Analyzing the effect of Supply Chain Complexity on Supply Chain performance: Perspective from Omani Industries

Today?s greater product variety, shorter product life cycle, and lower production costs are pushing companies to look beyond their own boundaries, thereby, creating complexity in the management of the supply chain. To manage complexity, it is imperative that the manager understand the associated complexity drivers within the SC network, their effect on performance measure and interaction effect of one driver over the others. Moreover, the manager should be able to devise a proper solution method or strategy to mitigate the effect of SC complexity. Recently, Piya et al. (2019) have identified twenty-three generic drivers of SC complexity. However, the interaction effect of one driver over others and their knock-on effect on the performance measures of SC is an unexplored area. Moreover, no research work in the past has developed a model to quantify the level of SC complexity based on various identified complexity drivers. To fill the gap in the research domain, this research work will focus on developing a novel mathematical model that can measure the level of SC complexity and prioritize the complexity drivers based on their knock-on effect on SC performance. The model will take into account the interaction effect of one driver over the others while measuring complexity and prioritizing the complexity driver. Further, a conceptual framework will be developed, which can act as a guideline for SC managers to identify the drivers in their SC network responsible for creating complexity, their interaction effect and effect on SC performance measures. The proposed framework will be tested and verified by implementing it in the real life industrial cases within the Sultanate of Oman.

Today?s greater product variety, shorter product life cycle, and lower production costs are pushing companies to look beyond their own boundaries, thereby, creating complexity in the management of the supply chain. To manage complexity, it is imperative that the manager understand the associated complexity drivers within the SC network, their effect on performance measure and interaction effect of one driver over the others. Moreover, the manager should be able to devise a proper solution method or strategy to mitigate the effect of SC complexity. Recently, Piya et al. (2019) have identified twenty-three generic drivers of SC complexity. However, the interaction effect of one driver over others and their knock-on effect on the performance measures of SC is an unexplored area. Moreover, no research work in the past has developed a model to quantify the level of SC complexity based on various identified complexity drivers. To fill the gap in the research domain, this research work will focus on developing a novel mathematical model that can measure the level of SC complexity and prioritize the complexity drivers based on their knock-on effect on SC performance. The model will take into account the interaction effect of one driver over the others while measuring complexity and prioritizing the complexity driver. Further, a conceptual framework will be developed, which can act as a guideline for SC managers to identify the drivers in their SC network responsible for creating complexity, their interaction effect and effect on SC performance measures. The proposed framework will be tested and verified by implementing it in the real life industrial cases within the Sultanate of Oman.