IntroductionCustomer waiting time for service typically represents the first direct interaction between customers and most service delivery processes, so the importance of properly managing waiting times is of significant interest to most service operations. In recent years, service managers have made efforts to reduce customer waiting times and, and in some cases, totally to eliminate waits by improving processes or by adopting faster service technologies.Customer reactions to waiting in line, whether they are good or bad, can color the customer's perception of the service delivery process. For example, customers in a restaurant who are unhappy about their long wait for seating may complain about the quality of the food, even if the food is totally acceptable. Chebat et al.'s (1994) study of bank customers supports this notion of a "halo effect", concluding that a customer's evaluation of service quality was affected not only by the end service received, but also by the service delivery process itself, which includes waiting time. It is therefore critical, in situations where waiting is inevitable, that service managers attempt to provide a high level of satisfaction with the waiting portion of the service experience.Previous research on customer satisfaction with respect to waiting in service operations has tended to parallel the broader research issue of customer satisfaction in services. This research can be divided into three broad areas:(1) developing a methodology for defining customer satisfaction;(2) measuring customer satisfaction; and(3) identifying the factors that affect the level of customer satisfaction. Customer satisfaction can, therefore, be conceived as one element of an overall model of customer behavior that evolves over time (Beardon and Teele, 1983;Day and Landon, 1977).

Organizational quality improvement practices have gained wide acceptance in manufacturing industries over the last several decades. A substantial number of books have been written on Lean and Six Sigma alone, which today are the leading improvement initiatives. The healthcare industry however has been slower to adopt these methods, although anecdotal evidence suggests they are now being gradually diffused throughout hospitals on an increasing basis. Yet, these new practices have been developed substantially without a theoretical foundation (Linderman et al. J Oper Manag 21:193-203, 2003) and the question of industry "fit" is the topic of debate for many physicians and administrators (Kassirer N Engl J Med 339: [1543][1544][1545] 1998). This article provides the descriptive results from our mixed methods research, combining survey questionnaire with semi-structured interviews, that examines implementation of two quality improvement initiatives (Lean and Six Sigma) in a cross-sectional sample of hospitals. We used correlations and non-parametric tests to examine relationships between goal attainment and quality management, and present descriptive findings about reported usage and adoption of quality initiatives. Importantly, we find that the efficacy of quality improvement initiatives in healthcare may be impeded by the lack of goal clarity and measurement. We build on these initial results by offering recommendations to improve results in practice, as well as an agenda for further research of quality initiatives in healthcare. The objectives of our research are to better understand how Lean and Six Sigma fit in the healthcare industry and to explore goal and value attainment from these projects.

Queuing, a familiar element of most service delivery systems, has the potential for significantly affecting the customer′s overall satisfaction with the service encounter. A customer′s degree of satisfaction with waiting or with the service received in its entirety is dependent on the actual performance of the delivery system, the customer′s expectations regarding that performance and the customer′s perception of the service encounter. The actual operational performance of different queuing configurations has been previously addressed, as have the issues of managing customers′ expectations and perceptions regarding their queuing experiences. This earlier research has identified several factors which can affect a customer′s perception of waiting and consequently his or her satisfaction with that wait. Proposes a taxonomy based on the service manager′s ability to control the customer′s perception of the queuing experience. Defines which queuing factors can be controlled by the firm, which factors can partially be controlled by the firm and which factors are outside the firm′s control, and suggests tactics for managing queues for each category of factors.

During the latter part of the 20th century, the service sector grew significantly in virtually every developed country, with the United States taking the lead. By 2000, services comprised almost 80% of U.S. employment. This rapid growth was caused by several factors including changing population lifestyles, deregulation, and new and improved infrastructure including the widespread availability of new technologies. With the service sector surpassing 50% of the U.S. economy in the 1950s, researchers -especially economists -began to examine the characteristics of services and attempt to apply some of the concepts that were developed and proven in manufacturing. From these early efforts there emerged a growing demand for business schools to develop both research agendas and courses in service operations. Beginning at the Harvard Business School in the early 1970s, and continuing through to the present, research and courses in service operations have evolved from simply applying basic manufacturing concepts in a service environment to recognizing the need for a trans-disciplinary approach appropriately suited to the particular characteristics of service operations. This article traces the evolution of service operations from its immediate prebusiness school days through its early years as an academic discipline in business schools to the present, identifying ''pioneers'' in service operations who truly blazed a previously unmarked trail that many have since followed. #

Professional service organizations are becoming an increasingly important segment of the service sector in the U.S. but little attention has been paid to the management of these organizations, particularly in relation to technical performance. This paper reports the findings of a survey of managers of Health Maintenance Organizations (HMOs) which related operations management decisions about organization, workforce management, quality management and planning and control, to clinical process and outcome performance.This research demonstrates that managerial decisions do affect clinical performance in HMOs. These findings have implications for both researchers and practitioners. For researchers, the study provides a framework for future research on the important link between management decisions and technical performance in professional service organizations. For practitioners, this study suggests that technical performance will be enhanced when professional work is appropriately managed.