In present situation AI occupying every corner of business activates and reshaping in the perception preference and decisions in the minds of purchases. Despite its benefits, the deployment of AI in customer decision management raises critical behavioural, ethical, and governance-related concerns. Algorithmic opacity, data privacy issues, and the potential manipulation of customer behaviour may affect trust and perceived fairness. Purpose of the Study: the research focused on the awareness and perception regarding AI integration, trust on AI on purchase decision management. This study throws light upon how user trust influence on purchase decision. Methodology: This research article adopted descriptive study of a specific phenomenon. Primary data with sample size of 88 respondents by simple random method.Cron`bach alpha for reliability, one sample t test, regression and ANOVA used for analysis. Findings: This study found that there are differences in opinion regarding AI usage, it’s hard to believe the AI for some quantum of purchase and there is a influence of AI on customer purchase decision. There are several factor influences on purchase decision such as price, advertisement, availability and affordability and now its AI integrated product. Research implication: The present study contributes meaningfully by analysing how AI applications influence customer purchase decisions. This research emphasise the significant of consumer trust on AI recommendations and their influence on the customer behaviour. The study focusing on the key issues which are related with the data privacy, ethical concern and transparency. This is very crucial to maintain accountability and sustainable strategy to maintain customer trust. Originality of the study: The present study provides insights into analyse the consumers trust and perspective of customer towards AI in purchase decision. it identifies the mechanism of AI trust and it through light on the key issues in AI and purchase decision.

Abstract: Purpose: The present research delves into the prominent influences of entrepreneurial marketing, which are present in community enterprises in South Asian countries whose mission is to solve deeply rooted social and economic issues such as poverty, lack of education and restricted access to healthcare. Methodology: Adopting a qualitative and action-oriented research paradigm, this paper explores the root cultural values, collective resources and shared trust that impact the success of community enterprises. Inclusive communication, collaborative leadership and local innovation are pointed to fundamental and necessary aspects for reaching out to marginalized communities by the research. Findings: The findings of this study reveal that entrepreneurial communities in South Asia have the potential to create sustainable development results, especially in the context of education, healthcare and the eradication of poverty. Originality: This work substantially benefits the debate on social entrepreneurship by offering examples of how marketing concepts can be locally transformed to facilitate inclusive growth and empower communities. Practical Implications: Entrepreneurs have the opportunities for community business to change marketing ideas into inclusive practices that support local innovation and problem solving of their teamwork. In that way, they create sustainable models of growth adjusted to the distinctive socio-cultural environment of South Asian communities. Social Implications: Entrepreneurs based in communities are described as the main agents of societal transformation who employ marketing strategies not only for profit but also for achieving sustainable social results. Community members' collaboration greatly depends on shared values, joint resources and trust which are considered the most essential elements. Besides, these factors allow communities to have social bonds and exchange mutual support.

 This paper has made an attempt to analyze the socio-economic factors of sample respondent employees of Public Sector and Private Sector Banks in Tirupati district, A.P and to examine the level of job satisfaction of sample respondent employees of Public Sector and Private Sector Banks in Tirupati district, A.P. The primary data has been collected from the respondent employees of Public and Private Sector Banks in Tirupati district for the year 2025-26. For the purpose of primary data collection, total sample was 400 employees, 200 each from Public Sector and Private Sector Banks were selected randomly. The primary data was conducted through structured questionnaire and some personal interview. Tools for measuring data mean, percentages and Chi-square test have been used. This paper reveals that majority of the sample respondents of Public Sector Banks (72.50 per cent) belong to male category whereas in the Private Sector Banks majority of the 127 sample respondents (63.50 per cent) belong to male category. However, the least number 55 sample respondents (27.50 per cent) belong to female category in Public Sector Banks whereas in the Private Sector Banks 73 sample respondents (36.50 per cent) belonging to female category. It is suggested that the Public Sector and Private Sector banks have to take step to improve recreational facility and communication system to make an employee most satisfied and Public Sector and Private Sector banks have to make some changes in its present training system, refresher course and performance appraisal system of it. It is concluded that the job satisfaction plays an important role on the employees working as well as in the progress of banking sector. Banking sector essentially provides job to a large number of individuals and thus it is necessary to measure satisfaction level of employees working at bank.

Credit scoring is fundamental to financial decision-making, yet most systems lack interpretability, leading to distrust and regulatory issues. This study addresses the problem of black-box models in credit risk assessment. The objective is to develop an Explainable AI (XAI) based credit scoring system to maintain transparency while improving accuracy. Data was obtained from a private sector bank in India, comprising 45,000 anonymized loan application records. Key metrics like credit history, income, employment status, and repayment records were measured. The data was analyzed using SHAP (SHapley Additive exPlanations) integrated with Gradient Boosting Machines (GBM). The proposed technique enables both prediction and feature explanation. The method applies local and global interpretability techniques for end-user trust. Six hypotheses were tested: H1—Income level has a positive impact on credit approval; H2—Longer employment duration increases creditworthiness; H3—Higher past delinquency negatively affects scores; H4—Applicants with collateral are more likely to get approved; H5—Existing debts reduce approval chances; H6—Credit history length influences risk grading. The findings show improved transparency without sacrificing predictive performance. The study concludes that XAI enhances trust and fairness in automated financial systems, aligning with regulatory requirements.

 Indian military textile supply chains operate across diverse operational environments and involve multiple institutions, suppliers, laboratories, quality-assurance establishments and logistics nodes. Military textiles-including combat uniforms, body armour, NBC/CBRN protective clothing, winter clothing and parachute textiles-are safety- and mission-critical products whose quality must remain traceable beyond procurement and acceptance. The existing ecosystem has a strong institutional foundation through the Defence Acquisition Procedure 2020 (DAP 2020), Directorate General of Quality Assurance (DGQA), Defence Research and Development Organisation (DRDO), Bureau of Indian Standards (BIS), Government e-Marketplace (GeM) and the Army Integrated Material Management Online System (IMMOLS). However, the article identifies a central gap: information generated during procurement, manufacturing, inspection, storage, issue, maintenance and disposal is not consistently connected through a persistent item-level identity. This limits rapid retrieval of product history, targeted recall, supplier accountability, lifecycle management and auditability. The article therefore proposes an Indian Military Digital Product Passport (IM-DPP) framework that combines globally recognised Automatic Identification and Data Capture (AIDC) technologies-barcodes, QR codes and RFID-with GS1 Digital Link and EPCIS event data, while integrating the resulting information with existing defence systems. A tiered information architecture is proposed to balance traceability with defence security requirements. The article further develops a pilot methodology, research hypotheses and a phased implementation roadmap. The framework is intended to strengthen quality assurance, operational readiness, indigenous-content verification, anti-counterfeit controls, lifecycle cost management and evidence-based defence procurement.

 This study focuses on the influence of employee training on achieving green objectives in luxury hotels, where sustainable practices are becoming increasingly vital for brand reputation and guest expectations. As luxury hotels face growing challenges to retain eco-certifications and achieve the ecological expectations of their most valuable clients, employees in housekeeping, food and beverage and maintenance jobs play an important role in the execution of green objectives of the organisation. This study investigates how focused employee training programs impact the employee motivation and employee productivity so that the effective adoption of sustainable practices is easily incorporated in their routine job roles. The methodology followed for this research was a quantitative approach where primary research was done through an online survey method using Google forms. Sampling was a mix of convenience sampling followed by the snowballing method. The respondents were hotel employees from several luxury hotels of Delhi- NCT. Statistical tests, hypothesis testing etc. was performed for analysing the data. A data of 90 respondents was taken as a sample. The results showed that there is strong statistical evidence that employees have a positive perception of training related to green objectives and employees demonstrate high motivation toward green objectives in luxury hotels when appropriate trainings are imparted. The result also showed that stronger personal environmental values lead to higher employee productivity on green objectives. In terms of academic implications, the impact of employee training on achievement of green objectives may add to both the field of human resources literature as well as research on sustainability.  Based on the findings, the managerial implications might include role-specific training to enhance employee motivation and employee productivity w.r.t green objectives of hotels. The study aims to highlight the critical role of employee training in bridging the gap between corporate green commitments and on-the-ground execution, providing actionable insights for luxury hotel brands to improve ESG performance and maintain a competitive advantage in a sustainability-conscious market.

The present study aims to examine the relationship between proactive sustainability and organizational performance, as well as the mediating role of organizational culture in strengthening this relationship. The research problem was formulated as the following main question (Is there an indirect relationship between proactive sustainability and organizational performance, mediated by organizational culture?) To answer this question, the researchers designed a hypothesis framework to clarify the relationship between the variables; based on this framework, a set of research hypotheses was formulated. The research sample was drawn from Maysan State University and its affiliated colleges, comprising 215 employees. The questionnaire was distributed to them, and 214 valid questionnaires suitable for statistical analysis were recovered, representing a response rate of 99 per cent The researchers utilised a range of off-the-shelf statistical software programmes, namely SPSS, AMOS and Excel, and relied on a set of statistical methods, including confirmatory factor analysis, Cronbach’s alpha, the normal distribution of data, and simple linear regression analysis. The research reached a number of conclusions, the most important of which was the existence of an indirect relationship between the variable ‘proactive sustainability’ and the enhancement of organizational performance, mediated by the variable ‘organizational culture’. The researchers also put forward a set of recommendations for the University of Maysan, the most important of which is the adoption of a clear strategy and policy for proactive sustainability in order to enhance the performance of the university and its affiliated faculties, as well as to foster a culture of open communication and empower staff to make decisions and take responsibility.

The transition to organic farming is increasingly recognized as a viable remedy for environmental degradation, health problems and the long-term viability of agricultural systems. However, despite growing awareness, farmers continue to adopt organic farming practices unevenly, creating a gap between intention and practice. This study proposes an enlarged Technology Adoption Model (TAM) to examine the key determinants of farmers' adoption of organic farming. By including components like perceived risk, social influence, perceived economic benefits, perceived environmental concern and institutional support, the model builds upon the traditional TAM concepts of perceived utility and perceived ease of use. Using primary data collected from farmers via a standardized questionnaire, the study employs structural equation modelling to investigate the relationships among these parameters. The findings demonstrate that perceived utility and environmental concern have a significant impact on farmers' opinions on organic farming, which in turn affects their behavioral intentions. Perceived risk also acts as a barrier to adoption, although institutional support and social influence are crucial mediators in turning intention into actual practice. The study contributes to the body of knowledge by highlighting the elements that facilitate the transition from intention to practice and by empirically validating an extended TAM in the context of organic farming. The results offer useful information that agricultural stakeholders, governments and extension agencies may utilize to develop targeted interventions that encourage farmers to adopt organic farming practices more broadly.

 Cause-related marketing (CRM) is defined as a company pitching to its customers, “if you buy product/service A, then we will donate in cash or kind to charitable cause B.” CRM has a positive impact on firm performance, and this is reflected in its rapid growth. However, the impact of CRM on societal welfare is controversial. This study presents a novel argument rooted in economic theory that CRM reduces societal welfare. CRM is a form of “bundling” of the product sold by the company and a donation to the cause. We present a mathematical model to show that bundling increases firms’ profits but reduces societal welfare. Finally, we recommend how firms and consumers can really help a charitable cause.

Home Science, as a discipline oriented toward the holistic wellbeing of the individual, family, and community, is undergoing a significant transformation under the influence of Artificial Intelligence (AI) and digital technologies. This paper presents a conceptual and descriptive examination of how AI-enabled tools, digital platforms, and Internet-of-Things (IoT) applications are reshaping teaching–learning processes, skill development, collaboration, and real-world application within Home Science education. Drawing upon secondary literature and an integrative conceptual framework, the study organizes the impact of these technologies into five interrelated dimensions: enhanced learning experience, improved teaching and assessment, skill development and practical learning, collaboration and accessibility, and real-world application and life impact. The paper further identifies key challenges confronting the adoption of AI in Home Science education, including cost, digital divide, teacher preparedness, data privacy, and the risk of over-reliance on technology, and proposes a way-forward framework anchored in infrastructure investment, capacity building, quality digital content, ethical use, and industry–academia partnerships. The paper argues that a judicious, learner-centred integration of AI and digital technologies can make Home Science education more personalized, inclusive, and future-ready while continuing to nurture the discipline's core values of competence, creativity, and compassion.

Organisations are being revolutionised by Artificial Intelligence (AI) technologies, automation, data-driven decision-making and improved digital capabilities. For optimal value of the opportunity for AI investment, it is important to ensure the integration of AI in the Human Capital Management (HCM) process. The article delves into the connection between AI-driven HCM and financial results in this article. It demands employee capabilities, human-AI working and sound leadership and ethical governance to achieve sustainable benefits. These findings offer insights that can help organisations develop strategies to drive financial success and growth for their employees and the responsible use of AI.

The increasing adoption of digital payment systems has transformed the way financial transactions are conducted, making digital payments an essential part of daily activities. However, despite this rapid technological advancement, variations exist in consumer experiences, acceptance levels and perceptions regarding government-led Digital Payment Services (GLDPs) facilitated through public and private sector banks. Therefore, this study aims to explore consumer perceptions regarding the adoption of government-led digital payment services and assess how these perceptions differ between customers of public sector banks and private sector banks. The research focuses on analysing dimensions such as awareness, accessibility, usability, trust, security and service-related challenges affecting adoption behaviour. Furthermore, the study compares consumer adoption patterns between Public Sector Banks (PSBs) and Private Sector Banks (PrSBs) and examines the challenges faced by users while utilizing government-supported digital payment platforms. A sample size of 390 consumers from SBI and HDFC banks is considered and an interview is conducted using a structured questionnaire. Both qualitative and quantitative approaches are used in the research methodology. Descriptive statistics and inferential statistical tools, which include factor analysis and SEM, were employed in analysing the data. The analysis on adoption behaviour demonstrated a moderate to high level of adoption of GLDPs among the consumers. Trust & security appear to be the strong drivers underscoring the significance of confidence in sustainable usage of digital platforms.

Financial literacy can be defined as the ability of individuals to effectively understand, manage, and utilize financial resources to achieve better financial outcomes. It plays a significant role in enhancing individual financial well-being as well as contributing to broader economic development. Since individual investors form an important part of the financial ecosystem, this study explores the influence of financial literacy on their investment decision-making behaviour. The study is based on data collected from more than 200 individual investors from Hyderabad and Secunderabad and examines key dimensions of financial literacy, including knowledge of financial products, accessibility to financial services, money management practices, awareness of investment alternatives, and the ability to make informed investment decisions. Additionally, the research investigates various behavioural biases that investors may develop through personal experiences, investment exposure, and social influences. The findings indicate that practical financial skills have the strongest influence on investment behaviour, whereas basic awareness of financial products has comparatively less impact. The study emphasizes that behavioural biases can significantly affect investment choices and may influence the overall performance and returns of investors. Based on these insights, the research provides recommendations for policymakers and financial institutions to promote skill-oriented financial education and strengthen investors’ decision-making capabilities.