A CONCEPTUAL MODEL OF CUSTOMER VALUE IN E-

Xu, Yunjie, National University of Singapore, 3 Science Drive 2, 1173, Singapore xuyj@comp.nus.edu.sg Cai, Shun, National University of Singapore, 3 Science Drive 2, 1173, Singapore caishun@comp.nus.edu.sg

Abstract

Customer value is crucial in predicting customer choice in traditional consumer behavior research. However, online customer value can be different from its offline counterpart because customer value is highly context-dependent. In online retailing settings, not only the product itself, but also the web store and the Internet channel contribute value to customers.

Synthesizing the research in consumer behaviour and IS, we propose an online customer value model with three key components: the outcome value, the process value, and the shopping enjoyment. These three dimensions capture different benefits an online consumer can obtain from a web store.

A pilot study with a sample of graduate students was carried out. The preliminary results validate our choice of constructs and test the validity and reliability of the instruments used in this study. With an explicit focus on the customer role of a web user, this value conceptualization is expected to facilitate better understanding of the online consumer behaviour.

Keywords: e-Commerce, customer value, process value, outcome value, shopping enjoyment

1 INTRODUCTION

Customer value is the net benefits a customer obtains from a product or a store. Customer value has received enduring research interests in marketing area for the past two decades (e.g. Parasuraman et al. 1985, Zeithaml 1988, Dodds et al. 1991, Holbrook 1999, Chen & Dubinsky, 2003). It plays a key role in predicting customer choice. If retailers can offer values to the consumer, they are on the way to creating competitive advantages (Scott & Lamont, 1977).

Despite the crucial importance of customer value in the offline environment, it is less studied in the e-Commerce context. Online customer value can be different from its offline counterpart. Previous researches have demonstrated the multidimensional and highly context-dependent nature of customer value (e.g. Parasuraman 1997, Holbrook 1999). In online retailing settings, not only the product itself, but also the web store and the Internet channel contribute value to customers. For example, customers may enjoy the extra convenience of online shopping (Keeney 1999). However, what really constitutes the value of a web store is not well understood. Different conceptualization has been proposed (e.g. Keeney 1999, Teo et al. 2003). The aim of this research is to develop a theoretical framework which conceptualizes and examines the different dimensions of customer value in online retailing settings.

2

2.1

THEORETICAL BACKGROUND

Traditional customer value research

In consumer behavior studies, there has been an enduring endeavor to understand the concept of customer value. Two major streams of research can be identified, with one focusing on the product value, and the other focusing the on the shopping value. Product value is defined as what a consumer gets for what she pays for a product (refer to Zeithaml 1988 for a systematic discussion). Though Zeithaml’s definition of product value is more than the quality/price tradeoff, the majority of marketing researchers defined it only as quality and price tradeoff (e.g. Sirohi et al. 1998), or value for the money. Product value was found to be critical to customer’s product choice decision (Dodds et al. 1991). Shopping value is defined as the evaluations of a shopping experience with a store (Babin et al. 1994), which focuses on the process of obtaining the desired products, rather than the products themselves. Offering shopping value to customer is claimed to be critical to the patronage behavior (Babin et al. 1994). Customer value is more used as an overarching concept that encompasses both the shopping value and the product value provided by a specific store (e.g. Chen & Dubinsky 2003). While related, it is important to notice the difference between product value and shopping value. First, the shopping value of a store addresses how products are provided to customer through the store operation (e.g. lower price, better service). Therefore, two stores selling the same products can be of different value to customers. Second, part of the product value, such as price, is determined by the store operation, making perception of product value overlapping with the that of the shopping value. Finally the concept of product value is defined at the product level, while shopping value is at the store level.

A distillation of germane literature reveals that both the product value and the shopping value manifest themselves in two aspects: the utilitarian and the hedonic value (e.g. Babin et al. 1994)

In a utilitarian view, regarding a specific shopping trip, consumers are concerned with purchasing quality products in an efficient and timely manner with a minimum of irritation (Childers et al. 2001). The perceived utilitarian customer value might depend on how successful the particular consumption need stimulating the shopping trip is accomplished (Babin et al. 1994). If we follow Rajeev and Ahtola (1985) and define the consumer attitude as composing of both utilitarian and affective aspect, the utilitarian shopping value relates to usefulness and wiseness of the purchases from a specific store.

In addition to its utilitarian value, shopping has been regarded as providing hedonic value through responses evoked during the experience (Hirschman & Holbrook 1982, Babin et al. 1994). Based on prior works, Babin et al. (1994) synthesized two schools of consumer shopping behavior studies, with one focusing on a “shopping as work” theme, and another depicting the “shopping fun side”. They suggested that “a shopping experience could evoke value either through successfully accomplishing its intended goal or by providing enjoyment and/or fun” (p.5). With regarding to the product value, both utilitarian and hedonic value were also identified by researchers (refer to Hirschman and Holbrook 1982 for more details).

Therefore, we recognize that customer value includes both utilitarian and hedonic aspects. With a focus on customer value in the e-Commerce context, we define the online customer value as the consumer’s overall assessment of the net benefits gained from shopping at a store through successfully obtaining quality products and shopping enjoyment. 2.2

Prior studies on customer value in e-Commerce

Since a customer has more than enough stores to choose from online, what are the key values an online store can offer to win the customer? Table 1 summarizes the most relevant studies that take customer value (including product value) as one of the main concepts in the e-Commerce context.

Reference & Field Independent variable Alba et al. 1997. Screening alternatives to form consideration set, providing Marketing information for selecting from consideration set, transaction cost,

entertainment, social interaction, and personal security.

Chen & Dubinsky, Retailer risk (NS), product price, valence of experience 2003. Marketing Childers et al. Usefulness, ease of use, and enjoyment 2001. Retailing

Davis et al. 1992. Usefulness, ease of use, enjoyment IS

Devaraj et al. SERVQUAL (empathy, reliability (NS), responsiveness (NS), 2002. IS assurance), price, time, ease of use, usefulness Gefen. 2002. IS SERVQUAL, cost to switch vendors, perceived risk, customer trust

Keeney. 1999. IS Product quality, obtaining cost, time to get product, convenience

to find/buy/service the product, privacy, shopping enjoyment, safety, environment impact

McKinney et al. Information quality satisfaction (sub-construct: understandability, 2002. IS reliability, usefulness), System quality satisfaction (sub-construct:

access, usability, navigation)

Shim et al. 2002. Service policy information availability, use of media technologies, IS convenience/simplicity of use, presentation/product/service

information

Srinivasan et al. Customization, contact interaction (communication facilities on 2002. Retailing the website), cultivation (desired email promotions), care

(customer support), community, choice (of products), convenience (ease of use)(NS), character (image of website)

Teo et al. 2003. IS Satisfaction, effectiveness, efficiency Torkzadh & Means objectives: Online payment (privacy & shipping error), Dhillon. 2002. IS Internet product choice (assortment & comparison), Internet

vendor trust (legitimacy & security), and shopping travel.

Fundamental objectives: Shopping convenience, Internet ecology, customer relationship (return & after-sales service), and Internet product value.

Dependent variable Attractiveness Customer value Attitude

Acceptance of

information systems Channel satisfaction & preference Trust, loyalty, perceived risk Satisfaction Information search satisfaction Lycos ranking E-loyalty

Overall value N/A

Table1. Representative literature on online customer value

A few observations can be drawn from the literature. First, a rich array of variables has been considered as important predictors of online consumer’s store attitude or behavioral intention. Such variables include product value, assortment, customer service, website functionalities, and emotional value of the website. Second, variables used cover different levels, if we apply the means-end chain approach to understanding the cognitive structure (Zeithaml 1988). Quality level variables, such as product/service attributes; functional level benefits, such as perceived usefulness; others are called “emotional payoff” (Zeithaml 1988), such as satisfaction. Third, product value and shopping value are not explicitly defined and distinguished by all the studies, which makes it difficult to separate the product effect and the store management effect on the consumer behavior. Finally, the web user’s role as a customer is quite often neglected. Similarly, the role of product value in the evaluation of total customer value is overlooked.

3 PROPOSED ONLINE CUSTOMER VALUE MODEL

Synthesizing the research in consumer behaviour and IS, we propose that there are three key customer value components in e-Commerce: the outcome value, the process value, and the shopping enjoyment. This conceptualization is consistent with the utilitarian and hedonic perspective in offline consumer research, with the utilitarian value broken down into the outcome and process values, and the shopping enjoyment being the hedonic value. The process value is defined as the saving of time and effort associated with the process of finding, ordering, and receiving product through a specific web store. The outcome value refers to the value of products provided by the web store to meet the customer’s needs and wants (Sheth et al. 1999). The shopping enjoyment refers to the extent to which the shopping experience with the web store is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated. It is clear that the process value and the shopping enjoyment collectively capture the shopping value, while the outcome value is the general product value offered by a store. Figure 1 shows the conceptualization of the customer value online and its effect on behaviour intentions.

Process value Outcome value Figure 1. 3.1

Shopping enjoymentSatisfaction

The three-component model of online customer value

Theoretical Support for the Three-Component Value Model

The three-component model can be supported by theories from multiple disciplines. The attitude psychology conceptualizes attitude as having both a cognitive and an affective components (e.g. Perloff 1993). Such dichotomy is the foundation of utilitarian and hedonic aspects of consumer value, regardless of the attitude object being a product or a store (e.g. Hirschman 1984). Numerous studies in consumer behavior testified the existence of such two aspects. The cognitive aspect of attitude underlies the utilitarian perception of online shopping, which can be further classified into the process value and outcome value. Similar conceptualization has been found in IS and marketing literature. In the context of user satisfaction, Mohr and Bitner (1995) distinguished two major dimensions of service quality: outcome and process. Further, in information systems success studies, Woodroof and Kasper (1998) see end user’s satisfaction on a information system as composed of two major dimensions: outcome (what the end user receive in using the system) and process (the manner which the outcome is realized). Moreover, the process value and the outcome value can be viewed as two components in the means-end chain, with the shopping process being the means and the obtained produce value being the end (Keeney 1999).

Utilitarian values can increase the hedonic value. In studying consumer value, Ahtola (1985) posits that hedonic and utilitarian aspects are normally positively correlated, and cognitive balance theories would predict that. Additionally, Babin et al. (1994) point out that a positive association can exist between the two dimensions of value, and the empirical evidence also supports this proposition. Besides, from means-end perspective, affective consequences are believed to be in the higher abstract level than functional consequences, because the affective consequences are more strongly related to consumers’ needs, goals and value (Claeys et al. 1995).

Although the process and outcome values proposed above resembles the “system usefulness” construct proposed in the IS area, there is crucial difference. Here we want to distinguish the two roles a web user assumes: as a system user and as a consumer (Koufaris 2002). Different roles imply the different values that a web user seeks. For the system user, obtaining information online is end of the system use, while for a customer, receiving valuable product is the end. A system user takes computer playfulness as the source of emotional reaction, while a consumer looks at shopping enjoyment. As Rai et al. (2002) point out, when we move from offline in-house systems to the e-Commerce systems, the user’s value factors can be different. The difference between an in-house system and a web retail system is fundamental: the former produces needed information to its internal user and accomplish its mission, while the latter is just one step in a long process to deliver consumption value to an external system user. At the strategic level, obtaining system user satisfaction is the major objective for the former, while sales and profit is the major objective of the latter. In this regard, the traditional system usefulness has an indirect impact on organization success, while the customer value of an e-Commerce system has a direct one.

In addition, there are also crucial differences of shopping process and decision making in an online context compared to its offline counterpart. Over traditional offline shopping activities, shopping from an online store involves a different process to acquire a product (Hoffman and Novak 1996, Keeney 1999), including the information search process (Shim et al. 2001), ordering process (interaction between customer and store) (Teo et al. 2003), and product delivering process (Keeney 1999). Further, making decision online also involves a different set of information clues (physical product/store environment vs. website presence/information quality) (Alba et al. 1997), as well as decision support mechanisms (O’Keefe and McEachern 1998) over traditional offline shopping. 3.2

The value components

Because the web user assumes dual roles, the process value includes more than the time and effort cost in using the system, but also the time and effort cost in product delivery, contacting of customer support staff offline or online, and complain handling. A convenient web site with very unpleasant customer service is of no value to the consumers, and evaluating the system’s efficiency without considering after sales service is not comprehensive, if not meaningless.

The outcome value refers to value of the product provided by the web store to meet the customer’s needs and wants (Sheth et al. 1999). It involves the net benefits received by the consumer through acquiring a desired product from the web store. Such product value can be achieved in two ways: one is the product quality and consumption value inherent in it; the other is the better option available on the web site that was otherwise not visible to the customer (e.g. Alba et al. 1997). The former product value is primarily determined by the product nature and the idiosyncratic need of the customer. The latter one is to a large degree managed by the vendor.

Shopping enjoyment is the intrinsic value when shop online. Much of the work on the role of enjoyment in computer use has been done in the context of word processing and graphics programs (Davis et al. 1992), and microcomputer usage (Igbaria, et al. 1996). However, shopping enjoyment arises not only from the system playfulness, but more from the recreational effect of shopping. As Babin et al. (1994) put it: some people shop to buy, others buy to shop. A well designed web store, as does its offline counterpart, entices its customers. There are many means that can provide enjoyment

to customers, for example, building an online community (Srinivasan et al. 2002), use of media (Shim et al. 2002), and providing extensive product and information.

4 METHOD AND PRELIMINARY DATA ANALYSIS

In order to test the proposed online store value component model, a pilot study was carried out. A convenience sample of graduate students who had prior online purchase experience was used. They were asked to list up to three online stores that they have purchased from before. Out of the stores they listed, one is chosen randomly as the target company, and a survey questionnaire is filled out. The whole process is done through a survey website in a self-administered way. Subjects were given SD$10 as a reward. Seventy two usable questionnaires were return.

Instrument to measure the three value components was developed by reusing the existing items in the literature as mush as possible. Minor revisions were made when appropriate. The sources of the items, as well as the item’s wording, were indicated in table 2.

Item OV1 OV2 OV3 OV4 PV1 PV2 PV3 EN1 EN2 EN3 EN4 EN5

Measures of Constructs (measured on seven-point, Likert-type scale)

Outcome value (based on Teo et al. 2003, Childers et al. 2001): Using this Website …would help me to make a better purchase decision. …would help me to buy product I really want. …would enable me to find a good deal. …would save me money.

Process value (based on Davis 19): Using this Website …would make my shopping less troublesome.

…would make my shopping process more effective. …would make my shopping more efficient.

Shopping enjoyment (based on Babin et al 1994): Using this web site was truly a joy.

Compared to other things, the time spent on this web site was truly enjoyable. Shopping on this web site was a very nice time out.

This web site immersed me in exciting products it offers.

I enjoyed this web site for its own sake, not just for the items I may have purchased.

Mean 5.15 5.20 4.87 4.69 5.38 5.29 5.27 4.93 4. 4.35 4.13 3.71

SD

1.208 1.353 1.576 1.526 1.340 1.356 1.484

1.317 1.253 1.280 1.402 1.462

Table 2. The initial instrument

Exploratory factor analysis was conducted to test the instrument’s convergent and discriminant validity in SPSS. The objective of this step is to cut out items that did not load on the appropriate high-level construct. Table 3 (a) reports the EFA result with principal component analysis and varimax rotation using SPSS.

The pilot study result shows that item OV1, OV2, and EN1 were not loading correctly on the intended factor. A focus group discussion with some subjects reveals that they had a clearly planned shopping task with little ambiguity, such as buying a phone card or a book, which needs no decision support from the web store. Therefore, OV1 and OV2 are less relevant. For item EN1, subjects show the confusion over what is “truly a joy”. Based on that, these three items were dropped, and the remaining items were analyzed again (table 3 (b)). The items show fairly nice loading on the intended construct (all above 0.5), and no cross-loading on other items (all below 0.4). The Alphas are .953, 0.928, and 0.846 for the outcome, process value and enjoyment respectively, exceeding the required level at .7. However, we believe such selection of items should be treated with caution. In the case of more sophisticated shopping task, a consumer might not know what to buy in advance. For example, to buy flowers, the customer may well follow the suggested product for a special occasion. In other cases, the product review from other customers might influence one’s choice. To avoid data snooping, these items might be tested again in other specific case before it is used for the final study.

(a) OV1 OV2 OV3 OV4 PV1 PV2 PV3 EN1 EN2 EN3 EN4 EN5

(b) Component Component

1 2 3 1 2 3

OV3 0.458 0.636 0.196 0.942 0.185 0.153 OV4 0.452 0.9 0.137 0.957 0.168 0.066 PV1 0.935 0.225 0.139 0.130 0.0 0.116 PV2 0.929 0.183 0.06 0.145 0.922 0.174 PV3 0.09 0.885 0.092 0.139 0.920 0.149 EN1 0.098 0.916 0.153 0.1 0.293 0.770 EN2 0.086 0.909 0.133 0.047 0.173 0.878 EN3 0.33 0.72 0.366 -0.094 0.137 0.874

0.146 0.306 0.76 EN4 0.296 -0.049 0.738 0.049 0.193 0.87 -0.084 0.17 0.87 0.292 -0.029 0.741

Table 3. Exploratory factor analysis of the initial instrument

5 CONCLUSIONS AND FUTURE RESEARCH

The study identifies three key components of online customer value, namely, the outcome value, the

process value, and shopping enjoyment. These three dimensions capture different benefits an online consumer can obtain from an online store. With an explicit focus on the customer role of a web user, this value conceptualization is expected to facilitate better understanding of the online consumer behavior. Much research remains to be done in investigating the role of customer value in e-commerce, namely, the relationship between three dimensions of customer value and customer satisfaction, purchase intentions as well as customer loyalty. Also, based on these value components, it is possible to further discover and test the antecedents for each of component, and hence provide more relevant managerial guidance in web store design. More importantly, longitudinal studies on customer’s value perception changes is certainly a fruitful pursuit that will contribute towards the dynamics nature of customer value.

References

Ahtola, O.T. (1985). Hedonic and utilitarian aspects of consumer behaviour: An attitudinal perspective. Advances in Consumer Research, 12 (1), 7-10.

Alba, J., Lynch, J.W.B., Janiszewski, C., Lutz, R., Sawyer, A., and Wood, S. (1997). Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplace. Journal of Marketing, 61 (3) 38-53.

Babin, B. J., Darben, W. R., and Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20 (1), 4-656.

Chen, Z. and Dubinsky, A.J. (2003). A conceptual model of perceived customer value in e-Commerce: A preliminary investigation. Psychology & Marketing, 20 (4), 323-347.

Childers, T.L., Carr C.L., Peck J. and Carson S. (2001). Hedonic and utilitarian motivations for online retail shopping behaviour. Journal of Retailing, 77 (4), 511-535.

Claeys, C., Swinnen, A., and Abeele, P. V. (1995). Consumers' means-end chains for 'think' and 'feel' products. International Journal of Research in Marketing, 12 (3), 193-208.

Davis, F.D. (19). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-340.

Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Psychology, 22 (14), 1111-1132.

Devaraj, S., Fan, M., and Kohli, R. (2002). Antecedents of B2C channel satisfaction and preference: Validating e-Commerce metrics. Information Systems Research, 3 (3), 316-333.

Dodds, W.B., Monroe, K.B., and Grewal, D. (1991). The effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28 (3), 307-319.

Gefen, D. (2002). Customer loyalty in e-Commerce. Journal of the Association for Information Systems, 3 (2), 27-51.

Hirschman, E.C. (1984). Experience seeking: A subjectivist perspective of consumption. Journal of Business Research, 12 (1), 115-136.

Hirschman, E.C. and Holbrook, M.B. (1982). Hedonic consumption: Emerging concepts, methods and propositions. Journal of Marketing, 46 (2), 92-101.

Holbrook, M.B. (1999). Introduction to consumer value. In: Consumer Value (ed. by M.B. Holbrook), 1–28. Routledge, London.

Igbaria, M., Parasuraman, S. and Baroudi, J. J. (1996). A motivational model of microcomputer usage. Journal of Management Information Systems, 13 (1), 127-144.

Keeney, R.L. (1999). The value of Internet commerce to the customer. Management Science, 45 (4), 533-2.

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behaviour. Information Systems Research, 13 (2), 205-223.

McKinney, V.M., Yoon, K., and Zahedi, F. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information System Research, 13 (3), 296-315. Mohr, L.A., and Bitner, M.J. (1995). The role of employee effort in satisfaction with service transactions. Journal of Business Research, 32, 239-252

Parasuraman, A. (1997) Reflections on gaining competitive advantage through customer value. Journal of the Academy of Marketing Science, 25 (2), 1-161.

Parasuraman, A., Zeithaml, V.A., and Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49 (4), 41-50.

Perloff, R.M. (1993). The Dynamics of Persuasion. Lawrence Erlbaum Associates Inc. Hillsdale, NJ. Rai, A., Lang, S.S., and Welker, R.B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13 (1), 50-69.

Rajeev, B. and Ahtola, O.T. (1990). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2 (2), 159-170.

Scott, J.E. and L.M. Lamont, (1977). Relating consumer values to consumer behaviour: A model and method for investigation. In Greer, T.W. (Ed.), Increasing Marketing Productivity, American Marketing Association, Chicago, IL, 283-288.

Sheth, J.N., B. Mittal, and B.I. Newman, (1999). Customer Behaviour: Consumer Behaviour and Beyond, Dryden Press.

Shim, J.P., Shin, Y.B., and Nottinghan, L. (2002). Retailer web site influence on customer shopping: An exploratory study on key factors of customer satisfaction. Journal of the Association for Information Systems, 3 (2), 53-76.

Sirohi, N., McLaughlin, W.W., and Wittink, D.R. (1998). A model of consumer perceptions and store loyalty intentions for a supermarket. Journal of Retailing, 74 (2), 223-245.

Srinivasan, S.S., Anderson, R. and Ponnavolu, K. (2002). Customer loyalty in e-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78 (1), 41-50.

Teo, H.H., Oh, L.B., Liu, C., Wei, K.K. (2003). An empirical study of the effect of interactivity on web user attitude. International Journal of Human-Computer Studies, 58(3), 281-305. Torkzadh, G. and Dhillon, G. (2002). Measuring factors that influence the success of Internet commerce. Information System Research, 13 (2) 187-204.

Woodroof, J., and Kasper, G.M. (1998).A conceptual development of process and outcome user

satisfaction”, in Garrity, E.J. and G. L.Sanders (Eds.), Information Systems Success Measurement, Chapter 6, 122-132.

Zeithaml, V.A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52 (3), 2-22.

O'Keefe,R.M., and McEachern, T. (1998) Web-based customer decision support systems. Communications of the ACM, 41(3), 71-78