Search results

Based on the role theory and prosocial motivation literature, this research aims to explore the bright and dark side of socially responsible human resource management (SRHRM) on hotel employees' outcomes through the mediation of role conflict. Besides, this study examines the moderating effect of prosocial motivation between role conflict and volunteering and organizational citizenship behavior (OCB).

The authors collected 326 employee-supervisor dyads data in two waves from 12 hotels in the province of Wuhan, China. Besides, structural equation modeling (SEM) analysis was adopted to test the hypothesized model.

As expected, the result shows that SRHRM can increase employees' volunteering and decrease their OCB through the mediation of the role conflict. Further, prosocial motivation strengthens the linkage between role conflict and volunteering, but not the relationship between role conflict and OCB.

This result enables hotel managers to adopt SRHRM as a useful tool of carrying out suitable corporate social responsibility (CSR) activities. Additionally, this study highlights the vital role of employee in successful CSR implementation.

Although the hotel industry contributes a lot to global economic development, CSR research specifically focused on hotel industry has been unexplored. Therefore, this research brings SRHRM into hotel industry and establishes a model specifying both the bright side and dark side effect of SRHRM in the hotel industry.

The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach.

A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance.

Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities.

One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible.

The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement.

To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.

Companies are adopting innovative methods for responsiveness and efficiency in the public transport sector. The implementation of air-taxi services (ATS) in the transport sector is a move in this direction. Air taxis have a two-pronged advantage as they can reduce travel times by avoiding traffic congestion and have the potential to reduce carbon footprint compared to traditional modes of public transportation. Many companies worldwide are developing and testing ATS for practical applications. However, many factors may play a significant role in adopting ATS in the transport sector. This paper attempts to unearth such critical success factors (CSFs) and establish the interrelationships between these factors.

Fifteen CSFs were identified by systematically reviewing the literature and taking experts' input. An integrated multi-criteria decision-making (MCDM) technique, Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (DEMATEL-ANP [DANP]) was used to envisage the causal relationships between the identified CSF.

The results reveal that Govt Regulations (GOR), Skilled Workforce (SKF) and Conductive Research Environment (CRE) are the most influential factors that impact the adoption of ATS in the transport sector.

The research implications of these findings will help practitioners and policymakers effectively implement ATS in the public transportation sector.

This is the first kind of study that identifies and explores the different CSFs for ATS implementation in public transportation. The CSFs are evaluated with the help of a framework built with inputs from logistics experts. The study recognizes the CSFs for ATS implementation and provides a foundation for future research and smooth adoption of ATS.

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

The purpose of this paper is to propose an integrated gray-decision making trial and evaluation laboratory (Grey-DEMATEL) framework to evaluate the ICT adoption barriers in manufacturing small and medium enterprises (MSMEs) running in developing countries. The proposed model is also tested for Indian MSMEs.

The model consists of 16 potential ICT adoption barriers selected from existing literature and refined based on discussion with domain experts. While DEMATEL analyses causal relationship and prioritizes them, Grey approach tackles individual biases and data insufficiency.

The authors conclude that lack of awareness about benchmarking and lack of management vision are the most critical ICT adoption barriers in the case of Indian MSMEs.

Outcomes of the present research are based on the experts’ inputs which are subject to the biases related to their experience and exposure. In India practices adopted by SMEs have geographical and political influence that is also neglected.

This study provides a model consisting of 16 ICT adoption barriers for MSMEs in developing country and a framework to analyze causal relationships among the barriers with the flexibility of data input from their own domain experts. The framework is also capable of dealing with expert biases and data insufficiency.

It is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance function to determine the tolerance relation. However, such a simple function does not take into account criterion weights and the interaction among criteria. Further, the traditional tolerance relation ignores interdependencies concerning direct and indirect influences among patterns. This study aimed to incorporate interaction and interdependencies into the tolerance relation to develop non-additive grey TRSCs (NG-TRSCs).

For pattern classification, this study applied non-additive grey relational analysis (GRA) and the decision-making trial and evaluation laboratory (DEMATEL) technique to solve problems arising from interaction and interdependencies, respectively.

The classification accuracy rates derived from the proposed NG-TRSC were compared to those of other TRSCs with distinctive features. The results showed that the proposed classifier was superior to the other TRSCs considered.

In addition to pattern classification, the proposed non-additive grey DEMATEL can further benefit the applications for managerial decision-making because it simplifies the operations for decision-makers and enhances the applicability of DEMATEL.

This paper contributes to the field by proposing the non-additive grey tolerance rough set (NG-TRS) for pattern classification. The proposed NG-TRSC can be constructed by integrating the non-additive GRA with DEMATEL by using a genetic algorithm to determine the relevant parameters.

This study aims to develop a cause-effect relationship between criteria that contribute to water security using the Intuitionistic Fuzzy-Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) method. Differently from the typical DEMATEL which utilizes crisp numbers, this modification introduces intuitionistic fuzzy numbers (IFNs) to enhance judgments in a group decision-making environment. In particular, the linguistic variables used in IF-DEMATEL are defined using the concept of three-tuple of IFNs.

Data with the linguistic variable “influence” were collected from a group of experts in water security via personal unstructured interviews. Seven water security criteria are considered in this study. Computational software was employed to execute the computational procedures of the IF-DEMATEL method. It is anticipated that by taking into account the hesitation degree of IFNs will reflect the scenario in real life, which could lead to precise decision-making.

The results show that “Over-Abstraction”, “Saltwater Intrusion” and “Limited Infrastructures” are the cause criteria that contribute to water security. In addition, the relationship map of influence shows that “Water Pollution” and “Rapid Urbanization” are the most vulnerable criteria as these two criteria are most easily affected by other criteria in a unidirectional relation.

It is anticipated that these findings will serve as useful references for water security management and policymakers.

The present study makes a noteworthy contribution to the modification of DEMATEL where three-tuple of intuitionistic fuzzy numbers are considered in the computations. The present study also provides additional evidence with respect to factors that contribute to water security.

This paper aims to identify and systematically analyze the causal-effect relationships among barriers to circular food supply chains in China.

Grounded in multiple organizational theories, this paper develops a theoretical framework for identifying relevant barriers to integrating circular economy philosophy in food supply chain management. The study uses 105 responses from Chinese food supply chain stakeholders including food processors, sales and distribution channels, consumers and government officials. It applies a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method to examine the causal-effect relationships among the identified barriers.

Overall, the results suggest two key cause barriers: first, weak environmental regulations and enforcement, and second, lack of market preference/pressure. Meanwhile, lack of collaboration/support from supply chain actors is the most prominent barrier. The key cause and prominent barriers are also identified for each of the supply chain stakeholder involved.

The study offers practical insights for overcoming barriers to integrating circular economy philosophy in the management of supply chains in the Chinese food sector, as well as in other contexts where similar challenges are faced. It also sheds light on which organizational theories are most suitable for guiding similar studies.

To the best of the authors’ knowledge, this is the first barrier study on circular food supply chains. The use of multiple organizational theories for the development of the theoretical framework is unique in barrier studies. The study offers insights from multiple stakeholders in the Chinese food supply chains.

The primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.

This research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.

This study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.

This analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.

This study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.