Search Results (40)

This study investigates the attributes influencing the adoption of fintech services for sustainable investment within the blue economy. Specifically, it integrates the Diffusion of Innovations (DOI) theory and the Technology Acceptance Model (TAM) to examine how the perceived relative advantages, compatibility, complexity, trialability, and observability of fintech services influence their perceived ease of use and perceived usefulness, and it explores their impact on the intention to adopt fintech services. Finally, the study assesses how the intention to adopt fintech services affects sustainable investment decisions in the blue economy. Data were collected from 224 stakeholders in the blue economy sectors in India during the summer of 2024 and analyzed using structural equation modeling with partial least squares (SEM-PLS). The results reveal which attributes significantly influence perceived ease of use and perceived usefulness. Additionally, perceived ease of use and perceived usefulness significantly influence the intention to adopt fintech services. The intention to adopt fintech services positively impacts sustainable investment decisions in the blue economy. This study provides a comprehensive framework for advancing fintech services that support sustainable investment decisions, thereby contributing to the growth of the blue economy. Full article

This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience. Full article

Despite the transformative potential of artificial intelligence (AI), small and medium-sized enterprises (SMEs) continue to face significant challenges in its effective adoption. While prior studies have emphasized strategic benefits and readiness models, there remains a lack of operational guidance tailored to SME realities—particularly regarding implementation barriers, resource constraints, and emerging demands for responsible AI use. This study presents an analysis of AI adoption in SMEs by integrating the technology–organization–environment (TOE) framework with selected attributes from the diffusion of innovations (DOI) theory to examine adoption dynamics through a dual structural and perceptual lens. Empirical insights from sectoral and regional contexts are also incorporated. Ten critical challenges are identified and analyzed across the TOE dimensions, ranging from data access and skill shortages to cultural resistance, infrastructure limitations, and weak governance practices. Notably, the framework is expanded to incorporate responsible AI governance and democratized access to generative AI—particularly open-weight large language models (LLMs) such as LLaMA, DeepSeek-R1, Mistral, and FALCON—as emerging technological and ethical imperatives. Each challenge is paired with actionable, context-sensitive solutions. The paper is a structured, literature-based conceptual analysis enriched by empirical case study insights. As a key contribution, it introduces a structured, six-phase roadmap methodology to guide SMEs through AI adoption—offering step-by-step recommendations aligned with technological, organizational, and strategic readiness. While this roadmap is conceptual and has yet to be validated through field data, it sets a foundation for future diagnostic tools and practical assessments. The resulting study bridges theoretical insight and implementation strategy—empowering inclusive, responsible, and scalable AI transformation in SMEs. By offering both analytical clarity and practical relevance, this study contributes to a more grounded understanding of AI integration and calls for policies, ecosystems, and leadership models that support SMEs in adopting AI not merely as a tool, but as a strategic enabler of sustainable and inclusive innovation. Full article

The construction industry is a major contributor to global CO₂ emissions due to high energy consumption in buildings and the production of carbon-intensive materials. Although Big Data is recognized as a transformative tool for improving sustainability by optimizing energy use, resource efficiency, and decision-making, its adoption in construction remains limited. This study aims to identify and analyze the technical, economic, and organizational factors influencing Big Data adoption for sustainability and climate neutrality in Swedish construction companies. A quantitative survey was conducted among 150 industry professionals, and the data were analyzed using descriptive statistics, Spearman correlations, ANOVA, chi-squared (χ²) tests, and principal component analysis (PCA), guided by the diffusion of innovations (DOI) theory. The results indicate that the respondents broadly acknowledge benefits such as energy savings, cost reductions, and improved decision support. The PCA revealed two key dimensions—one capturing technical/environmental benefits, the other economic/regulatory benefits—while barriers included standardization issues, limited digital skills, and investment uncertainties persist. The findings suggest that overcoming these barriers is essential for accelerating a strategic and climate-aligned digital transition in construction, offering actionable insights for policymakers and industry leaders. Full article

To gain a competitive advantage, enterprises are increasingly leveraging digital technologies to create unique value through innovative business models, streamlined operations, and enhanced customer experiences. Despite the widespread adoption of digital technology (DT) to drive digital transformation, research on the factors influencing the public’s intention to use DT for engaging in innovative business activities remains sparse. This study explores the determinants of the public’s intention to adopt DT by integrating the Diffusion of Innovations (DOI) theory and the Technology Acceptance Model (TAM), alongside dynamic individual differences such as perceived risk, computer self-efficacy, and computer anxiety. The findings demonstrate that perceived innovative characteristics and dynamic individual differences significantly impact the public’s intention to use DT through their attitude toward using DT. Finally, this study offers specific recommendations for enhancing the public’s intention to use DT, providing valuable insights for both industry practitioners and academic researchers. Full article

This study examines the factors influencing the behavioral intention and usage behavior of e-bikes in Metro Manila and the National Capital Region (NCR) using constructs from the Diffusion of Innovation (DOI) theory, the Technology Acceptance Model (TAM), and external variables such as government policies, infrastructure, social influence, and public awareness. A cross-sectional survey of 340 respondents was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the relationships among these constructs. The results indicate that perceived usefulness (PU), perceived ease of use (PEOU), social influence, and public awareness significantly affect behavioral intention, which strongly predicts e-bike usage behavior. Infrastructure also positively impacts ease of use, while trialability enhances perceived usefulness. However, the relationships between government policies and perceived usefulness, as well as between trialability and ease of use, were insignificant, reflecting contextual limitations in the Philippine setting. The findings highlight the importance of behavioral intention as a primary driver of e-bike adoption. To address barriers, practical recommendations include expanding bike lanes, implementing e-bike sharing systems, strengthening government incentives, and launching public awareness campaigns that highlight the benefits of e-bikes, such as cost savings and environmental sustainability. This study also contributes to theory by integrating DOI and TAM frameworks, offering a comprehensive understanding of e-bike adoption in developing urban settings. These insights provide actionable strategies for policymakers, manufacturers, and stakeholders to promote sustainable transportation in the Philippines and similar contexts. Full article

The fourth industrial revolution has introduced a range of digital technologies (DTs) that possess the potential to significantly enhance the operations and competitiveness of heavy-construction firms. Grounded in the Technology–Organization–Environment (TOE) Framework, the Resource-Based View (RBV) and the Diffusion of Innovation Theory (DOI), this study investigates the relationship between the adoption of digital technologies and the competitive edge (CE) of heavy-engineering firms. Specifically, this research seeks to assess how the adoption of DTs impacts four critical competitive-edge metrics: efficient resource management (CE1), real-time monitoring and control (CE2), data-driven decision-making (CE3) and improved collaboration and communication (CE4). A quantitative research approach was employed, using a structured questionnaire distributed to construction professionals in Lagos State, Nigeria. The principal results of the study revealed that firms adopting artificial intelligence (AI), cloud-based technology and the Internet of Things (IoT) exhibited significantly higher competitive-edge metrics compared to their counterparts. Notably, AI and cloud-based technology were found to have a particularly strong association with improved resource management, real-time monitoring, and decision-making processes. A major contribution of this research is the development of a DT-adoption model which can serve as a benchmarking tool for firms to assess their current adoption levels and identify areas for improvement. This model can also guide policymakers and regulators in developing strategies to encourage the integration of digital technologies within the heavy-construction industry. The originality of this study lies in its holistic approach, examining a broad spectrum of digital technologies and their collective impact on enhancing the competitive edge of construction firms. Full article

This narrative review synthesizes and analyzes empirical studies on the adoption and acceptance of ChatGPT in higher education, addressing the need to understand the key factors influencing its use by students and educators. Anchored in theoretical frameworks such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Diffusion of Innovation (DoI) Theory, Technology–Organization–Environment (TOE) model, and Theory of Planned Behavior, this review highlights the central constructs shaping adoption behavior. The confirmed factors include hedonic motivation, usability, perceived benefits, system responsiveness, and relative advantage, whereas the effects of social influence, facilitating conditions, privacy, and security vary. Conversely, technology readiness and extrinsic motivation remain unconfirmed as consistent predictors. This study employs a qualitative synthesis of 40 peer-reviewed empirical studies, applying thematic analysis to uncover patterns in the factors driving ChatGPT adoption. The findings reveal that, while the traditional technology adoption models offer valuable insights, a deeper exploration of the contextual and psychological factors is necessary. The study’s implications inform future research directions and institutional strategies for integrating AI to support educational innovation. Full article

Although the adoption of green innovation has been explored in various contexts, there is still a lack of research on the determinants of green technology innovation adoption (GTIA) in the third-party logistics (3PL) industry of emerging economies and the resulting economic, environmental, operational, and intangible outcomes. This study aims to investigate the influence of different determinants of technological, organizational, and environmental factors in the TOE-DOI framework on the adoption of green technology innovation, as well as the outcomes of such adoption. The study utilizes sample data from 544 Chinese 3PL firms and employs two-stage structural equation modeling and artificial neural network analysis. Partial least squares structural equation modeling (PLS-SEM) explains 85.4% of the variance in green technology innovation adoption, 21% in environmental outcomes, 18.5% in economic outcomes, 20.8% in operational outcomes, and 22.3% in intangible outcomes. The artificial neural network (ANN) model ranks the standardized importance of each predictive variable. The results indicate that institutional pressure is the most significant determinant of GTIA. Additionally, 3PL firms should consider the positive impact of green supplier integration and relative advantage. Complexity does not have a positive impact on GTIA. The longer a company has been established, the more experience and resources it accumulates, and the more opportunities it has to adopt green technology innovation. This study contributes to the existing research on emerging economies and other regions. Furthermore, this is the first study to successfully validate the nonlinear relationship within the Technology-Organization-Environment (TOE) framework and diffusion of innovation (DOI) theory, namely the TOE-DOI framework. The research findings further enhance the current understanding of green technology innovation adoption and its impact. This study provides valuable insights for managers and policymakers in the 3PL industry to achieve various effects, such as environmental, economic, operational, and intangible outcomes. Full article

Promoting the use of recycled water is essential for environmental sustainability. A key part of promoting the use of recycled water is effectively increasing the public’s intention to adopt it. This research attempts to explore the factors that influence the public’s intention to adopt recycled water. It therefore introduces the baseline water stress indicator and extends the survey area to areas of high water stress. Based on the Diffusion of Innovation Theory (DOI), a new research model is developed from the perspective of “information disclosure (knowledge)–psychological factors (persuasion)–adoption intention (decision)”, and the moderating role of policy instruments is considered. Structural equation modeling and hierarchical regression analysis are used to empirically analyze 724 valid questionnaires. The results indicate that psychological factors (trust, awareness of water environment protection, herd mentality) have multiple parallel mediating effects between recycled water information disclosure and adoption intention, and herd mentality is the key factor influencing the public’s intention to adopt recycled water. Command-and-control policy instruments inhibit adoption intention, while economic incentives and publicity-and-guidance policy instruments promote adoption intention. These findings can help policymakers seek and adopt effective policy measures and provide a reference for popularizing and promoting recycled water in areas with high water stress. Full article

The current investigation seeks to investigate the relationship between digital innovations and the sustainability perspectives of logistics operations. Despite the advancement of technologies for sustainable goals, it is evident that the importance of digital innovation is increasing as a means of enhancing sustainable operations. Current research is examining the determinants of digital innovation in small logistics firms. A new theoretical framework is developed based on technology adoption, technology integration, and sustainable operations by following the diffusion of innovation (DOI) theory. For this study, data were collected from 540 small logistical firms in China. The covariance-based structural equation modeling technique was used to test the proposed hypothesis. The results from the analysis indicate that technology adoption positively affects the environmental perspectives with coefficients = 0.293, social perspectives with coefficients = 0.461, and economical perspectives with coefficients = 0.461 of sustainable operations. Similarly, technology integration positively affects the environmental perspectives with coefficients = 0.512, social perspectives with coefficients = 0.347, and economical perspectives with coefficients = 0.415 of sustainable operations. In conclusion, the implementation of digital technology for innovation can help firms improve their logistical operations in terms of sustainability, which will deliver a robust business improvement according to this research. Full article

The socioeconomic contribution of microbusinesses towards emerging economies is undeniable. However, numerous factors have broadened the gap between microbusinesses and their smartification. This conceptual study proposes the Technology Adoption Model Canvas (TAMC) based on theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT2), Diffusion of Innovation (DOI), and the Business Model Canvas (BMC) alongside four new/emerging variables, making it possible to understand technology adoption through both individual/cognitive and organizational/physical perspectives. The framework is developed for food service (FS) microbusinesses to facilitate their adaptability in current and future market conditions. Subsequently, we explain the development of the TAMC, including its significance, limitations, and avenues for future research. The proposed framework can provide a solution for FS microbusinesses towards a ‘smarter’ and more sustainable future. It further guides the evaluation of both microbusinesses’ readiness and the factors driving/impeding them towards/from adopting smart technology. Full article

This article explores general concepts related to the diffusion of innovations theory (DoI) and its use regarding the adoption of nature-based solutions, specifically green roofs, in urban areas by private house/property owners in the city of Eindhoven (Netherlands). Given the gap in knowledge on the potential for the adoption of green roofs by private house/property owners as well as barriers and enablers to their implementation from the DoI perspective, we used a model for predicting the adoption of innovations (ADOPT). Results show that the predicted peak adoption level is 3% and that the time to peak adoption level is 17 years. However, the level of adoption can be significantly enhanced by increasing profit benefit (i.e., cost savings) in the years that they are used (+19 percent points adoption), reducing risk exposure (+17 percent points adoption), and improving ease and convenience (+15 percent points adoption), while the time to peak adoption level can be reduced by enhancing relevant and existing skills and knowledge (−3 years), simplifying trialability and innovation complexity (−2 years), and increasing observability (−1 year). Hence, key factors affecting the adoption of green roofs by private house/property owners have been identified, contributing to the formulation of urban climate change adoption strategies. Full article

Sustainable innovations, such as sustainable products or services, are becoming increasingly relevant for society and thrive on societies’ knowledge and usage. But this is where many cities/municipalities are experiencing disharmony: citizens often do not know that these sustainable innovations exist and, therefore, do not use them. Our study starts at this point: To address this disharmony in Germany, the government has established the German Sustainability Award, which honors cities/municipalities with outstanding sustainable innovations. We qualitatively surveyed the citizens and administrations of these cities about their knowledge and use in their city/municipality (using eight categories) under the theoretical lens of Rogers’ (1960/2003) Diffusion of Innovation Theory (DOI). In 29 interviews in six cities/municipalities, we were able to match sustainable innovations based on DOI. In particular, we determined that few sustainable innovations were only found in specific categories (such as economy (EC)), while others existed in all (such as climate and environment (CE) or education (ED)), and, e.g., city/municipality’s size did not matter at all. Full article

The transport sector is undergoing disruption due to trends such as tightening environmental targets, digitalization, and servitization, contributing to low-carbon mobility and offering citizen-oriented services. As a response, various initiatives, such as electric mobility (eMobility), have emerged that promote sustainable road transport and active mobility in the last few years. However, irrespective of the potential of eMobility, there are still few studies that examine individuals’ intention and adoption of eMobility-sharing services in smart communities. Accordingly, this study aims to develop a model grounded on the Diffusion of Innovation (DoI) theory to investigate the factors that impact individuals’ adoption of eMobility-sharing service and how to improve the adoption of eMobility-sharing service. A mixed-mode methodology was employed; quantitative data from survey questionnaires were used to gather data, and Statistical Package for Social Science (SPSS) was used to analyze the data. Additionally, qualitative data via interview was collected to demonstrate in ArchiMate modeling language how eMobility-sharing services are practically implemented as a use case study within smart communities. Findings from this study offer a model that focuses on eMobility-sharing adoption from the perspective of smart communities. Additionally, the findings offer a better understanding of how such integrated, multimodal systems fit with the sustainable mobility needs of citizens. More importantly, general recommendations to policymakers and practitioners to increase the uptake of shared eMobility are provided. Full article