Search results

The goal of the paper is twofold. First, it aims to empirically conceptualize whether a wide array of fragmented demand planning activities, performed in supply chains, can be logically categorized into actionable sets of practices, which then form a broader conceptualization of the demand planning process. Second, regarding certain contextual factors, our research seeks to investigate the contribution of demand planning, as a higher-order construct, to mitigating disruptions induced by operational risks in supply chains.

In this study, PLS-SEM was used to estimate the reflective-formative nature of the model. The results of PLS-SEM were additionally complemented by the assessment of the predictive power of our model. Finally, to reveal possible contingency effects, the multigroup analysis (MGA) was conducted.

The study suggests that demand planning process (DPP) is a second-order construct that is composed of four sets of practices, including goal setting, data gathering, demand forecasting, communicating the demand predictions and synchronizing supply with demand. The study also reveals that the demand planning practices, only when considered together, as a higher-order factor, significantly contribute to mitigating disruptions driven by operational risks. Finally, the research shows that the strength of the impact of demand planning on disruptions is contextually dependent.

While the study makes some important contributions, the obtained findings ought to be considered within the context of limitations. First, the study only investigates disruptions driven by operational risks, ignoring the negative consequences of environmental risks (terrorist attacks, natural disasters, etc.), which may have a far more negative impact on supply chains. Second, the sample is mostly composed of medium and large companies, not necessarily representative of demand planning performed by the entire spectrum of companies operating in the market.

The study shows that to effectively mitigate disruptions induced by operational risks, the demand planning practices should be integrated into a higher-order construct. Likewise, our research demonstrates that the intensity of demand planning process is contingent upon a number of contextual factors, including firm size, demand variability and demand volume.

The study indicates that to mitigate disruptions of operational risk, demand planning as a higher-order dynamic capability can be referred to the concept of organizational learning, which contributes to forming a critical common ground, ensuring the balance between formal and informal dynamic routines.

The paper depicts that to fully deal with disruptions, the demand planning practices need to be integrated and categorized into the dedicated higher-order. This may lead to forming demand planning as a higher-order dynamic capability that provides a more rapid and efficient rebuttal to any disruptions triggered by operational risks.

This paper aims to examine the relationship of supply chain disruption risk drivers to supply chain performance and firm performance outcomes.

Four disruption risk drivers for a supply chain are identified, namely, demand disruption risk, supply disruption risk, process disruption risk and environment disruption risk. A cross-sectional survey was developed and data was collected from 315 Chinese firms to determine the relationship of supply chain disruption risks to supply chain performance and firm performance.

The empirical findings show that supply disruption risks and process disruption risks have a significant impact on supply chain performance. In addition, this paper shows that supply disruptions, demand disruptions and process disruptions are significantly related to firm performance. This paper shows that supply chain disruption risks have different effects on supply chain performance and firm performance. Managers should be aware that disruption risk drivers can have an impact on firm performance that is different from their impact on supply chain performance. An important finding of the study is that the magnitude of the impact of disruption risks on supply chain performance is greater on the upstream side of the supply chain than on the downstream side of the supply chain.

This is one of the early studies to examine the effect of supply chain disruption risk drivers on both firm performance and supply chain performance. An important finding of the study is that the magnitude of the impact of disruption risks on supply chain performance is greater on the upstream side of the supply chain than on the downstream side of the supply chain.

This study assesses disruption risk management and resilience capabilities from the perspective of top-level operations and supply chain managers when faced with COVID-19 disruptions.

The study involves qualitative research via a triple-phase, interview-based method, following an interpretivist philosophy embodying an empathetic, subjective view to interpret the perspective of top-level managers. The data has been coded and analysed thematically.

Based on the ability to adapt to changing and uncertain environments using quick decision-making, technology and access to resources, the findings show a level of resilience adequate to withstand risk disruptions. The data do not expose differences between disruption management and traditional risk management but do display potential for businesses to adopt a disruption-oriented supply network that is flexible.

Currently, there are little data concerning COVID-19 disruption risk, and the propagation of these impacts throughout the supply chain. This study is limited to the perspective of top, senior-level managers in supply chain and operations.

The research signifies that by adopting a disruption-oriented, flexible network, business may have the means to overcome and surpass impacts from disruption risks. The study offers knowledge on supply chain resilience and flexibility in times of crisis. Managers and practitioners might adopt the evidence to support in developing strategies towards building resilient supply chains.

The findings and conclusions of this paper are the product of the authors’ own work, and the research has been supported appropriately through academic contributions in the study area. All sources have been acknowledged.

The relationship between just-in-time (JIT) and supply chain disruption risk is unclear from the existing literature. This paper aims to investigate the impact of supplier JIT and customer JIT on supplier disruption risk (SDR), internal disruption risk (IDR), and customer disruption risk (CDR) and explore the moderating role of supply chain centralization.

Based on survey data collected from 213 manufacturing firms in China, this study employs structural equation modeling with SmartPLS 3.0 to test the main proposed model and applies an ordinary least square regression to test the moderating effect.

The results demonstrate that supplier JIT is positively related to SDR and negatively associated with IDR. Customer JIT is positively associated with CDR but has no significant effect on IDR. The results also show that SDR and CDR lead to IDR and mediate the relationship between supplier JIT, customer JIT, and IDR. In addition, supply chain centralization amplifies the positive impacts of supply chain JIT on SDR and IDR.

This study makes two main contributions. First, the study provides a comprehensive analysis of the relationship between supply chain JIT and disruption risk. Second, the study addresses that implementing JIT in a supply chain with a centralized decision-making structure leads to a higher level of disruption risk.

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. The purpose of this paper is to extend developing research in this area by addressing gaps within existing literature related to environmental turbulence and uncertainties.

The authors test the 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.

The results show that both magnitude and probability of risk impact on the disruption risk, but the probability of loss is a dominant determinant. The authors 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, the results show that quality uncertainty negatively impacts on the severity of disruption risk.

The construct validity of demand uncertainty was under the required threshold, intimating the need for further construct development.

The framework provides managers with direction on how to formulate and target their disruption risk management strategies. The work also allows practitioners to critical reflect on implicit risk management strategies they may already employ and their effectiveness.

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.

The purpose of this paper is to provide the organization with a process for assessing risk associated with their supply chain and a framework from which they can build their strategy to manage risk.

The proposed process is based on a compilation of research and interactions with supply chain managers in various industries, and these sources provide a specific process to identify how critical the risk is, when to act upon it, and how to manage it. An adapted risk mitigation framework organizes strategies according to the likelihood of disruption and consequences. Included is an industry example used to demonstrate the framework.

The variability and uncertainty associated with supply chain risks make disruption difficult to predict. Furthermore, getting information from suppliers about the amount of risk associated with their operation in an attempt to scope one's own risk can be a challenge. Management must consider the amount of risk the organization is going to accept and how much to invest to mitigate it.

To manage the risk associated with supply chain disruption, an organization must deploy a strategy for assessing it. Once risk areas have been identified, the organization must design strategies which will mitigate the risk. The depth and degree to which risk is mitigated depends upon how risk-averse a company is and what they are willing to invest in this activity.

The purpose of this paper is to develop a taxonomy of how companies implement Supply Chain Risk Management (SCRM) in terms of two fundamental approaches: the first emerging from internal actions and operations within companies, and the other involving inter-organizational actions undertaken with external supply chain partners. This taxonomy aims to predict firms’ performance with regard to the frequency of supply chain disruption.

A cluster analysis of survey data from 908 firms representing 69 countries together with an analysis of variance.

The authors’ analysis demonstrates a clear structure of four different patterns of how companies manage supply chain risks: passive, internal, collaborative, and integral. The authors found that firms pursuing an inter-organizational orientation (collaborative and integral) face the lowest levels of supply chain disruption. On the contrary, strategies which simply concentrate on having greater control of internal operations are not vigorous enough to stop the cascade effect of a disruption at the supply chain level. Furthermore, the excellent performance of integral SCRM strategies also suggests that collaboration between buyers and suppliers ensures the efficacy of internal business continuity plans and security procedures.

Managers should play an active role in making sure that supply chain management and risk management disciplines evolve together. Obviously, when an exogenous event results in a supply chain disruption, a firm will try to put its operations under control through internal capabilities. But SCRM strategies designed proactively in advance with relevant partners are even more beneficial.

First, previous studies have limited the analysis of SCRM mainly to its reactive internal initiatives within a firm. This paper takes the SCRM literature beyond the internal focus by considering both internal and inter-organizational efforts and, more importantly, developing a single configurational model to analyze modes of interaction. Second, there is little empirical evidence showing the current situation of SCRM. Research in SCRM has been more qualitative than empirical, especially in global coverage. The research tackles this gap and, based on a broader scope of the samples the empirical findings show a higher level of generalizability.

Why do managers redesign global supply chains in a particular manner when faced with compounding geopolitical disruptions? In answering this research question, this study identifies a constrained system of reasoning (decision-making logic) employed by managers when they redesign their supply chains in situations of heightened uncertainty.

The authors conducted 40 elite interviews with senior supply chain executives in 28 companies across nine industries from November 2019 to June 2020, when the UK was preparing to leave the European Union, the US–China trade war was escalating, and Covid-19 was spreading rapidly around the globe.

When redesigning global supply chains, the authors find that managerial decision-making logic is constrained by three distinct environmental ecosystem conditions: (1) the perceived intensity of institutional pressures; (2) the relative mobility of suppliers and supply chain assets; and (3) the perceived severity of the potential disruption risk. Intense government pressure and persistent geopolitical risk tend to impact firms in the same industry, resulting in similar approaches to decision-making regarding supply chain design. However, where suppliers are relatively immobile and supply chain assets are relatively fixed, a dominant logic is consistently present.

Building on an institutional logics perspective, this study finds that managerial decision-making under heightened uncertainty is not solely guided by institutional pressures but also by perceptions of the severity of risk related to potential supply chain disruption and the immobility of supply chain assets. These findings support the theoretical development of a novel construct that the authors term ‘supply chain logics’. Finally, this study provides a decision-making framework for Senior Executives competing in an increasingly complex and unstable business environment.

The purpose of this paper is to investigate the knowledge existing in the literature on supply chain resilience for identifying the supply chain practices adopted for securing resilience in given uncertain event.

A systematic literature review is conducted to identify 84 conceptual and empirical studies. The research findings are synthesized in categories of uncertain events, supply chain practices and outcomes.

A set of propositions linking the uncertain events, mechanisms and supply chain resilience improvement is developed. It was found that the sufficient conditions for resilience under unexpected disasters are substantially different from those required for resilience against disruptions caused by internal practices or complexity.

Practitioners can benefit from the knowledge of interventions and mechanisms to improve their supply chain resilience in the face of different unpredictable situations. The contribution of this paper is twofold: first, it develops an actionable theory of supply chain resilience by developing testable propositions in the context of supply chains exposed to uncertainties resulting from unexpected disruptions, complexity of supply chains and adoption of certain internal practice; second, the paper highlights the key shortcomings of existing literature and provides opportunities for further research and improvement.

The purpose of this paper is to examine how firms can develop business risk resilience from supply chain disruption events, by developing big data analytics (BDA) capabilities within their organization. The authors test whether BDA mediates the impact of institutional response to supply chain disruption events, and information technology infrastructure capabilities (ITICs), on firm’s ability to develop risk resilience from supply chain disruption events.

The study is based on survey data collected from 225 firms, spread across several sectors in the USA and Europe. The respondents are primarily senior and middle management professionals who have experience within the information technology (IT) and supply chain domain. Validity and reliability analyses were performed using SPSS and AMOS; and covariance-based structural equation modeling was used to test the hypothesis.

The analysis reveals two significant findings. First, the authors observe that institutional experience with managing supply chain disruption events has a negative impact on firm’s ability to develop business risk resilience. However, if the organizations adopt BDA capabilities, it enables them to effectively utilize resident firm knowledge and develop supply chain risk resilience capacity. The results further suggest that BDA positively adds to an organization’s existing IT capabilities. The analysis shows that BDA mediates the impact of ITIC on the organization’s ability to develop risk resilience to supply chain disruption events.

This study is one of the few works that empirically validate the important role that BDA capabilities play in enabling firms develop business risk resilience from supply chain disruption events. The study further provides a counterpoint to the existing perspective within the supply chain risk management literature that institutional experience of managing past supply chain disruption events prepares the organization to deal with future disruption events. This paper adds to our understanding of how, by adopting BDA capabilities, firms can develop supply chain risk resilience from disruption events.