Behavioral Reasoning Theory Research Articles

Exploring Factors Affecting Millennial Tourists’ eWOM Behavior: A Lens of BRT Theory

This study employs behavioral reasoning theory (BRT) to investigate factors (i.e., personal values, reasons, and attitudes) affecting existing and future behaviors of Millennial tourists’ electronic word-of-mouth (eWOM). It uses a mixed-methods approach that includes qualitative interviews with 25 tourists to elicit specific reasons for and against eWOM and a survey of 572 Millennial-Chinese tourists to quantitatively validate our BRT structural model. The statistical results from SmartPLS 3.0 show that all hypotheses on direct effects have gained empirical support except for the relationships between the existing behavior and its respective reasons for and against eWOM. These two insignificant direct effects are, however, shown to be fully mediated by global attitudes, respectively. Moreover, gender moderates the relationships between reasons against eWOM and the existing behavior and reasons for eWOM and future behavior, respectively. Most findings regarding the foregoing direct, mediation, and moderation effects are exploratory. In addition, this study contributes significantly to the literature by successfully developing and validating the scale of reasons for and against Millennial tourists’ eWOM within the BRT framework. Destination managers can use this scale of reasons as both a diagnostic tool and a blueprint for eWOM management.

What makes citizens participate in government data governance? A study based on Behavioral Reasoning Theory

This study seeks to examine the underlying mechanisms that shape citizens’ intentions to participate in government data governance. By uncovering the multifaceted determinants that facilitate or inhibit such participation, this study provides a theoretical foundation and methodological approach for future related research. Based on the findings, practical strategies to bolster citizen engagement in government data governance are proposed. An integrated higher-order reflective-formative model was constructed using the Behavioral Reasoning theory as a foundational framework. This model amalgamates the Civic Voluntarism Model, the Administrative Burden Theory, and the Ladder of Citizen Participation Theory. We employed PLS-SEM to analyze the influence of value orientation, attitude, participation, and non-participation reasoning on civic participation intention. Simultaneously, we explored the effects of six lower-order factors—motivation, resource, mobilization, psychological cost, compliance cost, and learning cost—on participation and non-participation reasoning. The study found that value orientation significantly and positively influences both participation reasoning and attitudes. Conversely, value orientation has a significant negative effect on non-participation reasoning. Participation reasoning positively impacts attitudes and the willingness to participate. Non-participation reasoning negatively affects attitudes and the willingness to participate. Motivation plays a crucial role in shaping a citizen’s participation reasoning. Compliance cost is also a key factor influencing citizens’ non-participation reasoning.

ChatGPT Adoption in Marketing: Exploring Drivers and Barriers through Behavioral Reasoning Theory

Recent advancements in Generative Artificial Intelligence (GAI) have paved the way for developing sophisticated language models such as ChatGPT, which are widely employed across various areas, including marketing. However, despite its benefits in marketing, little attention has been paid to understanding the factors influencing ChatGPT adoption among marketing professionals. Also, existing literature tends to focus more on the advantages of ChatGPT, while there is a paucity of studies focusing on potential barriers to its adoption. To fill these gaps, a framework was developed using Behavioral Reasoning Theory and validated through a survey of 390 marketing experts. The study finds that marketers’ reasons for (against) positively (negatively) influence their attitude and adoption intention toward ChatGPT, and uncertainty avoidance as a cultural value significantly affects marketers’ attitudes and reasoning. Furthermore, this study highlights digital literacy’s moderating role, intensifying the negative relationship between “reasons against” and the intention to adopt ChatGPT, though it does not significantly affect the association between “reasons against” and attitude. Additionally, the findings offer managerial guidance for facilitating the adoption of GAI tools.

Behavioural Reasoning Theory Perspectives: Hospitality Accounting System Adoption

This study delves into the behavioural intention to adopt Hospitality Accounting Systems (HAS) in Bali's villa accommodation sector, employing the Behavioral Reasoning Theory (BRT) framework. Through a representative sample of 363 villa owners or managers, utilising the PLS-SEM technique, it explores how personal values, reasons for and against, and attitudes influence HAS adoption intentions. The findings underscore the significant impact of attitude on adoption intentions, with values significantly affecting attitude and reasons for and against. Interestingly, while reasons for directly influence intention, reasons against have the opposite effect. Future research avenues could explore additional factors influencing technology adoption and delve into the long-term implications of technology integration on organisational performance and user satisfaction. This study enriches theoretical frameworks and offers actionable insights for enhancing technology adoption in the hospitality industry and beyond.

Trash in the bin, to a cleaner scene we cling: a mixed method approach on tourists’ binning behavior at two spiritual destinations

ABSTRACT This study investigates tourists’ binning behavior and its importance for the environmental sustainability of tourist destinations, a topic currently understudied in academic research. Through the lens of behavioral reasoning theory (BRT), it explores the factors influencing tourists’ decisions to dispose of waste properly, employing a mixed-methods approach. Initial qualitative research at the Indian spiritual sites of Rishikesh and Haridwar identifies key motivators and barriers to binning behavior. These findings are then integrated into the BRT framework and confirmed via quantitative analysis using PLS-SEM. Results show that the perceived sacredness of a site and awareness of environmental risks encourage proper waste disposal, whereas perceptions of inefficacy, lack of facilities, and established habits deter it. The study underscores the role of environmental values in promoting responsible waste disposal, offering practical suggestions for enhancing sustainable tourism through targeted interventions in spiritual tourism settings.

Understanding Telehealth Adoption among the Elderly: An Empirical Investigation

The adoption of telemedicine among the elderly is vital due to their unique healthcare needs and growing engagement with technology. This study explores the factors influencing their adoption behaviors, identifying both facilitating and inhibiting elements. While previous research has examined these factors, few have empirically assessed the simultaneous influence of barriers and enablers using a sample of elderly individuals. Using behavioral reasoning theory (BRT), this research investigates telehealth adoption behaviors of the elderly in India. A conceptual model incorporates both “reasons for” and “reasons against” adopting telehealth, capturing the nuanced dynamics of adoption behaviors. Data from 375 elderly individuals were collected to validate the model through structural equation modeling. The findings reveal that openness to change significantly enhances attitudes towards telehealth and “reasons for” adoption, influencing behaviors. This research contributes to the healthcare ecosystem by improving the understanding of telehealth adoption among the elderly. It validates the impact of openness to change alongside reasons for and against adoption, refining the understanding of behavior. By addressing impediments and leveraging facilitators, this study suggests strategies to maximize telehealth usage among the elderly, particularly those who are isolated, improving their access to medical services.

Antecedent research on cross-border E-commerce consumer purchase decision-making: The moderating role of platform-recommended advertisement characteristics

Relying on the development of big data, internet technology, and digital trade, consumers are seeking cross-border e-commerce platforms increasingly. Platform-based advertising communication, characterized by low cost and wide coverage, is notable as one of the marketing strategies favored most within general cross-border e-commerce platforms. It furnishes consumers with abundant shopping options while it exerts influence on their purchasing decisions concurrently. Using Behavioral Reasoning Theory to explore in-platform advertisements' effect on consumer purchasing decisions in cross-border e-commerce platforms, this study introduces advertising features as moderating variables. From the perspectives of self-efficacy, behavioral rationality, and inclusiveness, a behavioral reasoning model for consumer purchasing decisions is constructed. This paper focuses on cross-border e-commerce platform consumers as the research object, and uses Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyze the data and validate the model. The results show that self-efficacy and behavioral rationality can have a direct effect on consumers' purchase decision-making behaviors, while self-efficacy plays a significant mediating role between behavioral reasonableness and purchase decision-making behaviors. Inclusiveness has a significant direct effect on self-efficacy and behavioral reasonableness; moreover, advertisement characteristics have a significant negative moderating effect on inclusiveness and behavioral reasonableness-adoption. This study revealed the influencing mechanisms of consumers' purchasing decision behavior on cross-border e-commerce platforms, and expands the scope of Behavioral Reasoning Theory's application. Further, it provides valuable insights for the development of cross-border e-commerce platforms that have both theoretical and practical significance.

Unveiling the influencing mechanism underlying users’ adoption and recommend intentions of central bank digital currency: A behavioral reasoning theory perspective

Despite the enormous benefits of the implementation of central bank digital currency (CBDC), the realization of these anticipated benefits depends on users' adoption and recommendations resulting from the consideration of both facilitators and inhibitors. Drawing on the behavioral reasoning theory (BRT), this study endeavors to unveil the influencing mechanism underlying users' CBDC adoption and recommend intentions using a hybrid approach integrating qualitative study (i.e., thematic analysis) and quantitative study (i.e., PLS-SEM). The qualitative research results indicate that relative advantage, incentive measures, government support, compatibility, and convenience are the “reasons for” users' CBDC adoption and recommend intentions, while tradition barrier, risk barrier, usage barrier, and image barrier are the “reasons against” users' CBDC adoption and recommend intentions. Further, the quantitative analysis of 638 pilot CBDC users suggests that users' CBDC adoption intentions positively influence their CBDC recommend intentions. “Reasons for” positively influence both users' attitudes and adoption intentions toward CBDC, whereas “reasons against” only negatively influence users' adoption intentions toward CBDC. Values (openness to change) positively influence users' “reasons for” and attitudes toward CBDC, and negatively influence users' “reasons against” adopting CBDC. Financial literacy strengthens the paths between “reasons for” and adoption intentions and weakens the paths between “reasons against” and adoption intentions. Theoretically, this study contributes by providing a thorough knowledge of users’ values, reasons, attitudes, and adoption and recommend intentions toward CBDC. Practically, this study renders insightful policy implications for central banks worldwide to promote CBDC applications.

Antecedents to the Adoption of Digital Marketing by Start-Ups Under Startup-India and E-Governance Initiatives

India is witnessing a dual transformation marked by technological advancements and a surge in entrepreneurial activity following the launch of various e-governance schemes and the Startup India program. However, the high failure rate among startups remains a significant concern, often attributed to inadequate marketing efforts due to financial constraints. To address this issue, enhancing digital marketing initiatives under Startup India could offer cost-effective solutions with higher returns on ad spend (ROAS). This research, grounded in the Behavioral Reasoning Theory (BRT), utilized cross-sectional data analyzed through Partial Least Square-Structured Equation Modelling (PLS-SEM) using SmartPLS software. The study revealed that beliefs, values, reasons for and against adoption, and attitudes influence startups' adoption of digital marketing. The findings of this study aim to provide practical insights for Startup India programs, entrepreneurs, and policymakers to understand better the motivators and barriers to adopting digital marketing technologies.

The effect of educational intervention based on the behavioral reasoning theory on self-management behaviors in type 2 diabetes patients: a randomized controlled trial

BackgroundDiabetes self-management education is necessary to improve patient outcomes and reduce diabetes-related complications. According to the theory of behavioral reasoning, the likelihood of performing a behavior is predicted by the link between beliefs, motivation, intention, and behavior. This study aimed to investigate the effect of an educational intervention based on the Behavioral Reasoning Theory (BRT) on self-management behaviors in patients with Type 2 Diabetes.MethodsA randomized controlled trial based on BRT was conducted on 113 patients with type 2 diabetes, with a control group and an intervention group followed for 3and 6 months. Data were collected using a researcher-made demographic questionnaire based on the constructs of BRT and behaviors related to self-management in patients with type 2 diabetes. In the intervention group were provided, 8 sessions of diabetes self-management education based on BRT. The control group only received the usual training of the center. Data was analyzed using SPSS26 software.ResultsAfter the educational interventions in the intervention group, there were statistically significant changes observed in the mean scores of all constructs, fasting blood sugar, and glycosylated hemoglobin. On the other hand, no statistically significant change was observed in the mean grades of the control group. All the observed changes were significant at the 0.05 level.ConclusionsThe results of this study were in favor of the effectiveness of an educational intervention that promotes diabetes self-management behaviors, using the principles of the behavioral reasoning theory. Which can be used in the design of health promotion programs for patients with diabetes.Trial registrationIranian Registry of Clinical Trials (IRCT), IRCT20131014015015N21.

Determinants of artificial intelligence-assisted diagnostic system adoption intention: A behavioral reasoning theory perspective

Artificial intelligence-assisted diagnostic systems (AIADS) signify a significant medical revolution, reducing environmental burdens and enabling AI-based medical services to catalyze sustainability-oriented positive change. Because users demonstrate almost contradictory attitudes or resistance to adopting medical information provided by AIADS, controversy persists regarding the use of the technology. Based on behavioral reasoning theory (BRT), this study adds empirical insights into the significant influence of users' values (openness to change) toward reasons (for and against) and their intentions to adopt AIADS from the perspective of behavioral reasoning. A scenario questionnaire survey of 604 Chinese users demonstrated that openness to change significantly impacts users' attitudes and reasons (for and against) adopting AIADS. A dual pathway explains the reasons for and against adopting AIADS. The findings contribute to BRT's application in AI-assisted medical service and provide implications to practitioners that will increase users' adoption of AIADS.

Determinants of ChatGPT Use and its Impact on Learning Performance: An Integrated Model of BRT and TPB

The rapid emergence of Generative Artificial Intelligence (GAI) heralds a significant shift, opening new frontiers in how education is delivered. This groundbreaking wave of technological advancement is poised to redefine traditional learning, promising to enhance the educational landscape with unprecedented levels of personalized learning and accessibility. Despite GAI’s progressive infiltration into various educational strata, limited empirical research exists on its impact on students’ learning performance. Drawing on the Theory of Planned Behavior (TPB) and Behavioral Reasoning Theory (BRT), this study investigates the determinants affecting students’ use of ChatGPT and its influence on learning performance. The data were collected from 357 university students and were analyzed using the PLS-SEM technique. The results supported the role of ChatGPT in positively affecting students’ learning performance. In addition, the results showed that reasons for and against adoption are pivotal in shaping students’ attitudes. ChatGPT use is found to be significantly affected by attitudes, subjective norms, and perceived behavioral control. Besides the theoretical contributions, the findings offer various implications for stakeholders and underscore the necessity for educational institutions to foster a conducive environment for GAI adoption, addressing ethical and technical concerns to optimize learning experiences.

An Empirical Study on the Willingness of Young Elderly to Use Elderly Companion Robot

In the context of an aging population, this study addresses the deficiency in existing research, which predominantly explores the willingness to utilize elderly companion robots from a positive standpoint. Our aim is to conduct a comprehensive analysis of the factors influencing the willingness of elderly individuals, with a focus on the young elderly population, to use elderly companion robot. We also intend to offer insights for the design and operation of these elderly companion robot. This study adopts the Behavioral Reasoning Theory (BRT) as its theoretical framework and incorporates the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model to examine the impact of various factors on users’ attitudes and behavioral intentions. We approach this analysis from both “reasons for” and “reasons against” perspectives, utilizing structural equation modeling as our analytical method to explore how each factor affects users’ attitudes and behavioral intentions. Values positively influence performance expectancy, social impact, facilitating conditions, and hedonic motivation, while negatively affecting hindering expectancy, low price value, unhabit, and privacy issues. Performance expectancy, facilitating conditions, and hedonic motivation have a positive impact on older people’s attitudes toward elderly companion robots, while unhabit negatively influences their attitudes. Social impact and hindering expectancy positively and negatively impact the elderly’s willingness to use elderly companion robots. Designers and manufacturers of robots can enhance the willingness of elderly individuals to use elderly companion robots by improving positive elements and addressing or modifying negative elements.

Investigating consumers’ adoption of AI chatbots for apparel shopping

Purpose Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping. Design/methodology/approach Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model. Findings The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping. Originality/value This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

Sipping a sustainable life: Exploring drivers and barriers in consumer attitudes toward non or low alcoholic spirits

Alcohol consumption continues to be prevalent and is on the rise in many countries, posing a grave risk for the health and wellbeing of millions and creating a strain on health services worldwide. A hopeful trend has emerged, however, as consumers' growing preference for healthier, sustainable lifestyles has led traditional alcoholic brands to innovate, launching reduced or non-alcoholic (NoLo) options. This aligns with the SDGs and is reflected in NoLo spirits representing four of Spain's top ten disruptive innovations of 2022. This paper uses a mixed methodology in a qualitative-quantitative sequential approach to gain insight into this phenomenon. The study involved 13 in-depth interviews with HoReCa (an acronym for Hotels, Restaurants, and Caterings) professionals and four focus groups among consumers. Second, behavioral reasoning theory (BRT) was used in a quantitative study aiming to explore motivations for and against consuming NoLo spirits. Data from a survey of 620 participants was conducted and analyzed using SEM-PLS to measure the antecedents of consumer's behavioral intention towards NoLo spirits and to gauge the potential for marketing opportunities. The research reveals that the purchase intention of NoLo spirits is strongly related to health consciousness, while enjoying the effects of alcohol for fun and entertainment, and the social pressure to drink hinders its consumption. In addition, it was found that “reasons for” are more substantial than “reasons against” the consumption of those beverages, differing significantly by age group. Results offer implications for theory and practice, including recommendations for practitioners and regulators willing to improve sustainability in the industry. Further, this paper helps augment the innovation adoption literature by using BRT in the paradoxical context of consumers' increasing alcohol abuse despite their professed attempts to adopt healthier lifestyles.

Consumers’ Intention to Use Renewable Energy Based on the Behavioral Reasoning Theory

Public concerns about climate change and environmental protection have triggered governments and corporations to do research on clean and cost-effective forms of energy. Green energy is relatively new in developing countries, which results in limited market penetration and low consumer acceptance. This study aims to investigate the relationship between global motives and consumer intentions to use renewable energy via the Behavioral Reasoning Theory (BRT). In this research, reasons for supporting the utilization of renewable energy are shown through environmental concerns and perceived benefits, while reasons against it are represented through perceived costs. An online survey obtained 275 valid data responses from Indonesian middle- and upper-class consumers. This data was analyzed using PLS-SEM to maximize the model's predictive value. All hypotheses tested, except for the effect of environmental concern and perceived cost on attitude, were proven to influence customer intentions to use renewable energy. This study found that perceived benefits gave the largest contribution to global motives for using renewable energy. Since this study involved consumers from the middle to upper class in developing countries, perceived behavioral control had the most influence on intention to use renewable energy compared to attitude and subjective norms.

Metode behavioral reasoning theory untuk meningkatkan daur ulang limbah gawai elektronik generasi Z di Jabodetabek

Background: This study examines the e-waste recycling intention of Generation Z (17-24 years old) in JABODETABEK which has a high level of adoption of electronic products. Method: This is a quantitative research with descriptive and single-cross sectional design. This study uses an innovation acceptance theory approach, namely Behavioral Reasoning Theory (BRT) with variables of value, reasons for, reasons against, attitude and intention. Partial Least Square – Structural Equation Modeling (PLS-SEM) is used to analyze the survey data due to non-normality of data distribution. Finding: This study finds that value has a positive effect on attitude and reasons for, both of which have a positive effect on intention. The reasons against variable shows that it is not affected by value and does not affect attitude or intention.

Assessing Factors Influencing Customers’ Adoption of AI-Based Voice Assistants

ABSTRACT The study aims to assess the factors that engage and accentuate usage pertaining to consumers with artificial intelligence-based voice assistants. Drawing on the Behavioral Reasoning Theory (BRT), the paper establishes relationships between the enablers and inhibitors on the adoption intention of voice assistants. To examine the hypothesized relationship, a quantitative approach employing PLS-SEM was utilized to evaluate a representative sample of 1189 Indian consumers and examining the psychological and functional constructs leading to adoption intention for voice assistants. The study reveals that the “value of openness to change” poses a significant effect toward “reasons for” adoption, among which “performance expectancy” and “hedonic motivation” play the most significant role in establishing a favorable attitude toward voice assistants’ adoption. Among the “reasons against”, the “value barrier” and “image barrier” come out to be major determinants leading to inhibitions regarding the usage of voice assistants. Besides this, the findings reclaim that “reasons” (for/against) shape to form the attitude of consumers toward voice assistants. The current research offers preliminary evidence with regard to the investigation of voice assistant adoption using the BRT that jointly examines enabling and inhibiting elements leading to consumers’ attitude formation. The study findings contribute to Human-Computer interaction literature by utilizing BRT framework which provides incremental evidence demonstrating a much broader and organic explanation of consumers’ cognition for the adoption of voice assistant technology. It also provides implications for tech-managers and algorithm designers to build effective voice technology for superior user experience.

Factors Influencing Customers’ Apparel Shopping Intention in Metaverse

ABSTRACT The emergence of the metaverse has opened an unbelievable online virtual world offering real-life immersive experiences to consumers. This study examines customers’ fashion apparel shopping intentions in the e-commerce metaverse. We propose a conceptual framework based on behavioral reasoning theory (BRT) to investigate the reasons for the adoption (or not) of the metaverse. The survey of 1170 customers was performed, and PLS-SEM was used to analyze data. The findings suggest that perceived enjoyment, interactivity, imagination, and sense of immersion favors the adoption, whereas perceived risk, traditional barrier, image barrier, and technological anxiety deter metaverse adoption. Our results advance the literature on innovative shopping technology and metaverse fashion apparel shopping intention. We provide guidelines for metaverse marketers and managers.

Examining the Moderating Role of Reasons in Masstige Luxury Buying Behavior.

This study proposes a new model derived from Behavioral Reasoning Theory (BRT) to examine the purchasing behavior of masstige jewelry consumers. The suggested model provides a more comprehensive understanding of the determinants of purchasing masstige products by considering values and reasons in addition to the global motives and intention. The study also examines, for the first time, the moderating role of reasons. It explores how reasons may strengthen or weaken the impact of perceived values on global motives. The proposed model was empirically tested using partial least squares-structural equation modeling (PLS-SEM) with survey data on the consumption of masstige jewelry brands in Türkiye. To provide a more complete understanding of the moderating role of reasons, submodels were constructed for different value-reason combinations. The results demonstrate notable differences in the goodness-of-fit measures between the moderated and non-moderated models. Specifically, reasons contributed to enhanced explanations of global motives and intention, both directly and indirectly. However, not all submodels yielded significant results in terms of the moderator effect. Thus, the empirical tests supported the hypotheses regarding the moderating effect only partially. Overall, the current findings further extend the existing frameworks and provide valuable insights into masstige jewelry purchasing behavior, which can be used by marketers to develop more effective strategies.