Journal of Asia-Pacific and European Business

A Research on the Impact of Advertising Slogans’ Attributes on Consumer Purchase Intention

Shipei Zhang — Sun, 24 Nov 2024 00:00:00 -0600

Advertising serves as a bridge between products and consumers. As a means of publicity, the ultimate goal of advertising is to cater to both the psychology and needs of consumers. The promotion of the product is the focal point of any marketing strategy. When designing advertisements, businesses should consider not only whether the content aligns with the product's characteristics but also how consumers perceive the advertisement's content. This paper, therefore, aims to study the effects of various attributes of advertising slogans on consumers' willingness to purchase, considering product types (hedonic, practical, and neutral) and focusing on a key element of advertising content: the slogan. Through this study, the paper concludes the following: the attributes of advertising statements for different product types significantly influence consumer attitudes and purchase intentions. Consumers respond more positively to emotional advertising statements for hedonic products, while rational statements are more effective for practical and neutral products. Moreover, consumer attitudes fully mediate the relationship between advertising statement attributes and purchase intentions for each product type. Thus, consumers are more inclined to purchase hedonic products paired with emotional slogans and practical or neutral products paired with rational slogans. Additionally, the sentence structures of different slogan attributes impact consumers' purchase intentions. For emotional slogans, consumers prefer imperative sentence types; for rational slogans, they favor non-invocative sentence types. This paper explores factors affecting consumers' purchase intentions from both a product and linguistic perspective, aligning with market needs and offering valuable insights for businesses' marketing decisions.

Research on the Impact of Executive Remuneration and Independent Director Ratio on Corporate Performance in Listed Companies

Yuyi Zhu, Jian Li — Thu, 31 Oct 2024 00:00:00 -0500

This paper evaluates the impact of executive remuneration and the ratio of independent directors on corporate performance, using data from listed companies from 2008 to 2019. The findings reveal that (1) executive remuneration is significantly and positively related to corporate performance, while the ratio of independent directors is significantly and negatively associated with corporate performance. Higher executive remuneration notably enhances corporate performance, whereas a larger proportion of independent directors appears to correlate with a decline in corporate performance. (2) Regarding the underlying mechanism, Tobin's Q plays both a full and partial mediating role in the effects of executive remuneration and the ratio of independent directors on corporate performance, respectively. (3) Heterogeneity analysis shows that the positive impact of executive remuneration on corporate performance is more pronounced in state-owned listed firms than in non-state-owned listed firms. Lastly, based on both empirical and theoretical research, this paper proposes recommendations to help improve corporate performance and foster competitive advantages for enterprises.

A Corpus-based Diachronic Study on the Linguistic Variation of Corporate Annual Reports from the Real Estate Industry in China

Chaowang Ren, Zixu Chen, Wanting Huang, Cannan Chen, Rui Guo — Sat, 09 Nov 2024 00:00:00 -0600

This project compiles a comprehensive corpus by collecting annual reports from Chinese listed companies over multiple years. Based on the characteristics of these reports, the study examines historical trends, industry-specific variations, and differences between Chinese and Western cultural contexts to identify key factors influencing the translation of annual reports in China. It conducts a multi-level analysis of these reports and summarizes the forms and distribution of related events. Tools like AntConc, WordSmith, and other corpus analysis software are used to examine the data. Finally, the study makes reasonable predictions regarding potential future trends based on the research findings.