The main objective of this research is to identify the impact of store design and ambience on consumer purchase decisions in retail chain outlets in Delhi-NCR, India. The foremost purpose of this research was to examine if the design and ambience of retail stores have any effect on the decisions of customers’ purchases. The study was descriptive in nature. For this research, a sample of 100 consumers was drawn who generally visit retail stores for shopping. A systematic questionnaire was prepared to collect the data and to analyze it; SEM, reliability, Convergent, Discriminate Validity and model fitness were achieved through SmartPLS3. The current study’s findings indicate that variables, such as window and mannequin display, visual merchandising, and store design and atmosphere have an effective impact on shoppers’ purchase decisions, whereas lighting and color, music, and signage have negligible effects. The findings of this study will provide managerial involvement to the industry in order to emphasize purchase ambition in order to improve profitability and sustainability. More examination of the factors that contribute to purchase aspiration and in other geological areas is advised for future scrutiny. This study presents a validated instrument for measuring the association between design atmosphere and consumer purchasing behavior and serves as a tool for evaluating the influence of various design atmospheric indicators. It is important to keep a steady staff of well-trained, polite salespeople on hand at all times. Customers are more likely to come back and eventually recommend the store to others if their needs are met by customer-focused salespeople who provide excellent service. This helps the merchant to compete in the market.

Social networking influencers are those who use images, videos, and other updates on social media platforms to affect consumers’ impressions of a company or product. The purpose of this study is to assess the present status of social networking sites and the online purchase intentions of consumers. This research paper is an attempt to identify the effect of various attributes of social networking that influence credibility and brand image, eventually leading to the purchase intention of consumers in Delhi NCR (National Capital Region), India. The data were collected using Google Forms via an online questionnaire with a sample size of 262 respondents. A convenient sampling technique was used; structure equation modeling (SEM), convergent and discriminant validity, and model fitness were achieved through Smart PLS 3. This study’s findings reveal that expertise, information quality, and trustworthiness have significant positive effects on credibility and brand image, as well as a significant positive indirect effect on online purchase intention. Other factors, such as entertainment, attractiveness, and likability, have no significant effect on credibility and brand image. The credibility of social networking and brand image mediate the positive relationship between information quality, expertise, trustworthiness, and consumer online purchase intention. On the other hand, the credibility of social networking and brand image mediate the lack of a positive relationship between likability, attractiveness, entertainment, and consumer online purchase intention.

Artificial intelligence (AI) systems have emerged as a powerful tool for management decision-making. However, there is a lack of a comprehensive framework that aims to bridge the gap between AI systems and human decision-makers. The proposed approach provides a novel framework, stepping towards the enhancement of AI-human communication with real-time feedback, iterative refinements, and user-centric interface designs. The framework is based on design principles of modularity, scalability, user-centricity, and adaptability, which were conceptualized to make it robust, flexible, and highly effective. Finally, it is expected that the indicated case studies and application scenarios will show the applicability and effectiveness of the framework in different contexts of industry, and therefore, provide concrete examples of how the benefits of the framework might be in practice. Simulation results show that the proposed mechanism has been significantly adopted, demonstrating a 10-20% increase in efficiency, user satisfaction, and feedback responsiveness compared to the existing mechanisms such as EHIDM and HCADMR. These results underscore the potential of the proposed framework to significantly enhance interaction dynamics between AI systems and human users.

Background/Objectives: Vision 2030 of Saudi Arabia is an important project that mainly targets the reduction in dependency on the oil economy through the growth of non-oil Industries. This study investigates Saudi Arabia’s effort for Vision 2030 to incentivise investment in the non-oil industry’s growth. Material and Methods:A sample of 225 employees of the non-oil industries of Saudi Arabia was selected as sample participants. A survey was conducted for data collection, and SPSS software was used to analyse the data. Findings:The findings indicate that sig values for all tests were 0.000 < 0.05 to support the selection of an alternative hypothesis. Therefore, it can easily be determined from the analysis that a more robust relationship is present between Vision 2030 with incentivised investment, economic stability, and financial accommodation.The advantages of reform programs have been effective in non-oil industries of Saudi Arabia to increase production standards and obtain more customer engagement.Conclusion: This research contributes to providing a straightforward concept in Vision 2030, which is Saudi Arabia’s reform program to develop the economic condition of Non-Oil Sectors. Hence, reform in the policy for economic stability can help to maintain the growth of different sectors and can further support financial assets.

This study examines associations among perceived political ideology, local stakeholder reactions, liability of foreignness, and perceived foreign direct investment (FDI) risk in India. Drawing on survey responses from 312 managers and executives, the study employs covariance-based structural equation modelling to assess theoretically specified direct and indirect relationships. The reported structural estimates indicate positive associations between perceived political hostility toward foreign investment and stakeholder resistance, liability of foreignness, and perceived FDI risk. Liability of foreignness is positively associated with perceived risk, whereas stakeholder resistance exhibits an unexpected negative association, contrary to the hypothesized direction. The findings highlight the relevance of managerial perceptions of political conditions and foreignness-related disadvantages to perceived investment risk. The cross-sectional, single-source design limits causal interpretation, while the negative stakeholder association requires further investigation.

This study investigates the organizational drivers of sustainability performance in the manufacturing sector and proposes and tests an integrated model grounded in dynamic capability theory. Using structural equation modeling on empirical data, it examines the role of digital leadership as a catalyst for sustainable practices, mediated by digital knowledge management and organizational resilience. The findings confirm that digital leadership exerts a significant total effect on sustainability outcomes. Crucially, this influence is primarily channeled through two parallel mediating pathways: by building organizational resilience and by establishing systematic digital knowledge management. The model demonstrates high explanatory power, revealing that sustainability performance is a systemic achievement, dependent on the synergistic interaction of strategic leadership, institutionalized learning, and adaptive capacity.