How artificial intelligence can change the core of marketing theory
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DOIhttp://dx.doi.org/10.21511/im.16(2).2020.08
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Article InfoVolume 16 2020, Issue #2, pp. 91-103
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Various recently-introduced applications of artificial intelligence (AI) operate at the interface between businesses and consumers. This paper looks at whether these innovations have relevant implications for marketing theory. The latest literature on the connection between AI and marketing has emphasized a great variety of AI applications that qualify this relationship. Based on these studies but focusing only on the applications with a direct impact on the relationship at the very heart of marketing, i.e., the one between firms and consumers, the paper analyzes three categories of AI applications: AI-based shipping-then-shopping, AI-based service robots, and AI-based smart products and domestic robots. The main result of this first analysis is that all three categories have to do, each in their own way, with mass customization. A discussion of this common trait leads us to recognize their ways to mass customization that – unlike the traditional approach developed thanks to flexible automation and product modularity technologies – place the customization process within a broader perspective of consumer needs management. This change in approach means that marketing should focus more on managing consumers’ needs than directly on the satisfaction of those needs. This finding marks a genuine discontinuity that opens up a new space for reflection for scholars and marketing managers alike.
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JEL Classification (Paper profile tab)M15, M31, O33
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References79
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Tables0
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Figures2
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- Figure 1. From traditional to AI-based mass customization
- Figure 2. From traditional to AI-based service industrialization
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- Addis, M., & Holbrook, M. (2002). On the conceptual link between mass customization and experiential consumption: An explosion of subjectivity. Journal of Consumer Behavior, 1(1), 50-66.
- Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34-49.
- Arora, N., Dreze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., Joshi, Y., Kumar, V., Lurie, N., Neslin, S., Sajeesh, S., Su, M., Syam, N., Thomas, J., & Zhang, Z. J. (2008). Putting one-to-one marketing to work: Personalization, customization, and choice. Marketing Letters, 19(3-4), 305-321.
- Baker, M. J. (2014). Marketing strategy and management (5th ed.). New York: Palgrave Macmillan.
- Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2020). Service robot implementation: A theoretical framework and research agenda. The Service Industries Journal, 40(3-4), 203-225.
- Bogue, R. (2017). Domestic robots: Has their time finally come? Industrial Robot, 44(2), 129-136.
- Bogue, R. (2019). Strong prospects for robots in retail. Industrial Robot, 46(3), 326-331.
- Čaić, M., Odekerken-Schröder, G., & Mahr, D. (2018). Service robots: Value co-creation and co-destruction in elderly care networks. Journal of Service Management, 29(2), 178-205.
- Cova, B., Dalli, D., & Zwick, D. (2011). Critical perspectives on consumers’ role as “producers”: Broadening the debate on value co-creation in marketing processes. Marketing Theory, 11(3), 231-241.
- Daugherty, P. R., & Wilson, H. J. (2018). Human + machine: Reimagining work in the age of AI. Boston: Harvard Business School Press.
- Davenport, T. H. (2018). The AI advantage: How to put the artificial intelligence revolution to work. Cambridge: The MIT Press.
- Davenport, T. H, Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.
- De Keyser, A., Köcher, S., Alkire, L., Verbeeck, C., & Kandampully, J. (2019). Frontline service technology infusion: Conceptual archetypes and future research directions. Journal of Service Management, 30(1), 156-183.
- Dellaert, B. G., & Stremersch, S. (2005). Marketing mass-customized products: Striking a balance between utility and complexity. Journal of Marketing Research, 42(2), 219-227.
- Di Bernardo, B., & Grandinetti, R. (2012). Contexts of experience. In F. Belussi, F., & U. Staber (Eds.), Managing networks of creativity (pp. 229-242). New York: Routledge.
- Fan, X., Ning, N., & Deng, N. (2020). The impact of the quality of intelligent experience on smart retail engagement. Marketing Intelligence & Planning.
- Feitzinger, E., & Lee, H. L. (1997). Mass customization at Hewlett-Packard: The power of postponement. Harvard Business Review, 75(1), 116-123.
- Fogliatto, F. S., Da Silveira, G. J., & Borenstein, D. (2012). The mass customization decade: An updated review of the literature. International Journal of Production Economics, 138(1), 14-25.
- Franke, N., Keinz, P., & Steger, C. J. (2009). Testing the value of customization: When do customers really prefer products tailored to their preferences? Journal of Marketing, 73(5), 103-121.
- Franke, N., & Schreier, M. (2010). Why customers value self-designed products: The importance of process effort and enjoyment. Journal of Product Innovation Management, 27(7), 1020-1031.
- García, C. G, Meana-Llorián, D., García-Bustelo, B. C. P., & Lovelle, J. M. C. (2017). A review about smart objects, sensors, and actuators. International Journal of Interactive Multimedia and Artificial Intelligence, 4(3), 1-10.
- Gilmore, J. H., & Pine II, B. J. (1997). The four faces of mass customization. Harvard Business Review, 75(1), 91-101.
- Gilmore, J. H., & Pine II, B. J. (2000). Markets of one: Creating customer-unique value through mass customization. Boston: Harvard Business School Press.
- Han, K. S., & Noh, M. H. (1999). Critical failure factors that discourage the growth of electronic commerce. International Journal of Electronic Commerce, 4(2), 25-43.
- Haug, A., Hvam, L., & Mortensen, N. H. (2012). Definition and evaluation of product configurator development strategies. Computers in Industry, 63(5), 471-481.
- Horvitz, E., & Mulligan, D. (2015). Data, privacy, and the greater good. Science, 349(6245), 253-255.
- Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
- Kaartemo, V., & Helkkula, A. (2018). A systematic review of artificial intelligence and robots in value co-creation: Current status and future research avenues. Journal of Creating Value, 4(2), 211-228.
- Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.
- Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263-267.
- Kotha, S. (1995). Mass customization: Implementing the emerging paradigm for competitive advantage. Strategic Management Journal, 16(S1), 21-42.
- Kotler, P. (1965). Diagnosing the marketing takeover. Harvard Business Review, 43(6), 70-72.
- Kotler, P., & Armstrong, G. (2018). Principles of marketing (17th ed.). Harlow: Pearson Education.
- Kramer, T. (2007). The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. Journal of Marketing Research, 44(2), 224-233.
- Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155.
- Lake, K. (2018). Stitch Fix’s CEO on selling personal style to the mass market. Harvard Business Review, 96(3), 35-40.
- Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., Wünderlich, N. W., & De Keyser, A. (2017). “Service Encounter 2.0”: An investigation into the roles of technology, employees and customers. Journal of Business Research, 79, 238-246.
- Levitt, T. (1960). Marketing myopia. Harvard Business Review, 38(4), 45-56.
- Levitt, T. (1976). Industrialization of service Harvard Business Review, 54(5), 63-74.
- Lillis, C. M., & McIvor, B. J. (1985). MDSSs at General Electric: Implications for the 1990s from experiences in the 1970s and 1980s. In R. D. Buzzell (Ed.), Marketing in the electronic age (pp. 89-106). Cambridge: Harvard University Press.
- Lin, W., Yueh, H.-P., Wu, H.-Y., & Fu, L.-C. (2014). Developing a service robot for a children’s library: A design-based research approach. Journal of the Association for Information Science and Technology, 65(2), 290-301.
- Longoni, C., Bonezzi, A., & Morewedge, C. (2019). Resistance to medical artificial intelligence. Journal of Consumer Research, 46(4), 629-50.
- Luce, L. (2019). Artificial intelligence for fashion: How AI is revolutionizing the fashion industry. New York: Apress.
- Maass, W., & Varshney, U. (2008). Preface to the focus theme section: “Smart products”. Electronic Markets, 18(3), 211-215.
- Malone, T. W. (2018). How human-computer “superminds” are redefining the future of work. MIT Sloan Management Review, 59(4), 34-41.
- Marinova, D., de Ruyter, K., Huang, M.-H., Meuter, M. L., & Challagalla, G. (2017). Getting smart: Learning from technology-empowered frontline interactions. Journal of Service Research, 20(1), 29-42.
- Marr, B., & Ward, M. (2019). Artificial intelligence in practice: How 50 successful companies used AI and machine learning to solve problems. Chichester: Wiley.
- Martin, N., & Morich, K. (2011). Unconscious mental processes in consumer choice: Toward a new model of consumer behavior. Journal of Brand Management, 18(7), 483-505.
- Matzler, K., Waiguny, M., & Füller, J. (2007). Spoiled for choice: Consumer confusion in Internet-based mass customization. Innovative Marketing, 3(3), 7-18.
- McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… Examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28-37.
- Meyer, G. G., Främling, K., & Holmström, J. (2009). Intelligent products: A survey. Computers in Industry, 60(3), 137-148.
- Modi, D., & Zhao, L. (2019). Trunk Club: Revolutionizing the retail model in fashion. In B. Jin, & E. Cedrola (Eds.), Process innovation in the global fashion industry (pp. 99-121). New York: Palgrave Pivot.
- Pagallo, U. (2013). Robots in the cloud with privacy: A new threat to data protection? Computer Law & Security Review, 29(5), 501-508.
- Pee, L. G., Pan, S. L., & Cui, L. (2019). Artificial intelligence in healthcare robots: A social informatics study of knowledge embodiment. Journal of the Association for Information Science and Technology, 70(4), 351-369.
- Peppers, D., & Rogers, M. (1993). The one-to-one future: Building relationships one customer at a time. New York: Century Doubleday.
- Pine II, B. J. (1993). Mass customization: The new frontier in business competition. Boston: Harvard Business School Press.
- Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
- Prahalad, C. K., & Ramaswamy, V. (2004). The future of competition: Co-creating unique value with customers. Boston: Harvard Business School Press.
- Robinson, S., Orsingher, C., Alkire, L., De Keyser, A., Giebelhausen, M., Papamichail, K. N., Shams, P., & Temerak, M. S. (2019). Frontline encounters of the AI kind: An evolved service encounter framework. Journal of Business Research.
- Schwab, K. (2017). The fourth industrial revolution. New York: Crown Business.
- Shen, A. (2014). Recommendations as personalized marketing: Insights from customer experiences. Journal of Services Marketing, 28(5), 414-427.
- Simonson, I. (2005). Determinants of customers’ responses to customized offers: Conceptual framework and research propositions. Journal of Marketing, 69(1), 32-45.
- Sohn, K., & Kwon, O. (2019). Technology acceptance theories and factors influencing artificial intelligence-based intelligent products. Telematics and Informatics, 47, 1-14.
- Steinhoff, L., Arli, D., Weaven, S., & Kozlenkova, I. V. (2019). Online relationship marketing. Journal of the Academy of Marketing Science, 47(3), 369-393.
- Sterne, J. (2017). Artificial intelligence for marketing: practical applications. Hoboken: Wiley.
- Syam, N., Krishnamurthy, P., & Hess, J. D. (2008). That’s what i thought i wanted? Miswanting and regret for a standard good in a mass-customized world. Marketing Science, 27(3), 379-397.
- Tao, Q., & Xu, Y. (2018). Fashion subscription retailing: An exploratory study of consumer perceptions. Journal of Fashion Marketing and Management, 22(4), 494-508.
- Teichmann, K., Scholl-Grissemann, U., & Stokburger-Sauer, N. E. (2016). The power of codesign to bond customers to products and companies: The role of toolkit support and creativity. Journal of Interactive Marketing, 36, 15-30.
- Tiihonen, J., & Felfernig, A. (2017). An introduction to personalization and mass customization. Journal of Intelligent Information Systems, 49(1), 1-7.
- Tomiyama, T., Lutters, E., Stark, R., & Abramovici, M. (2019). Development capabilities for smart products. CIRP Annals, 68(2), 727-750.
- Ustundag, A., & Cevikcan, E. (2017). Industry 4.0: Managing the digital transformation. Cham: Springer.
- van Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017). Domo arigato Mr. Roboto: Emergence of automated social presence in organizational frontlines and customers’ service experiences. Journal of Service Research, 20(1), 43-58.
- Van Wynsberghe, A. (2016). Healthcare robots: Ethics, design and implementation. Abingdon: Routledge.
- Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1-17.
- Warren, C., McGraw, A. P., & Van Boven, L. (2011). Values and preferences: Defining preference construction. Wiley Interdisciplinary Reviews: Cognitive Science, 2(2), 193-205.
- Wierenga, B. (2010). Marketing and artificial intelligence: Great opportunities, reluctant partners? In J. Casillas, & F. J. Martínez-López (Eds.), Marketing intelligent systems using soft computing: Managerial and research applications (pp. 1-8). Berlin: Springer-Verlag.
- Wierenga, B., & Oude Ophuis, P. A. M. (1997). Marketing decision support systems: Adoption, use, and satisfaction. International Journal of Research in Marketing, 14(3), 275-290.
- Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 295, 907-931.
- Zipkin, P. (2001). The limits of mass customization. MIT Sloan Management Review, 42(3), 81-87.