Abstract
In many situations, customers choose the facilities they want to interact with. One possible objective of the facility managers is to maximize the number of customers who use their facilities. In order to achieve this objective, they will need to make decisions regarding the features of their facilities, such as product variety, parking space, ambiance, prices, and, not least, the location of these facilities, particularly relative to the location of customers and possible competitors. To make their facilities attract as many customers as possible, the firms need to know what makes customers behave the way they do. Unfortunately for the firms, customer behavior is uncertain. This chapter examines the sources of customer-related uncertainty. These include the occurrence of unplanned purchases, the taste for variety—given product heterogeneity, imperfect information available to the customers about product and store features, and imperfect information on customers available to decision-makers. The effects of these uncertainties on customers’ behavior are also described: purchases distributed among all competitors, comparison shopping, multipurpose trips, and price and feature search. This behavior results in facility locations different from those obtained using models that do not consider uncertainty. In particular, we do see more agglomeration. The chapter then describes some models that include customer probabilistic choice rules and demonstrates how these rules can be integrated into facility location models.
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Notes
- 1.
Hotelling explicitly refers to product heterogeneity when firms “locate” in a space of customer preferences. However, when addressing geographical location, he uses homogeneous products.
- 2.
Actually, the gathering of information can be more permanent, which result in search behavior.
References
Altekin, F. T., Dasci, A., & Karatas, M. (2021). Linear and conic reformulations for the maximum capture location problem under multinomial logit choice. Optimization Letters, 15(8), 2611–2637.
Amos, C., Holmes, G. R., & Keneson, W. C. (2014). A meta-analysis of customer impulse buying. Journal of Retailing and Customer Services, 21(2), 86–97.
Anas, A. (1983). Discrete choice theory, information theory and the multinomial logit and gravity models. Transportation Research Part B, 17(1), 13–23. https://doi.org/10.1016/0191-2615(83)90023-1
Anderson, S. P., & Renault, R. (1999). Pricing, product diversity, and search costs: A Bertrand–Chamberlin–Diamond model. RAND Journal of Economics, 30, 719–735.
Anderson, S. P., De Palma, A., & Thisse, J.-F. (1992). Discrete choice theory of product differentiation. MIT Press.
Aros-Vera, F., Marianov, V., & Mitchell, J. E. (2013). P-hub approach for the optimal park-and-ride facility location problem. European Journal of Operational Research, 226(2), 277–285.
Attri, R., & Jain, V. (2018). A study of factors affecting customer shopping behavior. IUP Journal of Marketing Management, 17(1), 38–52.
Bell, D. R., Corsten, D., & Knox, G. (2013). Unplanned category purchase incidence: Who does it, how often, and why. https://repository.upenn.edu/marketing_papers/301. Last accessed on 01/30/2023.
Benati, S., & Hansen, P. (2002). The maximum capture problem with random utilities: Problem formulation and algorithms. European Journal of Operational Research, 143(3), 518–530.
Bierlaire, M., Hurtubia, R., & Flötteröd, G. (2009). A comparative analysis of implicit and explicit methods to model choice set generation. 9th Swiss Transport Research Conference, Switzerland. http://www.strc.ch/2009/Bierlaire.pdf. Last accessed on 01/30/2023.
Business Insider. (2021). The pandemic might have saved brick-and-mortar shopping as restrictions lift and customers head back to stores. https://www.businessinsider.com/pandemic-saved-brick-and-mortar-stores-walmart-and-target-2021-5. Last accessed on 01/30/2023.
Chamberlin, E. H. (1933). Theory of monopolistic competition. Harvard University Press.
Correia, I., & Saldanha-da-Gama, F. (2019). Facility location under uncertainty. In G. Laporte, S. Nickel, & F. Saldanha da Gama (Eds.), Location science (pp. 185–213). Springer.
Coto-Millán, P. (2003). Theory of utility and customer behaviour: A comprehensive review of concepts, properties and the most significant theorems. In Utility and production. Contributions to economics. Physica.
Cramer, J. S. (2002). The origins of logistic regression. Tinbergen Institute Working Paper No. 2002-119/4, Available at SSRN: https://ssrn.com/abstract=360300 or https://doi.org/10.2139/ssrn.360300. Both last accessed on 01/30/2023.
Daly, A., & Zachary, S. (1978). Improved multiple choice models. In D. Hensher & Q. Dalvi (Eds.), Identifying and measuring the determinants of mode choice. Teakfields.
Dam, T. T., Ta, T. A., & Mai, T. (2022). Submodularity and local search approaches for maximum capture problems under generalized extreme value models. European Journal of Operational Research, 300(3), 953–965.
De Palma, A., Ginsburgh, V., Papageorgiu, Y., & Thisse, J.-F. (1985). Heterogeneity and taste dispersion: The principle of minimum differentiation holds under sufficient heterogeneity. Econometrica, 53, 767–782.
Drezner, T. (2019). Gravity models in competitive facility location. In H. A. Eiselt & V. Marianov (Eds.), Contributions to location analysis. International series in operations research and management science (pp. 253–275). Springer.
Eaton, B. C., & Lipsey, R. G. (1979). Comparison shopping and the clustering of homogeneous firms. Journal of Regional Science, 19, 421–435.
Eaton, B. C., & Lipsey, R. G. (1982). An economic theory of central places. The Economic Journal, 92, 56–72.
Eiselt, H. A., Marianov, V., & Drezner, T. (2019). Competitive location models, Chapter 14. In G. Laporte, S. Nickel, & F. Saldanha da Gama (Eds.), Location science (2nd ed., p. 644p). Springer.
Fernández, P., Pelegrín, B., Lančinskas, A., & Žilinskas, J. (2017). New heuristic algorithms for discrete competitive location problems with binary and partially binary customer behavior. Computers and Operations Research, 79, 12–18.
Fischer, J. H., & Harrington, J. E., Jr. (1996). Product variety and firm agglomeration. The Rand Journal of Economics, 281–309.
Fitzsimons, G. J., Hutchinson, J. W., Williams, P., Alba, J. W., Chartrand, T. L., Huber, J., Kardes, F. R., Menon, G., Raghubir, P., Russo, J., Shiv, B., & Tavassoli, N. T. (2002). Non-conscious influences on customer choice. Marketing Letters, 13(3), 269–279. https://doi.org/10.1023/A:1020313710388
Fotheringham, A. S., & O’Kelly, M. E. (1989). Spatial interactions: Formulations and applications. Kluwer Academic Publishers.
Fox, E. J., Montgomery, A. L., & Lodish, L. M. (2004). Customer shopping and spending across retail formats. The Journal of Business, 77(S2), S25–S60. https://www.jstor.org/stable/10.1086/381518
Foxall, G. (2005). Understanding customer choice. Palgrave Macmillan.
Freire, A. S., Moreno, E., & Yushimito, W. F. (2016). A branch-and-bound algorithm for the maximum capture problem with random utilities. European Journal of Operational Research, 252(1), 204–212.
Gauri, D. K., Jindal, R. P., Ratchford, B., Fox, E., Bhatnagar, A., Pandey, A., Navallo, J. R., Fogarty, J., Carr, S., & Howerton, E. (2021). Evolution of retail formats: Past, present, and future. Journal of Retailing, 97(1), 42–61. https://doi.org/10.1016/j.jretai.2020.11.002
Haase, K., & Müller, S. (2014). A comparison of linear reformulations for multinomial logit choice probabilities in facility location models. European Journal of Operational Research, 232(3), 689–691.
Hakimi, S. (1990). Locations with spatial interactions: Competitive locations and games. In P. B. Mirchandani & R. L. Francis (Eds.), Discrete location theory (pp. 439–478). Wiley.
Hausman, J. A., & Newey, W. K. (2016). Individual heterogeneity and average welfare. Econometrica, 84(3), 1225–1248.
Hodgson, M. J. (1981). A location–allocation model maximizing customers’ welfare. Regional Studies, 15(6), 493–506.
Hoo, F. S. (2018). The one-stop shopping area for all your ‘Brooklyn bride’ needs. Available online at https://fashionista.com/2018/08/brooklyn-brides-bridal-shops-third-avenue. Last accessed on 01/30/2023.
Hotelling, H. (1929). Stability in competition. The Economic Journal, 39(153), 41–57.
Hübner, A., Hense, J., & Dethlefs, C. (2022). The revival of retail stores via omnichannel operations: A literature review and research framework. European Journal of Operational Research, 302, 799–818. https://doi.org/10.1016/j.ejor.2021.12.021
Huff, D. L. (1963). A probabilistic analysis of shopping center trade areas. Land Economics, 39(1), 81–89.
McCall, B. (2021). Bricks and mortar retailing far from dead – but now it’s just part of the mix. The Irish Timeshttps://www.irishtimes.com/special-reports/future-of-retail/bricks-and-mortar-retailing-far-from-dead-but-now-it-s-just-part-of-the-mix-1.4645578. Last accessed on 01/30/2023.
Jamal, M., & Lodhi, S. (2015). Customer shopping behavior in relation to factors influencing impulse buying: A case of superstores in Karachi, Pakistan. International Journal of Scientific and Research Publications, 5(12), 41–59.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decisions under risk. Econometrica, 47, 263–262.
Khapugin, S., & Melnikov, A. (2019). Local search approach for the medianoid problem with multi-purpose shopping trips. In M. Khachay, Y. Kochetov, & P. Pardalos (Eds.), Mathematical optimization theory and operations research (MOTOR 2019. Lecture Notes in Computer Science) (Vol. 11548). Springer. https://doi.org/10.1007/978-3-030-22629-9_23
Konishi, H. (2005). Concentration of competing retail stores. Journal of Urban Economics, 58(3), 488–512. https://doi.org/10.1016/j.jue.2005.08.005
Kress, D., & Pesch, E. (2016). Competitive location and pricing on networks with random utilities. Networks and Spatial Economics, 16(3), 837–863.
Krider, R. E., & Putler, D. S. (2013). Which birds of a feather flock together? Clustering and avoidance patterns, of similar retail outlets. Geographical Analysis, 45, 123–149.
Lancaster, K. J. (1966). A new approach to customer theory. Journal of Political Economy, 74(2), 132–157.
Li, M. (2015). Convenience and online consumer shopping behavior: A business anthropological case study based on the contingent valuation method. Anthropologist, 21(1,2), 8–17.
Lin, Y. H., & Tian, Q. (2021). Branch-and-cut approach based on generalized benders decomposition for facility location with limited choice rule. European Journal of Operational Research, 293(1), 109–119.
Ljubić, I., & Moreno, E. (2018). Outer approximation and submodular cuts for maximum capture facility location problems with random utilities. European Journal of Operational Research, 266(1), 46–56.
Loomes, G., Orr, S., & Sugden, R. (2009). Taste uncertainty and status quo effects in customer choice. Journal of Risk and Uncertainty, 39, 113–135. https://doi.org/10.1007/s11166-009-9076-y
Luce, R. D. (1957). A theory of individual choice behavior. Defense Technical Information Center Report. May 1957. https://apps.dtic.mil/sti/pdfs/AD0130718.pdf. Last accessed on 01/30/2023.
Luce, R. D. (1977). The choice axiom after twenty years. Journal of Mathematical Psychology, 15, 215–233.
Lüer-Villagra, A., Marianov, V., Eiselt, H. A., & Méndez-Vogel, G. (2022). The leader multipurpose shopping location problem. European Journal of Operational Research, 302(2), 470–481.
Mai, T., & Lodi, A. (2020). A multicut outer-approximation approach for competitive facility location under random utilities. European Journal of Operational Research, 284(3), 874–881.
Marianov, V., & Eiselt, H. A. (2016). On agglomeration in competitive location models. Annals of Operations Research, 246, 31–55. https://doi.org/10.1007/s10479-014-1704-5
Marianov, V., Eiselt, H. A., & Lüer-Villagra, A. (2018). Effects of multipurpose shopping trips on retail store location in a duopoly. European Journal of Operational Research, 269, 782–792. https://doi.org/10.1016/j.ejor.2018.02.024
Marianov, V., Eiselt, H. A., & Lüer-Villagra, A. (2020). The follower competitive location problem with comparison-shopping. Networks and Spatial Economics, 20(2), 367–393. https://doi.org/10.1007/s11067-019-09481-6
Martínez, F., Aguila, F., & Hurtubia, R. (2009). The constrained multinomial logit: Asemi-compensatory choice model. Transportation Research Part B: Methodological, 43(3), 365–377. https://doi.org/10.1016/j.trb.2008.06.006
Massara, F., Melara, R. D., & Liu, S. S. (2014). Impulse versus opportunistic purchasing during a grocery shopping experience. Marketing Letters, 25, 361–372.
McFadden, D. (1974). Conditional logit analysis of qualitative choice behaviour. In P. Zarembka (Ed.), Frontiers in econometrics (pp. 105–142). Academic Press.
McFadden, D., & Train, K. (2000). Mixed MNL models for discrete response. Journal of Applied Econometrics, 15(5), 447–470.
Méndez-Vogel, G., Marianov, V., Lüer-Villagra, A., & Eiselt, H. A. (2022). Store location with multipurpose shopping trips and a new random utility customers’ choice model. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2022.06.008
Mongin, P. (1998). Expected utility theory. In J. B. Davis, D. W. Hands, & M. Uskali (Eds.), The handbook of economic methodology. Edward Elgar.
Nakanishi, M., & Cooper, L. G. (1974). Parameter estimation for a multiplicative competitive interaction model: Least squares approach. Journal of Marketing Research, 11(3), 303–311.
O’Kelly, M. E. (1981). A model of the demand of retail facilities, incorporating multistop, multipurpose trips. Geographical Analysis, 13, 134–148.
Ortúzar, J. D., & Willumsen, L. G. (2022). Modelling transport (5th ed.). Wiley.
Papageorgiou, Y. Y., & Thisse, J.-F. (1985). Agglomeration as spatial interdependence between firms and households. Journal of Economic Theory, 37, 19–31.
Radu, V. (2022). Customer behavior in marketing – patterns, types, segmentation. Available online at https://www.omniconvert.com/blog/customer-behavior-in-marketing-patterns-types-segmentation/. Last accessed on 01/30/2023.
Reilly, W. J. (1929). Methods for the Study of Retail Relationships (Vol. 4). Bureau of Business Research Studies in Marketing.
Schnure, C. (2021). Brick-and-mortar retail is bouncing back. Forbes. Available online at https://www.forbes.com/sites/calvinschnure/2021/03/18/brick-and-mortar-retail-is-bouncing-back/?sh=30a76841d0f4. Last accessed on 01/30/2023.
Sheth, J. N. (2021). Future of brick-and-mortar retailing: how will it survive and thrive? Journal of Strategic Marketing, 29(7), 598–607. https://doi.org/10.1080/0965254X.2021.1891128
Shiu, E., Walsh, G., Hassan, L., & Shaw, D. (2011). Customer uncertainty revisited. Psychology and Marketing, 28(6), 584–607.
Schoemaker, P. J. H. (1980). Experiments on decisions under risk: The expected utility hypothesis. Martinus Nijho.
Snyder, L. V. (2006). Facility location under uncertainty: A review. IIE Transactions, 38(7), 547–564.
Solomon, M. R. (2017). Customer behavior: Buying, having and being (12th ed.). Pearson.
Stahl, K. (1982). Differentiate products, customer search, and locational oligopoly. Journal of Industrial Economics, 31, 97–113.
Thaler, R. H. (2015). Misbehaving: The making of behavioral economics. W W Norton & Co..
Tronier, R. M. (2022). America’s love for impulse spending is going strong in 2022. https://money.slickdeals.net/surveys/slickdeals-impulse-spending-survey-2022/. Last accessed on 01/30/2023.
Urbany, J. E., Dickson, P. R., & Wilkie, W. L. (1989). Buyer uncertainty and information search. Journal of Customer Research, 16, 208–215.
Wilson, A. G. (1967). A statistical theory of spatial distribution models. Transportation Research, 1, 253–269.
Williams, H. C. (1977). On the formation of travel demand models and economic evaluation measures of user benefit. Environment and Planning A, 9, 285–344.
Wolinsky, A. (1983). Retail trade concentration due to customers’ imperfect information. Bell Journal of Economics, 14, 275–282.
Acknowledgments
We gratefully acknowledge the support by grants FONDECYT 1220047, ANID PIA/PUENTE AFB220003, and Ph.D. scholarship from CONICYT-PFCHA/Doctorado Nacional/2019-21190765.
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Marianov, V., Méndez-Vogel, G. (2023). Customer-Related Uncertainties in Facility Location Problems. In: Eiselt, H.A., Marianov, V. (eds) Uncertainty in Facility Location Problems. International Series in Operations Research & Management Science, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-031-32338-6_3
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