Beyond the post: an SLR of enterprise artificial intelligence in social media DOI Creative Commons

Luis-Alfonso Maldonado-Canca,

Ana María Casado Molina, Juan-Pedro Cabrera-Sánchez

et al.

Social Network Analysis and Mining, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 20, 2024

Abstract This study explores the impact of artificial intelligence (AI) on brand communication within corporate social networks, analyzing its benefits, ethical and technical challenges, proposing responsible implementation strategies enriched with new theoretical contributions. To achieve this, a systematic literature review (SLR) was conducted based SPAR-4-SLR methodology by Paul et al. (2021), using 57 studies from Scopus Web Science over past six years. approach complemented recommendations Kitchenham Charters (2007) to ensure rigor thoroughness in analysis. The reveals that transforms interactions networks enabling effective personalization, optimizing customer experience, enhancing satisfaction. Benefits include precise segmentation, predictive analytics, service optimization through chatbots. However, significant challenges also emerge, such as data privacy, algorithmic bias, lack transparency AI models. necessity for practices regulations foster user trust mitigate risks associated digital is emphasized.

Language: Английский

Promoting sustainable development goals through generative artificial intelligence in the digital supply chain: Insights from Chinese tourism SMEs DOI Open Access
Shaofeng Wang, Hao Zhang

Sustainable Development, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 31, 2024

Abstract Interdisciplinary advancements, such as generative artificial intelligence (AI) and digital supply chains, can significantly contribute to achieving sustainable development goals (SDGs), particularly within tourism. This paper illuminates how it works well, focusing on the underexplored area of Environmental, Social, Governance (ESG) performance small medium‐sized tourism enterprises (SMEs) in China. Through a survey 429 international SMEs, we apply Resource‐Based View Dynamic Capabilities Theory investigate AI, ChatGPT, chains enhance innovation, collaboration, and, ultimately, ESG performance. The empirical findings underscore pivotal role AI augmenting via bolstering innovation collaboration chains. Additionally, moderating effect customer involvement positively influences relationship between chain By demonstrating these relations, our study contributes theoretical practical efforts toward broader achievement SDGs.

Language: Английский

Citations

11
Future behavioural of console gamers and mobile gamers: are they differ? DOI

Syahrulanuar Ngah,

Samar Rahi, Fei Long

et al.

Quality & Quantity, Journal Year: 2024, Volume and Issue: 58(6), P. 5531 - 5557

Published: May 23, 2024

Language: Английский

Citations

10
It’s not all fun and games: gamification in e-commerce on consumers’ impulse buying of retail food products DOI
Su-Kyung Lim, Yao‐Hua Tan, Xiu-Ming Loh

et al.

British Food Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Purpose This study aims to look into the role of gamification as an effective marketing tool engage with consumers and influence purchase behaviours. As there are a plethora gamified elements, it is crucial determine which them can significantly facilitate consumer behaviour. Therefore, unique stimulus–organism–response (SOR) framework encompasses four popular elements (i.e. fun, rewards, competition badges) was employed investigate consumers’ engagement. Design/methodology/approach An online survey utilized collect data yielded 307 responses. Subsequently, partial least squares-structural equation modeling (PLS-SEM) used analyse data. Findings Among assessed in this study, fun revealed be strongest facilitating antecedent shopping However, reward have insignificant effect on In addition, found that undergo processual development regard their impulse buying retail food products. More precisely, engagement significant facilitator customer satisfaction subsequently motivates buying. Originality/value among pioneering studies provide detailed insights different Furthermore, number practical theoretical implications for relevant stakeholders were discussed.

Language: Английский

Citations

1
Examine the factors influencing the behavioral intention to use social commerce adoption and the role of AI in SC adoption DOI Creative Commons

Shahzad Sadiq,

Kaiwei Jia,

Ihsan Aman

et al.

European Research on Management and Business Economics, Journal Year: 2025, Volume and Issue: 31(1), P. 100268 - 100268

Published: Jan. 1, 2025

Language: Английский

Citations

1
Chatbot dynamics: trust, social presence and customer satisfaction in AI-driven services DOI Creative Commons
Badrea Al Oraini

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Purpose This study investigated the factors that influence customer satisfaction with AI-driven services by focusing on chatbot agents. The conceptual model included psychological and social factors, such as trust, perceived presence, competence perception, social-oriented communication style, warmth subjective norms attachment anxiety. Design/methodology/approach A quantitative methodology was employed utilising a survey conducted among 525 consumers who interacted services. data were analysed using structural equation modelling (Smart-PLS 4.0) to test proposed hypotheses. Findings revealed communication, perceptions of warmth, trust significantly enhanced chatbots. Trust critical in fostering satisfaction, whereas presence anxiety had minimal impact. findings suggest despite emphasis its may depend contextual not captured this study. Originality/value extended Technology Acceptance Model Stereotype Content integrating norm Challenging conventional assumptions role anxiety, provides new insights into complex dynamics human–chatbot interactions, offering practical implications for improving design enhancing user experience emphasise importance satisfaction.

Language: Английский

Citations

1
Using SOR theory to examine the impact of AI Chatbot quality on Gen Z’s satisfaction and advocacy within the fast-food sector DOI
Ahmed Mostafa Abdelwaged Elayat, Reem Mohamed Elalfy

Young Consumers Insight and Ideas for Responsible Marketers, Journal Year: 2025, Volume and Issue: 26(2), P. 352 - 383

Published: Feb. 28, 2025

Purpose This study aims to provide empirical evidence verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine impact these dimensions on consumer satisfaction brand advocacy among Gen Z in fast food industry Egypt. Design/methodology/approach The data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple brands Structural equation modeling used analyze formulated hypotheses. Findings results showed that dimensions, specifically information authenticity system compliance, significantly enhance consumers’ satisfaction. In addition, observed wield a significant influence advocacy. contrast, insignificant relationship noticed between Moreover, mediating role not established. Practical implications Given is more technology savvy computer literate, marketers practitioners should invest tools respond expectations improve their perception services. Originality/value uses stimulus-organism-response theory understand effect within industry. Also, it introduced two novel main constructs quality, namely, compliance.

Language: Английский

Citations

1
How Do Consumers Trust and Accept AI Agents? An Extended Theoretical Framework and Empirical Evidence DOI Creative Commons
Xue Zhao, Weitao You, Ziqing Zheng

et al.

Behavioral Sciences, Journal Year: 2025, Volume and Issue: 15(3), P. 337 - 337

Published: March 10, 2025

With the rapid development of generative artificial intelligence (AI), AI agents are evolving into “intelligent partners” integrated various consumer scenarios, posing new challenges to conventional decision-making processes and perceptions. However, mechanisms through which consumers develop trust adopt in common scenarios remain unclear. Therefore, this article develops a framework based on heuristic–systematic model explain behavioral future consumers. This is validated PLS-SEM with data from 632 participants China. The results show that can link individuals’ dual decision paths further drive user behavior. Additionally, we identify key drivers behavior two dimensions. These findings provide practical guidance for businesses policymakers optimize design promote widespread acceptance adoption technologies.

Language: Английский

Citations

1
AI marketing and AI‐based promotions impact on consumer behavior and the avoidance of consumer autonomy threat DOI
George S. Spais, Ian Phau, Varsha Jain

et al.

Journal of Consumer Behaviour, Journal Year: 2023, Volume and Issue: 23(3), P. 1053 - 1056

Published: Sept. 14, 2023

None of the authors have a conflict interest to disclose. Data sharing not applicable this article as no datasets were generated or analysed during current study.

Language: Английский

Citations

19
Users’ continuance intention towards an AI painting application: An extended expectation confirmation model DOI Creative Commons
Xiaofan Yu, Yi Yang, Shuang Li

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(5), P. e0301821 - e0301821

Published: May 15, 2024

With the rapid advancement of technology, Artificial Intelligence (AI) painting has emerged as a leading intelligence service. This study aims to empirically investigate users’ continuance intention toward AI applications by utilizing and expanding Expectation Confirmation Model (ECM), Technology Acceptance (TAM), Unified Theory Use (UTAUT), Flow Theory. A comprehensive research model is proposed. total 443 questionnaires were distributed users with experiences for data collection. The hypotheses tested through structural equation modeling. primary conclusions drawn from this include: 1) plays crucial role, significantly positively predicting satisfaction social impact. 2) Personal innovativeness significant effect on confirmation. 3) Satisfaction, flow experience, influence directly predict intention, showing most impact, while perceived usefulness, enjoyment, performance expectancy show no impact intention. 4) Habit negative moderating role in association between continued use. These findings offer valuable insights inspiration seeking understand appropriate utilization provide actionable directions development painting.

Language: Английский

Citations

8
Explainable causal variational autoencoders based equivariant graph neural networks for analyzing the consumer purchase behavior in E-commerce DOI
Manoranjan Gandhudi,

P. J. A. Alphonse,

Vasanth Velayudham

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 136, P. 108988 - 108988

Published: July 23, 2024

Language: Английский

Citations

7