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1 – 3 of 3Meijuan Li, Jiarong Zhang and Zijie Shen
Three-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making…
Abstract
Purpose
Three-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.
Design/methodology/approach
First, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.
Findings
To evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.
Originality/value
The proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.
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Zhaojun Han, Shenyang Jiang, Zhanzhi Zheng and Yong Jin
While researchers recognize the significance of philanthropic donations in disaster relief and recovery, the benefits that firms derive from such donations remain unclear…
Abstract
Purpose
While researchers recognize the significance of philanthropic donations in disaster relief and recovery, the benefits that firms derive from such donations remain unclear, particularly when firms are adversely impacted by the disaster. To address this gap, this study seeks to elucidate the impact of various donation strategies on firm resilience in the context of the COVID-19 pandemic.
Design/methodology/approach
Based on the hand-collected data on donations, the authors employ ordinary least squares regressions to investigate the effectiveness of various donation strategies – including type, timing and location – in enhancing firm resilience in terms of the severity of stock price losses during the pandemic. To address potential endogeneity concerns, the authors use a two-stage least squares regression with instrumental variables.
Findings
This study finds robust evidence that certain donation strategies are more effective at mitigating stock price losses during the pandemic. Specifically, the authors find that in-kind donations (compared to monetary ones), earlier donations (compared to later ones) and donations targeting severely impacted areas (Hubei province vs. other places) are more effective methods to reduce the severity of stock price losses.
Originality/value
This study points out an alternative mechanism through which donations influence firm resilience during a crisis context and provides important managerial implications for firms to better engage in disaster donations.
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Ai-Fen Lim, Keng-Boon Ooi, Garry Wei-Han Tan, Tat-Huei Cham, Mohammad A.A. Alryalat and Yogesh K. Dwivedi
The evolution of modern digitalization technologies necessitates the development of a competitive digital supply chain quality management (SCQM) strategy by manufacturers. Using…
Abstract
Purpose
The evolution of modern digitalization technologies necessitates the development of a competitive digital supply chain quality management (SCQM) strategy by manufacturers. Using the new institutions and institutional theory (IIT), the study research first aims to identify the most important SCQM practices that can influence competitive performance (CP). Second, the authors intend to investigate the role of digital strategy alignment (DSA) in moderating the relationship between the multidimensionality of SCQM practices and CP among manufacturers.
Design/methodology/approach
The authors employ the Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique to examine 225 valid samples from Malaysian manufacturers who use SCQM practices.
Findings
The study findings indicate that five of the twelve hypotheses developed were accepted. This suggests that supplier focus, strategic collaboration, information sharing and customer focus are positively and significantly correlated with CP. Unexpectedly, DSA moderates the relationship between leadership and CP.
Originality/value
This study extended the new IIT by empirically testing the six SCQM practices for CP in a DSA context, which can serve as a model for future research in the SCQM, CP and DS fields.
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