From site automation to spatial orchestration: Private 5G and supply chain digital transformation in Taiwan
Private fifth-generation (5G) adoption is accelerating across supply chain operations. This study examines how private 5G network projects are configured as supply chain digital infrastructures and whether program maturity corresponds to a transition from isolated site automation toward wider orchestration. The full census of 33 projects in Taiwan’s Private 5G Network Innovative Application Diffusion Program was coded on theory-derived dimensions of sensing, response, coordination, cross-site scope, continuity, and inter-organizational scope. Descriptive statistics, Fisher’s exact tests, a Mann–Whitney U test, and a parsimonious logistic sensitivity model were employed because the portfolio is small and several contingency-table cells are sparse. The portfolio demonstrates a strong emphasis on site-level execution: 25 projects incorporate response affordances, 23 incorporate sensing affordances, 12 include coordination mechanisms, and only 5 explicitly extend across multiple sites. No project title explicitly indicates supplier/customer coordination or continuity and recovery. The higher maturity classification is associated with cross-site scope (odds ratio = 24.0; Fisher’s exact p = 0.008), whereas capability breadth does not differ by tier. The sensitivity model yields the same substantive pattern after controlling for internal-operation orientation, although uncertainty remains large. The data capture public project designs rather than realized operational outcomes; accordingly, the findings concern portfolio architecture, not causal performance effects. Managers and policy designers should complement private 5G with interoperable data, cross-site workflows, partner interfaces, security governance, and continuity routines. The study introduces a site-to-network transition model and identifies spatial orchestration, rather than a larger bundle of technology labels, as the observable feature distinguishing more mature projects.
- Aijaz A. Private 5G: the future of industrial wireless. IEEE Ind Electron Mag. 2020;14(4):136-145. doi: 10.1109/MIE.2020.3004975
- Ben-Daya M, Hassini E, Bahroun Z. Internet of things and supply chain management: a literature review. Int J Prod Res. 2017;57(15-16):4719-4742. doi: 10.1080/00207543.2017.1402140
- Barratt M, Oke A. Antecedents of supply chain visibility in retail supply chains: a resource-based theory perspective. J Oper Manag. 2007;25(6):1217-1233. doi: 10.1016/j.jom.2007.01.003
- Fawcett SE, Wallin C, Allred C, Fawcett AM, Magnan GM. Information technology as an enabler of supply chain collaboration: a dynamic-capabilities perspective. J Supply Chain Manag. 2011;47(1):38-59. doi: 10.1111/j.1745-493X.2010.03213.x
- Srinivasan R, Swink M. An investigation of visibility and flexibility as complements to supply chain analytics: an organizational information processing theory perspective. Prod Oper Manag. 2018;27(10):1849-1867. doi: 10.1111/poms.12746
- Bharadwaj A, El Sawy OA, Pavlou PA, Venkatraman N. Digital business strategy: toward a next generation of insights. MIS Quarterly. 2013;37(2):471-482. doi: 10.25300/MISQ/2013/37:2.3
- Fichman RG, Dos Santos BL, Zheng Z. Digital innovation as a fundamental and powerful concept in the information systems curriculum. MIS Quarterly. 2014;38(2):329-353. doi: 10.25300/MISQ/2014/38.2.01
- Vial G. Understanding digital transformation: a review and a research agenda. J Strateg Inf Syst. 2019;28(2):118-144. doi: 10.1016/j.jsis.2019.01.003
- Verhoef PC, Broekhuizen T, Bart Y, et al. Digital transformation: a multidisciplinary reflection and research agenda. J Bus Res. 2021;122:889-901. doi: 10.1016/j.jbusres.2019.09.022
- Christopher M, Peck H. Building the resilient supply chain. Int J Logist Manag. 2004;15(2):1-14. doi: 10.1108/09574090410700275
- Ponomarov SY, Holcomb MC. Understanding the concept of supply chain resilience. Int J Logist Manag. 2009;20(1):124-143. doi: 10.1108/09574090910954873
- Brandon-Jones E, Squire B, Autry CW, Petersen KJ. A contingent resource-based perspective of supply chain resilience and robustness. J Supply Chain Manag. 2014;50(3):55-73. doi: 10.1111/jscm.12050
- Kache F, Seuring S. Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. Int J Oper Prod Manag. 2017;37(1):10-36. doi: 10.1108/IJOPM-02-2015-0078
- Wamba SF, Gunasekaran A, Akter S, Ren SJ, Dubey R, Childe SJ. Big data analytics and firm performance: effects of dynamic capabilities. J Bus Res. 2017;70:356-365. doi: 10.1016/j.jbusres.2016.08.009
- Yoo Y, Henfridsson O, Lyytinen K. Research Commentary—The new organizing logic of digital innovation: an agenda for information systems research. Inf Syst Res. 2010;21(4):724-735. doi: 10.1287/isre.1100.0322
- Lyytinen K, Yoo Y, Boland RJ Jr. Digital product innovation within four classes of innovation networks. Inf Syst J. 2015;26(1):47-75. doi: 10.1111/isj.12093
- Nambisan S, Lyytinen K, Majchrzak A, Song M. Digital innovation management: reinventing innovation management research in a digital world. MIS Quarterly. 2017;41(1):223-238. doi: 10.25300/MISQ/2017/41:1.03
- Svahn F, Mathiassen L, Lindgren R. Embracing digital innovation in incumbent firms: how Volvo Cars managed competing concerns. MIS Quarterly. 2017;41(1):239-253. doi: 10.25300/MISQ/2017/41.1.12
- Warner KSR, Wäger M. Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal. Long Range Plann. 2019;52(3):326-349. doi: 10.1016/j.lrp.2018.12.001
- Hanelt A, Bohnsack R, Marz D, Antunes Marante C. A systematic review of the literature on digital transformation: insights and implications for strategy and organizational change. J Manag Stud. 2020;58(5):1159-1197. doi: 10.1111/joms.12639
- Frank AG, Dalenogare LS, Ayala NF. Industry 4.0 technologies: implementation patterns in manufacturing companies. Int J Prod Econ. 2019;210:15-26. doi: 10.1016/j.ijpe.2019.01.004
- Tortorella GL, Fettermann D. Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. Int J Prod Res. 2017;56(8):2975-2987. doi: 10.1080/00207543.2017.1391420
- Frederico GF, Garza-Reyes JA, Anosike A, Kumar V. Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Manag. 2019;25(2):262-282. doi: 10.1108/SCM-09-2018-0339
- Galbraith JR. Organization design: an information processing view. Interfaces. 1974;4(3):28-36. doi: 10.1287/inte.4.3.28
- Tushman ML, Nadler DA. Information processing as an integrating concept in organizational design. Acad Manage Rev. 1978;3(3):613-624. doi: 10.5465/amr.1978.4305791
- Rai A, Patnayakuni R, Seth N. Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly. 2006;30(2):225-246. doi: 10.2307/25148729
- Dubey R, Gunasekaran A, Childe SJ, Blome C, Papadopoulos T. Big data and predictive analytics and manufacturing performance: integrating institutional theory, resource-based view and big data culture. Br J Manag. 2019;30(2):341-361. doi: 10.1111/1467-8551.12355
- Mikalef P, Krogstie J, Pappas IO, Pavlou P. Exploring the relationship between big data analytics capability and competitive performance: the mediating roles of dynamic and operational capabilities. Inf Manag. 2020;57(2):103169. doi: 10.1016/j.im.2019.05.004
- Dubey R, Gunasekaran A, Childe SJ, Fosso Wamba S, Roubaud D, Foropon C. Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. Int J Prod Res. 2019;59(1):110-128. doi: 10.1080/00207543.2019.1582820
- Pettit TJ, Fiksel J, Croxton KL. Ensuring supply chain resilience: development of a conceptual framework. J Bus Logist. 2010;31(1):1-21. doi: 10.1002/j.2158-1592.2010.tb00125.x
- Braunscheidel MJ, Suresh NC. The organizational antecedents of a firm’s supply chain agility for risk mitigation and response. J Oper Manag. 2008;27(2):119-140. doi: 10.1016/j.jom.2008.09.006
- Ivanov D, Dolgui A. Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. Int J Prod Res. 2020;58(10):2904-2915. doi: 10.1080/00207543.2020.1750727
- Wieland A. Dancing the supply chain: toward transformative supply chain management. J Supply Chain Manag. 2020;57(1):58-73. doi: 10.1111/jscm.12248
- Belhadi A, Kamble S, Jabbour CJC, Gunasekaran A, Ndubisi NO, Venkatesh M. Manufacturing and service supply chain resilience to the COVID-19 outbreak: lessons learned from the automobile and airline industries. Technol Forecast Soc Change. 2021;163:120447. doi: 10.1016/j.techfore.2020.120447
- Ivanov D, Dolgui A. A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Prod Plan Control. 2020;32(9):775-788. doi: 10.1080/09537287.2020.1768450
- Ambulkar S, Blackhurst J, Grawe S. Firm’s resilience to supply chain disruptions: scale development and empirical examination. J Oper Manag. 2014;33-34(1):111-122. doi: 10.1016/j.jom.2014.11.002
- Scholten K, Schilder S. The role of collaboration in supply chain resilience. Supply Chain Manag. 2015;20(4):471-484. doi: 10.1108/SCM-11-2014-0386
- Chowdhury MMH, Quaddus M. Supply chain resilience: conceptualization and scale development using dynamic capability theory. Int J Prod Econ. 2017;188:185-204. doi: 10.1016/j.ijpe.2017.03.020
- Teece DJ. Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strateg Manag J. 2007;28(13):1319-1350. doi: 10.1002/smj.640
- Helfat CE, Peteraf MA. The dynamic resource-based view: capability lifecycles. Strateg Manag J. 2003;24(10):997-1010. doi: 10.1002/smj.332
- Wieland A, Wallenburg CM. The influence of relational competencies on supply chain resilience: a relational view. Int J Phys Distrib Logist Manag. 2013;43(4):300-320. doi: 10.1108/IJPDLM-08-2012-0243
- Queiroz MM, Telles R, Bonilla SH. Blockchain and supply chain management integration: a systematic review of the literature. Supply Chain Manag. 2019;25(2):241-254. doi: 10.1108/SCM-03-2018-0143
- Administration for Digital Industries. List of selected vertical industry application promotion groups for private 5G diffusion. Taiwan Government Data Open Platform. Published April 7, 2025. Accessed July 3, 2026. https://data.gov.tw/dataset/173248
- Administration for Digital Industries. List of 33 subsidized cases under the Private 5G Network Innovative Application Diffusion Program. Taiwan Government Data Open Platform. Published April 7, 2025. Accessed July 3, 2026. https://data.gov.tw/dataset/173249
- Gioia DA, Corley KG, Hamilton AL. Seeking qualitative rigor in inductive research: notes on the Gioia methodology. Organ Res Methods. 2012;16(1):15-31. doi: 10.1177/1094428112452151
- Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277-1288. doi: 10.1177/1049732305276687
- Duriau VJ, Reger RK, Pfarrer MD. A content analysis of the content analysis literature in organization studies: research themes, data sources, and methodological refinements. Organ Res Methods. 2007;10(1):5-34. doi: 10.1177/1094428106289252
- Kamalahmadi M, Parast MM. A review of the literature on the principles of enterprise and supply chain resilience: major findings and directions for future research. Int J Prod Econ. 2016;171:116-133. doi: 10.1016/j.ijpe.2015.10.023
- Hosseini S, Ivanov D, Dolgui A. Review of quantitative methods for supply chain resilience analysis. Transp Res E Logist Transp Rev. 2019;125:285-307. doi: 10.1016/j.tre.2019.03.001
- Huang K, Wang K, Lee PKC, Yeung ACL. The impact of Industry 4.0 on supply chain capability and supply chain resilience: a dynamic resource-based view. Int J Prod Econ. 2023;262:108913. doi: 10.1016/j.ijpe.2023.108913
- Ning Y, Li L, Xu SX, Yang S. How do digital technologies improve supply chain resilience in the COVID-19 pandemic? Evidence from Chinese manufacturing firms. Front Eng Manag. 2022;10(1):39-50. doi: 10.1007/s42524-022-0230-4
- Wu L, Zhang Z, Huang J, Su IH, Tian S. Digital technologies and supply chain resilience: a resource-action-performance perspective. Inf Syst Front. 2025;27(5):2137-2158. doi: 10.1007/s10796-025-10595-1
- Lin CC, Deng DJ, Hsieh LT, Pan PT. Optimal deployment of private 5G multi-access edge computing systems at smart factories: using hybrid crow search algorithm. J Netw Comput Appl. 2024;227:103906. doi: 10.1016/j.jnca.2024.103906
- Michaelides S, Lenz S, Vogt T, Henze M. Secure integration of 5G in industrial networks: state of the art, challenges and opportunities. Future Gener Comput Syst. 2025;166:107645. doi: 10.1016/j.future.2024.107645
- Apruzzese M, Bruni ME, Musso S, Perboli G. 5G and companion technologies as a boost in new business models for logistics and supply chain. Sustainability. 2023;15(15):11846. doi: 10.3390/su151511846
