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Necessary Condition Hypotheses in Operations Management

Author

Listed:
  • Dul, J.
  • Hak, A.
  • Goertz, G.
  • Voss, C.

Abstract

Purpose – To show that necessary condition hypotheses are important in operations management, and to present a consistent methodology for building and testing them. Necessary condition hypotheses (“X is necessary for Y”) express conditions that must be present in order to have a desired outcome (e.g. “success”), and to prevent guaranteed failure. These hypotheses differ fundamentally from the common co-variational hypotheses (“more X results in more Y”) and require another methodology for building and testing them. Design/methodology/approach – Reviewing operations management literature for versions of necessary condition hypotheses. Combining previous theoretical and methodological work into a comprehensive and consistent methodology for building and testing such hypotheses. Findings – Necessary condition statements are common in operations management, but current formulations are not precise, and methods used for building and testing them are not always adequate. Outline of the methodology of Necessary Condition Analysis (NCA) consisting of two stepwise methodological approaches, one for building and one for testing necessary conditions. Originality/value – Because necessary condition statements are common in operations management, using methodologies that can build and test such hypotheses contributes to the advancement of operations management research and theory.

Suggested Citation

  • Dul, J. & Hak, A. & Goertz, G. & Voss, C., 2010. "Necessary Condition Hypotheses in Operations Management," ERIM Report Series Research in Management ERS-2010-019-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:19666
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    File URL: https://repub.eur.nl/pub/19666/ERS-2010-019-LIS.pdf
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    References listed on IDEAS

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    1. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773.
    2. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
    3. Umble, Elisabeth J. & Haft, Ronald R. & Umble, M. Michael, 2003. "Enterprise resource planning: Implementation procedures and critical success factors," European Journal of Operational Research, Elsevier, vol. 146(2), pages 241-257, April.
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    Cited by:

    1. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: a research agenda for industrial maintenance management," International Journal of Production Economics, Elsevier, vol. 224(C).
    2. Jon Bokrantz & Jan Dul, 2023. "Building and testing necessity theories in supply chain management," Journal of Supply Chain Management, Institute for Supply Management, vol. 59(1), pages 48-65, January.
    3. Ksenija Denčić-Mihajlov & Mladen Krstić & Dejan Spasić, 2020. "Sensitivity Analysis as a Tool in Environmental Policy for Sustainability: The Case of Waste Recycling Projects in the Republic of Serbia," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    4. Awe, Olajumoke A. & Woodside, Arch G. & Nerur, Sridhar & Prater, Edmund, 2020. "Capturing heterogeneities in orchestrating resources for accurately forecasting high (separately low) project management performance," International Journal of Production Economics, Elsevier, vol. 224(C).
    5. Herrera, Maria Elena Baltazar, 2016. "Social innovation for bridging societal divides: Process or leader? A qualitative comparative analysis," Journal of Business Research, Elsevier, vol. 69(11), pages 5241-5247.
    6. Castelló-Sirvent, Fernando & García-García, Juan Manuel, 2022. "Exploring the language heterogeneity strategies of European think tanks," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    7. Wolfgang Messner, 2021. "Empirically assessing noisy necessary conditions with activation functions," Computational Management Science, Springer, vol. 18(1), pages 1-23, January.
    8. Sukhov, Alexandre & Friman, Margareta & Olsson, Lars E., 2023. "Unlocking potential: An integrated approach using PLS-SEM, NCA, and fsQCA for informed decision making," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    9. Gary Goertz & Tony Hak & Jan Dul, 2013. "Ceilings and Floors," Sociological Methods & Research, , vol. 42(1), pages 3-40, February.
    10. Aguilera-Caracuel, Javier & Fedriani, Eugenio M. & Delgado-Márquez, Blanca L., 2014. "Institutional distance among country influences and environmental performance standardization in multinational enterprises," Journal of Business Research, Elsevier, vol. 67(11), pages 2385-2392.
    11. Barbara Vis, 2012. "The Comparative Advantages of fsQCA and Regression Analysis for Moderately Large-N Analyses," Sociological Methods & Research, , vol. 41(1), pages 168-198, February.
    12. Barbara Vis & Jan Dul, 2018. "Analyzing Relationships of Necessity Not Just in Kind But Also in Degree," Sociological Methods & Research, , vol. 47(4), pages 872-899, November.
    13. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: an empirically grounded conceptualization," International Journal of Production Economics, Elsevier, vol. 223(C).
    14. Herman Aguinis & Ravi S Ramani & Wayne F Cascio, 2020. "Methodological practices in international business research: An after-action review of challenges and solutions," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(9), pages 1593-1608, December.
    15. Jan Dul & Sven Hauff & Ricarda B. Bouncken, 2023. "Necessary condition analysis (NCA): review of research topics and guidelines for good practice," Review of Managerial Science, Springer, vol. 17(2), pages 683-714, February.
    16. Castka, Pavel, 2018. "Modelling firms’ interventions in ISO 9001 certification: A configurational approach," International Journal of Production Economics, Elsevier, vol. 201(C), pages 163-172.
    17. Dul, Jan, 2016. "Identifying single necessary conditions with NCA and fsQCA," Journal of Business Research, Elsevier, vol. 69(4), pages 1516-1523.
    18. Eccarius, Timo & Chen, Ching-Fu, 2024. "Examining trust as a critical factor for the adoption of electric vehicle sharing via necessary condition analysis," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    19. Dul, J., 2015. "Necessary Condition Analysis (NCA)," ERIM Report Series Research in Management ERS-2015-004-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Battistoni, Elisa & Gitto, Simone & Murgia, Gianluca & Campisi, Domenico, 2023. "Adoption paths of digital transformation in manufacturing SME," International Journal of Production Economics, Elsevier, vol. 255(C).
    21. Fernando Castelló-Sirvent & Vanessa Roger-Monzó & Juan Manuel García-García, 2021. "International economic policy: a fuzzy set qualitative comparative analysis on think tanks in the press," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 2609-2627, January.

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    JEL classification:

    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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