Consumer adoption of mobile shopping apps is an emerging area in m-commerce which poses an interesting challenge for retailers and app developers. In this study, we adapt the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to investigate factors predicting consumer behavioral intention (BI) and use behavior (UB) towards mobile shopping apps, considering the impact of two manifestations of consumer's perceived risk: Privacy Risk and Security Risk. Because cultural characteristics may moderate the impact of these risks on behavioral intention and use behavior, we conduct two studies from two consumer panels from countries with significant difference in technology use as captured by the Computer-Based Media Support Index (CMSI), namely India (high CMSI) and USA (low CMSI). For both countries, the baseline UTAUT 2 constructs predict the Behavioral Intention to use mobile shopping apps (and subsequently use behavior). However, the manifestations of perceived risk are significant only for the country with the highest CMSI score, suggesting that cultural influences play a strong role in the adoption of m-shopping. Our study has practical implications for theory as it poses the use of m-shopping apps in a cross-cultural context, suggesting that privacy and security moderate intention to use differently across cultures as predicted by the CMSI. From that perspective, it also has practical implications for consumer behavior researchers and app developers challenged with app localization as well as retailers designing mobile shopping apps for an intercultural audience.
As research on smart cities garners increased attention and its status consolidates as one of the fanciest areas of research today, this paper makes a case for a cautious rethink of the very rationale and relevance of the debate. To this end, this paper looks at the smart cities debate from the perspectives of, on the one hand, citizens' awareness of applications and solutions that are considered 'smart' and, on the other hand, their ability to use these applications and solutions. Drawing from a detailed analysis of the outcomes of a pilot international study, this paper showcases that even the most educated users of smart city services, i.e., those arguably most aware of and equipped with skills to use these services effectively, express very serious concerns regarding the utility, safety, accessibility and efficiency of those services. This suggests that more pragmatism needs to be included in smart cities research if its findings are to remain useful and relevant for all stakeholders involved. The discussion in this paper contributes to the smart cities debate in three ways. First, it adds empirical support to the thesis of 'normative bias' of smart cities research. Second, it suggests ways of bypassing it, thereby opening a debate on the preconditions of sustainable interdisciplinary smart cities research. Third, it points to new avenues of research.
The impact of the generalized pattern search algorithm (GPSA) on power system complete observability utilizing synchrophasors is proposed in this work. This algorithmic technique is an inherent extension of phasor measurement unit (PMU) minimization in a derivative-free framework by evaluating a linear objective function under a set of equality constraints that is smaller than the decision variables in number. A comprehensive study about the utility of such a system of equality constraints under a quadratic objective has been given in our previous paper. The one issue studied in this paper is the impact of a linear cost function to detect optimality in a shorter number of iterations, whereas the cost is minimized. The GPSA evaluates a linear cost function through the iterations needed to satisfy feasibility and optimality criteria. The other issue is how to improve the performance of convergence towards optimality using a gradient-free mathematical algorithm. The GPSA detects an optimal solution in a fewer number of iterations than those spent by a recursive quadratic programming (RQP) algorithm. Numerical studies on standard benchmark power networks show significant improvement in the maximum observability over the existing measurement redundancy generated by the RQP optimization scheme already published in our former paper.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.