Article ID: | iaor200938045 |
Country: | United Kingdom |
Volume: | 8 |
Issue: | 234 |
Start Page Number: | 290 |
End Page Number: | 317 |
Publication Date: | Mar 2007 |
Journal: | International Journal of Management and Decision Making |
Authors: | Shankar K R Ravi, Vijayaraghavan P, Narendran T T |
Keywords: | artificial intelligence: decision support, queues: applications |
Product support offers competitive differentiation for high‐tech products in developing markets like India. Highly fluctuating numbers of daily customer field‐service requests mandate ‘optimal field staffing decision’. Despite an operational decision, it assumes strategic significance influencing long run customer service level. Companies decide on the field staff strength (fixed and outsourced) to comply with the fluctuating field service demand. This study models a real‐time customer support system featuring restricted daily working hours and decision making epochs. The study assesses the daily field service demand based on the cumulative sales developing a methodology. The study uses stochastic principles to derive mathematical expressions for average customer waiting time and cost of customer service in a service system with decision‐making epochs. Real time data that validate the model show that customer waiting time minimises with increased number of decision epochs without affecting the cost of service.