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Intelligent agents as innovations

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Abstract

This paper explores the treatment of intelligent agents as innovations. Past writings in the area of intelligent agents focus on the technical merits and internal workings of agent-based solutions. By adopting a perspective on agents from an innovations point of view, a new and novel description of agents is put forth in terms of their degrees of innovativeness, competitive implications, and perceived characteristics. To facilitate this description, a series of innovation-based theoretical models are utilized as a lens of analysis, namely Kleinschmidt and Cooper’s (J Prod Innovation Manage 8:240–251, 1991) market and technological newness map, Abernathy and Clark’s (Res Policy 14:3–22, 1985) competitive implications framework, and Moore and Benbasat’s (Inf Syst Res 2:192–222, 1991) list of perceived innovating characteristics. Together, these models provide a theoretical foundation by which to describe intelligent agents, yielding new insights and perceptions on this relatively new form of software application.

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Notes

  1. Here, risk is defined as the probability of an innovative product or service being commercially successful.

References

  • Abernathy WJ, Clark KB (1985) Innovation: mapping the winds of creative destruction. Res Policy 14:3–22

    Article  Google Scholar 

  • Agarwal R, Prasad J (1997) The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decis Sci 28:557–582

    Google Scholar 

  • Agarwal R, Prasad J (1998) A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf Syst Res 9:204–215

    Google Scholar 

  • Agarwal R, Tanniru M, Wilemon D (1997) Assimilating information technology innovations: strategies and moderating influences. IEEE Trans Eng Manage 44:347–358

    Article  Google Scholar 

  • Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs, New Jersey

    Google Scholar 

  • Allen JP (2000) Information systems as technological innovation. Inf Technol People 13:210–221

    Google Scholar 

  • Astebro T (1995) The effect of management and social interaction on the intra-firm diffusion of electronic mail systems. IEEE Trans Eng Manage 42:319–331

    Article  Google Scholar 

  • Bass FM (1969) A new product growth model for consumer durables. Manage Sci 15:215–227

    Google Scholar 

  • Booz, Allen and Hamilton Inc (1982) New product management for the 1980s. Booz, Allen and Hamilton Inc, New York

    Google Scholar 

  • Chandy RK, Tellis GJ (2000) The incumbent’s curse? Incumbency, size, and radical product innovation. J Marketing 64:1–17

    Article  Google Scholar 

  • Davenport E, Bruce I (2002) Innovation, knowledge management and the use of space: questioning assumptions about non-traditional office work. J Inf Sci 28:225–230

    Article  Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Q 13:319–340

    Google Scholar 

  • Descouza KC (2001) Intelligent agents for competitive intelligence: survey of applications. Competitive Intell Rev 12:57–63

    Article  Google Scholar 

  • Detlor B (2004) Towards knowledge portals: from human issues to intelligent agents. Kluwer, Dordrecht, The Netherlands

    Google Scholar 

  • DStar (2001) SAP/BiosGroup team to solve supply network complexity. Available at http://www.hpcwire.com/dsstar/01/0619/103169.html. Retrieved March 2004

  • Etzioni O, Weld DS (1995) Intelligent agents on the Internet: fact, fiction, and forecast. IEEE Expert 10:44–49

    Article  Google Scholar 

  • Fishbein M, Ajzen I (1975) Belief, attitude, intention, and behavior: an introduction to theory and research. Addison-Wesley, Reading, Massachusetts

    Google Scholar 

  • Freeman C (1991) The nature of innovation and the evolution of the productive system. In: OECD (ed) Technology and productivity—the challenge for economic policy. OECD, Paris, France

    Google Scholar 

  • Garcia R, Calantone R (2002) A critical look at technological innovation typology and innovativeness terminology: a literature review. J Prod Innovation Manage 19:110–132

    Google Scholar 

  • Garrido L, Sycara K (1996) Multi-agent meeting scheduling: preliminary results. In: Proceedings of the international conference on multi-agent systems (ICMAS‘96), Kyoto, Japan, December 1996, pp 95–102

  • Gilbert D, Aparicio M, Atkinson B, Brady S, Ciccarino J, Grosof B, O’Connor P, Osisek D, Pritko S, Spagna R, Wilson L (1995) IBM intelligent agent strategy. White paper, IBM Corporation

    Google Scholar 

  • Hall R, Andriani P (2002) Managing knowledge for innovation. Long Range Plann 35:29–48

    Article  MATH  Google Scholar 

  • Hayes-Roth B (1995) An architecture for adaptive intelligent systems. Artif Intell 72:329–365

    Article  Google Scholar 

  • Jennings NR, Norman TJ, Faratin P, O’Brien P, Odgers B (2000) Autonomous agents for business process management. Int J Appl Artif Intell 14:145–189

    Article  Google Scholar 

  • Kleinschmidt EJ, Cooper RG (1991) The impact of product innovativeness on performance. J Prod Innovation Manage 8:240–251

    Google Scholar 

  • Lange DB, Oshima M (1999) Seven good reasons for mobile agents. Commun ACM 42:88–89

    Article  Google Scholar 

  • Lieberman H (1995) Letizia: an agent that assists Web browsing. In: Proceedings of the international joint conference on artificial intelligence (IJCAI’95), Montreal, Canada, August 1995, pp 924–929

  • Lieberman H, Rosenzweig E, Singh P (2001) Aria: an agent for annotating and retrieving images. IEEE Comput 34:57–62

    Article  Google Scholar 

  • Maes P (1994) Agents that reduce work and information overload. Commun ACM 37:31–40

    Article  Google Scholar 

  • Maes P (1999) Smart commerce: the future of intelligent agents in cyberspace. J Interactive Marketing 13:66–76

    Article  Google Scholar 

  • Maes P, Kozierok R (1993) Learning interface agents. In: Proceedings of the 11th national conference on artificial intelligence (AAAI’93), Washington, District of Columbia, August 1993, pp 459–465

  • Mahajan V, Muller E, Bass FM (1990) New product diffusion models in marketing: a review and directions for research. J Marketing 54:1–26

    Google Scholar 

  • Majchrzak A, Cotton JC (1988) A longitudinal study of adjustment to technological change: the case of job transfers from mass to computer-automated batch production. J Occup Psychol 61:43–66

    Google Scholar 

  • Martinez E, Polo Y, Elavian C (1998) The acceptance and diffusion of new consumer durables: differences between first and last adopters. J Consumer Marketing 15:323–342

    Article  MATH  Google Scholar 

  • McCarthy J (1956) Inversion of functions defined by turing machines. Princeton University Press, Princeton, New Jersey

    Google Scholar 

  • McCarthy J (1958) Programs with common sense. In: Proceedings of the Teddington conference on the mechanization of thought processes, London, England, December 1958, pp 77–84

  • Mea VD (2001) Agents acting and moving in healthcare scenario—a paradigm for telemedical collaboration. IEEE Transac Eng Manage Inf Technol Biomed 5:10–13

    Article  Google Scholar 

  • Mesak HI, Clark JW (1998) Monopolist optimum pricing and advertising policies for diffusion models of new product innovations. Optimal Control Appl Methods 19:111–136

    Article  MathSciNet  Google Scholar 

  • Moon J-W, Kim Y-G (2001) Extending the TAM for a World-Wide-Web context. Inf Manage 38:217–230

    Article  Google Scholar 

  • Moore GC, Benbasat I (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf Syst Res 2:192–222

    MATH  Google Scholar 

  • Norman TJ, Jennings NR (2002) Constructing a virtual training laboratory using intelligent agents. Int J Continuous Eng Life-Long Learn 12:201–213

    Google Scholar 

  • Nwana HS, Ndumu DT (1999) A perspective on software agents research. Knowl Eng Rev 14:1–18

    Article  Google Scholar 

  • Plouffe CR, Hulland JS, Vandenbosch M (2001) Research report: richness versus parsimony in modeling technology adoption decisions—understanding merchant adoption of a smartcard-based payment system. Inf Syst Res 12:208–222

    Article  Google Scholar 

  • Raisinghani MS (2000) Software agents in today’s digital economy: transition to the knowledge society. In: Rahman SM, Bignall RJ (eds) Internet commerce and software agents. Idea Group Publishing, Hershey, Pennsylvania, pp 88–100

    Google Scholar 

  • Rogers EM (1962) Diffusion of innovations. Free Press, New York

    Google Scholar 

  • Rogers EM (1995) Diffusion of innovations, 4th edn. Free Press, New York

    Google Scholar 

  • Rogers EM, Shoemaker FF (1971) Communication of innovations. Free Press, New York

    Google Scholar 

  • Rowley J (2000) Product searching with shopping bots. Internet Res Electronic Netw Appl Policy 10:203–214

    Article  Google Scholar 

  • Salem DA, Foster-Fishman PG, Goodkind JR (2002) The adoption of innovation in collective action organizations. Am J Community Psychol 30:681–710

    Article  Google Scholar 

  • Sartor G, Branting LK (1998) Introduction: judicial applications of artificial intelligence. Artif Intell Law 6:105–110

    Article  Google Scholar 

  • Saygin AP, Cicekli I, Akman V (2000) Turing test: 50 years later. Minds Machines 10:463–518

    Article  Google Scholar 

  • Segal RB, Kephart JO (1999) MailCat: an intelligent assistant for organizing e-mail. In: Proceedings of the 3rd international conference on autonomous agents (Agents’99), Seattle, Washington, May 1999. ACM Press, New York, pp 276–282

  • Segal RB, Kephart JO (2000) Incremental learning in SwiftFile. In: Proceedings of the 17th international conference on machine learning, Stanford, California, June/July 2000. Morgan Kaufmann, San Francisco, pp 863–870

  • Sen S, Dutta PS, Mukherjee R (2000) Agents that represent buyer’s interest in e-commerce. In: Working notes of the AAAI-2000 workshop on knowledge-based electronic markets, Austin, Texas, July 2000

  • Serenko A, Cocosila M (2003) The social impacts of intelligent agents on Internet use. In: Proceedings of the international and interdisciplinary conference of the association of Internet researchers (AoIR 4.0), Toronto, Canada, October 2003

  • Serenko A, Ruhi U, Cocosila M (2004) Unplanned effects of intelligent agents on Internet use: a social informatics approach. In: Proceedings of the joint meeting of the international conference on politics and information systems, technologies and applications (PISTA 2004) and the international conference on cybernetics and information technologies, systems and applications (CITSA 2004), International Institute of Informatics and Systemics, Orlando, Florida, July 2004

  • Shoham Y (1997) An overview of agent-oriented programming. In: Bradshaw JM (ed) Software agents. AAAI Press/MIT Press, Menlo Park, California, pp 271–290

    Google Scholar 

  • Smith AE, Nugent CD, McClean SI (2003) Evaluation of inherent performance of intelligent medical decision support systems: utilising neural networks as an example. Artif Intell Med 27:1–27

    Article  Google Scholar 

  • Teng JTC, Grover V, Güttler W (2002) Information technology innovations: general diffusion patterns and its relationships to innovation characteristics. IEEE Trans Eng Manage 49:13–27

    Article  Google Scholar 

  • Tornatzky LG, Fleischer M, Chakrabarti AK (1990) The processes of technological innovation. Lexington Books, Lexington, Massachusetts

    Google Scholar 

  • Turban E, Aronson JE, Bolloju N (eds) (2001) Decision support systems and intelligent systems. Prentice Hall, Upper Saddle River, New Jersey

    Google Scholar 

  • Turing A (1950) Computing machinery and intelligence. Minds 59:433–460

    Google Scholar 

  • Utterback JM (1994) Mastering the dynamics of innovation: how companies can seize opportunities in the face of technological change. Harvard Business School Press, Boston, Massachusetts

    Google Scholar 

  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci 46:186–204

    Article  Google Scholar 

  • West LA, Jr., Hess TJ (2002) Metadata as a knowledge management tool: supporting intelligent agent and end user access to spatial data. Decis Support Syst 32:247–264

    Article  Google Scholar 

  • White JE (1997) Mobile agents. In: Bradshaw JM (ed) Software agents. AAAI Press/MIT Press, Menlo Park, California, pp 437–472

    Google Scholar 

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Acknowledgements

This paper is kindly supported by a grant from the Natural Sciences and Engineering Research Council of Canada.

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  1. Michael G. DeGroote School of Business, McMaster University, Hamilton, ON, Canada

    Alexander Serenko & Brian Detlor

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  1. Alexander Serenko
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Correspondence to Alexander Serenko.

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Serenko, A., Detlor, B. Intelligent agents as innovations. AI & Soc 18, 364–381 (2004). https://doi.org/10.1007/s00146-004-0310-5

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