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Mountaineering and related activities are increasingly becoming popular and are accompanied by an increase in medical incidents. Emergency operations in mountainous terrain are time-critical and often pose major logistical challenges for rescuers. Drones are expected to improve the operational performance of mountain rescuers. However, they are not yet widely used in mountain rescue missions. This paper examines the determinants that drive the behavioral intention of mountain rescuers to adopt drones in rescue missions.

This is a behavioral study that builds upon an extended model of the unified theory of acceptance and use of technology (UTAUT) and investigates the relationship between individual attitudes, perceptions, and intentions for drone adoption. Original survey data of 146 mountain rescuers were analyzed using moderated ordinary least squares (OLS) regression analysis.

Results indicate that the behavioral intention to use drones in mountain rescue missions is driven by the expected performance gains and facilitating conditions. Favorable supporting conditions and experience with drones further moderate the relationship between performance expectancy and behavioral intention. The effects for effort expectancy, social influence, and demonstrations were not significant.

Rescue organizations and stakeholders are recommended to consider the identified determinants in the implementation of drones in emergency logistics. Drone manufacturers targeting mountain rescue organizations are advised to focus on operational performance, provide sufficient support and training, and promote the gathering of practical experience.

A tailored-model that provides first empirical results on the relevance of personal and environmental factors for the acceptance of drones in emergency logistics is presented.

This study aims to investigate the factors that influence behavioral intention (BI) and usage of e-wallets by extending the unified theory of acceptance and use of technology (UTAUT) with constructs, namely, mobile self-efficacy, perceived enjoyment and satisfaction.

This quantitative study used partial least squares structural equation modeling on a sample of 576 mobile e-wallet users surveyed online.

The key findings indicate that the model can explain 58.8% of the variance in behavioral intention and 53.8% in usage. Moreover, mobile self-efficacy has a significant influence on perceived enjoyment. Perceived enjoyment significantly affects satisfaction, effort expectancy and performance expectancy. Furthermore, effort expectancy significantly influences customer satisfaction in contrast to performance expectancy. In addition, although performance expectancy, social influence and satisfaction significantly impact consumers’ behavioral intention, effort expectancy and facilitating conditions condition have an insignificant influence on consumers’ behavioral intention. E-wallet stakeholders can use the findings of this study to make strategic decisions regarding the e-wallet ecosystem.

Although previous studies have independently addressed the impact of mobile self-efficacy, perceived enjoyment and satisfaction on consumers’ behavioral intention and usage behavior, the expanded framework with the possible relationships proposed in this study has never been adequately studied in previous research in the context of e-wallets in developing countries based on an empirical analysis. This study represents one of the first attempts to improve the UTAUT by empirically analyzing these relationships.

Este estudio tiene como objetivo investigar los factores que influyen en la intención de comportamiento y el uso de los monederos electrónicos mediante la ampliación de la teoría unificada de aceptación y uso de la tecnología (UTAUT) con los constructos de autoeficacia móvil, disfrute percibido y satisfacción.

Este estudio cuantitativo utilizó un modelo de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM) sobre una muestra de 576 usuarios de monederos electrónicos móviles encuestados en línea.

Los principales resultados indican que el modelo puede explicar el 58,8% de la varianza en la intención de comportamiento y el 53,8% en el uso. Además, la autoeficacia en el uso del móvil influye significativamente en el disfrute percibido. El disfrute percibido afecta significativamente a la satisfacción, la expectativa de esfuerzo y la expectativa de rendimiento. Además, la expectativa de esfuerzo influye significativamente en la satisfacción del cliente, en contraste con la expectativa de rendimiento. Además, aunque la expectativa de rendimiento, la influencia social y la satisfacción influyen significativamente en la intención de comportamiento de los consumidores, la expectativa de esfuerzo y la condición de condiciones facilitadoras tienen una influencia insignificante en la intención de comportamiento de los consumidores. Las partes interesadas en los monederos electrónicos pueden utilizar las conclusiones de este estudio para tomar decisiones estratégicas en relación con el ecosistema de los monederos electrónicos.

Aunque estudios anteriores han abordado de forma independiente el impacto de la autoeficacia móvil, el disfrute percibido y la satisfacción en la intención de comportamiento y la conducta de uso de los consumidores, el marco ampliado con las posibles relaciones propuestas en este estudio nunca se ha estudiado adecuadamente en investigaciones anteriores en el contexto de los monederos electrónicos en los países en desarrollo sobre la base de un análisis empírico. Este estudio representa uno de los primeros intentos de mejorar el UTAUT analizando empíricamente estas relaciones.

本研究旨在通过扩展统 – 的技术接受和使用理论 (UTAUT), 研究影响电子钱包行为意图和使用的因素, 包括移动自我效能、感知乐趣和满意度等建构。

这项定量研究采用偏最小二乘法结构方程模型 (PLS-SEM), 对576名移动电子钱包用户进行了在线调查。

主要研究结果表明, 该模型可以解释58.8%的行为意图和53.8%的使用差异。此外, 移动自我效能感对感知到的享受有显著影响。感知到的享受显著影响满意度、努力期望和绩效期望。此外, 与绩效期望相比, 努力期望对顾客满意度有显著影响。此外, 尽管绩效期望、社会影响和满意度对消费者的行为意图有显著影响, 但努力期望和便利条件对消费者的行为意图没有显著影响。电子钱包的利益相关者可以利用本研究的结果来做出有关电子钱包生态系统的战略决策。

尽管之前的研究已经独立地探讨了移动自我效能、感知享受和满意度对消费者行为意图和使用行为的影响, 但本研究提出的具有可能关系的扩展框架在之前的研究中从未基于实证分析对发展中国家的电子钱包进行充分研究。本研究是通过实证分析这些关系来改进UTAUT的首次尝试之一。

This study aims to examine the mediating role of social influence on the relationship between key predictors of E-pharmacy adoption among young consumers based on the unified theory of adoption and use of technology (UTAUT).

This study employs a quantitative correlational research design. Based on cluster sampling, data was collected from 306 university students from three public universities in southwestern Nigeria. Data was analysed using partial least square structural equation modeling.

The primary determinant driving the adoption of e-pharmacy is performance expectancy. Social influence plays a partial mediating role in linking performance expectancy to e-pharmacy adoption. In contrast, it fully mediates the relationship between effort expectancy, facilitating conditions and the adoption of e-pharmacy services.

This study provides theoretical clarity on recent issues within the UTAUT framework. Findings highlight the complexity of how social factors interact with individual beliefs and external conditions in determining technology acceptance.

Research includes information relevant to access the impact of e-pharmacy services on healthcare accessibility, affordability and quality in developing countries.

The findings extend the adoption of technology literature in healthcare and offer a new understanding of adoption dynamics. The results emphasize the importance of performance expectancy in driving e-pharmacy adoption, providing a clear direction for stakeholders to enhance service quality and user experience of e-pharmacy. Additionally, the mediating effect of social influence highlights the significance of peer recommendations, celebrity endorsements and social media campaigns in shaping consumer adoption of e-pharmacies among young people.

In this article, the authors draw-upon an extended unified theory of acceptance and use of technology (UTAUT) and propose a research model involving performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and competitive pressure (CP) as potential salient factors explaining the adoption of digitalization in European SMEs. The authors also postulate that there may be cross-cultural differences, thereby leading us to include the country as a moderator in the model.

The authors validate this model with a cross-cultural sample involving 188 owner-managers from the Czech Republic and Slovakia and through the partial least square structural equation modeling (PLS-SEM) techniques as well as multi-group analysis.

The results using the study’s global dataset indicate that PE, FC and CP significantly affect owner-managers intentions toward digitalization in SMEs. The authors’ application of the multi-group analysis also suggests that although the two countries differ in digitalization adoption intention, the differences are statistically insignificant. In the conclusion, the authors highlight several implications these findings have for theory and practice.

The authors recommend that the providers of emerging digital technologies should improve on the performance features of those technologies and ensure they are relevant to the SMEs. By doing so, the adoption of digitalization will grow, because owner-managers of SMEs will have the confidence that adopting such technologies will improve their operations. Second, SMEs are required to provide adequate organizational and technical infrastructure to support digitalization adoption.

Aside from being among the few attempts to extend the explanatory power of UTAUT with PE, EE, FC and CP in investigating digitalization adoption in SMEs context, this study also validates its model with rigorous methodological approach as well as three datasets (global, Czech Republic and Slovakia) thereby strengthening the validity of the results.

The study applied the Unified Theory of Technology Acceptance and Use Theory 2 (UTAUT2) to predict blended learning acceptance by students in universities in Zimbabwe. Blended learning is a heterogeneous mode of teaching and learning that combines face-to-face (F2F) and online modes. Owing to advances in technology, and recently, the advent of pandemics, such as COVID-19, the need for multimodal teaching approaches, such as blended learning, to enhance access to education in universities has become very important.

A quantitative approach that used a structured questionnaire for data collection from a sample of 432 postgraduate students was used. Data validation was done using confirmatory factor analysis (CFA). The structural equation modelling technique was used for data analysis.

Results showed that out of the seven factors of the UTAUT2, the factors such as performance expectancy, effort expectancy, social influences, facilitating conditions and hedonic motivation significantly and positively influenced the behavioural intentions of students in universities to accept blended learning. On the other hand, habit and price value did not significantly influence university students' behavioural intentions to accept the bended learning mode. It was further shown in the study that behavioural intentions significantly influenced the acceptance of blended learning by university students. In light of the above results, it was concluded that the UTAUT2 could be used to predict the acceptance of blended learning by university students.

The main study limitation was that it was only carried out at universities that had information and communication technology (ICT) infrastructure challenges owing to the fact that the economic situation in Zimbabwe is depressed. Limited ICT infrastructure in the universities might have had some impact on the nature of behavioural intentions of students to accept blended learning as a learning mode. Further research could be carried out in countries with better economies that are able to fund ICT infrastructures of their universities and to establish whether the results of the current study could either be confirmed, disconfirmed or enriched.

The paper suggests that universities need to increase investment in ICT infrastructure as well as in capacitating students with the necessary ICT skills for the effective use of institutional ICT when learning using the blended learning mode. Without adequate and appropriate ICT infrastructure as well as necessary ICT skills, students may develop low motivation levels and negative attitudes towards blended learning, which may eventually may affect their acceptance of the learning mode.

There is no known study that has been conducted using the UTAUT2 to establish antecedents of behavioural intentions of students to accept blended learning in the context of Zimbabwean universities. This study therefore opens new ground on factors influencing the acceptance of blended learning in the context of Zimbabwean universities. Also, the results showed that habit and price value do not significantly contribute to the behavioural intentions of university students to accept blended learning, which is not consistent with findings of past studies. This inconsistency opens new opportunities for further studies on the conditions under which these two factors can be used to significantly contribute to the development of behavioural intentions of students to accept blended learning.

The purpose of this paper is to identify the factors affecting user acceptance for NFC mobile wallets in both Korean and US markets.

The proposed model extends the UTAUT2 model with new constructs of credibility (CR) and service smartness (SS). This study was analyzed using partial least square structural equation modeling on data collected from 701 college students between the ages of 18 and 29.

The results of this study demonstrate that performance expectancy (PE), effort expectancy (EE), CR, SS and habit (HB) have strong positive relationships with a user’s behavioral intention to use NFC mobile wallets. Comparing the results of the USA and South Korea, there are different results regarding PE and CR.

This study shows that all factors except social influence (SI) have significant positive relationships with the intention to adopt NFC mobile wallets: Among the original UTUAT2 factors, PE, EE and HB are important determinants of NFC mobile wallet adoption and the new constructs, CR and SS, are significant determinants that influence BI. However, the target respondents are limited to college students of South Korea and the USA Thus, caution should be used when applying the results of this study towards less ICT developed countries and towards different age groups.

This study provides multiple practical contributions. First, this study emphasizes HB as the strongest factor for adopting NFC mobile wallets in both South Korea and the USA Second, this study also highlights the importance of SS. Third, this study reveals that SI is not associated with the adoption of NFC mobile wallets. Fourth, nationality differences between the USA and South Korea account for the differences in consumer behaviors.

This study has two main contributions: First, this study introduces a modified UTAUT2 model with two new variables (CR and SS) useful for NFC mobile wallets. Second, this study compares the results of partial least square structured equation models (PLS-SEM) of the two nationality groups, South Korea and the USA

The purpose of this paper is to identify the factors affecting learners' perception of e-learning during the Coronavirus-2019 (Covid-19) pandemic. Furthermore, it investigates mechanisms that enhance students' engagement in e-learning, especially under the constraints created by the pandemic.

Quantitative research approach was used, and data were collected using a structured questionnaire. The sample consisted of 163 undergraduates registered at the Faculty of Management Studies of the Open University of Sri Lanka (OUSL). The structured questionnaire was designed taking into consideration learners attached to different regional centers and study centers of the OUSL.

As per the findings, performance expectancy, social influence, effort expectancy and service quality are the factors which have significant effects on students' “intention to use” e-learning as a method of pursuing education. Furthermore, it was observed that 65.6% of the students had access to technology through mobile phones, while 53.4% of the students had engaged in e-learning for the first time. This was mainly due to restrictions that were imposed during the Covid-19 pandemic.

The study will help in formulating policies and introducing procedures in relation to online teaching-learning models to be used by both teachers and learners, especially in similar pandemic situations in the future.

This study will assist to determine the effectiveness of the e-learning system used by the OUSL. The findings highlighted the importance of improving information technology (IT) facilities available at all the regional and study centers across Sri Lanka.

This study aims to ascertain the intentions of risk managers to use artificial intelligence in performing their tasks by examining the factors affecting their motivation.

The study employs an integrated theoretical framework that merges the third version of the technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology (UTAUT) based on the application of the structural equation model with partial least squares structural equation modeling (PLS-SEM) estimation on data gathered through a Likert-based questionnaire disseminated among Italian risk managers. The survey reached 782 people working as risk professionals, but only 208 provided full responses. The final response rate was 26.59%.

The findings show that social influence, perception of external control and risk perception are the main predictors of risk professionals' intention to use artificial intelligence. Moreover, performance expectancy (PE) and effort expectancy (EE) of risk professionals in relation to technology implementation and use also appear to be reasonably reliable predictors.

Thus, the study offers a precious contribution to the debate on the impact of automation and disruptive technologies in the risk management domain. It complements extant studies by tapping into cultural issues surrounding risk management and focuses on the mostly overlooked dimension of individuals.

Yet, thanks to its quite novel theoretical approach; it also extends the field of studies on artificial intelligence acceptance by offering fresh insights into the perceptions of risk professionals and valuable practical and policymaking implications.

This study aims to investigate the technology usage behaviour of the tourists in line with the modified unified theory of acceptance and use of technology (UTAUT) model.

Data were collected from a survey of 265 tourists using the random sampling technique. Partial least squares-based structural equation modelling (PLS-SEM) technique was used to analyze the data.

The findings revealed that performance expectancy, hedonic motivation and habit significantly influence the behavioural intention of tourists to use information and communication technology (ICT), while effort expectancy, social influence, and facilitating conditions do not have a significant influence. However, actual ICT usage behaviour largely depends on the behavioural intention of the tourists, and their habits, while the facilitating conditions do not have any influence in this case.

The findings uncover the core factors influencing tourists' actual ICT use behaviour that can assist the concerned stakeholders in designing tourism planning and sales. The study results also offer pathways for the world's tourism industry for a healthy recovery from the COVID-19 pandemic.

The findings have made robust contributions by extending the existing UTAUT-based literature by adding two new moderators in the relationship between behavioural intention and actual ICT usage behaviour.

The purpose of this paper is to determine the effects of factors affecting the acceptance and use of technology on the factors affecting women’s entrepreneurship motivation.

This study was conducted with 156 women entrepreneurs in Turkey in February 2019. A mixed method evaluation design has been adopted in the study.

The findings revealed that effort expectancy was negatively associated with behaviour intention and push factor and positively associated with pull factor. Performance expectancy was positively associated with balance factor, push factor and behaviour intention. Hedonic motivation was positively associated with behaviour intention and emotional factor. Behaviour intention was negatively associated with use behaviour. Facilitating conditions was positively associated with push factor. Habit was positively associated with behaviour intention and negatively associated with pull, push, balance and emotional factors. Necessities and habit were not motivation factors for women entrepreneurs.

The sample was restricted to women entrepreneurs, limiting the generalizability of the findings.

The practical implications of the study show that effort expectancy, performance expectancy, hedonic motivation, facilitating conditions and habit are the key factors for the women’s entrepreneurship motivation. Women’s entrepreneurship commissions to be established in chambers of commerce and industry can improve entrepreneurial motivation.

This is the first study that reveals the effects of technology acceptance and use behaviours on women’s entrepreneurship motivation. Theoretical background, discussion, managerial implications, limitations and recommendations for future studies are discussed.