EuroMid Journal of Business and Tech-Innovation (EJBTI)

Review of Logistics Challenges within the Construction Industry

2025-05-08T19:11:44+00:00

This study offers a comprehensive analysis of logistics functions in the construction industry and the challenges that affect project performance. In contrast to prior studies emphasizing logistics solutions, this study concentrates on identifying the challenges impeding efficient logistics management, which frequently result in delays and cost overruns. The study reviews 40 knowledge sources through a critical literature review to identify key logistics functions and their associated challenges. The logistics functions and associated challenges in the construction industry are categorized and analyzed through a systematic review of the literature. The study identifies six major logistics functions: planning and resource allocation, communication and coordination, materials management, inventory management and warehousing, transportation, and reverse logistics. Each function is associated with specific challenges, such as poor integration with suppliers and a lack of clarity regarding responsibilities in communication and coordination. By highlighting these challenges, the study aims to improve construction performance and address a gap in the existing literature, which often prioritizes solutions over the identification of underlying logistical issues. The findings offer a valuable foundation for researchers to further investigate these challenges and formulate targeted solutions and mitigation strategies, ultimately contributing to improved productivity and cost management in the construction sector.

Value-Belief-Norm Theory and Ethical Investment Behavior: A Gender-Based Analysis from Bengaluru

2025-04-09T18:11:58+00:00

This study applies the Value-Belief-Norm (VBN) theory to examine how investors’ ethical investment decisions are shaped by personal values, beliefs, and social norms. With growing attention to Environmental, Social, and Governance (ESG) and Socially Responsible Investing (SRI), the research investigates the psychological determinants of ethical investing, including whether perceptions differ by gender. Primary data were collected through a structured questionnaire distributed via snowball sampling to 100 investors in Bengaluru, India. The findings reveal significant positive correlations among values, beliefs, norms, and ethical investment behaviour, thereby confirming the applicability of the VBN framework in this context. However, independent samples t-tests show no statistically significant gender differences in perception, suggesting that ethical investment behaviour is influenced more by internalized moral and normative factors than by demographic attributes. The study contributes to behavioural finance literature by offering insights into the psychosocial underpinnings of ethical investing in an emerging economy setting.

Meta-Brand Engagement and Willingness to Buy: Exploring the Pre-Adoption Behavior on Emerging Digital Platforms

2025-04-09T10:32:13+00:00

This study investigates the impact of meta-brand engagement on consumers’ willingness to buy in the Metaverse. Adopting a quantitative, cross-sectional research design, data were collected through an online survey from 300 active Metaverse users, selected via purposive sampling to ensure relevance. Validated instruments measured various dimensions of meta-brand engagement and willingness to buy. The analysis employed both correlation and multiple regression techniques to test five hypotheses concerning these relationships. The results revealed that brand awareness and knowledge, as well as emotional and psychological factors, have a positive and significant influence on willingness to buy. Conversely, social and incentive factors exhibit a significant negative effect. The remaining factors—brand interaction and engagement and perceived value and experience—were not found to have a significant impact. These findings offer valuable insights into how meta-brand interactions shape consumer decision-making in virtual environments, providing actionable implications for marketers aiming to refine branding strategies within the Metaverse and deepen their understanding of virtual consumer behavior.

The Impact of Using Artificial Intelligence Applications on Reducing the Default Risk in MSMEs

2025-04-05T14:56:36+00:00

This study investigates the impact of artificial intelligence (AI) applications on reducing default risk in micro, small, and medium enterprises (MSMEs), with the aim of ensuring financial sustainability. By focusing on 450 MSMEs located in the North Al Batinah Governorate of the Sultanate of Oman, the research uses a regression model and various statistical tests to examine the relationship between AI adoption and default risk. The findings indicate that the use of AI is the most influential factor in mitigating default risk, highlighting the importance of encouraging AI adoption among MSMEs. Additionally, the perspectives of MSME owners play a significant role, suggesting that raising awareness of AI's benefits in credit risk management is essential. The study is limited to a specific region in Oman but offers valuable insights into the challenges and benefits of AI implementation in MSMEs. It recommends initiatives to shift the mindset of MSME owners toward embracing AI, as well as policies to support investment in AI tools to strengthen credit risk assessment and prevent financial distress. This research contributes to the growing body of knowledge by demonstrating how AI can reduce default rates and improve repayment performance, ultimately supporting the financial sustainability of MSMEs.

Stress and Job Satisfaction in Peruvian Public Officials: Engagement as a Mediating Factor

2025-04-02T20:53:24+00:00

This study investigates the mediating role of work engagement in the relationship between job stress and job satisfaction among employees in Peruvian public institutions. Using a quantitative, non-experimental, and cross-sectional design, data were collected via a five-point Likert scale survey administered to 144 staff members of the National Superintendency of Public Registries (SUNARP). Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to assess the measurement and structural models. Results indicate that work engagement significantly mediates the relationship between job stress and job satisfaction. Specifically, job stress negatively influences work engagement (path coefficient = –0.726), while work engagement positively predicts job satisfaction (0.762). A direct negative relationship was also observed between job stress and job satisfaction (–0.103). These findings underscore the importance of fostering employee engagement to mitigate the adverse effects of occupational stress and enhance satisfaction in the public sector context.