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Leveraging high-involvement practices to develop mass customization capability: A contingent configurational perspective

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  • Sandrin, Enrico
  • Trentin, Alessio
  • Forza, Cipriano

Abstract

This study focuses on the four human-resource-management (HRM) practices that characterize high involvement (HI), the most advanced approach to employee involvement. These practices push power, information, rewards, and knowledge down to the lowest level of an organization. The impact of these practices on a manufacturing firm's mass-customization capability (MCC) is examined, along with the way this impact is influenced by the degree of product customization (DPC) that the firm provides to its customers. Based on survey data from 195 manufacturing plants in three industries and eight countries, the study finds empirical evidence that these practices improve MCC when they are adopted jointly and, at the same time, DPC surpasses a certain threshold value. The same practices, when implemented independent of one another, do not have statistically significant effects on MCC. Furthermore, as DPC drops below the threshold, the effect of this configuration of practices becomes non-significant at conventional p levels and gradually decreases until it turns into a negative effect, which comes closer to statistical significance when the DPC reaches its minimum. This study is the first to examine the effects of HRM practices on MCC by taking full advantage of the contingent configurational perspective that is strongly advocated in the strategic HRM literature. The results of this study extend the debate on the organizational enablers of MCC and, at the same time, add to the well-established discussion on the performance outcomes of HRM practices in general and HI practices in particular.

Suggested Citation

  • Sandrin, Enrico & Trentin, Alessio & Forza, Cipriano, 2018. "Leveraging high-involvement practices to develop mass customization capability: A contingent configurational perspective," International Journal of Production Economics, Elsevier, vol. 196(C), pages 335-345.
    • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:335-345
    DOI: 10.1016/j.ijpe.2017.12.005
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    References listed on IDEAS

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    Cited by:

    1. Lin, Shunzhi & Lin, Jiabao, 2023. "How organizations leverage digital technology to develop customization and enhance customer relationship performance: An empirical investigation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
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    3. Na Liu & Pui-Sze Chow & Hongshan Zhao, 2020. "Challenges and critical successful factors for apparel mass customization operations: recent development and case study," Annals of Operations Research, Springer, vol. 291(1), pages 531-563, August.
    4. Linda Zhang & Sara Shafiee, 2022. "Developing separate or integrated configurators? A longitudinal case study," Post-Print hal-03707380, HAL.
    5. Shao, Xiao-Feng, 2020. "What is the right production strategy for horizontally differentiated product: Standardization or mass customization?," International Journal of Production Economics, Elsevier, vol. 223(C).
    6. Cannas, Violetta G. & Gosling, Jonathan & Pero, Margherita & Rossi, Tommaso, 2019. "Engineering and production decoupling configurations: An empirical study in the machinery industry," International Journal of Production Economics, Elsevier, vol. 216(C), pages 173-189.
    7. Cannas, Violetta G. & Gosling, Jonathan & Pero, Margherita & Rossi, Tommaso, 2020. "Determinants for order-fulfilment strategies in engineer-to-order companies: Insights from the machinery industry," International Journal of Production Economics, Elsevier, vol. 228(C).
    8. Cannas, Violetta Giada & Gosling, Jonathan, 2021. "A decade of engineering-to-order (2010–2020): Progress and emerging themes," International Journal of Production Economics, Elsevier, vol. 241(C).

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