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This study aimed to predict and understand the academic libraries' probability of successful adoption of blockchain within the lens of integrated technology acceptance model (TAM) and technology organization and environment theory (TOE) framework.

A mixed approach was employed to gather data from librarians (292) and system analysts (46) totaling 338 respondents. The total enumeration sampling technique was considered. Qualitative data were analyzed thematically, while quantitative data were analyzed using structural equation model (SEM).

Perceived usefulness and policy are the important factors that influence academic libraries' blockchain adoption intentions. Unlimited access to both print and electronic resources, security of users' information and easy collaboration between users and library staff were found to be the benefits of blockchain application to academic libraries' operations. Major challenges to the adoption of blockchain in academic libraries include the cost of infrastructure related to blockchain applications, privacy issues and a lack of understanding of blockchain technology among librarians.

Future studies would need to include more relevant items to the observed variables of the independent variables that were found insignificant in this study.

The findings of this study will create a roadmap for government and polytechnic management on the factors that could strengthen the adoption of blockchain in the libraries.

The outcome of this study came at a crucial moment when the majority of academic libraries in developing nations like Nigeria were skeptical about the deployment of blockchain technology in their libraries.

The study identified new factors that influence blockchain adoption intention.

The purpose of this research is to explore and explain education management information system (EMIS) post-adoption in the context of mandatory settings, focusing on perceived benefits and individual and institutional post-adoption usage.

To fulfill the research objectives, the study proposes a conceptual model grounded in the technology acceptance model (TAM) and the technology-organization-environment (TOE) framework. Data for model validation were obtained via a questionnaire and were collected from 144 teachers in public primary schools in the Republic of North Macedonia. For statistical analysis, PLS-SEM was used.

Based on the conducted statistical analysis, it is found that in mandatory environments, perceived ease of use, perceived usefulness, compatibility, complexity and governmental support are the factors that have indirect effects on the post-adoption usage, and only the factors, technological knowledge and external information and communication technology (ICT) support, have direct effects on the post-adoption usage. The individual post-adoption usage in mandatory settings depends on whether benefits are perceived in the course of EMIS usage; they become a central factor due to the accumulated knowledge and experience.

The main contribution of this study is to theoretically and empirically discover the most important factors that influence EMIS post-adoption usage. Perceived benefits are considered as external factors to the TOE framework and mediate the effect of TAM-TOE factors on individual post-adoption usage.

Cloud computing (CC) services have given a tremendous boost to the creation of efficient and effective solutions. With developing countries at a slow pace of adoption, this research aims to identify factors and their interrelationships influencing the adoption of CC in a developing country context. The developing countries are enjoying numerous benefits from CC services; however, its low adoption is still a question in developing economies; hence, the authors have selected the context of information and communication technology (ICT) firms in India.

The qualitative research method is used where experts from thirteen ICT firms in India are interviewed.

Sixteen factors, twenty-eight subfactors, and 25 interrelationships are revealed through content analysis. Further, causal loop diagrams are proposed to display the behavior of cause and effect of these factors from a system's perspective. This will help to understand the relationships among the factors in order to enhance the speed of CC adoption. Possible financial loss and resistance to change are found as the key barriers to adoption. The proposed interrelationships can guide both policymakers and service providers for designing effective CC policies.

This is the first scholarly work that identifies interrelationships among factors and subfactors, thereby providing a holistic picture to decision-makers while making a choice on whether to adopt cloud services or continue with on premise data centers and servers.

As a little research has been conducted to understand the factors influencing users’ intentions to adopt blockchain-based telemedicine (BBT), it is important to investigate BBT acceptance as incorporation of blockchain technology can solve telemedicine-related issues. Accordingly, this study aims to investigate the factors influencing behavioral intentions (BI) to adopt BBT.

An integrated model comprising the constructs taken from technology–organization–environment framework, technology acceptance model, unified theory of acceptance and use of technology and theory of planned behavior based on their relevance to the context and the objectives of the study has been used for this research. A quantitative approach has been used to test the hypotheses, for which the data was collected from 324 respondents through a self-administered questionnaire. Partial least squares structural equation modeling has been used to test the hypotheses.

The results of the study show that relative advantage, perceived usefulness, trust and perceived ease of use have a significant impact on BI to adopt BBT, whereas regulatory support, subjective norms and facilitating conditions do not have any significant impact on the same.

As the concept of BCT in Pakistan is at its nascent stage and literature regarding this technology’s adoption is also limited, researchers and scholars can apply it to several other fields in Pakistan. For example, this study can be extended to explore the factors influencing blockchain adoption in areas such as education, logistics, transportation, finances and management. This research only considers the direct effects of constructs on BI to adopt BBT and does not consider any mediation and moderations constructs. Future researchers can also study the influence of mediation and moderation constructs on BI to adopt BCT.

Although studies on the acceptance of telemedicine exist, there is a gap concerning the acceptance of BBT, which the current study helps to bridge. From a practical standpoint, the current study makes a highly valuable contribution toward understanding acceptance factors for BBT projects, leading to help policymakers devise policies to promote telemedicine.

This study aims to identify the driving factors that influence blockchain technology adoption in the context of a supply chain (SC), considering three dimensions: technology, transactions and collaboration.

An integrative systematic literature review of previous studies was conducted. Using three main dimensions: technology, transactions and SC collaboration, supported by the unified theory of acceptance and use of technology, transaction cost economics (TCE) and concepts of SC collaboration, the authors categorized factors that contributed to blockchain technology in SC in the extant literature and proposed a theoretical model that covers these three dimensions.

The findings reveal that the information sharing category – related to the SC collaboration dimension – is the category with the greatest number of motivating factors for blockchain adoption in the SC context, followed by performance expectancy and behavioral uncertainty.

The review considers papers published until 2021 obtained from a specific database.

This study focuses on filling the research gap concerning technology adoption as it considers the interconnection formed by two organizations, interorganizational transactions and SC collaboration, using complementary theories to explain the phenomenon.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

This systematic literature review aims to explore the adoption, global acceptance and implementation of human resources (HR) analytics (HRA) by reviewing literature on the subject. HRA adoption can assist HR professionals in managing complex procedures and making strategic human resource management (SHRM) decisions more effectively. The study also aims to identify the applications of analytics in various disciplines of management.

The review is conducted using a domain-based structured literature review (SLR), emphasizing the diffusion of innovative thinking and the adoption process of HRA among early adopters. The philosophical stances are analyzed with the combination of research onion model and PRISMA protocol. Secondary data are gathered from published journals, books, case studies, conference proceedings, web pages and media stories as the primary source of information.

The study finds that skilled professionals and management assistance can significantly impact adoption intentions, enabling professionals to deal with analytics. The examples and analytical models provided by early adopters allow managers to manage complex processes and make SHRM decisions.

The study suggests that the lack of use of quantitative techniques is a key limitation and should be considered in future studies. Despite the rise in the number of research papers on HRA, its application in the workplace remains limited.

This research can assist managers in implementing HRA and help resolve complex and inefficient processes, making SHRM decisions.

This study adds to the existing body of knowledge on how HRA can aid a company's efficacy and performance and can be considered one of the first to link adoption and HRA.

The study aims to develop an integrated model for three-dimensional (3D) printing adoption in the Gulf Cooperation Council (GCC) context to form a baseline for more theoretical and empirical debate from emerging markets.

A qualitative approach with a convenience sample is adopted since there is no formal body that has accurate data about the number of companies, governmental bodies, nongovernmental organizations, universities, labs, etc. that already have adopted 3D printing.

The results indicate that the technological usefulness of 3D printing and its ease-of-use factor were found to be lacking among community members and governmental officials. Yet, these factors were the most influential factor affecting the spread of 3D printing technology adoption in the GCC countries. Nevertheless, the adaptation of 3D printing is not yet at the level of its global markets, nor is it used within leading companies’ assembly lines. In addition, the 3D printing awareness and use increased during the COVID-19 pandemic. Yet, the adaptation rate is still below expectations due to several challenges that face the growth of the 3D printing market in the GCC countries. The most vital challenge facing 3D printing growth is manifested in governmental policies and regulations.

Companies’ managers can benefit from the current study results by focusing on the factors that facilitate 3D adoption and avoiding bottle-neck factors that hinder the speed of the 3D adoption. 3D providers can also benefit by understanding the factors that affect 3D adoption and designing their machine and marketing strategy in a way that helps the intended companies to easily adopt 3D printing.

To the best of the authors’ knowledge, this is the first study that explored 3D printing adoption on the GCC countries’ level. It also adds a new flavor to the literature by exploring 3D adoption during the COVID-19 crisis.

Due to the unprecedented disruptions in business operations, many organisations are turning to Cloud ERP implementation to ensure employees can access real-time business information from anywhere, enabling the continuity of business activities. As a result, over the past decades, literature on Cloud ERP implementation has seen significant growth across different subject areas. This paper aims to present a systematic literature review (SLR) that consolidates the literature scattered across various multidisciplinary subject areas, explores recent developments and identifies knowledge gaps for more impactful future research.

An SLR approach has been applied to a sample of 73 articles published until 1 February 2022.

Our SLR identifies and consolidates a set of critical enablers and barriers to the implementation of Cloud ERP. What is particularly interesting is that this study established a link between these enablers and barriers and four key innovation outcomes: product, service, process and business model innovations. A rigorous framework has been devised that demonstrates the nexus between enablers and barriers to Cloud ERP implementation and innovation outcomes in an organisation. In addition, this study has recognised several organisational theories from information systems literature that have the potential for future research in this emerging area.

This SLR makes several theoretical contributions to the literature on Cloud ERP implementation and its impact on innovation outcomes.

The review consolidates a wide range of literature to provide decision-makers with an integrated understanding of the most influential factors in Cloud ERP implementation.

SLR provides a comprehensive analysis of the current state of research on the topic, offering unique perspectives on developments in theory and knowledge gaps, as well as identifying future research opportunities in the area.