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The article examines the impact of implementing automated construction project management systems on the operational efficiency of construction companies under conditions of managerial digitalization. It analyzes the comprehensive effect of digital platforms on schedule compliance, cost control, and organizational manageability. The study emphasizes that the digital transformation of project management contributes to the reduction of time and financial losses, enhances the predictability of outcomes, and increases the resilience of project portfolios. Based on the synthesis of peer-reviewed empirical studies and industry case reports, this study demonstrates that the implementation of automated construction project management systems is consistently associated with improvements in schedule adherence, cost control, and organizational efficiency. The article presents a structured approach to evaluating digitalization effects using normalized performance indicators, highlighting that management automation is not merely a technological upgrade but a tool for systemic economic optimization of construction company operations.

Skill gap analysis is becoming more and more accepted as an important strategy tool for managing people well, especially in small and medium-sized IT businesses that are always changing. This study looks at how skill gap analysis affects some of the most important parts of people management, such as hiring, teaching, developing, and keeping employees. The study uses a variety of methods, including a literature review, polls, and case studies of Indian small and medium-sized businesses in the IT sector. It discovers that companies that use skill gap analysis have better worker harmony, lower employee loss, and higher employee output. The paper tells small business leaders how to include skill evaluation in their plans for hiring people. Tamil Nadu’s small and medium-sized IT businesses (SMEs) are very important to the state’s technological progress. But these groups often have trouble finding people with the right skills, which slows their growth and makes them less competitive. Skill gap analysis is becoming a useful strategy tool for finding and fixing these problems, which makes people management better. This piece goes into detail about how important skill gap analysis is for Tamil Nadu’s IT SMEs. It looks at the role it plays in developing the workforce, the problems that come up, and the steps that are being taken to fix these problems.

This research examines how explainable machine learning (XAI) techniques can identify and measure churn risk factors in India’s quick-commerce delivery platforms. Unlike prior studies focused on prediction accuracy, this work emphasises interpretability to ease practical business interventions. Utilizing Blinkit’s operational data, which shows a 47.35% churn rate, the study employs an ensemble method integrating Random Forests, Gradient Boosting, and SHAP analysis to break down churn drivers. The method introduces the Quick-Commerce Customer Stability Index (QCCSI), a composite measure integrating delivery reliability metrics (35%), support interaction quality (25%), engagement frequency (20%), and account tenure dynamics (20%). Analysis of 15,000+ customer transaction sequences reveal that delivery consistency (coefficient:
-0.68, p<0.001) and unresolved support queries (hazard ratio: 2.14) are the strongest predictors of churn. Critically, this study finds that customer dissatisfaction appears not from single failure events but from accumulated friction points. A three-point increase in QCCSI correlates with a 31.7% reduction in 90-day churn probability. Implementation of the proposed early warning system could preserve ₹142 million in annualized revenue for mid-market operators with 100,000 active users.

Social media is currently emerging as a simple way to easily connect, significantly reduce work off to determine one’s destinations, and this has changed the way information is passed and how tourists make decisions. Although its involvement has been increasing, the incorporation of the recent trends of social media in destination marketing is not fully integrated. So, in the current research is based on the gap in synthesis of current research because the recent studies have failed to synthesize their findings on changing social media practices in destination marketing. Google scholar was used to obtain data used to conduct a systematic literature review of studies published between 2016 and 2025. Totally 43 articles were chosen using a rigorous screening process and analyzed using NVivo 15 to derive thematic information in social media in destination marketing outcomes in the tourism industry. The most widely used platforms are Facebook, Instagram, Tik Tok, and YouTube, where the main focus is on user-carbonated content, influencer marketing, and sophisticated analytics. The strategies enhance the destination familiarity, create emotional attachment and enhance the loyalty and behavior intention of the tourists. The findings provide valuable suggestions to destination marketing agencies and tourism managers on adopting dynamic and technology-oriented practices.

Artificial Intelligence (AI) is reshaping financial decision-making by providing affordable, automated, and personalized tools that can support both individual investors and micro, small, and medium enterprises (MSMEs). This study examines perceptions of AI-driven financial platforms with emphasis on awareness, trust, and concerns among 100 respondents from Tamil Nadu, India. The analysis, based on descriptive design and supported by ANOVA and factor analysis, revealed that men reported greater confidence and willingness to use AI-based investment services, while women showed stronger concerns about privacy and reliability. Three underlying dimensions were identified: familiarity and preference for AI tools, perceived benefits and risks, and belief in AI’s ability to replace human advisors. Findings highlight that while AI can democratize financial access, adoption depends largely on user trust and gender-specific comfort levels. For MSMEs and entrepreneurs, AI-enabled financial literacy, transparent data practices, and hybrid human–AI advisory systems are essential for inclusive and responsible usage.

The new era of commerce defined as commerce 2.0 is characterized by advanced technologies such as AI, social media integration, sophisticated payment systems like UPI and other digital commerce aspects. These innovations have transformed consumer behavior for younger generations while the perceptions of older adults remain unexplored. This research aims to understand the attitudes, awareness, and experiences towards commerce 2.0 by individuals above the age of 50. The study investigates the factors influencing their perceptions, including usability, security, and trust. The data has been collected from 70 elder people through structured questionnaires and taken into consideration for an accurate outcome. The questionnaire assesses their familiarity with commerce 2.0, usage of online platforms, their views on the security and privacy of digital payments, and their opinions on the role of AI in personalized shopping. The study also identifies key barriers to adoption, such as a lack of technical knowledge and security concerns, alongside perceived benefits like convenience and accessibility. The findings provide insights into generational differences in technology adoption, highlight barriers faced by elder consumers, and suggests strategies for creating more inclusive and user-friendly digital commerce ecosystems

The Indian paint industry has consistently experienced double-digit growth over the past five years, making it a standout segment in the chemical industry. This study examines the marketing strategies of paint products, focusing on consumer satisfaction, brand image, reputation, and loyalty. The research aims to provide valuable insights for marketing professionals by identifying key factors that influence customer satisfaction, repurchase decisions, and brand recommendations. By analyzing both primary and secondary data, this exploratory study assesses the effectiveness of current marketing strategies in the paint industry and suggests improvements. The findings indicate that the rapid growth in paint usage can be attributed to effective advertising and increasing consumer awareness of product quality.

This empirical study explores the linkage between employee training. Job satisfaction, and job performance using data from 170 employees. Structural Equation Modelling (SEM) through AMOS software validates the measurement model and examines hypothesized relationships. The model shows an excellent fit (X2 /df =1.314, CFI= .987, TLI= .984, RMSEA= .043). Results reveal that training significantly influences job performance both directly and indirectly, with job satisfaction mediating the effect. All constructs demonstrate strong reliability, validity, consistency, reinforcing the theoretical framework that effective training and satisfaction improve performance. This study provides valuable insights for HR development, organization behaviour and performance management research.

The purpose of this study is to develop and test an architecture for Supply Chain Management Practices (SCMP) that takes into account delay, levels of information flow, and strategic supplier alliances. To find out how these traits impact the performance of manufacturing firms (MFP), the study uses linear regression, ANOVA, and Pearson correlation to examine data from 100 top executives in Andhra Pradesh manufacturing organisations.
Results show that sharing knowledge improves MFP, while delay and strategic supplier agreements don’t help at all. Importantly, the study indicated that higher SCMP levels boost firm and supply chain performance; this is helpful information for SCM evaluations by supply chain managers.
The findings of this pioneering study on supply chain management (SCM) in the manufacturing sector of Andhra Pradesh have important consequences for developing nations. Because growing the manufacturing sector and associated supply chains is essential to a flourishing economy, the results of this study couldn’t be more relevant

The banking sector in India has undergone rapid transformation, shaped by regulatory reforms, technological adoption, and shifting customer expectations. Understanding the factors that guide consumers in choosing between public and private sector banks is essential for improving service strategies and sustaining competitiveness. This study investigates key determinants influencing customer bank selection in Haryana, using data from 592 respondents. Six major factors were assessed: customer service, technology and innovation, product variety, efficiency and speed, brand image and marketing, and convenience and comfort. One-sample statistics and one-sample t-tests were applied to evaluate whether customer perceptions differed significantly from a neutral benchmark. The findings indicate that efficiency and speed, along with brand image and marketing, are the most influential determinants of bank preference. Customer service and convenience also significantly shape decision-making. In contrast, technology and innovation and product variety do not show significant deviation from the test value, suggesting these factors hold comparatively less weight for customers in this region. The study contributes to the understanding of consumer banking behavior in India and offers insights for banks seeking to enhance customer engagement and strengthen their competitive position