Paper Type
Completed Research Paper
Abstract
Capacity planning is a major challenge for service providers facing volatile demand. Inefficiencies result from idle capacity or lost revenue caused by peak loads. Concerning IT-driven services, recent technological developments offering dynamic integration and information capabilities may help. They enable an on-demand exchange of excess capacity between business partners and create value through efficient capacity allocation within a supply chain. This paper aims at examining this economic potential of IT-enabled excess capacity markets. Therefore, we use the model setting of a three-stage IT-driven service supply chain and discuss different factors influencing the capacity optimization problem. With a discrete-event simulation we then evaluate a representative factor quantitatively. Thus, we provide deeper insights about the usefulness of excess capacity markets for capacity optimization in different settings and scenarios. The results serve as a guide for practitioners, build the basis for further quantitative evaluation and represent a starting point for empirical validation.
Recommended Citation
Dorsch, Christoph, "IT-enabled Excess Capacity Markets for Services: Examining the Economic Potential in Cost-driven Service Supply Chains" (2013). AMCIS 2013 Proceedings. 15.
https://aisel.aisnet.org/amcis2013/eBusinessIntelligence/GeneralPresentations/15
IT-enabled Excess Capacity Markets for Services: Examining the Economic Potential in Cost-driven Service Supply Chains
Capacity planning is a major challenge for service providers facing volatile demand. Inefficiencies result from idle capacity or lost revenue caused by peak loads. Concerning IT-driven services, recent technological developments offering dynamic integration and information capabilities may help. They enable an on-demand exchange of excess capacity between business partners and create value through efficient capacity allocation within a supply chain. This paper aims at examining this economic potential of IT-enabled excess capacity markets. Therefore, we use the model setting of a three-stage IT-driven service supply chain and discuss different factors influencing the capacity optimization problem. With a discrete-event simulation we then evaluate a representative factor quantitatively. Thus, we provide deeper insights about the usefulness of excess capacity markets for capacity optimization in different settings and scenarios. The results serve as a guide for practitioners, build the basis for further quantitative evaluation and represent a starting point for empirical validation.