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Antecedents and consequents of industry 4.0 adoption using technology, organization and environment (TOE) framework: A meta-analysis

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Abstract

Industry 4.0 (I4.0) is of burgeoning interest for both researchers and practitioners in the operations management and supply chain context. In recent times, research has examined the antecedents and consequents of I4.0; however, inconsistencies in empirical findings have precluded a clear understanding of the drivers of I4.0 adoption and the subsequent impacts on firm performance. To address this issue, we conducted a meta-analysis of the key antecedents and consequents of I4.0. By establishing these pathways and processes using meta-analysis, we seek to reconcile conflicting results in prior literature and develop a unified framework of the antecedents and consequents of I4.0 adoption. Based on the empirical findings reported in 22 prior studies, we identified 12 antecedents representing technological, organizational, and environmental factors and four consequents representing firm performance of I4.0 adoption. Our findings facilitate managers to prioritize their resources to accentuate I4.0 adoption.

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Notes

  1. “https://www.fortunebusinessinsights.com/industry-4-0-market-102375”.

  2. “https://www.business-standard.com/article/companies/itc-accelerates-digitisation-to-enhance-operational-effectiveness-puri-120090400612_1.html”.

  3. “https://www.mckinsey.com/industries/metals-and-mining/how-we-help-clients/how-a-steel-plant-in-india-tapped-the-value-of-data-and-won-global-acclaim”.

  4. “https://www.mckinsey.com/industries/metals-and-mining/how-we-help-clients/how-a-steel-plant-in-india-tapped-the-value-of-data-and-won-global-acclaim”.

  5. https://www.bloorresearch.com/2018/05/3-it-infrastructure-enablers-for-industry-4-0/.

References

  • Abed, S. S. (2020). Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs. International Journal of Information Management, 53, 102118

    Article  Google Scholar 

  • Aboelmaged, M. G. (2014). Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International Journal of Information Management, 34(5), 639–651

    Article  Google Scholar 

  • Abou-Foul, M., Ruiz-Alba, J. L., & Soares, A. (2020). The impact of digitalization and servitization on the financial performance of a firm: an empirical analysis (pp. 1–15). Production Planning & Control

  • Aeknarajindawat, N. (2019). Dynamic Capabilities and Internet of Things as Predictors of Supply Chain Performance in Thailand: Mediating Role of Operational Agility. International Journal of Supply Chain Management Int J Sup Chain Mgt Vol, 8(5), 585

    Google Scholar 

  • Agostini, L., & Nosella, A. (2019). The adoption of Industry 4.0 technologies in SMEs: results of an international study. Management Decision, 58(4), 625–643

    Article  Google Scholar 

  • Arfi, W. B., Nasr, I. B., Khvatova, T., & Zaied, Y. B. (2021). Understanding acceptance of eHealthcare by IoT natives and IoT immigrants: An integrated model of UTAUT, perceived risk, and financial cost. Technological Forecasting and Social Change, 163, 120437

    Article  Google Scholar 

  • Arnold, C., & Voigt, K. I. (2019). Determinants of industrial internet of things adoption in German manufacturing companies. International Journal of Innovation and Technology Management, 16(06), 1950038

    Article  Google Scholar 

  • Aubert, B. A., Schroeder, A., & Grimaudo, J. (2012). IT as enabler of sustainable farming: An empirical analysis of farmers’ adoption decision of precision agriculture technology. Decision Support Systems, 54(1), 510–520

    Article  Google Scholar 

  • Awa, H. O., & Ojiabo, O. U. (2016). A model of adoption determinants of ERP within TOE framework. Information Technology & People, 29(4), 901–930

    Article  Google Scholar 

  • Awa, H. O., Ojiabo, O. U., & Emecheta, B. C. (2015). Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science & Technology Policy Management

  • Bag, S., Gupta, S., & Kumar, S. (2021). Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development. International Journal of Production Economics, 231, 107844

    Article  Google Scholar 

  • Bag, S., Telukdarie, A., Pretorius, J. H. C., & Gupta, S. (2018). Industry 4.0 and supply chain sustainability: framework and future research directions. Benchmarking: An International Journal, 28(5), 1410–1450

    Google Scholar 

  • Bahmanziari, T., Pearson, J. M., & Crosby, L. (2003). Is Trust Important in Technology Adoption? A Policy Capturing Approach.Journal of Computer Information Systems,10

  • Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, 107776

    Article  Google Scholar 

  • Bevan, P. (2018). IT infrastructure enablers for Industry 4.0. Bloor Research. URL https://www.bloorresearch.com/2018/05/3-it-infrastructure-enablers-for-industry-4-0/ (accessed 6.29.21)

  • Breunig, M., Kelly, R., Mathis, R., & Wee, D. J. M. Q. (2016). Getting the most out of Industry 4.0. McKinsey Global Institute

  • Bhatia, M. S., & Kumar, S. (2020). Critical success factors of Industry 4.0 in automotive manufacturing industry. IEEE Transactions on Engineering Management. DOI: https://doi.org/10.1109/TEM.2020.3017004

    Article  Google Scholar 

  • Buer, S. V., Semini, M., Strandhagen, J. O., & Sgarbossa, F. (2020). The complementary effect of lean manufacturing and digitalisation on operational performance.International Journal of Production Research,1–17

  • Buer, S. V., Strandhagen, J. O., & Chan, F. T. S. (2018). The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International Journal of Production Research, 56(8), 2924–2940

    Article  Google Scholar 

  • Chang, S. C., Chang, H. H., & Lu, M. T. (2021). Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM. Approach Mathematics, 9(4), 414

    Google Scholar 

  • Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021). Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change, 170, 120880

    Article  Google Scholar 

  • Chauhan, C., Singh, A., & Luthra, S. (2021). Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, 124809

    Article  Google Scholar 

  • Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4–39

    Article  Google Scholar 

  • Chen, L., Li, T., & Zhang, T. (2021). Supply chain leadership and firm performance: A meta-analysis. International Journal of Production Economics, 235, 108082

    Article  Google Scholar 

  • Chin, T., Wang, W., Yang, M., Duan, Y., & Chen, Y. (2021). The moderating effect of managerial discretion on blockchain technology and the firms’ innovation quality: Evidence from Chinese manufacturing firms. International Journal of Production Economics, 240, 108219

    Article  Google Scholar 

  • Ciano, M. P., Dallasega, P., Orzes, G., & Rossi, T. (2021). One-to-one relationships between Industry 4.0 technologies and Lean Production techniques: a multiple case study. International Journal of Production Research, 59(5), 1386–1410

    Article  Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation.Administrative Science Quarterly,128–152

  • Cram, W. A., D’arcy, J., & Proudfoot, J. G. (2019). Seeing the forest and the trees: a meta-analysis of the antecedents to information security policy compliance. MIS Quarterly, 43(2), 525–554

    Article  Google Scholar 

  • Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383–394

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology (pp. 319–340). MIS quarterly

  • Depietro, R., Wiarda, E., & Fleischer, M. (1990). The context for change: Organization, technology and environment. The Processes of Technological Innovation, 199(0), 151–175

    Google Scholar 

  • Di Maria, E., De Marchi, V., & Galeazzo, A. (2022). Industry 4.0 technologies and circular economy: The mediating role of supply chain integration. Business Strategy and the Environment, 31(2), 619–632

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., Bryde, D. J., Dwivedi, Y. K., & Papadopoulos, T. (2020). Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting. International Journal of Production Research, 58(11), 3381–3398

    Article  Google Scholar 

  • Fleischmann, M., & Ivens, B. (2019, January). Exploring the role of trust in blockchain adoption: an inductive approach. In Proceedings of the 52nd Hawaii international conference on system sciences

  • Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26

    Article  Google Scholar 

  • Gangwar, H., Date, H., & Raoot, A. (2014). Review on IT adoption: insights from recent technologies. Journal of Enterprise Information Management, 27(4), 488–502

    Article  Google Scholar 

  • Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26(2), 211–231

    Article  Google Scholar 

  • Geng, R., Mansouri, S. A., & Aktas, E. (2017). The relationship between green supply chain management and performance: A meta-analysis of empirical evidences in Asian emerging economies. International Journal of Production Economics, 183, 245–258

    Article  Google Scholar 

  • Ghadge, A., Kara, M. E., Moradlou, H., & Goswami, M. (2020). The impact of Industry 4.0 implementation on supply chains. Journal of Manufacturing Technology Management, 31(4), 669–686

    Article  Google Scholar 

  • Gillani, F., Chatha, K. A., Jajja, M. S. S., & Farooq, S. (2020). Implementation of digital manufacturing technologies: Antecedents and consequences. International Journal of Production Economics, 229, 107748

    Article  Google Scholar 

  • Greenwood, B. N., Agarwal, R., Agarwal, R., & Gopal, A. (2019). The role of individual and organizational expertise in the adoption of new practices. Organization Science, 30(1), 191–213

    Article  Google Scholar 

  • Gupta, H., Kumar, S., Kusi-Sarpong, S., Jabbour, C. J. C., & Agyemang, M. (2020). Enablers to supply chain performance on the basis of digitization technologies. Industrial Management. https://doi.org/10.1108/IMDS-07-2020-0421. & Data Systems. ahead-of-print

    Article  Google Scholar 

  • Hahn, G. J. (2020). Industry 4.0: a supply chain innovation perspective. International Journal of Production Research, 58(5), 1425–1441

    Article  Google Scholar 

  • Han, H., & Trimi, S. (2022). Towards a data science platform for improving SME collaboration through Industry 4.0 technologies. Technological Forecasting and Social Change, 174, 121242

    Article  Google Scholar 

  • Hofmann, E., Sternberg, H., Chen, H., Pflaum, A., & Prockl, G. (2019). Supply chain management and Industry 4.0: conducting research in the digital age. International Journal of Physical Distribution & Logistics Management, 49(10), 945–955

    Article  Google Scholar 

  • Hotrawaisaya, C., Pakvichai, V., & Sriyakul, T. (2019). Lean Production Determinants and Performance Consequences of Implementation of Industry 4.0 in Thailand: Evidence from Manufacturing Sector. https://doi.org/10.13140/RG.2.2.16491.69929

  • Jayashree, S., Hassan Reza, M. N., Malarvizhi, C. A. N., Maheswari, H., Hosseini, Z., & Kasim, A. (2021). The Impact of Technological Innovation on Industry 4.0 Implementation and Sustainability: An Empirical Study on Malaysian Small and Medium Sized Enterprises. Sustainability, 13(18), 10115

    Article  Google Scholar 

  • Jayashree, S., Reza, M. N. H., Malarvizhi, C. A. N., & Mohiuddin, M. (2021). Industry 4.0 implementation and Triple Bottom Line sustainability: An empirical study on small and medium manufacturing firms.Heliyon, 7(8), e07753

  • Jeyaraj, A., & Dwivedi, Y. K. (2020). Meta-analysis in information systems research: Review and recommendations. International Journal of Information Management, 55, 102226

    Article  Google Scholar 

  • Joshi, A. D., & Gupta, S. M. (2019). Evaluation of design alternatives of End-Of-Life products using internet of things. International Journal of Production Economics, 208, 281–293

    Article  Google Scholar 

  • Kalaitzi, D., & Tsolakis, N. (2022). Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage. International Journal of Production Economics, 248, 108466

    Article  Google Scholar 

  • Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408–425

    Article  Google Scholar 

  • Kamble, S. S., Gunasekaran, A., Ghadge, A., & Raut, R. (2020). A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs-A review and empirical investigation. International Journal of Production Economics, 229, 107853

    Article  Google Scholar 

  • Kamble, S., Gunasekaran, A., & Arha, H. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context. International Journal of Production Research, 57(7), 2009–2033

    Article  Google Scholar 

  • Koh, L., Orzes, G., & Jia, F. J. (2019). The fourth industrial revolution (Industry 4.0): technologies disruption on operations and supply chain management. International Journal of Operations & Production Management

  • Kolberg, D., & Zühlke, D. (2015). Lean automation enabled by industry 4.0 technologies. IFAC-PapersOnLine, 48(3), 1870–1875

    Article  Google Scholar 

  • Kumar, S., & Bhatia, M. S. (2021). Environmental dynamism, industry 4.0 and performance: Mediating role of organizational and technological factors. Industrial Marketing Management, 95, 54–64

    Article  Google Scholar 

  • Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & information systems engineering, 6(4), 239–242

  • Li, Y., Dai, J., & Cui, L. (2020). The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model. International Journal of Production Economics, 229, 107777

    Article  Google Scholar 

  • Liang, T. P., Kohli, R., Huang, H. C., & Li, Z. L. (2021). What Drives the Adoption of the Blockchain Technology? A Fit-Viability Perspective. Journal of Management Information Systems, 38(2), 314–337

    Article  Google Scholar 

  • Liao, Y., Deschamps, F., Loures, E. D. F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0-a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609–3629

    Article  Google Scholar 

  • Lin, D., Lee, C. K., Lau, H., & Yang, Y. (2018). Strategic response to Industry 4.0: an empirical investigation on the Chinese automotive industry. Industrial Management & Data Systems

  • Lin, H. F. (2014). Understanding the determinants of electronic supply chain management system adoption: Using the technology–organization–environment framework. Technological Forecasting and Social Change, 86, 80–92

    Article  Google Scholar 

  • Luthra, S., Kumar, A., Zavadskas, E. K., Mangla, S. K., & Garza-Reyes, J. A. (2020). Industry 4.0 as an enabler of sustainability diffusion in supply chain: an analysis of influential strength of drivers in an emerging economy. International Journal of Production Research, 58(5), 1505–1521

    Article  Google Scholar 

  • Mahmood, T., & Mubarik, M. S. (2020). Balancing innovation and exploitation in the fourth industrial revolution: Role of intellectual capital and technology absorptive capacity. Technological Forecasting and Social Change, 160, 120248. https://doi.org/10.1016/j.techfore.2020.120248

    Article  Google Scholar 

  • Mariani, M., & Borghi, M. (2019). Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries. Technological Forecasting and Social Change, 149, 119752

    Article  Google Scholar 

  • Mayr, A., Weigelt, M., Kuhl, A., Grimm, S., Erll, A., Potzel, M., & Franke, J. (2018). “Lean 4.0 - A Conceptual Conjunction of Lean Management and Industry 4.0.” 51st CIRP Conference on Manufacturing Systems, Procedia CIRP 72: 622–628

  • Menguc, B., Auh, S., & Uslu, A. (2013). Customer knowledge creation capability and performance in sales teams. Journal of the Academy of Marketing Science, 41(1), 19–39

    Article  Google Scholar 

  • Mital, M., Chang, V., Choudhary, P., Papa, A., & Pani, A. K. (2018). Adoption of Internet of Things in India: A test of competing models using a structured equation modeling approach. Technological Forecasting and Social Change, 136, 339–346

    Article  Google Scholar 

  • Moeuf, A., Lamouri, S., Pellerin, R., Tamayo-Giraldo, S., Tobon-Valencia, E., & Eburdy, R. (2020). Identification of critical success factors, risks and opportunities of Industry 4.0 in SMEs. International Journal of Production Research, 58(5), 1384–1400

    Article  Google Scholar 

  • Mubarak, M. F., & Petraite, M. (2020). Industry 4.0 technologies, digital trust and technological orientation: What matters in open innovation? Technological Forecasting and Social Change, 161, 120332

    Article  Google Scholar 

  • Narwane, V. S., Raut, R. D., Mangla, S. K., Gardas, B. B., Narkhede, B. E., Awasthi, A., & Priyadarshinee, P. (2020). Mediating role of cloud of things in improving performance of small and medium enterprises in the Indian context (pp. 1–30). Annals of Operations Research

  • Nguyen, X. T., & Luu, Q. K. (2020). Factors affecting adoption of industry 4.0 by small-and medium-sized enterprises: A case in Ho Chi Minh city, Vietnam. The Journal of Asian Finance Economics and Business, 7(6), 255–264

    Article  Google Scholar 

  • Olsen, T. L., & Tomlin, B. (2020). Industry 4.0: Opportunities and challenges for operations management. Manufacturing & Service Operations Management, 22(1), 113–122

    Article  Google Scholar 

  • Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127–182

    Article  Google Scholar 

  • Pappas, N., Caputo, A., Pellegrini, M. M., Marzi, G., & Michopoulou, E. (2021). The complexity of decision-making processes and IoT adoption in accommodation SMEs. Journal of Business Research, 131, 573–583

    Article  Google Scholar 

  • Piccarozzi, M., Aquilani, B., & Gatti, C. (2018). Industry 4.0 in management studies: A systematic literature review. Sustainability, 10(10), 3821

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Rey, A., Panetti, E., Maglio, R., & Ferretti, M. (2021). Determinants in adopting the Internet of Things in the transport and logistics industry. Journal of Business Research, 131, 584–590

    Article  Google Scholar 

  • Rosin, F., Forget, P., Lamouri, S., & Pellerin, R. (2020). Impacts of Industry 4.0 technologies on Lean principles. International Journal of Production Research, 58(6), 1644–1661

    Article  Google Scholar 

  • Satoglu, S., Ustundag, A., Cevikcan, E., & Durmusoglu, M. B. (2018). Lean Transformation Integrated with Industry 4.0 Implementation Methodology. In F. Calisir, & H. Camgoz Akdag (Eds.), Industrial Engineering in the Industry 4.0 Era (pp. 97–107). Cham: Springer International Publishing

    Chapter  Google Scholar 

  • Tornatzky, L., & Fleischer, M. (1990). The Process of Technology Innovation. Lexington, MA: Lexington Books

    Google Scholar 

  • Tortorella, G. L., Vergara, C., Garza-Reyes, A. M., J. A., & 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

    Article  Google Scholar 

  • Tortorella, G. L., Fogliatto, F. S., Espôsto, K. F., Cawley, M., Vassolo, A. F., Tlapa, R., D., & Narayanamurthy, G. (2020). Healthcare costs’ reduction through the integration of Healthcare 4.0 technologies in developing economies (pp. 1–21). Total Quality Management & Business Excellence

  • Tortorella, G. L., Giglio, R., & Van Dun, D. H. (2019). Industry 4.0 adoption as a moderator of the impact of lean production practices on operational performance improvement. International Jjournal of Ooperations & Pproduction Mmanagement

  • Tortorella, G. L., Saurin, T. A., Fogliatto, F. S., Rosa, V. M., Tonetto, L. M., & Magrabi, F. (2021). Impacts of Healthcare 4.0 digital technologies on the resilience of hospitals. Technological Forecasting and Social Change, 166, 120666

    Article  Google Scholar 

  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior (pp. 115–139). MIS quarterly

  • Wamba, S. F., & Queiroz, M. M. (2022). Industry 4.0 and the supply chain digitalisation: a blockchain diffusion perspective. Production Planning & Control, 33(2–3), 193–210

    Article  Google Scholar 

  • Zheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2021). The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review. International Journal of Production Research, 59(6), 1922–1954

    Article  Google Scholar 

  • Jeschke, S. (2017). Various. Industrial Internet of Things. In Springer Series in Wireless Technology. Cham: Springer International Publishing.

  • de Sousa Jabbour, A.B.L., Jabbour, C.J.C., Godinho Filho, M. and Roubaud, D. (2018), “Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations”, Annals of Operations Research, Vol. 270 No. 1, pp. 273-286

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.

    Article  Google Scholar 

  • Agostini, L., & Nosella, A. (2019). The adoption of Industry 4.0 technologies in SMEs: results of an international study. Management Decision, 58(4), 625-643.

  • Wamba, S. F., Gunasekaran, A., Papadopoulos, T., & Ngai, E. (2018). Big data analytics in logistics and supply chain management. The International Journal of Logistics Management.

  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.

    Article  Google Scholar 

  • Saengchai, S., & Jermsittiparsert, K. (2019). Improving sustainability performance through internet of things capability in thailand: mediating role of IOT enabled supply chain integration. International Journal of Supply Chain Management, 8(5), 572-584.

  • Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Luo, Z., Wamba, S. F., & Roubaud, D. (2019). Can big data and predictive analytics improve social and environmental sustainability?. Technological Forecasting and Social Change, 144, 534-545.

    Article  Google Scholar 

  • Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. Sage

  • Light, R. J., Richard, J., Light, R., & Pillemer, D. B. (1984). Summing up: The science of reviewing research. Harvard University Press.

  • KPMG (2018). https://assets.kpmg/content/dam/kpmg/xx/pdf/2018/10/industry-4-0-investment-dont-leave-government-incentives-on-the-table.pdf.

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  1. Production, Operations and Decision Sciences, XLRI Xavier School of Management, 831001, Jamshedpur, India

    Alok Raj

  2. Raj Soin College of Business, Wright State University, 3640 Colonel Glenn Highway, 45435, Dayton, OH, USA

    Anand Jeyaraj

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Raj, A., Jeyaraj, A. Antecedents and consequents of industry 4.0 adoption using technology, organization and environment (TOE) framework: A meta-analysis. Ann Oper Res 322, 101–124 (2023). https://doi.org/10.1007/s10479-022-04942-7

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