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Optimising allocation of marketing resources among offline channel retailers: A bi-clustering-based model

Author

Listed:
  • Xiao, Jin
  • Li, Yuxi
  • Tian, Yuhang
  • Jiang, Xiaoyi
  • Wang, Yuan
  • Wang, Shouyang

Abstract

Existing research on optimising marketing resource allocation focuses mainly on the customer rather than the retailer level. However, retailers play an important role in marketing channels, and optimising retailer-level marketing resource allocation poses important decision-making challenges. In this study, we proposed a retailer-level offline marketing resource-optimising allocation model based on retailer segmentation. The model consists of two stages. In the first stage, we built a retailer segmentation index system and introduced a bi-clustering algorithm to segment retailers that can cluster samples and features simultaneously. In the second stage, we proposed a new measurement for the rate of return on the utility of marketing resources and then leveraged the mean–variance model to find optimal marketing resource allocation plans. An empirical study of a famous Chinese alcoholic beverage company demonstrated that the proposed model outperformed four baseline models.

Suggested Citation

  • Xiao, Jin & Li, Yuxi & Tian, Yuhang & Jiang, Xiaoyi & Wang, Yuan & Wang, Shouyang, 2025. "Optimising allocation of marketing resources among offline channel retailers: A bi-clustering-based model," Journal of Business Research, Elsevier, vol. 186(C).
  • Handle: RePEc:eee:jbrese:v:186:y:2025:i:c:s0148296324004181
    DOI: 10.1016/j.jbusres.2024.114914
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    as
    1. Yuri Peers & Harald J. van Heerde & Marnik G. Dekimpe, 2017. "Marketing Budget Allocation Across Countries: The Role of International Business Cycles," Marketing Science, INFORMS, vol. 36(5), pages 792-809, September.
    2. Davcik, Nebojsa S. & Sharma, Piyush, 2016. "Marketing resources, performance, and competitive advantage: A review and future research directions," Journal of Business Research, Elsevier, vol. 69(12), pages 5547-5552.
    3. Yanwu Yang & Daniel Zeng & Yinghui Yang & Jie Zhang, 2015. "Optimal Budget Allocation Across Search Advertising Markets," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 285-300, May.
    4. Özalp Özer & Yanchong Zheng, 2016. "Markdown or Everyday Low Price? The Role of Behavioral Motives," Management Science, INFORMS, vol. 62(2), pages 326-346, February.
    5. Mora Cortez, Roberto & Højbjerg Clarke, Ann & Freytag, Per Vagn, 2021. "B2B market segmentation: A systematic review and research agenda," Journal of Business Research, Elsevier, vol. 126(C), pages 415-428.
    6. Paco, Arminda & Raposo, Mario, 2010. "Green Consumer Market Segmentation: Empirical Findings from Portugal," Apas Papers 203, Academic Public Administration Studies Archive - APAS.
    7. Liu, Jiapeng & Liao, Xiuwu & Huang, Wei & Liao, Xianzhao, 2019. "Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision," Omega, Elsevier, vol. 83(C), pages 1-13.
    8. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    9. Dan Zhang & Zhaosong Lu, 2013. "Assessing the Value of Dynamic Pricing in Network Revenue Management," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 102-115, February.
    10. Kim, Kyung Hoon & Kim, Kang Sik & Kim, Dong Yul & Kim, Jong Ho & Kang, Suk Hou, 2008. "Brand equity in hospital marketing," Journal of Business Research, Elsevier, vol. 61(1), pages 75-82, January.
    11. Ali Pilehvar & Wedad J. Elmaghraby & Anandasivam Gopal, 2017. "Market Information and Bidder Heterogeneity in Secondary Market Online B2B Auctions," Management Science, INFORMS, vol. 63(5), pages 1493-1518, May.
    12. Mehrdad Memarpour & Erfan Hassannayebi & Navid Fattahi Miab & Ali Farjad, 2021. "Dynamic allocation of promotional budgets based on maximizing customer equity," Operational Research, Springer, vol. 21(4), pages 2365-2389, December.
    13. Chun‐Hung Chiu & Tsan‐Ming Choi & Xin Dai & Bin Shen & Jin‐Hui Zheng, 2018. "Optimal Advertising Budget Allocation in Luxury Fashion Markets with Social Influences: A Mean‐Variance Analysis," Production and Operations Management, Production and Operations Management Society, vol. 27(8), pages 1611-1629, August.
    14. Home, Niilo, 2011. "Entrepreneurial orientation of grocery retailers in Finland," Journal of Retailing and Consumer Services, Elsevier, vol. 18(4), pages 293-301.
    15. Stephen L. France & Sanjoy Ghose, 2016. "An Analysis and Visualization Methodology for Identifying and Testing Market Structure," Marketing Science, INFORMS, vol. 35(1), pages 182-197, January.
    16. Bruce McWilliams, 2012. "Money-Back Guarantees: Helping the Low-Quality Retailer," Management Science, INFORMS, vol. 58(8), pages 1521-1524, August.
    17. Dahana, Wirawan Dony & Miwa, Yukihiro & Morisada, Makoto, 2019. "Linking lifestyle to customer lifetime value: An exploratory study in an online fashion retail market," Journal of Business Research, Elsevier, vol. 99(C), pages 319-331.
    18. Vilnai-Yavetz, Iris & Tifferet, Sigal, 2015. "A Picture Is Worth a Thousand Words: Segmenting Consumers by Facebook Profile Images," Journal of Interactive Marketing, Elsevier, vol. 32(C), pages 53-69.
    19. Ballestar, María Teresa & Grau-Carles, Pilar & Sainz, Jorge, 2018. "Customer segmentation in e-commerce: Applications to the cashback business model," Journal of Business Research, Elsevier, vol. 88(C), pages 407-414.
    20. Luzon, Yossi & Pinchover, Rotem & Khmelnitsky, Eugene, 2022. "Dynamic budget allocation for social media advertising campaigns: optimization and learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 223-234.
    21. Bianchi-Aguiar, Teresa & Hübner, Alexander & Carravilla, Maria Antónia & Oliveira, José Fernando, 2021. "Retail shelf space planning problems: A comprehensive review and classification framework," European Journal of Operational Research, Elsevier, vol. 289(1), pages 1-16.
    22. von Mutius, Bernhard & Huchzermeier, Arnd, 2021. "Customized Targeting Strategies for Category Coupons to Maximize CLV and Minimize Cost," Journal of Retailing, Elsevier, vol. 97(4), pages 764-779.
    23. Wu, Meng & Teunter, Ruud H. & Zhu, Stuart X., 2019. "Online marketing: When to offer a refund for advanced sales," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 471-491.
    24. Glen L. Urban & Philip L. Johnson & John R. Hauser, 1984. "Testing Competitive Market Structures," Marketing Science, INFORMS, vol. 3(2), pages 83-112.
    25. Marc Fischer & Sönke Albers & Nils Wagner & Monika Frie, 2011. "Practice Prize Winner --Dynamic Marketing Budget Allocation Across Countries, Products, and Marketing Activities," Marketing Science, INFORMS, vol. 30(4), pages 568-585, July.
    26. Gibbert, Michael & Golfetto, Francesca & Zerbini, Fabrizio, 2006. "What do we mean by "marketing" resources and competencies? A comment on Hooley, Greenley, Cadogan, and Fahey (JBR 2005)," Journal of Business Research, Elsevier, vol. 59(1), pages 148-151, January.
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