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Linking manufacturing flexibility to innovation performance in manufacturing plants

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  • Oke, Adegoke

Abstract

In the past few decades, the concept of manufacturing flexibility has become a key competitive criterion for many manufacturing organizations. The importance of flexibility in supporting other competitive criteria such as cost, quality and delivery speed has also been recognized (Bolwijn and Kumpe, 1990). However, there is a dearth of studies linking flexibility with another competitive criterion—innovation. In this study, we investigate the influence of the interaction of mix flexibility and labor flexibility on product innovation based on a survey of UK manufacturing plants. Further, we investigate the role of climate for innovation both as an antecedent of product innovation and a moderator that moderates the influence of the interaction of mix flexibility and labor flexibility on product innovation. The analyses reveal that the interaction of mix flexibility and labor flexibility positively predicts product innovation in manufacturing plants. Climate for innovation positively predicts product innovation and also positively moderates the interaction of mix and labor flexibility on product innovation. The implications for theory and practice are discussed.

Suggested Citation

  • Oke, Adegoke, 2013. "Linking manufacturing flexibility to innovation performance in manufacturing plants," International Journal of Production Economics, Elsevier, vol. 143(2), pages 242-247.
  • Handle: RePEc:eee:proeco:v:143:y:2013:i:2:p:242-247
    DOI: 10.1016/j.ijpe.2011.09.014
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    File URL: http://www.sciencedirect.com/science/article/pii/S0925527311004002
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    References listed on IDEAS

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    1. Jeffrey G. Miller & Aleda V. Roth, 1994. "A Taxonomy of Manufacturing Strategies," Management Science, INFORMS, vol. 40(3), pages 285-304, March.
    2. Cordero, Rene, 1990. "The measurement of innovation performance in the firm: An overview," Research Policy, Elsevier, vol. 19(2), pages 185-192, April.
    3. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
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    Citations

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    Cited by:

    1. Pravin Kumar & Rajesh K. Singh & Rakesh Kumar, 2017. "An integrated framework of interpretive structural modeling and graph theory matrix approach to fix the agility index of an automobile manufacturing organization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 342-352, January.
    2. Jain, Vineet & Raj, Tilak, 2016. "Modeling and analysis of FMS performance variables by ISM, SEM and GTMA approach," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 84-96.
    3. Choe, Pilsung & Tew, Jeffrey D. & Tong, Songzhen, 2015. "Effect of cognitive automation in a material handling system on manufacturing flexibility," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 891-899.
    4. repec:spr:gjofsm:v:19:y:2018:i:1:d:10.1007_s40171-017-0170-8 is not listed on IDEAS
    5. Seebacher, Gottfried & Winkler, Herwig, 2015. "A capability approach to evaluate supply chain flexibility," International Journal of Production Economics, Elsevier, vol. 167(C), pages 177-186.
    6. Yu, Kangkang & Cadeaux, Jack & Luo, Ben Nanfeng, 2015. "Operational flexibility: Review and meta-analysis," International Journal of Production Economics, Elsevier, vol. 169(C), pages 190-202.
    7. repec:eee:proeco:v:200:y:2018:i:c:p:343-352 is not listed on IDEAS
    8. Huo, Baofeng & Ye, Yuxiao & Zhao, Xiande & Shou, Yongyi, 2016. "The impact of human capital on supply chain integration and competitive performance," International Journal of Production Economics, Elsevier, vol. 178(C), pages 132-143.

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