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This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

The purpose of this paper is to capture the up-to-date development of quality management (QM) programs in China’s manufacturing landscape. The study aims to gain understanding on the current state-of-the-art QM programs adopted by Chinese manufacturing companies. Furthermore, the study investigates the key drivers and organizational characteristics that may shape the decisions on QM program adoption.

To gain a deep understanding of QM in China’s manufacturing landscape, in-depth interviews were conducted with production managers, quality managers, and/or executives of 12 manufacturing companies in four cities in China in May and June 2012. Each interview lasted about two hours and covered all aspects of QM in the business, including what quality programs are in place and why the business adopts and implements these programs. Grounded theory approach is used to conduct qualitative analysis on the interview transcripts using NVivo 9, a qualitative data analysis program.

Two categories of QM programs adopted by Chinese companies emerged from the analysis, namely, QM systems and QM certifications. QM systems include Total Quality Management (TQM), Six Sigma, and Lean. QM certification includes ISO 9000 series standard certificates, ISO 14000 certificate, OHSAS heath certificates, government regulatory certificates, and industry certificates. The authors found while Six Sigma and Lean adoption is related to parent company requirement, TQM adoption is related to internal quality improvement and control, quality assurance, leadership ideology, culture, and employee commitment. QM certification adoption is significantly related to external drivers. Regarding the effect of organizational characteristics, the study reveals that while corporate governance and ownership influence parent company requirements as an adoption driver, industry, product, and market segmentation influence industry requirements and government regulations as adoption drivers.

The findings and proposed conceptual framework are based on qualitative data collected from 12 companies in four cities in China, which may be limited to represent and reveal every aspect of QM programs adopted in Chinese manufacturing industries. The findings provide theoretical propositions that can be verified using a large sample set in future studies. In addition, although the study identified a variety of QM programs adopted, how these programs are implemented warrants further investigation.

This study gives a status update and in-depth investigation on the development of QM programs adopted in Chinese manufacturing companies. How internal drivers, external drivers, and organizational characteristics shape companies’ decision on program adoption were explored. The study results provide implications not only for companies that are involved in supply chains with operations in China, but also for Chinese domestic companies competing in global markets to have QM systems in place to ensure quality performance.

This study used multiple case study approach and grounded theory approach to conduct in-depth investigation on the current state of QM landscape in China’s manufacturing companies. It contributes to the body of knowledge on QM programs in China by uncovering the linkages between program adoption, key drivers, and organizational characteristics in an integrated framework.

This paper aims to propose a new genetically evolved fuzzy cognitive mapping approach as a decision-making framework for analyzing the relationships between the drivers and strategies for green computing adoption.

A focus group discussion among stakeholders in the Philippines is used to establish the relationships between the drivers and strategies of green computing adoption.

The proposed approach significantly reduces the time complexity for developing the fuzzy cognitive maps and provides a basis for comprehensively clustering drivers and strategies that share similar characteristics.

This paper’s results provide insights into how the drivers and strategies of green computing adoption facilitate the intention of adopting stakeholders. Moreover, it provides a framework for analyzing structural relationships that exist between factors in a compliant manner.

To the best of the author’s knowledge, the paper is the first to analyze the drivers and strategies of green computing under a complex systems’ perspective. Moreover, this is the first study to offer lenses in a Philippine scenario.

The purpose of this paper is to present a review of research developments on the ecosystem of driving forces for electronic procurement (e-procurement) on project procurement and to propose directions for future research for an effective adoption and sustained usage.

A systematic literature review was conducted in three phases to identify and examine literature. A total of 68 papers were retrieved and were thoroughly reviewed to identify the drivers for e-procurement.

A total of 61 drivers were identified and subsequently developed into a categorization framework for synthesized understanding which reveals existing interrelationships. Although literature has consensus on some selected drivers, few studies have identified drivers relating to sustainability. Gaps were identified from the existing literature and directions for future research were proposed.

Since this is a literature review, future research could conduct further investigations focusing on the research gaps identified. The framework developed presents a basis for further research to explore the drivers in various socio-economic environments.

This study provides valuable insights for improving the understanding of practitioners on the complex network of drivers for e-procurement. These findings stimulate discussions on benefits required for assessment in e-procurement adoption by practitioners.

This study provides the first comprehensive review of the drivers for e-procurement adoption in the construction industry, which was lacking in the existing body of knowledge.

Despite ample research on the adoption of online banking, the post-adoption phase remains largely neglected. The purpose of this paper is to develop a new conceptual model to investigate drivers, attitudes and behaviours in the post-adoption phase of the e-postbox, a co-creative online banking feature.

Research from bank marketing, services marketing, information systems and relationship management informs the proposed post-adoption model. Empirical tests rely on structural equation modelling and a sample of 750 current customers of the e-postbox of a large German bank.

The proposed model provides a multifaceted view of the post-adoption phase, including task-related, organisation-related and interpersonal communication-related drivers. This study reveals the importance of integrating dual interpersonal communication as a post-adoption driver and a post-adoption behaviour. It also extends the technology acceptance model by applying it to the post-adoption phase. Significant effects of age further suggest that younger customers express the most favourable attitudes towards and highest intentions to continue using the e-postbox; interestingly, older customers use it more and share more word-of-mouth.

This paper develops a post-adoption model that highlights the importance of continued usage for successful co-creation between the bank and its customers.

Managers can encourage continued usage during the post-adoption phase of a co-creative, digitalised service, which determines the retention of current customers and opportunities to attain new customers.

This study defines and establishes constructs for the post-adoption phase and categorises them according to post-adoption drivers, attitudes and behaviours.

Change drivers are events, activities, or behaviors that facilitate the individual adoption of change initiatives and the implementation of organizational change. The purpose of this paper is an exploratory study of whether gender differences exist for change drivers.

This paper involves a three‐year study of an organizational change in the banking industry, and uses survey and interview data.

Data show that the mean perceived significance of change drivers to the understanding and adoption of change initiatives by male and female employees is similar and does not vary at a statistically significant level. Statistically significant gender differences do exist in terms of the relationship between change drivers and employees' reported individual adoption of change initiatives. Qualitative data from the interviews support those quantitative findings, showing gender differences in how change drivers are perceived; differences in change‐related vision, leadership, communication and positive outcomes as drivers are discussed.

This is an exploratory study and needs to be replicated with other organizational changes in a variety of industries with varied employee demographics and differences in change leadership gender.

Change drivers are a form of resource allocation. Better understanding of gender differences in terms of the perception of and significance of change drivers to individual employees' understanding and adoption of change initiatives can result in more effective allocation of resources by change leaders.

Very limited prior research explores gender or other demographic differences for change drivers. This research provides an empirical study of gender and change drivers and extends prior research on change drivers and the change process.

The purpose of this article is to identify the drivers for, and barriers to, the adoption of assurance systems in a range of agri‐food value chains that will allow the design of better, more appropriate‐for‐the‐task assurance systems that are more likely to be fully utilised by value chain members.

Semi‐structured interviews were used to collect a snapshot of the knowledge, attitudes, skills and aspirations (KASA) of value‐chain members with regard to assurance systems in fruit (cherries), seafood (mussels) and red meat (lamb). Responses were grouped by KASA characteristic for qualitative analysis. The nature of the dairy industry necessitated the use of a desktop review of the food‐safety assurance system.

The actual drivers for, and barriers to, adoption varied with the industry studied but included the requirements of domestic and export market customers, realistic appreciation of risk, mandatory schemes, the influence of other value chain members, financial incentives and external influences. The major barrier to the adoption of assurance systems was the perception that the costs of such an assurance system outweigh its benefits.

This study was purely qualitative and covered only one value chain within each of three industries with a desktop review in a fourth industry.

A suite of drivers that includes financial incentives results in more effective adoption of assurance systems than a single driver such as market access.

The observations could lead to a series of design principles for the development and deployment of agri‐food assurance systems.

Rapid changes in the global environment and the effects of existing economic issues triggered by COVID-19 and the war in Ukraine have posed several challenges for manufacturing firms. A hybrid strategy integrating lean and agile (leagile) systems is viable for firms to enhance their capabilities in such dynamic contexts. This paper examines the critical drivers of leagile manufacturing system adoption in an emerging economy from the technological, organizational and environmental (TOE) perspective.

A cross-sectional survey is carried out to obtain data from 438 managers working in 219 manufacturing firms. Multiple regression analysis is applied to test the effect of technological, organizational and environmental drivers on the adoption of leagile systems.

The results show that organization capacity, environmental uncertainty and relative advantage demonstrate the most significant positive relationships with the leagile systems adoption wherein complexity and resistance to change appear to exhibit significant negative associations. Unexpectedly, firm size unveils no significant effect on the adoption of leagile systems.

To deal effectively with critical challenges triggered by ever-changing environment, firms have sought to adopt innovative systems for achieving products' availability in the markets at the right quality and price. A hybrid strategy integrating lean and agile (leagile) systems is viable to enhance a firm's capabilities in such dynamic contexts. The findings of our study help top management and policymakers identify and assess the critical drivers that may facilitate or hinder the successful adoption of leagile systems.

A major trend of studies in the field of manufacturing systems has focused on the critical success factors of adopting either lean or agile systems. Furthermore, research work concerning leagile as a hybrid system focuses primarily on the conceptual development rather than empirical grounds of leagile systems. Given the lack of empirical research in this field, this study offers an early attempt to predict leagile system adoption in an emerging economy. It also contributes to the manufacturing systems research by extending the extant knowledge about the role of firm-level drivers in leagile system adoption from the TOE perspective.

This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency.

ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM.

The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits.

The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.

The rise of artificial intelligence (AI) and differing attitudes towards its adoption in the building and environment (B&E) industry has an impact upon whether companies can meet changing demand and remain relevant and competitive. The emergence of Industry 4.0 technologies, coupled with the repercussions of COVID-19, increases the urgency and opportunities offered that companies must react to, as disruptive technologies impact how project management (PM) professionals work and necessitate acquisition of new skills. This paper attempts to identify the drivers of and barriers to, as well as the general perception and receptiveness of local PM professionals towards, AI adoption in PM and thereby propose potential strategies and recommendations to drive AI adoption in PM.

This study employs both quantitative and qualitative approaches to examine the findings gathered. A survey questionnaire was used as the primary method of gathering quantitative data from 60 local PM professionals. Statistical tests were performed to analyse the data. To substantiate and validate the findings, in-depth interviews with several experienced industry professionals were performed.

It is found that top drivers include support from top management and leadership, organisational readiness and the need for greater work productivity and efficiency. Top barriers were found to be the high cost of AI implementation and maintenance and the lack of top-down support and skilled employees trained in AI. These findings could be attributed to the present state of AI technologies being new and considerably underutilised in the industry. Hence, substantial top-down support with the right availability of resources and readiness, both in terms of cost and skilled employees, is paramount to kick-start AI implementation in PM.

Little research has been done on the use of AI in PM locally. AI's potential to improve the productivity and efficiency of PM processes in the B&E industry cannot be overlooked. An understanding of the drivers of, barriers to and attitudes towards AI adoption can facilitate more intentional and directed oversight of AI's strategic roll-out at both the governmental and corporate levels and thus mitigate potential challenges that may hinder the implementation process in the future.