An attention-based view of supply disruption risk management: balancing biased attentional processing for improved resilience in the COVID-19 context

IF 7.1 2区 管理学 Q1 MANAGEMENT International Journal of Operations & Production Management Pub Date : 2021-11-01 DOI:10.1108/ijopm-06-2021-0381
Harri Lorentz, Sini Laari, J. Meehan, Michael Eßig, M. Henke
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引用次数: 1

Abstract

PurposeIn the context of the COVID-19 pandemic, this study investigates a variety of approaches to supply disruption risk management for achieving effective responses for resilience at the supply management subunit level (e.g. category of items). Drawing on the attention-based view of the firm, the authors model the attentional antecedents of supply resilience as (1) attentional perspectives and (2) attentional selection. Attentional perspectives focus on either supply risk sources or supply network recoverability, and both are hypothesised to have a direct positive association with supply resilience. Attentional selection is top down or bottom up when it comes to disruption detection, and these are hypothesised to moderate the association between disruption risk management perspectives and resilience.Design/methodology/approachConducted at the early phases of the COVID-19 pandemic, this study employs a hierarchical regression analysis on a multicountry survey of 190 procurement professionals, each responding from the perspective of their own subunit area of supply responsibility.FindingsBoth attentional disruption risk management perspectives are needed to achieve supply resilience, and neither is superior in terms of achieving supply resilience. Both the efficiency of the top down and exposure to the unexpected with the bottom up are needed – to a balanced degree – for improved supply resilience.Practical implicationsThe results encourage firms to purposefully develop their supply risk management practices, first, to include both perspectives and, second, to avoid biases in attentional selection for disruption detection. Ensuring a more balanced approach may allow firms to improve their supply resilience.Originality/valueThe results contribute to the understanding of the microfoundations that underpin firms' operational capabilities for supply risk and disruption management and possible attentional biases.
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基于注意力的供应中断风险管理观点:平衡有偏见的注意力处理以提高COVID-19背景下的复原力
在2019冠状病毒病大流行的背景下,本研究探讨了供应中断风险管理的各种方法,以便在供应管理亚单位层面(例如,物品类别)实现有效的弹性响应。根据公司的注意基础观点,作者将供给弹性的注意前因建模为(1)注意视角和(2)注意选择。注意力视角关注供应风险源或供应网络的可恢复性,两者都被假设与供应弹性有直接的正相关。当涉及到干扰检测时,注意力选择是自上而下的或自下而上的,这些被假设为调节干扰风险管理观点与弹性之间的关联。设计/方法/方法本研究在2019冠状病毒病大流行的早期阶段进行,对190名采购专业人员进行了多国调查,每个人都从自己的供应责任亚单位领域的角度进行了回应,采用了分层回归分析。研究结果:要实现供应弹性,需要两种注意力中断风险管理观点,而在实现供应弹性方面,两种观点都不优越。为了提高供应弹性,既需要自上而下的效率,也需要自下而上的意外风险敞口——在平衡的程度上。实践启示:研究结果鼓励企业有目的地发展其供应风险管理实践,首先,包括两种观点,其次,避免在中断检测的注意选择中出现偏差。确保一个更加平衡的方法可以让公司提高他们的供应弹性。原创性/价值这些结果有助于理解支撑企业供应风险和中断管理以及可能的注意力偏差的运营能力的微观基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
13.30
自引率
17.20%
发文量
96
期刊介绍: The mission of the International Journal of Operations & Production Management (IJOPM) is to publish cutting-edge, innovative research with the potential to significantly advance the field of Operations and Supply Chain Management, both in theory and practice. Drawing on experiences from manufacturing and service sectors, in both private and public contexts, the journal has earned widespread respect in this complex and increasingly vital area of business management. Methodologically, IJOPM encompasses a broad spectrum of empirically-based inquiry using suitable research frameworks, as long as they offer generic insights of substantial value to operations and supply chain management. While the journal does not categorically exclude specific empirical methodologies, it does not accept purely mathematical modeling pieces. Regardless of the chosen mode of inquiry or methods employed, the key criteria are appropriateness of methodology, clarity in the study's execution, and rigor in the application of methods. It's important to note that any contribution should explicitly contribute to theory. The journal actively encourages the use of mixed methods where appropriate and valuable for generating research insights.
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