Consumer behavior has dramatically shifted in the modern era, significantly due to the development of digital platforms and a recent rapid increase in e-commerce. From the traditional shopping mode to online retail, it introduced new opportunities and challenges that businesses have to face with consumers to attract as much as possible. This will be the difference between what influences consumer preference. Knowing that is key in a business operating within both traditional and online markets. Some of the demographic attributes that affect their buying behavior include; gender, age, income, level of education and occupation. Demographics often reveal ways in which the groups of consumers may respond to, as well as associate with a shopping site. For instance, younger customers with their sometimes more advanced skills in technology prefer online shopping sites because it is more convenient, diversified, and allows for easier comparisons. Older demographics, however, may still prefer a traditional platform because they enjoy the tactile experience while shopping and can inspect merchandise in person. Higher incomes tend to correlate as e-commerce attracts consumers with high disposable incomes because of the broad premium offerings and offers in this field. Education and occupation also go into shopping, which tends to favor people having higher education and a higher profession in favor of their convenience and efficiency.

This paper will examine how such demographic factors affect consumer preference towards traditional platforms versus e-commerce platforms in the emerging market of Telangana, India. This study aims to delve into the relationship between demographic characteristics and preferences for platforms so that businesses will know how to target their various segments of consumers appropriately. Such knowledge will help companies adapt marketing strategies, product offerings, and consumer engagement tactics according to the dynamic changes that both traditional and e-commerce retail face.

Huang et al. (2020) did a research titled "The Business Analysis of Home Bias in E-commerce Consumer Behavior.'' Research on Electronic Commerce This article examines customer behavior in Taiwan using a literature analysis and field research for both local and international e-commerce service providers. The empirical analysis is conducted using the survey. Results are 1. Consumers in Taiwan possess extensive online buying experience with both local and international e-commerce service providers. The purchasing behavior of domestic and crossborder e-commerce service providers is influenced by individual customer variables, including gender, age, daily web browsing duration, the engagement level of e-commerce websites or applications, and the frequency of repeat purchases based on the product category of acquired goods. 3. There may exist a home bias in consumer e-commerce: when a comparable product is offered by both domestic and cross-border e-commerce platforms, customers are more inclined to engage with domestic e-commerce service providers. 

Kalim Khan et al. (2020) conducted a study titled ‘Understanding the Multi-screening Phenomenon for Online Shopping through the Perspective of Self-Regulation and Dual Process Theory: Case of the Chinese Young Generation.’ The research aims to elucidate the sponsorship of multi-screening in online shopping through the lens of self-regulation by developing a dual self-regulation model system. The research used structural equation modeling (SEM) for analysis using the AMOS statistical software. The findings indicate that both conscious and unconscious self-regulatory variables influence the adoption of multi-screening in online buying, suggesting that both thoughtful and impulsive processes play a role in consumer decision-making in this environment. 

Rosário, A., & Raimundo, R. (2021). E-commerce refers to the buying and selling of products and services over the internet, including monetary and data exchange to finalize transactions. E-commerce is revolutionizing marketing methods with advanced technology, enhancing product knowledge and decision-making processes. Consequently, marketing strategies progressively need extensive data to comprehend client demands, prompting the inquiry into selecting the appropriate marketing approach to align with customer expectations. This literature study seeks to elucidate the current expansion of e-commerce literature and its relationship with consumer marketing strategy. Existing research has investigated the transformation in human interaction resulting from social network creation, mostly focusing on online and social media marketing, but also addressing aspects such as cost efficiency, information quality, and trust development in online purchase. Nonetheless, current research has not comprehensively shown all the study streams, their interactions, and the potential for knowledge advancement. Consequently, a literature study on consumer marketing strategies for e-commerce during the last decade is timely. This report seeks to delineate research trends in the domain by conducting a Systematic Bibliometric Literature Review (SBLR) on marketing strategy inside e-commerce. The study includes 66 papers published in the Scopus® database, offering current insights on the subject. The LRSB findings were integrated across existing study subthemes. The following results are delineated: In the present competitive global business landscape, companies typically adopt strategies for e-commerce and online enterprises that utilize e-commerce platforms and social networks to enhance consumer insights, optimize marketing strategies, and disseminate innovative information. The paper's uniqueness is based on its LRSB approach, along with an examination of previously uncategorized papers. 

Jain, Reetika. (2022). The last decade has seen a significant increase in internet purchasing among Indian customers. This is complemented by a significant proliferation of e-commerce platforms that address the varied demands of these consumers. However, many e-commerce platforms continue to dominate the industry while others rapidly decline. This research aims to examine the prevalent e-commerce platforms used by Indians in the areas of food, shopping, entertainment, and transportation (cab services). The research further examines the impact of demographic characteristics (gender and age) on the online buying behavior of Indian customers. A questionnaire based on an online survey was used to gather data from the respondents. Data analysis and hypothesis testing were conducted with the Chi-square test. Analysis indicated that age disparities significantly influenced the online buying behavior of customers in India, more so than gender inequalities. The results of this research will assist ecommerce platforms in formulating strategies to attract previously underserved age demographics in India, since an increasing number of customers are becoming adept at navigating, ordering, and buying via digital channels. Keywords: E-commerce platforms, online purchasing behavior, demography, Indian customers. 

Astuti et al. (2023). This study seeks to determine the impact of demography, user experience, and platforms on the digital business landscape. This study employs a Systematic Literature Review (SLR) methodology with a qualitative approach to systematically synthesize descriptive qualitative research findings. The study determined that comprehending and regulating the impact of demographics, user experience, and e-commerce platforms is essential for success in e-commerce management. E-commerce enterprises that comprehend the demographic traits of their clientele, provide an optimal user experience, and use suitable platforms are more likely to attain success in a dynamic market. Demographics assist ecommerce enterprises in formulating marketing strategies tailored to client tastes and requirements according to distinct demographic segments. The customer experience, including intuitive navigation, site speed, payment security, and effective customer service, significantly impacts consumer happiness, enabling organizations to comprehend user behavior and refine marketing plans. The selection of a platform is crucial in pivotal choices that affect the operations and success of digital enterprises. Ecommerce systems have several benefits, such as simple installation, robust security, and the integration of diverse payment options. In the fast evolving digital business landscape, comprehending and effectively managing the impact of demographics, user experience, and e-commerce platforms is essential for achieving competitive advantage. Digital enterprises who can modify their strategy based on client demographic traits, provide an exceptional user experience, and choose suitable platforms are more likely to attain sustained success in this evolving industry. Staying abreast of trends and fostering innovation is essential for attaining and sustaining a competitive edge in digital commerce. This study indicates a substantial correlation between demographics and user experience, since these three characteristics significantly affect consumer buying decisions by providing a comparative analysis of many elements of online transactions in the digital marketplace.

Nithya and colleagues (2024). Online shopping entails the acquisition of products and services from vendors operating on the internet. Consumers may access online retailers from the convenience of their residences while seated at their computers. The primary objective of this research is to identify the elements that affect customers' attitudes about e-commerce transactions via online purchasing. The study examines the influence of socio-demographic factors (age, income, and occupation), online purchasing patterns (types of goods, e-commerce experience, and internet usage duration), and purchase perceptions (product perception, customer service, and consumer risk) on consumers' attitudes towards online shopping. It analyzes how perceived risks, hedonic motivation, website design, and psychological factors, including trust and security, impact the buying behavior of online shoppers.  Shana Shaikh. (2024). The e-commerce business is now seeing significant growth and expansion via e-trading. The market is significantly influenced by the rapid growth of the Ecommerce industry. The reactions and buying behaviors of consumers dictate the success of ecommerce. The key to success lies in a modestly competitive business model, strategic pricing, and direct delivery to customers' doorsteps. Multiple studies indicate that this business has surpassed conventional marketing tactics by providing incentives to customers, resulting in a substantial rise in demand. Considering that ecommerce is producing substantial money from the Indian market, it is seen as a promising industry. The objective of this study is to analyze the existing body of information about e-commerce and related subjects. The primary subjects of the research are the status of e-commerce in India, the adoption of technology in ecommerce, the socioeconomic impacts of e-commerce, consumer buying choices related to ecommerce, and the benefits and successes of e-commerce. Technological breakthroughs emerge rapidly and are swiftly adopted by the market. As customers increasingly integrate technology into their life, their expectations may evolve. Consequently, innovations in ecommerce and its business model may account for changes in customer buying behaviors. This study seeks to understand the future need for research about the impact of e-commerce on consumer buying behavior and the extent to which purchase may be influenced. 

Chavi Sawhney and colleagues (2024). This research aims to examine the differences in customer behavior between conventional and internet shopping. The objective of this study proposal is to provide a comprehensive strategy for the proposed inquiry. This research project facilitated the collection of responses from 100 individuals, comprising 73 females and 27 males, aged 15 to 60 years. This data allowed us to analyze the disparities in consumer behavior between online and traditional shopping, specifically concerning the major product categories of clothing, footwear, accessories, groceries, food and beverages, electronics, and home décor and kitchen appliances. The survey indicates that, overall, the majority of individuals choose offline buying, despite the substantial and steady growth of online shopping trends. This is due to their perception of superior product quality in markets compared to internet purchasing platforms. The predominant payment method for internet buying was identified as digital wallets or UPI, whereas cash was the leading choice for offline purchasing, closely succeeded by UPI. Consequently, it can be inferred that the online payment method is predominantly favored by the majority of individuals in both online and offline buying contexts. It was shown that individuals increased their internet buying frequency during the Covid-19 epidemic. ''The most often purchased online product category was apparel, footwear, and accessories, followed by groceries and food and drinks. In conclusion, while both online and offline shopping possess distinct advantages and disadvantages, consumers generally favor offline shopping for most products." Various factors, including quality, pricing, variety, assistance, and convenience, contribute to the disparities in consumer behavior between online and traditional shopping methods. 

OBJECTIVES OF THE STUDY

The main objectives of the study are to analyze: 

• To analyze the effect of Gender, age, income, education level, and occupation on the consumer preference for the traditional platform.
• To analyze the effect of Gender, age, income, education level, and occupation on the consumer preference for the e-commerce site.

Research Method: 

A quantitative research design was utilized in this study, with descriptive and inferential statistical analysis.

Sampling and Data Collection:

A total of 200 respondents were covered and studied, through a structured questionnaire, to find out the data. The sample was randomly selected from various regions of Telangana, representing a diverse range of gender, age, income, education, and occupation. The survey aimed to study consumer preferences in favor of using traditional versus e-commerce platforms. To this end, questions were developed on demographic variables; gender, age, income, education, and occupation.

Data Analysis Techniques:

The data collected was analyzed using both descriptive and inferential statistical methods. To analyze the demographic profile and preference of respondents, descriptive statistics including frequency distributions, percentages, and means were calculated. Inferential statistics were also used to test the relationship between the demographic factors and the preferred platform. Following tests have been applied in this research work:

Chi-Square Test of Independence – To measure whether gender has a significant relationship with the type of preference between one having traditionally or through ecommerce.

ANOVA (One-way Analysis of Variance) – To check if age groups differ significantly concerning their preference between the traditional and e-commerce channels.

Kruskal-Wallis Test – If income groups can be said to be different in regard to preference among the two platforms.

Logistic Regression - To determine whether demographic variables like gender, age, income, education, and occupation would influence the propensity to have a preference for traditional platforms over e-commerce platforms.

Hypothesis of the Study: 

Null Hypothesis (H₀):

There is no significant influence of the factors like gender, age, income, educational level, and occupation on consumers in buying preference between the two forms of platform: the traditional one and e-commerce platform in Telangana.

Alternative Hypothesis(H₁):

Gender, age, income, level of education, and occupations have played a significant influence on the buying preferences regarding traditional versus e-commerce portals within Telangana.

Demographic Profile: 

Gender of the Respondents: 

Table 1: Gender Profile of the respondents

The gender profile of the respondents has a skewed sample, but it still is close, with more males. More than 56.5% identified themselves as males, represented by 113 participants, whereas females constituted about 43.5%, represented by 87. This therefore presents a moderate disparity in the study by gender, thus potentially illuminating how this gender difference could influence preferences between traditional and e-commerce platforms. This might mean that there is a difference in preferences, shopping behavior, or even online engagement between the two genders, and that could be a very important demographic consideration when analyzing platform choice.

Age of the Respondents: 

Table 1: Age Profile of the respondents

The age profile of the respondents is spread wide. The majority falls in the age group of 18-25 years, which amounts to 35.5%, followed by 26-35 years, 31.5%; 36-45 years, 22.5%; and 46 years and above, 10.5%. This is likely to be a young to middle-aged population that will be very active on both traditional and e-commerce platforms. The respondents aged 18-35 years may prefer e-commerce because they are more familiar with the digital platform, whereas older respondents may prefer more traditional shopping methods. This age breakdown provides a strong foundation to consider the impact of age on platform preference.

Education Level of the Respondents: 

Table 1: Education Level of the respondents

Educational background of respondents: Most of the respondents are educated to a high level. 36% are undergraduates, and 32.5% are postgraduates. Only 19.5% of the sample have a high school education, and 12% fall into other categories. It indicates that the people who are responding are generally educated and, therefore, may have a choice for the shopping platform. More educated people have more preference for online buying as they are more familiar with the tools and, in general, are research-oriented while shopping. Therefore, an important variable to look for is the educational background, which may influence the traditional mode or the e-commerce platforms in terms of their choice of buying.

Occupation status of the Respondents: 

Table 1: Occupation status of the respondents

Occupation-wise, the highest proportion is that of salaried employees, 46%, followed by 26% students, 16.5% self-employed, and others, like homemakers, making up the remaining 11.5%. High proportion of salaried employees is a population that is most likely to have regular, steady income and possibly prefers convenience and efficiency that makes e-commerce more appealing. Students also tend to be technophiles and would like to shop online. Therefore, this occupational composition indicates that occupation is one of the significant determinants of consumer buying behavior when it comes to the decision between the traditional and ecommerce platforms.

Income status of the Respondents: 

Table 1: Income status of the respondents

The income distribution also reveals that 39% of the respondents have an earning below ₹20,000, and 35.5% have ₹20,001 - ₹50,000. The number of respondents in the higher-income brackets is relatively less-15.5% are in the ₹50,001-₹1,00,000 bracket, and an even lower percentage is ₹1,00,000 and above, at 10%. The audience here clearly cuts across from middleclass to lower class, which could be having implications on their buying choices. Traditional choice, for example, may dominate within a lower-income group due to lower costs or limited online shopping penetration, while it's the e-commerce that appeals to higher-income individuals.

Influence of Age on Buying Preferences

Table 1: Influence of Age on Buying Preferences

It also is observed that data in statistics presents trends of preference in buying through ecommerce for the age groups- 18-25 and 26-35. In those age groups, 63% and 71%, respectively, preferred online shops. In contrast, the 36-45 and 46 and above age groups have a relatively balanced preference between traditional and e-commerce platforms, but a higher percentage of respondents in these groups prefer traditional shopping methods. The 46 and above age group also highly prefers traditional platforms at a whopping 40 percent level and may reflect the impact of familiarity and comfort in a conventional shopping method. Thus, age may play as a strong determinant to this preference for platforms, while young people have a disposition to e-commerce rather than their elderly counterparts, who prefer conventional ways of shopping.

Influence of Gender on Buying Preferences

Table 1: Influence of Gender on Buying Preferences

Buying preferences by gender indicate that both males and females have an inclination toward e-commerce. However, trends are marginally different for both sexes. Males have a more pronounced leaning toward e-commerce, with 59% having a preference for it compared to 45% of females. However, females tend to be more evenly spread in the distribution of preferences between the traditional and e-commerce channels, as 42% of females strongly prefer to shop on traditional channels. On the other hand, males have a near equal split, with 41% of males preferring traditional channels over e-commerce. This implies that even though both genders have a preference for e-commerce to some extent, women might still be more inclined toward traditional shopping experiences compared to men, who show a more balanced or even slightly stronger inclination toward e-commerce.

Influence of Education Level on Buying Preferences

Table 1: Influence of Education Level on Buying Preferences

Varied education levels of respondents show varied preferences for the traditional and ecommerce platforms. A good majority of respondents were postgraduates; of whom, 47% chose to favor the online purchase option followed by the strong 24% for choosing e-commerce. Respondents with minimal education also happen to like traditional. Some 39% of graduates from the high school category strongly choose the option to prefer their shopping mode over the use of any technology-based portal. These findings show that the achievement of education greatly determines one's preference for platforms, especially regarding e-commerce, because one with more education levels more likely performs e-commerce operations, while those with lower education levels may feel more comfortable with traditional shopping.

Influence of Occupation on Buying Preferences

Table 1: Influence of Occupation on Buying Preferences

The pattern of the employment of respondents regarding platform preference depicts a clear trend. Students (63%) and salaried employees (53%) favor platform preference. Students are more tech friendly and will likely be more comfortable with e-commerce, but salaried employees could appreciate saving time by shopping on the web. Self-employed workers (41%) are heavily inclined to using traditional markets, as this may serve their schedules or business-oriented needs. Homemakers (42%) also report a tendency toward traditional methods of shopping; this can be put down to familiarity or habit. Generally speaking, occupation really matters in the choice of which channel of shopping is more preferred. Students and employed workers rely so much more on e-commerce than all other groups do, although self-employed persons and homemakers report preferring the traditional channel.

Influence of Income on Buying Preferences

Table 1: Influence of Income on Buying Preferences

Income does matter also in platform preference, although marginally. Some 42% of respondents earning below ₹20,000 report a strong liking for the traditional channel, possibly because it offers more affordable, touch-and-feel shopping options. Those in the ₹20,001 - ₹50,000 income bracket show a more balanced preference, as 31% still prefers traditional shopping, but 40% shows a preference for e-commerce. Higher-income individuals above ₹50,000 prefer e-commerce, as evidenced by the 35% of respondents in this group showing a preference for e-commerce platforms. This suggests that income is an important determinant of preference toward platforms, so low-income earners remain highly preferential toward brick-and-mortar platforms, while high-income earners are more inclined toward e-commerce due to the convenience, variety, and access it presents.

Hypothesis Testing: 

Null Hypothesis (H₀):

There is no significant influence of the factors like gender, age, income, educational level, and occupation on consumers in buying preference between the two forms of platform: the traditional one and e-commerce platform in Telangana.

Alternative Hypothesis(H₁):

Gender, age, income, level of education, and occupations have played a significant influence on the buying preferences regarding traditional versus e-commerce portals within Telangana.

Chi-Square Test of Independence (Gender vs. Platform Preference):

Chi-Square Test was used to find out if gender had a significant association with preference for the type of platform, Traditional or e-commerce.

Table 5: Contingency Table for Gender and Platform Preference

Table 5: Chi-Square Test Results

The p-value is 0.963, which is larger than 0.05. Thus, no relationship between gender and preference for a platform exists. Fail to reject the null hypothesis. Gender does not significantly influence the preference for traditional or e-commerce platforms.

ANOVA (One-Way Analysis of Variance) (Age vs. Platform Preference):

An ANOVA was conducted to ascertain whether there is a difference in the preference scores for the different age groups (measured on a Likert scale from 1 to 5).

Table 7: Age vs. Platform Preference

Table 7: ANOVA Results

The p-value is 0.005, less than 0.05. This means that age has an effect on platform preference. The null hypothesis is rejected. Age has an effect on whether consumers prefer the traditional or e-commerce platforms.

Kruskal-Wallis Test (Income vs. Platform Preference):

A Kruskal-Wallis test was used to check whether the preference of people differed across various income groups when scaled on a Likert scale.

Table 8: Income vs. Platform Preference

Table 8: Kruskal-Wallis Test Results

The p-value was 0.459 which is more than.05. Hence, income shows a non-significant variation to affect the platform preference. Fail to reject null. Income does not prove as a significant variable toward a choice between the conventional platform and e-commerce or an online platform.

Logistic Regression (Demographic Factors vs. Platform Preference):

Logistic Regression was conducted to derive the impact of demographic factors, which include gender, age, income, education level, and occupation, to the possibility of preferring traditional over an e-commerce.

Table 8: Logistic Regression Results

The p-values for gender, age, income, and education all fall below 0.05. It means that these factors are significant in influencing preference towards traditional platforms. Reject the null hypothesis. The gender, income, and education influence the likelihood of preferring a traditional platform. The Odds Ratios imply:

Men are 1.57 times more likely to have a preference for traditional compared to women.

Those coming in the category of more money ₹50, 001-₹1, 00,000/- will have a preference toward the traditional platform 1.82 times Graduate/postgraduates have 1.28 times the chance to be inclined towards the use of traditional platforms

This research depicts the strong influence of many demographic factors on the preference of consumers between traditional and e-commerce platforms in Telangana. Platform preference was influenced by gender, age, income, and education, but gender and income had a stronger influence on it. The preferences of males, people with higher incomes, and postgraduate holders were higher on traditional platforms. Moreover, age has also been a critical determinant in shaping preferences, as younger consumers between 18 and 25 are more likely to prefer ecommerce platforms, whereas the older age groups are more likely to prefer traditional methods of shopping. The outcome suggests that demographics are important in understanding consumer behavior in the region, which may be helpful for businesses that want to tailor their marketing strategies to different consumer segments.

However, it also showed that some variables, such as income, had no effect on platform choice when tested with the Kruskal-Wallis test. Nevertheless, the overall trend indicates that businesses should pay attention to demographic factors in devising strategies for both traditional and e-commerce platforms. It will enable companies to increase customer engagement, tailor offerings to specific groups, and fine-tune the customer experience along different demographics. In conclusion, demographic variables, especially gender, age, income, and education, play a critical role in shaping consumer preferences in Telangana, and being aware of these differences could guide businesses to effectively reach their desired audiences.

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