Zoran Kalinic

Determinants of users' intention to adopt m-commerce: an empirical analysis

Abstract The fast-growing penetration of mobile devices and recent advances in mobile technologies have led to the development of increasingly sophisticated services such as m-shopping for goods or services and m-payment. However, although the number of mobile subscribers is increasing, levels of actual m-commerce activities in many cases remain low. Determining what influences users’ intention to use m-commerce is therefore of growing importance. The purpose of this study was to investigate possible factors. To this aim, we developed a conceptual user adoption model based on technology acceptance model variables and on specific factors such as social influence, personal innovativeness, customization, and individual mobility. The empirical results show that social influence and customization significantly affect perceived usefulness; mobility, customization, and personal innovativeness significantly affect perceived ease of use; and perceived usefulness and perceived ease of use have a direct positive effect on behavioral intention.

Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization

Purpose The purpose of this paper is to determine statistically significant drivers of customer satisfaction in mobile commerce and to test the moderating effects of customization on the relationships between customer satisfaction and its predictors. Design/methodology/approach The sample comprised 224 respondents. Confirmatory factor analysis was used to test the validity of the model, and moderated regression analysis was applied to determine main and interaction effects. Findings Trust, perceived usefulness, mobility, and perceived enjoyment were found to be significant drivers of customer satisfaction. The results also indicate the statistical significance of two interaction effects: customization moderates the influence of mobility and the influence of trust on customer satisfaction. Research limitations/implications The study was conducted in a single time period and in a developing country where m-commerce is still not widely used. Future models should include new variables. Comparison between different age or gender groups would also be useful. Practical implications The findings are useful for m-commerce providers who are developing marketing campaigns, where the focus should be on promoting the mobility aspect of m-commerce, in particular its usefulness to consumers and its security. M-commerce activities should be developed and redesigned to better meet consumers’ specific demands and needs. Originality/value M-commerce customer satisfaction studies are rare. The developed model has five potential antecedents of satisfaction: trust, social influence, perceived usefulness, mobility, and perceived enjoyment. New insights are provided into the moderating role of customization.

Supplier Selection using NSGA-II Technique

In modern manufacturing industries, supplier selection is increasingly recognized as a critical decision in supply chain management. Supplier selection problem is a typical multiple criteria decision making problem involving a number of different and usually conflicting objectives. Because of that, modern supplier selection techniques imply solving of multi-objective optimization problems. In this paper supplier selection using evolutionary algorithm (NSGA-II method) is presented. Recent investigations show that quality and costs are among the most important selection factors. In this paper the authors used variance of quality and total costs as criteria for selection optimization. Results show that described methodology can be applicable for the practical purposes. DOI: 10.4018/jwp.2012100103 36 International Journal of Web Portals, 4(4), 35-47, October-December 2012 Copyright

Supplier Selection Using Multiobjective Evolutionary Algorithm

Supplier selection is one of the most critical activities of purchasing management. Nowadays, supplier selection includes a number of different and usually conflicting objectives. Because of that, modern supplier selection techniques imply solving of multiobjective optimization problems. In this paper supplier selection using evolutionary algorithm (SPEA method) is presented. As criteria for selection optimization we used variance of quality and total costs. Results show that described methodology can be applicable for the practical purposes.