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This article presents the findings of a survey conducted among British companies to discover to what extent marketing models are being used in practice. In two previous articles we discussed the problems of model building in marketing, examined several recent developments, argued that there was a need to measure the current status of marketing model building in Britain, and made a partial assessment of the state‐of‐the‐art by reviewing some of the most significant literature. The purpose of this paper is to present the findings of a survey we conducted among British companies to discover to what extent marketing models are being used in practice. We also present the conclusions we have drawn from the project.

Discusses decisions faced by marketing managers and whether answers to some important questions can be successfully answered. Examines marketing information systems (MIS) components – the data bank, the model bank, the measurement statistics bank, and the system user interface. Posits that there are economic benefits derived from making ‘better’ marketing decisions that result in larger monetary payoffs to the firm. Suggests a systematic impact study be based on analysis of the various steps that have to be taken in constructing a decision model. States MIS aids the marketing manager in specifying the decision model and in implementing this model. Concludes the MIS designer should look at each step in the construction of the decision model in order to estimate the potential impact of the change.

Examines some recent developments of the status of model building in marketing in the UK. Uses many examples from both the UK and the USA to emphasise developments, with Crawford, Koller and Little, with figures uses for extra emphasis. Investigates problems of modelling marketing processes and also recent development in marketing model building. Closes by discussing the present state of the art that involves literature and differences between the UK and USA in marketing and model building.

Marketing management presents challenging ground for the integrated use of intelligent agents. The design of a strategic marketing plan presents a natural division of four distinct yet independent decision problems. Concurrent execution of these four functions can yield a significant decrease in time‐to‐market for new products, and turnaround time for modified products. Electronic information is a two‐edged sword. On the one hand, it results in information overload, taxing the decision‐ making process. On the other hand, the electronic nature of these vast information flows makes them accessible to intelligent agents who can improve the decision‐making process. This paper presents the problem of information overload and decision‐making complexity in marketing management. In it, we present a blackboard‐based agent architecture that allows individual agents to proceed toward their given goals yet react opportunistically to developments reported by other marketing agents. We present the blackboard model of problem solving, and discuss why it is well suited to support multiple marketing agents. CMA, a multi‐agent model for concurrent marketing analysis, is discussed and the agent architecture required for creating a cooperating society of marketing agents is presented.

The chapter briefly reviews the eight volumes in my Legend series – organizational buying behavior, consumer behavior, product and new product management, marketing strategy, market segmentation, global marketing, marketing research and modeling, and the future of marketing. In addition, the chapter highlights the three driving forces of much of my research: (a) the real world challenges facing corporations and organizations, (b) the search for new methodological developments, and (c) the continuous challenge of the prevailing marketing concepts and approaches. The chapter concludes with some reflections on the evolution of marketing in the past five decades and my wish list for the discipline and my future activities.

Gives a general definition of the concept of marketing with the end of Tunbergen's division of the elements which form an economy. Provides an additional definition – “marketing in a limited sense”. Determines to what degree marketing in a limited sence has been developed. Considers some classification models developed during the last 15 years.

Discrete choice modeling has been discussed by both academics and practitioners as a means of analytical support for B2C relationship marketing. This paper aims to discuss applying this analytical framework in B2B marketing, with an example of cross‐selling high‐tech services to a large business customer. This example is also used to show how an algorithm of genetic binary choice (GBC) modeling, developed by the author, performs in comparison with major techniques used nowadays, and to analyze the financial impact of these different approaches on profitability of B2B relationship marketing operations.

Predictive models based on the regression analysis, the classification tree and the GBC algorithm are built and analyzed in the context of their performance in optimizing cross‐selling campaigns. An example of business case analysis is used to estimate the financial implications of the different approaches.

B2B relationship marketing, although differing from B2C in many aspects, can also benefit from analytical support with discrete choice modeling. The financial impact of such support is significant, and can be further increased by improving the predictive accuracy of the models. In this context the GBC modeling algorithm proves to be an interesting alternative to the algorithms used nowadays.

The generalizability of the findings, concerning performance characteristics of the algorithms, is limited: which method is best depends, for example, on data distributions and the particular relationships being modeled.

The paper shows how B2B marketing managers can increase the profitability of relationship marketing using discrete choice modeling, and how implementing new algorithms like the GBC model presented here can allow for further improvement.

The paper bridges the gap between research on binary choice modeling and the practice of B2B relationship marketing. It presents a new possibility of analytical support for B2B marketing operations together with financial implications. It also includes a demonstration of an algorithm newly developed by the author.

The purpose of this paper is to make explicit how marketers employed in the pharmaceutical sector can ensure that the company is positioned in the industry as a result of a sustainable competitive advantage being achieved. Various factors are highlighted, including high research and development costs, stringent government regulations and cultural factors such as religion.

The new product launch strategy model outlined in this paper was developed from both secondary and primary sources. A literature review was undertaken, a number of in‐depth personal interviews and a focus group session were conducted, which involved managers within a pharmaceutical company. The research strategy encompassed the case study method and the NPLS model was validated and can be viewed as generalisable.

It is clear from the research undertaken that some marketing models are viewed as being too complex; however, it is generally appreciated that marketing models can be used to interpret complex relationships that are evident in a marketing system.

Two weaknesses associated with the model were identified. First, the assumption that there was a one‐way relationship between the strategic launch decisions and the tactical launch decisions and, second, a feedback mechanism was absent that would provide users of the model with a means for evaluating their decisions and identifying alternative strategies and tactics. The model was amended and a feedback mechanism was introduced.

The NPLS model can be used by marketing practitioners to enhance communication between corporate level staff and subsidiary level staff, and can be used to implement and/or facilitate the strategic marketing concept within a pharmaceutical company. The model can also be used to focus attention on risk reduction/elimination associated with market entry.

The NPLS model is an addition to marketing knowledge and can assist marketing academics and researchers to understand better how marketing models can be constructed and implemented. The model can also be used by marketing practitioners employed by pharmaceutical companies to make tactical and strategic decisions; to evaluate a new product launch strategy; and to devise international marketing entry plans and strategies.