Using Electronic Customer Relationship Management to Maximize/Minimize Customer Satisfaction/Dissatisfaction

Nama kelompok :

Heri kurniawan (23210252)

Muhammad iqbal (24210736)

Yusuf fadillah (28210800)

Using Electronic Customer Relationship Management to Maximize/Minimize Customer Satisfaction/Dissatisfaction

Abstract

Electronic Customer Relationship Management (eCRM) has attracted the attention of managers and academic researchers for the past several years. Issues of eCRM have varied from marketing to information technology. While there are many concerns and efforts for successful management of customer relationship in the online environment, this study posits that the major components of eCRM include increasing customer satisfaction and customer loyalty, minimizing customer dissatisfaction, resolving customer complaints and increasing product/service quality. This paper has reviewed the issues on eCRM published over the past years that have involved major topics such as customer satisfaction and dissatisfaction. The study also reviewed customer loyalty and complaints that are consequences of customer satisfaction and dissatisfaction. The study provides implication both to researchers and businesses that a hybrid approach of marketing and information system perspectives leads successful eCRM.

Keywords: Electronic Customer Relationship Management (eCRM), Customer Satisfaction/Dissatisfaction, Complaining Behavior, and Customer Loyalty.

1.      I.                   Introduction

Electronic commerce relies on customer interactions via a computer and telecommunications infrastructure for the purpose of advertising, promoting, and selling products and services online. Electronic commerce replicates most of the physical activities that take place in the market place to the point where increasing electronic commerce usage are shifting companies from those traditional market places to new market spaces. The traditional market places emphasize “customer satisfaction” as a way to earn consumer loyalty and attract new customers. Therefore this study examines the firm’s approach to Customer Relationship Management in order to account for the new realities of market spaces. To be successful in a market space, a firm will have to be responsive to their virtual customers’ wants, needs and desires, and manage the interactions with them properly in order to arrive at a win/win outcome. Marketing considers that interactions between customers or potential customers and the firm arrive at a win/win outcome either in a market place or in a market space, when: i) such interaction(s) lead to the sale of a given item(s); and/or ii) such interactions lead to an increased likelihood that a sale of the same or other item(s) will happen in the near future to the satisfaction of both parties. Win/win means the customer wins through a satisfying purchase of a product or service and the firm wins by selling this product or service. Increased customer satisfaction will augment the likelihood that the customer will purchase again and/or induce other potential customers to buy, either through testimonials or word-of-mouth effects. Under this scenario, moving from the market place to the market space poses new challenges to the firm. Many years of experience have enabled them to manage market space, but market space is the result of a phenomenon (the web), which is about 20 years old.

In addition to the new realities of the market space, the constant development of the web as a new environment medium opens significant challenges to marketers, that they may not be well prepared face. The key new element is the dynamic nature of the interactive system used by customers to gain access to a firm’s web site, and what happens after the web site has been reached. Under this scenario, three important questions must be answered: i) How does a firm attract potential customers to its own web site; ii) Once customers enter the firm’s web site, how can the web site “cooperate with the customer” in order to arrive at a win/win situation; and iii) How must the firm adjust its marketing information systems to ensure that proper information and feedback is obtained from market space interactions for better management decision-making.

These three questions are not independent, i.e., the satisfaction experienced by a potential customer reaching a firm’s web site will depend on the prior experience and expectations that they build along the way (both in the past and in this particular web session) and the design of the web site, which may or may not handle those expectations in a “cooperative” manner. Management will not have a clue as to what happened if proper arrangements are not made to capture the satisfaction of the customers with the overall process. Because a market space is a unique blend of marketing activities in a “virtual,” interactive electronic environment, this paper will track the issue of customer satisfaction/dissatisfaction both from the traditional marketing viewpoint, and the more recent Information Technology views about interactive systems. In particular, given the importance of “cooperation” between the firm and its customers, current knowledge of user satisfaction with collaborative environments will also be included. All these aspects will help the future formulation of a “hybrid model of customer satisfaction” using the Web that accounts for all the components of market space, under the win/win mandate of the “marketing principle.”

Based on the consideration above, the purpose of this study is to review the state of art for eCRM by examining issues raised by researchers during the past several years, underlying theories and models of eCRM which are rooted on both consumer satisfaction and dissatisfaction in marketing, and other future research issues. The purpose of this study is to also review consequences of customer satisfaction/dissatisfaction such as customer loyalty and complaints.

1.      II.                Defining Electronic Customer Relationship Management

eCRM has attracted the attention of e-business managers and academic researchers who are interested in increasing repeat business and customer loyalty (Julta, Craig, and Bodorik, 2001). Various researchers have defined the eCRM according to different aspects. Based on the review by Jukic Jukic, Meamber and Nezlek (2002-2003), eCRM is a business strategy that utilizes the power of technology to tie together all aspects of a company’s business with the goal of building long-term customer loyalty. Jukic et al. (2002) also stressed that eCRM, in practical terms, is the management of customer interactions at all levels, channels, and media. Hansen (2000) sees eCRM as “a process of acquiring, retaining and growing profitable customers. It requires a clear focus on the service attributes that represent value to the customer ant that create loyalty.” A review by Romano and Fjermestad (2001-2002) emphasized that eCRM involves attracting and keeping “economically valuable” customers while repelling and eliminating “economically invaluable” ones. On the market space, eCRM is to build and maximize the value of the relationship with the customer and to improve customer retention rates (Jukic et al., 2002; Cho, Im, Hiltz, and Fjermestad, 2002).

Issues of eCRM have been developed from Relationship Marketing, which is to establish, maintain, and enhance relationships with customers and other partners, at a profit, so that the objectives of the parties involved are met (Grönroos, 2000). At the lowest level of a relationship, marketers build a financial bond with customers by using pricing strategies (i.e., periodic email notification of price discounts to individual users) (Strauss, El-Ansary, and Frost, 2003). At a level two-relationship, marketers stimulate social interaction with customers. Managing online community is one of the strategies for a level two relationship. For a deeper level relationship, e-businesses rely on creating structural solutions to customer problems. Offering customization service is a good example of level three-relationship (Strauss, El-Ansary, and Frost, 2003).

Among various levels of relationship marketing, online companies have been paying attention to making stronger relationships in order to retain existing or create future customers. For example, customization or online communities have been used to maintain a strong relationship with customers. While the Internet services are getting popular, one of the most important challenges is to reach customer satisfaction and maintain customer loyalty. Julta, Craig, and Bodorik (2001) notes that customer metrics affect eCRM; there include customer retention, satisfaction, acquisition, and profitability. Another side of eCRM includes how to minimize customer dissatisfaction and complaints. Cho, Im, Hiltz, and Fjermestad (2002) posit that minimizing customer dissatisfaction and complaints are part the key components of successful eCRM. Therefore, this study defines eCRM as an e-business strategy that interact with customers to maximize customer satisfaction, to build customer loyalty and also to attract potential customers to its website.

III.             MAXIMIZING/MINIMIZING CUSTOMER SATISFACTION/DISSATISFACTION AS MAJOR COMPONENTS OF ECRM

Various researchers have proposed a framework for eCRM studies. A previous review on eCRM in information system research by Romano and Fjermestad (2003) suggested the frameworks for CRM research, including eCRM within markets, eCRM business models, eCRM knowledge management, e-CRM technology issues, and e-CRM human issues. From about the early 1990s until now, studies on eCRM have addressed issues regarding i) factors affecting customer satisfaction and loyalty; ii) factors affecting customer dissatisfaction and complaints; iii) effectiveness of the website; iv) the impact of online communities on eCRM; v) supply chain management; and vi) knowledge management, etc. Cho, Im, Hiltz, and Fjermestad (2002) notes that the major eCRM components to be discussed include: i) maximizing customer satisfaction/minimizing customer dissatisfaction; ii) increasing customer loyalty; iii) increasing product/service quality; and iv) resolving customer complaints. This study will review issues of customer satisfaction/dissatisfaction including theories and models that have been frequently applied to eCRM. This study will also review issues of customer loyalty and complaints that are consequences of customer satisfaction/dissatisfaction.

Satisfaction is defined as a judgment that a product or service feature, or the product or service itself, provided (or is providing) a pleasurable level of consumption-related fulfillment, including levels of under- or over-fulfillment. (Oliver, 1981). According to Surprenant (1977), satisfaction leads to desirable consequences such as repeat purchase, acceptance of other products in the line, brand loyalty, store patronage, and, ultimately, higher profits and increased profit share. According to Tse andWilton (1988), satisfaction is the consumer’s response to the evaluation of the perceived discrepancy between prior expectations and the actual performance of the product as perceived after its consumption.

Maximizing customer satisfaction and maintaining customer loyalty have become objectives for eCRM. In an effort to provide a positive contrast for the new against the old, this paper first discusses the issue of customer satisfaction and customer loyalty as being at the center of successful brick-and-mortar physical business exchanges. The author focuses more on the customer satisfaction because it provides clues as to what managerial changes might have induced different and more desirable behaviors, raising the issue of customer loyalty myopia. This myopia stems from believing that consumer behavior can be created and sustained in and by itself without careful regard to its underlying basis on the customer satisfaction side, reviving the long-standing marketing dilemma of attitude and behavioral measures, and how much attitudes influence or predict behavior.

The level of detail goes beyond the customer satisfaction concept and much more deeply into the underlying theories and models that attempt to explain why people may or may not be satisfied. Given the recent dismal performance of most e-commerce stars  – e.g., amazon.com lost 70% its market value in 2000 – the author is forced to admit that customers’ purchasing behaviors are rather sticky and most e-commerce innovations will be absorbed gradually when customers prove their worth beyond the initial trial phase. This question’s importance transcends the domain of the enterprise and goes into society at large because shopping exchanges are a key element of the social order and economic growth.

Although customer satisfaction has been identified as a key component of eCRM (Cho, Im, Hiltz, and Fjermestad, 2002), the question of how to minimize online customer dissatisfaction has not received much attention. As with any transaction, online customer satisfaction/dissatisfaction is largely determined by how much the customer’s expectations differ from the product’s or service’s actual performance what traditional marketers refer to as the degree of disparity resulting from a customer’s disconfirmation of expectations (Anderson, 1973; Tse and Wilton, 1988). According to Cho, Im, Fjermestad and Hiltz (2001a and b), proposed model of online customer complaining behavior, online customer dissatisfaction results from unmet expectations about a product, technology issue; and/or Web assessment factors (Schubert and Selz, 1999), which include information content, customized product information, convenient after-sales support, privacy issues, and fast and accurate delivery, etc. Similarly, according to customer metrics by Julta and Bodorik (2001), online customer satisfaction primarily depends on lead-time, delivery speed, product or service introduction, and convenience.

RESEARCHERS IN THE CUSTOMER SATISFACTION/DISSATISFACTION (CS/D) AREA POSITED THAT THE FULFILLMENT OF EXPECTATIONS IS A DETERMINANT OF CONSUMER SATISFACTION. MOST OF THE DEFINITIONS OF SATISFACTION OR DISSATISFACTION THAT HAVE BEEN PROPOSED CONTAIN SOME MENTION OF “EXPECTATION” OR A SYNONYM (GILLY 1979). BEARDEN AND TEEL (1980) POSIT THAT THE INTENSITY OF COMPLAINT BEHAVIOR WAS OFTEN HYPOTHESIZED TO BE DIRECTLY PROPORTIONAL TO THE CUSTOMER’S DEGREE OF DISSATISFACTION.

IV.             THEORIES APPLIED TO ECRM STUDIES

Researchers on eCRM have applied various theories on customer satisfaction developed by marketing researchers. In this paper, authors cover in depth the most commonly accepted theories relating human factors to the satisfaction level and effective use of Computer Mediated Communications (CMC). This takes the view that current CMC techniques applied to e-commerce have grown out of different application domains where the needs and benefits sought may have been different from what is required for successful business applications.

Various satisfaction/dissatisfaction theories applied consumers’ judgment on satisfaction with product/service. Most of the early studies focused on approach to products only using comparison with their expectations about the product performance. Expectation and disconfirmation have been used as proxies to predict satisfaction and significant variables in a satisfaction function. If the performance is above the (predicted) expectations (i.e., if positive disconfirmation occurs), increases in satisfaction are expected, while if the performance is below expectations (i.e., if negative disconfirmation occurs), increases in dissatisfaction are expected.

Satisfaction/Dissatisfaction theories that frequently have been cited include cognitive dissonance theory (Festinger, 1957), contrast theory (Engel and Blackwell, 1982; Howard and Sheth, 1969; Cardozo, 1965), assimilation-Contrast Theory (Oliver, 1997), expectation – disconfirmation theory (Oliver and Desarbo, 1988), generalized negativity theory (Yi, 1990), level of aspiration (LOA) theory (Yi, 1990), and adaptation level theory (Helson, 1948, 1959, and 1964), etc. Other theories such as comparison-level theory, equity theory, and value-percept disparity theory have been applied for explaining the expectation-disconfirmation paradigm.

According to the cognitive dissonance theory, disconfirmed expectations create a state of dissonance or psychological discomfort (Festinger, 1957). The theory (Festinger, 1957) states that dissonant or inconsistent states may exist and are a source of psychological tension to the person perceiving them. This tension will lead to efforts to reduce dissonance and restore consistency. Mechanisms to reduce dissonance include changes in behavior or attitudes, or selective distortion of perceptions (Festinger, 1957). Thecontrast theory presumes that when product expectations are not matched by actual performance, the contrast between expectation and outcome, or the surprise effect, will cause the consumer to exaggerate the disparity (Engel and Blackwell, 1982; Howard and Sheth, 1969; and Cardozo, 1965). Similarly, assimilation-contrast Theory (Oliver, 1997) found that expectation and disconfirmation were independently related to the post-exposure ratings.

Another theory support for eCRM is called the adaptation level theory (Helson, 1964), which posits that one perceives stimuli only in relation to an adapted standard (Yi, 1990). Adaptation level theory says that if the original expectations were to change, the customer would still be free to compare unfavorably the product received with better ones (Helson, 1964). The generalized negativity theory stated that any disconfirmation of expectations is perceived as less pleasant than a disconfirmation of expectations (Yi, 1990). Yi (1990) restated that disconfirmation of expectations results in a hedonically negative state, which is generalized to objects in the environment. If consumers expect a particular performance from a product, and a discrepant performance occurs, they will judge the product less favorably than if they had not had prior expectations. The elements and the process may be viewed as analogous to the level of aspiration (LOA) theory’s description of the evaluation of differences between expected and actual performance and the perception of “success” or “failure” (Yi, 1990). Combining this idea from LOA theory, from Thibaut and Kelly, and from Sherif, one may suggest a model that calls attention particularly to some factors critical to the measurement of satisfaction.

Theories such as Hirshman’s (1970) exit-voice theory explained the role of customer complaints to customer satisfaction and loyalty. Hirshman’s (1970) exit-voice theoryexplained that the immediate consequences of increased customer satisfaction are decreased customer complaints and increased customer loyalty (Fornell and Wernerfelt, 1987). When dissatisfied, customers have the option of exiting (e.g., going to a competitor) or voicing their complaints in an attempt to receive retribution. An increase in overall customer satisfaction should decrease the incidence of complaints. Instead, overall customer satisfaction should also increase customer loyalty. Loyalty is the ultimate dependent variable in the model because of its value as a proxy for profitability (Reichheld and Schefer, 2000).

<<Table 1>>

Various researchers address the importance of customer satisfaction on the studies of Electronic Customer Relationship Management (eCRM: Table 1). Studies by Khalifa and Liu (2002-2003) and Ho and Wu (1999) apply the expectation disconfirmation theorydeveloped in marketing on their research model. Cho and Ha (2004a and b) applies various theories, such as uses and gratification theory and theory of reasoned action.Uses and gratification theory (Herzog, 1944; McGuire, 1974; Luo, 2002) has been frequently applied in this study to explain users’ attitudes toward movie-related web sites and consumer satisfaction. Another study by Cho and Ha (2004b) applies the von Neumann-Morgenstern utility theory that is developed by Hauser and Urban (1979) to explain the application of utilities to the method of decision analysis.

Another interesting theory that explains customer dissatisfaction and complaining behavior is called Equity theory (Blodgett, Granbois, and Walters, 1993). According to previous studies (Blodgett, Granbois, and Walters, 1993; Goodwin and Ross, 1990), how individuals involved in conflicts or disputes perceive justice has been explained by Equity theory. Complaint handling incidents, which are rated favorably, include compensation in line with the perceived costs experienced by the customer (Kelly and Davis, 1994), thus supporting an equity-based evaluation of complaint outcomes (Blodgett, Granbois, and Tax, 1997). A study by Tax, brown, and Chandrashekaran (1998) and Goodwin and Ross, (1990) addressed the concept of justice, as a comprehensive framework to explain people’s reactions to conflict situations. Three justice dimensions were discussed to explain complaint handling when customers encounter service failure (Blodgett, Grranbois, and Tax, 1997; and Tax, Brown, and Chandrashekaran, 1998). Dimensions includedistributive justice, procedural justice, and interactional justice. How individuals involved in conflicts or disputes perceive justice has been explained by Equity theory (Blodgett, Granbois, and Walters, 1993).

V.                MODEL OF CUSTOMER SATISFACTION/DISSATISFACTION

Traditional marketing researchers have suggested various models for customer satisfaction/dissatisfaction. Recently suggested models for eCRM have been developed from traditional customer satisfaction/dissatisfaction models. Those models for eCRM have investigated how variables affect customer satisfaction/dissatisfaction. Traditional models for customer satisfaction/dissatisfaction include the expectation disconfirmation model, perceived performance model, norms based model, multiple process models,attribution models, affective model, equity model, the American Customer Satisfaction Index Model (ACSI), and complaint behavior model.

Various researchers have measured the level of satisfaction/dissatisfaction and complaints by considering the difference between expectations and disconfirmation. Erevelles and Leavitt (1992) posit that the expectancy-disconfirmation (ED) paradigm has been dominated consumer satisfaction/dissatisfaction research since its emergence as a legitimate field of inquiry in the early 1970’s. According to this paradigm, consumers are believed to form expectations about a product prior to purchasing the product (Oliver, 1980). The ED paradigm can be derived from expectancy theory (Tolman, 1932) and especially, the notion of expectations is generally defined as consumers’ beliefs that a product has certain desired attributes (Erevelles and Leavitt, 1992). Bearden and Teel (1983) also considered the expectations disconfirmation in the model to examine the antecedents and consequences of customer satisfaction/dissatisfaction. Oliver (1980) established a process to describe how satisfaction is produced in this expectation-disconfirmation framework. Prior to making a purchase, buyers form expectations of the products or service. Consumption of the product or service reveals a level of perceived quality (which can be influenced, itself, by expectations). The perceived quality either positively confirms expectations or negatively disconfirms them. Expectations serve, in Oliver’s model, as an anchor or baseline for satisfaction, the positive confirmation or negative disconfirmation either increasing or decreasing the customer’s resulting satisfaction (Vavra, 1997).

A traditional model of satisfaction by Oliver (1980: Figure 1) is related to the “The American Customer Satisfaction Index (ACSI),” which was developed by Fornell (1992), roughly emulates a national measure conducted inSweden, the Swedish Customer Satisfaction Barometer. Fornell’s model expresses satisfaction as the result of three elements: perceived (experienced) quality, expectations, and perceived value. Customer satisfaction models (Figure 1) have considered three components: antecedents (pre-purchase), satisfaction process, and consequences (post-purchase). Prior experience is the most important antecedent of satisfaction. The model explains influences, such as demographics, word of mouth, personal expertise, evolution of technology, nature of competition, advertising and PR that affect customer expectations and performance. Further, the model explores how the satisfaction process subsequently influences complaining (or complementing) behavior as well as customer loyalty (Fornell, 1992). Models are also embedded in the system of cause and effect relationships (as shown in Figure 1), which makes it the centerpiece in a chain of relationships running from the antecedents of overall customer satisfaction – voice and loyalty (Bateson and Hoffman, 1999).

<<Figure 1>>

Table 2 summarizes variables applied for the study of eCRM. Cho, Im, Hiltz, and Fjermestad (2001b) examined how the differences in degree of dissatisfaction sometimes occur between online and offline customers for many reasons.  The major reasons include problems associated with different customer service center approaches (e.g., lack of an information or help desk during the order process, slow feedback response time, poor after-sales support), general terms and conditions (e.g., guarantees, guidelines for returning products), delivery issues (e.g., late or no delivery, product damage during delivery), security and privacy issues, failure of information quality, and system performance (e.g., slow web sites, broken links to other pages).

<<Table 2>>

Studies by Schubert (2002-2003) and Gehrke and Turban (1999) measured website effectiveness and also considered it as an important dependent variable for eCRM. Various studies applied customer satisfaction as a dependent variable that affects eCRM (Cho and Ha, 2004a). A suggested eCRM model by Lee, Kim and Moon (2000) applied customer loyalty as a dependent variable. The majority of studies examined website effectiveness including page loading speed, navigation efficiency (Gehrke and Turban, 1999), information quality (Cho and Ha, 2004a; Kim and Moon, 2000; Schubert, 2002-2003), product expectation (Cho, Im, Hiltz, and Fjermestad, 2001a and 2002; Lowengart and Tractinsky, 2001), brand familiarity (Cho and Ha, 2004a and b), and trust (Kimery and McCord, 2002; Kim and Moon, 2000). While there are many studies on CRM measured customer satisfaction, not many studies (Cho, Im, Hiltz, and Fjermestad, 2001a, 2002, and 2003) measured customer complaints or dissatisfaction as a dependent variable.

VI.             CONSEQUENCES OF CUSTOMER SATISFACTION/DISSATISFACTION

Traditional marketers (e.g., Oliver, 1980; Fornell, 1992) postulate that satisfaction subsequently influences complaining (or complementing) behavior as well as customer loyalty (Figure 1). A study by Cho, Im, Hiltz, and Fjermestad (2002) introduced components for the eCRM framework, such as maximizing customer satisfaction, minimizing customer dissatisfaction, resolving customer complaints, and improving product quality/customer service (Figure 2). This study posits that improving customer loyalty and minimizing customer complaints are major factors to increase/decrease customer satisfaction/dissatisfaction.

<<Figure 2>>

Customer Loyalty as a Consequence of Customer Satisfaction

Traditional researchers (e.g., Clark, Kaminski, and Rink, 1992) have addressed that brand switching as a result of dissatisfaction represents lost future sales to the customer, with losses potentially large if dissatisfaction is widespread, the product is frequently purchased, or is a large-ticket item. Customer loyalty is also the additional consideration of proxy for customer satisfaction. It is defined as a combination of both commitment to the relationship and other overt loyalty behaviors (Bhote, 1996).

With the development of e-businesses, “e-loyalty” has been receiving more attention recently. According to Reichheld and Schefer (2000), the Internet is a potentially powerful tool for strengthening relationships between firms and their customers. Various researchers found that the Web is actually a very sticky space in both the business-to-consumer and the business-to-business spheres (Reichheld and Schefer, 2000). Researchers also argue that the Web is the medium with high interactivity (Hoffman, Novak, and Chatterjee, 1995). A study by Reichheld and Schefer (2000) also argued that today’s online customers exhibit a clear proclivity toward loyalty, which can be reinforced by the proper use of Web technology. A traditional marketing study by Gardial, Clemons, and Woodruff, Schumann, and Burns (1994) stated that establishing effective relationships results in greater customer loyalty and improved data on customer usage.

Various researchers have suggested factors that affect online customer loyalty. eCRM Researchers (e.g., Lee, Kim, and Moon, 2000) suggest that managing communication between buyers and sellers is a means to maintain customer loyalty and increase retention rate. Studies by Cho, Im, Hiltz, and Fjermestad (2001a) and Levesque and McDougall (1996) encourage the use of complaints to improve communication channels between buyers and sellers in general, and as a specific means of turning dissatisfied customers into loyal repeat customers. A study by Figuiredo (2000) states that creating virtual communities are a strategy that attracts repeat purchasers and engenders repeat visits. Figuiredo (2000) also suggests that customer loyalty programs, such as frequent-flier miles are sufficient to foster consumer loyalty in the online environment. The importance of customization has been stated by Schafer, Konstan, and Riedl (1999) by addressing the role of a recommender system. According to Schafer, Konstan, and Riedl (1999), recommender systems are a key way to automate mass customization for E-commerce sites and to maintain the long-term vale of the customer of websites. Reichheld and Schefer (2000) also posit that the Internet offers companies unprecedented opportunities for getting to know their customers in depth and for customizing offerings to meet their preferences.

Managing Customer Complaints as a Consequence of Customer Dissatisfaction

In traditional markets, customer complaints are considered an important source of information (Tse and Wilton, 1988). Since complaint management is recognized as being central to customer satisfaction, any measure of complaint behavior should consider the degree and quality of the underlying customer satisfaction (Cho, Im, Hiltz, and Fjermestad, 2001b and 2003). Research by Singh and Wilkes (1996) has shown that effectively handling customer complaints has a dramatic impact on customer retention and loyalty. Although e-marketers or e-researchers have addressed the importance of customer satisfaction and customer retention, the issues of customer dissatisfaction and complaints in the Web environment have rarely been investigated. Few studies have examined factors affecting online customer complaints. According toClark, Kaminski, and Rink (1992) stated that defensive marketing is how to retain dissatisfied customers and argued that it has been neglected as an area of marketing study.

Both traditional and eCRM studies have examined factors affect customer complaints. Previous studies of customer complaining behavior have provided insights to businesses regarding which changes should be made to remedy customer problems or restitute purchase or usage-related problems (Yi, 1990). Researchers have frequently investigated that customer complaints are affected by individual customer characteristics, customer’s perceptions of the sources of their dissatisfaction, outcome expectancies, product type, and the costs associated with complaining (Yi, 1990; Singh and Howell, 1985). A study by Keaveney (1995) identified causal factors that trigger dissatisfaction, including pricing, inconvenience, core service failures, service encounter failures, employee responses to service failure, and ethical problems.

However, few researchers have addressed the issues of online customer complaints. Studies by Cho, Im, Hiltz, and Fjermestad (2001a, 2001b, and 2003) proposed the model of online customer complaining behavior, which has been developed from previous models by Bearden, Crockett, and Graham (1979), Landon (1977), Richins (1982), and Schubert and Selz (1999). Studies by Cho, Im, Hiltz, and Fjermestad (2001a and b) also investigated such technology factors as system performance, Web assessment factors, and other media characteristics as a primary cause of customer complaint behavior. Web assessment factors (Schubert, 2002-3), include information, agreement, and settlement components all of which can be used to evaluate online customer complaints and to measure the effectiveness of electronic commerce sites that transcend traditional marketing paradigms. Another study by Cho, Im, Hiltz, and Fjermestad (2002) found several factors that affect customer complaints and suggest effective ways of handling customer complaints, particularly with different product types. A study by Cho, Im, Hiltz, and Fjermestad (2003) measured the impact of factors such as the degree of dissatisfaction, ego involvement, perceived price, and information search effort to propensity to complain.

A study by Kelly and Davis (1994) has been addressed the importance of the effective complaint management that has a dramatic impact on customer retention, deflects potential word-of-mouth damage, and improves profitability. Several researchers have stated the importance of complaint management for eCRM. In the early days of e-commerce, Barbara (1985) suggested looking at complaint management as an important aspect of online strategic marketing one that has such potential benefits as maximizing customer satisfaction and loyalty, creating favorable publicity, and reducing the overall number of complaints. Sterne (1996) cites www.burke.com as an example of an online business that is considered a leader in e-CRM and improved relationships with online customers. Cho, Im, Hiltz, and Fjermestad (2001b) stated that complaint management is recognized as being central to customer satisfaction and any measure of complaint behavior should consider the degree and quality of the underlying customer satisfaction. Cho, Im, Hiltz, and Fjermestad (2001b) posits that online customer complaints show how e-businesses handle customer complaints – a reflection of how much they value their customers. A study by Edvardsson and Roos (2004) also noted the impact of customers’ complaint and switching behavior on building long-term and profitable relationships.

A study by Wang and Day (2001) described how online service quality is generated from feedback mechanisms that serve as intermediaries for Web-based information markets in other words, how online product or service quality is used to evaluate online businesses. For example, customers can use online feedback systems to share their evaluations of product/service quality, including online transactions. In their most simple form, these systems result in increased sales when product or service quality is reported as satisfactory or better, and decreased sales when customer complaints persist. Cho, Im, Hiltz, and Fjermestad (2002) also stated that online customer complaints, as a Web-enabled market feedback, have illuminated the origins and causes of online customer dissatisfaction. The qualitative components of this study focus on customer complaints gathered from public/non-profit feedback websites and online customer service centers. This study also found that major online customer complaints and dissatisfaction have been generated from the problems with Web customer service centers. This result provides implications for how e-businesses’ customer service centers should manage customer complaints effectively. The lack of research on online customer complaint management is surprising in light of the identification of this topic as a key eCRM issue by several leading e-businesses, including The Institute of International Research (http://www.iir-ny.com).

Based on the review of studies, addressed the importance of online customer complaints, this study readdressed that the proper management of online complaints has a direct effect on customer retention. Complaint management refers to the strategies used to resolve disputes and to improve ineffective products or services in order to establish a firm’s reliability in the eyes of customers (Tax, Brown and Chandrashekaran, 1998). Complaint data has been a key component in the process of problem correction and increased performance (Tax, Brown and Chandrashekaran, 1998). It is believed that successful management of customer complaints will contribute to improved eCRM by emphasizing its value to e-businesses – that is, how complaint management can affect customer retention and profitability.

1.      VII.                Conclusion

In an effort to provide a positive contrast for the new against the old, this paper addressed the issue of customer satisfaction and dissatisfaction as being at the center of successful e- business exchanges. Further, the author stressed the importance of customer loyalty and complaints as consequences of customer satisfaction and dissatisfaction. The author reviewed theories and models that have been applied by e-commerce customer relationship management. Theories applied to eCRM have been rooted in satisfaction/dissatisfaction theories and theories for customer complaining behavior that have been proposed by traditional marketers. This study also investigated models for customer satisfaction and complaining behavior that examine factors affecting customer relationship management.

This paper focuses on the how to maximize/minimize customer satisfaction/dissatisfaction for successful eCRM because it provides clues as to what managerial changes might have induced different and more desirable behaviors, raising the issue of customer loyalty myopia. This myopia stems from believing that consumer behavior can be created and sustained in and by itself without careful regard to its underlying basis on the customer satisfaction side, reviving the long-standing marketing dilemma of attitude and behavioral measures, and how much attitudes influence or predict behavior. This study also examined studies that addressed the importance of customer complaints that also go beyond the customer satisfaction concept and much more deeply into the underlying theories and models that attempt to explain why people may or may not be satisfied. This study suggested the ways to maximize/minimize customer satisfaction/dissatisfaction, such as improving customer loyalty and resolving customer complaints.

This study provides implications for both academics and practitioners. Future study will be needed to investigate mode of online customer satisfaction that are proposed by Fournier and Mick (1999), including satisfaction-as-contentment, satisfaction-as-pleasure, and dissatisfaction-as-surprise. Future research exploring consumer satisfaction of pure-play vs. multi-channel is also likely to be fruitful.  Other issues that increase the level of relationship between or within online customers and businesses will also be a future research.

Based on the review, this study found that little attention has been paid in issues of customer dissatisfaction and complaints in the online environment. This study found opportunities to measure online customer dissatisfaction and complaints both qualitatively and quantitatively. This study also recommended that e-businesses develop a defensive marketing strategy and complaint management as an excellent competitive tool for Customer Relationship Management (Cho, Im, Hiltz, and Fjermestad, 2002). Taking complaint management seriously affects such factors as product/service quality, website design, and optional policies. The author believes that managing customer dissatisfaction and complaints facilitate repeat business and customer loyalty. Efforts toward the effective resolution of customer problems serve as the basis for long-term product and successful eCRM.

Reference

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