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The impact of IoT on manufacturing firm performance: the moderating role of firm-level IoT commitment and expertise

物联网 业务 集合(抽象数据类型) 营销 产业组织 知识管理 计算机科学 计算机安全 程序设计语言
作者
Aishwarya Dash,Pushpesh Pant,S.P. Sarmah,Manoj Kumar Tiwari
出处
期刊:International Journal of Production Research [Taylor & Francis]
卷期号:62 (9): 3120-3145 被引量:3
标识
DOI:10.1080/00207543.2023.2218499
摘要

AbstractThe Internet of Things has received enormous attention. Despite the lucrative potential, this study tries to look beyond the hype to understand how IoT impacts firm performance. Based on the information processing theory, we intend to explore how IoT influences the financial performance of firms. Firms, which realise the urgent need to adopt IoT might encounter a diverse set of challenges, like whether adoption will be profitable, the level of commitment they should devote, and whether to adopt as a first or second-mover. We want to comprehend such adoption challenges on the Indian manufacturing firm's financial performance. This study uses panel data from BSE 500 listed manufacturing firms and conducts multivariate analysis to understand the relationship between the IoT implementation proxies: IoT adoption, first-mover advantage, and firm performance in the light of IoT commitment and experts. The result indicates that IoT implementation has an insignificant effect on manufacturing firm performance. Meanwhile, the consideration of IoT commitment and experts jointly can enable a manufacturing firm to reap significantly positive financial outcomes. In other words, the IoT commitment and expertise positively moderate the relationship. The finding is useful to the decision-makers to address the firm-level adjustment before the mere introduction of IoT.KEYWORDS: IoT adoptionIoT commitmentfirst-mover advantageinformation processing theoryIndustry 4.0firm performanceView correction statement:Correction Notice Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data of the study are available from the first author, A. Dash. It can be accessed upon reasonable request.Additional informationNotes on contributorsAishwarya DashMiss Aishwarya Dash has completed Ph.D. from the Department of Industrial and Systems Engineering at the Indian Institute of Technology Kharagpur, India in 2023. She has worked under the supervision of Prof. S P Sarmah (IIT Kharagpur, India) and Prof. M K Tiwari (IIT Kharagpur, India) during her Ph.D. She received an M.Tech. degree in Industrial Engineering & Management from CET, Bhubaneswar, in 2017 and a B.Tech. degree in Mechanical Engineering from IGIT Sarang, India, in 2015. Her research interests are digital (Industry 4.0) supply chain, cybersecurity, food supply chain and counterfeit products. She has articles in publications that are indexed by SCI and ABDC (categories A, B, and C).Pushpesh PantDr. Pushpesh Pant is an Assistant Professor of Operations at IMT Hyderabad. Earlier, he was associated with NMIMS Hyderabad Campus as an assistant professor. He has done his Ph.D. from IIT Kharagpur. He has worked under the supervision of two leading researchers in their area: Prof. SP Sarmah (IIT Kharagpur, India) and Prof. Shantanu Dutta (University of Ottawa, Canada) during his Ph.D. tenure. He has published in ABDC (category A, B, and C) and SCI indexed journals like the International Journal of Logistics Management, International Journal of Emerging Markets, Maritime Policy and Management, Plos One, Technology and Disability, Management of Environmental Quality, among others. Professor Pant has also participated and presented papers in scholarly conferences. His research interests include panel data modelling, empirical analysis, multivariate statistical modelling, supply chain finance, corporate governance, blockchain, text analytics, technology forecasting, and data mining. Currently, he serves as an article editor of SAGE open (SSCI journal) and reviewer of Computer and Industrial Engineering (SCI, ABDC A).S. P. SarmahProf. Sarada Prasad Sarmah received a Ph.D. degree in supply chain management from the Indian Institute of Technology, Kharagpur, West Bengal, India, in 2003. He is currently working as a professor, at the Department of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur. His research interests include supply chain coordination and contract design, supply chain risk management, and reverse logistics and optimisation. He is the Investigator of several high-valued research projects sponsored by the Ministry of Human Resource Development, the Government of India, and industrial consultancy projects. His contributions are published in many reputed journals including the European Journal of Operational Research, the International Journal of Production Economics, Transportation Research Part E: Logistics and Transportation Review, Computers and Industrial Engineering, Applied Mathematical Modelling, and Applied Intelligence.M. K. TiwariProf. Manoj Kumar Tiwari (FNAE, FNASc, FIISE) is Director, National Institute of Industrial Engineering (NITIE), Mumbai, India. He is also a Professor in the Department of Industrial and Systems Engineering at the Indian Institute of Technology, Kharagpur, India. He received BE in Mechanical Engineering from Visvesvaraya National Institute of Technology, Nagpur, India, in 1986, M Tech in Production Engineering from Motilal Nehru National Institute of Technology, Prayagraj, India, in 1990, and Ph.D. in the Department of Production Engineering from University of Jadavpur. He is actively involved in research relevant to the applications of optimisation, modelling, decision support systems, and data mining in the domain of logistics, supply chain management, and manufacturing systems.Correction StatementThis article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/00207543.2023.2229992)
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