Research Objectives - 生活型態在實體與虛擬通路之市場區隔研究

Chapter 1 Introduction

1.2 Research Objectives

Under the dynamic environment, consumers have much more chance to access products and media; this may create more difference in their preferences. Therefore, no matter marketing in physical or in virtual channel, to make effort to achieve higher accuracy of market segmentation is necessary. The traditional analytic model which based on factor analysis should be improved to match the needs from the dynamic market scenarios

This study aims to improve the elder method of market segmentation. As addressed above, lifestyle and values are important variables to influence consumer choices that should be included in the research to increase the richness of the explanation. In virtual channel, moreover, the model we presented here could be a new basis to segment the market online. Since most of the study of lifestyle has its own AIO measurement, this study also aims to create the survey with rich information and appropriate length. That is, using data mining tools to find the variables that have the critical influence to consumer choices. Therefore, to cut down the length of questionnaire and develop one moderate general lifestyle structure specific for Taiwan is also an important objective in this research.

After the conceptual structure of the basis in this study, market segmentation for different product targets are going to be discovered and explained. The link between consumers’ personal differences and product choice will be established, and their preferences in different segments are going to be discussed. After having more information of consumers in this research construct, decent market strategies in different channels can be generated. The comparison will be made to check if lifestyle and values variables can increase the accuracy of market segmentation in each market.

Since there are two rule-based data mining techniques applied here, the result of comparison will be concluded at the end.

To provide different market segmentation model, as the description mentioned above, there are three main objectives in this research:

(1) To develop a moderate survey of lifestyle and values for Taiwan;

(2) To establish the effective linkage between consumers lifestyle and product choices;

(3) Proposing this novel model to segment the market in different channels.

Chapter 2 Literature Review

In this chapter, main concepts of this research from previous literature will be presented, includes consumer behavior, market segmentation and the construct of lifestyle, that is, activities, interests and opinions. Also, other similar research used nowadays will also be proposed in this chapter.

2.1 Consumer behavior model

2.1.1 Definition of consumer behavior

Consumer behavior is a theory that integrates many different theories from different research field, for instance, marketing, economics, psychology and social science.

Therefore, many scholars had proposed definitions of it.

From Engel et al. (1995): consumer behavior is those actions directly involved in obtaining, consuming, and disposing of products and services, including the decision process that precede and follow these actions.

In this section, the consumer behavior model from Engel-Kollat-Blackwell is used as the basis of the concept in this research; this model is described as follows.

2.1.2 Models for consumer behavior: Engel-Kollat-Blackwell Model

Engel-Kollat-Blackwell model are proposed in 1968, after being revised in seven times, has became a complete and systematic structure in consumer behavior theory.

This model confers consumer behavior from the decision process. Integrated with the opinions from elderly scholars, it has become a full-scale model which regards consumer behavior as a sequential process instead of discontinuous individual actions. The characteristic of this model is it pus decision process as its central concept and also combines inner and outer factors interchangeably to create a whole decision making system.

There are fore main components in EKB model: input, information processing, decision process and variables influencing decision process.

Source: Engle, James F., Blackwell, Roger D. & Miniard, Paul W., Consumer Behavior, 8^th ed. Orlando Florida, Dryden Press, P.263, 1995.

Fig. 1 Engel-Kollat-Blackwell model

Kolter (1998) believes that the research of consumer behavior is to understand the whole process of black box. To know more about this implicit course, we have to recognize the process of consumer’s decision making and the background and characteristics of him.

Besides, EKB model has detailed discussion about the process of decision making and the sources of the factors which influence his decision making. From this model, it is obvious that individual difference plays an important role to the decision making process, that is, it influences consumer choices directly or indirectly, since the main purpose of this study is to

Stimuli

Input Variables Influencing

Decision Process Information

Processing

Decision Process

find out how personality and lifestyle, these individual differences, can affect consumers choices, therefore, this model is the appropriate conceptual base of this study.

2.2 Market segmentation

2.2.1 Segmentation to Marketing strategy

In today’s market, there are fewer and fewer situations where a mass marketing approach is feasible. This has come as a direct result of the increasing diversity of consumer needs (Wedel and Kamakura, 2000). The justification for segmenting consumer markets is that consumers who share similar characteristics will share similar attitudes, wants and needs and therefore responses towards marketing stimuli (Ahmad, 2003; Dibb et al., 2002).

Whereas heterogeneity is probably the most important reason for segmentation (Hunt and Arnett, 2004), decades age Smith (1956:5) defined market segmentation as “viewing a heterogeneous market as a number of smaller homogeneous markets, in response to differing preferences, attributable to the desires of consumers for more precise satisfaction of their varying wants”. Segmentation can be based on situations, product-situation and person-situation interactions (Van Raaij and Verhallen, 1994).

The nexus of market segmentation is that it allows a business to deal with diverse customer needs in a resource-efficient manner (Dibb and Simkin, 1996). The utility of market segmentation is hence rooted in two main reasons; namely, it enables the need analysis of a specific consumer segment, and it fosters marketing campaigns to be focused on the identified needs (Thach and Olsen, 2006).

Since segmentation have been the most frequent topic covered under the generic heading of marketing management, the role of segmentation in marketing strategy is presented in here.

For segmenting consumer and business markets, the major segmentation variables –geographic, demographic, psychographic, and behavioral segmentation- are summarized in Table 1.

Table 1 Major segmentation variable for consumer markets Segmentation types Segmentation variables Geographic Region; City or metro size; Density; Climate

Demographic Age; Family size; Family life cycle; Gender; Income;

Occupation; Education; Religion; Race; Generation;

Nationality; Social class

Psychographic Lifestyle; Personality

Behavioral Occasions; Benefits; User rate; Usage rate; Loyalty status; Readiness stage; Attitude toward product

Source: Kolter, P., 2000. Marketing Management. pp. 264.

Segmentation is a critical work for company before planning marketing strategy.

Therefore, adequate market-segmentation procedure is useful. There is three-step procedure for identifying market segments (Kolter, 1997).

Step 1: Survey stage

The researcher conducts exploratory interviews and focus groups to gain insight into consumer motivations, attitudes, and behavior. Then the researcher prepares a questionnaire and collects data on attributes and their important information.

Step 2: Analysis stage

The researcher applies factor analysis to the data to remove highly correlated variables, and then applies cluster analysis to create a specified number of maximally different segments.

Step 3: Profiling stage

Each cluster is profiled in terms of its distinguishing attitudes, behavior, demographics, psychographics, and media patterns. Each segment is given a name based on its dominant characteristic.

The process of market segmentation in this study will follow these stages presented above, and demographics, lifestyle and value these variables are used to segment the target market, with appropriate methodologies, we believe that the accuracy of marketing strategies generated for different market segments can be improved.

2.3 Lifestyles and Values

2.3.1Definition of psychographics and lifestyles

Lifestyle variables are usually associated with psychographic segmentation methods (Heath, 1995; Grunert et al., 1997), meaning that the variable… “was subjective in nature (in contrast to objective criteria like demographics or rate of usage) and that it was not product specific (unlike product attitudes or preferences), but rather a general characteristic of the consumer” (Grunert et al., 1997:4, Askegaard & Brunsø, 1999). Until now, the terms

“lifestyles” and “psychographics” are used interchangeably in the marketing literature, and there is much overlap in what these terms are generally thought to mean. One distinction between two terms is that the main purpose of psychographics is to obtain a better understanding of the consumer as a person by measuring him on multiple psychological dimensions, for instances, Nelson, Dorney and Peterson have used the term

“psychographics” to refer to studies that place comparatively heavy emphasis on generalized personality traits.

The core concept of life style mainly derived from psychology and social science. Since 1960s, psychographics and lifestyles have received wide attention among consumer researchers. The application of lifestyle variables in consumer research had first been introduced by Lazar in 1963 (cited by Grunert et al., 1997; Kamakura & Wedel, 1995;

Wedel & Kamakura, 2000). From Lazar, the definition of life style is as follows:

Life style is a systems concept. It refers to the distinctive or characteristic mode of living, in its aggregative and broadest sense, of a whole society or segment thereof. It is concerned with those unique ingredients or qualities which describe the style of life of some culture or group, and distinguish it from others. It embodies the patterns that develop and emerge from the dynamics of living in a society.

Lifestyle, therefore, is the result of such forces as culture, values, resources, symbols, license, and sanction. From one perspective, the aggregate of consumer purchases, and the manner in which they are consumed, reflect a society’s life style.

In conjunction with the definition, Lazar offers the “life style hierarchy” diagrammed below (see Fig. 2):

Source: Thomas P. Hustad & Edgar A. Pessemier, “The Development and Application of Psychographics”, in William D. Wells ed., Life Style and Psychographics, Chicago AMA, p.37, 1974.

Fig. 2 Lazar life style hierarchy

2.3.2 AIO statements

Early lifestyle segmentation studies operationalized the life-style construct through a large battery of Likert-type statements covering the following categories (Plummer, 1974).

Table 2 Life style dimensions

Activities interests Opinions Demographics Work

Stage in life cycle

Source: Joseph T. Plummer (1974), “The Concept and Application of Life Style Segmentation,” Journal of Marketing, Vol.62, May, pp.34-36.

Culture and Society

Group and Individual Expectations and Values

Life Style Patterns and Values

Purchase decision

Market Reaction of Consumers

z Activities: Reported behavior related to club membership, community, entertainment hobbies, shopping, social events, sports, vacation and work.

z Interests: Degree of excitement about and attention to achievement, community, family, fashion, food, home, job, media and recreation.

z Opinions: Beliefs about business, culture, economy, education, future, politics, products, self and social issues.

AIO components are also defined by Reynolds and Darden as follows:

An activity is a manifest action such as viewing a medium, shopping in a store, or telling a neighbor about a new service. Although these acts are usually observable, the reasons for the actions are seldom subject to direct measurement. An interest in some object, event, or topic is the degree of excitement that accompanies both special and continuing attention to it. An opinion is a spoken or written “answer” that a person gives in response to stimulus situations in which some question is raised. It is used to describe interpretations, expectations, and evaluations-such as beliefs about the intentions of other people, anticipations concerning future events, and appraisals of the rewarding or punishing consequences of alternative courses of action.

Aside from the Likert-type items about activities, interests and opinions, most AIO researches include demographic variables. The broad range of areas listed above is commonly used in AIO studies that can be applied to more than one product market.

Such studies may include between 200 to 300 AIO statements. Commonly, a data reduction technique such as factor analysis is first used to translate the large battery of items into a small, more meaningful and interpretable number of underlying psychographic dimensions (Alpert and Gatty, 1969; Darden and Reynolds, 1971; Reynolds and Darden, 1972; Moschis, 1976). For example, in an early study, Wells and Tigert (1971) used 300 Likert-type items that were then factor analyzed and reduced to 22 lifestyle dimensions. However, there are problems of this approach that researcher started to argue, from Gonzalez and Laurentino (2002): …

Surveys are over-long not just because of the large amount of data but also, perhaps even more, because of the scales used, mostly based on scoring, for each and every item in the questionnaire. This means that the respondents have to stop and think hard so as to rate each single item, leading to great fatigue, often not really necessary. Questionnaires are customarily self-administrated, which is an added handicap, as the questions used are

sometimes not easy to understand, and this form of survey does not allow for clarifications.

Both these factors, length and difficulty in understanding questions, lead to the spoiling of a great many questionnaires, especially those filled in by elderly folk, and to considerable biasing of data by flagging attention during the long time-span required for completion (Valette-Florence, 1994).

The bulkiness of the ensuing data also triggers a need for multiple statistical analyses, including factorial analysis of principal components, used with the aim of reducing the number of variables. These retain only a part of the information, to which further techniques are applied, thus leading in the end to a considerable amount of unused residual information, as the raw data are not handled directly, but undergo successive impoverishment.

The comments concerning the criticisms brought forward against the variables traditionally used in segmenting the market, particularly their limited explanatory value in the context of developed countries (Ritchie and Goeldner, 1987; Fisher, 1990; Mitchman, 1991; Witt and Moutinho, 1994; Lambin, 1995), justify the aims of the present study.

Instead of following the elderly approach, this study are going to be an improvement in the techniques for measuring lifestyle, followed by use of the construct to divide up consumers, provided that a relationship can be demonstrated between lifestyle and consumer behavior.

2.3.3 VALS and LOV

A widely used approach to lifestyle marketing is the values and lifestyle (VALS) and its most recent from, VALSⅡ. The original program was developed by Mitchell at SRI and defined nice American lifestyles shown in Fig.3, along with typical demographics and buying patterns. The main dimensions of the segmentation framework are primary motivation (the horizontal dimension) and resources (the vertical dimension). SRI describes consumer market segments as ideals-driven, achievement-directed, and self-expression. The system defines a typology of three basic categories of consumer values and lifestyles, with eight more-detailed types, such as innovators, thinkers, achievers, experiencers, believers, strivers, makers and survivors.

Sources: http://www.sric-bi.com/VALS/types.shtml

Fig. 3 VALSⅡ lifestyle segmentation

VALS uses the results of survey to segment the market and discover the suitable type of consumers to match different marketing proposes, until now, has gained rapid acceptance and widespread usage in marketing. However, it has its limitations, for instance, the result can only represent a broad picture of lifestyle temporarily, and also, huge diversity exists in different countries, societies, therefore it’s hard to say if this complete measurement of lifestyle is suitable to Taiwanese people, however, since lifestyle doesn’t change very often by times and has stabilities, VALS still has the value to be referenced. Some discriminating questions from this approach are going to be collected in this study in the questionnaire through expert advice.

In VALS survey, respondents are given a score that reflects the degree to which they share similar responses on lifestyles other than their primary lifestyle, therefore, consumers are not “pure” in their type of lifestyle. Since VALS is a proprietary data base, some consumer researchers also criticize the act that researchers do not have full information on the factor loadings or rotations or the explained variance, causing them to revert to the more

basic approaches based on the academic value studies of Rokeach and Schwartz.

Another alternative to VALS is the list of value (LOV) approach, developed by Kahle (1983). Typically, respondents are asked to rank a list of values derived from the Rokeach’s value survey (RVS), then marketers can use the top-ranked value to assign consumers to segments. The main distinction between the RVS and LOV sacles, from a theoretical point of view, is that the latter dose not include any value related to societal interests.(market segmentation). An empirical comparison between the RVS and LOV scales on a convenience sample of 356 residents of a college town (Beatty et al., 1985) showed limited evidence of convergent validity between the two scales. Also, there are several studies aims to compare VALS and LOV approaches, Kahle et al. (1986) found the LOV approach predicted consumer behavior better than VALS. But from the research of Thomas et al.

(1990), when used alone, VALS appears better than LOV, but when demographic data are included with LOV, the latter approach is more effective. Research by Kamakura and Novak (1992) incorporates the more conceptual approach of Schwartz to define market segments on the basis of the latent value systems of market segments, this extension of LOV approach reflects the multiple values that affect an individual’s buying behavior, provides a richer understanding of the activities and interests of the segments.

After going through different approaches to measure the value of consumer, even thought LOV has an obvious advantage that data collection is much simple, however, since LOV implies that consumption decision are not influenced by a consumer’s concern for the welfare of others or conformity to social norms and apparently these implications are not what happen in real life.

2.4 People oriented market segmentation based on lifestyle construct

The move from mass marketing to customer relationship marketing requires decision-makers to come up with specific strategies for each individual customer based on his/her profile (Shaw et al., 2001). In today’s environment of complex and ever changing customer preferences, marketing decisions that are informed by knowledge about individual customers become critical (Peppers and Rogers, 1993), which means market segmentation, the first step in the marketing process, should be well-discussed and defined.

Historically, there are two different approaches to market segmentation: people oriented and product oriented (Plummer, 1974). Product oriented segmentation has been applied commonly to better understand the structure of the market of a specific product, directly or

indirectly through consumers. This approach has been more extensively used in academic research, for instance, wire-related lifestyle, wine-related lifestyle, food-related lifestyle and travel-related lifestyle which are developed to better explain the consumer behavior of specific clusters divided by lifestyle variables toward specific product or event. However, this approach is still adequate in its description of the consumer as a person and the analytic results usually do not extend to other products or services consumed by individuals since their lifestyles are not truly being measured. It is important to note that the product-specific approach has some disadvantages, one is when carried close to its extreme, it degenerates into simple redundancy, even when the most discriminating product-related variables are not that redundant, and they are often obvious translations of what the product can or cannot do. Another disadvantage of the product specific approach is that each product requires a separate study which is expensive and time-consuming and since the variables in

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