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Title: Towards more effective service management decision making: design and application of an optimization model in a frontline employee management context
Authors: STREUKENS, Sandra 
de Ruyter, Ko
van Hoesel, Stan
de Jong, Ad
Issue Date: 2010
Source: DECISION SCIENCES, under review
Abstract: Despite the awareness that effective management of the climate in which service employees operate is a necessary condition for the development of favorable customer service evaluations and the generation of service revenues, little research exists that includes this knowledge in decision making models. By combining existing knowledge on service management with mathematical rigor, this study develops and empirically assesses a general applicable decision making approach that allows for an explicit evaluation and optimization of service profitability in an economically justified and service oriented manner. Service management theory is summarized in a behavioral model capturing the chain of effects among employee perceptions, customer evaluations, and service revenues. Subsequently, this behavioral model is integrated in a mathematical optimization framework. The decision making value of our approach lies in the explicit assessment of the following three issues: (i) evaluation and optimization of the profitability stemming from service investment strategies, (ii) the allocation of investment efforts to optimize financial performance, (iii) the robustness of the proposed solution to assess the impact of uncertainty in decision making. Besides offering a first in-depth treatment of profit optimization in service management, an additional contribution of our work lies in the fact that our study offers one of the few attempts to model the entire chain of effects between employee perceptions, customer evaluative judgments, and financial performance.
Notes: Under review at Decision Sciences (invited for review)
Keywords: : Services Management, Customer Service, Management Decision Making. Hierarchical Linear Modeling, Structural Equation Modeling, Dynamic Programming
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ISSN: 0011-7315
e-ISSN: 1540-5915
Category: O
Type: Preprint
Appears in Collections:Research publications

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