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Editorial—The Exploration-Exploitation Tradeoff and Efficiency in Knowledge Production

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  • K. Sudhir

    (Yale School of Management, New Haven, Connecticut 06520)

Abstract

Marketing Science is in a very healthy state as the premier journal for quantitative research in marketing. Since its inception, it has led the way in bringing novel and innovative methodologies and expanding into new substantive areas of inquiry. The journal is now at the cusp of its next stage of creativity and innovation. I outline new research possibilities due to big data, behavioral field studies, and managerial interest in substantive areas such as health, sustainability, emerging markets, innovation, and entrepreneurship. As quantitative marketing’s leading journal, Marketing Science should aid the field in the efficient production of in-depth, valid, current, and relevant knowledge across the breadth of the discipline. To this end, I will actively manage incentives for exploitation and deepening of existing competencies in established areas while supporting exploration and broadening into newer, riskier topics at Marketing Science . To increase the field’s overall efficiency of knowledge production, I suggest a lexicographic approach to reviewing where the incremental contribution threshold is primary and demands on quality of execution be driven by what is needed for proving the validity of the incremental contribution claims.

Suggested Citation

  • K. Sudhir, 2016. "Editorial—The Exploration-Exploitation Tradeoff and Efficiency in Knowledge Production," Marketing Science, INFORMS, vol. 35(1), pages 1-9, January.
    • Handle: RePEc:inm:ormksc:v:35:y:2016:i:1:p:1-9
    DOI: 10.1287/mksc.2015.0974
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    Cited by:

    1. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    2. Stephen J. Anderson & Rajesh Chandy & Bilal Zia, 2018. "Pathways to Profits: The Impact of Marketing vs. Finance Skills on Business Performance," Management Science, INFORMS, vol. 64(12), pages 5559-5583, December.
    3. Yan Lu & Debanjan Mitra & David Musto & Sugata Ray, 2020. "Can Brands Circumvent Marketing Regulations? Exploiting Umbrella Branding in Financial Markets," Marketing Science, INFORMS, vol. 39(1), pages 71-91, January.
    4. Raphael Thomadsen & Robert P. Rooderkerk & On Amir & Neeraj Arora & Bryan Bollinger & Karsten Hansen & Leslie John & Wendy Liu & Aner Sela & Vishal Singh & K. Sudhir & Wendy Wood, 2018. "How Context Affects Choice," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 3-14, March.
    5. Alok Gupta, 2018. "Editorial—Traits of Successful Research Contributions for Publication in ISR : Some Thoughts for Authors and Reviewers," Information Systems Research, INFORMS, vol. 29(4), pages 779-786, December.
    6. Cheng He & O. Cem Ozturk & Chris Gu & Jorge Mario Silva-Risso, 2021. "The End of the Express Road for Hybrid Vehicles: Can Governments’ Green Product Incentives Backfire?," Marketing Science, INFORMS, vol. 40(1), pages 80-100, January.
    7. Chenxi Li & Xueming Luo & Cheng Zhang, 2017. "Sunny, Rainy, and Cloudy with a Chance of Mobile Promotion Effectiveness," Marketing Science, INFORMS, vol. 36(5), pages 762-779, September.
    8. Darius Schlangenotto & Dennis Kundisch & Nancy V. Wünderlich, 2018. "Is paid search overrated? When bricks-and-mortar-only retailers should not use paid search," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(4), pages 407-421, November.
    9. Asim Ansari & Yang Li & Jonathan Z. Zhang, 2018. "Probabilistic Topic Model for Hybrid Recommender Systems: A Stochastic Variational Bayesian Approach," Marketing Science, INFORMS, vol. 37(6), pages 987-1008, November.
    10. Zecong Ma & Sergio Palacios, 2021. "Image-mining: exploring the impact of video content on the success of crowdfunding," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(4), pages 265-285, December.
    11. Sreejith Kumar Krishnakumar & Rajiv Kishore & Nallan C. Suresh, 2022. "Expansive or focused attention? An exploration–exploitation perspective on e‐Business systems and firm performance," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2038-2066, May.
    12. Xiao Liu & Alan Montgomery & Kannan Srinivasan, 2018. "Analyzing Bank Overdraft Fees with Big Data," Marketing Science, INFORMS, vol. 37(6), pages 855-882, November.
    13. Leif Nelson & Duncan Simester & K. Sudhir, 2020. "Introduction to the Special Issue on Marketing Science and Field Experiments," Marketing Science, INFORMS, vol. 39(6), pages 1033-1038, November.
    14. Yang, Zhengliang & Caputo, Vincenzina, 2023. "Introducing automatic video mining to agricultural economics: A case study from a crowdfunding website," 2023 Annual Meeting, July 23-25, Washington D.C. 335600, Agricultural and Applied Economics Association.
    15. K. Sudhir, 2017. "Congratulations to Richard Thaler for Winning the Nobel Prize in Economics," Marketing Science, INFORMS, vol. 36(6), pages 813-814, November.
    16. Olivier Toubia, 2022. "Editorial: A New Chapter or a New Page for Marketing Science ?," Marketing Science, INFORMS, vol. 41(1), pages 1-6, January.
    17. K. Sudhir, 2019. "Editorial: An Update on the Frontiers Section," Marketing Science, INFORMS, vol. 38(6), pages 913-917, November.
    18. K. Sudhir, 2018. "Editorial—Introducing A New Section— Marketing Science: Frontiers," Marketing Science, INFORMS, vol. 37(1), pages 1-4, January.
    19. Li, Xi & Shi, Mengze & Wang, Xin (Shane), 2019. "Video mining: Measuring visual information using automatic methods," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 216-231.

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