It is a hard task for manufacturers or marketers to understand customer requirements about linguistic imprecision, multiple needs and complex interactions. This research utilized Means-End Chain (MEC) to explore customer preferences in purchasing bundle. Based on the calculations results, a valuable cosmetic bundle should provide functional value as the first priority but transaction value is the last one. Manufacturers and marketers should focus on the priority attributes that customers require. Marketers could base on this information to develop appeal and communication strategy.
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Product bundling is widely practiced in todays marketplace. Marketers use the joint pricing for the sale of two or more products and/or services in a single package (Stremersch and Tellis, 2002). Past research has paid much attention to monetary benefits of bundles; however, the product attributes of bundles in satisfying the needs of customers is seldom mentioned (Soman and Gourville, 2001; Chung and Rao, 2003). Firms could utilize product bundles to increase performance and create a competitive advantage by increasing customer value. Thus, using bundling strategy will provide a variety of benefits that customers require and enhance the overall evaluation of a product bundle (Janiszewski and Cunha, 2004). Concerning previous research about value, most scholars have described the concept in terms of a trade-off. Although Williams and Soutar (2000) proposed the dimensions of customer value-functional, social, emotional, epistemic and conditional value, the causal relationships that manufacturers and/or retailers desire is lacking. Woodruff (1997) attempted to use the hierarchy concept to explain customer value; however, the concrete variables are not available. Thus, breaking down the concept of value and exploring the preferences for product bundles are necessary for marketers, so as to both understand the preferences of customers and to create a competitive advantage.
However, understanding customer preference is difficult to achieve in marketing. The first reason is that customers will consider multiple criteria, at the same time, for their alternatives in the decision making process. In this process there is likely to be interaction among the different criteria. Thus, the evaluating process is complex. The second reason is that human assessment of qualitative attributes is always subjective and imprecise. Thus, the descriptions of customer requirements are usually linguistic and vague (Chan et al., 1999).
According to research by Euromonitor International in 2008, the market worth of the global cosmetics and toiletries (C and T) industry is about US$ 330 billion (bn) in the 52 main countries; of these, the top 3 sales countries are North America (50.4 bn), Japan (29.8 bn) and Brazil (18.2 bn). Concerning the sales amount of C and T retail channels, hypermarkets, pharmacies and department stores dominate over 50% of global sales. In the practice of C and T sales, single function products cannot satisfy the multiple requirements of customers. Customers consider issues of both attribute completeness and utility complementarily. Various cosmetic bundles are available and play an increasingly important role in the C and T market to satisfy customer needs (Melanie, 2008). Thus, this study examines three real cosmetic bundles to find the critical product attributes for improvement and then plan a complementary bundle.
Product bundle: Bundling occurs when two or more products or services are sold together as a single package for a single selling price. Adams and Yellen (1976) define bundling as selling goods in packing. Guiltinan (1987) defines bundling as two or more products and/or services in a single package for a special price. Monroe (1990) defines it as the selling of two or more products/services at a single price. Recently, Stremersch and Tellis (2002) define bundling as the sale of two or more separate products in one package. Based on the above definitions, there are two themes about bundling strategies, the product form and the bundling focus. In the former case, pure bundling and mixed bundling are involved. Mulhern and Leone (1991) argues that pure bundling denotes that the services are available only in the bundle form-they cannot be purchased separately; in contrast, mixed bundling allows customers either to purchase one or more of the services individually or to purchase the bundle.
In most of the previous literature, there is a plethora of price bundling research which views bundling just as a pricing and promotional tool used at short notice and for a short duration. For example, Harlam et al. (1995) adapted the value function of prospect theory to examine how consumers evaluate the outcomes of components as well as bundle pricing and make a purchase choice. Soman and Gourville (2001) used the concept of sunk cost to examine how price bundling affects the decision by the consumer. In contrast, few researchers are involved in exploring preferences in bundle purchasing, despite the potential for more strategic applications to create added value and provide a more long-term differentiation strategy (Stremersch and Tellis, 2002). For example, product bundling benefits customers by reducing the time and cognitive effort required to make purchase decisions (Moriarty and Kosnik, 1989). Product bundling also could be a strategy for new product introduction through bundling with an existing product (Simonin and Ruth, 1995). Sarin et al. (2003) applied product bundling as a strategy to reduce the perceived risk with new high-tech products because customers are subject to additional worries about compatibility between parts of a product system.
Whether considering price bundling or product bundling research, the key to effective bundling is the degree of value for customers (Jiang et al., 2011). The influence of value depends on the attributes among the components of the bundle which can provide diverse benefits and satisfy customers multiple needs at same time. Legarreta and Miguel (2004) indicated the benefits of bundles arise from the complementary nature of the products, the convenience and lower search cost of one-stop shopping, introduction to new service and the perception of added-value. Thus, attributes of product bundle that a customer needs include not only the tangible characteristics of components but also the intangible characteristics that components possess. If researchers could determine the influential attributes and understand the preferences of customers, manufacturers and marketers could use this information to provide value to customers more exactly. This is also the most important research motivation of this study (Zanjani et al., 2009).
Customer value: In 2004, the American Marketing Association offered the formal definition: Marketing is an organizational function and a set of processes for creating, communicating and delivering value to customers and for managing customer relationships in ways that benefit the organization and its stakeholders. Based on this definition, customer value plays an important role for firms to develop customer relationships. However, what is customer value? It may bring to mind two different concepts. Firstly, some authors might think of personal values-the shared, central beliefs about right and wrong, good and bad, which guide behavior and this sense is also the key point of this study (Lee et al., 2009). Secondly, the concept of the value of a customer is gaining importance because of the growing interest in customer relationship management. This concept refers to the economic (e.g., profit) value to a seller of patronage by a customer over a lifetime (Sudhahar et al., 2006).
About personal values, there are three different definitions. The first one identifies value with the monetary price of the product. For example, Oliver (2000) argued that customer value is the hypothetical price for a suppliers offering at which a particular customer would be at overall economic break even, relative to the best alternative available to the customer for performing the same set of functions. The second one focuses on any benefit that a product can contribute, identifying the value as the utility or value added that allows the consumer to achieve his/her objectives. For example, Afuah (2002) indicated that the value that a customer attaches to the characteristics is a function of the extent to which they contribute to the customers utility or pleasure. The third one considers the relationship between quality and price. For example, Monroe (1990) suggested Buyers perceptions of value represent a balance between the quality or benefits they perceive in the product relative to the sacrifice they perceive by paying the price. This reflects a tradeoff between benefit and sacrifices; it has also been adapted by most scholars. For example, Woodruff (1997) stated that Customer value is a customers perceived preference for and evaluation of those product attributes, attribute performances and consequences arising from use that facilitate (or block) achieving the customers goals and purposes in use situations. Smith and Colgate (2007) argue that customer values should be further divided into four categories, including function/instrumental, experiential/hedonic, symbolic/expressive and cost/ sacrifice.
In fact, there are two similar definitions which could help us to obtain the overall view of customer value. Value is the consumers overall assessment of the utility of a product, based on perceptions of what is received and what is given (Zeithaml, 1988). Perceived value is defined as the degree to which a potential adopter perceives that the benefits of a product exceed the sacrifices associated with its adoption and consumption (Mazumdar and Jun, 1993). Based on these views, customer value is the trade-off between what the customer receives and what the customer gives up in acquiring and using a product. Thus, the customer value could be the result of perceived benefits minus perceived sacrifices (Montinaro and Sciascia, 2011).
Means-end chain: The first versions of Means-End Chain (MEC) were introduced by advertising practitioners (Young and Feigin, 1975) who developed guidelines for the creative process and took their point of departure in investigating what degree of involvement and what kind of information processing are typical for the product in question. Gutman (1982) developed this thinking further by suggesting that consumers use a cognitive chain for buying decisions that relates product attributes to benefits, which in turn contribute to fulfill personal values. The core assumption of this approach is that consumers view product attributes or service bundles as means to achieve desired ends; that is, consumption-relevant knowledge is represented in memory as hierarchical cognitive structures at various levels of abstraction and their associative links to consumers self-knowledge. These cognitive structures are labeled means-end chains and are the result of learning and experience processes (Reynolds and Gutman, 1988).
Means-end theory asserts that product attributes are the anchor for the meanings that consumers find in products. Specifically, product attributes yield benefits which move consumers closer to their vision of the good life as described by their personal value. Interviews with customers often yield hundreds of ladders about the relevant connections between attributes and values. Researchers typically summarize the hundreds of ladders they have collected in a visual diagram known as a customer decision map. By representing a series of ladders in one or more customer decision maps, researchers can clarify customers thinking and simplify the process of communicating their analyses with others. To further increase the visual clarity of customer decision maps, some means-end researchers insist that these maps be drawn so that no lines cross. As Gengler and Reynolds (1995) have noted, there is a tension here between the desire not to lose valuable insights and the need for a customer decision map that is easily interpretable by other key decision makers. The challenge is to create a map that is both accurate and aesthetically pleasing which requires a trade-off between validity and parsimony. To make this possible, means-end researchers do not try to represent every possible means-end ladder in a single map. Instead, they typically try to represent most of the information contained in the set of means-end ladders they have identified in their research.
In the marketing field, MEC theory can be thought of as a predominant approach to understanding consumers product knowledge. Woodruff (1997) suggested that consumers conceive of desired value in a means-end way and suggested a concept hierarchy model of consumer value. Starting at the bottom of the hierarchy, customers learn to think about products as bundles of specific attributes and attribute performances. Although Woodruff (1997) proposed the conceptual customer value hierarchy model, the components of each level are not available. Thus, this study will utilize this method to develop the framework of customer value for product bundles in order to explore the preferences of customers.
RESEARCH DEVELOPMENT AND DESIGN
Research samples and investigation process: To explore the customers preference in selecting bundles, this study firstly interviewed 48 cosmetic experts to construcBt a customer value framework of cosmetic bundles in year 2010. Next, questionnaires were designed to obtain the weight of attributes for cosmetic bundles. As being at an exploratory stage, this study relies on theoretical, purposeful and relational sampling to expand theoretical concepts. The criteria here to select the participants for this study are experts with sufficient knowledge domain or consumption experience in cosmetics. Thus, besides the Very Important Persons (VIPs) of target customers aged from 20 to 45, three different types of experts were also considered, including scholars, cosmetologists and sales clerks. There are four reasons for adopting these experts and VIPs views. First, compared with general consumers, experts and VIPs have more complete product knowledge about cosmetics. Second, general consumers just focus on their own demands; however, experts have more experience of contact with different cases. Third, compared with general consumers, the VIPs have more shopping experience in purchasing different cosmetic bundles. Lastly, for scholars, sales clerks and cosmetologists, their jobs are to provide information for customers and/or to help satisfy customers needs in their use.
Construct the hierarchical customer value framework of product bundle: To develop the framework of customer value of product bundle, the Means-End Chain (MEC) is adopted in this study. The laddering technique and customer decision maps are the two major processes in MEC. The laddering technique helps research to focus on the data concerning product attributes; data is collected using in-depth interviews. Each expert is asked three questions about cosmetic bundles. The questions are as follows:
|•||From your industrial experience and/or professional knowledge, what cosmetic bundle outcomes (or value) are most often expected by customers and why?|
|•||From your industrial experience and/or professional knowledge, what consequences (or benefits) are most often considered when purchasing and using cosmetic bundles and why?|
|•||From your industrial experience and/or professional knowledge, what product characteristics (or attributes) of cosmetic bundle are customers mostly concerned about and why?|
After the interviews with all of the experts, the focus of the analysis was to construct the HCVF. The HCVF can be constructed by modifying the method developed by Reynolds and Gutman (1988) for data collection on MECs. This study, argues that, besides C-C relations, the relation A-A also needs to be considered and a crossover could exist among attributes in the HVM. Based on laddering theory, the performance of higher levels (abstract) is provided by the lower levels (concrete). However, this provision from lower to higher level could be an indirect relation through another element of the same lower level. Thus, besides the relation of A-C, C-C and C-V, the A-A will also appear in the table of the summary implication matrix. Constructing the HVM includes the following steps:
|•||Classify all responses into the three basic A/C/V levels|
|•||Break down all responses into individual summary codes|
|•||Because overly broad or detailed individual summary codes are unsuitable for analysis, redundant or meaningless codes are distinguished and eliminated from the relevant elements that are the focus of the target product|
|•||Re-code related (remaining) elements|
|•||The A-C-V relationships are summarized into the summary implication matrix table, which includes A-A, A-C, C-C and C-V. The numbers in the A/C/V Table 1 and 2 represent the following:|
|•||The numbers in integer form represent the direct relationship of row elements to column elements.|
|•||The numbers in decimal form represent the indirect row-column frequency|
|•||Direct relations are implicative relations among adjacent elements. Indirect relations refer to two elements that are indirectly connected but can be adjacent to other elements|
|•||The HCVF are constructed from the summary implication matrix table by a cut-off value criterion|
Based on the method developed by Gengler and Reynolds (1995), the cut-off value should never be less than 70%, with an average number normally falling in the 75 to 85% range.
The HVM of product bundle: A content analysis was conducted on the interview data. Firstly, following the open coding of in-depth interviews with cosmetic experts, 51 elements were identified; then, based on the concept of A/C/V, these 51 elements were classified into three different levels-product attributes, expected consequences and desired value. Secondly, in order to distinguish relevant elements for constructing the framework, the researcher showed these classified results to the experts with a request to eliminate redundant and similar codes. Thirdly, the researcher re-coded the remaining elements resulting from the feedback from experts and from these, 22 product attributes, 10 expected consequences and 4 desired values are extracted. Then, the summary implication matrix of A/C/V was constructed by analyzing the in-depth interviews with cosmetic experts. The table of the A/C/V implication matrix is shown in Table 1 and 2. The construction of the implication matrix (Table 1, 2), represented the number of times each element leaded to another, that was, on a ladder which element preceded another. The number of relations was presented through numbers in a fractional form, where the direct relations appeared to the left of the decimal point and the indirect relations to the right.
|Table 1:||The summary implication matrix of A/C/V|
|The numbers in integer form represent the direct relationship of row elements to column elements; the numbers in decimal form represent the indirect row-column frequency|
|Table 2:||The summary implication matrix of A/C/V|
|The numbers in integer form represent the direct relationship of row elements to column elements; the numbers in decimal form represent the indirect row-column frequency|
Lastly, according to decision rules of the cut-off values, the HVM of product bundle chains was established in Fig. 1.
|Fig. 1:||The HVM of cosmetic bundle|
This HVM accounted for 81.35% of all of the connections in the raw laddering data. The cut-off value is determined by the following rules:
|•||Cut-off value = 4 when the A-C-V variable relations are direct|
|•||Cut-off value = 3.2 when the A-C-V variable relations are both direct and indirect|
|•||Cut-off value = 0.5 when the A-C-V variable relations are indirect|
Customers preference at the attribute level: In the previous study about MEC, most researchers focus on hierarchical relationships of A-C and C-V level in the HVM. However, these hierarchical relationships could only provide direct and superficial evidences. About horizontal interaction relationships in the same level, such as C-C and A-A, are not or few mentioned. One possible reason due to the methodology limitations of MEC - psychosocial consequence is upper level than functional consequence level and the cross line could not exist among attributes. Without above limitations or trammels, however, the HVM is more complicated in reading but it also provide more explanatory capability and reciprocal causation (especially in A-A level) through horizontal causal relationship.
This study utilized means-end chain to develop the framework of customer value for product bundles in order to explore the preferences of customers. From the result, the product attributes could be separated into two types in this study. The first type had a direct relationship with product performance which was provided by the internal attributes of the product, such as sun protection, whitening, revitalizing and so on. Such product attributes fell under symbolic and functional value. The other type was an indirect relationship with product performance which was provided by external attributes of the product, such as being well-known, the production place, easy purchase and so on. These product attributes fell under safety and transaction value.
Besides, that internal product attributes which possessed the maximum value not only provided prior importance for the customer to obtain the expected consequences but also became an accelerator for the other attributes in the same consequence to enhance their performance.
Therefore, we might imply that Customers depend on suggestions by other people (word of mouth) and certification from enterprises to evaluate brand reputation and utility compatibility of cosmetics bundles. After further thinking, customers still believe others suggestions and the components of products as prior factors to assess the above expected consequence. Thus, customers were practical and did care about the price rationality rather than the extra gift in purchasing cosmetics bundles.
CONCLUSIONS AND SUGGESTIONS
In general, the modification of the means-end chain allows us to construct a hierarchy framework of customer value and to allow product attributes to be linked. Through the indirect relation by linking attributes, the explanation capability for forming consequence could be enhanced effectively; furthermore, the thinking process of customers could be understood completely.
In practice, cosmetics companies utilize DM, mail and media as advertising tools to attract customers attention. Through this communication process, marketers could understand customers preferences and concerns and then help them to purchase the products they need. Thus, concerning appeal issues, marketers could focus on the product attributes that match customers preferences and through advertisements appeal to customers. For example, Moisturized skin, Sun Protection, Cleaning, Firming and Natural component are the top 5 product attributes that customers prefer. Marketers could manifest the above attributes and mark them in appeal strategies of cosmetics bundles. Furthermore, marketers need to focus on the convenience of time saving and point out that the advantages of purchasing cosmetics bundles by a company are not only cheaper than separate purchasing; the more important benefit is that the bundle provides multiple faculties which make the purchase easy.
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