The impact of digital image-based features on users' emotions and online behaviours in the food industry

活力 叙事性 独创性 社会化媒体 实证研究 心理学 符号学 数字媒体 身份(音乐) 认知心理学 社会心理学 计算机科学 叙述的 万维网 美学 创造力 哲学 语言学 物理 认识论 量子力学
作者
Grazia Murtarelli,Stefania Romenti,Chiara Valentini
出处
期刊:British Food Journal [Emerald Publishing Limited]
卷期号:124 (1): 31-49 被引量:13
标识
DOI:10.1108/bfj-12-2020-1099
摘要

Purpose Online images can convey sensory-based elements affecting digital users' emotions and digital engagement. The purpose of this study is to investigate which image-based features are more effective in conveying and stimulating particular emotions and engagement towards organizations operating in the food industry. Design/methodology/approach An online experimental survey was implemented. Two image-based features, narrativity and dynamism were chosen. The stimuli comprise four images, one with high and one with low level of narrativity, and one with high and one with low dynamism, published by a food company on its official Instagram account. Food-identity, emotional appeals and digital visual engagement behaviours were measured. A total of 141 students between 19 and 25 years old of a European University completed the questionnaire. Data was analysed through SPSS software using t -test analysis. Findings Results show that both narrativity and dynamism impact digital users' emotions and it was found to impact digital visual engagement attitude. Food involvement was measured in terms of food identity impact the effects of specific image-based features on emotions and visual engagement. Research limitations/implications The study focuses on only two visual social semiotics features – narrativity and dynamism – and therefore, only partially captures the potentialities of images in digital communications. Practical implications This study provides professionals with empirical evidence and insights for effectively planning a visual social media strategy. Originality/value This paper contributes to the stream of research in social media communications by investigating the visual social semiotic features of images published online by a food company.

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