OPERATIONS ECONOMICS: Topics in service management MECS 470

Journal of Service Research, 2003

Service managers face the problem of simultaneously developing and implementing both capacity and demand management strategies. Often they must choose between marketing options, for shifting or increasing demand, or operations management options such as adding additional capacity via more equipment or employees. The interaction of these two functional area strategies can have surprising, unintended, and often detrimental outcomes from a profit perspective. This article looks at the outcomes of various combinations of these decisions in a service network, a service with multiple activities within one site. We develop and apply an integrative model for determining the profit-maximizing capacity management strategy for a service network. We implement the model by combining a conjoint analysis-based optimal product design model from marketing with a simulation model investigating capacity and demand management strategies from operations management. We tested the model using data from an actual service network, a ski resort. Our results indicated that queue information signage was the most effective strategy for improving profitability. We also found that a decision that management believed would increase revenues-changing the customer class mix-actually decreased profitability substantially.

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European Journal of Operational Research, 2017

Most research in queuing has focused on the optimisation of performance and equilibrium analysis, with little attention to the understanding of how managers actually make decisions. In this paper, we use an experimental setup to investigate the decision-making process in a queuing capacity expansion problem, in the presence of capacity adjustment delays. The experiment represents a queuing system with one facility and virtual customers who decide whether or not to patronise the facility. Subjects play the role of facility managers who adjust the facility's service capacity to maximise profits. We analyse the actions of the manager to provide new insights into how their behaviour affects the evolution and success of the service system. Our results identify three types of managers: incremental, lumpy and reactive investors, and indicate that these groups use different decision rules. The first group achieved the best performance, and the last group the worst. While managers' decisions are influenced by the backlog of work and the available service capacity, they do not correctly account for their past, but not-yet-implemented, decisions.

Insights into Economics and Management vol 10, 2021

In this paper we present an optimization approach to assessing the performance of service organizations from an Efficiency Analysis standpoint. In what concerns the empirical illustration, even though the paper employs data from a sample of Decision Making Units (DMUs) pertaining to a public system of academic libraries, there is no loss of generality if and when other kinds of organizations are considered. Summing up, our approach combines in a simple way efficiency scores computed from the estimation of selected Data Envelopment Analysis (DEA) models and a long run evaluation provided by Markovian analysis. The Markovian approach provides better knowledge concerning the time delay required for efficiency to be attained for the first time when a prescribed operation plan happens to be adopted. The text is organized in five sections that include this introduction. The second section brings together some background ideas and results that helped found the paper. In the next section the methodological procedure is explained, followed by empirical findings in the fourth section. Conclusions, limitations and pending issues are presented to close the text.

Decision Sciences, 2005

ABSTRACTService guarantees consist of a promise to a customer (marketing), the delivery of a service to the customer (operations), and actions to appease the customer when service failures happen (recovery). A part of recovery involves offering the customer an economic and/or noneconomic payout when things go wrong. When the economic payout is too high or low, the impact on the organization and the customer is usually negative. Therefore, determining the size of the economic payout is of critical strategic and tactical importance in businesses. Yet, no systematic quantitative methods are found in the literature to help managers determine the economic payout for service failures. The current ways an economic payout is determined are management judgment, the consensus of customer focus groups, competitive benchmarking, and the use of simple expected value methods. In this article, we define the Economic Payout Model for Service Guarantees (EPMSG) that provides an optimal service guara...

International Journal of Services Technology and Management, 2004

Abstraet: This study has a twofold objectivc. First, we attempt to promotc an understanding of the relationship betwecn the dcsign of Service Opcrations Stratcgics and their implementation, as they are driven by the eustomisation efforts. Seeond, we study the extent to which such service orientation may have t\\"o difIerent forms, depending upon whether a company focuses on services that may have long-term or short-term efIects on the customer nature. Consequently, a eompany aiming at raising its quality levels, and therefore its performance, should design and implement its Service Operations Strategy, mirroring the scrvicc oricntation of the firm. \Ve suggest four dimensions (Time, Spacc, Scale and Scope), whieh contribute towards explaining the two mcntioned approaches. This may address the proecss of implernentation of the Serviee Operations Strategy. Keywords: service operations; opcralions stralegy; nc\\' scrvice development proccss; markeling/operations interface; service-positioning matrix; customisalion; service quality.

In this paper we present an optimization approach to assessing the performance of service organizations from an Efficiency Analysis standpoint. In what concerns the empirical illustration, even though the paper employs data from a sample of Decision Making Units (DMUs) pertaining to a public system of academic libraries, there is no loss of generality if and when other kinds of organizations are considered. Our approach combines in a simple way efficiency scores computed from the estimation of selected Data Envelopment Analysis (DEA) models and a long run evaluation provided by Markovian analysis. DEA models allow to consider several inputs and outputs estimated by different units of measurement and hence eliminate the need to define or redefine either resource or performance “indicators” of any type such as can be frequently found in the literature. To the best of our knowledge, the combination proposed here – i. e., a combination of DEA and Markovian Analysis – cannot be found in ...

Systems Research and Behavioral Science, 2013

Table 4 Research topics in information transmitting and communication industries Categories Detailed information Broadcasting OR in Business Commercial scheduling on TV broadcasting (Bollapragada and Garbiras,

Journal of Operations and Supply Chain Management, 2013

The goal of this article is to join the theoretical contributions of operations management and economical theory for the analysis of services' strategic positioning. In the beginning it presents the explanation about three services taxonomies with similar conceptual formation; these taxonomies are centered in the process perspective and the goal is to develop their contributions for the service strategic analysis. On one hand, it shows the operations vision in relationship to the client contact, the process standardization and the production capacity. On the other hand, it shows the economic vision and it takes into consideration three perspectives: i) the main process involved, if concentrated on people, physical goods, or information; ii) the relationship with the client and the grade of standardization and professional capacity; iii) the degree of capital intensity and scale. As a result, it proposes an integration matrix based on three variables: capital intensity, scale and client's contact.