Submission deadline: May 31st, 2022
☆☆☆Special Issue Editors
Managing Guest Editor:
Zhong-Zhong Jiang, Professor of Operations Management, School of Business Administration, Northeastern University, China， firstname.lastname@example.org
Hubert Pun, Associate Professor of Management Science, Ivey Business School, Western University, Canada, email@example.com
Yeming Gong, Professor of Management Science, EMLYON Business School, France, firstname.lastname@example.org
Xiaolong Guo, Associate Professor of Operations Management, School of Management, University of Science and Technology of China, China, email@example.com
Service-oriented manufacturing (SOM, also known as product servicisation or servitisation) is an emerging business paradigm that forms a critical part of the transformation of economic structure in Industry 4.0 (Huang, Chen, Sun, Zhang, & Yao, 2020; Rymaszewska, Helo, & Gunasekaran, 2017; Visnjic Kastalli & Van Looy, 2013). With SOM, manufacturers gradually change products to platforms as they implement and promote Industry 4.0 technologies. These products then become carriers of communication between manufacturers and customers. Consequently, manufacturers earn revenue not only for sales of their products, but according to the service and utility delivered by those products (He, Jiang, Wang, Sun, & Xie, 2020; Zhen, 2012). As an example of SOM, Rolls-Royce provides pay-by-the-hour contracts for customers’ use of its engines, while BMW and Ford both offer arrangements that charge customers based on their mileage or driving time (Jiang, Feng, & Yi, 2021).
This shift to SOM will enhance information flows delivered through the carriers and potential demand for side-line ranges of products. More specifically, for manufacturers producing correlated products and services, the traditional supply chain network will be transformed into an ecosystem of interactions among the relevant players, including suppliers, manufacturers, customers, and end consumers (Kohtamaki, Parida, Oghazi, Gebauer, & Baines, 2019; Rasouli, 2020). For instance, as a leading manufacturer in the era of Industry 4.0, Haier has already developed such a manufacturing ecosystem with product servicisation. To date, this platform, COSMOPlat (cosmoplat.com), hosts 3.9 million suppliers and 340 million customers.
With the support of digital technologies, such as Internet of Things, artificial intelligence, big data, and blockchain, the service quality provided by service-oriented manufacturers (SOMers) can be improved and personalised for individual customers. SOMers are able to collect customers’ usage information on their products through digital technologies, and then apply this information to better understand customers’ preferences on both products and services (Crossler & Belanger, 2019; Suppatvech, Godsell, & Day, 2019). This process helps SOMers develop more attractive products and services, such as those involving customer-driven product design, personalised maintenance, and product lifecycle management. As a result, SOM is considered a more sustainable, profitable, and customer-friendly business model (Agrawal & Bellos, 2017; Orsdemir, Deshpande, & Parlakturk, 2019).
At the same time, the transformation driven by SOM reshapes the power structure and the trading relationships between members of traditional manufacturing supply chains. The result—a so-called “SOM supply chain”—poses a wide range of new operational challenges (Jiang, Feng, Yi, & Guo, 2021; Jiang, He, Qin, Sun, & Wang, 2021; Luo, Guan, He, Gong, & Yue, 2021; Pun, Swaminathan, & Hou, 2021; Raddats, Kowalkowski, Benedettini, Burton, & Gebauer, 2019), including product quality design, reliability management, maintenance support, spare inventories, customer relationship management, privacy concerns, and supply chain contracting.
2. Potential Research Topics
With the celebration of the 60th anniversary of the International Journal of Production Research (IJPR), the purpose of this special issue is to publish high-quality original research and review articles that explore research questions for SOM supply chain management in Industry 4.0. Research papers with quantitative and qualitative methodologies, such as empirical studies, analytical studies, data-driven optimisation, and simulation, are all welcomed.
This special issue will adhere to IJPR’s standard of publishing cutting-edge, relevant, and rigorous work that fills existing research gaps. Accordingly, we welcome novel submissions that are neither published nor currently under review elsewhere.
Potential topics include, but are not limited to, the following:
△Contracting and maintenance support in SOM supply chains
△New product development and service innovation in SOM supply chains
△Quality design and reliability management in SOM supply chains
△Behaviour modelling and customer relationship management with SOM (e.g., fairness concerns, reference effect, behaviour-based pricing, customers' privacy concerns, etc.)
△Sustainable operations of SOM with emerging business models, relevant to the sharing economy, crowdfunding, and crowdsourcing
△Product line design and pricing optimisation in SOM supply chains
△Data-driven innovations of SOM supply chains
△Mechanism and governance scheme design for SOM supply chains as ecosystems
△Applications of digital technologies in SOM supply chains (e.g., Internet of Things, blockchain, artificial intelligence, and big data)
△Service-oriented smart manufacturing and Robot as a Service (RaaS)
△Digital twin technology and SOM
△Technology management of SOM supply chains
3. Submission Requirements
Manuscripts should not have been previously published nor be currently under consideration for publication elsewhere. Manuscripts should be submitted via the IJPR submission site: https://mc.manuscriptcentral.com/tprs.
During the submission process, please select “Service-oriented Manufacturing Supply Chain Management in Industry 4.0” from the special issue dropdown menu. For Guide for Authors, please refer to the webpage:
4. Publication Schedule
The submission deadline is May 31st, 2022.
The special issue is scheduled for publication in 2023.
Agrawal, V. V., & Bellos, I. (2017). The potential of servicizing as a green business model. Management Science, 63(5), 1545-1562. https://doi.org/10.1287/mnsc.2015.2399
Crossler, R. E., & Belanger, F. (2019). Why would I use location-protective settings on my smartphone? Motivating protective behaviors and the existence of the privacy knowledge-belief gap. Information Systems Research, 30(3), 995-1006. https://doi.org/10.1287/isre.2019.0846
He, N., Jiang, Z.-Z., Wang, J., Sun, M. H., & Xie, G. H. (2020). Maintenance optimisation and coordination with fairness concerns for the service-oriented manufacturing supply chain. Enterprise Information Systems, 15(5), 694-724. https://doi.org/10.1080/17517575.2020.1746406
Huang, F., Chen, J. H., Sun, L. H., Zhang, Y. Q., & Yao, S. J. (2020). Value-based contract for smart operation and maintenance service based on equitable entropy. International Journal of Production Research, 58(4), 1271-1284. https://doi.org/10.1080/00207543.2019.1617450
Jiang, Z.-Z., Feng, G., & Yi, Z. (2021). How should a capital-constrained servicizing manufacturer search for financing? The impact of supply chain leadership. Transportation Research Part E: Logistics and Transportation Review, 145, 102162. https://doi.org/10.1016/j.tre.2020.102162
Jiang, Z.-Z., Feng, G., Yi, Z., & Guo, X. (2021). Service-oriented manufacturing: A literature review and future research directions. Frontiers of Engineering Management, forthcoming, https://doi.org/10.1007/s42524-021-0171-3
Jiang, Z.-Z., He, N., Qin, X., Sun, M., & Wang, P. (2021). Optimizing production and maintenance for the service-oriented manufacturing supply chain. Annals of Operations Research, 1-26. https://doi.org/10.1007/s10479-020-03758-7
Kohtamaki, M., Parida, V., Oghazi, P., Gebauer, H., & Baines, T. (2019). Digital servitization business models in ecosystems: A theory of the firm. Journal of Business Research, 104, 380-392. https://doi.org/10.1016/j.jbusres.2019.06.027
Luo, D., Guan, Z., He, C., Gong, Y., & Yue, L. (2021). Data-driven cloud simulation architecture for automated flexible production lines: application in real smart factories. International Journal of Production Research, 1-23. https://doi.org/10.1080/00207543.2021.1931977
Orsdemir, A., Deshpande, V., & Parlakturk, A. K. (2019). Is servicization a win-win strategy? Profitability and environmental implications of servicization. Manufacturing & Service Operations Management, 21(3), 674-691. https://doi.org/10.1287/msom.2018.0718
Pun, H., Swaminathan, J., & Hou, P. (2021). Blockchain adoption for combating deceptive counterfeits. Production and Operations Management, 30(4), 864-882. https://doi.org/10.1111/poms.13348
Raddats, C., Kowalkowski, C., Benedettini, O., Burton, J., & Gebauer, H. (2019). Servitization: A contemporary thematic review of four major research streams. Industrial Marketing Management, 83, 207-223. https://doi.org/10.1016/j.indmarman.2019.03.015
Rasouli, M. R. (2020). An architecture for IoT-enabled intelligent process-aware cloud production platform: A case study in a networked cloud clinical laboratory. International Journal of Production Research, 58(12), 3765-3780. https://doi.org/10.1080/00207543.2019.1634847
Rymaszewska, A., Helo, P., & Gunasekaran, A. (2017). IoT powered servitization of manufacturing - an exploratory case study. International Journal of Production Economics, 192, 92-105. https://doi.org/10.1016/j.ijpe.2017.02.016
Suppatvech, C., Godsell, J., & Day, S. (2019). The roles of internet of things technology in enabling servitized business models: A systematic literature review. Industrial Marketing Management, 82, 70-86. https://doi.org/10.1016/j.indmarman.2019.02.016
Visnjic Kastalli, I., & Van Looy, B. (2013). Servitization: Disentangling the impact of service business model innovation on manufacturing firm performance. Journal of Operations Management, 31(4), 169-180. https://doi.org/10.1016/j.jom.2013.02.001
Zhen, L. (2012). An analytical study on service-oriented manufacturing strategies. International Journal of Production Economics, 139(1), 220-228. https://doi.org/10.1016/j.ijpe.2012.04.010