Advertisement

Journal of the Academy of Marketing Science

, Volume 44, Issue 1, pp 24–45 | Cite as

Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing

  • V. KumarEmail author
  • Ashutosh Dixit
  • Rajshekar (Raj) G. Javalgi
  • Mayukh Dass
Conceptual/Theoretical Paper

Abstract

In this digital era, marketing theory and practice are being transformed by increasing complexity due to information availability, higher reach and interactions, and faster speeds of transactions. These have led to the adoption of intelligent agent technologies (IATs) by many companies. As IATs are relatively new and technologically complex, several definitions are evolving, and the theory in this area is not yet fully developed. There is a need to provide structure and guidance to marketers to further this emerging stream of research. As a first step, this paper proposes a marketing-centric definition and a systematic taxonomy and framework. The authors, using a grounded theory approach, conduct an extensive literature review and a qualitative study in which interviews with managers from 50 companies in 22 industries reveal the importance of understanding IAT applications and adopting them. Further, the authors propose an integrated conceptual framework with several propositions regarding IAT adoption. This research identifies the gaps in the literature and the need for adoption of IATs in the future of marketing given changing consumer behavior and product and industry characteristics.

Keywords

Intelligent agent technologies Marketing strategy Grounded theory 

Notes

Acknowledgments

We thank the editor, and the reviewers for their valuable guidance in revising this manuscript. We also thank Andrew Petersen, Denish Shah, Insu Park, Ifitkhar Sikder, Gayatri Shukla and Hannah Kim for their comments on the earlier version of this manuscript. We also thank Renu for copyediting this manuscript.

References

  1. Abegglen, J. C., & Stalk, G., Jr. (1985). Kaisha the Japanese corporation (2nd ed.). New York: Basic Books Inc.Google Scholar
  2. Aizawa, A. (2002). An Approach to Microscopic Clustering of Terms and Documents. In M. Ishizuka & A. Sattar (Eds.), Pricai 2002: Trends in Artificial Intelligence. Tokyo: Springer.Google Scholar
  3. Antia, K. D., & Frazier, G. L. (2001). The severity of contract enforcement in inter-firm channel relationships. Journal of Marketing, 65(October), 67–81.CrossRefGoogle Scholar
  4. Brustoloni, J. C. (1991). Autonomous agents: characterization and requirements. Carnegie Mellon Technical Report CMU-CS-91-204, Carnegie Mellon University 1991.Google Scholar
  5. Bace, R. G. (2000). Intrusion detection. Indianapolis: Macmillian.Google Scholar
  6. Bakos Yannis, J. (1997). Reducing buyer search costs: implications for electronic marketplaces. Management Science, 43(12), 1613–1630.Google Scholar
  7. Balasubramanian, S., Krishnan, V. V., & Sawhney, M. (2000). New Offering Realization in the Networked Digital Environment. In J. Wind & V. Mahajan (Eds.), Digital Marketing (pp. 310–338). New York: Wiley.Google Scholar
  8. Barney, J. B. (2001). Is the resource-based view a useful perspective for strategic management research? yes. Academy of Management Review, 26(1), 41–56.Google Scholar
  9. Bass, F. M. (1969). A new product growth model for consumer durables. Management Science, 15(January), 215–227.CrossRefGoogle Scholar
  10. Bedford, D. (2012). “Expanding the definition and measurement of knowledge economy—integrating triple bottom line factors into knowledge economy index models and methodologies” Proceedings of the European Conference on Intellectual Capital, 67–74.Google Scholar
  11. Beverland, M. B., Kates, S. M., Lindgreen, A., & Chung, E. (2010). Exploring consumer conflict management in service encounters. Journal of the Academy of Marketing Science, 38, 617–633.CrossRefGoogle Scholar
  12. Binmore, K., & Vulkan, N. (1999). Applying game theory to automated negotiation. Netnomics, 1(1), 1–9.CrossRefGoogle Scholar
  13. Bodapati, A. V. (2008). Recommendation systems with purchase data. Journal of Marketing Research, 45(1), 77–93.CrossRefGoogle Scholar
  14. Boehm, B., & Turner, R. (2005). Managing challenges to implementing agile processes in traditional development organizations. IEEE Software, 22(5), 30–39.CrossRefGoogle Scholar
  15. Chaib-Draa, B., & Dignum, F. (2002). Trends in agent communication language. Computational Intelligence, 18(2), 89–101.CrossRefGoogle Scholar
  16. Chang, J.-H., Lee, J. W., Kim, Y., & Zhang, B.-T. (2002). Topic Extraction from Text Documents Using Multiple-Cause Networks. In M. Ishizuka & A. Sattar (Eds.), Pricai 2002: Trends in Artificial Intelligence. Tokyo: Springer.Google Scholar
  17. Chen, D.-N., Jeng, B., Lee, W.-P., & Chuang, C.-H. (2008). An agent-based model for consumer-to-business electronic commerce. Expert Systems with Applications, 34(2008), 469–481.CrossRefGoogle Scholar
  18. Chen, Y., & Sudhir, K. (2004). When shopbots meet emails: implications for price competition on the internet. Quantitative Marketing and Economics, 2(3), 233–255.CrossRefGoogle Scholar
  19. Clemons, E. K. (2009). Business models for monetizing internet applications and web sites: experience, theory, and predictions. Journal of Management Information Systems, 26(2), 15–41.CrossRefGoogle Scholar
  20. Coen, M. H. (1994). ″SodaBot: A software agent environment and construction system″ A. I. Technical Report 1493, M. I. T. Artificial Intelligence Laboratory.Google Scholar
  21. Day, G. (1999). The market driven organization: Understanding, attracting, and keeping valuable customer. New York: The Free Press.Google Scholar
  22. De Figueiredo, J. M. (2000). Finding sustainable profitability in electronic commerce. Sloan Management Review, 41(4), 41–52.Google Scholar
  23. Deshpande, R., Farley, J. U., & Webster, F. E., Jr. (1993). Corporate culture, customer orientation, and innovativeness in Japanese firms: a quadrad analysis. Journal of Marketing, 57(1), 23–37.CrossRefGoogle Scholar
  24. Diehl, K., Kornish, L. J., & Lynch, J. G., Jr. (2003). Smart agents: when lower search costs for quality information increase price sensitivity. Journal of Consumer Research, 30(1), 56–71.CrossRefGoogle Scholar
  25. Dubosson-Torbay, M., Osterwalder, A., & Pigneur, Y. (2002). E-business model design, classification, and measurements. Thunderbird International Business Review, 44(1), 5–23.CrossRefGoogle Scholar
  26. Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: what are they? Strategic Management Journal, 21(10–11), 1105–1121.CrossRefGoogle Scholar
  27. Fasli, M. (2007). On agent technology for e-commerce: trust, security and legal issues. The Knowledge Engineering Review, 22(1), 3–35.CrossRefGoogle Scholar
  28. Festa, P., Pardalos, P. M., & Resende, M. G. C. (1999). Feedback Set Problems. In D.-Z. Du & P. M. Pardalos (Eds.), Handbook of Combinatorial Optimization. Norwell: Kluwer Academic Publishers.Google Scholar
  29. Franklin, S., & Graesser, A. (1996). Is it an agent, or just a program? A taxonomy for autonomous agents. In J. Muller & J. Gauldie (Eds.), Intelligent Agents III (pp. 21–35). Berlin: Springer.Google Scholar
  30. Frazier, G. L., & Howell, R. D. (1983). Business definition and performance. Journal of Marketing, 47(Spring), 59–67.CrossRefGoogle Scholar
  31. Frazier, G. L., Maltz, E., Antia, K. D., & Rindfleisch, A. (2009). Distributor sharing of strategic information with suppliers. Journal of Marketing, 73(July), 31–43.CrossRefGoogle Scholar
  32. Glaser, Barney G. (1994), More Grounded Theory Methodology. A Reader, Mill Valley, Ca.: Sociology Press.Google Scholar
  33. Glaser, B. G. (1998). Doing grounded theory: Issues and discussions. Mill Valley: Sociology Press.Google Scholar
  34. Glaser, B. G., & Strauss, A. L. (1967). Discovery of grounded theory: Strategies for qualitative research. Hawthorne: Aldine de Gruyter.Google Scholar
  35. Glazer, R. (1991). Marketing in an information-intensive environment: strategic implications of knowledge as an asset. Journal of Marketing, 55(4), 1–19.CrossRefGoogle Scholar
  36. Goldberg, I. A. (2000). A pseudonymous communications infrastructure for the internet, doctoral dissertation, computer science. Berkeley: University of California.Google Scholar
  37. Goulding, C. (2002). Grounded theory: A practical guide for management business and market researchers. London: Sage.Google Scholar
  38. Greshoff, A. D., & West, P. M. (1998). Using a community of knowledge to build intelligent agents. Marketing Letters, 9(1), 79–91.CrossRefGoogle Scholar
  39. Grewal, R., Chakravarty, A., & Saini, A. (2010). Governance mechanisms in business-to-business electronic markets. Journal of Marketing, 74(4), 45–62.CrossRefGoogle Scholar
  40. Guttman, R. H., Moukas, A. G., & Maes, P. (1998). Agent mediated electronic commerce: a survey. The Knowledge Engineering Review, 13(2), 147–159.CrossRefGoogle Scholar
  41. Hansen, D. R., & Mowen, M. M. (2011). Cornerstones of cost accounting. Mason: South-Western Cengage Learning.Google Scholar
  42. Hodgdon, P. N. (1997). The role of intelligent agent software in the future of direct response. Journal of Direct Marketing, 59(9), 141–143.Google Scholar
  43. Hoffmann, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: conceptual foundations. Journal of Marketing, 60(3), 50–68.CrossRefGoogle Scholar
  44. Huang, C.-C., Liang, W.-Y., Lai, Y.-H., & Lin, Y.-C. (2010). The agent-based negotiating process for B2C e-commerce. Expert Systems with Applications, 37(2010), 348–359.CrossRefGoogle Scholar
  45. Huhns, M. N., & Singh, M. P. (1998). Readings in agents. San Francisco: Morgan Kaufmann.Google Scholar
  46. Hunt, S. D. (2002). Foundations of marketing theory: Toward a general theory of marketing. New York: M.E. Sharpe, Inc.Google Scholar
  47. Iacobucci, D., Arabie, P., & Bodapati, A. (2000). Recommendation agents on the internet. Journal of Interactive Marketing, 14(3), 2–11.CrossRefGoogle Scholar
  48. Iyer, G., & Pazgal, A. (2003). Internet shopping agents: virtual co-location and competition. Marketing Science, 22(1), 85–106.CrossRefGoogle Scholar
  49. Jaworski, B. J., & Kohli, A. K. (1993). Market orientation: antecedents and consequences. Journal of Marketing, 57(3), 53–70.CrossRefGoogle Scholar
  50. Johnson, J. L., Lee, R. P., Saini, A., & Grohmann, B. (2003). Market-focused strategic flexibility: conceptual advances and an integrative model. Journal of the Academy of Marketing Science, 31(1), 74–89.CrossRefGoogle Scholar
  51. Jose C. Brustoloni (1991). Autonomous Agents: Characterization and Requirements. Carnegie Mellon Technical Report CMU-CS-91-204, Carnegie Mellon UniversityGoogle Scholar
  52. Kobsa, A., & Schreck, J. (2003). Privacy through pseudonymity in user-adaptive systems. ACM Transactions on Internet Technology, 3(2), 149–183.CrossRefGoogle Scholar
  53. Köhler, C. F., Rohm, A. J., De Ruyter, K., & Wetzels, M. (2011). Return on interactivity: the impact of online agents on newcomer adjustment. Journal of Marketing, 75(2), 93–108.CrossRefGoogle Scholar
  54. Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: the construct, research propositions, and managerial implications. Journal of Marketing, 54(2), 1–18.CrossRefGoogle Scholar
  55. Kotler, P. (1999). Marketing Management (Millenniumth ed.). New Jersey: Prentice Hall.Google Scholar
  56. Kumar, V., Jones, E., Venkatesan, R., & Leone, R. P. (2011). Is market orientation a source of sustainable competitive advantage or simply the cost of computing? Journal of Marketing, 75(1), 16–30.CrossRefGoogle Scholar
  57. Kumar, V., & Reinartz, W. (2012). Customer relationship management: Concept, strategy, and tools. Heidelberg: Springer.CrossRefGoogle Scholar
  58. Liang, W.-Y., & Huang, C.-C. (2002). The agent-based collaboration information system of product development. International Journal of Information Management, 22(3), 211–224.CrossRefGoogle Scholar
  59. Liberman, H., Faabog, A., Espinosa, J. M., & Stocky, T. (2004). Commonsense on the go. BT Technology Journal, 22(4), 241–252.CrossRefGoogle Scholar
  60. Liu, H, Lieberman, H and Selker, T (2002). “Automatic affective feedback in an email browser,” in MIT Media Laboratory Software Agent Group Technical Report, November.Google Scholar
  61. Lynch, J. G., Jr., & Ariely, D. (2000). Wine online: search cost affect competition on price. quality, and distribution. Marketing Science, 19(1), 83–101.CrossRefGoogle Scholar
  62. MacKenzie, S. B., & Lutz, R. J. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48–65.CrossRefGoogle Scholar
  63. Maes, P. (1994). Agents that reduce work and information overload. Communications of the ACM, 37(7), 30–40.CrossRefGoogle Scholar
  64. McAfee, A., & Brynjolfsson, E. (2008). Investing in the it that makes a competitive difference. Harvard Business Review, 86(7/8), 98–107.Google Scholar
  65. Menguc, B., & Auh, S. (2006). Creating a firm-level dynamic capability through capitalizing on market orientation and innovativeness. Journal of the Academy of Marketing Science, 34(1), 63–73.CrossRefGoogle Scholar
  66. Montgomery, A. L., Hosanagar, K., Krishnan, R., & Clay, K. B. (2004). Designing a better shopbot. Management Science, 50(2), 189–206.CrossRefGoogle Scholar
  67. Moorman, C., Deshpandé, R., & Zaltman, G. (1993). Factors affecting trust in market research relationships. Journal of Marketing, 57(1), 81–101.CrossRefGoogle Scholar
  68. Morgan, G. (1997). Images of organizations (2nd ed.). California: Sage Pubs, Inc.Google Scholar
  69. Murthi, B. P. S., & Sarkar, S. (2003). The role of the management science in research on personalization. Management Science, 49(10), 1344–1362.CrossRefGoogle Scholar
  70. Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(4), 20–35.CrossRefGoogle Scholar
  71. Němacová, Z., & Dvořák, J. (2011). The model of e-commerce strategy focused on customers. Economics and Management, 16, 1292–1297.Google Scholar
  72. Olson, E. M., Slater, S. F., & Hult, G. T. M. (2005). The importance of structure and process to strategy implementation. Business Horizon, 48, 47–54.CrossRefGoogle Scholar
  73. Osterwalder, A (2009). “Business model alchemist: Scanning your business model’s environment” (accessed April 25, 2011), [available at http://www.businessmodelalchemist.com/2009/07/scanning-your-business-models.html].
  74. Palmatier, R. W., Dant, R. P., & Grewal, D. (2007). A comparative longitudinal analysis of theoretical perspectives of interorganizational relationship performance. Journal of Marketing, 71(4), 172–194.CrossRefGoogle Scholar
  75. Pant, G., & Menczer, F. (2002). Myspiders: evolve your own intelligent web crawlers. Autonomous Agents and Multi-Agent Systems, 5(2), 221–229.CrossRefGoogle Scholar
  76. Peppers, D., Rogers, M., & Dorf, B. (1999). Is your company ready for one-to-one marketing? Harvard Business Review, 77(1), 151–160.Google Scholar
  77. Maes, P. ed (1991). Designing autonomous agents, MIT Press.Google Scholar
  78. Porter, M. E. (2001). Strategy and the internet. Harvard Business Review, 79(3), 62–78.Google Scholar
  79. Preist, C, Bartolini, C and Phillips, I (2001). “Algorithm design for agents which participate in multiple simultaneous auctions” Agent-Mediated Electronic Commerce III: Lecture Notes in Computer Science, 139–54.Google Scholar
  80. Hayes-Roth, R (1995). An architecture for adaptive intelligent systems. Artificial Intelligence: Special Issue on Agents and Interactivity, (72): 329–365.Google Scholar
  81. Reibstein, D. J. (2002). What attracts customers to online stores, and what keeps them coming back? Journal of the Academy of Marketing Science, 30(4), 465–473.CrossRefGoogle Scholar
  82. Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: Free Press.Google Scholar
  83. Russell, S. J. and P. Norvig (1995). Artificial intelligence: A modern approach. Prentice Hall.Google Scholar
  84. Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004). Return on marketing: using customer equity to focus marketing strategy. Journal of Marketing, 68(1), 109–127.CrossRefGoogle Scholar
  85. Rust, R. T., & Oliver, R. W. (1994). The death of advertising. Journal of Advertising, 23(4), 71–77.CrossRefGoogle Scholar
  86. Rust, R. T., & Varki, S. (1996). Rising from the ashes of advertising. Journal of Business Research, 37(3), 173–181.CrossRefGoogle Scholar
  87. Schurr, P. H., & Ozanne, J. L. (1985). Influence on exchange processes: buyers’ preconceptions of a seller’s trustworthiness and bargaining toughness. Journal of Consumer Research, 11(4), 939–953.CrossRefGoogle Scholar
  88. Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. NewYork: Doubleday/Currency.Google Scholar
  89. Shardanand, U and Maes, P (1995), “Social information filtering: algorithms for automating ‘word of mouth’,” in Proceedings of CHI′95, Human Factors in Computing Systems, 210–17.Google Scholar
  90. Sheng, Y. P., Mykytyn, P. P., Jr., & Litecky, C. R. (2005). Competitor analysis and its defenses in the e-marketplace. Communications of the ACM, 48(8), 107–112.CrossRefGoogle Scholar
  91. Sinkovics, R. R., Penz, E., & Ghauri, P. N. (2005). Analyzing textual data in international marketing research. Qualitative Marketing Research: An International Journal, 8(1), 9–38.CrossRefGoogle Scholar
  92. Smith, M. D. (2002). The impact of shopbots on electronic markets. Journal of the Academy of Marketing Science, 30(4), 446–454.CrossRefGoogle Scholar
  93. Smith, M. D., & Brynjolfson, E. (2001). Customer decision making at an internet shopbot: brand matters. Journal of Industrial Economics, 49(4), 541–558.CrossRefGoogle Scholar
  94. Smith, D. C., Cypher, A., & Spohrer, J. (1994). Kidsim: programming agents without a programming language. Communications of the ACM, 7(37), 55–67.Google Scholar
  95. Somefun K, Gerding, E, Bohte,S and La Poutré, H. (2003). “Automated negotiation and bundling of information goods” in Proceedings of the 5th Workshop on Agent Mediated Electronic Commerce (AMEC V). Melbourne, Australia.Google Scholar
  96. Stewart, D. W., & Pavlou, P. A. (2002). From consumer response to active consumer: measuring the effectiveness of interactive media. Journal of the Academy of Marketing Science, 30(4), 376–396.CrossRefGoogle Scholar
  97. Strauss, A. L., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks: Sage.Google Scholar
  98. Sujan, H., Weitz, B. A., & Kumar, N. (1994). Learning orientation, working smart, and effective selling. Journal of Marketing, 58(3), 39–52.CrossRefGoogle Scholar
  99. Tanimoto, J., & Fujii, H. (2003). A study of diffusional characteristics of information on a human network analyzed by a multi-agent simulator. The Social Science Journal, 40(3), 479–485.CrossRefGoogle Scholar
  100. Taylor, J. W. (1992). Competitive intelligence: a status report on US business practices. Journal of Marketing Management, 8, 117–125.CrossRefGoogle Scholar
  101. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.CrossRefGoogle Scholar
  102. Tellis, G. J. (1986). Beyond the many faces of price: an integration of pricing strategies. Journal of Marketing, 50(4), 146–160.CrossRefGoogle Scholar
  103. Timmers, P and Gasόs, J (2001).“Agent technologies and business models for electronic commerce” In Agent-Mediated Electronic Commerce III, Current Issues in Agent Based Electronic Commerce Systems, Springer, 177–90.Google Scholar
  104. Titkov, L., Poslad, S., & Tan, J. J. (2006). An integrated approach to user centered privacy for mobile information services. Applied Artificial Intelligence, 20(2–4), 159–178.CrossRefGoogle Scholar
  105. Urban, G. L., Sultan, F., & Qualls, W. (1999). Design and evaluation of a trust based advisor on the internet. Cambridge: Sloan School of Management, Massachusetts Institute of Technology.Google Scholar
  106. Varadarajan, P. R., & Yadav, M. S. (2002). Marketing strategy and the internet: an organizing framework. Journal of the Academy of Marketing Science, 30(4), 296–312.CrossRefGoogle Scholar
  107. Vulkan, N., & Jennings, N. R. (2000). Efficient mechanisms for the supply of services in multi-agent environments. Decision Support Systems, 28(1–2), 5–19.CrossRefGoogle Scholar
  108. Warkentin, M, Sugumaran, V and Bapna, R (2001).“Intelligent agents for electronic commerce: trends and future impact on business models and markets.” in Agent-Mediated Electronic Commerce III, Current Issues in Agent Based Electronic Commerce Systems, Springer, 101–20.Google Scholar
  109. Wiedmann, K. P., Walsh, G., & Mitchell, V. W. (2001). The mannmaven: an agent for diffusing market information. Journal of Marketing Communications, 7(4), 195–212.CrossRefGoogle Scholar
  110. Wooldridge, M. (2002). An introduction to multi agent systems. Chichester: John Wiley and Sons.Google Scholar
  111. Zahay, D. L., & Handfield, R. B. (2004). The role of learning and technical capabilities in predicting adoption of B2B technologies. Industrial Marketing Management, 33, 627–641.CrossRefGoogle Scholar
  112. Zhao, K., Xia, M., & Shaw, M. J. (2007). An integrated model of consortium bases e-business standardization: collaborative development and adoption with network externalities. Journal of Management Information Systems, 23(4), 247–271.CrossRefGoogle Scholar
  113. Zhu, Z., Nakata, C., Sivakumar, K., & Grewal, D. (2007). Self-service technology effectiveness: the role of design features and individual traits. Journal of the Academy of Marketing Science, 35(4), 492–506.CrossRefGoogle Scholar

Copyright information

© Academy of Marketing Science 2015

Authors and Affiliations

  • V. Kumar
    • 1
    Email author
  • Ashutosh Dixit
    • 2
  • Rajshekar (Raj) G. Javalgi
    • 2
  • Mayukh Dass
    • 3
  1. 1.J. Mack Robinson College of BusinessGeorgia State UniversityAtlantaUSA
  2. 2.Ahuja College of BusinessCleveland State UniversityClevelandUSA
  3. 3.Rawls College of BusinessTexas Tech UniversityLubbockUSA

Personalised recommendations