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Purpose – The advent of mobile telephony devices with strong internet capabilities has laid the foundation for mobile commerce (m-commerce) services. The purpose of this paper is to empirically examine predictors of m-commerce adoption using a modification of the widely used technology acceptance model and the unified theory of acceptance and use of technology model. Design/methodology/approach – The data were collected from 213 respondents by means of an online survey. The data were analyzed through multi analytic approach by employing structural equation modeling (SEM) and neural network modeling. Findings – The SEM results showed that variety of services, social influence, perceived usefulness, cost and perceived trust have significant influence on consumer’s intention to adopt m-commerce. The only exception was perceived ease of use which observed statistically insignificant influence on adoption of m-commerce. Furthermore, the results obtained from SEM were employed as input to the neural network model and results showed that perceived usefulness, perceived trust and variety of services as most important predictors in adoption of m-commerce. Practical implications – The findings of this study give an insight of key determinants that are important to develop suitable strategic framework to enhance the use of m-commerce adoption. In addition, it also provides an opportunity to academicians and researchers to use the framework of this study for further research. Originality/value – The study is among a very few studies which analyzed m-commerce adoption by applying a linear and non-linear approach. The study offers a multi-analytical model to understand and predict m-commerce adoption in the developing nation like India.

Purpose 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. Design/methodology/approach Data were collected through a structured survey from 208 Omani Mbanking users and analysed using a two-staged regression and neural network (NN) model. Findings 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. Practical implications 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. Originality/value 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.

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Mobile applications are becoming a preferred delivery method for the government sector and contributing to more convenient and timely services to citizens. This study examines the intention to use mobile applications for the government services (mG-App) in Oman. This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) model by including two constructs namely trust and information quality. Data were collected from 513 mobile application users across Oman. The research model was analyzed in two stages. First, structural equation modelling (SEM) was employed to determine significant determinants affecting users' acceptance of mG-App. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of determinants of acceptance of mG-App. The findings revealed that trust and performance expectancy are the strongest determinants influencing the acceptance of mG-App. The findings of this research have provided theoretical contributions to the existing research on mG-App and practical implications to decision-makers involved in the development and implementation of mG-App in in Oman.

Purpose 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. Design/methodology/approach The study uses neural network to analyze the antecedents/antecedents × religiosity → PECB relationships by using a sample of 306 consumers from Oman. Findings 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. Research limitations/implications 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. Practical implications 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. Social implications 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. Originality/value 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.

This study develops a new research model to understand and predict the key determinants influencing the adoption of mobile payment services in a Middle Eastern country, Oman. The research model was tested using a hybrid structural equation modeling (SEM) and neural network (NN) modeling. The findings suggest valuable insights to the mobile payment service providers in the development of appropriate and effective strategy to raise the number of new consumers in Oman.