Unlocking supply chain disruption risk within the Thai beverage industry

نویسندگان

  • Ying Kei Tse
  • Rupert L. Matthews
  • Kim Hua Tan
  • Yuji Sato
  • Chaipong Pongpanich
چکیده

Purpose: A growing need for global sourcing of business has subjected firms to higher levels of uncertainty and increased risk of supply disruption. Differences in industry and infrastructure make it more difficult for firms to manage supply disruption risks effectively. This study aims to extend developing research in this area by addressing gaps within existing literature related to environmental turbulence and uncertainties. Design/Methodology/Approach: We test our model using data collected from 253 senior managers and directors in the Thai beverage industry using advanced statistical techniques to explore the relationship between representations of supply disruption risk and uncertainty. Findings: The results show that both magnitude and probability of risk impact on the disruption risk, but the probability of loss is a dominant determinant. We also find that demand uncertainty and quality uncertainty affect the risk perception of purchasing managers, and are related to the magnitude of disruption risk, rather than the frequency of occurrence. Interestingly, our results show that quality uncertainty negatively impacts on the severity of disruption risk. Research limitations/ implication: The construct validity of demand uncertainty was under the required threshold, intimating the need for further construct development. Practical Implications: The framework provides managers with direction on how to formulate and target their disruption risk management strategies. The work also allows practitioners to critically reflect on implicit risk management strategies they may already employ and their effectiveness. Originality/Value: The paper identifies key antecedents of supply disruption risk and tests them within a novel industrial context of the beverage industry and a novel national context of Thailand.

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عنوان ژورنال:
  • Industrial Management and Data Systems

دوره 116  شماره 

صفحات  -

تاریخ انتشار 2016