Search Results (29)

With the rapid advancement of the Internet and big data, data sharing has become pivotal for enhancing operational efficiency and user experience across industries. In the restaurant sector, the emergence of smart kitchens has accelerated digital transformation, underscoring the critical importance of data sharing. In this study, we investigate the evolutionary dynamics among four key stakeholders in the smart kitchen ecosystem: data providers, data-sharing platforms, data consumers, and regulators. We develop a four-party evolutionary game model to analyze the strategic interactions and behavioral evolution of each participant, applying replicator dynamics and Lyapunov stability theory. Our findings reveal that (1) data providers’ willingness to supply high-quality data is strongly influenced by platform incentives; (2) platforms’ adoption of data governance mechanisms depends on associated governance costs; (3) regulatory subsidies contribute significantly to system stability; and (4) increased financial support for regulators promotes favorable system evolution. This work offers both theoretical insights and practical guidance for data sharing in smart kitchens, providing a novel perspective on digital transformation within the restaurant industry. Full article

In the rapidly evolving global business landscape, servitization and digitalization have emerged as key strategies for enhancing firm competitiveness and performance. This study examines their impact, along with the moderating role of government support, in the Indonesian shipping industry. Drawing on the resource-based view (RBV), servitization and digitalization are conceptualized as internal drivers of performance, while Resource Dependence Theory (RDT) positions government support as an external factor that reduces environmental uncertainty and strengthens these relationships. Using data from 345 shipping companies, analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM), the results show that both servitization and digitalization positively affect competitiveness and performance. Furthermore, government support significantly enhances these effects by providing resources such as infrastructure and financial incentives, facilitating the adoption of digital strategies and service-based models. Beyond firm outcomes, these transformations align with broader sustainability objectives by improving resource efficiency, reducing waste and delays, and potentially lowering the environmental footprint of logistics activities. This study advances theoretical understanding by demonstrating the central role of external resources—particularly government support—in enabling successful digital and service transformations. For policymakers, the findings emphasize the need for targeted incentives and infrastructure to accelerate industry-specific innovation and sustainability goals. For practitioners, they highlight the importance of aligning strategic initiatives with government policies to maximize the benefits of servitization and digitalization. Full article

Despite the acknowledged importance of capital for start-up success, gender disparities persist when trying to raise funds from external sources, including angel investors, venture capitalists, and financial institutions. Many studies have shown that gender stereotypes are harmful and prevent women from gaining access to resources, e.g., capital, distorting their start-up valuations, and influencing the resulting financing decisions. In recent years, gender-specific support measures have emerged that attempt to overcome gender inequalities in early-stage entrepreneurship, including gender-specific accelerator programs. However, there remains a lack of research on the effects of these gender-specific support programs. This study therefore investigates the influence of participating in gender-specific accelerator programs on access to angel capital, as a highly relevant source for the early financing of (women-founded) start-ups, considering signaling theory and its influence by the role congruity theory in an entrepreneurial context. A laboratory experiment involving 227 participants was conducted to explore these dynamics, reflecting perceptions of signals for angel investors. Overall, the findings suggest that gender-specific accelerator programs may positively influence perceived investment decisions by enhancing perceived team competence. Furthermore, investor gender moderates the perception of team competence. The signaling effect that (gender-specific) accelerators have on angel investors does not appear to be as great for men investors as it is for women investors. The findings contribute to signaling theory by understanding the impact of participation in (gender-specific) accelerator programs on the investment decision of angel investors while advocating for more inclusive approaches to fostering diversity and inclusivity within the start-up ecosystem. Full article

The incorporation of environmental, social, and governance (ESG) concerns into corporate finance has accelerated globally; nevertheless, empirical data about its effects in the U.S. context is still scarce. This research examines the impact of sustainable financing on the financial performance of non-financial enterprises listed on the New York Stock Exchange (NYSE) from 2008 to 2024. This study used the stakeholder theory and other theories to analyze four aspects of sustainable finance: green financing efforts, emission reduction strategies, sustainable product initiatives, and environmental investment initiatives. The study implemented a dynamic panel regression model with the two-step Generalized Method of Moments (GMM) to mitigate endogeneity and omit variable bias. The findings indicate that green finance, emission reduction strategies, and sustainable product efforts have a positive and significant impact on Return on Assets (ROA) and Return on Net Operating Assets (RNOA), demonstrating their effectiveness in enhancing financial performance. Conversely, environmental investment programs exhibited a strong and negative correlation with financial success, indicating immediate cost implications. These findings emphasize the significance of strategic planning in sustainability investments and reinforce the necessity for legislative incentives to assist enterprises throughout the transition. This study enhances the literature by providing U.S.-specific, component-level insights into the financial implications of sustainable financing, therefore offering pragmatic counsel for managers, investors, and regulators. Full article

This study examines the Enron collapse through an integrated theoretical framework combining the financial saturation paradox with the dynamics of a naturally occurring Ponzi process. The central objective is to evaluate whether endogenous market mechanisms—beyond managerial misconduct—played a decisive role in the emergence and breakdown of the Enron stock bubble. A logistic-growth-based saturation model is formulated, incorporating positive feedback effects and bifurcation thresholds, and applied to Enron’s stock price data from 1996 to 2001. The computations were performed using LogletLab 4 (version 4.1, 2017) and Microsoft^® Excel^® 2016 MSO (version 2507). The model estimates market saturation ratios (P/Pp) and logistic growth rate (r), treating market potential, initial price, and time as constants. The results indicate that Enron’s share price approached a saturation level of approximately 0.9, signaling a hyper-accelerated, unsustainable growth phase consistent with systemic overheating. This finding supports the hypothesis that a naturally occurring Ponzi dynamic was underway before the firm’s collapse. The analysis further suggests a progression from market-driven expansion to intentional manipulation as the bubble matured, linking theoretical saturation stages with observed price behavior. By integrating behavioral–financial insights with saturation theory and Natural Ponzi dynamics, this work offers an alternative interpretation of the Enron case and provides a conceptual basis for future empirical validation and comparative market studies. Full article

This follow-up scientific case study builds on prior research to explore the computational challenges of applying quantum algorithms to financial asset management, focusing specifically on solving the graph-cut problem for investment recommendation. Unlike our prior study, which focused on idealized QAOA performance, this work introduces a graph compression pipeline that enables QAOA deployment under real quantum hardware constraints. This study investigates quantum-accelerated spectral graph compression for financial asset recommendations, addressing scalability and regulatory constraints in portfolio management. We propose a hybrid framework combining the Quantum Approximate Optimization Algorithm (QAOA) with spectral graph theory to solve the Max-Cut problem for investor clustering. Our methodology leverages quantum simulators (cuQuantum and Cirq-GPU) to evaluate performance against classical brute-force enumeration, with graph compression techniques enabling deployment on resource-constrained quantum hardware. The results underscore that efficient graph compression is crucial for successful implementation. The framework bridges theoretical quantum advantage with practical financial use cases, though hardware limitations (qubit counts, coherence times) necessitate hybrid quantum-classical implementations. These findings advance the deployment of quantum algorithms in mission-critical financial systems, particularly for high-dimensional investor profiling under regulatory constraints. Full article

Enhancing innovation capability can effectively promote the development of traditional industries. Based on Lewin’s behavioral model theory, this study investigated the relationship between industrial support policies and innovation behavior within traditional industries. Utilizing survey data collected from 152 traditional industrial enterprises in 2024 and employing structural equation modeling, the main findings are as follows: Industrial support policies can effectively alleviate the “innovation inertia” of traditional industries, with all policies being significant at the 1% confidence level. Among them, policies related to industry–university–research cooperation platforms have the most significant impact, with a standardized coefficient of 0.941, followed by fiscal and taxation policies (standardized coefficient: 0.846) and financial policies (standardized coefficient: 0.729). Innovation motivation acts as a mediating mechanism between industrial policies and innovation behavior. Industrial support policies accelerate the conversion of reserve-oriented patent portfolios into practical applications, helping to break through patent barriers and effectively alleviate innovation inertia. Consequently, the government should prioritize improving public services, and policy formulation needs to be oriented towards enhancing innovation efficiency. While ensuring industrial security, it is advisable to moderately increase competition to guide traditional industry market players towards thriving in competitive environments. Full article

In the face of accelerating digital transformation and AI-driven innovations in the post-COVID-19 era, the effectiveness of Human Resource Information Systems (HRIS) is critical to organizational resilience and sustainable digital transformation in highly regulated sectors. This study examines how information quality, executive innovativeness, and staff IT capabilities influence HRIS effectiveness and evaluates the mediating role of Information System (IS) Ambidexterity, defined as an organization’s ability to explore and exploit its IS resources concurrently. By confirming the impact of organizational enablers on HRIS effectiveness, the study provides theoretical grounding for digital transformation strategies rooted in Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT). Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS was employed for its strength in modeling complex relationships and validating latent constructs in organizational contexts. Empirical data were gathered from 157 HR leaders across financial institutions in Pakistan. The results confirm that the identified enablers significantly impact both IS Ambidexterity and HRIS effectiveness and also emerge as strategic levers for building resilient, data-driven HRIS frameworks. IS Ambidexterity, a relatively underexplored construct in information systems research, enhances the strategic contribution of HRIS by serving as a dynamic capability that enables organizations to adapt and create sustained value in evolving digital environments. HRIS effectiveness contributes to efficiency, agility, strategic responsiveness, and cost optimization in financial institutions. The findings contribute to theory by integrating IS enablers with dynamic capability mediation, enriching the RBV-DCT interplay. This study provides evidence-based insights for developing economies pursuing sustainable digital transformations. Full article

The convergence of blockchain and metaverse technologies is poised to redefine how Global Value Chains (GVCs) create, capture, and distribute value, yet scholarly insight into their joint impact remains scattered. Addressing this gap, the present study aims to clarify where, how, and under what conditions blockchain-enabled transparency and metaverse-enabled immersion enhance GVC performance. A systematic literature review (SLR), conducted according to PRISMA 2020 guidelines, screened 300 articles from ABI Global, Business Source Premier, and Web of Science records, yielding 65 peer-reviewed articles for in-depth analysis. The corpus was coded thematically and mapped against three theoretical lenses: transaction cost theory, resource-based view, and network/ecosystem perspectives. Key findings reveal the following: 1. digital twins anchored in immersive platforms reduce planning cycles by up to 30% and enable real-time, cross-border supply chain reconfiguration; 2. tokenized assets, micro-transactions, and decentralized finance (DeFi) are spawning new revenue models but simultaneously shift tax triggers and compliance burdens; 3. cross-chain protocols are critical for scalable trust, yet regulatory fragmentation—exemplified by divergent EU, U.S., and APAC rules—creates non-trivial coordination costs; and 4. traditional IB theories require extension to account for digital-capability orchestration, emerging cost centers (licensing, reserve backing, data audits), and metaverse-driven network effects. Based on these insights, this study recommends that managers adopt phased licensing and geo-aware tax engines, embed region-specific compliance flags in smart-contract metadata, and pilot digital-twin initiatives in sandbox-friendly jurisdictions. Policymakers are urged to accelerate work on interoperability and reporting standards to prevent systemic bottlenecks. Finally, researchers should pursue multi-case and longitudinal studies measuring the financial and ESG outcomes of integrated blockchain–metaverse deployments. By synthesizing disparate streams and articulating a forward agenda, this review provides a conceptual bridge for international business scholarship and a practical roadmap for firms navigating the next wave of digital GVC transformation. Full article

Amid accelerating globalization and urbanization, regional revitalization has become a key policy direction for countries to address regional decline. Among these, social capital and community empowerment can significantly promote regional development. Social capital emphasizes how trust, norms, and reciprocity facilitate collective action, while community empowerment focuses on improving residents’ participation and autonomous decision-making capacity. Existing research primarily focuses on cases from Europe and America; there is no in-depth exploration of the interaction between regional revitalization and social capital in Taiwan. Notably, systematic studies are lacking regarding the mechanisms through which University Social Responsibility (USR) programs engage and promote community development. This study takes the Wanli and Jinshan districts in northern Taiwan as case study examples. We employ action research and qualitative research methods to analyze the role of social capital and community empowerment in regional revitalization. This paper reviews how internal trust and cooperation within a community build bonding social capital. It explores how USR programs promote collaboration between communities and external resources through bridging social capital. The findings indicate that bonding social capital can enhance community cohesion and support regional revitalization efforts; bridging social capital can introduce academic, corporate, and governmental resources, providing technical and financial support for community innovation. The participatory mechanism of USR programs not only fosters civic awareness development but also offers a cross-organizational cooperation platform for regional revitalization, enabling communities to integrate internal and external resources more effectively. The results of this study indicate that bonding and bridging social capital can achieve complementary effects through USR programs, further promoting community empowerment and regional development. This study deepens the application of social capital theory in regional revitalization. It provides an empirical basis for policymakers and academic institutions to optimize the planning and implementation of future USR programs. While the study focuses on a geographically bounded set of cases and employs an exploratory qualitative design, these choices enabled a rich, context-sensitive understanding of how regional self-governance and community capital may be strengthened in practice. Future research could extend this line of inquiry by examining additional locales, adopting longitudinal perspectives, and integrating mixed-method approaches, thereby further amplifying the robustness and applicability of the propositions advanced here. Full article

The construction sector plays a pivotal role in sustainability efforts, driving the need for innovative solutions like Building Information Modeling (BIM) to optimize green building design and performance. This study examines the diffusion of BIM functionalities that support sustainability, particularly in energy efficiency, water management, material selection, indoor environmental quality, and green building certification. Using the innovation diffusion theory, the research employs three mathematical models—internal, external, and mixed—to analyze the adoption patterns of BIM for green building applications. Empirical findings reveal that external factors, such as government regulations, financial incentives, and industry trends, significantly influence the diffusion of BIM functions related to environmental performance. The mixed diffusion model demonstrates the highest explanatory power, indicating that both external and internal drivers play a role, particularly in material selection and lifecycle assessment. This study highlights the growing integration of BIM in sustainable construction, reinforcing the need for regulatory support to accelerate adoption. These findings offer valuable insights for researchers, policymakers, and industry professionals, demonstrating how BIM can drive greener practices in the built environment. Policymakers should focus on developing policies and offering incentives such as feed-in tariffs, investment tax credits, and integrating Green BIM requirements into building codes to encourage sustainable construction practices. Also, curricula should be updated to include real-world projects and experiential learning to improve the adoption and efficiency of Green BIM practices. Future research should explore enhanced digital frameworks to further improve BIM’s impact on sustainability and lifecycle optimization. Full article

This study examines the experiences of pre-service teachers (PSTs) participating in Australian state-and-territory-specific programs that address teacher workforce shortages in Australia. Using a multi-methods approach, data from surveys and interviews are used to explore the impact of these programs on PSTs’ academic outcomes, professional learning, and well-being. Situated learning theory underpins the analysis, emphasising communities of practice, legitimate peripheral participation, and self-identity development. The findings reveal significant benefits such as accelerated career growth, enhanced confidence, and the integration of theory and practice. Enablers include school mentorship, university flexibility, and financial compensation inclusive of paid teaching programs. However, challenges persist, including emotional and workload pressures, inconsistent mentorship, and ambiguous application processes. This study recommends improving policy implementation and support structures, advocating for streamlined application processes, strategic workload management, and enhanced mentorship. These findings could contribute to understanding the competing demands of PSTs and inform policy improvements for future educators. Full article

A significant portion of small and medium-sized enterprises (SMEs) are usually allocated to the construction sector, which plays a vital role in many economies. SMEs currently face serious concerns regarding the pursuit of sustainability. Limited financial resources (FRs) frequently prevent SMEs from implementing sustainable practices. Therefore, these enterprises should mitigate expenses to invest in environmentally friendly initiatives. Enhancing resources and developing ways to accelerate Turkish SMEs’ shift toward sustainability is vital. Moreover, adopting artificial intelligence (AI) and green innovation strategies (GISs) can boost sustainable competitive advantage (SCA) and lead them to success. This study utilized the natural resource-based view theory (NRBV), developed to compensate for the RBV’s shortcomings by incorporating the natural environment into the RBV’s framework. This study uses structural equation modeling (SEM) to examine the causal effect between the study variables based on the responses received from 228 executives within SMEs in Turkey’s construction sector. The findings of this study reveal that FRs significantly impact the SCA among SMEs, while GIS serves as a mediator in the relationship. Additionally, the moderating impact of AI adoption promotes sustainability development in this industry. This study is significant because it contributes to the body of knowledge regarding the relationship between the study’s constructs that align with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), presented by the United Nations in 2015. This goal promotes robust infrastructure, encourages sustainable and inclusive industrialization, and stimulates innovation in the SME construction industry. Although these variables have been studied individually in previous studies, this study integrates them into a thorough framework that emphasizes the function of GIS as a mediator in the relationship between FRs and SCA, and the interaction effect of AI adoption. This study offers useful information to managers, stakeholders, politicians, and SME leaders, enabling them to make well-informed decisions about sustainable practices. Full article

Industry 4.0 presents an opportunity to gain a competitive advantage through productivity, flexibility, and speed. It also empowers the manufacturing sector to drive the sustainability revolution to achieve net zero carbon by reducing emissions in operations. In this paper, the aim is to demonstrate a practical implementation of a smart manufacturing application using a systematic approach based on conceptual six-gear smart factory roadmap with connectivity, integration and analytics stages to build a smart production management ecosystem using off-the-shelf technologies applied in precision manufacturing. Business benefits from the smart manufacturing application implementation are realized in terms of operational performance, economic benefits, and environmental sustainability over a period of three years (before and after smart manufacturing). The productivity improves as a result of the 47% improvement made to the machines’ utilization and the 53% reduction in the total downtime waste. Economic benefits are realized in terms of a cost saving of GBP 420 K that could cost the business and the returns of the financial investment made, which is recovered within a year. An environmental sustainability impact is realized by a reduction in the total greenhouse gas (GHG) emissions by 43%, mostly due to the reduction in the Scope 2 emissions in operations by 50%, which is significantly impacted by the reduction of energy consumption and better power consumption management. The significance of this work is the bridging of the gap between theory and practice by rapidly applying the six-gear smart factory roadmap to start, scale, and sustain the implementation of smart manufacturing applications in the manufacturing industry. This roadmap can serve as a strategic framework tool for smart manufacturing implementations. The technical architecture can serve as a guide for the practical implementation of smart manufacturing applications to reduce the complexity of development. This work also bridges the gap in academia and in industry by showcasing a real-world actual business benefits realized from smart manufacturing, as well as showcasing the practical implementations, limitations, and opportunities of smart manufacturing applications in the precision manufacturing industry, all of which reduce the internal barriers and challenges facing smart manufacturing and industry 4.0 adoption. The value realized in gaining a competitive advantage and driving environmental sustainability from smart manufacturing in this study can serve as a case study for academics and for industry business leaders, digital champions, and digital lighthouses to support value creation and to drive and accelerate smart manufacturing applications, digital transformation initiatives, and industry 4.0 adoption across the value chain. Full article

With the increasing global concern for environmental protection and sustainable development, the low-carbon transformation of the manufacturing industries has become a top priority. The rapid development of green digital technology (GDT) provides new opportunities and a strong impetus for the low-carbon transformation of the manufacturing industries. Meanwhile, green credit, as an important financial tool to promote the development of the green economy, plays a key role in guiding resource allocation. In order to respond to the urgent global demand for environmental protection and sustainable development and to accelerate the pace of the low-carbon transformation of manufacturing industries, based on evolutionary game theory, this paper constructs a three-party evolutionary game model of commercial banks (CBs), digital businesses (DBs) and manufacturing industries (MIs); further subdivides the MIs into two categories of non-polluting MIs and polluting Mis; and performs a numerical simulation using Python to analyze the influence of the main parameters on the evolutionary stabilization strategy. The results of the study are as follows: (1) Changes in the interest rate of the green credit have a greater impact on the strategic evolution process of polluting MIs than non-polluting MIs. The green credit model contributes to the introduction of GDT for the low-carbon transformation by non-polluting MIs, although for polluting MIs, the model hinders, to some extent, their introduction of GDT for the low-carbon transformation. (2) Polluting MIs are more sensitive to the investment cost of introducing GDT than non-polluting MIs. When the support benefits of GDT are too low, polluting MIs are more inclined to choose independent innovation to realize the low-carbon transition. (3) Government subsidies to DBs in terms of GDT innovation are crucial to the DBs’ strategy choices. High subsidies can significantly accelerate the cooperation process between DBs and Mis. The findings reveal the challenges and opportunities faced by both non-polluting and polluting manufacturing industries in the process of the low-carbon transformation. In addition, the study provides theoretical references for the behavioral decisions of commercial banks, digital businesses, and manufacturing industries, and proposes corresponding management suggestions to promote the sustainable development of the manufacturing industries. Full article