)
Shukla, A., Deshmukh, S., Kanda, A.: Environmentally responsive supply chains: learnings from Indian auto sector. J. Adv. Manag. Res. 6(2), 154–171 (2009)
Sroufe, R.: Effects of environmental management systems on environmental management practices and operations. Prod. Oper. Manag. 12(3), 416–431 (2003). https://doi.org/10.1111/j.1937-5956.2003.tb00212.x
Stevens, G.: Integrating the supply chains. Int. J. Phys. Distrib. Mater. Manag. 8(8), 3–8 (1989)
Strawn, G.O.: Scientific research: how many paradigms? Educ. Rev. 47, 26 (2012)
Tseng, M.-L., Wu, K.-J., Lim, M.K., Wong, W.-P.: Data-driven sustainable supply chain management performance: a hierarchical structure assessment under uncertainties. J. Clean. Prod. 227, 760–771 (2019)
Vachon, S., Mao, Z.: Linking supply chain strength to sustainable development: a country-level analysis. J. Clean. Prod. 16, 1552–1560 (2008)
Venkatesh, V.G., Kang, K., Wang, B., Zhong, R.Y., Zhang, A.: System architecture for blockchain based transparency of supply chain social sustainability. Robot. Comput. Integrat. Manufact. 63 (2020). https://doi.org/10.1016/j.rcim.2019.101896
Waller, M.A., Fawcett, S.E.: Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logist. 34(2), 77–84 (2013)
Wang, Y., Hajli, N.: Exploring the path to big data analytics success in healthcare. J. Bus. Res. 70, 287–299 (2017)
Wernerfelt, B.: A resource-based view of the firm. Strateg. Manag. J. 5(2), 171–180 (1984). https://doi.org/10.1002/smj.4250050207
Winter, S.G.: The satisficing principle in capability learning. Strateg. Manag. J. 21(10–11), 981–996 (2000). https://doi.org/10.1002/1097-0266(200010/11)21:10/11%3c981::AID-SMJ125%3e3.0.CO;2-4
Wixom, B.H., Yen, B., Relich, M.: Maximizing value from business analytics. MIS Q. Exec. 12, 111–123 (2013)
Wong, C.Y., Arlbjorn, J.S., Johansen, J.: Supply chain management practices in the toy supply chain. Supply Chain Manag. Int. J. 10(5), 367–378 (2005)
Wook Kim, S.: Effects of supply chain management practices, integration and competition capability on performance. Supply Chain Manag. Int. J. 11(3), 241–248 (2006). https://doi.org/10.1108/13598540610662149
Wu, S.J., Melnyk, S.A., Calantone, R.J.: Assessing the core resources in the environmental management system from the resource perspective and the contingency perspective. IEEE Trans. Eng. Manage. 55(2), 304–315 (2008). https://doi.org/10.1109/TEM.2008.919727
Zhong, R.Y., Newman, S.T., Huang, G.Q., Lan, S.: Big Data for supply chain management in the service and manufacturing sectors: challenges, opportunities, and future perspectives. Comp. Indust. Eng. 101, 572–591 (2016)
Zhu, C., Du, J., Shahzad, F., Wattoo, M.U.: Environment sustainability is a corporate social responsibility: measuring the nexus between sustainable supply chain management, big data analytics capabilities, and organizational performance. Sustainability 14, 3379 (2022)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Abdulameer, S.S., Ibrahim, Y.M. (2023). The Moderating Role of Big Data Analytics Capabilities in the Relationship Between Supply Chain Management Practices and Sustainable Performance: A Conceptual Framework from a Metaverse Perspective. In: Al-Emran, M., Ali, J.H., Valeri, M., Alnoor, A., Hussien, Z.A. (eds) Beyond Reality: Navigating the Power of Metaverse and Its Applications. IMDC-IST 2024. Lecture Notes in Networks and Systems, vol 895. Springer, Cham. https://doi.org/10.1007/978-3-031-51716-7_11
Download citation
DOI: https://doi.org/10.1007/978-3-031-51716-7_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-51715-0
Online ISBN: 978-3-031-51716-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)