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... we tested the structural model to check the validity and reliability (including Cronbach alpha, composite reliability (CR), and average variance extracted (AVE)). The reliability and composite reliability values (Table 2) were above the threshold of 0.70. All constructs' AVE (average variance extracted) ranged from 0.513 to 0.675. ...Similar publications
Purpose
Examining turnover as a noteworthy concern for businesses irrespective of their scale, this research delves into the factors influencing the inclination of employees in small and medium-sized enterprises to depart from their current workplaces. Additionally, the study explores how organizational commitment moderates the connections between...
Citations
... Owners obtain value by sharing idle resources, while demanders obtain goods at a lower price, thereby improving the utilization of goods. Low pollution and low cost are the main reasons for the vigorous development of the sharing economy [1]. However, the complex global economic environment makes many enterprises face the challenge of survival and development. ...
This paper studies the impact of artificial intelligence (AI) on improving consumers' participation in the sharing economy. With the rise of environmental awareness and the proliferation of digital platforms, artificial intelligence has become vital for improving trust and asset matching. However, enterprises should avoid possible risks when applying AI. This paper assumes that SE platformed enterprises will eventually adopt AI tools and strategies to optimize efficiency and improve user experiences. This paper mainly studies from two aspects. First, it discusses how enterprises use artificial intelligence to improve platform functions to improve customer experience. Second, this paper proposes an implementation framework for SE enterprises using the SLO analysis framework to protect the valuable SLO of SE enterprises. This article focuses on technical, legal, ethical, and consumer perspectives in the SLO analysis process. This paper concludes that artificial intelligence is a sustainable and cost-effective strategy for the sharing economy that helps achieve environmental and economic goals. The research results of SE platforms leverage the perception of being a positive, pro-environmental, pro-community building modality, preventing losing its social license to operate, emphasizing the potential of artificial intelligence to improve customer satisfaction and participation through personalized services and responsive customer support.
... A recent contribution from the 2022-2025 literature is the emergence of technologies such as Artificial Intelligence (AI), live commerce, and omnichannel strategies in boosting customer engagement and operational efficiency for MSMEs (Nalbant & Aydin, 2025;Nazir et al., 2023;Takainga et al., 2025). Several studies have identified that the use of digital metrics and platform-based reporting systems greatly assists MSME players in monitoring marketing performance in real time (Alam & Mubarak, 2025;Purnomo, 2023) However, major challenges persist, including limited digital literacy, uneven internet infrastructure, and the high costs of digital advertising on major platforms (Ding, 2021;Raza, 2021). ...
The rapid advancement of digital technology has transformed business practices globally, impacting not only large corporations but also Micro, Small, and Medium Enterprises (MSMEs). In the digital era, MSMEs are required to adopt innovative strategies, particularly in marketing, to remain competitive and sustainable. Digital marketing has emerged as a crucial tool for MSMEs to expand market reach, improve operational efficiency, and better engage with consumers through platforms such as social media, e-commerce, and digital analytics. In Indonesia, digital adoption among MSMEs is growing significantly. As of December 2023, approximately 41.2% of MSMEs have integrated into the digital ecosystem, with the government targeting 30 million MSMEs to be digitalized by 2024. Despite the promising growth and numerous benefits such as increased revenue and market access MSMEs still face major challenges including limited digital literacy, inadequate infrastructure, and financial constraints. This study aims to conduct a literature review on the dynamics of digital marketing among MSMEs within the digital business ecosystem. It seeks to explore the factors influencing the effectiveness of digital marketing strategies, the challenges faced in their implementation, and the adaptive measures adopted by MSMEs. The findings are expected to provide strategic insights for MSME development and inform policymakers in creating a supportive digital economic environment. Ultimately, this review aspires to contribute to the formulation of inclusive and sustainable digital marketing strategies for MSMEs in Indonesia.
... Currently, scholars have conducted extensive research on consumer repurchase intention, but much of it has focused on consumer quality. For instance, the research of Nazir et al. (2023) investigated how consumer engagement on social media and providing a satisfying consumer experience are significant factors influencing consumer repurchase intentions in the hospitality industry [70]. Besides, according to Ding (2023), enhancing the focus on customer experience by platform merchants can increase the competitive advantage of community groupbuying businesses [71]. ...
In the ever-changing community e-commerce, it is crucial to comprehend the complex connection between quality of a community e-commerce platform and the behavior of consumers in order to maintain growth and competitiveness. This study empirically examines the influence of community e-commerce platforms’ quality, including system quality, information quality, and service quality, on consumers' intention to repurchase, with a specific focus on daily necessities. Stimulus-Organism-Response (SOR) paradigm is adopted to examine how the perception of hedonic and utilitarian values influence the connection between platform quality and repurchase intentions. The results of an online survey conducted with 181 users of community e-commerce platforms demonstrate significant impact of system quality and service quality on repurchase intention. This study particularly emphasizes the key role of the clustering algorithm in precision marketing. Clustering algorithm helps to organize and collect user behavior models and related information, and segment consumer groups, thus laying a solid foundation for precision marketing. During the process of users segmentation, it explores the similarities and differences of different groups, combines market and product development strategies, and targets the selection and integrattion of user markets. This improves the accuracy of market strategies, ensures the full implementation of consumer-ccentric service concept, fully meets the needs of different consumer groups, tracks the status of target customers in real-time, and carries out marketing work.This enhancement is predominantly mediated by perceived hedonic and utilitarian values, highlighting their crucial importance in the process of consumer decision-making. The study also reveals that the impact of information quality on repurchase intentions is limited, and its indirect effect through perceived utilitarian value is also minimal. This sheds light on the complex relationship between platform quality and consumer perceptions. This study enriches the existing literature by providing a detailed understanding of the factors that influence customer loyalty in the digital market. It also provides strategic advice to community ecommerce platforms that seek to increase consumer engagement and enhance their competitive position by implementing qualitative improvements in systems, services, and information distribution.
... Among qualitative studies, the meta-synthesis method is a consistent approach for data analysis. This process utilizes rigorous qualitative methods to combine existing qualitative studies to create more meaning through an interpretive process [16,21,24,40,41]. This method is a structured model for qualitative text analysis and extracting concepts that are used in the meta-synthesis method. ...
The adoption of artificial intelligence (AI) based marketing systems by companies is increasing. These systems can help companies improve their marketing performance, increase their market share, and reduce their marketing costs. Few researchers, in this regard, have sought to investigate the causes of the nonacceptance of marketing systems based on AI. This article uses the qualitative research method to identify the effective factors in the adoption of marketing systems based on AI. The current study is practical in aim and qualitative in essence, utilizing an exploratory methodology. The statistical population of the research includes 238 studies including articles on the factors of acceptance of marketing systems based on AI between 2019 and 2024. The data collection tool was selected in the form of a systematic review and library studies of literature and previous researches, and the research method is the meta-synthesis of Sandelowski and Barroso. The sampling method is also selected based on the entry and exit criteria of the PRISMA (preferred reporting items for systematic reviews and meta-analyses) method. PRISMA is a framework for evaluating and enhancing the quality of review articles and scientific studies through systematic review and meta-synthesis. The findings of this research show that the four factors of functional expectations, usage expectations, organizational factors, and user intent have a significant effect on the acceptance of these systems. Companies that promote a culture of learning and embracing innovation are more likely to adopt these systems. These findings can help companies to increase the adoption of AI-based marketing systems in their organization.
... Digital innovations have transformed consumer purchases and business practices (Nazir et al., 2023). Recent research confirmed personalized shopping and AI virtual assistants' role in e-commerce's growth in innovation (Kamoonpuri and Sengar, 2023). ...
This study investigated the impact of AI price and product recommendation accuracy on customer satisfaction based on the stimulus-organism response (SOR) theory. Analysing online users’ surveys through PLS-SEM, this study found that brand sensitivity significantly moderates the relationship between AI recommendation's product accuracy and personalized service satisfaction but not the link between price accuracy and personalized service satisfaction. Investment strategy exhibited an insignificant moderating effect on the relationship between personalized service satisfaction, product and price accuracy. The results revealed that accurate price and product recommendation directly impact personalized service satisfaction. This is the first study to examine AI recommendation’s effects on personalized service satisfaction with the multi-moderation of investment strategy and brand sensitivity. The findings extend the SOR framework in literature to the AI-powered online shopping. They provide practical information for e-commerce providers to enhance customer satisfaction by adopting AI technologies that accurate recommend price and product to their potential customers. Policy makers may implement related policies to enhance AI price and product recommendation transparency by encouraging the usage of explainable artificial intelligence and providing more education to customers about AI recommendations in online shopping platforms.
... As an important consequence of user trust, the intention to accept and use AI has become a hot research topic (Nazir et al., 2023). Previous studies consistently show that there is a significant positive correlation between user trust in AI and its adoption. ...
With the rapid development of generative artificial intelligence (AI), AI agents are evolving into “intelligent partners” integrated into various consumer scenarios, posing new challenges to conventional consumer decision-making processes and perceptions. However, the mechanisms through which consumers develop trust and adopt AI agents in common scenarios remain unclear. Therefore, this article develops a framework based on the heuristic–systematic model to explain the behavioral decision-making mechanisms of future consumers. This model is validated through PLS-SEM with data from 632 participants in China. The results show that trust can link individuals’ dual decision paths to further drive user behavior. Additionally, we identify the key drivers of consumer behavior from two dimensions. These findings provide practical guidance for businesses and policymakers to optimize the design and development of AI agents and promote the widespread acceptance and adoption of AI technologies.
... Further, (Chen et al., 2022b) studied AI utilization within home-sharing platforms to facilitate business operations and enhance customer experience. Also, (Nazir et al., 2023) facilitated the understanding of AI to influence consumer engagement on social media and conversion rates to boost consumer satisfaction and repurchase intention on for hospitality organizations. In the same context, (Teng et al., 2023) explored the relationship between restaurant innovativeness, customer engagement and customer advocacy based on the SOR model. ...
Purpose
This study aims to provide empirical evidence to verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine the impact of these dimensions on consumer satisfaction and brand advocacy among Gen Z in the fast food industry in Egypt.
Design/methodology/approach
The empirical data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple fast food brands in Egypt. Structural equation modeling was used to analyze the formulated hypotheses.
Findings
The results showed that AI Chatbot quality dimensions, specifically information authenticity and system compliance, significantly enhance young consumers’ satisfaction. In addition, information authenticity of AI Chatbot quality was observed to wield a significant influence on young consumers’ advocacy. In contrast, an insignificant relationship was noticed between satisfaction and advocacy. Moreover, the mediating role of consumer satisfaction was not established.
Practical implications
Given that Gen Z is more technology savvy and computer literate, marketers and practitioners of fast food brands should invest in AI tools to respond to young consumers’ expectations and improve their perception of their services.
Originality/value
This study uses stimulus-organism-response theory to understand the mediating effect of young consumers’ satisfaction in the relationship between AI Chatbot quality and consumer brand advocacy within the fast food industry. Also, it introduced two novel main constructs of AI Chatbot quality, namely, information authenticity and system compliance.
... These factors are deemed to need deeper analysis and additional understanding to match the product portfolio for Muslim tourists. Furthermore, we also discuss expectationconfirmation theory (ECT) (Oliver, 1980) concerning satisfaction and loyalty in the Halal tourism industry; we focus on contemporary approaches to loyalty in the digital business era with the help of the ChatGPT tool (Hsu and Lin, 2023;Nazir et al., 2023). ...
... Recent studies have proposed that ChatGPT and other advanced AI tools can bring great value to customers and organizational performance in the tourism and hospitality industry (Han et al., 2024;Nazir et al., 2023). Nevertheless, ChatGPT's effects on Halal tourism as a sector have not been researched extensively. ...
Purpose- This study aims to examine the impact of using ChatGPT on the Halal tourism experience. It examines the relationships among Halal-friendly travel motivations and satisfaction, revisit intention and electronic word-of-mouth (e-WoM) while testing the moderating effect of ChatGPT on the relationship between satisfaction and revisit intention.
Design/methodology/approach- This study employed a quantitative methodology. Using purposive sampling techniques, it approached about 800 tourists (from November 2023 to January 2024) from several halal tourism destinations in Indonesia. A total of 395 usable surveys were analyzed to test the relationships and moderation effects by SEM.
Findings- The study indicates that Halal-friendly travel motivations positively impact Muslim tourist satisfaction, which in turn influences e-WoM and revisit intention. Importantly, ChatGPT significantly moderates the relationship between satisfaction and revisit intention, thereby strengthening tourist loyalty for those using the AI tool.
Practical implications- The study's findings provide practical guidelines for halal tourism providers to enhance Halal-compliant services and incorporate ChatGPT as an AI tool to boost Muslim travelers' satisfaction, drive e-WoM, and increase revisit intentions. AI technology gives Halal tourism companies an advantage in offering customized, immediate support, which leads to Muslim visitors becoming loyal.
Originality/value- The study fills a significant gap in the Halal tourism literature by examining AI's impact on the market. It expands the Expectation-Confirmation Theory (ECT), the push-pull theory and word-of-mouth models in Halal tourism. It also contributes to AI adoption in Halal tourism by addressing how modern AI tools can influence tourist behaviors, improve satisfaction and encourage repeat visits.
... Customer satisfaction mediates the relationship between customer experiences and repurchase intentions, emphasizing its critical role in fostering customer loyalty and encouraging repeat purchases Anita et al. (2021a), and satisfying customer experiences enhance the likelihood of repeat purchase (Ellitan, 2022). The satisfying experiences created by effective AI-driven engagement and optimization lead to higher repurchase intentions Nazir et al. (2023) and satisfied customers are more likely to return due to positive previous experiences (Nazir et al., 2012). ...
... Repurchase intention is the likelihood that a customer will choose to purchase a product or service again based on previous positive experiences (Nazir et al., 2023). It is used as a measure of customer loyalty and is seen as a critical factor for the ongoing success of online retail businesses where Customer satisfaction is a pivotal mediator, translating perceived value into repurchase intentions, with variations observed across different demographic and economic segments (C. ...
... 14. Life below Water: The goal is to conserve and use oceans, seas, and marine resources in a sustainable way. It focuses on reducing marine pollution, protecting marine ecosystems, and Nazir et al. (2023) explores the impact of artificial intelligence (AI) technology on consumer repurchase intentions within the hospitality industry, utilizing a quantitative approach with data from 308 hotel customers in Oman. Anchored in the Stimulus-Organism-Response theory, the study examines how AI as a stimulus enhances consumer engagement on social media, affects conversion rate optimization, and increases satisfying consumer experiences, subsequently influencing repurchase intentions. ...
The purpose of this study was to investigate the impact of artificial intelligence
technology on customer repurchase intention within the flight booking sector.
The study focused on understanding how AI-driven processes such as customer
interaction on social platforms, conversion rate optimization, and satisfying
customer experience mediates the relationship between AI technologies and
repurchase intention. The main purpose of the study was to examine the impact
of artificial intelligence technology on repurchase intention with the mediation
effects of conversion rate optimization, customer interaction on social platform
and satisfying customer experience. A structured questionnaire was used to gather
data from respondents living in the Kathmandu Valley. The study employed a
quantitative research design, and statistical tools such as SPSS and SMART-PLS
were used for data analysis, including confirmatory factor analysis and hypothesis
testing. The results indicated that AI technology significantly influences customer
repurchase intention, with customer interaction, CRO, and satisfying customer
experiences serving as crucial mediating factors. Findings suggest that airlines utilizing AI to enhance customer interaction and satisfaction are more likely to
experience increased customer loyalty and repurchase behavior.
Recommendations include adopting AI tools for personalized marketing
strategies, improving customer experiences, and fostering deeper engagement
through social platforms. This study adds value to both academic literature and13
the airline industry by providing insights into the growing role of AI in shaping
consumer behavior.
... Therefore, companies are working to meet consumer needs and improve customer experience, to attract and retain customers (Nazir et al., 2023). Prioritising customer engagement in the digital world has become essential because of the importance of online communications (Mehta and Sood, 2023). ...
... With the rapid advancement of artificial intelligence (AI) significantly transforming customer service environments, chatbots have emerged as pivotal tools for enhancing the customer experience (Tu et al., 2023). In industries ranging from e-commerce to financial services, chatbots are increasingly deployed to automate customer support, improve efficiency and provide 24/7 interaction opportunities (Nazir et al., 2023;Isiaku et al., 2024). These AI-driven systems, designed to mimic human conversation, have the potential to improve customer satisfaction by responding to queries, resolving issues and offering personalised experiences (Waghambare et al., 2024). ...
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 social presence, competence perception, social-oriented communication style, warmth perception, subjective norms and attachment anxiety.
Design/methodology/approach
A quantitative methodology was employed utilising a survey conducted among 525 consumers who interacted with chatbot services. The data were analysed using structural equation modelling (Smart-PLS 4.0) to test the proposed hypotheses.
Findings
The study revealed that social-oriented communication, perceptions of competence and warmth, trust and subjective norms significantly enhanced customer satisfaction with chatbots. Trust was critical in fostering satisfaction, whereas perceived social presence and attachment anxiety had minimal impact. The findings suggest that despite the emphasis on social presence, its influence on satisfaction may depend on contextual factors that were not captured in this study.
Originality/value
This study extended the Technology Acceptance Model and Stereotype Content Model by integrating factors such as perceived social presence, trust, competence perception, social-oriented communication style, warmth perception, subjective norm and attachment anxiety. Challenging conventional assumptions on the role of social presence and attachment anxiety, the study provides new insights into the complex dynamics of human–chatbot interactions, offering practical implications for improving chatbot design and enhancing user experience that emphasise the importance of trust, competence and social-oriented communication in customer satisfaction.
