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电子商务环境下企业顾客忠诚度的影响因素研究——以凡客诚品为例外文及翻译.doc
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电子商务环境下企业顾客忠诚度的影响因素研究——以凡客诚品为例外文及翻译.doc
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外文翻译之一
Satisfaction Strength and Customer Loyalty
作者: Murali Chandrashekaran /Kristin Rotte/ Stephen S. Tax/ Rajdeep Grewa
国籍:Australia
出处:Journal Of Marketing Research ,2006,5(9):1784-1789
原文正文:
Abstract
Although empirical research indicates that satisfaction is intimately linked to
loyalty, anecdotal evidence reveals that many customers who state that they
are very satisfied with a service provider nevertheless subsequently defect.. In
this paper, the authors focus on identifying which customers are vulnerable to
defection despite stating high levels of satisfaction. Drawing on the emerging
perspective to modeling individual judgments that recognizes that individuals
differ in the strength (i.e., conviction, certainty) with which judgments are
professed, the authors first decompose a customer’s stated satisfaction into
two related but independent facets – satisfaction level and satisfaction strength
The authors then examine the role of satisfaction strength in the translation of
satisfaction to loyalty. Results from two studies are reported. In the first study,
set in a B2B service context, the authors analyze data obtained from an
ongoing customer satisfaction tracking study being conducted by a large
service organization in the US. Data from over 25,000 customers are used to
calibrate the satisfaction model and examine the effect of satisfaction strength
on the translation of satisfaction to loyalty. In the second study, a conceptual
replication set in a B2C context, the authors examine decision-making
following a failed service encounter and a recovery attempt by the service
provider. The authors study the impact of perceptions of service recovery on
the level and strength of the stated satisfaction with the service recovery, and
then focus on the effect of satisfaction strength in the translation of stated
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satisfaction to loyalty. The two studies strongly demonstrate that the covert
satisfaction strength plays a central role in the translation of satisfaction to
loyalty. A key finding that is uncovered, and replicated, in this research is that
while satisfaction does indeed translate to loyalty when the satisfaction
judgment is strongly-held (i.e., with low uncertainty), the translation is
significantly lowered, on average, by almost 60%, when the same stated
satisfaction is more weakly-held (i.e., fraught with uncertainty). The studies
also indicate that aspects of prior relational experience (length of relationship,
volume of business, and favorability of prior experiences) serve to isolate,
rather than insulate, a firm’s customers, resulting in even greater vulnerability
Overall, the findings contribute to a better understanding of the process by
which satisfaction leads to customer loyalty
Research Framework
We build on the extant satisfaction and judgment formation literatures to
recognize that a customer’s overtly stated satisfaction is comprised of two
related but distinct dimensions – the level of satisfaction and the covert
strength with which that satisfaction judgment is held. Several lines of thought
support this two-dimensional conceptualization of revealed satisfaction. For
instance,scholars in the area of services marketing note that customer
expectations are often fuzzy (e.g., Rustet al 1999), and it is often difficult for
customers to precisely estimate the level of received service (Parasuraman,
Zeithaml and Berry 1985). Thus, it is likely that the resulting satisfaction
judgments themselves are laden with uncertainty. Consequently, customers
are likely to differ in the strength with which they hold their satisfaction. This is
also consistent with the psychological view of human judgments succinctly
expressed by Koehler (1994, p. 461): “Although we believe a great many
things, we hold some of our beliefs with greater conviction than others.”
Satisfaction model
Letting SATi denote the stated satisfaction of the its customer, we recognize
that SATi is a realization from a distribution of possible judgments, such that SLi,
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