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This study aims to investigate the key factors that motivate learners to use handheld devices to access library resources. To do so, this study integrates the technology acceptance model (TAM) and the DeLone and McLean information systems success (D and M-ISS) model.

The relationship between the causes and the outcomes may not be symmetrical. To test this proposition, data were collected from 210 respondents in a Gulf country and analysed using structural equation modelling (SEM) and complemented by fuzzy set qualitative comparative analysis (fsQCA).

The SEM results revealed that three constructs – perceived ease of use (PEOU), service quality (SQ) and system quality (SEQ) are strong drivers of students’ continuous intention to use handheld devices to access library resources. However, perceived usefulness (PU) and information quality (IQ) do not significantly influence students’ intentions. Besides, SQ and PEOU are positively related to PU. Furthermore, fsQCA results show that two different conjunctions, PU*PEOU*IQ*SEQ and PEOU*SQ*IQ*SEQ, cause the students to show a continuous intention to use handheld devices to access library resources.

Unlike previous studies on mobile library resource utilization, this analysis extends TAM to investigate the linear additive influence of two basic TAM constructs: PEOU and PU, and three constructs, namely, SEQ, SQ and IQ of the ISS model, on students’ library resource utilization. Furthermore, the findings of SEM were complemented by a set theory-based configuration method, fsQCA, to investigate the asymmetrical, equifinal and configurational causation leading to the desired outcome. The findings of this study have theoretical and practical implications.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

This paper aims to integrate Big Data in e-government in Oman, also known as “e-Oman”, wherein Big Data might be better harnessed to tackle real-time challenges.

Besides a description of the concepts of e-government and Big Data in general, the paper underscores the dimensions of “e-Oman”. Following a qualitative approach, the paper asserts how integration of Big Data in “e-Oman” may be useful by invoking examples from four short case studies across different sectors.

The paper supports the integration of “e-Oman” and Big Data wherein besides providing smooth public services, the government is encouraged to forge inter- and intra-ministerial collaboration and public-private partnership. The paper probes through the challenges and opportunities in effecting this integration.

The paper provides a platform for the policymakers to conceive of a synchronized programme for integrating “e-Oman” and the Big Data generated by it. This integration would go a long way in building upon the economy of Oman, besides providing better public services to the individuals and businesses on a real-time basis.

The paper does throw light on the issues of privacy and confidentiality of data available with the government. There are challenges of cybercrime as well. Therefore, the paper posits that a robust fool-proof infrastructure should be instituted by the government for effecting integration of e-government and Big Data.

This paper seeks to fill the gap in extant literature which remains scant on the integration of e-government with Big Data. This is especially true in the case of Oman where not a single study has been presented to probe this issue. Given that “e-Oman” is expanding its scope over the years, this paper foresees the concomitant opportunities and challenges in the integration of Big Data in “e-Oman”.

With the changing landscape of the globalised business world, business-to-business supply chains face a turbulent ocean of disruptions. Such is the effect that supply chains are disrupted to the point of failure, supply is halted and its adverse effect is seen on the consumer. While previous literature has extensively studied risk and resilience through mathematical modelling, this study aims to envision a novel supply chain model that integrates blockchain to support visibility and recovery resilience strategies.

The stochastic bi-objective (cost and shortage utility) optimisation-based mixed-integer linear programming model integrates blockchain through a binary variable, which activates at a particular threshold risk-averse level of the decision-maker.

Firstly, visibility is improved, as identified by the average reduction of penalties by 36% over the different scenarios. Secondly, the average sum of shortages over different scenarios is consequently reduced by 36% as the recovery of primary suppliers improves. Thirdly, the feeling of shortage unfairness between distributors is significantly reduced by applying blockchain. Fourthly, unreliable direct suppliers resume their supply due to the availability of timely information through blockchain. Lastly, reliance on backup suppliers is reduced as direct suppliers recover conveniently.

The findings indicate that blockchain can enhance visibility and recovery even under high-impact disruption conditions. Furthermore, the study introduces a unique metric for measuring visibility, i.e. penalty costs (lower penalty costs indicate higher visibility and vice versa). The study also improves upon shortages and recoveries reported in prior literature by 6%. Finally, blockchain application caters to the literature on shortage unfairness by significantly reducing the feeling of shortage unfairness among distributors.

This study establishes blockchain as a pro-resilience technology. It advocates that organisations focus on investing in blockchain to enhance their visibility and recovery, as it effectively reduces absolute shortages and feelings of shortage unfairness while improving recovery and visibility.

To the best of the authors’ knowledge, this is a unique supply chain model study that integrates a technology such as blockchain directly as a binary variable in the model constraint equations while also focusing on resilience strategies, costs, risk aversion and shortage unfairness.

Mobile banking (Mbanking) is one of the most widely used mobile technology applications in recent times. This research aims to develop and test a research model by integrating social influence, trust and compatibility along with demographic variables into the original technology acceptance model (TAM) for Mbanking adoption which can be useful for understanding individual behaviours from an international business perspective.

Data were collected through a structured survey from 208 Omani Mbanking users and analysed using a two-staged regression and neural network (NN) model.

The results showed that perceived ease of use and demographic variables were not statistically significant in the multiple linear regression model, whereas the importance of the aforementioned variables was relatively high in the results obtained from the NN model. Furthermore, other predictors, namely, trust, perceived usefulness, compatibility and social influence included in the proposed research model that were established as significant by the regression model were assigned high relative importance by the NN model as well.

The study reflects the customer’s opinion from a developing country perspective. In addition, the research makes a significant theoretical contribution by using predictive modelling instead of causal or explanatory modelling for the development of a new and extended TAM model. The findings can be gainfully used by international business to understand Omani customer- and design-appropriate strategies for market penetration.

This study offers deeper understanding about Mbanking adoption from a developing country perspective and identifies and integrates important variables that influence the adoption in the aforementioned context.

The purpose of this study is to examine the predictabilities of five intra-personal factors to predict pro-environmental consumer behavior (PECB) and the moderating role of religiosity in Oman.

The study uses neural network to analyze the antecedents/antecedents × religiosity → PECB relationships by using a sample of 306 consumers from Oman.

This study finds that the most important predictors of PECB, according to the order of importance, are attitude × religiosity, knowledge, concern × religiosity, knowledge × religiosity, value, religiosity, attitude, concern and value × religiosity.

The convenience sample from a single Islamic country limits the generalizability of the findings. Future studies should use probabilistic sampling techniques and multiple Islamic countries located in different geographical regions.

To promote PECB, businesses and policymakers should provide environmental education to expand knowledge and value, leverage ecological religious values in integrated marketing communications, make positive inducements to change attitude and concern enhancing interventions.

As religiosity enhances PECB by moderating the impacts of environmental intra-personal factors on PECB, businesses and policymakers should find ways to use faith-based ecological messages in Islamic countries.

Determining the predictabilities of psychological factors and their interactions with religiosity to predict PECB in Islamic countries is necessary for promoting environmentally friendly products in Islamic countries and for reducing the ecological damage to the environment.

The purpose of this paper is to study the role of religiosity in consumer pro-environmental behavioral intention (CPEBI). Consumer pro-environmental value, knowledge, concern and attitude predict CPEBI; however, previous findings are neither consistent about their predictabilities nor clear about the order of importance of these predictors. Further, while religiosity has the potential to affect values, beliefs, attitudes and behaviors, its role in CPEBI research has been neglected.

Data are collected from a sample of 306 respondents from Oman, an Islamic country with mostly Muslim consumers, and analyzed using a neural network model.

This study finds that the most important predictors of CPEBI, in order of importance, are attitude, concern, knowledge, religiosity and value. Further, results indicate that religiosity moderates the impacts of, in order of importance, attitude, value, concern and knowledge on CPEBI.

Both businesses and policy makers can prioritize intervention strategies according to the importance of the predictors and can leverage faith-based messages and programs for promoting CPEBI toward creating a better environment for all.

Determining the predictabilities of psychological factors and their interactions with religiosity to predict CPEBI in Islamic countries is necessary for promoting environmentally friendly products in Islamic countries and for reducing the ecological damage to the environment.

The purpose of this paper is to develop a research model for understanding the relationship between service quality dimensions and demographic variables, and the willingness to use e-government services in Oman. Understanding the key determinants of electronic government (e-government) services is an important issue for enhancing the degree of use of these services by users.

The data were collected using Google forms from 248 e-government service users. The hierarchical regression analysis was used to test the research model.

The results showed that service quality dimensions, namely, reliability, security, efficiency and responsiveness, were the key determinants that influenced the willingness to use e-government services. In addition to service quality dimensions, two demographic variables, namely, age and education level of respondents, showed a statistically significant relationship with the willingness to use e-government services.

The findings of this study provide useful insights into the decision-makers of e-government services in Oman and similar emerging economies. At the same time, these findings can also be used by academicians and information systems researchers for further research.

This study is probably the first attempt to model e-government services on the basis of service quality dimensions and demographic variables in Gulf Cooperation Council countries. Moreover, this study will enrich the existing literature on the adoption of e-government services.

The purpose of this paper is to understand the factors influencing adoption of internet banking in urban India.

A model has been proposed based on the technology acceptance model (TAM). The proposed model is referred to as extended TAM and is better suited to identify and quantify the important factors that influence adoption of internet banking technology in India. Primary data relating to the variables affecting technology adoption and demographic profile are collected using a questionnaire survey. Data were collected from 344 individuals who are either current/prospective internet banking users. Structural equation modeling was used to identify the important factors affecting internet banking technology adoption.

The factors of perceived usefulness, perceived ease of use, social influence, awareness, quality of internet connection and computer self-efficacy are primary determinants of the attitude toward the use of internet banking in urban India. The attitude toward the use of internet banking can be used to predict the intention to use internet banking systems by users.

This research enables internet banking service providers in urban India to design new service offerings or modify current service offerings to achieve higher adoption rates in internet banking.

The paper investigates the adoption of internet technologies by banking users by proposing an extended TAM model that is more appropriate to capture the issues related to adoption in urban India. The paper is of value to researchers in the area of technology adoption and banking service providers in urban India.