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This paper aims to identify the relevant contributing constructs of readiness for the implementation of intelligent contracts (iContracts) in the construction industry. This study investigates the relationship between the personality dimensions of technology readiness index (TRI) and the system specific factors of technology acceptance model (TAM) within the context of iContracts.

Drawing insights from the extant literature and the author's previous qualitative investigations into iContract readiness constructs, a quantitative approach is used to operationalise the constructs by offering relevant statements to be measured and validated through a multiple-item scale against the users intent to accept the future iContract technology.

This study confirms and validates the relationship of the proposed iContract readiness index (iCRI) statements against the established TAM factors by offering 18 new constructs influencing technology readiness of the iContract technology. This study proves 9 of the 12 hypotheses highlighting key factors to be addressed for the successful development of the iContract technology.

This paper contributes to the body of knowledge by proposing a novel iCRI that informs an iContract technology readiness acceptance model (iCTRAM) for a trending technology. The iCTRAM can guide developers in producing an appropriate iContract solution and assess the readiness of users and organisations for the successful adoption of the iContract concept.

This study offers a unique theoretical framework, in an embryonic field, for predicting the success of iContract implementation within construction organisations. This study combines the established studies of TRI and TAM in producing a predictive iContract readiness assessment tool.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.

The success of an Electronic Health Record (EHR) system is determined by the numerous facilitators and obstacles that influence physicians' intentions toward using these technologies. This study examines physicians' intentions to use EHR by applying the extended technology readiness and acceptance model (TRAM) factors, the result demonstrability, colleagues' opinions, perception of external control, and organizational support.

Convenience sampling was used to collect data from physicians in Egypt (n = 520). To evaluate the model's hypotheses, this study used the partial least squares structural equation modeling (PLS-SEM) method with WarpPLS.7.

The results revealed that positive TR factors (innovativeness and optimism) positively affect perceived usefulness and ease of use, while negative TR factors (discomfort and insecurity) negatively impact perceived usefulness and ease of use. Furthermore, the result demonstrability and colleagues' opinions positively influence perceived usefulness, while the perception of external control and organizational support positively influence perceived ease of use. In addition, significant relationships between perceived ease of use and usefulness and adoption intention were identified.

This is the first study to apply the TRAM to understand physicians' adoption intentions to use EHR systems. Moreover, this study determined the different roles of positive and negative TR affecting physicians' cognition regarding using EHR systems.

This research proposal aims to address the growing significance of artificial intelligence (AI) technology in the field of records and information management (RIM) within the African context. Despite the increasing prevalence of AI, there is a lack of comprehensive understanding regarding the factors influencing AI readiness and adoption in RIM. The primary purpose of this paper is to explore these factors and propose an AI readiness and adoption conceptual framework.

A comprehensive literature review was conducted to identify the proposed variables and support the hypothesis development. The theoretical foundation of the proposed conceptual framework is based on three theories: the technology acceptance model (TAM), the technology readiness index (TRI) and the cognitive appraisal theory (CAT).

The literature reveals that there is a lack of empirical investigation of AI readiness and adoption within the RIM context. Through the proposed conceptual model, the researcher anticipates uncovering critical insights into the factors influencing AI readiness and adoption in RIM practices across African nations.

The proposed model is not yet empirically tested and the study's scope is limited to African nations.

The proposed model takes a pioneering approach to empirically investigate AI readiness and adoption within the RIM field, specifically in an African context which is understudied.

This study aims to develop a model for readiness measurement and to study readiness levels for online testing of undergraduate students in Thailand’s distance education programs.

In total, 870 undergraduate students enrolled in the 2022 academic year of a Thai university were sampled for the study. The samples were divided into two groups: Group 1 comprised 432 students who underwent exploratory factor analysis (EFA) and Group 2 comprised 438 students who underwent second-order confirmatory factor analysis (CFA). Both were multi-stage random samples. Descriptive statistics, item-total correlations (ITCs), coefficient correlations, EFA and second-order CFA were used.

The readiness for the online testing model comprised 5 factors and 33 indicators. These included self-efficacy (SE) in utilizing technology (nine indicators), self-directed learning (SL) for readiness testing (six indicators), adequacy of technology (AT) for testing (five indicators), acceptance of online testing (AC) (seven indicators) and readiness training for testing (six indicators). The model was congruent with empirical data, and the survey results indicated that students were highly prepared at the “high” level.

This study disclosed several factors and indicators involved in the readiness for online testing. The university may use these findings in preparing its students for online testing for better achievement.

These findings may serve as a framework for the analysis of the readiness issues for online testing of undergraduate students and also offer guidance to the universities preparing to offer online testing.

This paper delves into the multi-faceted factors influencing the adoption and utilisation of online travel agencies (OTAs) for reserving hotel accommodations. The study aims to expand upon the unified theory of acceptance and use of technology (UTAUT2) framework to accomplish this objective by integrating the critical dimension of technology readiness (TR).

Four hundred and fifty-three (453) inbound tourists were asked to share their feedbacks on their recent OTA booking experience. Structural equation modelling (SEM) was used to confirm the study model and test the study hypotheses.

This study found that the motivating TR attributes favourably affect the acceptance and actual use of OTAs, while the inhibitors TR reflects adverse effects on OTA’s usage. On the other hand, the OTAs usage attributes: performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value and habit are all significant determinants of consumers' behavioural intention.

The originality of this study lies in providing a more comprehensive explanation and prediction of consumer behaviour in relation to OTAs. Specifically, it recognises the importance of TR as a significant determinant of technology adoption and usage within the service industry realm.

Although change is a necessary part of organisational life, achieving a successful change is complex. Change readiness is a critical element in successful change implementation, yet studies assessing change readiness as an underlying mechanism in the link between organisational-level factors and successful change implementation are scarce, particularly in the African context. Accordingly, the present study examined the extent to which change readiness mediates the link between learning organisation and successful change implementation in the Ghanaian context.

The study utilized a standardized questionnaire to collect data from 364 participants, working in public and private universities in Ghana. The participants were selected via the convenience sampling strategy to complete the survey on the main variables at a single point in time. The study was purely quantitative, as path analysis – a form of structural equation modelling was employed to test the hypothesized relationships in the study.

The results show that both learning organisation and change readiness facilitated successful change implementation. Finally, it was observed that change readiness served as an important mediating mechanism in the link between learning organisation and successful change implementation.

Change readiness was found to explain the link between learning organisation and successful change implementation. Thus, it is important that managers and leaders of public and private sector educational institutions in Ghana invest resources into preparing and getting employees to accept, be committed to and ready for change.

The present study contributes to the scarce knowledge of the mediating role of change readiness in the link between learning organisation and successful change implementation in the African context.

The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.

Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.

Due to the critical importance of digital transformation in enhancing industrial growth and competitiveness, especially in heavy construction, this study introduces a tailored capability assessment model and self-appraisal tool for firms in this sector. These resources enable them to gauge their readiness for adopting digital technology effectively.

Utilizing the Technology—Organization—Environment (TOE) and Natural Resource Dependence Theory (NRDT) frameworks, 22 markers were identified to structure a questionnaire distributed to construction professionals. Descriptive analysis and fuzzy synthetic evaluation (FSE) were used to develop the capability assessment model. A validation survey assessed the validity of both the model and the self-appraisal instrument.

The study identified the top five significant markers: (1) leadership commitment to digital transformation, (2) workforce readiness for technology integration, (3) potential ROI through efficiency gains, (4) technology maturity for construction applications and (5) complexity of integrating new technologies with existing workflows. Through FSE, the most critical factors were technology-related, organizational and resource optimization markers.

By employing the TOE and NRDT frameworks, the study identifies the most critical factors influencing digital adoption in heavy construction. Also, the user-friendly self-appraisal instrument developed in this study can be considered a valuable contribution, as it provides heavy construction firms with a practical tool for ongoing monitoring and improvement of their digital transformation efforts.