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The objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.

A well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.

The study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.

This study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.

To the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.

This study investigates the relationship between bank capital and liquidity creation and further examines the effect that institutional quality has on this relationship in Sub-Saharan Africa (SSA).

The data comprise 41 universal banks in nine SSA countries from 2010 to 2022. The study employs the two-step system generalized methods of moments and further uses alternative estimators such as the fixed-effect and two-stage least squares methods.

The empirical results show that bank capital has a direct positive and significant effect on liquidity creation. In addition, the positive effect of bank capital on liquidity creation is enhanced, particularly in a strong institutional environment. The results imply that nonconstraining capital regulatory policies bolster bank solvency, improve risk-absorption capacity and increase liquidity creation.

This study has several policy implications. First, it provides empirical evidence on the position of banks in SSA on the financial fragility and risk-absorption hypothesis of bank capital and liquidity creation debates. This study shows that the effect of bank capital on liquidity creation in SSA countries is positive and supports the risk-absorption hypothesis. Second, this study highlights that a country's quality institutions can complement bank capital to increase liquidity creation. In addition, this study highlights that nonconstraining capital regulatory policies will bolster bank solvency, improve risk-absorption capacity and increase liquidity creation.

The novelty of this study is that it introduces the country's quality institutional environment into bank capital and liquidity creation links for the first time in SSA.

The purpose of this study is to investigate the antecedent factors influencing e-loyalty toward e-wallet payment apps in developing countries (e.g. Jordan). This study also investigates the mediating role of perceived usefulness (PU) and the moderating role of electronic word of mouth (e-WOM) toward these apps.

An online questionnaire was used for data collection from 251 actual users of e-wallet payment apps. To estimate and test the research-proposed model, the partial least squares structural equation modeling (PLS-SEM) was employed.

The results mainly confirm that perceived trust (PT), perceived financial cost (PFC) and perceived ease of use were found to be determinants of PU; perceived security (PS), PT, PFC, perceived ease of use and perceived enjoyment (PE) were found to be determinants of e-satisfaction, whereas e-satisfaction and e-WOM were found to be determinants of e-loyalty toward e-wallet payment apps. Likewise, the results support the significant effect of the moderating effect of e-WOM. Conversely, the direct and indirect impact of PU and perceived health benefits (PHB) on e-satisfaction is not supported; therefore, hypotheses H4, H5 and H9 were rejected.

This study contributes to the understanding of the critical success factors underlying e-wallet apps during and post-COVID-19 era, which can help policymakers in banks and other financial institutions (service providers) to increase the diffusion rate of financial inclusion by the usage of e-wallet apps.

This study aims to offer a hybrid stand-alone system for electric vehicle (EV) charging stations (CS), an emerging power scheme due to the availability of renewable and environment-friendly energy sources. This paper presents the analysis of a photovoltaic (PV) with an adaptive neuro-fuzzy inference system (ANFIS) algorithm, solid oxide fuel cell (SOFC) and a battery storage scheme incorporated for EV CS in a stand-alone mode. In previous studies, either the hydrogen fuel of SOFC or the irradiance is controlled using artificial neural network. These parameters are not controlled simultaneously using an ANFIS-based approach. The ANFIS-based stand-alone hybrid system controlling both the fuel flow of SOFC and the irradiance of PV is discussed in this paper.

The ANFIS algorithm provides an efficient estimation of maximum power (MP) to the nonlinear voltage–current characteristics of a PV, integrated with a direct current–direct current (DC–DC) converter to boost output voltage up to 400 V. The issue of fuel starvation in SOFC due to load transients is also mitigated using an ANFIS-based fuel flow regulator, which robustly provides fuel, i.e. hydrogen per necessity. Furthermore, to ensure uninterrupted power to the CS, PV is integrated with a SOFC array, and a battery storage bank is used as a backup in the current scenario. A power management system efficiently shares power among the aforesaid sources.

A comprehensive simulation test bed for a stand-alone power system (PV cells and SOFC) is developed in MATLAB/Simulink. The adaptability and robustness of the proposed control paradigm are investigated through simulation results in a stand-alone hybrid power system test bed.

The simulation results confirm the effectiveness of the ANFIS algorithm in a stand-alone hybrid power system scheme.

Although karmic beliefs have been found to be positively correlated with pro-social behaviors, the role of karmic beliefs in social entrepreneurship remains relatively unknown. Drawing on the morally extended theory of planned behavior, this paper aims to explore the karmic aspect of social venturing, wherein individuals’ social entrepreneurial intentions and their moral antecedents are activated by karmic beliefs.

The study was performed on a sample of 401 university students in Vietnam. Cronbach’s alpha, confirmatory factor analysis and hierarchical regression analyses were then used to test the reliability, validity of scales and developed hypotheses.

The findings illustrate that karmic beliefs are strongly and positively correlated with empathy, moral obligation, social entrepreneurial self-efficacy and perceived social support. Moreover, individuals’ social entrepreneurial intentions are not only significantly and directly stimulated by karmic beliefs but also receive the indirect effects of karmic beliefs through three mediators: empathy, moral obligation and social entrepreneurial self-efficacy.

The study added fresh perspectives on the role of karmic beliefs in social entrepreneurship literature. Additionally, this study shed a new light on entrepreneurial literature by morally extending theory of planned behavior to explore underlying mechanisms of moral and empathetic components on transferring the effects of karmic beliefs on social entrepreneurial intentions.

The purpose of this study is to investigate the impact of big data (BD) analytics capabilities (BDACs) on green supply chain integration (GSCI) and green innovation (GI) in the context of a developing country, Jordan. In addition, the mediating effect of GSCI on the relationship between BDAC and GI is investigated.

Data collection was carried out through a survey with 300 respondents from food and beverages manufacturing firms located in Jordan. Partial least squares-structural equation modeling (PLS-SEM) technique was applied to analyze the collected data. Natural resource-based view (NRBV) theory was the adopted theoretical lens for this study.

The results revealed that BDAC positively and significantly affects both GSCI and GI. In addition, the results demonstrated that GSCI positively and significantly affects GI. Further, it is also found that GSCI positively and significantly mediates the relationship between BDAC and GI.

This study developed a theoretical and empirical model to investigate the relationship between BDAC, GSCI and GI. This study offers new theoretical and managerial contributions that add value to the supply chain (SC) management literature by testing the mediation model in food and beverages manufacturing firms located in Jordan.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

Quality is a sensitive and high-priority issue in the global construction including in Bangladesh. This research is intended to provide necessary information to stakeholders and authorities for better management of the construction quality in Bangladesh. Therefore, this study seeks to find and prioritize the factors affecting the construction quality in Bangladesh.

In total 65 factors were extracted and categorized from the literature and expert panel discussion. Subsequently, these factors were designed in a questionnaire under 13 major groups for a survey where 176 construction professionals participated and returned their completed survey form. Collected data were tested by the Cronbach Alpha to check the reliability before proceeding to the Relative Importance Index (RII) analysis for determining the relative ranks of identified factors.

Statistical analysis of survey data represents that the most significant factors are: lack of management commitment, lack of technical skill and experience of the consultant, delays in progress investigation, political interference and contractor's desire for unrealistic profit. The most crucial major groups of factors influencing the construction quality are management, material, consultant, cost and time and contract-related major groups.

It will contribute to the body of knowledge, as it points out the impact of factors affecting quality in Bangladeshi construction. Authorities and stakeholders can be helped by the overview of the high and low ranks factors, understanding the diverse characteristics of factors and making more aware the industry about the quality issues which need to be a top concern to solve. Other developing countries that share the same socio-economic context as Bangladesh can be benefit from the results of this study to control quality issues in construction.

Studies focusing on the growth of indigenous construction firms (ICFs) are getting dated, and unreflective of recent policy changes in developing countries. This study sought to analyze critical barriers to the growth of ICFs and obtain an unsupervised parsimonious grouping of the barriers for policy improvements.

A mix of quantitative and qualitative research methods was adopted for the study. ICFs in Nigeria were cross-sectionally surveyed based on a set of firm growth barriers obtained from literature and refined by focus group discussion. Descriptive (means, standard deviations, percentages) and inferential (Kruskal-Wallice and Mann-Whitney U test) statistics were used in the analyses of the data. Factor analysis was used to group the variables.

Results showed that “declining” ICFs are more negatively impacted by low construction mechanization/use of labor intensive methods, inadequate geographical reach of operations, and inadequate flow of jobs/low demand than “stunted” and “growing” ICFs. The three main domains of critical barriers to the growth of ICFs were identified in descending order of importance as low patronage, difficulty accessing funds, and business management incapacity.

The study recommends improvements in access to funds for ICFs by increasing the percentage of advance payments, and creating a pool of equipment for easy hire by ICFs. ICFs are advised to seek information on tendering opportunities outside their regions of domicile in order to increase their patronage.

This study reveals differences in the impacts of growth barriers on ICFs at different growth levels. This study also clarifies persisting barriers to the growth of ICFs [primarily construction micro, small and medium-sized enterprises (MSMEs)] from a developing country perspective using a longer list of variables.