Int J Performability Eng ›› 2024, Vol. 20 ›› Issue (6): 355-366.doi: 10.23940/ijpe.24.06.p3.355366
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Koteswarapavan Chivukula* and Laxmi Narayan Pattanaik
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* E-mail address: koteswarapavan@gmail.com
Koteswarapavan Chivukula and Laxmi Narayan Pattanaik. Effects of Industry 4.0 Technologies on Lean Manufacturing and Organizational Performances: An Empirical Study using Structural Equation Modelling [J]. Int J Performability Eng, 2024, 20(6): 355-366.
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[1] Narula S., Puppala H., Kumar A., Luthra S., Dwivedy M., Prakash S. and Talwar V., 2023. Are Industry 4.0 technologies enablers of lean? Evidence from manufacturing industries. International journal of lean six sigma, 14(1), pp.115-138. [2] Ojha R.,2023. Lean in industry 4.0 is accelerating manufacturing excellence-A DEMATEL analysis. The TQM Journal, 35(3), pp.597-614. [3] Moeuf A., Pellerin R., Lamouri S., Tamayo-Giraldo S. and Barbaray R., 2018. The industrial management of SMEs in the era of Industry 4.0. International journal of production research, 56(3), pp.1118-1136. [4] Rosin F., Forget P., Lamouri S. and Pellerin R., 2020. Impacts of Industry 4.0 technologies on Lean principles. International Journal of Production Research, 58(6), pp.1644-1661. [5] Hoellthaler G., Braunreuther S. and Reinhart G., 2018. Digital Lean ProductionAn Approach to Identify Potentials for the Migration to a Digitalized Production System in SMEs from a Lean Perspective. Procedia Cirp, 67, pp.522-527. [6] Enke J., Glass R., Kreß A., Hambach J., Tisch M. and Metternich J., 2018. Industrie 4.0-Competencies for a modern production system: A curriculum for Learning Factories. Procedia manufacturing, 23, pp.267-272. [7] Hofmann, E. and Rüsch, M., 2017. Industry 4.0 and the current status as well as future prospects on logistics. Computers in industry, 89, pp.23-34. [8] Pagliosa M., Tortorella G. and Ferreira J.C.E., 2019. Industry 4.0 and Lean Manufacturing: A systematic literature review and future research directions. Journal of Manufacturing Technology Management, 32(3), pp.543-569. [9] Buer S.V., Strandhagen J.O. and Chan F.T., 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), pp.2924-2940. [10] Rossini M., Costa F., Tortorella G.L., Valvo A. and Portioli-Staudacher A., 2022. Lean Production and Industry 4.0 integration: how Lean Automation is emerging in manufacturing industry. International Journal of Production Research, 60(21), pp.6430-6450. [11] Tortorella, G.L. and Fettermann, D., 2018. Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research, 56(8), pp.2975-2987. [12] Ghaithan A., Khan M., Mohammed A. and Hadidi L., 2021. Impact of industry 4.0 and lean manufacturing on the sustainability performance of plastic and petrochemical organizations in Saudi Arabia. Sustainability, 13(20), p.11252. [13] Ooi L.L., Teh S.Y. and Cheang P.Y.S., 2023. The impact of lean production on sustainable organizational performance: the moderating effect of industry 4.0 technologies adoption. Management Research Review, 46(12), pp.1802-1836. [14] Maware, C. and Parsley, D.M., 2023. Can industry 4.0 assist lean manufacturing in attaining sustainability over time? Evidence from the US organizations. Sustainability, 15(3), p.1962. [15] Kamble S., Gunasekaran A. and Dhone N.C., 2020. Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies. International journal of production research, 58(5), pp.1319-1337. [16] Panizzolo R., Garengo P., Sharma M.K. and Gore A., 2012. Lean manufacturing in developing countries: evidence from Indian SMEs. Production Planning & Control, 23(10-11), pp.769-788. [17] Womack, J.P. and Jones, D.T., 1997. Lean thinking—banish waste and create wealth in your corporation. Journal of the Operational Research Society, 48(11), pp.1148-1148. [18] Gatell, I.S. and Avella, L., 2024. Impact of Industry 4.0 and circular economy on lean culture and leadership: Assessing digital green lean as a new concept. European Research on Management and Business Economics, 30(1), p.100232. [19] Abuzaid A., Alateeq M., Baqleh L., Madadha S. and Haraisa Y., 2023. The moderating effect of strategic momentum on the relationship between big data analytics capabilities and lean supply chain practices. Uncertain Supply Chain Management, 11(3), pp.1085-1098. [20] Samadhiya A., Agrawal R. and Garza-Reyes J.A., 2024. Integrating industry 4.0 and total productive maintenance for global sustainability. The TQM Journal, 36(1), pp.24-50. [21] Kagermann H., Helbig J., Hellinger A. and Wahlster W., 2013. Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. Forschungsunion. [22] Dewi N., Said J., Faiza S. and Julian L., 2024. The effect of big data competencies and tone at the top on internal auditors fraud detection effectiveness. Decision Science Letters, 13(1), pp.153-160. [23] Kolberg, D. and Zühlke, D., 2015. Lean automation enabled by industry 4.0 technologies. IFAC-PapersOnLine, 48(3), pp.1870-1875. [24] Varela L., Araújo A., Ávila P., Castro H. and Putnik G., 2019. Evaluation of the relation between lean manufacturing, industry 4.0, and sustainability. Sustainability, 11(5), p.1439. [25] Sony M.,2018. Industry 4.0 and lean management: a proposed integration model and research propositions. Production & Manufacturing Research, 6(1), pp.416-432. [26] Sanders A., Elangeswaran C. and Wulfsberg J.P., 2016. Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management (JIEM), 9(3), pp.811-833. [27] Gallo T., Cagnetti C., Silvestri C. and Ruggieri A., 2021. Industry 4.0 tools in lean production: A systematic literature review. Procedia Computer Science, 180, pp.394-403. [28] Kolberg D., Knobloch J. and Zühlke D., 2017. Towards a lean automation interface for workstations. International journal of production research, 55(10), pp.2845-2856. [29] Wagner T., Herrmann C. and Thiede S., 2017. Industry 4.0 impacts on lean production systems. Procedia Cirp, 63, pp.125-131. [30] Bega M., Sapel P., Ercan F., Schramm T., Spitz M., Kuhlenkötter B. and Hopmann C., 2023. Extension of value stream mapping 4.0 for comprehensive identification of data and information flows within the manufacturing domain. Production Engineering, 17(6), pp.915-927. [31] Mariappan R.C.S., Veerabathiran A., KP P. and KEK V., 2023. Intelligent VSM Model: a way to adopt Industry 4.0 technologies in manufacturing industry. The International Journal of Advanced Manufacturing Technology, 129(5), pp.2195-2214. [32] Vlachos I.P., Pascazzi R.M., Zobolas G., Repoussis P. and Giannakis M., 2023. Lean manufacturing systems in the area of Industry 4.0: A lean automation plan of AGVs/IoT integration. Production planning & control, 34(4), pp.345-358. [33] Dalenogare L.S., Benitez G.B., Ayala N.F. and Frank A.G., 2018. The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of production economics, 204, pp.383-394. [34] Bibri S.E., Krogstie J., Kaboli A. and Alahi A., 2024. Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review. Environmental Science and Ecotechnology, 19, p.100330. [35] Chauhan C., Singh A. and Luthra S., 2021. Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, p.124809. [36] Belhadi A., Kamble S.S., Zkik K., Cherrafi A. and Touriki F.E., 2020. 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. Journal of Cleaner Production, 252, p.119903. [37] Sadeghi M., Nikfar M. and Rad F., 2024. Optimizing warehouse operations for environmental sustainability: a simulation study for reducing carbon emissions and maximizing space utilization. Journal of Future Sustainability, 4(1), pp.35-44. [38] Joshi S., Sharma M., Bartwal S., Joshi T. and Prasad M., 2022. Critical challenges of integrating OPEX strategies with I4. 0 technologies in manufacturing SMEs: A few pieces of evidence from developing economies. The TQM Journal, 36(1), pp.108-138. [39] Duman, M.C. and Akdemir, B., 2021. A study to determine the effects of industry 4.0 technology components on organizational performance. Technological Forecasting and Social Change, 167, p.120615. [40] Zanchi M., Lorenzi A., Prezioso M., Powell D. and Gaiardelli P., 2023, September. Effects of Lean and Industry 4.0 Technologies on Job Satisfaction: A Case-Based Analysis. In IFIP International Conference on Advances in Production Management Systems (pp. 27-38). Cham: Springer Nature Switzerland. [41] Holuša V., Vaněk M., Beneš F., Švub J. and Staša P., 2023. Virtual Reality as a Tool for Sustainable Training and Education of Employees in Industrial Enterprises. Sustainability, 15(17), p.12886. [42] Patel V., Chesmore A., Legner C.M. and Pandey S., 2022. Trends in workplace wearable technologies and connected‐worker solutions for next‐generation occupational safety, health, and productivity. Advanced Intelligent Systems, 4(1), p.2100099. [43] Inman, R.A. and Green, K.W., 2018. Lean and green combine to impact environmental and operational performance. International Journal of Production Research, 56(14), pp.4802-4818. [44] Chiarini A.,2021. Industry 4.0 technologies in the manufacturing sector: Are we sure they are all relevant for environmental performance?. Business Strategy and the Environment, 30(7), pp.3194-3207. [45] Romero D., Gaiardelli P., Powell D., Wuest T. and Thürer M., 2019. Total quality management and quality circles in the digital lean manufacturing world. In Advances in Production Management Systems. Production Management for the Factory of the Future: IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1-5, 2019, Proceedings, Part I (pp. 3-11). Springer International Publishing. [46] Demeter, K. and Matyusz, Z., 2011. The impact of lean practices on inventory turnover. International journal of production economics, 133(1), pp.154-163. [47] Kumar A., Agrawal R., Wankhede V.A., Sharma M. and Mulat-Weldemeskel E., 2022. A framework for assessing social acceptability of industry 4.0 technologies for the development of digital manufacturing. Technological Forecasting and Social Change, 174, p.121217. [48] Marodin G.A., Frank A.G., Tortorella G.L. and Fetterman D.C., 2019. Lean production and operational performance in the Brazilian automotive supply chain. Total Quality Management & Business Excellence, 30(3-4), pp.370-385. [49] Zhang B., Niu Z. and Liu C., 2020. Lean tools, knowledge management, and lean sustainability: The moderating effects of study conventions. Sustainability, 12(3), p.956. [50] García Alcaraz J.L., Díaz Reza J.R., Arredondo Soto K.C., Hernandez Escobedo G., Happonen A., Puig I Vidal R. and Jiménez Macías E., 2022. Effect of green supply chain management practices on environmental performance: case of Mexican manufacturing companies. Mathematics, 10(11), p.1877. [51] Fullerton R.R., Kennedy F.A. and Widener S.K., 2014. Lean manufacturing and firm performance: The incremental contribution of lean management accounting practices. Journal of Operations Management, 32(7-8), pp.414-428. [52] Siraj N., Hágen I., Cahyadi A., Tangl A. and Desalegn G., 2022. Linking Leadership to Employees Performance: The Mediating Role of Human Resource Management. Economies, 10(5), p.111. [53] Hair J.F.,2009. Multivariate data analysis. [54] Curran P.J., West S.G. and Finch J.F., 1996. The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological methods, 1(1), p.16. [55] Podsakoff P.M., MacKenzie S.B., Lee J.Y. and Podsakoff N.P., 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), p.879. [56] Nunnally J.C.,1978. Psychometric Theory 2nd edition (New York: McGraw). [57] Fornell, C. and Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), pp.39-50. [58] Bong M., Woo Y. and Shin J., 2013. Do students distinguish between different types of performance goals?. The Journal of Experimental Education, 81(4), pp.464-489. [59] Akkuş A.,2019. Developing a scale to measure students’ attitudes toward science. International Journal of Assessment Tools in Education, 6(4), pp.706-720. [60] Hui, L.S. and Singh, G.S.B., 2020. The Influence of Instructional Leadership on Learning Organisation at High Performing Primary Schools in Malaysia. Asian Journal of University Education, 16(2), pp.69-76. [61] Wang X., Wang Q., Cai Y. and Tu D., 2023. Measurement invariance and latent mean differences of the morbid curiosity scale (MCS) across the United States and China. Heliyon, 9(9). |
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