Increasing global interest in diet and fitness mobile applications (apps) has prompted the question: What are the factors affecting users’ adoption and usage behaviors on a specific fitness app? By combining the unified theory of acceptance and use of technology (UTAUT) with the health belief model (HBM), and including risk perception of information technology with the farsighted planner and myopic doer from the theory of self-control, we explore the understanding of this academic question. We analyzed data from 8,840 users of Boohee, a diet and fitness app (ranked first in the weight-loss category on the App Store in China). Structural equation modeling revealed that self-efficacy as well as the perceived benefits, barriers, and threats of weight loss significantly influence a fitness app’s performance expectancy, which, in turn, predicts users’ intention to adopt it. Furthermore, actual usage behavior (i.e., diet, exercise, weight, and login records within 30 days after respondents completed the questionnaire) is positively affected by weight-loss intention and behavioral intention to use the app and negatively affected by users’ risk perception. The main findings of this research could help healthcare practitioners and app developers find better ways to encourage people to adopt health apps for various reasons. App developers should attach more importance to users’ actual continuous use behavior than to their intention to use an app. They should provide sufficient introductory information about their apps, thereby reducing users’ risk perception and generating reasonable performance expectancy of the app, so as to improve users’ actual continuous use behavior.

With the popularity of the health and wellness trend in recent years, smartphone fitness applications have become more and more popular. Thus, this study explored factors affecting the behavioral intention to use and the actual usage behavior of smartphone fitness apps from technical, health, and social perspectives by integrating the Social Cognitive Theory (SCT) and Unified Theory of Acceptance and Use of Technology (UTAUT). We examined whether perceived usefulness, perceived ease-of-use, social influence, self-efficacy, goal-setting, and self-monitoring predict usage behavior. Based on the survey responses of 1066 smartphone fitness apps users, we revealed that all of the variables, except for self-monitoring, significantly influence usage behavior, while behavioral intention acts as a total mediator between perceived usefulness, perceived ease-of-use and usage behavior. Drawing on the research findings, we suggest that influencing behavioral intention to use a fitness app can be an effective method to increase its adoption. Therefore, app developers need to pay attention to interventions that seek to enhance the usefulness of the app, provide professional counseling, as well as an opportunity for effortless goal setting features.

This study aims to explore how consumers’ psychological factors affect their pro-environment purchasing behavior in a smog-ridden city. Based on the Protective Action Decision Model and Heuristic–Systematic Model, this study proposed a model to investigate consumers’ decision-making process in purchasing green anti-smog products. It also provided new empirical evidence for the role of personal norms on consumers’ green consumption behavior by examining the differences between two groups of consumers (i.e., green and non-green) through a multi-group path analysis. The predictions were tested using a questionnaire survey of 1,124 participants living in the Beijing–Tianjin–Hebei region of China. Results indicated that product knowledge, smog knowledge, risk perception, and systematic processing positively affected consumers’ purchase intention. In addition, the significant differences of consumers with various personal norms in purchase decision-making were found in the current study. In the green group, product knowledge positively affected consumers’ risk perceptions and systematic processing intentions. Information seeking increased their purchase intentions. However, these relationships were not significant in the non-green group. This study contributes to the existing literature by linking consumers’ protective behaviors with green consumption and providing a comprehensive model for predicting consumers’ purchase decisions.

The main purposes of government environmental policy include improving the objective natural environment as well as reducing the health risk of the public. A majority of studies have tested the means of achieving the first goal. In this paper, we aimed to gather empirical evidence pertaining to the realization of the second goal by drawing on a quasi-natural experiment that was conducted based on the “Action Plan on Air Pollution Prevention and Control” issued in 2013 (AP2013). The research data came from the tracking data of 17,766 individuals from 112 prefecture-level cities of China in 2012 and 2014. Through ordinal logistic regression and DID analysis, a causal relationship between the AP2013 policy and public health risk perceptions was verified, indicating that this policy can significantly decrease public health risk perceptions. By constructing different subsamples, an inverted U-shaped relationship between the causal effect and the length of the policy implementation window was established, which demonstrated the short-term signal effect and long-term implementation effect of this policy. The conclusions can help with the communication and implementation of a government’s policy.