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This paper conducts a Systematic Literature Review (SLR) of Machine Learning (ML) in Supply Chain Management through bibliometric and network analysis, the authors are able to grasp key features of the contemporary literature. The study makes use of state-of-the-art analytical framework based on a unified approach to reveal insights from the present body of knowledge and the potentials for future research developments.

Unlike standard literature reviews, in SLR, a structured approach is followed. The approach enables utilizing contemporary tools and software packages such as R-package “bibliometrix” and Gephi for exploratory and visual analytics. A number of clustering methods are employed to form clusters. Later, multivariate analysis methodologies are adopted to determine the dominant clusters for the influential co-cited references.

Using contemporary tools from Bibliometric Analysis (BA), the authors identify in an exploratory analysis, the influential authors, sources, regions, affiliations and papers. In addition, the use of network analysis tools reveals research clusters, topological analysis, key research topics, interrelation and authors’ collaboration along with their patterns. Finally, the optimum number of clusters computed for cluster analysis is decided using a systematic procedure based on multivariate analysis such as k-means and factor analysis.

Modern-day supply chains increasingly depend on developing superior insights from large amounts of data available from diverse sources in unstructured and semi-structured formats. In order to maintain a competitive edge, the supply chains need to perform speedy analysis of big data using efficient tools that provide real-time decision-making insights. Such an analysis necessitates automated processing using intelligent ML algorithms. Through a BA followed by a detailed data visualization in a network analysis enabled grasping key features of the contemporary literature. The analysis is based on 155 documents from the period 2008 to 2018 selected using a systematic selection procedure.

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.

More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.

The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.

This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.

The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.

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 paper is to understand the customer perception of service quality with respect to the e-Government services in Oman and conduct an investigation in order to determine the key factors that affect the quality of e-Government services in Oman.

Primary data relating to the variables affecting quality of e-Government services and demographic profile data are collected using a questionnaire survey. The questionnaire was designed based on literature review and focus groups. Factor analysis method is employed to identify and rank the important factors affecting service quality.

The study found that the four factors listed in the descending order of importance, reliability, responsiveness, efficiency, and security are primary determinants of the quality of e-Government services in Oman.

This research enables government organizations to enhance their understanding of customer perception of e-Government services. The customer preference information can provide useful direction to the design, implementation, and management of e-Government services.

Improved service quality of e-Government systems can enhance public participation in these systems that have been established with huge investments. The improved participation can result in increased levels of efficiency, convenience, public awareness, transparency, engagement, and information for decision-making.

The paper addresses quality of e-Government services for the first time in Oman and in the gulf region using a carefully designed research study. The paper is of value to researchers in the area of service quality of e-Government, Government of Oman, and governments in the gulf region and other developing countries that are involved in designing and managing e-Government service systems.

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.

The purpose of this paper is to explore the main determinants of Internet banking users on the basis of literature of technology acceptance model (TAM). Understanding and predicting main determinants of Internet banking is an important issue for banking industry and users.

Service quality and trust were incorporated in the TAM together with demographic variables. The data were collected using Google Docs from 110 Omani Internet banking users. A two-staged regression-neural network model was applied to understand and predict Internet banking adoption.

The results obtained from multiple linear regression model were compared with the results from neural network model to predict Internet banking adoption and the performance of latter model was found to superior. The neural network model was able to capture relative importance of all independent variables, service quality, trust, perceived usefulness, perceived ease of use, attitude and demographic variables, whereas perceived ease of use and demographic variables were not significant predictors of Internet banking adoption as per the regression model.

This study provides useful insights with regard to development of Internet banking systems to banking professionals and information systems researchers in Oman and similar emerging economies.

This study is probably the first attempt to model Internet banking adoption in Gulf Cooperation Council using a predictive rather than explanatory focus. The majority of studies in Internet banking adoption in Oman and elsewhere usually utilize modeling methods suited for explanatory purposes.

This paper aims to understand the interrelationships between the various factors that affect the use of course Web sites by university students in a developing country. The factors considered for the purpose of studying these interrelationships include perceived usefulness, perceived ease of use, perceived Web site credibility and Web site learning acceptance and satisfaction. Furthermore, a comparative study of the potential differences in perceptions between Indian and Omani students with respect to the aforementioned factors is also presented.

A survey instrument was used to collect data from students. Based on an extensive literature review, this paper uses empirical research to analyze student satisfaction in relation to learning through course Websites. Data were analyzed using factor analysis, structural equation modeling and a t-test.

Under the newly proposed construct, Web site credibility was found to be an important predictor of Web site learning acceptance and satisfaction, whereas perceived usefulness and perceived ease of use were mediating variables. In the extended study that compared the relative perceptions of Indian and Omani students, a statistically significant difference in Indian and Omani students was observed for Web site learning acceptance and satisfaction.

This study can provide valuable insights for decision-makers that will aid the development of more user-friendly course Web sites for higher education institutions and also promote higher levels of learning, satisfaction and greater course web site usage.

This study is probably the first attempt made to observe students’ perceptions of learning via course Web sites in Oman. Furthermore, the use of perceived Web site credibility as a factor in understanding perceptions regarding course Web site learning is a unique feature presented by this paper that is seldom seen in the existing research literature.

The purpose of this paper is to investigate the quality determinants influencing the adoption of e-government services in Oman and compare the performance of multiple regression and neural network models in identifying the significant factors influencing adoption in Oman.

Primary data concerning service quality determinants and demographic variables were collected using a structured questionnaire survey. The variables selected in the design of the questionnaire were based on an extensive literature review. Factor analysis, multiple linear regression and neural network models were employed to analyze data.

The study found that quality determinants: responsiveness, security, efficiency and reliability are statistically significant predictors of adoption. The neural network model performed better than the regression model in the prediction of e-government services’ adoption and was able to characterize the non-linear relationship of the aforementioned predictors with the adoption of e-government services. Further, the neural network model was able to identify demographic variables as significant predictors.

This study highlights the importance of service quality in the adoption of e-government services and suggests that an enhanced focus and investment on improving quality of the design and delivery of e-government services can have a positive impact on the usage of the services, thereby enabling the Oman Government in achieving the governance objectives for which these technologies were employed.

Studies in the area of e-government typically focus either on technology adoption problems or service quality problems. The role of service quality in adoption is rarely addressed. The research presented in this paper is of great value to the institutions that are involved in the development of technology-based e-government services in Oman.