Measuring Variability Factors in Customer Values, Technology Convergence and Profit Optimization in a Retailing Firm: A Framework for Analysis

Measuring Variability Factors in Customer Values, Technology Convergence and Profit Optimization in a Retailing Firm: A Framework for Analysis

Dr. Rajagopal (Monterrey Institute of Technology and Higher Education ITESM, Mexico)
DOI: 10.4018/978-1-60566-248-0.ch005

Abstract

Estimating value drivers for a new product can be tricky because there is no direct historical data. However, we can assume that the impact from changes in price or availability of complements will be similar to what other markets have experienced. Following discussion in the chapter develops the framework for measuring the consumer values in reference to establishing the long run relationship by the firm and optimizing its profit levels. The discussions in the chapter attempt to endure the core issues of consumer values in retailing the products and services as how to conceptualize consumer values, how to measure it, and how to manage it.
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Review Of Literature

The concept of consumer satisfaction has a long history in marketing thoughts. Studies of consumer behavior emphasize consumer satisfaction as the core of the post-purchase period. Because consumer satisfaction presumably leads to repeat purchases and favorable word-of-mouth publicity, the concept is essential to marketers. In saturated markets consumer satisfaction is thought to be one of the most valuable assets of a firm. Consumer satisfaction serves as an exit barrier, thereby helping the firm to retain its consumers. The impact of loyal consumers is considerable; for many industries, the profitability of a firm increases proportionally with the number of loyal consumers and high sales to new consumers can be attributed to word-of-month referrals. Several contributions have been made in relation to various mechanisms for improving and using consumer satisfaction. Barsky and Labagh (1992) proposed a consumer-satisfaction matrix as a tool for evaluating guest information and attitudes, and for identifying related strengths and weaknesses. Dube et al. (1994) described how consumer satisfaction data can be used for positioning strategies that will help the business carve a niche, whereas Morgan (1993) investigated consumers' value of benefits offered in mid-scale restaurant chains. Some contributions in the marketing literature suggest that there are very high expectations for these loyalty-building initiatives (Reichheld and Sasser 1990; Nalebuff and Brandenburger 1996; Reichheld 1996). The academics, consultants and business people speculated that marketing in the new century would be very different from the time when much of the pioneering work on consumer loyalty was undertaken (e.g. by Churchill 1942; Brown 1953; Cunningham 1956, 1961; Tucker 1964; Frank 1967). Yet there exists the scope for improving the applied concepts as there have been many changes over conventional ideologies.

The well-known disconfirmation of expectations model of satisfaction suggests that consumer satisfaction is a result of a comparison between company performance and consumer expectations (Oliver, 1980; 1981). Disconfirmation models are usually focused on performance of specific attributes and expectations (Bearden and Teel, 1983; Churchill and Surprenant, 1982; Tse and Wilton, 1988; Oliver, 1993). However, there is a gap in our current understanding of satisfaction in a channel’s context where relationship-building rather than transactional exchange assumes importance. The comparison process between actual performance and expectations may be moderated by the presence of firm and environmental variables such as consumer power, consumer size, rivalry, channel configuration, product line growth rate, supplier flexibility and consumer service. The relationship between consumer service and satisfaction has been investigated to a limited extent in the logistics literature (Mentzer et al., 1989; Emerson and Grimm, 1996). Mentzer et al. (1989) call for a formal analysis of logistics and marketing consumer service items in order to establish certain general dimensions of consumer service and to investigate their impact on consumer satisfaction. Further, Mentzer et.al. (1989) and Emerson and Grimm (1996) found that the performance on certain logistics and marketing consumer service dimensions directly contributes to consumer satisfaction in a channels setting.

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