Kamila Sobol and Marilyn Giroux
A fear appeal is a communication tactic designed to scare people into adopting desired behaviors (e.g. wash hands to avoid contracting COVID-19). While it is generally…
Abstract
Purpose
A fear appeal is a communication tactic designed to scare people into adopting desired behaviors (e.g. wash hands to avoid contracting COVID-19). While it is generally acknowledged that fear appeals can be persuasive at motivating behavior, this paper aims to identify how to optimally identify how to optimally frame the focal threat to increase their effectiveness as well as to uncover additional underlying processes.
Design/methodology/approach
The authors conducted four experimental studies.
Findings
This research validates that exposure to fear appeals can strongly motivate behavior. However, this study shows that this effect is moderated by threat specificity. Specifically, this study demonstrates that people are more motivated to engage in behaviors that facilitate threat avoidance after exposure to a personally relevant threat that represents a nonspecific (e.g. aging appearance) rather than a specific outcome (e.g. wrinkles). This effect is mediated by perceptions of assimilation (versus contrast) to the focal threat. This study reliably shows the effect across three threat domains (i.e. aging appearance, weight gain, illness) and for different behaviors.
Originality/value
Theoretically speaking, this study contributes to the fear appeal literature by identifying a new type of message framing that has the potential to increase fear appeal’s persuasive power, and uncovering a distinct mechanism by which fear appeals impact behavior. Practically speaking, the findings confirm that fear appeals have the potential to help marketers mobilize consumer behavior, especially when the communication highlights a nonspecific rather than specific threat.
Details
Keywords
Qiuyan Zhong, Shuyuan Liang, Li Cui, Hing Kai Chan and Yue Qiu
The purpose of this paper is to analyse consumer purchasing behaviour in different cultural settings by exploring the value of consumer reviews from various countries.
Abstract
Purpose
The purpose of this paper is to analyse consumer purchasing behaviour in different cultural settings by exploring the value of consumer reviews from various countries.
Design/methodology/approach
This study uses online review mining technology to collect, process and analyse user review data from multiple countries. The main procedures of this research are data collection, data pre-processing, feature extraction and sentiment analysis. Online reviews from the American, British and Indian websites for the iPhone 5s are analysed.
Findings
Every country has unique cultural characteristics, and these cultural differences affect consumers’ perceptions, attitudes and purchasing behaviours. The results show that consumers from different countries exhibit different levels of attention towards the same product and have different emotional inclinations for the same product feature. In addition, the study also identified the advantages and disadvantages of the product.
Limitations implications
The user reviews provide abundant feedback information that serves as a good intelligence resource for companies. Under the premise of different language habits, this paper uses a universal approach to analyse consumer behaviour from online reviews in different countries, which can help reveal consumers’ emotional inclination towards each feature of a product. This approach can be extended to other brands of mobile phones or other industries.
Practical implications
Multinational companies should analyse the cultural characteristics of target groups when proposing transnational development strategies. Companies can understand the perceptions of their products based on the consumer reviews and can formulate their marketing and product strategies by considering consumer purchasing behaviours arising from cultural differences.
Originality/value
This study identifies differences in consumer behaviour in different cultural settings by using a data mining method, which can help companies understand consumer perceptions and the performance and quality of product features.