| dc.description.abstract | Mobile shopping only relates to specific elements of the purchase process, mostly in business-to-consumer and consumer-to-consumer scenarios. M-shopping is one of the most popular online pastimes in the world, with e-commerce sales reaching 4.28 trillion US dollars globally in 2020 and revenues predicted to reach 5.4 trillion US dollars in 2022. Mobile commerce (M-commerce) diverges from traditional electronic commerce (E-commerce) due to disparities in its user interface and the correlated factors of risk, interactivity, ubiquity, localization services, and patterns of usage. Social media is influencing consumer purchase decisions more and more, overshadowing conventional opinions on goods and services. This study sought to assess proximity and route map with regard to consumers’ M-shopping behavior in Kenyas Nairobi Metropolitan Region. The objectives of the study were; to investigate place convenient modelled in the current m-shopping applications, to examine the influence of proximity and route map in the current m-shopping applications and to model proximity and route map in an m-shopping application. A cross-sectional research design was adopted and a sample size of 106 respondents determined using a simple random sampling technique. The primary data was collected through structured survey questionnaires, after which, STATA software was used for its analysis. The study established a statistically significant relationship between the convenient in m-shopping applications and consumer’s m-shopping behaviour (ꭕ2=6.370a, p=.041<0.05). A statistically significant relationship between the proximity in the current m-shopping applications and consumer’s m-shopping behaviour was also noted (ꭕ2=13.234a, p=.001<0.05). Further, it established a positive statistically significant relationship between the route map in the current m-shopping applications and consumer’s m-shopping behaviour (ꭕ2=72.192a, p=.000<0.05). Analyzing the influence of proximity distance on consumer’s behavior revealed that, consumers tend to favor businesses located closer to their current location when making buying decisions through m-shopping applications. Further, provision of vendor-consumer real-time navigation assistance would enhance consumer’s behavior. Despite the high deployment of mobile shopping applications, less attention is given to the proximity distance and route map aspects in the mobile shopping landscape. Consequently, this negatively impacts on the consumer’s m-shopping behavior. Besides, this study serves as an intervention target for improving the consumer’s behavior. It’s therefore recommendable that the developers should adopt a holistic and consumer-vendor centered approach to mobile applications. In addition, implementation studies should be employed to test this model and identify other factors that may be useful to effectively improve on the m-shopper’s behavior. Future research opportunities lie in exploring advanced technologies such as augmented reality (AR) integration with route maps in M-Shopping applications or analyzing data-driven approaches for personalized recommendations based on both proximity distance and historical buying patterns. By continuously evolving strategies informed by consumer behavior analysis within M-Shopping applications, businesses can stay ahead in meeting the dynamic needs of tech-savvy consumers in markets like Nairobi Metropolitan where digital innovation continues to drive shopping trends forward. | en_US |
