A Study of Customer Buying Behavior for Online Shopping with Special Reference to Electronic Goods

Indian Journal of Economics and Finance (IJEF) ISSN: 2582-9378 (Online), Volume-5 Issue-2, November 2025 19 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com A Study of Customer Buying Behavior for Online Shopping with Special Reference to Electronic Goods Punit Dubey, Rajeev Sharma, Vandana Kanaskar Abstract: This paper aims to identify the various factors that affect customer buying behaviour. In the Digital era, online shopping has seen a rapid rise. The emergence of the internet and technological progress has transformed how consumers interact with commerce. Online shopping has become a pivotal element of modern consumer behavior, altering purchasing habits, preferences, and decision-making processes. This essay provides a comprehensive analysis of consumer behaviour in the context of online shopping, addressing factors that shape buying decisions, the significance of trust and convenience, the influence of social dynamics, the psychological elements that impact choices, and the implications for businesses. By reviewing existing research and empirical evidence, this study provides meaningful insights into the complexities of online consumer behaviour in the electronic goods sector. Keywords: Online Shopping, Customer Behavior, Trust Abbreviations: TAM: Technology Acceptance Model AR: Augmented Reality AI: Artificial Intelligence I. INTRODUCTION Beginning in the late 1990s, online shopping has surged in popularity as more consumers have expanded their purchases to a broader variety of products. The consumer is the key point in any marketing, as they are a very important person who decides what to purchase, when to purchase, why to purchase, from whom to purchase, where to purchase, and how much to purchase. In this sense, "the consumer is the supreme in the market". As consumers, we play a vital role in the health of the local, national, or international economy. Consumers make decisions by allocating their scarce income across all possible goods to obtain the greatest satisfaction. Manuscript received on 28 March 2025 | First Revised Manuscript received on 16 April 2025 | Second Revised Manuscript received on 18 October 2025 | Manuscript Accepted on 15 November 2025 | Manuscript published on 30 November 2025. *Correspondence Author(s) Dr. Punit Dubey*, Principal & Professor, Department of Under Graduation, Indore International College Affiliated to Devi Ahilya University, Indore (M.P), India. Email ID: [email protected], ORCID ID: 0009-0005-9591-591X Dr. Rajeev Sharma, Associate Professor, Department of MBA, Modern Institute of Pharmaceutical Sciences, Indore (M.P.), India. Email ID: rajeevsharm[email protected] Dr. Vandana Kanaskar, Assistant Professor, Department of Commerce, SAGE University, Indore (M.P.), India. Email ID: [email protected] © The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/ Formally, we say that consumers maximize their utility subject to budget constraints. Utility is the satisfaction a consumer derives from consuming a good. As noted above, a utility's determinants are decided by a host of non-economic factors. The relative utilities of goods measure consumer value. These reflect the consumer's preferences. The underlying foundation of demand, therefore, is a model of consumer behaviour. The individual consumer has a set of choices and values that lie outside the realm of economics. They are undoubtedly influenced by culture, education, and personal tastes, among many other factors. In this model, the measure of these values for a particular good is the real opportunity cost to the consumer who purchases and consumes it. If an individual purchases a specific good, then the opportunity cost of that purchase is the forgone goods the consumer could have bought instead. II. REVIEW OF LITERATURE Liang and Lai (2000) [1] stated that purchasing products or services through the Internet is known as online shopping behaviour. He identifies five steps for conventional shopping behavior. Schubert and Selz (1999) [2] identify electronic community quality factors like settlement, agreement and information stages. Bellman et al. (1999) [3] examine the relationship between consumer characteristics, consumer attitudes and consumer demographics for online shopping. Fishbein and Ajzen (1975) [4] Explain the relationship between attitudes, behaviour and purchase intention, which helps shape the actual behaviour of consumers. Borchers (2001) [5] explains three dimensions, i.e. legal framework, system and third-party recognition. Whereas Lee et al. (2000) [6] argue that if we have limited online vendors, we have a greater chance to maximise profits. Various researchers examine the impact of customers on online shopping, depending on factors such as variety, Product quality, features, performance, Product availability, price, social references, product requirements, and brand. Kym (2003) [7] stated in his research that the costs associated with transactions, levels of uncertainty, and the specificity of assets significantly influence the acceptance of digital products by consumers. In contrast, only transaction costs and uncertainty affect consumers' acceptance of physical products. According to Liang and Huang (1998) [8] Develop transaction cost theory and found that the transaction influences the decision to purchase A product's online costs are associated with the channel through which it is sold. The transaction Costs for a product on the internet are influenced by factors such as uncertainty and asset specificity. Jhang et al., (2001) [9] found A Study of Customer Buying Behavior for Online Shopping with Special Reference to Electronic Goods 20 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com electronic commerce technology develops and draws in more mainstream consumers, the virtual nature of the electronic commerce environment will emerge as a significant concern. Numerous consumers experience discomfort regarding this virtual aspect. Lowengart and Tractinsky (2001) [10] evaluates the likelihood of purchasing items from a specific online retailer when considering various alternative vendors. We employ a multinomial logit choice model to examine experimental data on consumer preferences across two distinct product categories—books and computers, which differ in risk. Some service factors also related to online shopping behaviour include communication with vendors, product delivery time, reliability of the purchasing process, availability of personalised service, return/refund policy, Fraud/scam, tracking facilities, transaction costs, and other Promotional activities. According to Lohse and Spiller (1998) [11] explain that considering the resources required to launch an online retail store or modify the design of an existing one, it is crucial to dedicate product development resources to interface features that truly enhance store traffic and sales. Using a regression model, we forecast store traffic and revenue based on interface design attributes, including the number of links leading to the store, image dimensions, product quantity, and features related to store navigation. By measuring the advantages of user interface elements, we aim to simplify the process of designing and assessing various storefronts by pinpointing the features that most significantly influence traffic and sales. Ho and Wu (1999) [12] found five antecedents of customer satisfaction to be more appropriate for online shopping on the Internet. Bhatnagar et al. (2000) [13] explain Online shopping provides consumers the ability to purchase items from remote locations with ease. One concern consumers have is the safety of sending credit card information online. Additionally, buyers may feel uneasy about purchasing without physically inspecting the product, especially if they can't return it if it doesn't meet their expectations. However, the risks associated with online shopping are minimal or outweighed by the convenience it offers. Consumers make decisions under uncertainty, aiming to maximise their anticipated benefits. Chao et al. (2001) [14] studied post-purchase behaviour in online and offline shopping environments and found that complaint handling is the most crucial parameter to drive satisfaction in online and offline purchasing. Li et al. (1999) [15] found his research that online shopping behavior is significantly affected by demographics, knowledge of channel, shopping orientation and perceived channel utilities. Li and Zhang (2002) [16] defined consumer satisfaction as the extent to which consumers' perceptions of the online shopping experience confirm their expectations. Gefen et al. (2003) [17] stated that if the customer doesn't have sufficient trust in the online vendor, then the customer leaves the website. Examine the role of trust and the Technology Acceptance Model (TAM) in online shopping, with a focus on high-value purchases, such as electronics. It provides insights into how trust influences consumer decisions. According to Hoffman et al., studies show that this distrust stems from cyber-consumers' perception of limited control over how Web retailers access their data while they browse online. These privacy concerns encompass aspects of both environmental control and the control over the secondary use of information. Acknowledging consumers' rights to ownership of their data online is a crucial initial move in this effort to restore balance [18]. Mayer et al. (1995) [19] studied trust, including characteristics of the trustor, the trustee, and the role of risk. Culnan & Armstrong (1999) [20] 1identified that risk perception is a primary obstacle to the future growth of online commerce. A high level of trust by buyers has been found to stimulate favourable attitudes and behaviour. Schurr and Ozanne (1985) [21] trust plays a vital role for having bargaining power right to seller and expected trustworthiness and toughness in bargaining cause higher level of relationship between buyer and seller. Anderson and Narus (1990) [22] found in his research that in both the models of the manufacturer firm and the distributor firm, cooperation is redefined as a precursor to trust instead of being seen as a result of it. Kini and Choobineh (1998) [23] suggested that trust in the Internet business is necessary, but not sufficient, for Internet buying behavior to take place. The consumer must also trust the online shopping platform. Lohse et al. (2000) [24] used panel data to explore the predictors of online purchasing behaviour. They found that typical online consumers are characterised by their wired lifestyle and are time-starved. Therefore, they suggested providing customised information to online shoppers who purchase standard or repeat items, thereby increasing convenience and speeding up purchase decisions. Loshe and Spiller (1998) [25] examine online retail store attributes and web information systems. Zhang et al. (2010) [26] explore the factors influencing consumer behaviour in online shopping, including trust, convenience, and pricing strategies. It provides a framework for understanding how consumers make purchasing decisions in the electronics sector. Adomavicius and Tuzhilin (2005) [27], discuss the role of recommender systems in enhancing the online shopping experience, particularly for electronics. It highlights how personalized recommendations can increase sales and customer satisfaction. III. RESEARCH METHODOLOGY A. Research Objectives ▪ To study the customers' online shopping behaviour. ▪ To find out the customers' preference towards online shopping. ▪ To study the effect of price on the preference for online shopping. B. Sample Size: The Sample size for this research is 100 respondents. C. Tool for Data Collection: Questionnaire, Personal Interview. A self-administered questionnaire is prepared for data collection. Indian Journal of Economics and Finance (IJEF) ISSN: 2582-9378 (Online), Volume-5 Issue-2, November 2025 21 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com D. Research Framework Data Analysis and Interpretation of Gender Graph 1: - Gender Interpretation: The survey respondents are predominantly male, comprising 70% of the sample, while females account for 30%, as shown in the chart. Do You Have an Online Shopping Account/User ID Graph 2: - Account/User ID Interpretation: In this survey We conclude that 90% of people have online shopping Accounts or user IDs, and 10% do not, as shown in the given chart. How often do you go Online Shopping? Consumer Characteristics Cultural Social Personal Consumer Psychology Motivation Perception Emotion Memory Attitude Towards Online Shopping Intention to shop online Decision Making Online Purchasing Perceived Risk Data Privacy Fraud & Security Concern Product Attribute/Characteristics Price and Selection Competitor Offering Marketing Tactics Product Service of Brand Incentives/ Schemes Communication Distribution Website Quality Customer Satisfaction Trust Fig.1: Research Framework A Study of Customer Buying Behavior for Online Shopping with Special Reference to Electronic Goods 22 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com Graph 3: - Often do You go Online Interpretation: In the given graph, 5% fall in highly irregular, 15% Irregular, 50% Average, 25% Regular & 10% Highly Regular. How Much Do You Spend on Average Each Time When You Shop Online? Graph 4: Amount Spends Interpretation: In this survey, we found that the percentage of customers who want to purchase products or goods in the year is as follows: less than 1000 is 12%, 10002000 is 26%, 2000-5000 is 32%, 5000-10000 is 22%, and more than 10000 is only 8%. Payment Type to be Used for Online Shopping Graph 5: Payment Type Interpretation: In this survey, we found that the most commonly used payment type is cash on delivery, at 52%, followed by debit card at 28%, then credit card at 12%, EMI transaction at 6%, and the least used option is electronic transfer, which is used by only 2%. Do You Often Shop Online for Which Type of Products? Graph 6: - Often Shop Online Interpretation: In this graph, customers choose online grocery shopping (38%), followed by clothes (27%), shoes (15%), electronics (11%), and cosmetics (9%). Commonly Used for Shopping Graph 7: Most Common Website Interpretation: The most commonly used website is Flipkart, at 36%, followed by Amazon at 32%, Myntra at 18%, Snapdeal at 8%, and eBay at 6%. How Did You Come to Know About Your Brand? Graph 8: How Did You Come to Know About Your Brand Interpretation: In this graph, customers obtain information about the product from the shop owner (7%), friends (16%), advertisements (25%), social media (27%), and the internet (25%). How Much Is Your Monthly Income/Salary Indian Journal of Economics and Finance (IJEF) ISSN: 2582-9378 (Online), Volume-5 Issue-2, November 2025 23 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com Graph 9: Monthly Income Interpretation: This graph shows that customers with an income of less than 5000 are 15%, those with an income between 5000 and 10000 are 30%, those with an income between 10000 and 20000 are 27%, those with an income between 20000 and 30000 are 18%, and those with an income of more than 30000 are only 10%. Which Brand Would You Like to Purchase? Graph 10: Most Preferred Brand Interpretation: In this graph, LG is the most preferred brand (32%), followed by Samsung (26%), Sony (22%), Whirlpool (16%), and Havells (4%). How Many Electronics Products Have Been Bought in the Past Year? Graph 11: Electronics Products Have Been Bought in the Past Year Interpretation: In this graph, only 5% of customers did not purchase any electronic product in the last year, 29% of customers purchased 1 product, 26% of customers purchased two products, 22% of customers purchased three products, and only 5% of customers bought more than three electronic products. Please Mark Tick ( ) Against the Factors Which Are Important to You While Shopping Online S. No Factors/Att ributes Most Prefer able Prefer able Aver age Not Prefer able Highly not Prefer able 1 Website 2 Type of payment mode 3 Website design 4 Reputation 5 Response/D elivery Graph 12: Important Factors for Online Shopping Interpretation: In this graph, customer attraction for website design is 26% most preferred, 24% preferable, 19% Average, 16% not preferable, and 15% highly not preferred. The preferred payment mode is 22% for the customer, 18% is also preferable, 15% is average, 25% is not preferable, and 20% is highly not preferable. Ease of operation: 32% of customers prefer it when operating a website, 28% like it, 18% are average, 14% are not preferable, and 8% are highly not preferable. Response and delivery time are most preferable for 19%, preferable for 17%, average for 23%, not preferable for 21%, and highly not preferable for 20%. Trustworthiness is an important aspect, and it is shown clearly that 38% of customers fall into the most preferable category, 32% into the preferable category, 18% into the average category, 8% into the not preferable category, and only 4% into the highly not preferable category. IV. RESULTS AND FINDINGS We typically recruit respondents who are predominantly male (70% of the sample), with 30% female. We conclude that 90% of persons have an online shopping Account or user ID, and 10% do not. We conclude that Most people engage in online shopping once a month and are not interested in doing so regularly. We conclude that most people spend between $2,000 and $5,000 on online shopping. We conclude that most people prefer cash-on-delivery payment. We conclude that most people do online grocery shopping rather than online clothing shopping. We conclude that most people use the site for online shopping, A Study of Customer Buying Behavior for Online Shopping with Special Reference to Electronic Goods 24 Published By: Lattice Science Publication (LSP) © Copyright: All rights reserved. Retrieval Number:100.1/ijef.A261805010525 DOI:10.54105/ijef.A2618.05021125 Journal Website: www.ijef.latticescipub.com with Flipkart being the most popular, followed by Amazon. We conclude that most people prefer social media to advertisements and the internet as sources of information about electronic brands. We conclude that most persons have an Average salary of 5000-10000. We conclude that most people purchase LG and then Samsung. We conclude that most people's concerns relate to website design and ease of use, which often arise during online shopping. We conclude that one product was purchased by the majority of customers in the year. In this research, we found that trustworthiness is the most critical aspect of electronic shopping behaviour. V. CONCLUSION AND SUGGESTION In this research, we identify various parameters that influence customers' online purchases of electronic goods, with trust acting as a mediator. Consumer behaviour in online shopping is a dynamic and intricate phenomenon that evolves alongside technological advances and shifting consumer preferences. The digital age has fundamentally altered how individuals engage with commerce, transforming purchasing habits, preferences, and decision-making processes. As the lines between the physical and virtual worlds increasingly blur, it is crucial to understand the factors driving online purchasing decisions, the importance of trust and convenience, the influence of social dynamics, the psychological underpinnings of decision-making, and the broader implications for business. By aligning their strategies with these evolving trends, companies can effectively navigate the digital landscape, crafting meaningful and satisfying experiences for today’s online consumers while solidifying their position in the ever-changing world of ecommerce. Through ongoing adaptation and a profound understanding of consumer behaviour, businesses can pave the way for sustained growth and long-term success in the dynamic and competitive realm of online shopping. LIMITATION A small or non-representative sample size may limit the generalizability of the findings. Research conducted in a specific region or culture may not apply to other contexts. The study may be limited by the time frame in which data was collected, making it challenging to capture long-term trends or changes. Reliance on self-reported data (e.g., surveys or interviews) may introduce biases, such as social desirability bias and recall inaccuracies. The availability or accessibility of technology may constrain the study. The research may focus on a narrow aspect of the topic, leaving other vital factors unexplored. The findings may not be generalisable to different settings, populations, or periods. Researcher bias or methodological flaws in data analysis may affect the accuracy of the results. Limited access to funding, tools, or expertise may restrict the depth or breadth of the research. Ethical considerations may limit the types of data that can be collected or the methods that can be used. The rapid evolution of technology and consumer behaviour may render findings outdated quickly. Cross-sectional studies may not capture changes in consumer behaviour over time. Findings may be specific to certain industries or product categories and may not apply universally. FUTURE SCOPE OF STUDY The future scope of study in online electronic shopping is vast, encompassing emerging technologies such as artificial intelligence (AI), augmented reality (AR), and the metaverse, which are reshaping consumer experiences. Research can explore the impact of sustainability and ethical consumerism, mobile commerce (m-commerce), and voice-activated shopping through intelligent assistants. Additionally, crosscultural comparisons, the role of social commerce and influencer marketing, and the psychological drivers of consumer behavior offer rich avenues for investigation. The integration of omnichannel retail strategies, the ethical implications of AI, and the long-term effects of global trends, such as the COVID-19 pandemic, also present significant opportunities for future research. Understanding these dynamics will help businesses adapt to evolving consumer preferences and technological advancements, ensuring sustained growth in the competitive e-commerce landscape. DECLARATION STATEMENT After aggregating input from all authors, I must verify the accuracy of the following information as the article's author. ▪ Conflicts of Interest/ Competing Interests: Based on my understanding, this article has no conflicts of interest. ▪ Funding Support: This article has not been funded by any organizations or agencies. This independence ensures that the research is conducted with objectivity and without any external influence. ▪ Ethical Approval and Consent to Participate: The content of this article does not necessitate ethical approval or consent to participate with supporting documentation. ▪ Data Access Statement and Material Availability: The adequate resources of this article are publicly accessible. ▪ Author's Contributions: The authorship of this article is contributed equally to all participating individuals. REFERENCES 1. Liang, T., and Lai, H. (2000). Electronic store design and consumer choice: An empirical study, Proceedings of the 33rd Hawaii International Conference on System Sciences. DOI: http://doi.org/10.1109/HICSS.2000.926863 2. Schubert, P. and Selz, D. (1999). Web Assessment: Measuring the effectiveness of electronic commerce sites beyond traditional marketing paradigms, in the proceedings of the 32nd Hawaii International Conference on System Sciences. 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More than 10 of his research papers/articles have been published in reputed research journals & News Paper. His research articles on management and commerce have also been published in several edited volumes. Dr. Dubey has received a grant of Rs. 2,00,000 from AICTE under the Conference scheme as a CoApplicant and Rs. 1,00,000 under the SPICES scheme. Dr. Dubey has been working in college service since 2014. Currently, he serves as an Associate Professor in the Management Department at the Modern Group of Institutions, Indore, affiliated with Devi Ahilya University, Indore. Dr. Rajeev Sharma is an associate professor at the Modern Institute of Pharmaceutical Sciences, handling core subjects like marketing management, product, and brand management for pharma products. He has over 20 years of experience in academics, industry, administration, and research. He has published various research papers in reputed UGC-listed, UGC-CARE, peer-reviewed journals, as well as in ABDC-, Web of Science- , PubMed-, Publons-, and Scopus-indexed journals. He has actively participated in numerous national and international conferences and workshops at prestigious institutions, including the Indian Institutes of Management (IIMs). Dr. Vandana Kanaskar was born on June 27, 1978, in Ujjain, Madhya Pradesh. She has completed her PhD from Dr A.P.J. Abdul Kalam University, Indore, Madhya Pradesh. Her specialisation areas include Finance, Business Mathematics, Management, etc. She has actively participated in more than 15 National and international conferences, seminars, and webinars. She has also presented research papers—more than 6 of which have been published in Reputable Journals and are indexed in Scopus. 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