A new approach to evaluate the market share of service industries
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A new approach to evaluate the market share of service industries C Wu, S-M Hsu and T-W Tien National Taiwan University of Science and Technology The purpose of this paper is to apply the model of stochastic networks (networks of quasi-reversible stations) to customer brand-choice behaviour for studying the market share of some service undustries such as in life insurance. We estimate the market share and the mean unit sales of a speci®ed brand in a static market. The model involves use time, customer loyalty, brand switching, initial purchasing and market share variation. Keywords: marketing; market share; stochastic networks
Introduction Many companies aim at expanding or maintaining their market share and improving their pro®tability. Large market share does have advantages such as larger purchase discounts, lower production costs, and improved corporate image. Ravenscroft,1 and Szymanski et al2 provided a generally positive association between market share and business pro®tability. Gale3 used regression analysis to examine the relation between market share and pro®tability. He found that high market share is associated with high rates of return and the effect of share on pro®tability depends on other ®rms and industry characteristics. The effect of market share on pro®tability tends to be greater when the ®rm is relatively large or when the competitive environment is characterised by high concentration or moderate growth. Kotler4 de®ned four measures to express market share: (1) overall market share; (2) served market share; (3) relative market share to top three competitors; and (4) relative market share to leading competitors. All these four measures are based on either dollar sales or unit sales. However, for some industries, the share can be measured by the base of active customers. For example, considering an insurance company to measure its market share, it should relate to the base of active customers of the company and the industry, since how many insurers of the day would represent its daily unit sales. Of course, such properties are not unique to insurance companies. It also involves all sorts of organisations that there exists business whose income can be counted by the base of active customers, for example, (1) ®nancial consultant (2) law consultant Correspondence: Dr C Wu, Department of Business Administration, National Taiwan University of Science and Technology, 43 Keelung Road Sec 4, Taipei, Taiwan.
(3) house leasing (4) machine leasing (5) telecommunication company (there is a program that pays ®xed bills and then enjoys in®nite local calls) (6) cable TV To predict the share of these businesses, the properties concerning consumer purchasing behaviour should be taken into account. Firstly, instead of interpurchase time we should relate customers' use time to a company's sales. Use time means the length of the time a product is used until customers have exhausted their purchases
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