Search results

This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

The United Nation's 2030 mission provides scholars, practitioners and governments with a valuable framework to direct their research in a way that tackles societal issues. Towards this aim, some key Sustainable Development Goals focus on improving the well-being of humans and societies; however, the literature dealing with individual financial well-being is still underdeveloped and fragmented. To address this significant research gap, this paper reviews the literature on financial well-being. It provides an in-depth analysis of different theories, mediators and moderators employed in financial well-being studies to deepen the theoretical framework and widen the scope of financial well-being research.

Using the Web of Science Core Collection database (WoS), the literature on financial well-being was reviewed (n = 32) following a systematic review approach.

Findings revealed that (a) there is a limited application of theories in financial well-being studies (n = 19) with the majority of studies (n = 15) employing only one theory; (b) twenty-one different theories were used with the maximum number of theories employed by any study was four; (c) the theory of planned behavior was the most commonly used (n = 4); (d) While a reasonable number of studies examine mediators and moderators in antecedents-financial well-being relationships, studies examining mediators and moderators relationships in financial well-being-outcomes relationships are limited. Based on these findings, this review identified a need for future theory-based financial well-being research and examining the role of underlying and intervening mechanisms in antecedents-financial well-being-outcomes relationships.

The study concludes by suggesting some relevant theories and prospective variables that can explain potential financial well-being relationships. To the best of the author's knowledge, this is the first review on the use of theories, mediators and moderators in financial well-being studies.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

The purpose of this study is to present a general review that provides an overview of the concept of sustainability and the effectiveness of mathematics curricula in courses where deeper work on economic and environmental sustainability has become central.

A qualitative methodology consisting of a review based on a pre-defined systematic method was used to exhaustively search and identify the most relevant answers to the research question: What is the role of mathematics to sustainability? To facilitate answering such a broad question, several concrete questions were formulated. Answers from published and unpublished documents were analysed. The quality of the extracted data was assessed, and the results were synthesized.

It was concluded that, on the one hand, the discipline of mathematics has much to contribute to solving the problems of sustainability; on the other hand, new mathematics is appearing stimulated by new challenges.

This work presents social implications in an innovative way. It allows for an increase in educational sustainability by bringing the academic community closer to the business world and the challenges of society and, furthermore, by having a major impact on the motivation of teachers and students to develop cooperative work within university institutions.

The originality is based on an a priori analysis for the construction and implementation of didactic tools for university teacher training in the area of mathematics within the framework of sustainable development, both economically and environmentally.

The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.

In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.

The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.

The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.

Although many firms are investing considerable resources in building and designing strong and effective internal auditing (IA) to improve corporate governance and internal control processes, IA literature is still relatively fragmented. Therefore, this paper aims to provide a systematic review of studies on IA in 27 European countries and the UK.

Based on the Scopus database, 142 papers published between 1987 and 2022 were analyzed. This study focused on evaluating and analyzing the characteristics of literature and the themes investigated with a focus on four key aspects: governance, the effectiveness of IA, the relationship between internal auditors and other parties and risk management to provide directions for future research.

This study found that IA literature did not provide the integrated knowledge of internal audit functions (IAFs) and the factors that could contribute to their implementation as required. The results showed that the UK, Greece and Italy dominate the published literature in terms of the number of studies. There are a few studies that investigate IA in private institutions and nonprofit organizations. Interestingly, a vast majority of studies are not based on theoretical grounds. The results also showed that there is an absence of studies that discuss the impact of cultural and political systems as well as the demographic characteristics of auditors on the implementation of IAFs.

This study is useful for researchers, organizations and regulators because it contributes to the literature by highlighting the intellectual development of IA in the European countries and the UK, providing several directions for future studies. To the best of the authors’ knowledge, this research is the first study to use a systematic review approach in evaluating the intellectual development of IA research in European countries, identifying areas and elements that received less attention in previous studies and providing a roadmap for future studies.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

In recent years, mandatory rules and regulations were issued to stress the importance of increasing gender diversity in companies, assuming that gender diversity would enhance financial performance. Thus, the purpose of this paper is to review recent research concerning board gender diversity and its impact on financial performance for the period of 2002 to 2022.

Using the Web of Science and Scopus databases, 152 studies were analyzed, out of 91 high-impact journals. The analysis focuses on discussing the moderating, mediating and controlling variables and exploring the theories and theoretical foundations that are most prevalent in the literature.

The findings indicated an incompatibility between the results of the studies on the impact of gender diversity on financial performance. In addition, results showed the majority of studies focused on discussing the controlling variables associated with the company compared to the variables related to employees or the surrounding environment. On the other hand, the results also showed widespread use of the theoretical basis with the development of new theories in the recent period in parallel with the increase in the literature.

The results of this study help to reconcile the findings of the different and conflicting literature by presenting the perception that the efficacy of the positive impact of gender diversity on financial performance is related to several organizational and environmental factors that companies have to consider.