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RISS 인기검색어
- 검색키워드
- 저자 : Laszlo Sajtos (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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USE OF ONLINE FEATURES FOR ONLINE COMPLAINT: IMPLICATIONS ON THE WELL-BEING OF CONSUMERS AND FIRMS
Yean Shan Beh,Laszlo Sajtos 글로벌지식마케팅경영학회 2018 Global Marketing Conference Vol.2018 No.07
It is a fact that the present online technologies have empowered consumers not only to share their positive service experiences they have had with a firm on the Internet, but also to express their negative views online via multiple platforms by using varied online communication features (OCFs) (e.g. status updates, comments, chats, reviews, and feedback forms). With that, this study employed the concept of online features affordances, such as response expectation, identifiability (of complainants), and content visibility, based on a novel conceptualization through the lens of uses and gratifications (U&G) theory from a varied perspective. Hence, by modelling consumers’ motivation to complain about brand via online in conjunction with the selected OCF affordances, this study investigated their joint impact on consumers’ emotions and intentions towards the defaulting firm upon making an online complaint. The data were analysed by using correspondence analysis and structural equation modelling approaches. As a result, this study revealed that consumers’ motivation to complain and their interactions with affordances (but not the affordances themselves) exemplify a significant effect upon influencing the intention towards the (defaulting) firm after disclosing a negative service incident. In particular, content visibility and response expectation appear to display an impact on redress-seeking and egoistic complainants, respectively. These findings, hence, provide relevant insights for firms to manage their complaint channels and to address online customer feedback in a more effective manner for mutual benefits. Furthermore, this study happens to be the first of its kind to weigh in OCFs as the concerned media and further proposes a design-based affordance view of OCFs in explaining their influence on both consumers and brands.
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CUSTOMERS’ RESOURCE INTEGRATION PRACTICES FOR ONLINE COMPLAINTS
Yean Shan Beh,Laszlo Sajtos 글로벌지식마케팅경영학회 2018 Global Marketing Conference Vol.2018 No.07
Failure in servicing has detrimental effects upon customers, which can be translated into loss of resources. As such, this study employed the conservation of resources (COR) theory and developed a novel conceptualization that captures customers’ resource losses (after a failure), as well as their complaint process, by capturing dynamic loss, activation, and recovery of customers’ resources, in the case of a service failure. The use of online features and platforms for customers to voice their complaints was conceptualised as resource integration between the customer and the firm. The outcomes revealed online complaining as self-protective and selfenhancement behaviour. It is also unravelled in this study that various personal- and firm-related resource integrations in an online complaining context could result in varying emotional states and behavioural intentions among the affected customers towards the defaulting firm. These results open up an avenue for firms to devise effective intervention strategies.
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Ben Voyer,Marion Sangle Ferriere,Laszlo Sajtos,Billy Sung 글로벌지식마케팅경영학회 2023 Global Marketing Conference Vol.2023 No.07
Service encounters increasingly feature AI-powered inputs such as add-ons recommendations or aftercare solutions. These novel forms of customer service, provided by AI rather than humans, can shape customers’ sense of agency throughout the customer journey. Customers find themselves in a form of competitive collaboration with AI, sharing tasks, resources, inputs, and decisions. This research conceptualises and develops a scale to measure shared agency power during customer-AI interactions. Understanding the role of agency in AI- customer interactions is important, as agency represents a source, mechanism, delimiter and effect of a human’s or a machine’s actions. Agency may differ across various service encounters and with it, the type of perceived risks associated with human-AI interactions. Future research may use the shared agency power scale to better understand the nature and impact of customer-AI interactions in a service context on traditional marketing factors.
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