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Journal ArticleDOI

Assessing the Service-Profit Chain

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TLDR
In this article, the authors used customer surveys from more than 500 branches of a bank in Brazil to model the service-profit chain (SPC) at a strategic and operational level, where the strategic model provides the key relationships and metrics that are needed to ensure that all subunits of the firm follow a consistent strategy.
Abstract
The service-profit chain (SPC) is a framework for linking service operations, employee assessments, and customer assessments to a firm's profitability (Heskett et al. 1994). The SPC provides an integrative framework for understanding how a firm's operational investments into service operations are related to customer perceptions and behaviors, and how these translate into profits. For a firm, it provides much needed guidance about the complex interrelationships among operational investments, customer perceptions, and the bottom line.Implementing the SPC is a pervasive problem among most service firms, and several attempts have been made to model various aspects of the SPC. However, comprehensive approaches to model the SPC are lacking, as most studies have only focused on discrete aspects of the SPC. There is a need for approaches that combine data such as measures of operational inputs, customer perceptions and behaviors, and financial outcomes from multiple sources, providing the firm with not only comprehensive diagnosis and assessment but also with implementation guidelines. Importantly, an approach that is sensitive to and can accommodate the strengths and weaknesses of such data sets is required. We outline and illustrate such an approach in this paper. Our approach has the potential to both identify and quantify the benefits of implementing a service strategy, especially for firms having multiple units (e.g., banks with branches, retail outlets, and so forth).The implementation approach is illustrated using data from a national bank in Brazil. We used customer surveys from more than 500 branches of the bank. Each individual customer's marketing survey data was linked to a number of operational metrics. First, behavioral measures of retention, such as the length of the customer's relation with the bank, the deposit amount, and number of transactions with the bank, were obtained and merged with the survey data. Second, the main branch used by each customer was identified and operational inputs (e.g., number of employees, number of available automated teller machines (ATMs)) used at that branch were obtained and merged with the data set. This data set was used to model the SPC at astrategic andoperational level.Thestrategic analysis consisted of a structural-equation model that identified the critical conceptual relationships that parsimoniously articulate the SPC for this bank. For instance, from among a variety of attribute-level perceptions, the bank was able to identify those perceptions that were critical determinants of behavioral intentions. Similarly, from a variety of available behavioral metrics, the bank was able to identify those behaviors most relevant to profitability. Theoperational analysis utilized Data Envelopment Analysis (DEA) and provides customized feedback to each branch in implementing the strategic model. It provides each branch with a metric of its relative efficiency in translating inputs such as employees and ATMs into relevant strategic outcomes such as customer intentions and behaviors. Our illustration shows how top management can use the strategic and operational analysis in tandem. Whereas the strategic model provides the key relationships and metrics that are needed to ensure that all subunits of the firm follow a consistent strategy, the operational analysis enables each branch to benchmark its unique position so that the branch can implement the strategic model in the most efficient way. Thus,simultaneously implementing the strategic and operational model enables a firm to have a centralized focus with decentralized implementation. For this bank, the operational analysis shows that for a branch to achieve superior profitability, it is important that the branch manager not only be efficient in achieving superior satisfaction (as indicated in positive behavioral intentions) but also be efficient in translating such attitudes and intentions into relevant behaviors. In other words, superior satisfaction alone is not an unconditional guarantee of profitability.

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References
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Journal ArticleDOI

Structural equation modeling in practice: a review and recommended two-step approach

TL;DR: In this paper, the authors provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development, and present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests.
Journal Article

SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality.

TL;DR: In this paper, the authors describe the development of a 22-item instrument (called SERVQUAL) for assessing customer perceptions of service quality in service and retailing organizations, and the procedures used in constructing and refining a multiple-item scale to measure the construct are described.
Journal Article

Putting the Service-Profit Chain to Work

TL;DR: The service-profit chain puts hard values on soft measures, helping managers quantify their investments in people and then integrate those measures into a comprehensive service picture as discussed by the authors, which can be used to evaluate the performance of service organizations.
Book

"Data Envelopment Analysis: Theory, Methodology, and Applications"

TL;DR: In this article, the authors present DEA Software Packages for the U.S. Airline Industry and present a Spatial Efficiency Framework for the Support of Locational Decision (SELF).
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A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction

TL;DR: In this paper, the authors developed and estimated a dynamic model of the duration of the provider-customer relationship that focuses on the role of customer satisfaction, and the model is estimated as a left-truncated, proportional hazards regression with cross-sectional and time series data describing cellular customers perceptions and behavior over a 22-month period.
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