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The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.

The purpose of this paper is to incorporate factors that characterize the agricultural activity as productivity indices to compute the agricultural competitiveness of regions in order to rank the regions, and compare the results with those obtained by applying other commonly used social and economic indicators.

The authors identify regional factors related to the use of water, soil, production, revenues, and rural population, which conform a total of six productivity indices, that the authors then employ to calculate the regional agricultural competitiveness index.

The agricultural-related indices are informative in supporting the regional ranking related to resources and technology utilization. The results reveal that the coastal regions are the most competitive when compared to the regions located in the highlands and the jungle. Nevertheless, in contrast with other existing competitiveness rankings, the present study identifies the regions with the greatest potential for agriculture.

The authors identify the regions which have a higher potential of development considering the natural resources and agricultural production. The authors hope that this paper can assist regional and national policymakers in their endeavor to improve regional and national competitiveness.

The authors identify the regions with a higher potential of development considering natural resources and agricultural production and the possibilities to improve their competitiveness.

The study also bears social implications, given that the rural activities in Peru are carried out by approx. 7 million inhabitants, whose contribution to the gross domestic product (GDP) is as much as 7 percent, making use of about 94 percent of the available water.

The originality of the present paper resides in the attempt to compute a regional competitiveness index by taking agricultural resources as determinant factors. The authors rank the regions based on their agricultural competitiveness.

Regional competitiveness refers to the capacity of a region to manage its resources and competencies to increase the well-being of its people. Measuring regional competitiveness is, thus, a major consideration for policymakers, businesses and the academic community in their endeavour to improve the same. This paper aims to demonstrate a novel way to calculate the regional competitiveness index under a two-stage objective general index (OGI) framework.

The authors compute the regional competitiveness index under a two-stage OGI framework. In the first stage, they aggregate the sub-factor level information into a factor level index; in the second stage, they use the factor level index to obtain a regional competitiveness index.

The authors discuss the properties of the proposed index in detail. They further analyse five periods of regional competitiveness of Peru spanning the period 2008-2015. Among others, the results reveal the existence of the resource curse of the mining regions of Peru.

The paper is a contribution to the practical measurement of competitiveness.

The calculation of a regional competitiveness index is vital for improving the competitiveness of the countries and for reducing regional inequalities.

When compared to the existent methods available in the literature, the advantage of the proposed method resides in the fact that the derived index has a positive correlation with the factor-level indices and the factor-level indices have a positive correlation with the sub-factor-level information.

This study investigates the interrelationships between efficiency, competition and risk in the Chinese banking industry.

Parametric stochastic frontier analysis is used to estimate bank efficiency; the Lerner index is used as the competition indicator; accounting ratios and a translog function are used to measure different types of risk and finally, the three-stage least square estimator is used to investigate the interrelationships.

The results of this study show that the impact of competition on different types of risk is significant and positive, while there is a significant and positive impact of credit risk, liquidity risk and capital risk on bank competition. In addition, the findings demonstrate that the interrelationships between efficiency and competition are significant and negative. The authors do not find any robust interrelationships between different types of risk and different types of efficiency; the authors find that diversification and higher levels of profitability reduce bank credit risk. The results suggest that a higher developed banking sector reduces the level of bank competition in China.

This is the first piece of research that comprehensively investigates the interrelationships between different types of risk, competition and different efficiencies in China.

The purpose of this paper is to investigate the mediator role that knowledge sharing plays between organisational culture, organisational structure, and technology infrastructure and process improvement in a knowledge management context in manufacturing enterprises operating in the food, beverage and textile industry.

An empirical study is conducted with a sample of 200 food, beverage and textile companies. Data are obtained by means of a survey questionnaire applied to general managers in each of the sample firms. The impact of the factors organisational culture, organisational structure and technology infrastructure on process improvement via knowledge sharing is assessed. Structural equation modelling and maximum likelihood estimation are applied to find the direction and strength of the relationships.

The main findings indicate the significant relationships between knowledge sharing and process improvement, between organisational culture and knowledge sharing, and between organisational structure and knowledge sharing. The relationship between technology infrastructure and knowledge sharing is found not to be significant.

The findings of the present study are limited to the food, beverage and textile industry. Future research could incorporate data from other manufacturing sectors or service companies.

This study provides practical guidance for general managers who wish to implement process improvement programmes.

Several authors have noted that there are few research studies concerning the interaction between each phase of knowledge management and total quality management practices. This study is interested in knowledge sharing and its impact on process improvement in a knowledge management context.

The purpose of this paper is to propose the microeconomics concept of elasticity to estimate the SERVQUAL gap elasticity to derive important insights for service providers to develop the right strategies to bridge the overall gap in service.

The dimensions of SERVQUAL adopted from Parasuraman et al. (1988) and Kumar et al. (2009) are first verified for their unidimensionality using structural equation modeling and reliability in the context of United Arab Emirates banking industry. Furthermore, the technique of dominance analysis is used to derive the relative importance of dimensions for different groups of banks. Finally, the stepwise log-linear regression models are used to estimate the gap elasticity to measure the responsiveness of the overall SERVQUAL gap to a change in customers’ perception on different dimension.

The results reveal that the dimension which is prioritized as the most important dimension need not to be the one to be targeted under the resource constraint to react faster to the changes of customers’ banking behavior.

This is probably the first attempt to examine the service quality through gap elasticity. This method is especially useful when the traditional approach to measure relative importance of critical factors fails to clearly discriminate between two or more dimensions, which, in turn, may lead to failure in decision making to choose the right strategies to bridge the overall gap in the service.