Impact of Motivation and Workload on Service Time Components: An Empirical Analysis of Call Center Operations

Ahmad M. Ashkanani · Benjamin B. Dunford · Kevin J. Mumford

14 citations0/0 files storedManagement Science

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Employee Performance and Motivation Job Satisfaction and Organizational Behavior Advanced Queuing Theory Analysis

Abstract

We study the joint effects of motivation and workload on human servers’ service time. Using operational and survey data from a call center with a pooled queue structure and limited financial incentives, we examine how individual differences between servers’ trait intrinsic motivation (IM) and extrinsic motivation (EM) impact their average offline, online, and total service times in response to changing workloads. We find significant differences in the patterns of workload and service time relationships across different stages of the service request between servers possessing different combinations of trait motivation. For example, servers with a combination of high IM and low EM were approximately 15% (161%) faster in processing the offline portion of service requests than their peers with the opposite combination (low and high) when workload levels were low (high), respectively. In contrast, servers with high IM-low EM were approximately 35% (5%) slower in processing the online portion of service requests than their low IM-high EM counterparts when workload levels were low (high), respectively. Our findings suggest important nuances in how servers with different trait motivation types respond to changing workload across different stages of the service request. The behavioral pattern shown by high IM-low EM servers is consistent with the preferences of productivity-seeking call center managers who favor speedup and slowdown at certain stages of the service request, conditional to workload. These findings underscore the importance of accounting for trait-based individual differences for a more complete understanding of the complex relationship between workload and service time. This paper was accepted by Charles Corbett, operations management.

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