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.
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