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As artificial intelligence (AI) has become increasingly popular and accessible, most companies have recognized its far-reaching potential. However, despite numerous research papers on organizational adoption of new technologies including AI, little is known about individual employees’ intentions to use them. Given that organizational innovations are of limited value if they are not adopted by employees, the purpose of this study is to understand the underlying factors that push employees to make use of these new technologies in the workplace.

This study builds on previously developed technology acceptance models to provide a new theoretical model. The model is then tested using data collected from a survey of 203 employees and analyzed through structural equation modeling.

Findings show that five factors affect employees’ intention to use AI either directly or as mediators. Organizational culture and habit exert a positive impact on employees’ intention to use AI, whereas job insecurity has a negative impact. Perceived self-image and perceived usefulness fully mediate the relation between job insecurity and intention to use. Moreover, perceived self-image and perceived usefulness partially mediate the relationship between habit and intention to use.

To the best of the authors’ knowledge, this study is among the first to determine the factors that influence employees’ intention to use AI in general and more particularly chatbots within the workplace.

Cryptocurrencies such as bitcoins represent a novel method of conducting financial transactions and exchanging money. However, their adoption by the general public remains low. Within countries facing financial distress and characterized by a high level of risk, cryptocurrency adoption might offer opportunities for countering crises. The purpose of this study is to explore the factors that influence individuals' adoption of cryptocurrencies for financial transactions within a high-risk context.

To do so, it presents a behavioral model, which is tested using data collected from a survey of 255 respondents residing in Lebanon. The causal relationships between the different factors and individuals' willingness to use cryptocurrencies were then analyzed through Structural Equation Modeling.

Findings show that financial technology awareness and social influence contribute to reducing perceived risk and increasing individuals' willingness to use cryptocurrencies, while individuals' risk aversion and the presence of regulatory support increase the perceived risk of cryptocurrencies.

The study is among the first to use a human-centered approach to understanding cryptocurrency adoption and takes place within a country that is facing a deep financial crisis. Its outcomes contribute to existing theories of cryptocurrency adoption and provide policymakers with insight into how adoption is unfolding namely in developing countries.

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.

The study provides a comprehensive understanding of the issues and illegal activities related to cryptocurrencies and their negative repercussions. This study aims to identify and classify cryptocurrency downsides using grounded theory and in-depth interviews. The study also analysed investors’ reluctance to invest in cryptocurrency. This pioneering qualitative study illuminates a deep and multifaceted criminal aspect of cryptocurrency.

The study conducted in-depth interviews with respondents who have experience and knowledge of cryptocurrency investments. The interviews were recorded and transcribed. The analysis was performed using the NVivo 14 software in the study.

The study specified two major types of cryptocurrency’s negative aspects: barriers and illegal usage. Barriers to cryptocurrency investment include technological, security, trust, market-related and regulatory reasons. Terrorist funding, money laundering, fraud and ransom payments are all examples of illegal usage. The results of the word cloud analysis are consistent with the overall findings of the survey, which highlighted illegal usage as a prominent negative element of cryptocurrencies. It is a key reason why cryptocurrency is not included in investing portfolios by investors.

The study’s findings provide useful insights for policymakers to develop better methods for successfully mitigating risks and ensuring responsible and sustainable usage of cryptocurrencies. In addition, the study could serve as a stepping stone for more cryptocurrency-related studies, contributing to the development of a more complete and nuanced comprehension of this emergent technology and its societal effects.

In recent years, the proliferation of social commerce (s-commerce) has attracted many researchers to investigate the drivers of individuals' intentions. However, the empirical results reported in these studies were fragmented and inconsistent. This has led various meta-analyses to synthesize these findings, but without including a large number of s-commerce studies. In addition, investigating meta-analytically the effects of moderators such as the six dimensions of Hofstede's national culture is still lacking.

Drawing on nine theories and models, this meta-analysis aims to summarize the findings reported in 109 s-commerce studies published between 2011 and 2021 and to examine the moderating role of national culture. The correlation coefficient (r) has been used as the main effect size for this study. Based on the random-effects method, the CMA V3 software has been employed to calculate the weighted mean effect sizes.

The meta-analysis results showed that all the 11 hypothesized direct relationships are positive and significant. The moderator results also revealed that five out of six cultural dimensions significantly moderate the examined associations.

This research serves to enrich the existing s-commerce literature by addressing contradictory and mixed results reported in the empirical studies. This study is one of the first of its kind to investigate the role of Hofstede's six cultural dimensions as moderators in the field of s-commerce using the meta-analytic techniques.

This study aims to analyze the factors that drive purchases via Instagram and contribute to the growth of Instagram Commerce and examine the moderating role of gender, age and experience in Instagram use in the proposed relationship between six variables derived from commitment–trust theory, the technology acceptance model and consumer decision-making theory.

A survey was completed by respondents after watching a video about Instagram Commerce. A total of 404 valid responses were collected. The research model was analyzed using partial least squares structural equation modeling.

This study makes numerous contributions to Instagram Commerce and holds significant implications for professionals in the social commerce field. Among other results, we found that trust, attitude, perceived usefulness and alternative evaluation significantly affected consumers’ purchase intentions. However, this study found no relationship between trust or ease of use and purchase intention. Finally, it demonstrates the moderating role of gender, age and experience on some of these relationships.

This research centers on an analysis of consumer purchase behavior on Instagram Commerce, taking a highly innovative approach. The particular originality of this study lies in the proposed model of adoption of social commerce via Instagram, based on a critical framework. This study also provides an original analysis of the moderating effect of the classification variables: gender, age and experience in Instagram use.

Factores que impulsan la intención de compra en Istagram Commerce

Resumen

Los objetivos de la presente investigación son (i) analizar los factores que impulsan las compras a través de Instagram y contribuyen al crecimiento del comercio en Instagram y (ii) examinar el papel moderador del género, la edad y la experiencia en el uso de Instagram sobre la relación propuesta a partir de seis variables derivadas de la Teoría del Compromiso-Confianza, el modelo TAM y la Teoría de la Toma de Decisiones del Consumidor.

Los encuestados completaron una encuesta después de ver un vídeo sobre Instagram Commerce. Se recogieron un total de 404 respuestas válidas. El modelo de investigación se analizó mediante un modelo de ecuaciones estructurales de mínimos cuadrados parciales.

El presente estudio hace numerosas contribuciones al Instagram Commerce y tiene importantes implicaciones para los profesionales del campo del comercio social. Entre otros resultados, encontramos que la confianza, la actitud, la utilidad percibida y la evaluación alternativa afectan significativamente a las intenciones de compra de los consumidores. Sin embargo, este estudio no encontró ninguna relación entre la confianza o la facilidad de uso y la intención de compra. Por último, se demuestra el papel moderador del género, la edad y la experiencia en algunas de estas relaciones.

Esta investigación se centra en un análisis del comportamiento de compra de los consumidores en Instagram Commerce, adoptando un enfoque muy innovador. La originalidad particular del trabajo radica en la propuesta de un modelo de adopción del comercio social a través de Instagram, basado en un marco crítico. El estudio también proporciona un análisis original del efecto moderador de las variables de clasificación: género, edad y experiencia en el uso de Instagram.

本研究的目的是(i)分析推动通过Instagram购买并促进Instagram商务发展的因素; (ii)研究性别、年龄和使用Instagram的经验对源自承诺-信任理论、TAM模型和消费者决策理论的六个变量之间的拟议关系的调节作用。

受访者在观看了有关Instagram商业的视频后完成了一项调查。共收集到404份有效的回复。研究模型采用偏最小二乘法结构方程模型进行分析。

本研究对Instagram商务做出了许多贡献, 并对社交商务领域的专业人士具有重要意义。在其他结果中, 我们发现信任、态度、感知有用性和替代性评价对消费者的购买意向有显著影响。然而, 本研究发现信任或易用性与购买意向之间没有关系。最后, 它证明了性别、年龄和经验对其中一些关系的调节作用。

这项研究以分析消费者在Instagram商务上的购买行为为中心, 采取了一种高度创新的方法。这项研究的独特之处在于提出了一个基于批判性框架的通过Instagram进行社交商务的模型。该研究还对分类变量的调节作用进行了原创性分析：性别、年龄和使用Instagram的经验。

This paper aims to explain how Web 2.0, social connectedness online, has created incredible new business options. This research’s primary goal is to help businesses use these resources more effectively and perform better.

Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

Theories encompassing social support and related approaches to “word of mouth” online, electronic purchasing and virtual communities mediated by technological platforms are the foundational frameworks for this research piece. It then produces a statistical model that enables users to predict how social commerce (s-commerce) building blocks, including forums, communities, ratings and reviews and recommendations, assist businesses in introducing innovative strategies to win in the digital markets. The results necessarily focus on trust, an essential component of e-commerce. Reciprocally, the study reverses engineer’s trust through the constructs of this moment mentioned.

The present study describes the scope of empirical testing and validation of this framework and assists practitioners in further strengthening s-commerce strategy, an emerging and essential platform in the e-commerce industry.

Research highlights the dearth of current analysis in such conceptual domains while generating novel research insights aimed at e-commerce and digital business. From the viewpoint of potential and recurring customers who interact with online communities and product offerings, the study captures the essence of human interactions, often known as trade relationships, online.

This study contributes to examining the factors that drive the adoption of cryptocurrencies for financial transactions in the tourism and hospitality industries. This is crucial to develop tourism and hospitality and stimulate financial inclusion in developing and developed countries.

This research paper employs the SEM model and bootstrapping method on a sample of 417 French participants involved in tourism and hospitality industries to reveal the causal pathway between a set of independent factors and the willingness to adopt cryptocurrencies for financial transactions.

The empirical findings reveal that ease of use, perceived usefulness, social influence, and financial literacy increase the willingness to use cryptocurrencies. French hotels need to have a strategic orientation, to deal with customers, competitors and changing technological environment. The study also reveals that social influence and financial literacy reduce the level of perceived financial risk and thus, leads to increase the intention to adopt the new type of decentralized currencies.

In contrast to previous studies that focused on the volatility and risk of cryptocurrencies, this research employs a human-centric approach covering different factors that could lead to the adoption of the new type of currency for financial transactions in tourism and hospitality industries.

Given the severe impact of coronavirus disease 2019 (COVID-19) on bank business activities, this study aims to examine how green brand image and online trust affect customers' continuance intention (CI) under the boundary condition of perceived effectiveness of e-services (PEES).

An extensive review of the green marketing perspective was conducted to identify the incremental contributions of the current study (e.g. extensions of online trust and PEES). The authors used the common questionnaire survey strategy for the data collection while applying the partial least squares technique for further analyses.

Using data from 460 bank customers, the findings indicated that online trust positively mediates the relationship between green brand image and CI under the moderating effect of PEES. At high levels of PEES, online trust exerts strongest effect on customers' CI.

This study responds to the emerging call for understanding the PEES role, under which online trust leads to CI in the context of the global pandemic.

The authors provide bank managers with a helpful extension of green marketing with PEES to manage online trust and customer intention, thereby increasing the managers' strategic effectiveness.

The current study explores the moderating role of PEES that plays in the green brand image, online trust and CI relationships, in responding to the pandemic situation.

This study investigates the relationship between social commerce adoption determinants, perceived trust and purchase behaviour among pastry product consumers.

The research data were collected using a five-point Likert from 409 pastry consumers through an online survey. Partial least square-structural equation modelling (PLS-SEM) was utilised to test the study model and hypotheses.

The study findings indicate that pastry consumers perceived social commerce as effortless, engaging, enjoyable, can be trusted, simple to use and time-saving, motivating them to consume pastry products via social commerce platforms.

This study provides insights and implications for social commerce researchers and marketers related explicitly to perishable products.

This study is one of the few studies that predict and explain the consumer acceptance of social commerce in the pastry products realm. As only a handful of research has endeavoured to research social commerce, this study findings contribute to the conceptualisation of technology acceptance theory by understanding the determinants of social commerce adoption among consumers.