An Empirical Investigation of the Relationships among Climate, Capabilities, and Unit Performance

For the current study, the authors examined the relationships among two dimensions of organizational climate and several indices of individual- and unit-level effectiveness. Specifically, the article proposes that an organization ’s service and training climate would be related to employee capabilities—operationalized in terms of frontline service capabilities and managerial support capabilities—and that such capabilities would be related to unit- level measures of employee turnover and sales growth. Using survey and operational data from 201 management and frontline staff members in 22 units of a national restaurant chain, the results from correlation and regression analyses generally supported the proposed relationships. This study replicates and extends previous research and provides a foundation for future conceptual development and empirical work in this research area.

Accounting for the Multi-Period Impact of Service When Determining Employee Requirements for Labor Scheduling

Providing good customer service, inexpensively, is a problem commonly faced by managers of service operations. To tackle this problem, managers must do four tasks: forecast customer demand for the service; translate these forecasts into employee requirements; develop a labor schedule that provides appropriate numbers of employees at appropriate times; and control the delivery of the service in real-time. This paper focuses upon the translation of forecasts of customer demand into employee requirements. Specifically, it presents and evaluates two methods for determining desired staffing levels. One of these methods is a traditional approach to the task, while the other, by using modified customer arrival rates, offers a better means of accounting for the multi-period impact of customer service. To calculate the modified arrival rates, the latter method reduces (increases) the actual customer arrival rate for a period to account for customers who arrived in the period (in earlier periods) but have some of their service performed in subsequent periods (in the period). In an experiment simulating 13824 service delivery environments, the new method demonstrated its superiority by serving 2.74% more customers within the specified waiting time limit while using 7.57% fewer labor hours.