Consumer Behavior Toward AI-Powered Chatbots in Interactive Marketing: The Moderating Role of Perceptual Psychology

This study examines the determinants of corporate tax compliance in Thailand, partic-ularly in the context of increasing digitalization. While prior studies have separately addressed technology acceptance and behavioral intention, few have integrated these domains to explain voluntary tax compliance. This research employs a hybrid model that combines the Technology Acceptance Model (TAM), the Theory of Planned Be-havior (TPB), and taxpayer responsibility theory. Using data from 500 corporate ac-countants, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Importance–Performance Map Analysis (IPMA) to analyze the data. The results demonstrate that perceived ease of use, subjec-tive norms, and perceived behavioral control significantly influence tax intention, which in turn affects compliance behavior. Furthermore, attitudes toward technology and perceived usefulness indirectly support compliance, while taxpayer responsibility ex-hibits a strong direct effect. These findings contribute to the theoretical understanding of compliance behavior and offer practical insights for enhancing technology-enabled tax systems in emerging markets. This study examines the determinants of corporate tax compliance in Thailand, partic-ularly in the context of increasing digitalization. While prior studies have separately addressed technology acceptance and behavioral intention, few have integrated these domains to explain voluntary tax compliance. This research employs a hybrid model that combines the Technology Acceptance Model (TAM), the Theory of Planned Be-havior (TPB), and taxpayer responsibility theory. Using data from 500 corporate ac-countants, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Importance–Performance Map Analysis (IPMA) to analyze the data. The results demonstrate that perceived ease of use, subjec-tive norms, and perceived behavioral control significantly influence tax intention, which in turn affects compliance behavior. Furthermore, attitudes toward technology and perceived usefulness indirectly support compliance, while taxpayer responsibility ex-hibits a strong direct effect. These findings contribute to the theoretical understanding of compliance behavior and offer practical insights for enhancing technology-enabled tax systems in emerging markets.

Purpose –The research aims to investigate the behavioralintentions of dorm students in Izmir, Turkey towards a food delivery e-commerce platform, utilizing the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) in the post-COVID19 era.Design/methodology/approach-Data from 224 dorm students were collected via a structured Google Forms questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.0. Confirmatory factor analysis was applied to measure the structural model.Findings -Actual use (AU), item-information quality (IQ), and hedonic motivation (HM) significantly affect overall satisfaction and loyalty (S&L). Hedonic motivation refers to the enjoyment of using the platform, while the quality of the item information reflects the accuracy and reliability of the information provided. The analysis showed that hedonic motivation, information quality of TPB, and TAM's actual use explained 75.10% of the variance in satisfaction. The variance of price to sale (PS), restaurant credibility (RC), and navigational design (ND) explained 69.0% of the variance of information-item quality (IQ). Intention to use (ITU) explained 57.7% of the variance of the actual use (AU). Discussion -The findings suggest that e-commerce platforms can boost user engagement and satisfaction by improving navigational design and aligning with dorm students' hedonic motivations, thus enhancing loyalty and reuse. The post-COVID-19 era is dramatically changing consumer behavior and increasing trust in digital platforms for safety and convenience. The research contributes insights into dorm students' online food delivery behavior, emphasizing the importance of user satisfaction and loyalty in digital commerce and providing actionable strategies for service enhancement.

ObjectiveThis study investigates the factors influencing physicians’ acceptance and adoption of artificial intelligence (AI) technologies in clinical practice, integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), while also examining the mediating role of trust.MethodsA structured survey was conducted among 414 physicians assessing their perceptions of AI technologies using constructs from TPB, TAM, and trust-related factors. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for data analysis.ResultsFindings confirm that TPB and TAM effectively explain physicians’ AI acceptance, with TPB exhibiting a stronger predictive power compared to TAM. Trust emerged as a critical determinant in AI adoption, fully mediating the relationship between perceived behavioral control (p < 0.001), subjective norms (p < 0.05), perceived usefulness (p < 0.001), ease of use (p < 0.001), and behavioral intention. Notably, perceived ease of use (p < 0.001) had the strongest direct impact on trust, while perceived usefulness (p < 0.001) significantly influenced behavioral intention. Attitude toward AI showed a significant effect (p < 0.01). Subjective norms and perceived behavioral control had weaker direct influences (p < 0.05 and p = 0.07, respectively).ConclusionTrust plays a pivotal role in AI adoption, shaping physicians’ acceptance beyond traditional TPB and TAM factors. Healthcare administrators, policymakers, and technology developers should focus on enhancing trust by improving AI transparency, interpretability, and user-friendly design.

Electronic Word-of-Mouth (eWOM) has become a critical factor influencing consumer decision-making in the digital tourism industry. In Indonesia, the rapid growth of Online Travel Agents (OTAs) has increased competition, making consumer trust and purchase intentions largely dependent on online reviews. This research aims to analyze the effect of eWOM on online hotel booking purchase intentions, focusing on the credibility, quality, and expertise of reviewers as key determinants of consumer trust and behavior. The study adopts the Information Adoption Model (IAM) and the Theory of Planned Behavior (TPB) as theoretical frameworks to explain how consumers process online information and make booking decisions. A quantitative approach is employed, using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between eWOM dimensions and purchase intentions. PLS-SEM is chosen due to its predictive and exploratory capabilities, allowing comprehensive testing of measurement validity, reliability, and structural path coefficients. Data were collected from OTA users in Indonesia through a structured online survey and analyzed to assess convergent and discriminant validity. The findings reveal that information credibility and reviewer expertise significantly enhance consumer trust, which in turn positively influences purchase intentions. Information quality also plays a mediating role in shaping consumer perceptions. These results suggest that OTAs should prioritize strategies that ensure authentic, high-quality reviews to strengthen customer engagement and conversion rates. This study provides theoretical contributions to eWOM and consumer behavior research while offering practical implications for OTAs to improve digital marketing strategies in Indonesia’s competitive tourism sector.

The Farmer’s Card becomes one of the requirements to get the subsidized fertilizer as a tool of access to banking services integrated into an E-wallet or ATM (Automatic Teller Machine). The new technology indicates the problem found in the field, which is the lack of awareness and knowledge of the farmers who own the Farmer’s Card in understanding the function of each feature provided by the Card. This research is conducted to analyze the readiness and the acceptance factors of the farmers who own the Farmer’s Card toward the interest of using the Farmer’s Card in the Sumenep Regency. The Technology Readiness and Acceptance Model (TRAM), which is the collaboration of the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM), is being used to analyze the interest in the use of the Farmer’s Card. Quantitative data is collected through interviews with structured questionnaires that refer to the previous research indicators on the Technology Readiness and Acceptance Model (TRAM). The sample was conducted on 140 farmers who own the Farmer’s Card. The analysis was performed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) through the SmartPLS software. The results of the hypothesis show that the function or the advantage of the Farmer’s Card has a direct and significant influence on the interest of the farmers in using the Farmer’s Card. On the other hand, the simplicity of using the Farmer’s Card is considered insignificant and challenging for the farmers. The Farmer’s Card program can be successful. It is suggested that the government and the farmers, who own the Farmer’s Card, need to approach and improve their communication through intensive guidance. Keywords: readiness, acceptance, farmer's card, PLS-SEM, subsidized fertilizer

This study examines the factors influencing seniors’ adoption of virtual reality (VR) cognitive training games by integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). Beyond the traditional constructs of these models, the research incorporates perceived enjoyment (PE), personal innovativeness (PI), and computer anxiety (CAX) to address seniors’ cognitive health needs and explore VR-based non-pharmacological interventions. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study analyzed direct and indirect effects on adoption within a questionnaire-based framework. The research was conducted at community care centers in Taoyuan City, Taiwan, with 150 seniors aged 65–80. Participants engaged in a 20-min session with Nintendo Switch VR games and subsequently completed a questionnaire assessing their experiences. Results revealed that perceived ease of use (PEOU), PE, and subjective norms (SN) significantly shaped attitudes toward VR adoption, which strongly influenced behavioral intention (BI). BI emerged as a robust predictor of actual usage behavior (AUB), while CAX negatively impacted BI, highlighting the need to address emotional barriers. This study underscores the importance of designing intuitive, engaging, and accessible VR cognitive training games tailored for seniors. It also highlights the pivotal role of family and caregivers in fostering adoption, alongside the necessity of providing social and emotional support. These findings contribute to the theoretical understanding of VR-based games adoption in older adults and offer practical guidance for developers and healthcare providers aiming to create effective interventions for cognitive health.

Although AI holds potential for enhancing teachers’ efficiency, empirical research on teachers’ intention to use (IU) it remains limited. Few studies have integrated digital leadership (DL) and digital readiness (DR) into established acceptance models such as the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Furthermore, the mediating role of perceived usefulness (PU) in AI adoption, particularly in primary and secondary education, is still underexplored. This study addresses this gap by examining how DL, DR, and PU affect teachers’ intention to adopt AI. Data were collected from 382 primary and secondary school teachers in four cities in Greater Jakarta , Indonesia, using a non-probability convenience sampling method. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that while DL initially showed no significant direct effect on IU AI, a substantial positive effect emerged after controlling for training, support, and resource access, highlighting its essential yet complex role in shaping teachers’ behavior. Additionally, DL exerts a strong indirect effect on IU AI through DR and PU. These results suggest that successful AI integration requires school leaders to strengthen teachers’ DR and proactively communicating AI’s benefits to enhance PU.

IntroductionThe rapid growth of financial technology has led to the emergence of sharia-compliant services like SyarQ, an Islamic-based online installment platform. Understanding the factors that influence consumer interest in such services is essential for their adoption and success.ObjectivesThis study aims to analyze the factors affecting users' interest in using SyarQ's services by integrating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB).MethodA quantitative and exploratory research design was employed, utilizing online questionnaires distributed to 100 verified SyarQ users. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed hypotheses and examine the relationships between variables.ResultsThe findings reveal that user attitude has a positive and significant effect on the interest in using SyarQ services. Perceived behavioral control positively influences perceived ease of use but does not significantly affect interest directly. Perceived ease of use positively affects both attitude and perceived usefulness. Subjective norms have a positive and significant impact on perceived usefulness but do not significantly influence interest. Perceived usefulness does not have a significant effect on attitude or interest.ImplicationsThe study suggests that enhancing user attitudes and simplifying the user experience can increase consumer interest in Sharia-compliant fintech services like SyarQ. Providers should focus on improving the ease of use and addressing factors that positively influence user attitudes to attract and retain customers.Originality/NoveltyThis research contributes to the existing literature by combining TAM and TPB to examine user interest in a Sharia-compliant fintech platform. It offers valuable insights into consumer behavior within Islamic financial services, a relatively underexplored area.

This research paper explores the pivotal role of digital transformation and technology ecosystems in the data storage industry, focusing on the adoption of emerging technologies. The study constructs a comprehensive theoretical framework through a questionnaire-based approach by integrating the Technology Acceptance Model (TAM) and extending it with the Stimulus Theoretical Framework. The primary aim is to identify critical factors influencing successful adoption, considering the current state of digital transformation and the dynamics of technology ecosystems within organizations. The literature review explores influential theories like TAM, Diffusion of Innovations, Theory of Task Technology Fit, and the Unified Theory of Acceptance and Use of Technology, informing the research's framework with insights into consumer acceptance of new technologies. Using a mixed-methods approach, the study incorporates qualitative insights from a multi-case study employing systematic thematic content analysis, categorizing user acceptance of 5G, Artificial Intelligence, Cloud Computing, and Edge in major storage entities: Dell Technologies, IBM, HPE, Hitachi Vantara, and NetApp. For the quantitative aspect, a structured questionnaire based on the Technology Acceptance Model (TAM) and the Stimulus Theoretical Framework was used to gather insights on digital transformation, technology ecosystems, perceived usefulness, ease of use, and intention to use from senior and mid-level employees in storage organizations. A pilot study with 45 responses was conducted, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4. The Confirmatory Factor Analysis, employing the same software and sample size, evaluated the loading of items onto their respective constructs. The five key constructs include digital transformation, technology ecosystem, Perceived Usefulness (PU), Perceived Ease of Use (PEU), Intention to Use (IU), and technology adoption outcome. Our findings shed light on the intricate dynamics within these constructs and highlight the importance of early detection and rectification of questionnaire deficiencies. The results and discussion section emphasizes the impact of digital transformation and technology ecosystems, with perceived usefulness and ease of use as key motivators influencing employees' responses and intention to adopt. The study systematically analyzes expected technology adoption outcomes, contributing to a deeper understanding of successful technology integration in the enterprise storage sector.

The rapid growth of AI-based e-commerce has yet to integrate spiritual values such as ta‘abbud, essential for Muslim consumers in fostering trust and holistic well-being. This study aims to explore the role of ta‘abbud in AI recommendation systems, enhancing consumer well-being materially and spiritually through increased consumer trust. The research is grounded in four theoretical frameworks: the Technology Acceptance Model (TAM), Consumer Well-Being, Consumer Behavior, and AI Personalization. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess relationships between variables. Data were collected via a stratified sampling questionnaire involving 240 Generation Z respondents. The findings reveal that information accessibility significantly influences the shopping experience (R² = 0.743), whereas recommendation quality moderately affects consumer trust (R² = 0.724). Furthermore, AI-based recommendation personalization enhances consumer well-being (R² = 0.635) by improving trust and recommendation relevance (R² = 0.586). Although the effect of ta‘abbud is relatively small, it plays a meaningful role in shaping trust in AI systems, particularly for halal product purchases. This study offers practical implications for Sharia-compliant e-commerce in building consumer loyalty through value-based strategies.

Artificial intelligence (AI) has become an essential part of modern e-commerce, primarily through algorithm-driven personalisation that customises product suggestions and content for individual consumers. Although AI applications are spreading rapidly, there is limited empirical evidence on how AI-driven personalisation influences online purchase intentions in emerging markets, particularly regarding the psychological processes underlying this relationship. This study investigates the impact of AI-driven personalisation and consumer attitudes towards AI on online purchase intentions, with consumer awareness acting as a mediating variable. Rooted in the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB), the study uses a quantitative, cross-sectional research design. Data were gathered from online shoppers in major cities across South-East Nigeria through a structured questionnaire. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to examine both direct and indirect relationships among the study's constructs. The results show that consumer attitude towards AI has a significant positive direct effect on online purchase intention. Conversely, AI-driven personalisation does not significantly influence purchase intention. Instead, its impact works indirectly via consumer awareness. Further analysis reveals that consumer awareness significantly mediates the relationship between consumer attitude towards AI and online purchase intention, emphasising awareness as a vital cognitive pathway through which positive perceptions of AI are converted into behavioural intention. The study concludes that AI personalisation alone is not enough to encourage online purchasing in emerging markets unless consumers clearly understand how AI systems operate and the value they offer. By empirically positioning consumer awareness as a key mediating factor, the study expands TAM and TPB in AI-enabled consumption contexts. It offers practical insights for e-commerce platforms seeking to deploy AI responsibly and effectively in emerging digital economies.

Amid accelerating climate change and the global shift toward sustainable consumption, agricultural by-products have gained attention as low-carbon alternatives to conventional plastic packaging. This study explores the psychological and behavioral mechanisms underlying consumer acceptance of sugarcane bagasse containers, aiming to advance understanding of how agricultural residue-based innovations drive sustainable packaging adoption. An integrated framework (EPIM-LCP) is developed by synthesizing the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Environmental Behavior Theory (EBT). Based on empirical data from 450 respondents in Guangxi, China, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test eleven hypotheses. Results reveal that environmental concern and environmental values significantly enhance low-carbon awareness, which positively shapes consumer attitudes. Perceived usefulness and ease of use influence attitudes, mediating their impact on acceptance intention. Attitude, subjective norms, and perceived behavioral control all significantly predict adoption intention, with attitude being the most influential factor. Two key mediation pathways are identified: (1) environmental cognition → low-carbon awareness → attitude → intention; and (2) technical perception → attitude → intention. The model exhibits strong predictive validity through PLS-Predict analysis. This research contributes to sustainable packaging literature by being one of the first to integrate TAM, TPB, and EBT for agricultural by-products adoption. The findings offer theoretical insights into consumer psychology while providing practical implications for designers, marketers, and policymakers promoting bio-based packaging solutions.

This study explores the factors influencing car sharing adoption in Thailand, focusing on regional differences between Bangkok and the Eastern Economic Corridor (EEC).Using an integrated model of the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB), data were gathered from 800 respondents through online surveys and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).The findings highlight notable regional distinctions: in Bangkok, perceived physical risk and environmental awareness significantly affect the perceived usefulness of car sharing services, while in the EEC, perceived value plays a critical role.Additionally, subjective norms have a stronger influence in Bangkok, reflecting the city's cultural emphasis on social conformity.In contrast, the industrial nature of the EEC underscores the importance of perceived behavioral control as a key determinant.This study adds to the body of literature by offering insights into regional variations in car sharing adoption and provides practical recommendations for policymakers and service providers to tailor their strategies to different urban settings.

This study applies the Technology Acceptance Model (TAM) to evaluate the factors influencing the adoption of pneumatic precision planters in corn farming in the Philippines. Da-ta from 393 farmers were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between Perceived Usefulness (PU), Perceived Ease of Use (PEU), Behavioral Intention (BI), and three extended TAM constructs: Compatibility (CO), Observability (OB), and Personal Innovativeness (PI). The model was validated for reliability and discriminant validity, with the Average Variance Extracted (AVE) ranging from 0.664 to 0.823. Statistical significance was observed in ten out of twelve hypothesized relationships, indicating a high likelihood of adoption. This study extends TAM by incorporating external factors such as CO, OB, and PI, offering a deeper understanding of how these variables influence farmers’ perceptions of the technology’s usefulness and ease of use. The findings suggest that, for successful adoption, policymakers should focus on enhancing the visibility of the technology’s benefits, ensuring compatibility with existing farming practices, and promoting openness to innovation through targeted education and support. The results highlight the need for practical interventions, such as educational programs and demonstration projects, which could significantly improve technology adoption, productivity, and sustainability in Philippine agriculture.

Enhancing sustainable fashion through QR-enabled showrooming: A Philippine consumer behavior perspective.