Abstract
Purpose
This paper sets out to explore whether and how the bullwhip effect, as found in product supply chains, might also manifest itself in services, as well as what policies can be successful for mitigating it.
Design/methodology/approach
A combination of analytic methods was used—inductive case analysis and analysis of data from two service supply chains in the telecom industry.
Findings Empirical evidence from two cases was examined and provides support for the presence of a service bullwhip effect. Quantitative and qualitative case data were used to explore how this effect manifests itself in services, the distinctive drivers of the bullwhip effect in services, and the managerial actions that can either trigger or mitigate these bullwhip effects. Eight propositions are developed. Three types of characteristics that potentially make the bullwhip effect worse in services than in manufacturing are identified: (1) the destabilizing effects of manual rework in otherwise automated service processes, (2) the omission of accurate and timely data on rework volumes upstream in the chain, pointing at future bullwhip effects downstream, and (3) the lack of a supply-chain mindset within the various departments jointly responsible for delivering the service, leading to longer delays in reacting to service bullwhips as they develop over time.
Originality/value
This paper explores an area that has been well researched in manufacturing, but not in services, and it contributes to both the theory and practice of service supply chains.
Research limitations
The research is based on two cases within a single industry, limiting generalizability. The propositions developed need testing in a wider set of contexts, including hybrid service and product supply chains.
Practical implications
The implications of this research can help organizations prevent or reduce the negative impact of planned and unplanned fluctuations in their service supply chains.
This paper sets out to explore whether and how the bullwhip effect, as found in product supply chains, might also manifest itself in services, as well as what policies can be successful for mitigating it.
Design/methodology/approach
A combination of analytic methods was used—inductive case analysis and analysis of data from two service supply chains in the telecom industry.
Findings Empirical evidence from two cases was examined and provides support for the presence of a service bullwhip effect. Quantitative and qualitative case data were used to explore how this effect manifests itself in services, the distinctive drivers of the bullwhip effect in services, and the managerial actions that can either trigger or mitigate these bullwhip effects. Eight propositions are developed. Three types of characteristics that potentially make the bullwhip effect worse in services than in manufacturing are identified: (1) the destabilizing effects of manual rework in otherwise automated service processes, (2) the omission of accurate and timely data on rework volumes upstream in the chain, pointing at future bullwhip effects downstream, and (3) the lack of a supply-chain mindset within the various departments jointly responsible for delivering the service, leading to longer delays in reacting to service bullwhips as they develop over time.
Originality/value
This paper explores an area that has been well researched in manufacturing, but not in services, and it contributes to both the theory and practice of service supply chains.
Research limitations
The research is based on two cases within a single industry, limiting generalizability. The propositions developed need testing in a wider set of contexts, including hybrid service and product supply chains.
Practical implications
The implications of this research can help organizations prevent or reduce the negative impact of planned and unplanned fluctuations in their service supply chains.
| Original language | English |
|---|---|
| Pages (from-to) | 765-788 |
| Journal | International Journal of Operations & Production Management |
| Volume | 33 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2013 |