Felipe Bastos dos Reis, Adriana Marotti de Mello, João Valsecchi Ribeiro de Souza
Industry 4.0 technologies are increasingly recognized as important contributors to the transition toward a circular economy, yet their association with circular business models (CBMs) remains poorly understood. This paper examines how Industry 4.0 technologies contribute to CBM implementation. Drawing on a systematic literature review of 34 papers and an analysis of 13 illustrative cases from the Circular X and Ellen MacArthur Foundation databases, the study maps the relationship between technologies, applications, and CBM patterns. The findings identify seven core technologies, Artificial Intelligence, Big Data, Cloud Computing, Internet of Things, Additive Manufacturing, Augmented Reality, and Blockchain, and 14 key applications linked to circular business models, such as data integration, predictive maintenance, smart energy management, and supply chain traceability. The results suggest that technology adoption alone is not necessarily associated with circular outcomes. Most applications correspond to efficiency-oriented strategies, particularly the reduction of material and energy consumption, indicating that current uses of Industry 4.0 in CBMs remain strongly oriented toward digital optimization. When technologies are not aligned with circular value propositions, efficiency gains may generate rebound effects, potentially increasing environmental impacts. This study advances the circular economy literature by providing a configurational perspective on the implementation of Industry 4.0 technologies within CBMs and by mapping how digital capabilities contribute to specific circular applications. Practically, the findings offer guidance for managers seeking to prioritize technology investments and move circular business strategies beyond operational efficiency toward circular transformation. Overall, the study contributes to a more comprehensive understanding of how the association between Industry 4.0 technologies and circular transformation, rather than digital optimization alone, appears stronger when their applications align with CBM patterns and circular value propositions.
Abstract Integrating blockchain technology into green building (GB) projects presents substantial opportunities to improve transparency, traceability, and collaboration in the construction sector. However, blockchain’s successful implementation into GB projects remains limited due to the lack of a clear understanding of the critical success factors (CSFs) that facilitate effective adoption. This study identified and classified the CSFs affecting blockchain’s implementation within the GB context using a quantitative approach. A systematic literature review (SLR) and expert consultations initially were performed to establish a preliminary list of 27 CSFs. A validated questionnaire survey subsequently was conducted among industry professionals and academic specialists in GB and digital technologies, resulting in 115 valid responses. Data were examined through exploratory factor analysis (EFA) to identify the fundamental dimensions influencing the implementation of blockchain success. Emergent findings identified five critical factor groups, namely technology-related, organizational and strategic–related, government-related, stakeholder engagement–related, and environmental and GB alignment–related, which collectively explain 74.59% of the total variance. The reliability analysis validated internal consistency among all extracted factors. Practically, the results will support policymakers in designing regulatory and incentive mechanisms, assist organizations in developing strategic adoption plans, and help project stakeholders align blockchain initiatives with sustainability objectives, thereby accelerating digital transformation within the GB sector.
Huriye Gonca Di̇ler, Münevvere YILDIZ, N. Serap VURUR, Letife Özdemir
In today's world, sustainability strategies play a critical role in the transformation of global economies and industries. Green Economic Growth (GEG), which prioritizes environmental factors, is gaining increasing importance. Financial and green innovation are identified as the main driving forces behind GEG. However, research on the effects of these factors in OECD countries remains limited, and existing findings often show inconsistencies regarding the direction and magnitude of these effects. This study aims to comprehensively examine the impact of financial and green innovation on GEG in OECD countries. Using annual data from 15 OECD countries for the period 1996–2021, panel data techniques are applied. Cointegration tests are conducted to determine the presence of long-run relationships among the variables. Subsequently, long-run coefficients are estimated using the panel quantile regression method. The robustness of the findings is tested through OLS and fixed effects models. Additionally, causality tests are employed to explore the directional relationships between the variables. The results indicate that green innovation has a positive long-run effect on GEG, whereas financial innovation exerts a negative impact. Causality tests reveal bidirectional relationships among all variables. Policy recommendations include the promotion of green bonds and sustainable finance instruments, support for green investments through regulations that take environmental risks into account, and the expansion of access to green projects via technologies such as blockchain-based carbon markets. This research provides valuable insights for policymakers in designing more effective strategies to foster sustainable economic growth.
Purpose The purpose of this paper is to apply the integration of signaling theory and self-congruity theory to explain the mechanism by which blockchain-enabled traceability and transparency influence consumers’ willingness to pay a premium for sustainable fashion products. Design/methodology/approach Quantitative data was collected through an online survey with 622 participants in Vietnam using snowball sampling. The participants were those who had awareness or experience with sustainable fashion and blockchain technology. The research model and hypotheses were tested using partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS 4 software. Findings The study found that blockchain signals strongly activate four types of symbolic meanings (status, environment, innovation and fashion). These symbolic meanings reinforce identification with personal identity and feelings of brand authenticity, which in turn promote willingness to pay a premium. Notably, the results showed that hyperopia did not play a moderating role in the relationships between psychological mechanisms and willingness to pay a premium. Originality/value This study contributes by extending signaling theory and self-congruity theory to a blockchain-enabled sustainable fashion context. Rather than proposing a fundamentally new psychological mechanism, it shows how blockchain-based traceability and transparency can function as credibility-enhancing signals that activate established symbolic, identity-related and authenticity-based processes associated with willingness to pay a premium.
Environmental Sustainability in Business
Consumer Behavior in Brand Consumption and Identification