Consumer acceptance of social recommender systems in India

Virdi, Preeti; Kalro, Arti D.; Sharma, Dinesh

doi:10.1108/oir-05-2018-0177

Cited by 13 publications

(28 citation statements)

References 105 publications

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“…Different from the traditional sales model, in the context of social e-commerce, the emerging sales model pays more attention to the information interaction between producers and consumers, consumers, and the generation and influence of network externalities in social networks. According to the time of rise, the existing main marketing models mainly include recommendation reward model, group purchase model, and crowdfunding model, which will be summarized in the following article [15].…”

Section: Related Research On Emerging Sales Models Of Social E-mentioning

confidence: 99%

Analysis of Consumer Recommendation Behavior and Market Equilibrium in E-Commerce from the Perspective of Social Media

Jiang

Chen

2023

Advances in Multimedia

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Under the strategic goal of building a domestic economic cycle, the development quality of social e-commerce in my country needs to be improved urgently. The main reason for the low quality of social e-commerce development in my country is that the natural advantages of social e-commerce, such as high-efficiency dissemination of information and increased consumer utility due to improper sales model design, cannot play a role. However, the lack of research on social e-commerce systems makes it difficult for retailers to obtain effective theoretical guidance for their sales model design. Based on this, this paper takes the three most important and important social e-commerce sales models in my country at present—recommended reward model, online group purchase model, and online crowdfunding model as the research objects, and systematically analyzes the consumer recommendation behaviors in the three sales models. By analyzing and market equilibrium, while improving the theoretical research of social e-commerce, it also provides theoretical basis and policy guidance for the optimal mode design of social e-commerce under different sales modes. This paper considers the consumer recommendation behavior in social networks and analyzes the main characteristics of the three sales models in view of the development status and specific problems of social e-commerce in my country, and then constructs retailer-existing consumer-potential The three-agent dynamic Stackelberg game model of consumers analyzes the influence mechanism and market equilibrium of consumer recommendation behavior under three sales models.

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Section: Related Research On Emerging Sales Models Of Social E-mentioning

confidence: 99%

Analysis of Consumer Recommendation Behavior and Market Equilibrium in E-Commerce from the Perspective of Social Media

Jiang

Chen

2023

Advances in Multimedia

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“…Additionally, Racherla and Friske (2012) found that peer recognition and reputation are fundamental aspects of maintaining trust in the fidelity of communication and information exchange when observing online product reviews. This type of social relationship effectively enhances the online recommender system (Sun et al, 2015), particularly when considering social networks of consumers (Virdi et al, 2020). Their findings showed that more trustworthy reviewers had greater influence over consumers, and this added significantly to the perceived usefulness of reviews.…”

Section: Hypotheses Developmentmentioning

confidence: 99%

How trust leads to online purchase intention founded in perceived usefulness and peer communication

Harrigan

Feddema

Wang

et al. 2021

J of Consumer Behaviour

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This study seeks to understand the specific factors on social media that help drive the intention to purchase fashion‐related products, focusing on the central role of trust. The unique contribution of this research lies in its exploration of the interplay between perceived usefulness of the fashion brand's social media and peer communication on the fashion brand's social media in driving trust in the fashion brand's social media and, ultimately, purchase intention. Theoretically, we combine the technology acceptance model and consumer socialisation theory to explore the mediating role of trust in a rapidly expanding and growing industry sector. In surveying 150 Europeans to test our hypotheses around the aforementioned concepts, findings show that the perceived usefulness of a brand's social media is impacted by a set of atmospheric cues, and it influences the level of trust in both the fashion brand and its social media channels. Peer communication also influences perceived usefulness and level of trust in both the fashion brand and its social media channels. Trust in the brand but not its social media channels impacts purchase intention. The role of privacy concerns is limited in our model. We draw implications for theory around combining consumer socialisation theory and the technology acceptance model and for managers around parallel strategies to build different sets of trust on social media.

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“…Te simulation traces in Figure 7 show that DFr leads to both CRr and CRa whereas CRr leads to CRa with a close margin. Tis suggests that recommender with this characteristic will display dissatisfaction which will make it unable to achieve the task due to reactance [101,102]. 4.…”

Section: Case Twomentioning

confidence: 99%

Computational Model of Recommender System Intervention

Ojeniyi

Ajibade

Obafunmiso

et al. 2022

Applied Computational Intelligence and Soft Computing

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A recommender system is an information selection system that offers preferences to users and enhances their decision-making. This system is commonly implemented in human-computer-interaction (HCI) intervention because of its information filtering and personalization. However, its success rate in decision-making intervention is considered low and the rationale for this is associated with users’ psychological reactance which is causing unsuccessful recommender system interventions. This paper employs a computational model to depict factors that lead to recommender system rejection by users and how these factors can be enhanced to achieve successful recommender system interventions. The study made use of design science research methodology by executing a computational analysis based on an agent-based simulation approach for the model development and implementation. A total of sixteen model concepts were identified and formalized which were implemented in a Matlab environment using three major case conditions as suggested in previous studies. The result of the study provides an explicit comprehension on interplaying of recommender system that generate psychological reactance which is of great importance to recommender system developers and designers to depict how successful recommender system interventions can be achieved without users experiencing reactance and rejection on the system.

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Consumer acceptance of social recommender systems in India

Cited by 13 publications

References 105 publications

Analysis of Consumer Recommendation Behavior and Market Equilibrium in E-Commerce from the Perspective of Social Media

Analysis of Consumer Recommendation Behavior and Market Equilibrium in E-Commerce from the Perspective of Social Media

How trust leads to online purchase intention founded in perceived usefulness and peer communication

Computational Model of Recommender System Intervention

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