Industry Policy Makers Research Articles

Transforming credit risk assessment: A systematic review of AI and machine learning applications

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.

Innovation capability and R&D performance of organizations: moderating role of industry–academic knowledge transfer

Purpose This study aims to examine how an organization’s innovation capability could influence research and development (R&D) performance. It also investigates if industry–academic knowledge transfer has a moderating relationship between organizational innovation capability and exploration and exploitative innovation in improving the R&D performance of the organizations. Design/methodology/approach Based on the literature and dynamic capability view, a conceptual model was developed and then validated using the partial least squares-structural equation modeling technique considering 387 responses from academicians and industry personnel. Findings The study found that industry–academic knowledge transfer has a significant moderating impact toward improving innovation capability, organizations’ R&D performance and exploration innovation. However, it has an insignificant moderating impact on improving innovation capability and exploitative innovation. Practical implications Organizational innovation capability is characterized by both exploratory and exploitative innovation. Both types of innovation support the R&D performance of an organization. Also, organizations that closely work with academic institutions could gain significant R&D knowledge from academic expertise. This study provides food for thought for the academic community as well as industry policymakers. Originality/value There are significant opportunities for academic institutions to gain practical knowledge from industry which can help them to accelerate their R&D activities. However, transferring knowledge between industry and academia has challenges related to intellectual property, patents and so on. Not much research has been conducted in this area. Thus, the proposed research model is unique and adds to the existing literature.

Influence of Artificial Intelligence on Engineering Management Decision-Making with Mediating Role of Transformational Leadership

The relationship between AI and management decision-making has received increasing attention in the literature, but the impact of AI on managerial decision-making through transformational leadership has not yet been thoroughly examined. Thus, this study investigates the impact of artificial intelligence on engineering management decision-making through transformational leadership. The participants include 385 employees drawn from manufacturing, construction, and information technology firms in Turkey. The data were processed using WarpPLS (7.0), and the estimation was conducted with the use of “partial least squares structural equation modeling (PLS-SEM)”. A positive and significant direct influence of “artificial intelligence” and “transformational leadership” on engineering management decision-making practices was demonstrated in this study, while transformational leadership was also found to have a significant mediating role in the relationship between artificial intelligence and engineering management decision-making practices. This study concluded with theoretical and practical implications for policymakers in the engineering industry by providing an integrated framework that allows for a nuanced examination of how AI impacts engineering management decision-making. It accounts for individual perceptions, leadership influences, and organizational adaptations, providing a comprehensive lens through which to analyze the complex interplay between AI technology, leadership, and decision-making processes in engineering management contexts. In addition, the findings of our study have significant implications for engineers and for governments creating standards to help preserve engineering businesses. Leaders and practitioners should research the instillation of values inherent to AI for an organization like engineering businesses to ensure that AI is being used to enable effective decision-making towards ensuring the accomplishment of their sustainable competitive advantage.

The extended theory of planned behavior in customer’s intention to visit halal hotels

Purpose This study aims to explore the application of the theory of planned behavior (TPB) in understanding Muslim consumers’ visitation motives to halal hotels. The model tests the impact of additional factors to the TPB such as religious commitment, religious-identification and information seeking behavior on consumers’ attitudes and intentions to visit Halal hotels. Design/methodology/approach Survey data was collected from 183 respondents to examine the relationships between these factors and customers’ intention to visit halal hotels. The survey participants were selected from diverse backgrounds to ensure a representative sample. Structural equation modeling was used to assess the conceptual model. Findings This study highlights the significance of attitudes shaped by subjective norms and information seeking behavior, emphasizing their influence on consumers’ inclination to visit halal hotels. In addition, the role of religious commitment is examined, shedding light on the impact of individuals’ strong faith in shaping their attitudes and behaviors toward halal hotels. Originality/value These results contribute to the existing literature on Halal consumer behavior and provide practical implications for professionals and policymakers in the hospitality industry. Understanding the factors that influence customers’ intentions to visit halal hotels can assist in developing tailored marketing strategies and creating an inclusive environment.

ANALYSIS OF MARKETING CAPABILITIES, COMPETITIVE ADVANTAGE AND ORGANIZATIONAL CULTURE IN IMPROVING SME PERFORMANCE(SMALL AND MEDIUM ENTERPRISES)

Small and Medium Enterprises (SMEs) face significant challenges in maintaining performance amidst increasingly tight market competition, especially in utilizing marketing capabilities, competitive advantages, and organizational culture. This study aims to explore the impact of investment in training and technology, participation in industry conferences, and collaboration with technology partners on SME performance. Qualitative research methods were used, including in-depth interviews and thematic analysis, to identify key factors influencing the success of these strategies. The results show that investments in training and technology significantly increase employee competency and technology adoption, while participation in technology conferences and collaborations expands innovation opportunities and market access. The implications of these findings underscore the importance of an integrative approach that combines training, technology and strategic partnerships to enhance the competitiveness and long-term success of SMEs. This research provides new contributions to the SME management literature as well as practical recommendations for industry players and policy makers.

Unlocking the potential: Insights from industry on barriers, solutions and policy gaps in Ireland's energy storage sector

The energy storage sector across Europe faces many financial, regulatory and policy barriers which has to date hindered development in many countries. This study documents industry perspectives from Ireland, a country which requires a significant increase in the development of energy storage due to security of supply concerns, its isolation from Europe’s central transmission network and its reliance on wind energy as a primary intermittent renewable energy resource. Using focus groups and a survey with the renewable energy and storage sector, we document perspectives on the critical barriers, innovative solutions and policy gaps identified by industry stakeholders and policy makers. Our participants believe energy storage will play a crucial role in unlocking Ireland’s substantial wind energy potential in order to meet its energy security and climate aspirations. However, our respondents suggest that unlocking this potential will require a coherent national energy storage strategy designed to reduce curtailment, identify storage technologies with duration-specific targets and establish a more comprehensive renewable energy plus storage power procurement mechanism designed for the Irish market which supports the grid, rewards low carbon technologies and reduces emissions.

Compliance to building thermal envelope insulation requirements based on theory of planned behavior (TPB) and procedural justice theory (PJT)

The construction industry plays a crucial role in achieving sustainable development, particularly in the context of energy conservation. addressing the building's optimized energy efficiency is essential, as it accounts for a significant portion of global energy consumption. While many countries have implemented policies related to building energy conservation, the lack of compliance with relevant regulations remains a challenge. However, voluntary self-regulated compliance can be encouraged through flexible approaches that leverage normative influence and equitable governance attributes within the regulatory system. This study evaluates the building contractors' intention to comply with the Building Thermal Envelope Insulation Requirements (BTE-IR), a critical energy conservation measure for buildings. An integrative model combining the Procedural Justice Theory (PJT) and the Theory of Planned Behavior (TPB) was developed to quantitatively investigate individual and social factors influencing compliance with BTE-IR. The study analyzed a sample of 214 Iranian building contractors using Partial Least Squares Structural Equations Modeling (PLS-SEM). The core findings revealed that subjective norms (β = 0.330, p < 0.01) and perceived behavioral control (β = 0.337, p < 0.01) significantly influence intention to comply with BTE-IR. Additionally, the study explored the moderating effects of job satisfaction, job commitment, years of experience, project experience and marital status on the relationships between variables in the research model. These findings can inform construction industry policymakers in developing optimized strategies for self-regulated compliance with BTE-IR and legitimizing the regulatory system for enforcing sustainable practices.

Unlocking Customer Loyalty in Indonesian Local Coffee Shops: An In-depth Analysis of The Influential Factors

Research aims: The purpose of this study is to investigate and assess the impact of various factors on customer loyalty within Indonesian local coffee shops. Specifically, the research aims to explore how value co-creation, product quality, store ambiance, and service quality influence consumer satisfaction. Additionally, the study will examine the relationships among switching costs, customer loyalty, and trust, as well as the mechanisms by which switching costs and trust affect loyalty through the mediating role of satisfaction. Through this comprehensive analysis, the study seeks to provide insights into the dynamics of customer loyalty in the coffee shop industry.Design/Methodology/Approach: In this study, the main quantitative research method was cross-sectional surveys. The hypotheses were assessed using SEM-PLS and Smart PLS.Research findings: The research findings provide valuable insights related to the factors that influence consumer loyalty in the local coffee shop industry in Indonesia, emphasizing the importance of customer satisfaction, switching costs, trust, and the role of mediating factors in fostering long-term loyalty among customersTheoretical Contribution/Originality: The theoretical contribution and originality of the study lie in its exploration of value co-creation, mediating factors, empirical analysis techniques, localized context, and practical implications within the context of consumer loyalty in local coffee shops in Indonesia. These aspects contribute to advancing knowledge in the field of consumer behavior and loyalty within the coffee shop industry.Practitioners/Policy Implications: By implementing these practical implications, practitioners and policymakers in the coffee shop industry can enhance customer satisfaction, build loyalty, and create a competitive advantage in the market. These recommendations aim to improve customer experiences, strengthen relationships, and drive business growth in the local coffee shop sector in Indonesia.Research Limitations/Implications: The research model may have limitations in capturing the full complexity of customer loyalty dynamics. Including additional variables or exploring different theoretical frameworks could provide a more comprehensive understanding of the factors influencing loyalty.

Substitution effect of Asian economies on China’s industrial and supply chains: from the perspective of global production network

This paper views China Production Network (CPN) as an integral component of the Global Production Network (GPN) and constructs null model (GIVCBN-I model) and the counterfactual model (GIVCBN-II or GIVCBN-III model) to identify and measure the potential industrial relocation risk exposure of CPN based on the Multi-Regional Input-Output (MRIO) table. The main findings are as follows. Firstly, Altasia will induce more of China’s industrial and supply chains to break compared with ASEAN, which also means that strong industrial complementarity exists between Japan, South Korea, India, Bangladesh and the ASEAN member countries, enabling Altasia to have a more significant substitution effect on China. Secondly, the counterfactual models’ network-level characteristic indicators are worse than those of the null model in economic terms, suggesting that removing trade barriers for intermediate goods within Altasia could lead to the decoupling of industrial sectors in the CPN, thereby accelerating the trend of China’s industrial and supply chains relocating offshore. Thirdly, according to the comparison results of node-level characteristic indicators, Altasia has weakened China’s influence scope, profitability, and robustness of risk within the global industrial and supply chains, but mainly concentrating on its resource-intensive and labor-intensive sectors rather than capital-intensive and technology-intensive sectors, which indicates that some China’s industrial sectors still maintain substantial competitive advantages in the GPN. In sum, this paper provides theoretical guidance for identifying and analyzing the trends of industrial relocation in the Asia-Pacific region and helps industrial policymakers deepen the understanding of regional economic integration and its impact.

The role of tourism entrepreneurial ecosystems to support sales growth of European countries

PurposeOur comprehensive study, which is highly relevant to the current state of the tourism industry, investigated the extensive impact of tourism entrepreneurial ecosystems (TEE) on sales growth in European countries based on a sample of 109 entrepreneurs.Design/methodology/approachWe studied 109 entrepreneurs in the tourism sector in Germany and France and analyzed the data using quantitative methods.FindingsThe results showed that financing and funding, networks, technological and international trade affect the sales growth of the tourism entrepreneurs. In addition, the uneducated workforce, legal and political factors as well as TEE do not influence the sales growth.Originality/valueThese findings have significant and practical implications for entrepreneurs and policymakers in the tourism industry, providing them with valuable insights for decision-making.

Some Aspects and Convergence of Human and Veterinary Drug Repositioning.

Drug innovation traditionally follows a de novo approach with new molecules through a complex preclinical and clinical pathway. In addition to this strategy, drug repositioning has also become an important complementary approach, which can be shorter, cheaper, and less risky. This review provides an overview of drug innovation in both human and veterinary medicine, with a focus on drug repositioning. The evolution of drug repositioning and the effectiveness of this approach are presented, including the growing role of data science and computational modeling methods in identifying drugs with potential for repositioning. Certain business aspects of drug innovation, especially the relevant factors of market exclusivity, are also discussed. Despite the promising potential of drug repositioning for innovation, it remains underutilized, especially in veterinary applications. To change this landscape for mutual benefits of human and veterinary drug innovation, further exploitation of the potency of drug repositioning is necessary through closer cooperation between all stakeholders, academia, industry, pharmaceutical authorities, and innovation policy makers, and the integration of human and veterinary repositioning into a unified innovation space. For this purpose, the establishment of the conceptually new "One Health Drug Repositioning Platform" is proposed. Oncology is one of the disease areas where this platform can significantly support the development of new drugs for human and dog (or other companion animals) anticancer therapies. As an example of the utilization of human and veterinary drugs for veterinary repositioning, the use of COX inhibitors to treat dog cancers is reviewed.

Understanding the drivers of innovative work behaviour among millennial employees in India’s IT sector: some exploratory research findings

PurposeThe study aims to develop a hierarchical model for innovative work behaviour (IWB) that can capture the complex associations among the factors contributing to IWB within the information technology (IT) sector. To accomplish this, the authors rely on an abductive approach using a graph theoretic model, often called interpretive structural modelling (ISM).Design/methodology/approachAfter conducting an in-depth literature review and using the Delphi method, the authors identified 12 factors (11 enablers and IWB as an outcome). The authors collected data through the Delphi approach by sending the questionnaire to 11 experts from academia and the IT sector who have extensive experience and knowledge relevant to the study. The authors then used the ISM method to analyse the relationships among these factors and understand their driving forces.FindingsBased on the ISM model and the Matrice d'Impacts Croisés Multiplication Appliquée à un Classement analysis, the authors have identified that inclusive leadership, proactive personality and knowledge creation ability are the variables with strong driving power but weak dependence. Conversely, IWB has strong dependence but weak driving power. These findings suggest that to foster IWB, the organisation should prioritise inclusive leadership, proactive personality and knowledge-creation ability to succeed in challenging times. The study’s findings contribute to the social exchange theory, which explains IWB in a dynamic setting. Additionally, the study helps address the significant concerns that most IT companies face during times of crisis.Practical implicationsThe study provides valuable guidance for managers and policymakers who are grappling with the challenges of improving IWB in the IT sector. This study is particularly relevant as the industry is currently navigating an economic recession and facing intense competition from other tech companies launching new products and services.Originality/valueThis research holds great significance for top executives, line managers and policymakers in the IT industry. It sheds light on the relevance and importance of various factors facilitating millennials' IWB.

Analisis Implementasi Pendidikan dan Pelatihan Human Capital di Industri Kreatif

Creative industries play an important role in the global economy, and the development of high-quality human resources is essential to drive innovation and productivity. The purpose of this study is to analyze the status of the implementation of human resource development and training in the creative industry. Using a qualitative approach, data was collected through in-depth interviews with industry players, academics, and policy makers, as well as analysis of related documents. The results showed that the combination of formal and non-formal education, cooperation between industry and educational institutions, and the use of modern technology play an important role in the development of human resources. Although formal education provides a solid theoretical foundation, non-formal education and technologies such as e-learning and VR can help improve certain practical skills according to market needs. . Collaboration between industry and educational institutions ensures relevant curricula and valuable practical experience for learners. Despite challenges such as limited resources and rapid technological change, effective education and training can enhance the competitiveness and growth of creative industries.

Determinants and Outcomes of Green Technology Innovation Adoption among Third-Party Logistics Firms in China: A SEM-ANN Analysis

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.

A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems

The increasing density of urban populations has spurred interest in utilizing underground space. Underground logistics systems (ULS) are gaining traction due to their effective utilization of this space to enhance urban spatial efficiency. However, research on technological advancements in related fields remains limited. To address this gap, we applied a data-driven approach using patent data related to the ULS to develop a technology roadmap for the field. We employed Latent Dirichlet Allocation (LDA), a machine learning-based topic modeling technique, to categorize and identify six specific technology areas within the ULS domain. Subsequently, we conducted portfolio analytics to pinpoint technology areas with high technological value and to identify the major patent applicants in these areas. Finally, we assessed the technology market potential by mapping the technology life cycle for the identified high-value areas. Among the six technology areas identified, Topic 1 (Underground Material Handling System) and Topic 4 (Underground Transportation System) showed significant patent activity from companies and research institutions in China, the United States, South Korea, and Germany compared to other countries. These areas have the top 10 patent applicants, accounting for 20.8% and 13.6% of all patent applications, respectively. Additionally, technology life cycle analytics revealed a growth trajectory for these identified areas, indicating their rapid expansion and high innovation potential. This study provides a data-driven methodology to develop a technology roadmap that offers valuable insights for researchers, engineers, and policymakers in the ULS industry and supports informed decision-making regarding the field’s future direction.

Examining the Impact of Influencers and Bloggers on Behavioral Intentions among Youth in Sindh Pakistan

This study examines the impact of attitude, social media influencers, electronic word of mouth (e-WOM) and credibility on behavioral intention among youth. An online survey was distributed with the help of an adapted questionnaire from past studies. A total of 200 cases were considered in this study, and reliability analysis and regression analysis were performed in SPSS version 25. The findings revealed that all variables of attitude, social media influencers, and electronic word of mouth (e-WOM) positively and significantly impact behavioral intention. However, the attitude was found to have a more significant impact on the behavior of the youth of Pakistan due to higher beta values than the dependent variables. Therefore, policymakers in the textile industry can consider these variables in the future.

Exploring Customer Trust and Online Continuance Shopping Intention of Cosmetics, with Mediating Effect of Perceived Risk

Purpose This study aims to explore the relationship between customer trust, perceived risk, and online continuance shopping intention in the cosmetics industry. It focuses on understanding the direct impact of customer trust on shopping intention and the mediating role of perceived risk. The research provides insights to help marketers and policymakers enhance consumer trust and mitigate perceived risks in online shopping. Theoretical Framework This study's theoretical framework is based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). It extends these models by including customer trust and perceived risk as key factors influencing online continuance shopping intention in the cosmetics industry. Methodology The study employs a Partial Least Squares (PLS) approach for Structural Equation Modelling (SEM) to analyze the relationships between customer trust, perceived risk, and online continuance shopping intention. Findings The study reveals that customer trust significantly boosts online continuance shopping intention, encouraging repeat purchases. Perceived risk partially mediates this relationship, meaning while trust reduces perceived risk, the presence of risk still negatively impacts the intention to continue shopping online. The path coefficients quantify these relationships, highlighting the strength and significance of both direct and indirect effects. Implication For marketers and policymakers in the online cosmetics industry, the study suggests that building customer trust through transparent communication, reliable service, and secure payments is crucial for fostering repeat purchases. Additionally, reducing perceived risks with clear return policies, product guarantees, and data protection measures can alleviate customer concerns.

Impact of health tourism visitor experiences on behavioral intention

PurposeThis paper examines the factors that influence behavioral intention in the context of medical tourism in Türkiye. With the growing popularity of Türkiye as a destination for medical tourism, it is essential to understand the key determinants influencing individuals’ intention to engage in medical tourism activities.Design/methodology/approachThis study used the Extended Theory of Planned Behavior (E-PBT) variables, which include attitude, subjective norm and perceived behavioral control, to measure their influence on behavioral intention. In addition, a customer experience scale was used to assess the influence of dimensions such as education, entertainment, aesthetics and escapism on behavioral intention. The research instrument was validated by expert review, and data were collected using purposive sampling. A total of 420 surveys were deemed suitable for analysis.FindingsThe path analysis revealed that attitudes and perceived behavioral control positively impacted behavioral intention within the domain of medical tourism in Türkiye. Conversely, subjective norms did not have a significant positive effect on behavioral intention. Furthermore, it was observed that the dimensions of entertainment, escape and aesthetics positively affected behavioral intention. However, education and aesthetics did not significantly influence behavioral intentions.Practical implicationsThe results of this paper have practical implications for marketers and policymakers in the medical tourism industry in Türkiye. Understanding the factors that drive individuals’ behavioral intentions can assist in developing effective marketing strategies to attract and serve potential medical tourists. Medical tourism providers can enhance their services by optimizing attitudes and perceived behavioral control while emphasizing entertainment and escapism for their clientele.Originality/valueThis research focuses on uncovering factors influencing individuals’ behavioral intentions in medical tourism in Türkiye. Using the E-PBT framework and exploring the dimensions of the customer experience scale, this study aimed to understand the driving forces behind individuals’ decisions to engage in medical tourism.

Strategies of Green Industrial Policy: How States Position Firms in Global Supply Chains

The resurgence of industrial policymaking—particularly for emerging low-carbon industries—challenges social science theories that expect such interventions from centralized states or suggest that different kinds of states specialize in various forms of innovation policy. Interventionist forms of industrial policy have made a comeback among liberal economies. Coordinated economies now make use of market-driven strategies. This paper argues that the new generation of industrial strategies is shaped by the industrial development challenges that policymakers face at the sectoral level. It proposes a new theoretical framework that distinguishes between the policy orientation (targeted or open-ended) and the central agents driving financial and technological decision-making (governments or firms). We show that the choice of strategy is shaped by the level of uncertainty and the position of the domestic industry in global supply chains, that is, whether global supply chains are emerging or mature and whether the domestic industry is an entrant or incumbent.

Hospitality customer intentions to write fake online reviews: A cross-cultural approach

This paper examines the antecedents and consequences of customer intentions to write fake online reviews on Agoda.com as a case in the hospitality context. Brand nostalgia, brand strength, moral attitude, review-related skepticism, and perceived unfairness were represented as antecedents of customer intentions, while boycott behavior, willingness to pay a price premium, and customer satisfaction were represented as consequences of their intentions. Data was gathered using a structured survey from 373 Italian, 440 French, and 392 British customers. Findings present significant insights into customer intentions to write fake online reviews. In addition, multi-group analysis highlights the differences among nationalities. This paper provides valuable insights for industry professionals and policymakers in the hospitality industry.