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Smart product service system hierarchical model in banking industry under uncertainties

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  • Tseng, Ming-Lang
  • Bui, Tat-Dat
  • Lan, Shulin
  • Lim, Ming K.
  • Mashud, Abu Hashan Md

Abstract

This study adopts the diffusion of innovation theory as to develop the smart product service system model in banking industry due to prior studies are lacking in identifying the attributes. The smart product service system functions are bearing high uncertainty and system complexity; hence, the hybrid method of fuzzy Delphi method and fuzzy decision-making trial and evaluation laboratory to construct a valid hierarchical model and identified the causal interrelationships among the attributes. The smart product service system hierarchical model with eight aspects and 41 criteria are proposed enriching the existing literature and that identify appropriate strategies to achieve operational performance. The results show that seven aspects and 22 criteria are determined as the valid hierarchical model. The institutional compression, digital platform operation, and e-knowledge management are the causing aspects helps to form smart product service system operational performance in high uncertainty. For practices, the banking decision-makers should develop innovative actions relied on the forcible compression, cyber-physical systems, industrial big data, cloud service allocation and sharing, and transparency improvement as they are most importance criteria playing a decisive role in a successful SPSS. This provides guidelines for banking industry practice in Taiwan encouraging the miscellany of digital technology accomplishment for sustainable target.

Suggested Citation

  • Tseng, Ming-Lang & Bui, Tat-Dat & Lan, Shulin & Lim, Ming K. & Mashud, Abu Hashan Md, 2021. "Smart product service system hierarchical model in banking industry under uncertainties," International Journal of Production Economics, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:proeco:v:240:y:2021:i:c:s0925527321002206
    DOI: 10.1016/j.ijpe.2021.108244
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    Cited by:

    1. Tseng, Ming-Lang & Bui, Tat-Dat & Lim, Ming K. & Fujii, Minoru & Mishra, Umakanta, 2022. "Assessing data-driven sustainable supply chain management indicators for the textile industry under industrial disruption and ambidexterity," International Journal of Production Economics, Elsevier, vol. 245(C).
    2. Ya-Ping Hu & Chun-Wei Lin & Eko Hariyadi, 2024. "Achieving Sustainability in Banking through Smart Product-Service Systems: An Integrated Robust Fuzzy DEMATEL," International Journal of Economics and Financial Issues, Econjournals, vol. 14(5), pages 81-91, September.
    3. Yang, Zaoli & Li, Qin & Charles, Vincent & Xu, Bing & Gupta, Shivam, 2023. "Supporting personalized new energy vehicle purchase decision-making: Customer reviews and product recommendation platform," International Journal of Production Economics, Elsevier, vol. 265(C).
    4. Ching-Hsin Wang & Yi-Chun Chen & Jovi Sulistiawan & Tat-Dat Bui & Ming-Lang Tseng, 2021. "Hybrid Approach to Corporate Sustainability Performance in Indonesia’s Cement Industry," Sustainability, MDPI, vol. 13(24), pages 1-21, December.

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