Volume 7 Issue 6 Nov-Dec 2025

As crypto exchanges and decentralized exchanges have proven untrustworthy, this paper seeks to create a rigorous Blockchain Project Evaluation Model (BPEM) for assessing the trustworthiness of a blockchain project. This BPEM will collate the components of technical audit, on-chain and off-chain analytics, liquidity indicators, and behavioral indicators into a single score of the project. The relevance of this work is driven by widespread instances of trade volume manipulation, opaque tokenomics, and tightening regulatory requirements (including in the context of MiCA). The scientific novelty lies in the creation of a hybrid MCDM architecture with an automated Incongruity Detection System (IDS) module that cross-checks tokenomics, liquidity, on-chain activity, and public statements and introduces a penalty coefficient into the final rating. The results of BPEM validation across case studies of wash trading and hidden centralization demonstrate that the key indicators of project resilience are not nominal volume but market depth, liquidity quality, and the integrity of on-chain data, and that identified inconsistencies act as early markers of scam projects and systemic risks. It is shown that a comprehensive multifactor analysis significantly outperforms the use of isolated metrics and can serve as a backbone for listing and compliance procedures. The article is of practical value for researchers of decentralized finance, risk managers, crypto exchange analysts, and digital asset regulators

The textile MSME sector of Gujarat functions within a rapidly transforming industrial environment where the availability, accessibility, and utilization of growth opportunities varies significantly across enterprises. Recognizing these differences, this study examines how textile MSME entrepreneurs perceive the adequacy of growth opportunities and how such perceptions shape their satisfaction levels. Based on responses from 487 enterprises across 28 districts, the research employs descriptive statistics, factor analysis, correlation analysis, discriminant modelling, and cluster analysis to identify the key drivers influencing growth perceptions. Five major opportunity dimensions emerged from factor extraction, namely funding prospects, regulatory norms, customer-centered practices, profitability orientation, and organizational culture. The empirical results indicate that the perceived adequacy of these opportunities has a strong positive relationship with entrepreneurial satisfaction, with firms demonstrating greater financial access, stronger market integration, and higher adoption of digital systems reporting higher satisfaction. Cluster classifications reveal heterogeneous expectations from government support, ranging from regulatory simplification and administrative efficiency to wider market access and integrated growth facilitation. The study underscores that strengthening financial inclusion, promoting technological advancement, enhancing policy transparency, and improving market linkages are essential for reinforcing entrepreneurial satisfaction and enabling sustainable expansion of Gujarat’s textile MSMEs.

Textile industries have remained among the most labor-intensive sectors in India and are a major employer. Tamil Nadu is one of the most prominent destinations for textile and garment production. The growth of the textile industry has been consistent with the level of competitiveness, which is largely driven by the effectiveness and flexibility of Human Resource Management. HRM is a major determinant of whether the organization will be able to attract, cultivate, and retain a workforce capable of meeting the challenges of modernization, pursuing quality, and meeting international market demands. Therefore, this study intended to examine the impact of HRM practices on labor turnover, worker productivity, and attrition in the textile industry in the state of Tamil Nadu, India. The purpose of this study, therefore, was to examine the causes of high attrition rates and analyze HRM practices used to create a working environment conducive to employee retention in the textile industry, which was conducted in major industrial clusters including Coimbatore, Tirupur, Erode, and Karur. * To understand the impact of HR policies related to selection, training, labor welfare, remuneration, and performance appraisal on the job satisfaction and commitment of the textile labor. The methodology included both quantitative and descriptive research, and, as such, primary data were collected through a structured questionnaire administered to 150-200 textile employees to evaluate perceptions of HRM practices and the determinants of large-scale retention. The data were then analyzed using parametric tests (univariate, bivariate, and multivariate) and exploratory statistical tools, including reliability tests (Cronbach’s Alpha), Correlation Analysis, and Principal Component Analysis (Factor Analysis) to examine relationships among variables and their influence on labor turnover. The study revealed that Welfare measures, continuous training programs, and fair performance appraisal were the most correlated with employee satisfaction and retention. In other words, when emoluments were managed in a fair manner, employees were less likely to seek a change in employment. Poor compensation, high work pressure and workplace stress, and a lack of growth opportunities were responsible for high attrition. The research is an additional resource for existing studies on the subject, providing regional insight into HRM in one of India’s industrial states. The study’s results would help policymakers, trade unions, and HR managers. For instance, a common approach to mitigate the influence of this type of human resource management is to establish a regulatory framework to reduce labor turnover; these steps can be taken at the policy and industry levels, respectively.

The hasty expansion of e-commerce in the marketplace has led to heightened competition, making it essential for businesses to ensure customers remain satisfied and loyal over the long term. This study examines the influence of various elements of the digital marketing mix on consumer satisfaction and loyalty within the online environment. A survey involving 1,000 online shoppers was conducted to gain insights into how digital interactions between customers and companies can be improved. Specifically, the study focused on four strategic approaches: social media engagement, email communication, search engine visibility enhancement, and mobile commerce optimization. The findings revealed that social media interactions and email campaigns had the most significant impact on customer satisfaction and retention. The study strongly recommends that e-commerce firms adopt more innovative digital engagement practices to enhance customer experiences and support sustained business growth.

The study focuses on unveiling the awareness level of bank employees towards CBDCs, as they are the main intermediaries in between the RBI and the general public. For the effortless implementation of the digital rupee, the concept must be well and properly understood by the users. It covers the bank employees’ understanding on conceptual level, policy and regulatory level, technological level as well as examines their source of information regarding the concept. Primary data have been used for the study which was collected through a structured questionnaire and the same was analysed using descriptive statistics, Mann Whitney U Test, Kruskal Wallis H Test and Dunn’s Post Hoc Test. And the results show that the employees possess a moderate level of understanding regarding the concept, regulatory aspects, technological framework, and sources of learning related to CBDC, and the findings suggest that while the foundational understanding of CBDC is emerging among bank employees, gaps remain in technological and policy-related awareness.

Clean Development Mechanism (CDM) is driving low-carbon projects and transfer of technology by the corporate that aligns with the global shifts towards net-zero economy. The study intended to analyse Carbon emission reduction in achieving Certified Carbon Emission (CERs) through CDM by the Public and Private Limited Companies in India under UNFCCC. The secondary data on CERs derived from UNFCCC were used and analyzed descriptive statistics. The study found that wind energy, hydropower and solar energy were used in recognition of CERs by Private sector Firms and the Public Limited Companies have utilised primarily wind energy, energy from managing wastes, solar energy and hydro power. The number of sustainable projects has increased during the latter part of the study period. The study will be useful to wide range of audiences and stakeholders including investors, bankers, companies, Government, CER issuers and auditors to achieve Net Zero

As globalization continues to expand market reach, multinational corporations (MNCs) increasingly rely on digital marketing strategies to enhance their visibility, credibility, and customer engagement. This study examines the effectiveness of search engine optimization (SEO), social media marketing, email promotions, and localization in influencing consumer perceptions and driving international market success. Using statistical analyses, including ANOVA and Chi-square tests, the findings indicate that SEO credibility varies by gender, while email marketing is equally effective across demographics. Additionally, digital engagement strategies such as personalized content and interactive campaigns are perceived positively across all age groups, highlighting their universal applicability. Furthermore, digital marketing has a statistically significant impact on purchase decisions, emphasizing its role as a key driver of consumer behaviour. These insights provide strategic recommendations for optimizing digital marketing efforts in global markets

As India transitions towards a digital-first healthcare economy, e-pharmacies have emerged as a pivotal alternative to traditional brick-and-mortar chemists. This study investigates the consumer perception of online pharmacies in India, analyzing the behavioral drivers (convenience, price, privacy) against the psychological barriers (trust, safety, lack of human touch). Synthesizing data from 2023–2025, this paper reveals a clear demographic divide: while urban millennials and Gen Z view e-pharmacies as a primary utility, the elderly and rural populations remain hesitant. The study concludes that while “discounts” are the initial hook, “trust” and “fulfillment reliability” are the determinants of long-term retention

Under NABARD’s Self Help Group Bank Linkage Program credit is being provided to huge number of Self Help Groups. With increase in loan disbursement Non-performing assets are also increasing. As development initiative like this requires long term viability mitigating credit risk is must for banks engaged in extending credit under this program. With changing times Non-performing assets pattern and trend changes and require strategies relevant with current scenario. For this purpose paper studies the pattern and trend in Non-performing Assets in different agencies empirically for five years and found out that CoBs NPA percentage is significantly different than Commercial and RRBs. Credit risk mitigation strategies for effective credit and NPA management under the program are also suggested

This study examined the influence of extrinsic motivation on employee performance at Kipchabo Tea Factory in Nandi County, Kenya. As a key player in Kenya’s agricultural sector, particularly in tea processing, the factory operates in an industry that remains central to the national economy yet continues to grapple with persistent productivity challenges (KIPPRA, 2020). These challenges underscore the need to understand motivational factors that shape employee output. The study specifically evaluated how compensation, job security, recognition and awards, promotion opportunities, leadership support, and training initiatives affect employee performance. Guided by Herzberg’s Two-Factor Theory and Maslow’s Hierarchy of Needs, the study adopted a descriptive research design and drew a sample of 200 respondents from a target population of 400 employees using stratified random sampling. Data were collected using a structured questionnaire, whose reliability was confirmed through a Cronbach’s alpha coefficient of .709. Descriptive statistical methods—including means and standard deviations—were used for data analysis. Findings indicated that extrinsic motivation positively contributes to improved employee performance, with recognition and awards emerging as the most significant predictor. The study recommends regular appraisal of reward structures, adoption of participatory management practices, and enhanced investment in employee development to sustain motivation and optimize performance.