Green consumers’ behavioral intention and loyalty to use mobile organic food delivery applications: the role of social supports, sustainability perceptions, and religious consciousness

AbstractConsumer behavior in the food industry has undergone significant changes in recent years, largely driven by growing consumer awareness of environmental, technological, religious, and social concerns. As a result, organic food has emerged as a popular alternative to conventionally produced food. Many emerging nations, including Bangladesh, promote its consumption due to its perceived health and safety benefits. Despite this growing trend, there remains a need for more understanding of consumer behavior, particularly concerning their motivations for continuous purchases toward mobile organic food delivery applications. In order to fill this knowledge gap, this study looks at how six indirect predictors (emotional support, informational support, environmental consciousness, religious consciousness, trust, and technological consciousness) affect customer loyalty through the intention to use organic food. This study employed a purposive sampling technique (i.e., judgmental sampling) and collected data from 386 respondents across three cities in Bangladesh. Data analysis was conducted using SmartPLS 3 software. The study found that all predictors, except for technological consciousness, significantly influenced behavioral intention, which, in turn, significantly influenced loyalty. Additionally, the study revealed that the five predictors, excluding technological consciousness, indirectly influenced loyalty through behavioral intention. The results of this study add to the existing literature on organic food by extending social support theory to include consumers' primary motivations, such as environmental, religious, technological, and social consciousness, as predictors of loyalty to use mobile organic food delivery applications. The study highlights the importance of sustainable food consumption in promoting environmental protection, ensuring social justice, creating economic success, and providing valuable insights for implementers looking to expand the organic food market. Graphical abstract</jats:p

An empirical recommendation framework to support location-based services

© 2020 by the authors. The rapid growth of Global Positioning System (GPS) and availability of real-time Geo-located data allow the mobile devices to provide information which leads towards the Location Based Services (LBS). The need for providing suggestions to personals about the activities of their interests, the LBS contributing more effectively to this purpose. Recommendation system (RS) is one of the most effective and efficient features that has been initiated by the LBS. Our proposed system is intended to design a recommendation system that will provide suggestions to the user and also find a suitable place for a group of users and it is according to their preferred type of places. In our work, we propose the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm for clustering the check-in spots of the user's and user-based Collaborative Filtering (CF) to find similar users as we are considering constructing an interest profile for each user. We also introduced a grid-based structure to present the Point of Interest (POI) into a map. Finally, similarity calculation is done to make the recommendations. We evaluated our system on real world users and acquired the F-measure score on average 0.962 and 0.964 for a single user and for a group of user respectively. We also observed that our system provides effective recommendations for a single user as well as for a group of users

Understanding the Predictors of Rural Customers’ Continuance Intention toward Mobile Banking Services Applications during the COVID-19 Pandemic

The purpose of this study is to examine the antecedents of customers’ continuance intention to use mobile banking services applications (MBSAs) during the COVID-19 pandemic. Grounding on the Technology Acceptance Model, Theory of Planned Behavior, and Cognitive Load Theory, an integrated conceptual framework was proposed and tested incorporating psychological factors (i.e., cyberchondria, perceived anxiety) and situational factors (i.e., social distance, institutional support). Data were collected from 250 rural customers and analyzed with Structural Equation Modeling. The results showed that subjective norms, perceived ease of use, social distance, attitudes, cyberchondria, and institutional support influenced users’ continuance intention. Moreover, the results showed that perceived anxiety, subjective norms, perceived ease of use, and perceived usefulness influenced users’ attitudes. Besides, the findings suggested that attitudes mediate the influence of subjective norms, usefulness, ease of use, and social distance on users’ intention. This study is unique in terms of investigating pandemic-specific psychological and situational factors in explaining consumers’ continuance intention. Therefore, the service providers and professionals should be cautious in designing MBSAs so that consumers’ usage behaviors may not vary during an unprecedented situation (e.g., COVID-19). The theoretical and practical implications were discussed

Evaluating the Determinants of Customers’ Mobile Grocery Shopping Application (MGSA) Adoption during COVID-19 Pandemic

The study aims at determining the predictors of mobile grocery shopping applications (MGSAs) acceptance and their impact on behavioral intention to use MGSA during COVID-19 outbreaks. Based on the technology acceptance model and theory of planned behavior, we analyzed the influence of social distancing, fear of COVID-19, subjective norms, shopping attitudes, ease of use, usefulness on behavioral intention to use MGSAs. Data were collected from 565 users and analyzed with structured equation modeling (SEM) using SMART PLS 3 software. Findings depicted that shopping attitudes were predicted by subjective norms, ease of use, and usefulness. In contrast, behavioral intention is predicted by subjective norms, attitudes, ease of use, usefulness, fear of COVID-19, and social distancing. The study contributes to the extant literature incorporating fear of COVID-19 and social distancing as psychological and situational variables into the technology acceptance model and theory of planned behavior, which may guide the marketing practitioners to promote online sales in an unprecedented situation