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Articles

Evaluating readiness degree for Industrial Internet of Things adoption in manufacturing enterprises under interval-valued Pythagorean fuzzy approach

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Pages 226-256 | Received 30 Dec 2020, Accepted 05 Apr 2022, Published online: 01 Jun 2022

References

  • Bakioglu, G., & Atahan, A. O. (2021). AHP integrated TOPSIS and VIKOR methods with pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Applied Soft Computing Journal, 99, February, 106948. https://doi.org/10.1016/j.asoc.2020.106948
  • Ben-Daya, M., Hassini, E., & Bahroun, Z. (2017). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4719–4742. https://doi.org/10.1080/00207543.2017.1402140.
  • Bogicevic, V., Bujisic, M., Bilgihan, A., Yang, W., & Cobanoglu, C. (2017). The impact of traveler-focused airport technology on traveler satisfaction. Technological Forecasting and Social Change, 123, October, 351–361. https://doi.org/10.1016/j.techfore.2017.03.038
  • Breunig, M., Kelly, R., Mathis, R., & Wee, D. (2016). Getting the Most Out of Industry 4.0. Retrieved October 26, 2020, from. https://www.mckinsey.com/business-functions/operations/our-insights/industry-40-looking-beyond-the-initial-hype Mckinsey & Company
  • Bruijn, H., & Janssen, M. (2017). Building cybersecurity awareness: the need for evidence-based framing strategies. Government Information Quarterly, 34(1), 1–7. https://doi.org/10.1016/j.giq.2017.02.007
  • Buer, S. V., Strandhagen, J. O., & 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), 2924–2940. https://doi.org/10.1080/00207543.2018.1442945.
  • Bughin, J., & van Zeebroeck, N. (). The best response to digital disruption. MIT Sloan Management Review 26 october 2020 https://sloanrview.mit.edu/article/the-right-response-to-digital-disruption,),
  • Büschgens, T., Bausch, A., & Balkin, D. B. (2013). Organizational culture and innovation: A meta analytic review. Journal of Product Innovation Management, 30(4), 763–781. https://doi.org/10.1111/jpim.12021
  • 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(C), 383–394. https://doi.org/10.1016/j.ijpe.2018.08.019
  • Davis, J., Edgar, T., Graybill, R., Korambath, P., Schott, B., Swink, D., Wetzel, J., & Wetzel, J. (2015). Smart manufacturing. Annual Review of Chemical and Biomolecular Engineering, 6(1), 141–160. https://doi.org/10.1146/annurev-chembioeng-061114-123255
  • Díaz, M., Martín, C., & Rubio, B. (2016). State-of-the-art, challenges, and open issues in the integration of internet of things and cloud computing. Journal of Network and Computer Applications, 67(May), 99–117. https://doi.org/10.1016/j.jnca.2016.01.010
  • Du, Y., Hou, F., Zafar, W., Yu, Q., & Zhai, Y. (2017). A novel method for multiattribute decision making with interval-valued pythagorean fuzzy linguistic information. International Journal of Intelligent Systems, 32(10), 1085–1112. https://doi.org/10.1002/int.21881
  • Duerr, S., Holotiuk, F., Wagner, H.T., Beimborn, D., & Weitzel, T. (2018). What is digital organizational culture? insights from exploratory case studies. Proceedings of the 51st Hawaii International Conference on System Sciences. Hawaii, (pp. 5126–5135). HICSS 2018. https://doi.org/10.24251/HICSS.2018.640 ISBN: 978-09981331-1-9
  • Fischer, C., & Pöhler, A. (2018). Supporting the change to digitalized production environments through learning organization development. In C. Harteis (Ed.), The impact of digitalization in the workplace: an educational view (pp. 141–160). Springer International Publishing.
  • Frank, A. G., Mendes, G. H. S., Ayala, N. F., & Ghezzi, A. (2019). Servitization and industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective. Technological Forecasting and Social Change, 141, April, 341–351. https://doi.org/10.1016/j.techfore.2019.01.014.
  • Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of Enterprise Information Management, 28(1), 107–130. https://doi.org/10.1108/JEIM-08-2013-0065
  • Genpact Research Institute (2016) Industrial internet and lean digitalSM: generating “machine to P&LSM” impact. https://www.genpact.com/downloadable-content/industrial-internet-and-lean-digital-generating-machine-to-p-and-l-impact.pdf. Accessed on October 11, 2020
  • Ghanbari, A., Laya, A., Alonso-Zarate, J., & Markendahl, J. (2017). Business development in the internet of things: A matter of vertical cooperation. IEEE Communications Magazine, 55(2), 135–141. https://doi.org/10.1109/MCOM.2017.1600596CM
  • Ghobakhloo, M. (2018). The future of manufacturing industry: A strategic roadmap toward industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936. https://doi.org/10.1108/JMTM-02-2018-0057
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3), 179–188. https://doi.org/10.1007/s12525-015-0196-8
  • Gul, M. (2018). Application of pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: The case of a gun and rifle barrel external surface oxidation and colouring unit. International Journal of Occupational Safety and Ergonomics, 26(4), 705–718. https://doi.org/10.1080/10803548.2018.1492251
  • Gul, M., & Ak, M. F. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, September, 653–664. https://doi.org/10.1016/j.jclepro.2018.06.106
  • Haktanır, E., & Kahraman, C. (2019). A novel interval-valued pythagorean fuzzy QFD method and its application to solar photovoltaic technology development. Computers & Industrial Engineering, 132, June 361–372. https://doi.org/10.1016/j.cie.2019.04.022
  • Hasselblatt, M., Huikkola, T., Kohtamäki, M., & Nickell, D. (2018). Modeling manufacturer’s capabilities for the internet of things. Journal of Business & Industrial Marketing, 33(6), 822–836. https://doi.org/10.1108/JBIM-11-2015-0225.
  • Hecklau, F., Galeitzke, M., Flachs, S., & Kohl, H. (2016). Holistic approach for human resource management in industry 4.0 6th CLF-6th CIRP Conference on Leanring Factories, Procedia CIRP 29-30 Jun, 2016 Norway, 54, 1–6. https://doi.org/10.1016/j.procir.2016.05.102
  • Horváth, D., & Szabó, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146. September, 119–132. https://doi.org/10.1016/j.techfore.2019.05.021
  • Hsu, C. W., & Yeh, C. C. (2017). Understanding the factors affecting the adoption of the Internet of Things. Technology Analysis and Strategic Management, 29(9), 1089–1102. https://doi.org/10.1080/09537325.2016.1269160.
  • Hughes, B. B., Bohl, D., Irfan, M., Margolese-Malin, E., & Solórzano, J. R. (2017). ICT/Cyber benefits and costs: Reconciling competing perspectives on the current and future balance. Technological Forecasting and Social Change, 115(February), 117–130 http://dx.doi.org/10.1016/j.techfore.2016.09.027
  • IIbahar, E., Karasan, A., Cebi, S., & Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103(March), 124–136. https://doi.org/10.1016/j.ssci.2017.10.025
  • Ikävalko, H., Turkama, P., & Smedlund, A. (2018). Value creation in the internet of things: Mapping business models and ecosystem roles. Technology Innovation Management Review, 8(3), 5–15. https://doi.org/10.22215/timreview/1142
  • Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of big data analytics and supply chain management. International Journal of Operations & Production Management, 37(1), 10–36. https://doi.org/10.1108/IJOPM-02-2015-0078
  • Kamble, S. S., Gunasekaran, A., Parekh, H., & Joshi, S. (2019). Modeling the internet of things adoption barriers in food retail supply chains. Journal of Retailing and Consumer Services, 48(May), 154–168. https://doi.org/10.1016/j.jretconser.2019.02.020
  • Kamble, S. S., Gunasekaran, A., & Sharma, R. (2018). Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Computers in Industry, 101(October), 107–119. https://doi.org/10.1016/j.compind.2018.06.004
  • Karkouch, A., Mousannif, H., Moatassime, H. A., & Noel, T. (2016). A model-driven architecture-based data quality management framework for the internet of things. Proceedings of 2016, the 2nd international conference on cloud computing technologies and applications, cloud tech 24-26 May 2016, Marrakech, Morocco (pp. 252–259). IEEE. https://doi.org/10.1109/cloudTech.2016.7847707
  • Khan, M. A., & Salah, K. (2018). IoT security: Review, blockchain solutions, and open challenges. Future Generation Computer Systems, 82(May), 395–411. https://doi.org/10.1016/j.future.2017.11.022
  • Kiel, D., Arnold, C., & Voigt, K. I. (2017). The influence of the industrial internet of things on business models of established manufacturing companies – A business level perspective. Technovation, 68,(December), 4–19. https://doi.org/10.1016/j.technovation.2017.09.003
  • Kovács, O. (2018). The dark corners of industry 4.0 – Grounding economic governance 2.0. Technology in Society, 55(November), 140–145. https://doi.org/10.1016/j.techsoc.2018.07.009
  • Lee, I., & Lee, K. (2015). The internet of things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440. https://doi.org/10.1016/j.bushor.2015.03.008
  • Lerch, C., & Gotsch, M. (2015). Digitalized product-service systems in manufacturing firms: A case study analysis. Research-Technology Management, 58(5), 45–52. https://doi.org/10.5437/08956308X5805357
  • Lokuge, S., Sedera, D., Grover, V., & Xu, D. (2019). Organizational readiness for digital innovation: development and empirical calibration of a construct. Information & Management, 56(3), 445–461. https://doi.org/10.1016/j.im.2018.09.001
  • Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6(June), 1–10. https://doi.org/10.1016/j.jii.2017.04.005
  • Majeed, A. A., & Rupasinghe, T. D. (2017). Internet of Things (IoT) embedded future supply chains for industry 4.0: An assessment from an ERP-based fashion apparel and footwear industry. International Journal of Supply Chain Management, 6(1), 25–40.
  • Malviya, R. K., & Kant, R. (2016). Hybrid decision making approach to predict and measure the success possibility of green supply chain management implementation. Journal of Cleaner Production, 135(November), 387–409. https://doi.org/10.1016/j.jclepro.2016.06.046
  • Martinez-Caro, E., Cegarra-Navarro, J. G., & Alfonso-Ruiz, F.J. ((2020)). Digital technologies and firm performance: the role of digital organisational culture. Technological Forecasting and Social Change, 154(May), https://doi.org/10.1016/j.techfore.2020.119962 119962
  • 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. the 51st CIRP Conference on Manufacturing Systems, Procedia CIRP 16-18 May 2018 Stockholm, Sweden 72 (Procedia CIRP): 622–628. https://doi.org/10.1016/j.procir.2018.03.292
  • Mital, M., Choudhary, P., Chang, V., 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(November), 339–346. https://doi.org/10.1016/j.techfore.2017.03.001.
  • Mohagheghi, V., Mousavi, S. M., Mojtahedi, M., & Newton, S. (2020). Evaluating large, high-technology project portfolios using a novel interval-valued phygorean fuzzy set framework: an automated crane project case study. Expert Systems With Applications, 162(December), 113007. https://doi.org/10.1016/j.eswa.2019.113007
  • Müller, J. M., Kiel, D., & Voigt, K. I. (2018). What drives the implementation of industry 4.0? the role of opportunities and challenges in the context of sustainability. Sustainability, 10(1), 247. https://doi.org/10.3390/su10010247
  • Ng, I., Scharf, K., Pogrebna, G., & Maull, R. (2015). Contextual variety, Internet-of-Things and the choice of tailoring over platform: Mass customisation strategy in supply chain management. International Journal of Production Economics, 159(January), 76–87. https://doi.org/10.1016/j.ijpe.2014.09.007
  • Nolich, M., Spoladore, D., Carciotti, S., Buqi, R., & Sacco, M. (2019). Cabin as a home: A novel comfort optimization framework for IoT equipped smart environments and applications on cruise ships. Sensors, 19(5), 1060–1084. https://doi.org/10.3390/s19051060
  • Oliveira, T., Martins, R., Sarker, S., Thomas, M., & Popovič, A. (2019). Understanding SaaS adoption: The moderating impact of the environment context. International Journal of Information Management, 49(December), 1–12. https://doi.org/10.1016/j.ijinfomgt.2019.02.009
  • Ouaddah, A., Mousannif, H., Elkalam, A. A., & Ouahman, A. A. (2017). Access control in the internet of things: Big challenges and new opportunities. Computer Networks, 112(January), 237–262. https://doi.org/10.1016/j.comnet.2016.11.007
  • Parry, G. C., Brax, S. A., Maull, R. S., & Ng, I. C. L. (2016). Operationalising IoT for reverse supply: The development of use-visibility measures. Supply Chain Management: An International Journal, 21(2), 228–244. https://doi.org/10.1108/SCM-10-2015-0386
  • Peng, X., & Yang, Y. (2016). Fundamental properties of interval-valued pythagorean fuzzy aggregation operators. International Journal of Intelligent Systems, 31(5), 444–487. https://doi.org/10.1002/int.21790
  • Perez-Dominguez, L., Alvarado-Iniesta, A., Garca-Alcaraz, J. L., & Valles-Rosales, D. J. (2018b). Intutionistic fuzzy dimensional analysis for multi-criteria decision making. Iranian Journal of Fuzzy Systems, 15(6), 17–40. http://doi.org/10.22111/IJFS.2018.4363
  • Perez-Dominguez, L., Rodriguez-Picon, L. A., Alvarado-Iniesta, A., Cruz, D. L., & Xu, Z. (2018a). MOORA under pythagorean fuzzy set for multiple criteria decision making. Complexity, 2018, 1–10. https://doi.org/10.1155/2018/2602376.
  • Raj, A., Dwivedi, G., Sharma, A., Jabbour, D. S. 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(June), 107546. https://doi.org/10.1016/j.ijpe.2019.107546
  • Rajput, S., & Singh, S. P. (2019). Industry 4.0- challenges to implement circular economy. Benchmarking. An International Journal, 57(June), 315–338. https://doi.org/10.1108/BIJ-12-2018-0430
  • Raut, R., Priyadarshinee, P., Jha, M., Gardas, B. B., & Kamble, S. (2018). Modeling the implementation barriers of cloud computing adoption: An interpretive structural modeling. Benchmarking: An International Journal, 25(8), 2760–2782. https://doi.org/10.1108/BIJ-12-2016-0189
  • Reaidy, P. J., Gunasekaran, A., & Spalanzani, A. (2015). Bottom-up approach based on Internet of Things for order fulfillment in a collaborative warehousing environment. International Journal of Production Economics, 159(January), 29–40. https://doi.org/10.1016/j.ijpe.2014.02.017
  • Ryan, P. J., & Watson, R. B. (2017). Research challenges for the internet of things: What role can OR play? Systems, 5(1), 1–32. https://doi.org/10.3390/systems5010024
  • Rymaszewska, A., Helo, P., & Gunasekaran, A. (2017). IoT powered servitization of manufacturing – An exploratory case study. International Journal of Production Economics, 192(October), 92–105. http://dx.doi.org/10.1016/j.ijpe.2017.02.016.
  • Sarvari, P. A., Ustundag, A., Cevikcan, E., Kaya, I., & Cebi, S. (2018). Technology roadmap for industry 4.0: industry 4.0: managing the digital transformation (pp. 95–103). Springer International Publishing. https://doi.org/10.1007/978-3-319-57870-5_5
  • Schallock, B., Rybski, C., Jochem, R., & Kohl, H. (2018). Learning factory for industry 4.0 to provide future skills beyond technical training the 8th Conference on Learing Factories 2018 (CLF 2018) - Advanced Engineering Education & Tranining for Manufacturing Innovation 12-13 April 2018 Patras, Greece. 23 (Elsevier Procedia), 27–32. https://doi.org/10.1016/j.promfg.2018.03.156
  • Seiti, H., Hafezalkotob, A., Najafi, S. E., & Khalaj, M. (2019). Developing a novel risk-based MCDM approach based on D numbers and fuzzy information axiom and its applications in preventive maintenance planning. Applied Soft Computing, 82(September), 105559. https://doi.org/10.1016/j.asoc.2019.105559
  • Sivathanu, B. B., & Pillai, B. Smart HR 4.0 – How industry 4.0 is disrupting HR. (2018). Human Resource Management International Digest, 26(4), 7–11. available at. https://doi.org/10.1108/HRMID-04-2018-0059
  • Sony, M., & Naik, S. (2019). Key ingredients for evaluating industry 4.0 readiness for organizations: a literature review. Benchmarking: An International Journal, 27(7), 2213–2232. https://doi.org/10.1108/BIJ-09-2018-0284
  • Tang, Y., & Yang, Y. (2021). Sustainable e-bike sharing recycling supplier selection: an interval-valued pythagorean fuzzy MAGDM method based on preference information technology. Journal of Cleaner Production, 287(March), 125530. https://doi.org/10.1016/j.jclepro.2020.125530
  • Trappey, A. J.C., Trappey, C. V., Govindarajan, U. H., Chuang, A. C., & Sun, J. J. (2017). A review of essential standards and patent landscapes for the internet of things: A key enabler for industry4.0. Advanced Engineering Informatics, 33(August), 208–229. https://doi.org/10.1016/j.aei.2016.11.007.
  • Vey, K., Fandel-Meyer, T., Zipp, J. S., & Schneider, C. (2017). Learning & development in times of digital transformation: Facilitating a culture of change and innovation. International Journal of Advanced Corporate Learning, 10(1), 22–32. https://doi.org/10.3991/ijac.v10i1.6334
  • Wang, B., Zhao, J. Y., Wan, Z. G., Ma, J. H., Li, H., & Ma, J. (2016). Lean intelligent production system and value stream practice. Proceedings of the 3rd International Conference on Economics and Management, ICEM 2016, 2-3 July, 2016 (Publons) Suzhou, Jiangsu, China, 442–448. https://doi.org/10.12783/DTEM/ICEM2016/4106.
  • Yager R.R. (2014). Phyhagorean membership grades in multi-criteria decision making. IEEE Transactions on Fuzzy Systems, 22(4), 958–965.
  • Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model. Computers in Human Behavior, 45(April), 254–264. https://doi.org/10.1016/j.chb.2014.12.022
  • Yu, C., Shao, Y., Wang, K., & Zhang, L. (2019). A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued phythagorean fuzzy environment. Expert Systems With Applications, 121(C), 1–17. https://doi.org/10.1016/j.eswa.2018.12.010.
  • Yucesan, M., & Gul, M. (2020). Hospital service quality evaluation: An integrated model based on pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Computing, 24(5), 3237–3255. https://doi.org/10.1007/s00500-019-04084-2
  • Yucesan, M., & Kahraman, G. (2019). Risk evaluation and prevention in hydropower plant operations: A model based on pythagorean fuzzy AHP. Energy Policy, 126(March), 343–351. https://doi.org/10.1016/j.enpol.2018.11.039
  • Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning–I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5