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This paper aims to develop an integrated framework for a deeper understanding of employee sustainable behaviors in the workplace by using theories, such as behavioral reasoning theory, planned-behavior theory, goal-directed behavior theory, norm activation theory and belief-value-norm theory.

A quantitative approach is used in the present research. This study used data from 343 employees who are from the hospitality and tourism industry to investigate the formation of employees’ sustainable behaviors.

The research framework assumes that the reasons for sustainable behavior and the reasons against sustainable behavior predict global motives, which comprise attitude, subjective norm and behavioral control, and moral norm mediates the relationship between global motives, positive and negative anticipated emotions and behavioral intention. The hypothesized theoretical model had a sufficient degree of total variance with the behavioral intention and generally verified the hypothesized relationships, which served as a basis for modeling employee sustainable behavior in the workplace.

This study integrated a framework that contributes to employee sustainable behavior in the tourism and hospitality industry by identifying the effects of motivational process, moral process and emotional process to perform sustainable behavior.

To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.

A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.

The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.

This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

The purpose of this paper is to examine the relative influence of “reasons for” and “reasons against” adoption of mobile banking (m-banking) among Indian consumers.

Using the framework of behavioral reasoning theory (BRT), hypothesized relationships between values, reasoning constructs, attitude and intentions were developed. The hypotheses were tested using a representative sample of data obtained from Indian banking consumers (n=379). Confirmatory factor analysis and structural equation modeling were used to analyze the data.

The findings indicate that both “reasons for” and “reasons against” have an influence on m-banking adoption. Among the “reasons for” m-banking adoption, ubiquitous is the major determinant, and among the “reasons against” m-banking adoption, tradition barrier is the major determinant. The findings also confirm that value of “openness to change” significantly influences reasons for adoption and has no impact on reasons against and attitude toward m-banking.

This study examines customers in only one context (i.e. India). Future research can examine samples in other countries so that the results can be generalized. Also the mediating role of demographic factors can be studied in future studies to predict m-banking adoption.

The findings of this study emphasize the importance of examining both the pro-adoption and anti-adoption factors while developing marketing strategy. This study confirms that m-banking adoption can be increased if managers attempt to minimize the effect of barriers of m-banking adoption.

This is the first study to examine m-banking adoption using BRT, which investigates the reasons for and reasons against m-banking adoption in a single framework.

The purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based wearables for the healthcare of older adults and it aims to understand the relative effect of “reasons for” and “reasons against” adoption of IoT-based wearables for health care among older adults.

The hypothesized relationships were established using the BRT and empirically tested using a representative sample of 815 respondents. The data were analyzed using the PLS-SEM method.

The findings of this study demonstrate that adoption intention of IoT-based wearables for the health care of older adults is influenced by “reason for” and “reason against” adoption. The finding shows that “reasons for” adoption are ubiquitous, relative advantage, compatibility and convenience and “reasons against” adoption are usage barrier, traditional barrier and risk barrier. Value of “openness to change” significantly influences the “reasons for” and “reasons against” adoption of IoT-based wearables.

This cross-sectional study is conducted only in the Indian context and future research can be conducted in other countries to generalize the results.

This research highlighted both the adoption factors—“for” and “against,” which should be considered while developing marketing strategies for IoT-based wearables for health care of older adults. Adoption of IoT-based wearables for healthcare of older adults will increase when marketers endeavor to minimize the effects of the anti-adoption factors.

This is a unique study that examines the adoption of IoT-based wearables for healthcare among older people using the BRT, by probing the “reasons for” and “reasons against” adoption in a single framework.

This study aims to explore the essential factors of the reason for (RF) and reason against (RA) and their impact on tourist attitudes and intentions to use e-bike sharing services by using a novel approach based on behavioral reasoning theory (BRT).

A quantitative method was used to collect data from 292 tourists and analyze the data using the partial least squares structural equation modeling (PLS-SEM) technique.

The outcomes indicate that both “RF” and “RA” are crucial in affecting tourist attitudes and intentions to use e-bike-sharing services. In addition, factors such as convenience, price saving and time saving were identified as “RF” while “RA” weather conditions, safety concerns and image barriers were identified that affect tourist attitudes and intention to use e-bike sharing services. These findings also indicate that tourists’ values of openness to change significantly influence “RF” and have no impact on “RA” and attitude toward e-bike-sharing services.

This study provides valuable insights that complement the existing literature on electric bike sharing and BRT in the context of promoting sustainable and eco-friendly consumption.

This research takes a significant step forward in investigating the tourist attitudes and intentions toward using e-bike sharing services in a tourist destination growing economy by using the BRT theory and proposing a model that considers both the “RF” and “RA” using e-bikes for urban transportation.

本研究旨在利用基于 BRT 的新方法, 探讨使用电动自行车共享服务的支持原因（RF）和反对原因（RA）的基本因素及其对游客使用电动自行车共享服务的态度和意图的影响。

采用定量方法收集 292 名游客的数据, 并使用 PLS-SEM 技术分析数据。

结果表明“RF”和“RA”对于影响游客使用电动自行车共享服务的态度和意图至关重要。此外, 方便、节省价格和节省时间等因素被确定为“RF”, 而“RA”则被确定为影响游客态度和使用电动自行车共享服务意愿的天气条件、安全问题和形象障碍。这些发现还表明, 游客对变革的开放价值观显着影响“RF”, 但对“RA”和对电动自行车共享服务的态度没有影响。

这项研究提供了宝贵的见解, 在促进可持续和环保消费的背景下补充了有关电动自行车共享和 BRT 的现有文献。

本研究利用 BRT 理论, 在调查经济增长的旅游目的地中游客对使用电动自行车共享服务的态度和意图方面迈出了重要一步, 并提出了一个同时考虑“RF”和“RA”的模型用于城市交通的电动自行车。”

Este estudio pretende explorar los factores esenciales de las razones a favor (RF) y en contra (RA) y su impacto en las actitudes e intenciones de los turistas de utilizar los servicios de bicicletas eléctricas compartidas (e-bike sharing) utilizando un enfoque novedoso basado en la BRT.

Se utilizó un método cuantitativo para recopilar datos de 292 turistas y analizarlos mediante la técnica PLS-SEM.

Los resultados indican que tanto la “RF” como la “RA” son cruciales para afectar a las actitudes e intenciones de los turistas de utilizar los servicios de e-bike-sharing. Además, se identificaron como “RF” factores como la comodidad, el ahorro de precio y el ahorro de tiempo, mientras que como “RA” se identificaron las condiciones meteorológicas, las preocupaciones por la seguridad y las barreras de imagen que afectan a las actitudes de los turistas y a su intención de utilizar los servicios de e-bike sharing. Estos resultados también indican que los valores de apertura al cambio de los turistas influyen significativamente en “RF” y no tienen ningún impacto en “RA” ni en la actitud hacia los servicios de e-bike sharing.

Este estudio aporta valiosas ideas que complementan la bibliografía existente sobre el uso compartido de bicicletas eléctricas (e-bike sharing) y el BRT en el contexto de la promoción de un consumo sostenible y respetuoso con el medio ambiente.”

Esta investigación da un importante paso adelante en la investigación de las actitudes e intenciones de los turistas hacia la utilización de los servicios de e-bike sharing en un destino turístico de economía en crecimiento utilizando la teoría del BRT y proponiendo un modelo que tiene en cuenta tanto la “RF” como la “RA” que utilizan las e-bikes para el transporte urbano.”

Blockchains provide significant benefits for business operations due to its transparency, traceability and information sharing. However, application to the food and beverage (F&B) industry was scarce. The purpose of this study is to explore how to form F&B managers’ blockchain adoption by applying behavioral reasoning theory (BRT). Additionally, supply chain partnerships (SCPs) were tested for the potential moderating roles within BRT. This study’s findings expand existing knowledge by providing novel information for F&B management.

Data were collected from F&B managers by using an online survey method. A structural equation modeling and multi-group analysis were performed to test the hypothesized relationships.

Findings revealed that the positive effects of “reasons for” on “attitudes,” and “adoption intentions” while “reasons against” did not show such effects. Environmental benefits of blockchains were found to lead more positive attitudes while traditional barriers were the greatest constraints for adopting blockchains. This study supports the significant moderating roles of SCPs within the context of F&B blockchain adoption.

This study contributes to the technology literature in the foodservice context by applying BRT as a theoretical lens. The importance of developing SCPs for F&B blockchain adoption and exploitation is highlighted.

区块链因其透明度、可追溯性和信息共享而为企业运营提供了重要的好处。然而, 将其应用于食品和饮料（F&B）行业却很少见。本研究探讨了如何通过应用行为推理理论（BRT）来形成 F&B 管理者的区块链采用。此外, 本研究还测试了供应链合作（SCPs）在BRT内的潜在调节作用。通过为F&B 管理提供新颖信息, 我们的研究结果扩展了现有知识领域。

采用在线调查方法收集了来自 F&B 管理者的数据。进行了结构方程建模和多组分析, 以测试假设关系。

研究结果显示, “支持的原因”对“态度”和“采用意向”有积极影响, 而“反对的原因”则没有显示出这种影响。区块链的环境优势被发现会导致更积极的态度, 而传统障碍是采用区块链的最大限制因素。本研究还证实了 SCP 在 F&B 区块链采用背景下的重要调节作用。

本研究通过应用 BRT 作为理论视角, 为餐饮服务背景下的技术文献做出了贡献。强调了发展 F&B 区块链采用和利用的供应链合作的重要性。

This study aims to use the novel approach of applying the behavioural reasoning theory (BRT) to understand the relative influence of reason for and reason against the adoption of mobile learning applications (M-learning apps) among information technology (IT) and information technology enabled services (ITeS) employees.

This study surveys 680 employees of IT and ITeS companies in India to examine the adoption of M-learning apps for learning using the BRT and the primary data analysis was done using the partial least squares-structural equation modelling technique.

It is found that the context-specific adoption factors for M-learning apps are hedonic motivation, self-efficacy, learning autonomy, ubiquitous and relative advantage, whereas the reasons against adoption of the M-learning apps are traditional barrier, usage barrier and image barrier. It is also found that values of openness to change positively affect the reasons for adoption and do not significantly affect reasons against adoption of M-learning. Values of openness to change affect the attitude towards M-learning apps and attitude affects the adoption intention of M-learning apps for learning.

This cross-sectional study was conducted only in the Indian IT/ITeS firms and future research can be conducted in other sectors and countries to generalize the results.

This research uniquely highlights the adoption factors both for and against, which should be considered while developing marketing strategies for M-learning apps’ adoption. It is imperative for training managers to consider these factors during the selection of M-learning apps and for designers while designing the M-learning apps.

This study provides new insights towards the use of mobile apps for learning with the employees’ perspective using the BRT theory and it highlights the reason for adoption and reason against adoption of M-learning apps.

The purpose of this study is to investigate the motivations and barriers behind the adoption of bike-sharing services, explore the influence of individual values and environmental knowledge on bike-sharing adoption and analyze the relationship between reasons, attitude and intention to utilize bike-sharing.

The study initially conducted a semi-structured interview with 19 bike-sharing users and performed a thematic analysis to identify the context-specific motivators and barriers. The identified factors were then incorporated into the behavioral reasoning theory (BRT) framework and quantitatively examined using the data gathered from 412 Indian bike-sharing users.

The findings outlined the complex reasoning process underlying bike-sharing adoption and how environmental value and attitude are related to the reasons. Further, the study examined the moderating impact of environmental knowledge, which was overlooked in previous studies.

The study provides valuable suggestions to bike-sharing businesses, which helps them to induce facilitators and remove barriers.

Behavioral research in bike-sharing is in its embryonic stage. This is one of the initial attempts to address this knowledge deficit by comprehensively examining the factors affecting bike-sharing intention through the theoretical lens of BRT.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

The purpose of this paper is to investigate the adoption of Internet of Things (IoT) in the agriculture industry by the farmers' in India using the theoretical lens of the behavioral reasoning theory (BRT).

A survey on farmers was conducted to examine the adoption of IoT in agriculture industry (IoT-A) using BRT. The data analysis of the primary survey was done by applying the structural equation modelling (SEM) technique.

The ‘reasons for’ adoption of IoT-A were as follows: Relative advantage, social influence, perceived convenience, and perceived usefulness. The ‘reasons against’ adoption were as follows: Image barrier, technological anxiety, perceived price and perceived risk. The BRT theory provides the platform to discuss the psychological processing of acceptance of IoT in agriculture industry by the farmers.

This research has unique implications as it studies the rural consumers’ behavior of innovation adoption namely IoT in agriculture. It provides the specific reasons ‘for’ and ‘against’ IoT adoption in agriculture, which will give directions to the marketers of IoT technology to develop suitable marketing strategies to improve the adoption in rural areas.

This research takes the first step in the direction toward deliberation of the adoption of IoT-A by farmers in an emerging Indian economy using the BRT theory, which discusses the ‘reasons for’ and ‘reasons against’ adoption in a proposed model.