Supply chain viability: conceptualization, measurement, and nomological validation.
TL;DR: In this paper, a measurement scale for supply chain viability (SCV) is proposed, which is first defined and operationalized as a construct, followed by content validation and item measure development.
Abstract: Supply chain viability (SCV) is an emerging concept of growing importance in operations management. This paper aims to conceptualize, develop, and validate a measurement scale for SCV. SCV is first defined and operationalized as a construct, followed by content validation and item measure development. Data have been collected through three independent samplings comprising a total of 558 respondents. Both exploratory and confirmatory factor analyses are used in a step-wise manner for scale development. Reliability and validity are evaluated. A nomological model is theorized and tested to evaluate nomological validity. For the first time, our study frames SCV as a novel and distinct construct. The findings show that SCV is a hierarchical and multidimensional construct, reflected in organizational structures, organizational resources, dynamic design capabilities, and operational aspects. The findings reveal that a central characteristic of SCV is the dynamic reconfiguration of SC structures in an adaptive manner to ensure survival in the long-term perspective. This research conceptualizes and provides specific, validated dimensions and item measures for SCV. Practitioner directed guidance and suggestions are offered for improving SCV during the COVID-19 pandemic and future severe disruptions.
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TL;DR: The COVID-19 pandemic has challenged supply chains (SC) on an unprecedented scale testing viability and adaptation under severe uncertainty as discussed by the authors, however, the literature on the adaptation strategies and strategies is limited.
Abstract: The COVID-19 pandemic has challenged supply chains (SC) on an unprecedented scale testing viability and adaptation under severe uncertainty. However, the literature on the adaptation strategies and...
164 citations
TL;DR: In this paper, the authors examined the impact of the COVID-19 pandemic on food retail supply chains and their resilience and proposed several directions and practical implementation guidelines to improve the food retail SC resilience.
Abstract: In this study, we examine the impact of the COVID-19 pandemic on food retail supply chains (SCs) and their resilience. Based on real-life pandemic scenarios encountered in Germany, we develop and use a discrete-event simulation model to examine SC operations and performance dynamics with the help of anyLogistix digital SC twin. The computational results show that food retail SC resilience at the upheaval times is triangulated by the pandemic intensity and associated lockdown/shutdown governmental measures, inventory-ordering dynamics in the SC, and customer behaviours. We observe that surges in demand and supplier shutdowns have had the highest impact on SC operations and performance, whereas the impact of transportation disruptions was rather low. Transportation costs have spiked because of chaotic inventory-ordering dynamics leading to more frequent and irregular shipments. On bright side, we observe the demand growth and utilization of online sales channels yielding higher revenues. We propose several directions and practical implementation guidelines to improve the food retail SC resilience. We stress the importance of SC digital twins and end-to-end visibility along with resilient demand, inventory, and capacity management. The outcomes of our study can be instructive for enhancing the resilience of food retail SCs in preparation for future pandemics and pandemic-like crises.
153 citations
TL;DR: A systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics focuses on different costs induced by the planning of proactive investments in robustness and through parametrical/structural adaptation at the recovery stage.
115 citations
TL;DR: A discrete-event simulation model is used to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic and shows that supply chains with postponed demand and shutdown capacity during the pandemic are particularly prone to disruption tails.
Abstract: Entering the COVID-19 pandemic wreaked havoc on supply chains Reacting to the pandemic and adaptation in the "new normal" have been challenging tasks Exiting the pandemic can lead to some after-shock effects such as "disruption tails" While the research community has undertaken considerable efforts to predict the pandemic's impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production-inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails We then developed and examined two strategies to avoid these disruption tails First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control
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TL;DR: In this article, the authors examined the link between firm resources and sustained competitive advantage and analyzed the potential of several firm resources for generating sustained competitive advantages, including value, rareness, imitability, and substitutability.
46,648 citations
TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Abstract: Valid measurement scales for predicting user acceptance of computers are in short supply. Most subjective measures used in practice are unvalidated, and their relationship to system usage is unknown. The present research develops and validates new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance. Definitions of these two variables were used to develop scale items that were pretested for content validity and then tested for reliability and construct validity in two studies involving a total of 152 users and four application programs. The measures were refined and streamlined, resulting in two six-item scales with reliabilities of .98 for usefulness and .94 for ease of use. The scales exhibited hgih convergent, discriminant, and factorial validity. Perceived usefulness was significnatly correlated with both self-reported current usage r = .63, Study 1) and self-predicted future usage r = .85, Study 2). Perceived ease of use was also significantly correlated with current usage r = .45, Study 1) and future usage r = .59, Study 2). In both studies, usefulness had a signficnatly greater correaltion with usage behavior than did ease of use. Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage. Implications are drawn for future research on user acceptance.
40,720 citations
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each.
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.
Table of Contents
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
37,124 citations
TL;DR: The dynamic capabilities framework as mentioned in this paper analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change, and suggests that private wealth creation in regimes of rapid technology change depends in large measure on honing intemal technological, organizational, and managerial processes inside the firm.
Abstract: The dynamic capabilities framework analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change. The competitive advantage of firms is seen as resting on distinctive processes (ways of coordinating and combining), shaped by the firm's (specific) asset positions (such as the firm's portfolio of difftcult-to- trade knowledge assets and complementary assets), and the evolution path(s) it has aflopted or inherited. The importance of path dependencies is amplified where conditions of increasing retums exist. Whether and how a firm's competitive advantage is eroded depends on the stability of market demand, and the ease of replicability (expanding intemally) and imitatability (replication by competitors). If correct, the framework suggests that private wealth creation in regimes of rapid technological change depends in large measure on honing intemal technological, organizational, and managerial processes inside the firm. In short, identifying new opportunities and organizing effectively and efficiently to embrace them are generally more fundamental to private wealth creation than is strategizing, if by strategizing one means engaging in business conduct that keeps competitors off balance, raises rival's costs, and excludes new entrants. © 1997 by John Wiley & Sons, Ltd.
27,902 citations
TL;DR: In this paper, the authors explore the usefulness of analyzing firms from the resource side rather than from the product side, in analogy to entry barriers and growth-share matrices, the concepts of resource position barrier and resource-product matrices are suggested.
Abstract: Summary The paper explores the usefulness of analysing firms from the resource side rather than from the product side. In analogy to entry barriers and growth-share matrices, the concepts of resource position barrier and resource-product matrices are suggested. These tools are then used to highlight the new strategic options which naturally emerge from the resource perspective.
18,677 citations