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Implementation of digital manufacturing technologies: Antecedents and consequences

Gillani, Fatima, Chatha, Kamran Ali, Sadiq Jajja, Muhammad Shakeel, Farooq, Sami·2020·International Journal of Production Economics

Abstract

Abstract The use of digital manufacturing technologies (DMTs) is changing the face of the manufacturing landscape and enhancing the competitiveness of firms. However, its implementation is still a relatively unexplored phenomenon and demands attention. The purpose of this study is to determine the role played by technological context, organizational context, and environmental context of firms in the implementation of the DMTs. A hypothesized model is proposed and tested using survey-based data from the International Manufacturing Strategy Survey VI comprising 931 firms across developed and developing countries. The proposed research model gains support from the technology–organization–environment framework and the combinatorial technology evolution theory, which together provide a holistic understanding of the technology implementation process in terms of its enablers and performance outcomes. We find that although the organizational context and environmental context impact DMTs' implementation, these impacts are mediated through the technological context of the firm. Moreover, the implementation of these technologies has a significant impact on firm performance in terms of flexibility, design, delivery, and quality performance. Contributing to the empirical research gap in the domain of DMTs’ implementation, this study also generates insights for practitioners about the complementarity of the technological, organizational, and environmental factors that together enable the implementation of DMTs and enhance firm performance.

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Research works printed but not linked: 152

  1. Agrifoglio, 2017, How emerging digital technologies affect operations management through co-creation. Empirical evidence from the maritime industry, Prod. Plann. Contr., 28, 1298, 10.1080/09537287.2017.1375150 · DOI
  2. Alshamaila, 2013, Cloud computing adoption by SMEs in the north east of England: a multi-perspective framework, J. Enterprise Inf. Manag., 26, 250, 10.1108/17410391311325225 · DOI · Paper page
  3. Amoako-Gyampah, 2008, Manufacturing strategy, competitive strategy and firm performance: an empirical study in a developing economy environment, Int. J. Prod. Econ., 111, 575, 10.1016/j.ijpe.2007.02.030 · DOI · Paper page
  4. Arvanitis, 2001, The determinants of the adoption of advanced manufacturing technology: an empirical analysis based on firm-level data for Swiss manufacturing, Econ. Innovat. N. Technol., 10, 377, 10.1080/10438590100000015 · DOI
  5. Badri, 2000, Operations strategy, environmental uncertainty and performance: a path analytic model of industries in developing countries, Omega, 28, 155, 10.1016/S0305-0483(99)00041-9 · DOI · Paper page
  6. Baron, 1986, The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations, J. Pers. Soc. Psychol., 51, 1173, 10.1037/0022-3514.51.6.1173 · DOI · Paper page
  7. Battaïa, 2018, Future trends in Management and Operation of Assembly Systems: from customized assembly systems to cyber-physical systems, Omega, 78, 1, 10.1016/j.omega.2018.01.010 · doi:10.1016/j.omega.2018.01.010
  8. Beaumont, 1997, Technology, manufacturing performance and business performance amongst Australian manufacturers, Technovation, 17, 297, 10.1016/S0166-4972(97)00011-4 · DOI
  9. Beck, 2006, Small and medium-size enterprises: access to finance as a growth constraint, J. Bank. Finance, 30, 2931, 10.1016/j.jbankfin.2006.05.009 · DOI · Paper page
  10. Bell, 1997, Technological accumulation and industrial growth: contrasts between developed and developing countries, Technol. Glob. Econ. Perf., 83137, 83
  11. Belvedere, 2017, ICT-enabled time performance: an investigation of value creation mechanisms, Prod. Plann. Contr., 28, 75
  12. Bibby, 2018, Defining and assessing industry 4.0 maturity levels–case of the defence sector, Prod. Plann. Contr., 29, 1030, 10.1080/09537287.2018.1503355 · DOI · Paper page
  13. Boer, 2019, Design-for-variety and operational performance: the mediating role of internal, supplier and customer integration, J. Manuf. Technol. Manag., 30, 438, 10.1108/JMTM-03-2018-0065 · DOI
  14. Bokrantz, 2017, Maintenance in digitalised manufacturing: delphi-based scenarios for 2030, Int. J. Prod. Econ., 191, 154, 10.1016/j.ijpe.2017.06.010 · DOI · Paper page
  15. Bollen, 1992, Tests for structural equation models: introduction, Socio. Methods Res., 21, 123, 10.1177/0049124192021002001 · DOI · Paper page
  16. Bourke, 2016, AMT adoption and innovation: an investigation of dynamic and complementary effects, Technovation, 55, 42, 10.1016/j.technovation.2016.05.003 · DOI
  17. Brandyberry, 1999, Intermediate performance impacts of advanced manufacturing technology systems: an empirical investigation, Decis. Sci. J., 30, 993, 10.1111/j.1540-5915.1999.tb00916.x · DOI
  18. Brettel, 2014, How virtualization, decentralization and network building change the manufacturing landscape: an Industry 4.0 Perspective, Int. J. Mech. Ind. Sci. Eng., 8, 37
  19. Buer, 2018, The link between industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda, Int. J. Prod. Res., 56, 2924, 10.1080/00207543.2018.1442945 · DOI · Paper page
  20. Cagliano, 2011, The impact of country culture on the adoption of new forms of work organization, Int. J. Oper. Prod. Manag., 31, 297, 10.1108/01443571111111937 · DOI
  21. Cagliano, 2014, Alternative uses of temporary work and new forms of work organisation, Prod. Plann. Contr., 25, 762, 10.1080/09537287.2012.750387 · DOI
  22. Cagliano, 2006, The linkage between supply chain integration and manufacturing improvement programmes, Int. J. Oper. Prod. Manag., 26, 282, 10.1108/01443570610646201 · DOI · Paper page
  23. Cagliano, 2000, Advanced manufacturing technologies and strategically flexible production, J. Oper. Manag., 18, 169, 10.1016/S0272-6963(99)00022-4 · DOI
  24. Caniato, 2013, The effect of global supply chain configuration on the relationship between supply chain improvement programs and performance, Int. J. Prod. Econ., 143, 285, 10.1016/j.ijpe.2012.05.019 · DOI
  25. Castelo-Branco, 2019, Assessing industry 4.0 readiness in manufacturing: evidence for the European union, Comput. Ind., 107, 22, 10.1016/j.compind.2019.01.007 · DOI · Paper page
  26. Cenamor, 2017, Adopting a platform approach in servitization: leveraging the value of digitalization, Int. J. Prod. Econ., 192, 54, 10.1016/j.ijpe.2016.12.033 · DOI · Paper page
  27. Chan, 2013, Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms, Int. J. Prod. Res., 51, 1196, 10.1080/00207543.2012.693961 · DOI
  28. Chandra, 2018, Exploring factors influencing organizational adoption of augmented reality in e-commerce: empirical analysis using technology-organization-environment model, J. Electron. Commer. Res., 19
  29. Chaudhuri, 2018, Supply chain integration, risk management and manufacturing flexibility, Int. J. Oper. Prod. Manag., 38, 690, 10.1108/IJOPM-08-2015-0508 · DOI · Paper page
  30. Chaudhuri, 2019, A socio-technical view of performance impact of integrated quality and sustainability strategies, Int. J. Prod. Res., 57, 1478, 10.1080/00207543.2018.1492162 · DOI
  31. Cheng, 2016, Interplant coordination, supply chain integration, and operational performance of a plant in a manufacturing network: a mediation analysis, Supply Chain Manag.: Int. J., 21, 550, 10.1108/SCM-10-2015-0391 · DOI
  32. Cheng, 2018, The evolution of investment patterns on advanced manufacturing technology (AMT) in manufacturing operations: a longitudinal analysis, Int. J. Prod. Econ., 203, 239, 10.1016/j.ijpe.2018.06.019 · DOI
  33. Chiarello, 2018, Extracting and mapping industry 4.0 technologies using wikipedia, Comput. Ind., 100, 244, 10.1016/j.compind.2018.04.006 · DOI · Paper page
  34. Collins, 2006, Knowledge exchange and combination: the role of human resource practices in the performance of high-technology firms, Acad. Manag. J., 49, 544, 10.5465/amj.2006.21794671 · DOI · Paper page
  35. Cruz-Jesus, 2019, Understanding CRM adoption stages: empirical analysis building on the TOE framework, Comput. Ind., 109, 1, 10.1016/j.compind.2019.03.007 · DOI · Paper page
  36. Cua, 2001, Relationships between implementation of TQM, JIT, and TPM and manufacturing performance, J. Oper. Manag., 19, 675, 10.1016/S0272-6963(01)00066-3 · DOI · Paper page
  37. Da Silveira, 2014, An empirical analysis of manufacturing competitive factors and offshoring, Int. J. Prod. Econ., 150, 163, 10.1016/j.ijpe.2013.12.031 · DOI
  38. Dalenogare, 2018, The expected contribution of Industry 4.0 technologies for industrial performance, Int. J. Prod. Econ., 204, 383, 10.1016/j.ijpe.2018.08.019 · DOI · Paper page
  39. Darbanhosseiniamirkhiz, 2012, Advanced manufacturing technology adoption in SMEs: an integrative model, J. Technol. Manag. Innovat., 7, 112, 10.4067/S0718-27242012000400009 · DOI
  40. Das, 2003, Relative importance of contingency variables for advanced manufacturing technology, Int. J. Prod. Res., 41, 4429, 10.1080/00207540310001595819 · DOI
  41. Depietro, 1990, vol. 199
  42. de Sousa Jabbour, 2018, When titans meet – can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors, Technol. Forecast. Soc. Change, 132, 18, 10.1016/j.techfore.2018.01.017 · DOI · Paper page
  43. De Weck, 2014, Trends in advanced manufacturing technology innovation, Prod. Innov. Econ., 235
  44. Demeter, 2003, Manufacturing strategy and competitiveness, Int. J. Prod. Econ., 81, 205, 10.1016/S0925-5273(02)00353-5 · DOI
  45. Demeter, 2011, Labour productivity change: drivers, business impact and macroeconomic moderators, Int. J. Prod. Econ., 131, 215, 10.1016/j.ijpe.2010.11.003 · DOI
  46. Diamantopoulos, 2001, Index construction with formative indicators: an alternative to scale development, J. Market. Res., 38, 269, 10.1509/jmkr.38.2.269.18845 · DOI · Paper page
  47. Dolgui, 2019, Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications, Int. J. Prod. Res., 57, 411, 10.1080/00207543.2018.1442948 · DOI · Paper page
  48. Dosi, 1994, Generalized urn schemes and technological dynamics, J. Math. Econ., 23, 1, 10.1016/0304-4068(94)90032-9 · doi:10.1016/0304-4068(94)90032-9
  49. Dubey, 2017, Ubiquitous manufacturing: overview, framework and further research directions, Int. J. Comput. Integrated Manuf., 30, 381
  50. Ehie, 2016, Analysis of manufacturing strategy in developing countries: a sample survey of Nigerian manufacturers, J. Manuf. Technol. Manag., 27, 234, 10.1108/JMTM-07-2014-0094 · DOI
  51. Esmaeilian, 2016, The evolution and future of manufacturing: a review, J. Manuf. Syst., 39, 79, 10.1016/j.jmsy.2016.03.001 · DOI · Paper page
  52. Falissard, 1999, The unidimensionality of a psychiatric scale: a statistical point of view, Int. J. Methods Psychiatr. Res., 8, 162, 10.1002/mpr.66 · DOI
  53. Farooq, 2017, Management of automation and advanced manufacturing technology (AAMT) in the context of global manufacturing, Int. J. Prod. Res., 55, 1455, 10.1080/00207543.2017.1296205 · doi:10.1080/00207543.2017.1296205
  54. Fatorachian, 2018, A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework, Prod. Plann. Contr., 1
  55. Frank, 2019, Industry 4.0 technologies: implementation patterns in manufacturing companies, Int. J. Prod. Econ., 210, 15, 10.1016/j.ijpe.2019.01.004 · DOI · Paper page
  56. Frank, 2019, Servitization and Industry 4.0 convergence in the digital transformation of product firms: a business model innovation perspective, Technol. Forecast. Soc. Change, 141, 341, 10.1016/j.techfore.2019.01.014 · DOI · Paper page
  57. Frohlich, 2001, A taxonomy of manufacturing strategies revisited, J. Oper. Manag., 19, 541, 10.1016/S0272-6963(01)00063-8 · DOI · Paper page
  58. Frohlich, 2001, Arcs of integration: an international study of supply chain strategies, J. Oper. Manag., 19, 185, 10.1016/S0272-6963(00)00055-3 · DOI · Paper page
  59. Gattullo, 2019, Towards augmented reality manuals for industry 4.0: a methodology, Robot. Comput. Integrated Manuf., 56, 276, 10.1016/j.rcim.2018.10.001 · DOI · Paper page
  60. Ghobakhloo, 2011, Adoption of e-commerce applications in SMEs, Ind. Manag. Data Syst., 111, 1238, 10.1108/02635571111170785 · DOI · Paper page
  61. Grundy, 2006, Rethinking and reinventing Michael Porter's five forces model, Strat. Change, 15, 213, 10.1002/jsc.764 · DOI · Paper page
  62. Gunasekaran, 2018, Agile manufacturing practices: the role of big data and business analytics with multiple case studies, Int. J. Prod. Res., 56, 385, 10.1080/00207543.2017.1395488 · DOI · Paper page
  63. Gutierrez, 2015, Technological, organisational and environmental factors influencing managers' decision to adopt cloud computing in the UK, J. Enterprise Inf. Manag., 28, 788, 10.1108/JEIM-01-2015-0001 · DOI · Paper page
  64. Hadjimanolis, 1999, Barriers to innovation for SMEs in a small less developed country (Cyprus), Technovation, 19, 561, 10.1016/S0166-4972(99)00034-6 · DOI · Paper page
  65. Haleem, 2017, Supplier corporate social responsibility practices and sourcing geography, J. Clean. Prod., 153, 92, 10.1016/j.jclepro.2017.03.143 · DOI
  66. Hallgren, 2009, Lean and agile manufacturing: external and internal drivers and performance outcomes, Int. J. Oper. Prod. Manag., 29, 976, 10.1108/01443570910993456 · DOI · Paper page
  67. Hernández-Espallardo, 2009, Product innovation in small manufacturers, market orientation and the industry's five competitive forces: empirical evidence from Spain, Eur. J. Innovat. Manag., 12, 470, 10.1108/14601060910996927 · DOI
  68. Hofmann, 2017, Industry 4.0 and the current status as well as future prospects on logistics, Comput. Ind., 89, 23, 10.1016/j.compind.2017.04.002 · DOI · Paper page
  69. Holmström, 2017, Sustainability outcomes through direct digital manufacturing-based operational practices: a design theory approach, J. Clean. Prod., 167, 951, 10.1016/j.jclepro.2017.03.092 · DOI
  70. Holmström, 2014, Digital manufacturing-driven transformations of service supply chains for complex products, Supply Chain Manag.: Int. J., 19, 421, 10.1108/SCM-10-2013-0387 · DOI · Paper page
  71. Hong, 2014, Strategic customer service orientation, lean manufacturing practices and performance outcomes: an empirical study, J. Serv. Manag., 25, 699, 10.1108/JOSM-12-2013-0355 · DOI
  72. Hong, 2019, Managing sustainability orientation: an empirical investigation of manufacturing firms, Int. J. Prod. Econ., 211, 71, 10.1016/j.ijpe.2019.01.035 · DOI
  73. Horbach, 2011, Building blocks for adaptable factory systems, Robot. Comput. Integrated Manuf., 27, 735, 10.1016/j.rcim.2010.12.011 · DOI
  74. Horváth, 2019, Driving forces and barriers of Industry 4.0: do multinational and small and medium-sized companies have equal opportunities?, Technol. Forecast. Soc. Change, 146, 119, 10.1016/j.techfore.2019.05.021 · DOI · Paper page
  75. Hsu, 2014, Examining cloud computing adoption intention, pricing mechanism, and deployment model, Int. J. Inf. Manag., 34, 474
  76. Hu, 1999, Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives, Struct. Equ. Model.: A multidiscip. J., 6, 1, 10.1080/10705519909540118 · DOI · Paper page
  77. Huo, 2014, The effects of competitive environment on supply chain information sharing and performance: an empirical study in China, Prod. Oper. Manag., 23, 552, 10.1111/poms.12044 · DOI · Paper page
  78. Ilin, 2017, Understanding the determinants of e-business adoption in ERP-enabled firms and non-ERP-enabled firms: a case study of the Western Balkan Peninsula, Technol. Forecast. Soc. Change, 125, 206, 10.1016/j.techfore.2017.07.025 · DOI
  79. Jajja, 2018, Impact of supply chain risk on agility performance: mediating role of supply chain integration, Int. J. Prod. Econ., 205, 118, 10.1016/j.ijpe.2018.08.032 · DOI · Paper page
  80. Kamble, 2018, Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry, Comput. Ind., 101, 107, 10.1016/j.compind.2018.06.004 · DOI · Paper page
  81. Kiel, 2017, The influence of the Industrial Internet of Things on business models of established manufacturing companies–A business level perspective, Technovation, 68, 4, 10.1016/j.technovation.2017.09.003 · DOI · Paper page
  82. Kim, 1988, Environment, generic strategies, and performance in a rapidly developing country: a taxonomic approach, Acad. Manag. J., 31, 802, 10.2307/256339 · DOI · Paper page
  83. Kosiba, 2018, Examining customer engagement and brand loyalty in retail banking: the trustworthiness influence, Int. J. Retail Distrib. Manag., 46, 764, 10.1108/IJRDM-08-2017-0163 · DOI
  84. Li, 2018, The digital transformation of business models in the creative industries: a holistic framework and emerging trends, Technovation
  85. Li, 2018, China's manufacturing locus in 2025: with a comparison of “Made-in-China 2025” and “Industry 4.0”, Technol. Forecast. Soc. Change, 135, 66, 10.1016/j.techfore.2017.05.028 · DOI · Paper page
  86. Lian, 2014, An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital, Int. J. Inf. Manag., 34, 28
  87. Liao, 2017, Past, present and future of Industry 4.0-a systematic literature review and research agenda proposal, Int. J. Prod. Res., 55, 3609, 10.1080/00207543.2017.1308576 · DOI · Paper page
  88. Lin, 2014, Understanding the determinants of electronic supply chain management system adoption: using the technology–organization–environment framework, Technol. Forecast. Soc. Change, 86, 80, 10.1016/j.techfore.2013.09.001 · DOI · Paper page
  89. Lindell, 1997, Global strategies of US and Scandinavian R&D-intensive small-and medium-sized companies, Eur. Manag. J., 15, 92, 10.1016/S0263-2373(96)00077-1 · doi:10.1016/s0263-2373(96)00077-1
  90. Mangla, 2018, Barriers to effective circular supply chain management in a developing country context, Prod. Plann. Contr., 29, 551, 10.1080/09537287.2018.1449265 · DOI · Paper page
  91. Marsh, 1985, Application of confirmatory factor analysis to the study of self-concept: first-and higher order factor models and their invariance across groups, Psychol. Bull., 97, 562, 10.1037/0033-2909.97.3.562 · doi:10.1037/0033-2909.97.3.562 · Paper page
  92. Martins, 2016, An empirical analysis to assess the determinants of SaaS diffusion in firms, Comput. Hum. Behav., 62, 19, 10.1016/j.chb.2016.03.049 · DOI · Paper page
  93. Masood, 2019, Augmented reality in support of Industry 4.0—implementation challenges and success factors, Robot. Comput. Integrated Manuf., 58, 181, 10.1016/j.rcim.2019.02.003 · DOI · Paper page
  94. Mellor, 2014, Additive manufacturing: a framework for implementation, Int. J. Prod. Econ., 149, 194, 10.1016/j.ijpe.2013.07.008 · DOI · Paper page
  95. Müller, 2018, Redundant configuration of robotic assembly lines with stochastic failures, Int. J. Prod. Res., 56, 3662, 10.1080/00207543.2017.1406672 · DOI
  96. Nunnally, 1967, vol. 226
  97. Oliveira, 2019, Understanding SaaS adoption: the moderating impact of the environment context, Int. J. Inf. Manag., 49, 1
  98. Oliveira, 2014, Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors, Inf. Manag., 51, 497, 10.1016/j.im.2014.03.006 · DOI · Paper page
  99. Ooi, 2018, Cloud computing in manufacturing: the next industrial revolution in Malaysia?, Expert Syst. Appl., 93, 376, 10.1016/j.eswa.2017.10.009 · DOI · Paper page
  100. Oztemel, 2018, Literature review of Industry 4.0 and related technologies, J. Intell. Manuf., 1
  101. Paashuis, 1997, Organizing for concurrent engineering: an integration mechanism framework, Integrated Manuf. Syst., 8, 79, 10.1108/09576069710165765 · DOI
  102. Peña-Vinces, 2012, Effect of ITC on the international competitiveness of firms, Manag. Decis., 50, 1045, 10.1108/00251741211238328 · doi:10.1108/00251741211238328
  103. Porter, 1991, Towards a dynamic theory of strategy, Strat. Manag. J., 12, 95, 10.1002/smj.4250121008 · DOI · Paper page
  104. Porter, 2008, The five competitive forces that shape strategy, Harv. Bus. Rev., 86, 78
  105. Puklavec, 2018, Understanding the determinants of business intelligence system adoption stages: an empirical study of SMEs, Ind. Manag. Data Syst., 118, 236, 10.1108/IMDS-05-2017-0170 · DOI · Paper page
  106. Ramanathan, 2017, Adoption of business analytics and impact on performance: a qualitative study in retail, Prod. Plann. Contr., 28, 985, 10.1080/09537287.2017.1336800 · DOI · Paper page
  107. Raymond, 2005, Antecedents and performance outcomes of advanced manufacturing systems sophistication in SMEs, Int. J. Oper. Prod. Manag., 25, 514, 10.1108/01443570510599692 · DOI
  108. Reischauer, 2018, Industry 4.0 as policy-driven discourse to institutionalize innovation systems in manufacturing, Technol. Forecast. Soc. Change, 132, 26, 10.1016/j.techfore.2018.02.012 · DOI · Paper page
  109. Rungtusanatham, 2014, Theorizing, testing, and concluding for mediation in SCM research: tutorial and procedural recommendations, J. Oper. Manag., 32, 99, 10.1016/j.jom.2014.01.002 · DOI · Paper page
  110. Rymaszewska, 2017, IoT powered servitization of manufacturing–an exploratory case study, Int. J. Prod. Econ., 192, 92, 10.1016/j.ijpe.2017.02.016 · DOI · Paper page
  111. Sabi, 2018, A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa, Inf. Syst. Front, 20, 1381, 10.1007/s10796-017-9739-1 · DOI
  112. Small, 1997, Developing a framework for the effective planning and implementation of advanced manufacturing technology, Int. J. Oper. Prod. Manag., 17, 468, 10.1108/01443579710167203 · doi:10.1108/01443579710167203
  113. Strozzi, 2017, Literature review on the ‘Smart Factory’concept using bibliometric tools, Int. J. Prod. Res., 55, 6572, 10.1080/00207543.2017.1326643 · DOI · Paper page
  114. Sun, 2018, Understanding the factors affecting the organizational adoption of big data, J. Comput. Inf. Syst., 58, 193
  115. Svahn, 2017, Embracing digital innovation in incumbent firms: how volvo cars managed competing concerns, MIS Q., 41, 10.25300/MISQ/2017/41.1.12 · DOI · Paper page
  116. Sveiby, 2002, Collaborative climate and effectiveness of knowledge work–an empirical study, J. Knowl. Manag., 6, 420, 10.1108/13673270210450388 · DOI · Paper page
  117. Swamidass, 1998, Explaining manufacturing technology use, firm size and performance using a multidimensional view of technology, J. Oper. Manag., 17, 23, 10.1016/S0272-6963(98)00016-3 · DOI · Paper page
  118. Swink, 2007, Capturing the competitive advantages of AMT: design–manufacturing integration as a complementary asset, J. Oper. Manag., 25, 736, 10.1016/j.jom.2006.07.001 · DOI · Paper page
  119. Swink, 2007, Managing beyond the factory walls: effects of four types of strategic integration on manufacturing plant performance, J. Oper. Manag., 25, 148, 10.1016/j.jom.2006.02.006 · DOI · Paper page
  120. Szalavetz, 2019, Industry 4.0 and capability development in manufacturing subsidiaries, Technol. Forecast. Soc. Change, 145, 384, 10.1016/j.techfore.2018.06.027 · DOI · Paper page
  121. Teece, 1996, Firm organization, industrial structure, and technological innovation, J. Econ. Behav. Org. Sci., 31, 193, 10.1016/S0167-2681(96)00895-5 · DOI · Paper page
  122. Thomé, 2016, Design-manufacturing integration and manufacturing complexity: a contingency investigation of job rotation and co-location, Int. J. Oper. Prod. Manag., 36, 1090, 10.1108/IJOPM-11-2014-0550 · DOI
  123. Tippins, 2003, IT competency and firm performance: is organizational learning a missing link?, Strat. Manag. J., 24, 745, 10.1002/smj.337 · DOI · Paper page
  124. Tortorella, 2018, Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies, Int. J. Prod. Res., 56, 2975, 10.1080/00207543.2017.1391420 · DOI · Paper page
  125. Tortorella, 2019, Industry 4.0 adoption as a moderator of the impact of lean production practices on operational performance improvement, Int. J. Oper. Prod. Manag., 39, 860, 10.1108/IJOPM-01-2019-0005 · DOI · Paper page
  126. Tracey, 1999, Manufacturing technology and strategy formulation: keys to enhancing competitiveness and improving performance, J. Oper. Manag., 17, 411, 10.1016/S0272-6963(98)00045-X · DOI · Paper page
  127. Tsou, 2015, Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: the case of the IT industry, Int. J. Inf. Manag., 35, 1
  128. Tushman, 1998, Dominant designs, technology cycles, and organization outcomes, vol. 1998, A1
  129. Vachon, 2008, Environmental management and manufacturing performance: the role of collaboration in the supply chain, Int. J. Prod. Econ., 111, 299, 10.1016/j.ijpe.2006.11.030 · DOI · Paper page
  130. Vinodh, 2009, Agility through rapid prototyping technology in a manufacturing environment using a 3D printer, J. Manuf. Technol. Manag., 20, 1023, 10.1108/17410380910984267 · DOI
  131. Voss, 1998, Differences in manufacturing strategy decisions between Japanese and Western manufacturing plants: the role of strategic time orientation, J. Oper. Manag., 16, 147, 10.1016/S0272-6963(97)00034-X · DOI
  132. Wadhwa, 2012, Flexibility in manufacturing automation: a living lab case study of Norwegian metal casting SMEs, J. Manuf. Syst., 31, 444, 10.1016/j.jmsy.2012.07.008 · DOI
  133. Wang, 2002, CAD/CAM integrated system in collaborative development environment, Robot. Comput. Integrated Manuf., 18, 135, 10.1016/S0736-5845(01)00027-8 · doi:10.1016/s0736-5845(01)00027-8
  134. Wang, 2016, Adoption of open government data among government agencies, Govern. Inf. Q., 33, 80, 10.1016/j.giq.2015.11.004 · DOI · Paper page
  135. Wiengarten, 2016, Risk, risk management practices, and the success of supply chain integration, Int. J. Prod. Econ., 171, 361, 10.1016/j.ijpe.2015.03.020 · DOI · Paper page
  136. Wiengarten, 2019, Re-evaluating supply chain integration and firm performance: linking operations strategy to supply chain strategy, Supply Chain Manag.: Int. J., 24, 540, 10.1108/SCM-05-2018-0189 · DOI
  137. Wu, 2014, A stage-based diffusion of IT innovation and the BSC performance impact: A moderator of technology–organization–environment, Technol. Forecast. Soc. Change, 88, 76, 10.1016/j.techfore.2014.06.015 · DOI
  138. Xu, 2018, Industry 4.0: state of the art and future trends, Int. J. Prod. Res., 56, 2941, 10.1080/00207543.2018.1444806 · DOI · Paper page
  139. Yang, 2010, Mediated effect of environmental management on manufacturing competitiveness: an empirical study, Int. J. Prod. Econ., 123, 210, 10.1016/j.ijpe.2009.08.017 · DOI · Paper page
  140. Yang, 2011, Impact of lean manufacturing and environmental management on business performance: an empirical study of manufacturing firms, Int. J. Prod. Econ., 129, 251, 10.1016/j.ijpe.2010.10.017 · DOI · Paper page
  141. Yin, 2018, The evolution of production systems from Industry 2.0 through Industry 4.0, Int. J. Prod. Res., 56, 848, 10.1080/00207543.2017.1403664 · DOI · Paper page
  142. Youn, 2015, Invention as a combinatorial process: evidence from US patents, J. R. Soc. Interface, 12, 20150272, 10.1098/rsif.2015.0272 · DOI · Paper page
  143. Yu, 2015, Computer-integrated manufacturing, cyber-physical systems and cloud manufacturing–concepts and relationships, Manuf. Lett., 6, 5, 10.1016/j.mfglet.2015.11.005 · DOI
  144. Zaiţ, 2011, Methods for testing discriminant validity, Manag. Market. J., 9, 217
  145. Zangiacomi, 2017, The implementation of digital technologies for operations management: a case study for manufacturing apps, Prod. Plann. Contr., 28, 1318, 10.1080/09537287.2017.1375142 · DOI
  146. Zelbst, 2010, Impact of RFID technology utilization on operational performance, Manag. Res. Rev., 33, 994, 10.1108/01409171011083996 · DOI
  147. Zelbst, 2012, Impact of RFID on manufacturing effectiveness and efficiency, Int. J. Oper. Prod. Manag., 32, 329, 10.1108/01443571211212600 · DOI
  148. Zhang, 2006, Achieving flexible manufacturing competence: the roles of advanced manufacturing technology and operations improvement practices, Int. J. Oper. Prod. Manag., 26, 580, 10.1108/01443570610666957 · DOI
  149. Zhao, 2008, The impact of power and relationship commitment on the integration between manufacturers and customers in a supply chain, J. Oper. Manag., 26, 368, 10.1016/j.jom.2007.08.002 · DOI · Paper page
  150. Zhu, 2006, Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies, Eur. J. Inf. Syst., 15, 601, 10.1057/palgrave.ejis.3000650 · DOI · Paper page
  151. Zhu, 2005, Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry, Inf. Syst. Res., 16, 61, 10.1287/isre.1050.0045 · DOI · Paper page
  152. Zuehlke, 2010, Smart Factory—towards a factory-of-things, Annu. Rev. Contr., 34, 129, 10.1016/j.arcontrol.2010.02.008 · DOI · Paper page

Cited by

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Metadata

Authors
Gillani, F., Chatha, K. A., Sadiq Jajja, M. S., & Farooq, S.
Venue
International Journal of Production Economics
Publisher
Elsevier BV
Published
2020-11
Volume
229
Pages
107748
ISSN
0925-5273 (ISSN-L)
OpenAlex
W3021635736
Cited by
209
References
19
FWCI
18.38
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)

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This page
CoChat. (2026). Citation check: Implementation of digital manufacturing technologies: Antecedents and consequences. https://app.cochat.ai/papers/10.1016/j.ijpe.2020.107748
The paper
Gillani, F., Chatha, K. A., Sadiq Jajja, M. S., & Farooq, S. (2020). Implementation of digital manufacturing technologies: Antecedents and consequences. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2020.107748

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.