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The commonly used e-procurement systems still show unsatisfactory implementation outcomes because many organisations are still unable to effectively interpret the initial adoption decision. The e-procurement systems are generally developed at organisational level, but their usage is at individual level, by the employees particularly. This paper examined technology acceptance model’s (TAM) key antecedents, involving e-procurement systems usage by employees in their daily activities. This study aims to examine the impact of factors affecting e-procurement acceptance among users through the mediating role of users’ attitude. The commonly used e-procurement systems still show.

TAM was applied and expanded in this study, in exploring the factors impacting the employees’ e-procurement acceptance. This study used quantitative method, and questionnaires were distributed to 200 users in Jordanian public shareholding firms. The collected data were quantitatively analysed using PLS modelling.

Significant TAM relationships involving e-procurement were affirmed. The expanded TAM in the scrutiny of antecedents showed that content, processing and usability affected perceived usefulness, while perceived convenience did not affect the usefulness factor. Furthermore, it was noticed that perceived ease of use was affected by usability and training, while perceived connectedness was not affected by usability and training.

The results demonstrated the necessity of e-procurement training. Furthermore, at the start of the implementation stage, effective design on system navigation and system usability, and consistent support, could increase use effectiveness and acceptance. Also, expedient information and buyer–supplier product flows should be made available.

Most organizations invest a lot of time and money in installing e-procurement systems to deliver their goods at the right time and at the right price. However, many of these e-procurement systems have failed due to low acceptance among users. Thus, to the best of the authors’ knowledge, this is the first study that used TAM and theory of planned behaviour in examining the effects of perceived convenience, perceived connectedness, content, training, processing and usability factors, in Jordanian firms. Lastly, the focus of this study was on the individual employee’s acceptance, rather than on the organisational-level adoption, as the unit of analysis, to provide insight on how organisations can achieve maximally from e-procurement investments and from other comparable technologies of e-supply chain management.

The evolution of e-health technologies presents promising alternatives for health-care excellence. Despite the benefits arising from mobile e-health (m-health) and wearables technologies, the literature stands many contradictories signs regarding how users accept and engage in using these technologies. This study aims to synthesize the estimations about m-health user acceptance technologies.

A meta-analytic structural equation modeling was carried out using the 778 relationships estimated by 100 previous research. The estimations follow the relations and constructs proposed in the UTAUT2 technological acceptance model.

The results indicate the performance expectancy, effort expectancy, social influence and habit constructs are most important for predicting the behavioral intention of use of m-health technologies. The Latin American users of e-health technologies are still underestimated in the literature.

The study presents a guide to understanding the acceptance process of m-health technologies and delivers a general orientation for developing new m-health devices considering their acceptance by users.

As a result of the COVID-19 pandemic, numerous businesses have migrated to an online delivery platform (ODP) to survive and reconnect with their customers. This study aims to focus on how the public perceives ODP. It examined the acceptance of digital platforms for delivering daily necessities, especially food, in Brunei Darussalam during the COVID-19 pandemic.

The online survey collected 350 valid samples, and the online questions were distributed using a snowball sampling method, with the questionnaire’s softcopy prepared in Qualtrics and sent via email and social media as hyperlinks. In 2021, we sent out the questionnaire link via email, WhatsApp and Facebook to people and organizations for about six months.

According to the findings of the study, product quality is a critical factor that consumers consider while making online purchases of different products. The COVID-19 condition positively affects customer acceptance, performance, effort and product quality. This research indicates that service quality, online habits and trust do not influence customer acceptance of an ODP.

The study contributes to the body of knowledge regarding factors influencing the acceptance of ODPs. The factors that influence people’s acceptance of ODPs, especially during the COVID-19 pandemic, are assessed as to whether the COVID-19 pandemic influences people’s acceptance and the identified factor that has the strongest influence on the acceptance of digital delivery platforms.

The study contributes to the growing body of knowledge about how customer behaviors triggered by the COVID-19 condition influence customer acceptance of ODP and how behavior influences customer acceptance of ODP.

This paper is useful to academics, practitioners and policymakers in public administration and policy management. The research provides some insights into massive adoption of ODPs that affects the disruption of conventional business practices.

This study pinpoints the critical factors influencing the acceptance of blockchain technology in supply chain management in the light of the extended unified theory of acceptance and use of technology (UTAUT2) with additional factors personal innovativeness in technology and user's self-efficacy.

The questionnaire-based data was obtained from SC professionals in China (Beijing). The essential factors influencing it are evaluated through structural equation modeling (SEM), using AMOS software.

The empirical findings specify that performance expectancy, facilitating conditions, price value, hedonic motivation, user self-efficacy, and personal innovativeness are positively influencing user satisfaction. User satisfaction has a substantial progressive effect on habit. Furthermore, facilitating conditions, price value, habit, user self-efficacy, personal innovativeness, and user satisfaction have a progressive impact on continued intention to use blockchain technology in supply chain management.

Although numerous studies investigated the influencing factors of blockchain technology adoption in supply chain management, no study examined the determinants of UTAUT2. However, this study not only empirically studied the UTAUT2 model but also extended it with the most influencing elements such as personal innovativeness in technology and user's self-efficacy. Furthermore, this study contributes to the BT-enabled SCM literature by studying the continued use and acceptance, rather than testing behavioral intention and initial adoption which is common in previous studies of BT-enabled SCM. Finally, this study discusses the limitations, future directions, and managerial implications of the results so that supply chain professionals can deliver what supply chain stakeholders require.

Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance.

A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management.

Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk.

Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features.

The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base.

This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.

Open government data (OGD) is a comparatively new field in e-government and the factors influencing its continuance use by citizens have not been extensively explored. A better understanding of these factors can help the government to articulate strategies and policies that can advance the acceptance and use of OGD technologies. Thus, this paper aims to empirically determine the predictors influencing the continuance usage intention of OGD technologies.

Following an empirical investigation among 370 respondents in Bangladesh, a developing country, the paper applied path analysis using the structural equation modeling approach. The unified theory of acceptance and use of the technology model is integrated with the information system continuance model to investigate the continuance usage intention of OGD technologies.

The outcomes of this study reveal that performance expectancy, effort expectancy, social influence and facilitating conditions (FC) directly affect users’ satisfaction (SAT). In addition, SAT and FC were found statistically significant toward continuance usage intention of OGD technologies.

The findings of this study suggest policymaker and OGD providers to formulate or modify their strategies to retain the existing OGD users and stimulate persistence usage.

Facilitating long-term use by citizens would increase their engagement and they might derive value from the OGD platforms. Concurrently, the government’s objective of ensuring increased future use of OGD technologies would be better realized.

The novelty of this study lies in the fact that it addresses a previously overlooked area of open data research, namely, the acceptance and use of open data technologies and ways to stimulate it. This study has contributed to the existing but limited literature on continuance usage intention of OGD technologies in the context of a developing country.

Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects.

After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS.

The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies.

This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

When organizations implement a new information system (IS), they often experience users' resistance behaviors. This study explored the effects of IS self-efficacy, perceived ease of use, perceived usefulness, and anxiety on resistance to IS change within the hospitality domain. It also compared these relationships before and after completing e-learning courses for a new IS.

Survey responses were gathered from current and future hospitality employees. All hypotheses were tested via confirmatory factor analysis and structural equation modeling.

The results demonstrated that (1) IS self-efficacy had significant effects on both perceived usefulness and perceived ease of use of IS; and (2) IS anxiety had a significant impact on resistance to IS change, both before and after completing the e-learning courses. The results also showed that self-efficacy had a significant effect on anxiety and, in turn, resistance to change, after completing the e-learning courses, but not prior to the training.

This study addressed the lack of theory-driven empirical research on predictors of user resistance to IS change, based on social cognitive theory, technology acceptance models, and user resistance research.

Based on the findings, hospitality operators and vendors can focus on improving factors influencing user adoption of a new IS when they design and implement it. Operators can design better change management strategies to reduce resistance to IS change.

Few investigations have been conducted to explain the relationships among the aforementioned factors, before and after completing e-learning for a hospitality IS.

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.

In the global migration crisis COVID 19 had devastating consequences. Workers were confined to their locations due to travel restrictions and working from home became “working away from home” for millions of migrant workers. Mobile financial services emerged as key to livelihood of the mobile remittance recipients. It is essential for service providers to gain insights of users' motives to use mobile remittance services.

This study proposed the model by extending unified theory of acceptance and use of technology (UTAUT) model and integrating by perceived cost (PC) and perceived security (PS). Based on the survey data (n = 344) the proposed model was tested using analysis of variance (ANOVA) analysis.

The findings reveal that performance expectancy, effort expectancy, PC and PS affect the users' behavioral intention (BI) to use mobile remittance applications. Social influence nonsignificantly affects the BI and there is no significant influence of facilitating conditions on user behavior.

The volume of migrant workers preCOVID 19 reached 3.5% of the global population, the shear number of unprotected workers plunged into devastation by the COVID-19 impact is huge to cause an economic meltdown. Under the pandemic crisis conditions, the findings provide several practical implications on how service providers could improve their products and services to increase mobile remittance applications usage.