-
A Study on Factors Influencing Consumers' Buying Behaviour: Gold
Geetanjali Gupta
*
Issue: Volume 14, Issue 3, September 2026
Pages: 83-88
Received: 16 February 2026
Accepted: 15 June 2026
Published: 8 September 2026
Abstract: Gold has traditionally held a significant position in the Indian economy and society, serving not only as jewellery but also as a valuable form of savings and investment. The purchase and ownership of gold jewellery are influenced by cultural traditions, social status, financial security, and investment considerations. India is one of the world's major markets for gold jewellery, and the growing demand for gold has increased the importance of understanding consumer and jeweller buying behaviour. Against this background, the present study examines the buying behaviour of jewellers in New Delhi, with particular emphasis on the role of gold jewellery as an investment and savings instrument. The study adopts a systematic approach to examine the factors influencing the purchase of gold jewellery and the investment preferences of jewellers in New Delhi. Primary data were collected from jewellers through a structured questionnaire, while relevant secondary information was obtained from existing literature and other published sources. The collected data were analysed to identify patterns in purchasing behaviour and to understand the extent to which gold jewellery is purchased for investment purposes. The findings indicate that gold jewellery continues to be an important investment avenue among jewellers in New Delhi. A considerable proportion of respondents reported purchasing gold jewellery as an investment, demonstrating that gold serves purposes beyond personal adornment. The study concludes that gold remains an important savings and investment vehicle in India, supported by its cultural significance, perceived value, and long-term financial appeal. Understanding these purchasing patterns can help jewellery businesses, policymakers, and other stakeholders better respond to changing preferences in the Indian gold market.India's gold market is mostly used for the purchase and sale of tangible gold as well as gold jewellery. In India, gold has a variety of uses, and wearing it has a number of consequences. It shows standard of living. India is thought to have the world's quickest rate of growth in gold jewellery. After deposits and mutual funds, it is the second most popular investment choice in India and is recognized as a savings and investment vehicle. Therefore, the buying behaviour of jewellers in the city of New Delhi is the focus of this study. According to the study's findings, many have bought gold jewellery as an investment.
Abstract: Gold has traditionally held a significant position in the Indian economy and society, serving not only as jewellery but also as a valuable form of savings and investment. The purchase and ownership of gold jewellery are influenced by cultural traditions, social status, financial security, and investment considerations. India is one of the world's m...
Show More
-
A Comparative Study of Machine Learning-Based Predictive Models for House Price Prediction
Issue: Volume 14, Issue 3, September 2026
Pages: 89-97
Received: 16 February 2026
Accepted: 15 June 2026
Published: 8 September 2026
Abstract: Predicting house prices is vital in helping homebuyers, investors, real estate agencies, and policymakers make informed decisions. But it's hard to precisely value a house when there are a number of factors at play – from property details to location to market conditions. The present study accounts for the comparative analysis of four machine learning techniques Multiple Linear Regression (MLR), Support Vector Regression (SVR), Feed Forward Neural Network (FFNN) and Extreme Gradient Boosting (XGBoost)) on predicting house prices by applying the Boston Housing dataset. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and Coefficient of Determination (R2) were used to assess the models. Experimental results showed that XGBoost had the lowest RMSE (3.9147), MAE (2.8454), MSE (15.3252) and the highest R2 value (0.7910) among all the models. The second best result was obtained by SVR while FFNN gave an accurate prediction and MLR gave the least accurate result. The analysis results show that the XGBoost model can better capture the complex nonlinear relationship between house attributes and makes it significantly better than the traditional regression model and neural network model. In conclusion, XGBoost is a powerful and stable model that can be used to accurately predict house prices and value real estate.
Abstract: Predicting house prices is vital in helping homebuyers, investors, real estate agencies, and policymakers make informed decisions. But it's hard to precisely value a house when there are a number of factors at play – from property details to location to market conditions. The present study accounts for the comparative analysis of four machine learn...
Show More
-
Transition to Circular Economy: Stakeholder Interventions in Sustainable Municipal Waste Management
Sangeetha Kulala Kodibettu
*
,
Professor Seshaiah Manasi
Issue: Volume 14, Issue 3, September 2026
Pages: 98-105
Received: 16 February 2026
Accepted: 15 June 2026
Published: 8 September 2026
Abstract: Rapid urbanization and industrialization are the major reasons to generate the more waste in the cities. The linear economy system is largely implemented by the public, i.e., purchase, use, and dispose. As a result, most of the waste are end with landfill. Hence, this study mainly focused on the shift from a linear economy system into circular economy system, such as reduce, reuse, and recycle, to facilitate sustainable waste management in the cities. This study examines the role of stakeholder intervention (households, Resident Welfare Associations (RWAs), Non-Governmental Organizations (NGOs), and the Solid Waste Management (SWM) Department) in the successful transition towards a circular economy system in municipal waste management. This study used both qualitative and quantitative approaches to examine the stakeholders' behaviour across the two major best practices wards of Bangalore, such as HSR Layout and Koramangala ward. The findings of the study highlight that households’ behaviours towards waste segregation and disposal, RWAs and NGOs' initiatives towards awareness creation and implementing circular economy practices, and an effective operational system by the SWM department help to achieve sustainable solid waste management. These stakeholders' active involvement in circular economy practices helps to reduce landfill dependency, enhance recycling efficiency, and convert the waste into a resource. The effective coordination among these stakeholders are able to facilitate long-term sustainable waste management in the city.
Abstract: Rapid urbanization and industrialization are the major reasons to generate the more waste in the cities. The linear economy system is largely implemented by the public, i.e., purchase, use, and dispose. As a result, most of the waste are end with landfill. Hence, this study mainly focused on the shift from a linear economy system into circular econ...
Show More
-
Leveraging Social Media for Sustainable Development Campaigns
Issue: Volume 14, Issue 3, September 2026
Pages: 106-113
Received: 16 February 2026
Accepted: 15 June 2026
Published: 8 September 2026
Abstract: Social media has emerged as a powerful tool for promoting sustainable development initiatives on platforms like Instagram, Twitter, You Tube, Facebook, Twitter, etc. due to its wide reach and engagement potential. This paper examines the effectiveness of utilizing social media platforms for sustainable development campaigns. The objective of this research is to assess how social media can be leveraged to raise awareness, mobilize support, and drive action towards sustainable development goals. Problem Statement: Despite the increasing use of social media for advocacy purposes, there is a need to understand its impact on sustainable development campaigns comprehensively. This research aims to address this gap by exploring the role of social media in fostering sustainable behavior change and community engagement. Research Questions & Hypotheses: 1. How does social media influence public perceptions and attitudes towards sustainable development? Hypothesis: Social media engagement positively correlates with increased awareness and support for sustainable development initiatives. 2. What strategies are most effective in leveraging social media for sustainable development campaigns? Hypothesis: Interactive and visually compelling content generates higher levels of engagement and participation in sustainable development campaigns on social media platforms. Research Methodology: This study employs a mixed-methods approach of primary and secondary data sources, combining quantitative analysis of social media data with qualitative interviews and surveys to gather insights into user perceptions and behaviours. Key Findings & Conclusions: Preliminary findings suggest that social media plays a crucial role in spreading a word and driving support for sustainable development campaigns. Interactive content, influencer partnerships, and targeted messaging emerge as key success factors in driving engagement and action. Discussions & Recommendations: The findings highlight the importance of strategic communication and community engagement strategies in maximizing the impact of sustainable development campaigns on social media. Recommendations include the development of tailored content, fostering partnerships with influencers and organizations, and leveraging data analytics to measure and optimize campaign effectiveness.
Abstract: Social media has emerged as a powerful tool for promoting sustainable development initiatives on platforms like Instagram, Twitter, You Tube, Facebook, Twitter, etc. due to its wide reach and engagement potential. This paper examines the effectiveness of utilizing social media platforms for sustainable development campaigns. The objective of this r...
Show More
