| Received date: 1999-04-24Foundation item: Under the auspices of Guangdong Provincial Natural Science Foundation(No.980268) |
2.1 Definition of market segmentation
So called market segmentation refers to the identification of groups of customers-or market segments-that have similarities in characteristics or similarities in needs who are likely to exhibit similar purchase behavior and/or responses to changes in the marketing mix[1-2].Or market segmentation is the division of a total population of travelers into groups (segments) that are relatively homogeneous with respect to certain personal characteristics (the segmentation base)[16].Market segments consist of groups of people or organizations that are similar in terms of how they respond to a particular marketing mix or in other ways that are meaningful for marketing planning purpose.Marketing mix is a set of product, price, position and promotion, and can be briefly considered as ‘4Ps’.2.2 Characteristics, functions and limitationsCharacteristics·the process by which market segment are identified;·the foundation for an overall marketing strategy;·a process of analyzing markets, finding a niche, and developing and capitalizing on a superior position with that niche; and·central to a market and customer needs and wants.Functions·design responsive products to meet the needs of the marketplace;·develop effective and cost efficient promotional strategies;·provide insight on present marketing strategies;·provide data on which to base resource allocation decisions; and·have available important data on which long-range planning for market growth or product development can be basedLimitations·findings that may omly provide a composite profile of the market;·changing lirestyles has made segmentation more difficult;·segmentation is not a remedy other marketing organization deficiencies;·segmentation effectiveness is limited by management ability to use the results;·many segmentation studies emphasize methodological and statistical procedures over substance; and·The marketing research required for market segmentation may be expensive.3 Application in Transit IndustryGenerally speaking, market segmentation is classified as the category of economics. In the past, the theory was ignored or little highlighted by researchers, transportation planners, transit operators and managers, considering transportation as a service industry is rather different from manufacturing, processing and production sectors centering on their final products, while transportation only provides service to meet the demands of customers. They generally thought service had substantial differentiality with products. The idea lasted a relatively long time, especially during product-oriented period. All operating activities were rotated around product, emphasizing on production yield and quality, no matter what needs in the marketplace or customers. After a large scale of production, Fordist as remarking cornerstone, oversupply of products led to fierce competition in the market with numerous producers. Under the historical background, contemporary marketing theory was established. The primary principle of marketing theory is at the core of customers or market, thus firms or enterprises produce what the customers want rather than make a decision on expectations or wants of producers themselves. The implication of products were extended, and a perfect product should contain internal quality, external quality-package, and service. When users buy the product. They are entitled to obtain relative service-presale or postsale service.Expanding the concept of product leads to application of market theory in transportation. In comparison with production or trade fields, the less documentation is available in transportation in transportation industry. These applications are distributed on several regimes, such as transportation policy, planning and management, energy and environment, travel pattern and behavior, transit marketing, travel demand analysis, and mode choice model, etc.In transport policy, a survey of all current Austrian Car-sharing Organization (ACO) members is used to quantify urban local market segment potentials and applied to two residential areas. Results indicate a substantial reduction of aggregate private vehicle mileage. Combining behavior impact with market segment size results in the quantification of emission reduction and car ownership reduction due to car-sharing, which is a decentralized demand-side transport policy [17].Toh, R.S. et al (1990) identified the behavioral, attitudinal and demographic correlates of frequent flier members and non-members as well as light, medium and heavy users of air travels in the US using multiple discriminant analysis and other statistical techniques[18]. These membership categories are viable bases for segmentation and the appropriate marketing mixes are then designed to conform to the discriminating characteristics of the target markets of different airlines.Dobson et al (1978) illustrated a relatively uncomplicated and effective perceptual market segmentation procedure for transportation policy analysis through a flowchart describing the technique, an empirical application and the tests of the reliability of the derived market segmentation structures across split halves of a data set[19]. The procedure was calibrated on a sample of Los Angeles CBD workers. The segmentation structure was correlated highly with appropriated mode choice patterns. It was also observed that perceptual segmentation membership was a stronger determinant of mode choice than zone network time and cost. The segmentation can be used in developing short-range forecasting models and its potential for developing information aids to target groups of travelers. Echols, J.C. (1983) identified several issues on Workshop on Systems Operations, including 1) Deregulation impacts; 2) financial consequences; 3) market segmentation; 4) social goals; 5)users subsidies; and 6) equity.Margolin, J.B. et al (1978) examined consumer motivation concerning ride sharing, particularly carpooling, according to a market segmentation approach. The major market segmentation involved dividing the sample by commuting mode and pattern and by occupation type. The factors discussed include: 1) attitudes toward costs or interpersonal aspects of carpooling, time variables, carpool routes, parking management and convenience issues; and 2) demographic characteristics of the two types of commuters. A special analysis focuses on the attitudes of those sole drivers who stated that they were interested in carpooling versus those who stated that they were not. The purpose is to highlight the motivation of a prime target group toward three carpool strategies: carpool match method, parking management, and dedicated carpool routes.In fare elasticity, results of the Chicago Transport Authority (CTA) surveys revealed an apparent lack of sensitivity to fare increases related distance traveled. Cummings, C.P. et al (1989) used these results and market segmentation, together with historical analysis of ridership response to three recent CTA fare increases, several elasticities are derived for use in systematically analyzing potential ridership response to future CTA fare structure options[20].In market research, Rebecca (1998) focuses on the statues of market research as practiced in transit agencies and identifies major market issues confronting them, evaluating market research strategies appropriate for transit and provides guidance to integrate and institutionalize market research into decision-making processes of transit agencies, analyzing some institutional barriers to limit the use market research. Jakubiak et al (1990) used market research to improve management of transportation system[21]. It is designed to aid officials at many levels with transport agencies. They presented techniques of modern market research, including data collection (focus group, panel surveys, and telephone, mail and intercept surveys), data analysis (cross-tabulations, importance-performance analysis) and multivariate statistics (regression analysis, factor analysis, discriminant analysis, multidimensional scaling, psychographic market segmentation, perceptual mapping and conjoint analysis). Walb and Booth (1985) reviewed current marketing practice at representative transit agencies in North America, revealing a number of promising new practices including market segmentation, target marketing, direct contact marketing, electronic user information aids and consumer orientation training[22]. The role of marketing in the transit industry has undergone numerous changes in the past decade, expanding as the task of attracting new riders or retaining existing riders has become more complicated. The complexity of the marketing function encompasses market research, service development, pricing, promotion (radio and television advertising, use of car cards and billboards), consumer aids (schedules and timetables, telephone information system and system maps) and evaluation.In travel pattern and behavior, Roberts, R.A. (1986) predicted the future of the Portland transit market using demographic trends [23]. Demographic changes affect the market for urban transportation in many ways. Identifying these changes and monitoring demographic trends can give the planners better insight into the future nature of the transit market. An inductive approach is used to examine some of the demographic variables most important to the transit market. Then the market segmentation that exists in the Portland standard metropolitan statistical area is identified. Tischer, M. L. (1983) summarized alternative analytical approaches to the traditional planning and modeling process [24]. Survey strategies and market segmentation are reasonably well utilized in practice, and attitudinal analyses have been performed in a few transit, carpool and pedestrian planning studies. Travel behavior analysis techniques are most suited in strategic planning and project planning. Blankenship, D.P. (1976) conducted segmentation analysis of transit users and nonusers [25]. A stratified random sample of households was used to ensure accurate spatial representation. Market segmentation was used to ascertain the attitudinal framework. The survey identified various demographic and psychographic profiles that may impact current, future, private and public transportation modes. The factors were concerned in the survey including social status; funding public transit; psychological automobile captivity to transit dependency; vehicle availability and trip market profiles; conceptual awareness and anticipated use; anticipated demand for public rapid transit; marketing and advertising analysis.In transport planning, Trombly, J.W (1986) reviewed the use of market segmentation analysis in transportation energy planning [26]. Two statewide telephone surveys completed to identify groups sharing a similar response to energy price increases and supply short falls. These responses were then used to construct matrices of interitem correlation. The action factors contained shop travel, nonautomobile mode choice, vehicle replacement, automobile maintenance, moving nonautomobile work travel, changing leisure activity and canceling a vacation. The results yielded a consistent set of factors across survey years that are use in a cluster analysis algorithm to identify segment sharing a similar response to conservation. He results of the study can be used to design programs and policies to meet future planning needs. Nicholaidis, G.C. et al (1977) described a comparison of market segmentation using six different bases-two based on demographic variables, two on travel choice constraints, and two on attitudinal variables[16]. The six segmentations were compared with respect of five criteria judged to be important considerations in transportation planning: measurability, statistical robustness, sustainability, and relation to travel behavior and relation to planning of service options. The results showed that no single segmentation base was superior.In mode choices, Dehghani and Talvitie (1980) using market segmentation to identify following segments [27]: one-versus two car households; commuters bound for the central business district (CBD) versus others; and low-and high-income households that also value service attributes unequally. A simplistic method is used to aggregate rail and bus modes in five-and four-alternative models, respectively. Finally, coefficients estimated by means of observation of level-of-service attributes or by means of multinomial logit models that estimate these attributes are compared. Stopher, P.R. (1977) discussed the development of individual-choice models of the destination choice of nongrocery shopping locations [28]. Two key features of the approach are used of perceptual data for characterizing alternative destinations and attempt to segment the population before the model building on the basis of homogeneity of perceptions of destinations. Data were obtained about the perceptions of shoppers of several shopping locations and on their preferences for various attributes of shopping locations. The attributes were selected as those that make up the image of a shopping location independent of the transportation system. Several techniques are discussed for segmenting the population by perception, all of which are based on analysis of the psychological distance between shopping locations. Given the special properties of psychological distance, two forms of were undertaken. First, correlation was computed for the set of interpoint were used as inputs to an individual scaling process. Market segmentation was sought through a hierarchic, fusion clustering process on the axis weights for each socioeconomic group. The results of these analyses converge well. Length of residence and age were found to be important segmentation variables. Sex and income were not found to be very powerful segmentation variables, but occupation may be worth study as a basis for segmentation.In travel-demand analysis, Salomon, I et al (1982) suggested the employment of the life-style concept as an improved basis for segmentation[29]. Lifestyle is defined as the behavioral pattern that results from three major life decision: the decision to form a household, the decision to participate in the labor force, and the orientation toward leisure. By using available socioeconomic variables, an attempt is made to identify lifestyle groups and to use them as market segments in a joint mode and destination choices model. Two tests were presented. One is the use of lifestyle specific variables in the model specification; and the other is the estimation of separate models for each market segment. Both approaches have shown an improvement in the model performance compared with either a pooled model or an income-base and a life-cycle/ occupation-based segmentation.Unbar, F.C. (1977) reported that disaggregate travel-demand models can be applied to market segments. The method leads to improved accuracy of travel forecasts because appreciation bias is reduced. The wore-trip modal split is simulated on National Personal Transportation Survey data. Travel demand is forecast under a variety of transportation policies that involve automobile controls and transit level-of-service improvement.In ridership, Rebecca, E,Y (1998) provided an overview of market segmentation-what it is and why is relevant to public transit agencies. It serves as an introduction for managers to the basic concepts and approaches of market segmentation and provides steps and procedures for marketers or market researchers who have the responsibility for implementing a market segmentation program to increase transit ridership. He emphasized on the problems likely to arise in implementing segmentation studies, ways to encourage the use of market segmentation at transit agencies, and methods to translate segmentation findings into strategy. Private and public sector examples of market segmentation analyses are extensively used.AcknowledgementThe authors would like to thank Dr. Claude Comtois for the valuable comments.References[1] Rebecca E Y. handbook: Integrating market research into transit management. TCRP. 37. 1998a. TRB.[2] Rebecca E Y. handbook: using market segmentation t increase transit ridership. TCRP 36, 1998b. TRB[3] Winter N A. 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Transport Policy, 1996, (3/4): 177-185.[18] Toh R S et al. A multiple discriminant approach to identifying frequent fliers in airline travel: some implications for market segmentation target marketing and product differentiation [J]. Logistics and Transportation Review, 1990, 26(2): 179-197.[19] Dobson R et al. Perceptual market segmentation techniques for transportation analysis [J]. Logistics and Transportation analysis [J], TRR, 1978, (673):145-152, TRB.[20] Cumming C P et al. Market segmentation of transit fare elasticities [J]. Transportation Quarterly, 1989, 43(3): 407-420.[21] Jakubiak S et al. Using market researches to improve management of transportation systems [J]. NCHRP, 1990, 329, 81P. TRB.[22] Walb C et al. Transit marketing: the state of the art [J]. TRR, 1985, 1039, P9-16, TRB.[23] Roberts R A. Analysis of demographic trends and travel patterns: implications for the future of the Portland transit market [J]. TRR, 1986,1067,1-8, TRB.[24] Tischer ML. Workshop on travel behavior characteristics and analysis: workshop summary [J]. TRR, 1983, 202.72-73, TRB.[25] Blankenship D P. Segmentation analysis of transit users and nonusers [J]. TRR, 1976, 590,1-4, US Transportation Research Board (TRB).[26] Trombly J W. An investigation into the use of market segmentation analysis for transportation energy planning [J]. TRR, 1986,1092. 39-47, TRB.[27] Dehghani Y et al. Model specification, modal aggregation and market segmentation in mode choice models: some empirical evidence [J]. TRR, 1980, 755 28-34, TRB.[28] Stopher P R. Development of market segmentation of destination choices [J]. TRR, 1977, 649: 14-22, TRB.[29] Salomon I et al. Life-style segmentation in travel demand analysis [J]. TRR, 1982, 879: 37-45, TRB.[30] Charles River Associates. Building transit ridership: an exploration of transit’s market share and the public policies that influence it [J]. TCRP, 1997, 27: 162, TRB.[31] Dunbar F C. Policy-contingent travels forecasting with market segmentation [J]. TRR, 1977, 637: 27-32, TRB.[32] O’sullivan P. Transport Policy. Barnes & Noble Books,1980.[33] TRR 1607. Transportation forecasting and travel behavior [J]. TRB,1997.[34] TRR 1554.Advanced traffic management systems and high-occupancy-vehicle systems [J]. TRB, 1996.BiographiesZHANG Yun-quan(1963-), male, a native of Hangzhou city of Zhejiang Province, is Ph.D. Candidate and Asociate Professor in Center for Urban and Regional Studies, Zhongshan University. His research interests include urban transportation geography, real restate development and mineral engineering; Email: yunquanz@gzcc.goy,cn; YAN Xiao-pei (1956-), female, is Professor and Ph.D. Tutor in the center. Her research interests include urban geography, information industry and urbanization as well as urban transportation theory; HE Chong-ming (1963-), male, is senior engineering and Deputy Director in Guangzhou Transportation Institute. His research interest includes transportation planning and management.
