Abstract

This study examines the effect of the booth Recommender system (BRS) embedded in a mobile device on the goals of exhibition attendees, based on two main theories that are unplanned behaviour and goal frame theories. Previous studies have overlooked the importance of the unplanned behavioural effectiveness of IT devices for understanding motivation and delivering unexpected outcomes at exhibitions. The BRS offers customized, personalized, and advanced information to attendees; experiences with the BRS lead to unplanned behaviour. In this paper, we distinguish several goal frames, including hedonic, gain, and normative goals, which contribute to the relationship between continued BRS use and unplanned booth visits. Continued BRS use directly influences revisit intentions to an exhibition and contributes to unplanned booth visits. We analysed data from 508 attendees at a franchise exhibition using structural equation modelling (SEM) method. Our research empirically determined that goal framing theory and unplanned behaviour via continued BRS use embedded in a mobile device are connected. Continued BRS use in an exhibition can contribute to attendees’ impulsive behaviour and can induce them to return to an exhibition. The results and implications are discussed.

Highlights

  • Recommender systems can provide more specific, detailed, and personalised service than at any other time in history through web-based and smart devices

  • This study focused on whether exhibition attendees’ adoption of the booth Recommender system (BRS) embedded in a mobile device leads to their revisit intention to exhibitions

  • Exhibition attendees’ points of view regarding the BRS were segmented into three types based on goal framing theory; perceived enjoyment, perceived usefulness, and threats to freedom of choice, which represent the hedonic goal, the gain goal, and the normative goal, respectively. These three goals were found to have a significant influence on both continued BRS use embedded in a mobile device and unplanned booth visits

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Summary

Introduction

Recommender systems can provide more specific, detailed, and personalised service than at any other time in history through web-based and smart devices. Recommendation mechanisms are becoming increasingly critical in supporting customised and personalised service for consumers’ and end users’ decision-making processes by providing expertise to select appropriate and optimal options [1]. Due to this strength of Recommender systems, they might support the growth and sustainability in each industry to which these these recommendation mechanisms have been applied. In spite of Recommender mechanisms being spread to numerous branches of an individuals’ life, their effectiveness should be investigated through assorted approaches, due to the fact that people may be inclined to avoid Recommender systems in favour of freedom of choice.

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