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1 – 2 of 2Yajun Zhang, Zhuoyan Shao, Jin Zhang, Banggang Wu and Liying Zhou
Facilitated by image retouch tools, social media influencers can digitally enhance their self-image in product recommendation posts. This paper proposes that image enhancement may…
Abstract
Purpose
Facilitated by image retouch tools, social media influencers can digitally enhance their self-image in product recommendation posts. This paper proposes that image enhancement may serve as a cue for the audience to assess the authenticity of the influencer (“true to oneself”), which further affects the influencer's product recommendation effectiveness (i.e. attitudes toward the post and recommended product).
Design/methodology/approach
Experiment 1 examines the effect of image enhancement on consumers' perceived influencer authenticity and product recommendation effectiveness. Experiment 2 considers the moderating role of post type, examining the effects in informational versus storytelling posts.
Findings
Consumers perceived an influencer to be more authentic when the image is not enhanced; in turn, consumers reported more favorable attitudes toward the post and the recommended product upon reading the post. The effects are moderated by post type: the effect of image enhancement (through perceived influencer authenticity) exists in posts using an informational message format but is attenuated for those using a storytelling message format.
Originality/value
This research enriches the literature on authenticity cues by documenting a novel visual cue and contributes to influencer marketing by identifying a nuanced interactive effect between image enhancement and post type on recommendation effectiveness.
Details
Keywords
Manuel Pedro Rodríguez Bolívar and Laura Alcaide Muñoz
This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging…
Abstract
Purpose
This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.
Design/methodology/approach
VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.
Findings
The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.
Practical implications
The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.
Social implications
The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.
Originality/value
Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.
Details