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This paper aims to empirically explore the TOE (technology-organisation-environment) factors influencing small to medium-sized enterprises' (SMEs') adoption of enterprise applications (EA).

Direct interviews were used to collect data from a random sample of SMEs located in the northwest of England. Using partial least squares (PLS) technique, 102 responses were analysed.

Results indicate that technology, organisation and environment contexts impact SMEs' adoption of EA. This suggests that the TOE model is indeed a robust tool to predict the adoption of EA by SMEs.

Although this study focused on examining factors that influence SMEs' adoption of a set of systems such as CRM and e-procurement, it fails to differentiate between factors influencing each of these applications. The model used in this study can be used by software vendors not only in developing marketing strategies that can target potential SMEs, but also to develop strategies to increase the adoption of EA among SMEs.

This model could be used by software vendors to determine which SMEs they should target with their products. It can also be used by policy makers to develop strategies to increase the rate of EA adoption among SMEs.

This paper provides a model that can predict SMEs' adoption of EA. SMEs, adoption, enterprise applications, enterprise systems, ICT, PLS, technology-organisation-environment framework, TOE

Cloud manufacturing (CMfg) has emerged as a service-oriented paradigm that enables modularization and on-demand servitization of resources in the context of manufacturing. The plethora of studies on CMfg has led the authors to investigate its implementation, as most of the literature is theoretical or simulation-based. Therefore, the purpose of this study is to investigate the reality of the CMfg concept in terms of adoption.

A tri-theoretic model is developed using the technology adoption model, diffusion of innovation and technology-organization-environment for hypotheses development. Data are collected from 218 US manufacturers. The data analysis approaches are partial least squares structural equation modeling, while data visualization is done to further analysis.

The study shows that most of the US manufacturers are reluctant to adopt the CMfg. Further, the statistical findings imply that competitive pressure, top management support, compatibility and trialability play a vital role in its adoption. The success of the CMfg adoption relies on the implementation of the pre-installation stage and the top management decisions.

For practitioners, the study provides insight on how to supervise the CMfg platform implementation to improve the adoption process. For researchers and academicians, the significance of trialability provides a wide range of research topics on developing the CMfg trials and models.

This paper highlights the concerns of manufacturers about the pros and cons of the CMfg adoption, as this topic has not been given due attention in the literature. This will help to align future research directions according to market concerns and mitigating the factors that are hindering its adoption.

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.

The purpose of this study is to analyse the factors influencing intention to adopt 3D design digital technologies (3DDTs) by Colombian firms.

A conceptual framework was developed using technology-organization-environment (TOE) and technology acceptance model (TAM) theoretical frameworks. From a sample of 138 firms, a structural equation model was analysed with partial least squares (SEM-PLS).

The study identified that perceived usefulness in the technological dimension; technological competence and top management support in the organizational dimension; and competitive pressures in the environmental dimension, are variables affecting intention to adopt 3DDT. The effects of the mediating variables with respect to intention to adopt the technology are also analysed, such as perceived usefulness on the effect of ease of use; top management support on the effect of technological competence and financial readiness; and competitive pressures on the effect of stakeholder pressure. The model explained 71.1% of the 3DDT intention to adopt.

The model can be used as a guideline to ensure a positive outcome of the 3DDT adoption in organizations. The results could be useful to understand a technological adoption process for digital transformation.

The proposed model integrates some contributions from the TAM and TOE theories and identifies some novel mediating effects that improve its predictive and explanatory power. Furthermore, this is a pioneering study in empirical research on 3DDT in the context of a developing country, specifically in Colombia. The findings from this study provide a foundation for other studies, as well as constructive insights for digital transformation, due to its infancy in an emerging economy.

As insiders remain to be a main reason behind security breaches, effective information security awareness campaigns become critical in protecting organizations from security incidents. The purpose of this paper is to identify factors that influence organizational adoption and acceptance of computer-based security awareness training tools.

The paper uses content analysis of online reviews of the top ten computer-based security awareness training tools that received Gartner peer insights Customers’ Choice 2019 award.

This study identifies nine critical adoption and success factors. These are synthesized into a conceptual framework based on the technology–organization–environment framework. The findings reveal that technological, organizational and environmental factors come into play in adoption decisions but with varying degrees of importance.

This study highlights key factors that technology vendors should take into consideration when designing computer-based security awareness training tools to increase adoption rates.

This research offers a novel contribution to the literature on information security awareness delivery methods by identifying key factors that influence organizational adoption and acceptance of computer-based security awareness training tools. Those factors were identified using content analysis of online reviews, which is a new methodological approach to the information security awareness literature.

Understanding the critical determinants for the adoption of electronic markets (e-markets) is significant for the development of sustainable electronic business. The purpose of this paper is to investigate the critical determinants for the adoption of e-markets in Australian small- and medium-sized enterprises (SMEs) for electronic business.

A comprehensive review of the related studies is conducted. That leads to the development of a conceptual model for exploring the critical determinants for the adoption of e-markets in Australian SMEs. Such a model is then tested and validated using structural equation modelling on the survey data collected, leading to the identification of the critical determinants for e-market adoption in Australian SMEs.

The study reveals that perceived direct benefit, perceived trust, top management support and external pressures are critical for the adoption of e-markets in Australian SMEs. Perceived indirect benefit and organization readiness are insignificant for the adoption of e-markets.

This paper contributes to existing electronic business research by enriching the understanding of the critical determinants for the adoption of e-markets in Australian SMEs. Such a study provides government departments, e-market operators and SMEs with practical guidelines for the better use of e-markets in electronic business.

This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.

This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.

Digital transformation in supply chains (SCs) has emerged as one of the most effective ways to minimize SC disruption risks. Given the unprecedented impact of the COVID-19 pandemic on global SCs, this study aims to identify and provide empirical evidence about the drivers of digital SC transformation, considering the interactivity between environmental dynamism, technology, and organizational capabilities during the pandemic era.

Using partial least squares structural equation modeling (PLS-SEM), this study examines 923 firms in Vietnam to ascertain the drivers of digital SC transformation between small- and medium-sized enterprises (SMEs) and large enterprises, based on the technology–organization–environment (TOE) as an overarching framework.

This study finds that greater digital SC transformation adoption could be achieved under the interactivity between the TOE components of firms' technological competencies, learning capabilities, and disruptions in socioeconomic environments due to the COVID-19 pandemic. Moreover, a multigroup analysis shows that the drivers of digital SC transformation differ between SMEs and large enterprises. SMEs were found to be more motivated by the COVID-19 disruption risk when adopting digital SC models.

This study represents an original and novel contribution from Vietnam as an emerging market to the literature on the impact of COVID-19 on the global value chain. Apart from the unique dataset at the firm level, the analysis of interactions between external and internal drivers of digital SC transformation could provide crucial managerial implications for SMEs to survive major disruptions, such as those caused by the COVID-19 pandemic.

The paper aims to address the organizational transformation of firms for value creation resulting from cloud computing (CC).

With reference to the theory of organizational fit, we modeled organizational transformation as a function of five aspects of CC practice: functionality, data management, roles and competences of information technology services, control and organizational culture. The output variable was tested against a set of input variables defined with reference to the technology–organization–environment (TOE) and technology acceptance model (TAM). Based on a sample of 487 companies in seven countries in Europe, Asia, and the United States, the authors distinguished two groups of firms: transformational and hyper transformational.

The results highlight the key factors that determine whether a firm falls into one of these two groups, and include perceived usefulness and perceived ease of use, complexity and compatibility of CC technology, and adequacy of resources. Top management support and government policy are found to only play a role for the transformational group while, surprisingly, vendor support had no impact for either group.

This research contributes to the literature on the role of digital transformation in value creation and on digitization of firms and organizational design, notably by considering the contribution of CC to the organizational dimension. To the best of the authors’ knowledge, this is the first study to make the link between TOE and TAM models and organizational fit theory, thereby going beyond the general approach to adoption found in information system research.

Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant.

A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry.

The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants.

This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology.

This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.