Amal Dabbous, Karine Aoun Barakat and May Merhej Sayegh
As artificial intelligence (AI) has become increasingly popular and accessible, most companies have recognized its far-reaching potential. However, despite numerous research…
Abstract
Purpose
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.
Design/methodology/approach
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
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.
Originality/value
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.
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Amal Dabbous, May Merhej Sayegh and Karine Aoun Barakat
Cryptocurrencies such as bitcoins represent a novel method of conducting financial transactions and exchanging money. However, their adoption by the general public remains low…
Abstract
Purpose
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.
Design/methodology/approach
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
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.
Originality/value
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.
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Ahmad A. Khanfar, Reza Kiani Mavi, Mohammad Iranmanesh and Denise Gengatharen
Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of…
Abstract
Purpose
Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of expectations, leading to unsuccessful implementations. This paper aims to identify and elucidate the factors influencing AI adoption at both the organisational and individual levels. Developing a conceptual model, it contributes to understanding the underlying individual, social, technological, organisational and environmental factors and guides future research in this area.
Design/methodology/approach
The authors have conducted a systematic literature review to synthesise the literature on the determinants of AI adoption. In total, 90 papers published in the field of AI adoption in the organisational context were reviewed to identify a set of factors influencing AI adoption.
Findings
This study categorised the factors influencing AI system adoption into individual, social, organisational, environmental and technological factors. Firm-level factors were found to impact employee behaviour towards AI systems. Further research is needed to understand the effects of these factors on employee perceptions, emotions and behaviours towards new AI systems. These findings led to the proposal of a theory-based model illustrating the relationships between these factors, challenging the assumption of independence between adoption influencers at both the firm and employee levels.
Originality/value
This study is one of the first to synthesise current knowledge on determinants of AI adoption, serving as a theoretical foundation for further research in this emerging field. The adoption model developed integrates key factors from both the firm and individual levels, offering a holistic view of the interconnectedness of various AI adoption factors. This approach challenges the assumption that factors at the firm and individual levels operate independently. Through this study, information systems researchers and practitioners gain a deeper understanding of AI adoption, enhancing their insight into its potential impacts.
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Zefeng Bai, Pengcheng Wang and Miaoqing Jia
In this paper, we empirically investigate how crypto investments in times of economic downturn would affect credit card usage, a widely used payment method that has a significant…
Abstract
Purpose
In this paper, we empirically investigate how crypto investments in times of economic downturn would affect credit card usage, a widely used payment method that has a significant impact on individual financial well-being.
Design/methodology/approach
We carry out an ordinary least squares regression analysis and an instrumental variable design on data from the most recent National Financial Capability Study 2021 (NFCS2021). The NFCS2021 collects information about various demographic and financial backgrounds of US adults.
Findings
We find that crypto investments are associated with a significantly higher likelihood of credit card misuse, as indicated by making only the minim um payments, late payments and using credit cards for cash advances. Meanwhile, social media use is a strong predictor of crypto investments. Results from our analysis are robust after accounting for endogeneity concerns using an instrumental variable design.
Originality/value
Our findings provide new insights into the influence of emerging financial instruments on delinquent credit card behaviors, which can further intensify individual and household financial instability during periods of market stress. Furthermore, our findings underscore the necessity of improving individual awareness of the high-risk characteristics of cryptocurrencies, despite their increasing popularity in the financial marketplace in the current financial marketplace.
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Rajasshrie Pillai, Raman Preet, Brijesh Sivathanu and Nripendra P. Rana
The emergence of cryptocurrency has developed a new payment system that is changing how financial transactions happen in hospitality. Consumers/travelers have started…
Abstract
Purpose
The emergence of cryptocurrency has developed a new payment system that is changing how financial transactions happen in hospitality. Consumers/travelers have started experimenting with cryptocurrency payments in hotels and restaurants. However, extant research is lacking in understanding the consumer adoption intention of cryptocurrency payments. This study investigates the intention to use cryptocurrency payments in the hospitality industry.
Design/methodology/approach
The conceptual model in this study is based on the Behavioral Reasoning Theory, and it explores the motivating and deterring factors influencing the adoption of cryptocurrency payments in the hospitality industry. A quantitative survey was conducted among 1,080 consumers to examine and confirm the model, with data being analyzed through the Partial Least Squares Structural Equation Modeling (PLS-SEM) method.
Findings
The outcome of this work showed that the “reasons for” positively influence and “reasons against” negatively influence consumers’ attitudes and use intentions. Consumers’ values of openness to change positively influence the “reasons for” and do not influence the “reasons against” and attitude toward the use of cryptocurrency payments.
Practical implications
This work contributes to practice by providing insights to customers (users/payee), hospitality managers (investors) and organizations/firms (receiving crypto payments) as well as to financial firms and the government.
Originality/value
This research contributes to cryptocurrency payment adoption and behavioral finance literature. The research uniquely provides the adoption and inhibiting factors for cryptocurrency payment in an integrated framework in the hospitality sector.
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Tri Minh Cao and Loc Thi Vy Nguyen
This study aims to assess the factors that impact the adoption of artificial intelligence (AI) in the human resource (HR) recruitment procedure in Vietnam’s medium-sized firms.
Abstract
Purpose
This study aims to assess the factors that impact the adoption of artificial intelligence (AI) in the human resource (HR) recruitment procedure in Vietnam’s medium-sized firms.
Design/methodology/approach
Through a quantitative approach, this paper collected data of 297 hiring managers, HR directors and top-level executives from Vietnam’s medium-sized firms with a structured questionnaire. The partial least squares structural equation model was used to analyze the data and evaluate the hypothesis model (on platform Smart PLS 3.0).
Findings
The results show that in Vietnam’s medium-sized companies, both perceived benefits and perceived sacrifices directly impact on perceived value, which leads to organizations’ adoption of AI. HR readiness also has a moderating effect between perceived value and AI adoption.
Research limitations/implications
Future research can compare AI adoption between large and medium companies, as well as other criteria in Asian countries. Other organizational constructs can be considered moderators between perceived value and AI adoption.
Practical implications
This study offers a context-specific understanding of the practice of using AI to acquire talent in Vietnam. Both of AI technology’s perceived benefits and perceived sacrifices directly impact its perceived value, therefore indirectly impacting its adoption. In this study, HR readiness serves as an inhibitor to adoption. Some essential managerial implications are suggested.
Originality/value
This study provides valuable insights into applying AI to Vietnam’s medium-sized companies, especially in the recruitment process. It adds to a substantial body of work on applying AI to HR management.
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Faezal Bin Ramly and Mohd Zaidi Md Zabri
This study pioneers the investigation into the determinants influencing Malaysian investors' intentions towards Non-Fungible Token (NFT) investments, utilizing an extended Unified…
Abstract
Purpose
This study pioneers the investigation into the determinants influencing Malaysian investors' intentions towards Non-Fungible Token (NFT) investments, utilizing an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework. It explores the burgeoning interest in NFTs within the Malaysian market, an emerging economy, and identifies the behavioral adoption determinants critical for NFT investment decisions.
Design/methodology/approach
Adopting a quantitative methodology, the research engaged 183 experienced Malaysian investors through a structured online questionnaire survey. The study employed regression analysis to assess the impact of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Perceived Usefulness, Social Support and Perceived Trust on NFT investment intentions.
Findings
The findings reveal that Performance Expectancy and Social Support significantly predict the intention to invest in NFTs, accounting for 47% of the variance in investment intentions. The study highlights the crucial role of perceived benefits and community support in shaping Malaysian investors' engagement with NFTs, amidst the complexities of the digital asset landscape.
Research limitations/implications
The study acknowledges the limitation posed by its sampling method and size, suggesting the need for broader investigations that include a more diverse demographic to enhance the generalizability of the findings. Future research could further delve into the specific behaviors, motivations and challenges of NFT investors and creators.
Practical implications
The significant predictive power of Performance Expectancy indicates a primary financial motivation among Malaysian NFT investors, suggesting policymakers consider regulations that foster innovation and growth in the NFT sector while safeguarding investors. The study also underscores the importance of community support, pointing towards the development of platforms that facilitate knowledge sharing among NFT enthusiasts.
Social implications
By demonstrating the pivotal role of social support in the NFT investment decision-making process, the research implies a powerful sense of community among investors in the digital asset space. It suggests the potential of NFTs to foster a more inclusive and accessible market for creative industry entrepreneurs, facilitating direct engagement and profit realization.
Originality/value
This research marks a significant departure from existing studies by tailoring the UTAUT model specifically to the NFT investment context in Malaysia. It unveils the nuanced dynamics influencing NFT investment intentions, emphasizing the unique contributions of Performance Expectancy and Social Support, thus providing a fresh perspective on NFT adoption in emerging markets.
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Labaran Isiaku, Abubakar Sadiq Muhammad and Dokun Oluwajana
The purpose of this study is to investigate offline retailers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT/2), technology…
Abstract
Purpose
The purpose of this study is to investigate offline retailers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT/2), technology acceptance model (TAM) and other related variables.
Design/methodology/approach
A mixed-method (QUANT-Qual) was employed. The study employed a quantitative approach (partial least squares-structural equation modeling) for Study 1 and a qualitative focus group discussion for Study 2. The qualitative segment enhances the comprehension and interpretation of outcomes derived from the quantitative analysis.
Findings
Study 1 identified six crucial factors in cryptocurrency adoption: trust, personal innovation, hedonic motivation, social influence, safety and a positive attitude. Perceived ease of use, price value and satisfaction were non-significant. Study 2 elaborates on the findings, and highlights the reasons for the insignificant factors.
Research limitations/implications
This research contributes to theoretical knowledge by empirically testing established technology acceptance theories like UTAUT/2 and TAM in the context of retail cryptocurrency adoption. It introduces previously unexplored factors, such as personal innovativeness, hedonic motivation and safety/reliability, enriching the theoretical landscape.
Practical implications
This study provides practical insights for cryptocurrency stakeholders, including government, regulators, consumers, businesses and the financial sector, regarding retailers' intentions to adopt cryptocurrencies in North Cyprus.
Social implications
This study can enhance understanding of factors facilitating cryptocurrency integration into mainstream retail, potentially reshaping traditional finance. Economically, adoption can boost financial inclusion, offering efficient transaction methods. This transition may disrupt existing economic models, drive payment technology innovation and change consumer behavior toward digital assets.
Originality/value
This study stands out by using a mixed-method approach to comprehensively examine cryptocurrency adoption by offline retailers, considering various factors and providing a holistic perspective, unlike previous research that often focused on specific user groups.
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Eloy Gil-Cordero, Pablo Ledesma-Chaves, Rocío Arteaga Sánchez and Ari Melo Mariano
The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.
Abstract
Purpose
The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.