Toward a framework for developing knowledge-based decision support systems for customer satisfaction assessment: An application in new product development
ABSTRACT Customer-oriented product development has become increasingly necessary for competitive reasons. This paper describes a framework and a methodology for the design, development, and implementation of knowledge-based decision support systems for customer satisfaction assessment. A generic approach is presented that integrates knowledge-based systems with both a well-known and accepted modeling technique (scoring models), and several decision support techniques (such as the analytic hierarchy process and discriminant analysis). In addition to the fexibility and developmental advantages of knowledge-based systems, additional benefits of this approach include reduced information processing and gathering time, improved communications with senior management, and better management of scarce development resources. To simplify the exposition, we illustrate the framework and methodology within the context of a successful system implementation. The resulting system, known as the Customer Satisfaction Assessment System (CSAS), is designed to provide the decision support necessary to evaluate whether or not full-scale development of a candidate product should proceed. The system assesses and estimates the extent to which a potential new product will meet the expectations of the customer. CSAS incorporates market research findings, as well as strategic evaluation factors and their interrelationships. It can function as a stand-alone system or in conjunction with other evaluation systems (e.g., those providingfinancial, technological, manufacturing, and marketing evaluations) to provide a complete assessment of the product under consideration. Since its implementation, the experts' and other users' expressions of complete satisfaction and commitment to the system has been an indication of its value as an important decision support tool. The paper concludes with a discussion of the lessons learned for future implementations and some important extensions of this research.
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ABSTRACT: A review of marketing applications of the analytic hierarchy process (AHP) shows that major concerns involve the accuracy of knowledge elicitation and choice of a suitable knowledge base. Decision support is suggested with a series of decision rules based on different variations of AHP for both structuring and evaluation, presented in the user interface. Models that solved historical information needs can also be adapted for current marketing conditions by incorporating AHP within a marketing knowledge-based decision support system (KB-DSS). Current decision rules might be chosen on the basis of past behaviour that has proved successful, sharing similar marketing conditions and characteristics, captured within a suitable knowledge base. Decision rules are then chosen on the basis of their relevance to the current problem, based on historical AHP case data that are continuously revised. This proposal reduces data collection and processing time.European Journal of Marketing 07/2001; 35(7/8):872-894. · 0.96 Impact Factor
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ABSTRACT: Although knowledge elicitation, the process of extracting knowledge from human experts to be incorporated into a knowledge-based system, has been the subject of some notable studies, less attention has been paid to the methods of analysing the raw data once it has been extracted from the expert. When knowledge elicitation sessions are interview-based, the resultant form of raw data is usually a transcript of the interviewee's utterances. This paper describes an investigation into the preliminary stage of analysing such transcripts. It outlines the development of an approach to eliminate unnecessary detail from interview transcripts, thus enabling attention to be focused upon the remaining, more relevant data via a simple technique based upon cheap and readily available technology. The paper then outlines a rapid-prototyping approach for evaluating this method, the results of which were felt to be very encouraging.Expert Systems 01/1996; 13(1):3 - 13. · 0.77 Impact Factor
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ABSTRACT: Purpose – The purpose of this paper is to identify potential Finnish wellbeing tourism segments based on factors connected to tourists' lifestyles, and find out if there are statistically significant differences between the segments concerning demographic factors, factors related to travelling behaviour, and interests in diverse activities. Design/methodology/approach – Potential tourists are segmented based on activities, interests and opinions (AIO-segmentation). The data of the tourist profiles for the research were collected during 2007 and 2008 by self-administered electronic questionnaire. In total 1,012 sufficient responses were obtained. Collected data were analyzed by using factor-cluster method in order to group respondents into different segments. Findings – Altogether six segments were identified: Sport and nature people interested in technology; Home appreciating travellers; Family and health oriented sport and nature people; Culture appreciative self-developers; Material wellbeing appreciatives; and Indifferent about travelling and social issues. Statistically significant differences were found between the segments considering geo-demographic factors, travelling habits and also interest in different activities. Originality/value – General research concerning the wellness and wellbeing of tourists has been rather rare. This research provides more comprehensive and general information about potential wellbeing of tourists in the Finnish context.Tourism Review 07/2010; 65(2):41-51.