Intelligent Systems and B2B
Applied Intelligent Systems in Business-to-Business Marketing, Special issue of Industrial Marketing Management, Edited by Francisco J. Mart?nez-L?pez and Jorge Casillas; Deadline 15 Sep 2011
|ARC: Connections: ELMAR: Posting||Related ARContent: Industrial Marketing Management|
Call for Papers INDUSTRIAL MARKETING MANAGEMENT
Special Issue on
Applied Intelligent Systems in Business-to-Business Marketing
Submission deadline: September 15th, 2011
Dr. Francisco J. Martínez-López
University of Granada (Spain) and Open University of Catalonia, Barcelona (Spain)
Dr. Jorge Casillas
University of Granada (Spain)
Main Scope of the issue
A forthcoming issue of Industrial Marketing Management (IMM) will be devoted to the presentation of original, rigorous and significant contributions on Artificial Intelligence-based solutions, with a strong, practical logic and preferably with empirical applications, developed to aid the management of any of the marketing issues in a Business-to-Business context.
Rationale for the special issue
Basically, the AI core focuses on the development of valuable, automated solutions (i.e. intelligent agents/systems) to problems which would require the intervention of intelligence if done by humans (Negnevitsky, 2004). In a business context, there are problems to be tackled that require this particular characteristic, which need human judgement and analysis to assess and solve these problems with guarantees of success. These decisional situations frequently relate to strategic issues in firms, where problems are far from being well-structured. Developing and applying ad-hoc intelligent systems, due to their particular strengths to process data and provide valuable information either with a data-driven or, especially, with a knowledge-driven approach, might be of interest to managers in their decision-making (Martínez-López and Casillas, 2009).
However, in spite of their potentialities to contribute to companies’ strategic intelligence (i.e. business intelligence + competitive intelligence + knowledge management) (see Liebowitz, 2006), this research theme has received scarce attention in journals that deal with business and management. A basic search in Scopus (i.e. article title, abstract and keywords) reveals that the number of papers published on both business and artificial intelligence/intelligent systems is less than 150; the figure is below 50, when marketing, instead of business, is used as the searching term. In Wierenga (2010), some reflections are made on the motives that might explain the limited materialization of such potentialities; e.g. the hegemony of Operations Research (OR) and econometrics-based methods as the traditional techniques used by managers to support decision-making on quantitative problems, or the insufficient attention paid to marketing applications in the AI field, among others. In this regard, the overall number of published articles in more technical-oriented subjects (e.g. Computer Science, Decision Sciences, or Engineering, among others) treating issues on artificial intelligence/intelligent systems applied to marketing is below 300 (see Scopus).
There is also a lack of advanced research books with a clear focus on AI methods and applications for marketing, although there are some remarkable introductory books (e.g. Berry and Linoff, 1997; Matsatsinis and Siskos, 2002). By contrast, though specific books on the subject are scarce, there are books whose general scope touches on AI applications for management/business that contain chapters on the marketing issue (e.g. Aliev, Fazlollahi and Aliev, 2004; Bidgoli, 1998; Carlsson, Fredrizzi and Fuller, 2003; Prasad, 2008). Recently, we edited a book volume titled “Marketing Intelligent Systems using Soft Computing: Managerial and Research Applications” (2010, Springer), containing the reflections of various notable marketing and management scholars on the potentialities of AI-based methods for marketing, as well as a collection of advanced research works devoted to a variety of marketing issues.
The main conclusions we draw (see, also: Casillas and Martínez-López, 2009) are that: the AI discipline offers real opportunities for advancing the analytical methods and systems used by firms to manage a variety of marketing issues. Furthermore, well-conceived and designed intelligent systems are expected to outperform OR or statistical-based supporting tools in complex, qualitative and/or difficult-to-program marketing problems and decisional scenarios; secondly, these opportunities still need to be truly materialized by researchers and practitioners. More interdisciplinary and applied contributions are necessary for this promising research stream to really take off.
With this special issue, Industrial Marketing Management aims to promote, stimulate and publish high-quality contributions on applied-intelligent systems to support the management of any B2B marketing issue. Some interesting areas of application might be, but are not limited to, the following:
- Segmenting and targeting business markets.
- Managing customers’ relationships.
- Marketing channel relationships.
- Organizational buying and supply chain management processes.
- Business intelligence and knowledge management.
- Managing personal selling.
- B2B communications decisions.
- B2B pricing strategies.
- Product development, innovation and creativity.
- Services management in business markets.
- Web intelligence and B2B e-commerce applications.
All submissions that are original, high-quality and unpublished elsewhere are welcomed. The managerial orientation of IMM requires all submissions to pay particular attention to their practical applicability. Thus, regardless of specific references to this subject in the manuscript, the submission should dedicate a section to discussing in detail the main implications of the application, tool or solution presented for management. Each manuscript that passes the initial screening review will be submitted to a blind-review process run by three referees.
General guidelines for submissions (“Guide for authors”) can be found at the IMM website: www.elsevier.com/locate/indmarman. Each submission should be sent as an attached MS Word file to both guest editors, Francisco J. Martínez-López (email@example.com) and Jorge Casillas (firstname.lastname@example.org), with an additional copy sent to the IMM Editor-in-Chief, Peter Laplaca (email@example.com). Please clearly indicate in your cover letter that your submission is for this special issue, with the following submission message: “Submission to IMM SI on Intelligent Systems”.
Important Approximate Dates
- Deadline for submission of papers: September 15, 2011
Initial screening: October, 2011
First-round decisions: December, 2011
First-round revisions due: March 31, 2012
Second-round decisions: April 30, 2012
Second-round revisions due: June30, 2012
Final decisions: August 1, 2012
Final materials due from Authors September 15, 2012
Aliev, R.A.; Fazlollahi, B.; Aliev, R.R. (2004). Soft Computing and its Applications in Business and Economics (Studies in Fuzziness and Soft Computing) (Hardcover), Springer
Berry, M.; Linoff, G. (1997). Data mining techniques: for marketing, sales and marketing support, Wiley.
Bidgoli, H. (1998). Intelligent Management Support Systems (Hardcover), Quorum Books.
Carlsson, C.; Fedrizzi, M.; Fuller, R. (2003). Fuzzy Logic in Management (International Series in Operations Research & Management Science), Springer
Casillas J.; Martínez-López F. J. (2009). “Mining uncertain data with multiobjective genetic fuzzy systems to be applied in consumer behaviour modeling,” Expert Systems with Applications (36:2, part 1), pp. 1645-1659.
Casillas J.; Martínez-López, F.J. (Eds.) (2010). Marketing Intelligent Systems using Soft Computing: Managerial and Research Applications, Springer.
Liebowitz, J. (2006). Strategic Intelligence: Business Intelligence, Competitive Intelligence, and Knowledge Management, Taylor & Francis, Inc.
Martínez-López F.J.; Casillas J. (2009). “Marketing Intelligent Systems for consumer behaviour modelling by a descriptive induction approach based on Genetic Fuzzy Systems,” Industrial Marketing Management (38:7), pp. 714-731.
Matsatsinis, N.F.; Siskos, Y. (2002). Intelligent Support Systems for Marketing Decisions (International Series in Operations Research & Management Science), Springer
Negnevitsky, M. (2004). Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition), Addison-Wesley.
Prasad, S. (Ed.) (2008). Soft Computing Applications in Business (Studies in Fuzziness and Soft Computing) (Studies in Fuzziness and Soft Computing), Springer
Wierenga, B. (2010). “Marketing and artificial intelligence: great opportunities, reluctant partners,” in J. Casillas and F.J. Martínez-López (Eds.) Marketing Intelligent Systems using Soft Computing: Managerial and Research Applications, Springer, pp. 1-8.