Customer
satisfaction is a key and valued outcome of good marketing practice. According
to Drucker (1954), the principle purpose of a business is to create satisfied
customers. Increasing customer satisfaction has been found to lead to higher
future profitability (Anderson, Fornell, and Lehmann 1994), lower costs related
to defective goods and services (Anderson, Fornell, and Rust 1997), increased
buyer willingness to pay price premiums, provide referrals, and use more of the
product (Reichheld 1996; Anderson and Mittal 2000), and higher levels of
customer retention and loyalty (Fornell 1992; Anderson and Sullivan 1993;
Bolton 1998). Increasing loyalty, in turn, has been found to lead to increases
in future revenue (Fornell 1992; Anderson, Fornell, and Lehmann 1994) and
reductions in the cost of future transactions (Reichheld 1996; Srivastava,
Shervani, and Fahey 1998). All of this empirical evidence suggests that
customer satisfaction is valuable from both a customer goodwill perspective and
an organization’s financial perspective.
A firm’s
future profitability depends on satisfying customers in the present – retained
customers should be viewed as revenue producing assets for the firm (Anderson
and Sullivan 1993; Reichheld 1996; Anderson and Mittal 2000). Empirical studies
have found evidence that improved customer satisfaction need not entail higher
costs, in fact, improved customer satisfaction may lower costs due to a
reduction in defective goods, product re-work, etc. (Fornell 1992; Anderson,
Fornell, and Rust 1997). However, the key to building long-term customer satisfaction
and retention and reaping the benefits these efforts can offer is to focus on
the development of high quality products and services. Customer satisfaction
and retention that are bought through price promotions, rebates, switching
barriers, and other such means are unlikely to have the same long-run impact on
profitability as when such attitudes and behaviors are won
through
superior products and services (Anderson and Mittal 2000). Thus, squeezing
additional reliability out of a manufacturing or service delivery process may
not increase perceived quality and customer satisfaction as much as tailoring
goods and services to meet customer needs (Fornell, Johnson, Anderson, Cha, and
Everitt 1996).While it seems clear that increasing customer satisfaction is
beneficial to a marketing manager, how to measure it is less clear. Customer
satisfaction has been studied from the perspective of the individual customer
and what drives their satisfaction (Oliver and Swan 1989; Oliver 1993; Fournier
and Mick 1999) as well as from an industry-wide perspective to compare customer
satisfaction scores across firms and industries (Fornell 1992; Anderson,
Fornell, and Lehmann 1994; Fornell et al. 1996; Mittal and Kamakura 2001),
while other research has examined customer satisfaction in a single
organization (Schlesinger and Zornitsky 1991; Hallowell 1996; Loveman 1998) or
across several organizations (DeWulf, Odekerken-Schröder, and Iacobucci 2001).
In addition, specific tools for measuring customer satisfaction have been
developed in the past, including SERVQUAL (Parasuraman, Berry, and Zeithaml
1988, 1991). Thus, there exists an ample literature on which to draw when
attempting to measure customer satisfaction. In attempting to measure customer
satisfaction, it is possible that attributes can have different satisfaction
implications for different consumer and market segments – the usage context, segment
population, and market environment can influence satisfaction and product use (Anderson
and Mittal 2000). Failure to take into account segment-specific variation may
lead a firm to focus on the wrong aspect for a given set of consumers (Anderson
and Mittal 2000). Furthermore, consumers with similar satisfaction ratings, yet
different characteristics, may exhibit different levels of repurchase behavior
(Mittal and Kamakura 2001). It is clear, then, that market and consumer
segments should be important factors to consider when measuring customer
satisfaction and its implications. Garbarino and Johnson (1999) did consider
segments in the customer base in their study of satisfaction where they
analyzed the different role played by satisfaction between low relational and
high relational customers. Their study, however, involved customers from only a
single organization. Our approach extends this work by studying customers from
multiple organizations, and shares some similarities with Anderson and Sullivan
(1993) with respect to the type of analysis and sampling methods. The goals of
their research, however, were to study the antecedents and consequences of
customer satisfaction rather than investigate how different types of
satisfaction may influence the overall measure of customer satisfaction. In
addition, our theoretical approach shares some similarities to Hutchison,
Kamakura, and Lynch (2000) who posited that unobserved heterogeneity is a
problem for interpreting results from behavioral experiments. The basic point
of their argument is that aggregation may create effects that do not exist in
any segments, or may mask effects that do exist. The present study makes a
similar point
and
provides an analytical method for overcoming such a problem.
Kekre,
Krishnan, and Srinivasan (1995) examine heterogeneity of effects across
individual customers of a single company using a random effect ordered probit
model. These models are similar to the hierarchical linear models considered
here, and a single customer could be considered a subunit. Our study extends
this previous work by allowing for multiple levels of randomization. For
example, we have random samples of organizations and random samples of subunits
within the organizations. An additional extension is that we attempt to explain
the variation across subunits
