INTRODUCTION

In recent years, analyzing and learning consumer behavior has been crucial for an organization's offline or online success (Kapuria & Nalawade, 2021). Consumers are the only factor that drives the market. All corporate activities are conducted with considering the customer’s interests in mind (Sarkar & Das, 2017). Traditional shopping is the process of selling, buying, or exchanging goods; information or services are physically possible in a physical store (Balaji & Murugavel, 2022). Otherwise, offline or traditional shopping refers to anyone visiting a shop, mall, or store and purchasing anything they require (Vora, 2018).

With the advancement of novel thoughts, offline retail businesses have had a sturdy demand for internet transformation. In the omnichannel market, offline, online interconnection, and closed-loop consumption are taking shape (Wang et al., 2021). The altering tastes of customers, rising revenue levels, rising mobile usage, and broader access to digital media substantially impact the Indian retail industry’s dynamics (Halan & Singh, 2023).

E-commerce in India is anticipated to attain Rs.2,000 billion by the year 2023, mainly driven by classifications like electronics and fashion (Sudhakar Shukla, 2021). Comparing online to offline (O2O) and business to consumer attracts probable consumers by bridging the gap between the online platform and physical store (Ryu et al., 2022), which allows customers to experience physical products in brick-and-mortar stores and then pay and buy the product online (Wang et al., 2021).

Some existing researchers have developed an O2O model to bridge the gap between online platforms and physical stores (Kim et al., 2022). The O2O model is not an easy integration of offline and online, yet it is an organic integration (Chai et al., 2021; Wang et al., 2021). Many businesses must build a seamless experience between offline and online interactions to retain and attract customers (Shen et al., 2019).

The rising penetration of smartphones and the internet and altering customer preferences have been the primary drivers of this development. Offline stores and online platforms operate separately and cannot cooperate, which fails to offer seamless service for customers (Chen et al., 2019). Some studies on the O2O model have recently prevailed, including consumer purchase and return policies, service quality, and supply chain management (Kim et al., 2022; Shi et al., 2019). With the fast improvement of e-commerce, customers are entering a multichannel period (Du et al., 2019).

The studies on multichannel management, showrooming, and free-rising represent the most customers turning into cross-channel purchasers, and the influencing aspects are assessed by integrating offline and online channels (Swoboda & Winters, 2021). As the O2O model combines offline and online, it is essential to comprehend how customers consider the offline and online influencing aspects to coordinate offline stores with online platforms (Vinhas & Gibbs, 2018). Offline retail businesses experience extreme competition from several sources because of increased online shopping. The menace of online shopping relates to all small start-up companies and large organizations (Lee et al., 2022). Just because an organization is an industry leader currently, there is no assurance that it will retain its competitive edge in the future (Lumadi, 2014). The menace of online shopping is more significant, particularly for traditional businesses unprepared to embrace the altering commercial landscape (Kaushik et al., 2020). All retail sectors must consider the challenges they face in their market growth (Kamalesh, 2023).

The pandemic increased online sales and led to faster development in online shopping, but it also hindered the offline sales of traditional businesses (Siddiqui & Mehrotra, 2021). Online shopping’s success became a drawback for conventional shopping in some areas. Online shopping has advantages and disadvantages that are the same as those of traditional retail businesses. A mix of price, convenience, quality, and lack of time alters how customers shop in India (Ahlawat et al., 2022).

Most older people in India prefer traditional retail shopping due to the need for more awareness of the online platform and the lack of trust and security. The conventional shopping procedure, where individuals swift through goods and feel the textures and colors feel them can be greatly enjoyable (Jain, 2014). Also, shopping in India is well-known for the time a family spends together, such as an outing on holidays or weekends (Halan & Singh, 2023).

The entire family goes together, does some shopping, catches movies, and eats in a restaurant. It is practically a family get-together on any day, but it is not probable due to the family members’ hectic work schedules (Billings, 2024). However, these experiences cannot be experienced through online shopping. One can purchase any product more easily online, and the experience of spending the most valuable time with one's family cannot be simulated by oneself (Sarkar & Das, 2017).

Regardless of the relevance of customer offline behavior and online attitudes, most studies have yet to enlarge beyond online behavior and online attitude into offline behavior (Bhat et al., 2020). Only some studies have tried to explore the offline behavioral intention of customers from Tamil Nadu (Kang et al., 2018). The counting to retail spaces in Tamil Nadu has its innate cultural purchasing strategies in markets. The necessity of regulating commodity costs and prices is also evident in the postulate of well-established offline retailing procedures in stores in the Tamil Nadu region. Therefore, the study aims to study the Influence of online shopping on offline traditional retail businesses in Tamil Nadu.

PROBLEM STATEMENT

In recent years, many Tamil Nadu retailers have faced many issues with online shopping; it has significantly influenced the retail business and the economic growth in the Tamil Nadu area. Consumers are altering business regulations, and retailers should adapt to them. Retailers, thus, must meet changing consumer demands in physical stores and online through the related novel solutions and the combination of offline and online shopping experiences (Ponraj, 2019). Online shopping positively and negatively impact traditional stores (Gupta, 2020). It is dramatically considered that conventional retail shops in Tamil Nadu must increase their share gain, keep their customers happy, and, in the meantime, look to attain maximum profit.

Nevertheless, online shopping helps to develop traditional businesses into the online business world, which promotes financial benefits (Kumar & Ayodeji, 2021). However, some conventional businesses experience heavy losses in their profitability because of the evolution of online shopping. Ultimately, retailers from varied districts in Tamil Nadu appear to be rationally confined to the prospective adoption of online business patterns. Since intense attraction to shopping motives also demands the traditional business pattern, adopting online practices may require high-cost facilitations and will be overwhelming for small retailers. So, some conventional retailers might even go out of business.

Because of online shopping, traditional offline retailers experience problems such as decreased profit, reduced sales volume, FDI investment, maintaining various stocks, 24/7 services, the arrival of technologies, and various payment methods . Thus, the present study analyzes the Influence of online shopping on traditional retail businesses.

SIGNIFICANCE OF STUDY

The study provides insights into the influence of digital shopping on the traditional retail business. Product diversity, trust, convenience, psychological factors, and payment methods influence customers to opt for online and offline shopping. Procurement of services or products over the internet, online shopping has gained massive popularity in recent years, primarily due to individuals find it easy and convenient to purchase from the comfort of their office or home and also relieved from the troubles of going from one shop to another in pursuit of good quality.

The arrival of technological advances and the internet has been both a boon and a bane to traditional retailers (Banerjee, 2019). Those who want to expand their business to the next level adopt an online shopping method to fulfill the consumers' requirements and attract and retain existing customers. The study also analyzes the various factors influencing online and offline shopping. The study has highlighted several factors affecting traditional retailers, like a decrease in profit, reduced sales volume, a decrease in customer base, etc.

Research objectives

• To assess the factors that influence consumers towards offline purchases.

• To evaluate the various benefits derived by consumers inclined to shop online.

• To examine the retailer's opinion towards traditional retailing and online shopping.

Research Hypothesis

H11: Online shopping is more prevalent among consumers in Tamil Nadu

H10: Online shopping is not commonplace among consumers in Tamil Nadu

H21: Digital marketing has a significant impact on traditional retail marketing in Tamil Nadu

H20: Digital marketing has no significant effect on traditional retail marketing in Tamil Nadu

H31: There is a significant association between issues of online shopping and consumer behavior

H30: There is no significant association between issues of online shopping and consumer behavior

H41: Socio-economic and psychological factors have a significant impact on traditional retail marketing

H40: Socio-economic and psychological factors do not have a significant impact on traditional retail marketing

The paper is organized in the following order: Section 1 provides an elaborate introduction regarding the Influence of digital shopping applications among traditional retailers in Tamil Nadu. Furthermore, the introduction section illustrates the significance of the research. In section 2, prevailing research works related to the current study will be reviewed. The current study’s research methodology will be elucidated in section 3. In section 4, the outcome of the analysis will be discussed. In section 5, the outcome of the analysis will be addressed with existing studies. Finally, in section 6, the brief conclusion regarding the current research will be discussed along with limitations and future recommendations of the study.

LITERATURE REVIEW

Factors influencing offline and online purchase

Behavior of consumers is the study of how people use and select a product or service and also considers the motivations, psychology, and behavioral traits. The research aimed to discover the diverse aspects and their impacts on the customer's procurement pattern for readymade garments in online and offline modes of shopping. The study was conducted using qualitative analysis based on secondary data.

The research exposed that the primary aspects are psychological, economic, cultural, and social factors that affect the buying patterns of consumers. The results would support traditional retailers of readymade garments and online shopping sites in considering all the other aspects when farming the marketing strategies to satisfy their consumers and attain marketing objectives. Also, the study concluded that the buying pattern alters a person's life cycle in the circumstances of garments. Also, the study stated that peer groups and family references impact an individual's purchasing behavior.

Demographic and socioeconomic aspects also contribute to the improvement of modern retail formats. The main goal of the research (Upadhyay, 2015) was to study the impacts of socioeconomic aspects on the buying patterns of urban youth in the retail market. The study used purposive sampling methods and the non-probability judgment sampling approach. In this sampling method, the scholar selects a sample from the set population that the researcher considers to represent the total population. The study used primary data and employed a structured questionnaire method to collect data. The data was collected from 300 participants, which was considered essential and valuable since it contained all applicable information required to fulfill the aim of the study. The study was based on the exploratory study model in which the effects of socioeconomic aspects on the purchase patterns of urban youth in the retail market are enquired about.

The entire shopping concept has undergone a sea alteration in customer buying behavior and format, ushering in a shopping behavior revolution in India. The study (Jain, 2014 ) compared the diverse aspects that affect the customers’ buying behavior regarding purchases from an unorganized or organized retail outlet in Rajasthan. The current study empirically analyzed the buying behavior of unorganized and organized retail consumers in Rajasthan. The study collected responses from 400 consumers, of which 200 were taken from unorganized and the other 200 from organized retail outlets.

The survey was conducted in Ajmer, Jaipur City, Jodhpur, Kota, and Udaipur. The study of retail consumers’ purchase behavior states that critical buying decision influencers shape consumers' preferences regarding what to purchase and where. The study identified that unorganized retail has many advantages, such as home delivery, credit facility, and availability of petty and small things, but is deprived of various fronts like an attractive image of the store, convenience when shopping, and great ambiance and so on. The study suggested that these are all reasons for the organized and unorganized retail outlets required to develop on several fronts.

Economic impact of online and offline shopping

Online shopping is a new, convenient way of shopping (Reddy, 2015). The study aimed to identify the impacts of online shopping on the real economy. The study identified four negative impacts. The first one includes the lower cost of online stores, which would enhance the bankruptcy of medium and small-sized businesses. The second one, online stores, has a low demand for entity shops that would affect the real estate industries. Third, the staff waste rate in online shops is higher. Lastly, they can lower the product price due to the lower cost of online shops. Certain retailers would keep lowering the product prices to attract more customers, leading to market competition.

One of the fast-developing sectors in India is the retail sector. It is the economy’s backbone and around 10% of the nation’s GDP. The study aimed to comprehend a consumer's perspective on the COVID-19 impact on offline traditional shopping. The study used a structured questionnaire to administer responses and gather reliable information. The study collected 100 responses, in which 50 females and 50 males from diverse age groups were selected.

The study stated that to survive in the market, the transformation of offline traditional trade or shopping to online is one of the aspects that has grasped attention worldwide. Online shopping was improved during COVID-19, and there are opportunities for buyers and sellers to identify a novel way to buy and sell their services and products. Online shopping uses the gains of the internet for an economical and faster way to do business during the pandemic.

Influence of online shopping on traditional retailers

Online business has transformed the business simulation and altered how consumers approach retail. Despite its momentous impact on shopping behavior, e-commerce is simply an evolution. Several manufacturers and retailers have quickly identified the various opportunities created by new technology.

The study aimed to examine the opinion of the retailers towards online shopping as well as their demographic profile. Fastness is not the success of online marketing; it is the size, brands, variety, and cheap cost. These factors are offered to the consumer once rather than in the subsequent purchase. All these aspects are to be valued by the consumers occasionally when they buy the product. The study discovered that online marketing retailers proved competitive and diligent in breaking people’s traditional shopping habits. The study suggested that if the sustained tactics are boosted with sufficient modification, the business will grow into a million-dollar business in the upcoming years.

The marketing standards have achieved a paradigm swing with the involvement of technology in marketing products and services. The marketing procedure has wholly moved from traditional logistics to modern logistics. The objective (Aashirwad, 2022) was to explore the effect produced by online marketing on traditional retail textile stores in the study area.

The traditional retail textile shop owners in Chennai were considered for data collection for the study. There are two basic techniques for sampling: non-probability and probability sampling. There has yet to be a definite list of individuals for textile retailers in Chennai. Therefore, it was decided to choose a store from the taluks randomly.

The study was conducted based on the sample size of 320 retail textile stores and grounded on that to have a geographic representation of the chosen district; the sample was distributed amongst an equal distribution of textile stores based on several taluks from every income division of Chennai. The study made several recommendations that may aid in enhancing the position of textile retailers in the market. The study suggested many strategies, and adopting some will encourage textile retailers to improve their business opportunities for a long duration while enduring the effects of online marketing.

In the past ten years, the internet has changed the method of buying and selling products and services. The study aimed to comprehend the effects of online shopping on retail trade-in Tirunelveli. The study’s population includes online shoppers and retailers in Tirunelveli district. Retailers belong to various industries like jewelry, consumer goods, textiles, books, the service sector, technological goods, etc. The size of the study population is unknown and cannot be defined in precise numbers.

The researcher used a sample survey method. Retailers are facing a tough time enduring the effects of online shopping trends spreading like a virus among most people in the nation. Therefore, retailers have to manage the current distraction from digital technologies and prioritize investment in technologies that will add value for the customers or enhance the efficiency of the functions. Both retail and e-stores have to survive in their method. They both offer livelihood to thousands of individuals.

The retail industry in India has developed into the most fast-paced and dynamic industry because of the arrival of various new players. The study aimed to explore the opinion of retailers towards online shopping and traditional retailing. The study also intended to test the significance and relationship between the perception of traditional retailers and online shoppers. The study used a structured questionnaire to collect data from 384 respondents.

The retailers functioning with multiple and single brands are satisfied with the several tactics created by the online companies, shopping pleasure, quality guarantee, deprived of hygiene in traditional shopping, ethics of business is followed, facilities prepared over affirmative, variety, contiguity, reduction and destructive have high impacts on online shopping. The study identified other benefits such as image, value, expectation, service, quality, loyalty, and satisfaction that substantially impacted traditional shopping over online shopping. Therefore, the study stated that customers are more enlightened and happier with online purchases than with offline shopping.

The dynamics of the retail industry in India are substantially influenced by altering consumer tastes, increasing income levels, broad access to digital media, and rising usage of mobile. The study (Sudhakar Shukla, 2021) aimed to analyze the impacts of online shopping over traditional offline retail shops in the electronic products sector. The study used a structured questionnaire to collect data grounded on general knowledge and theory; the scholar framed the questionnaire. The retail industry can adapt to altering trends and comprehend the customers’ mentality, which will become a successful investment. In contrast, others who ignore understanding the customers’ mindset might risk losing a substantial amount of enterprise.

Research Gap

The retail industry in India has 12 million outlets, the largest in the world. The study's limitations are that the respondents were unwilling to provide actual information and needed to gain awareness of some features. The restriction to keep the questionnaire concise has limited the study in some features. Also, the study area was limited to only a few cities in the Tamil Nadu district, which led to a limitation.

RESEARCH METHODOLOGY

Research Design

The current research is reliant on empirical as well as descriptive studies. The research embraces the quantitative analysis technique and practices the primary data. The primary data collection was accomplished by surveying with questionnaires, and then the gathered data was analyzed using the SPSS tool. The data will be collected from the retail shop owners. The primary data collected is nearly 100 from the owners of traditional retail businesses.

The primary stage of the research design identifies the variables that contributed to the impacts of online shopping. The factors influencing offline and online shopping were explained. The research by design is quantitative and exploratory, seeking to uncover the underlying impacts of online shopping, not traditional retail business. All the positive and negative factors were considered in the study.

The data is gathered from the retailers. Establishing the relationship and link between the variables selected in this study is performed by implementing ANOVA evaluation, correlation, frequency of the variables, and regression evaluation. The process included in the study is illustrated in Figure 1. The independent variables of Growth, Challenges, economic impact, and online marketing are considered. The dependent variables are online shopping and Offline shopping.

Data Collection Strategy and Participants

The most crucial stage of research is the data collection process. This emphasizes the research objectives to increase logical knowledge of research questions. The primary responsibility of a researcher is to select a suitable data collection method. Data has been collected from 100 retailers to analyze the impact of online shopping on traditional retail businesses. The data was collected from retailers who face challenges due to online shopping.

Data Sampling and Sample Size

The judgment sampling method was used to select the sample from the population. The current study utilizes the Judgment sampling approach in the primary data and secondary data sources, a non-probability sampling technique where the researcher decides who must be combined or obtained as the sample regarding his knowledge and judgment (Thomas, 2022).

The respondent's selection process is expected to provide beneficial information for the research. The main reason for using a purposive sampling strategy is because the statement is constructed based on the research objectives, and specific people may provide substantial views needed for the research questions. Thus, it is required to be combined into the sample (Denieffe, 2020). The samples under this purposive sampling approach are obtained from 100 retailers.

Sample Size

The valuable respondents for the survey were filtered using purposive sampling methods. The sample size for the research is 100 retailers from various sectors were considered. After collecting the data, it is fed as different variables and assessed through the SPSS tool to accomplish the research aim.

Research Instrument

The research tools are employed in education, health sciences, and social sciences to monitor scholars and clients. The probable research uses a structured questionnaire from numerous respondents. The instrument utilized in the study is the structured questionnaire, which is revealed as the survey questions. Questionnaires were designed and distributed to retailers of the traditional retail business. Every sample possesses the same probability as other research samples to be chosen, representing the whole population.

Data analysis

Quantitative analysis is designated as a systematic phenomenon through congregating data and executing computational, mathematical, and statistical approaches (Jung, 2019). The quantitative approach congregated data from prospective and conventional management employees with sampling tools and provided online surveys, polls, etc. The outcome of the quantitative method is determined numerically. The numerical values are interpreted, and the upcoming research is predicted along with appropriate changes.

The quantitative data analysis method analyzes data gathered using structured questionnaires from sample respondents. The data are recorded using an Excel sheet to reveal study variables. The software tool SPSS analyzes the study variables in the Excel sheet. The study's outcome is estimated using five approaches: ANOVA, Reliability, Correlation, Coefficient, and Frequency.

The given techniques will be applied to identify the data and verify the association between the study variables of the current research. Based on the outcome of the study variable, interpretations will be conducted, and essential development will be recommended for the current study. With the help of SPSS software, the outcome of the current research will be efficient for documenting the study variables. The result of the variables’ frequency will be demonstrated in the figures and table. In contrast, correlation, ANOVA, and regression evaluations will be conducted to assess the current study's structured hypothesis.

Many researchers utilize SPSS software to analyze both quantitative and qualitative data. The software will perform various text analysis, descriptive statistical analysis, data integration, open-source extensibility, and machine learning algorithms. SPSS software will be used to analyze empirical and qualitative data along with the congregated data from the targeted participants. The software will convert and cover the scale of the questions. This software will aid the researchers in enhancing the projects, identifying the study problem, and providing solutions for the identified issues through statistical analysis. Moreover, this software tests the study’s hypothesis and assumes the statistical effect among the study variables. Therefore, the current study will utilize SPSS software to analyze the study's test hypothesis.

Ethical considerations

Certain ethics will be followed while conducting the research analysis as the study is based on the Influence of online shopping on traditional retail businesses. There are various factors influencing online and offline shopping. The morals followed in the study are before the researcher's survey evaluation, and data is passed to the participants in the prior phase. The participants are not forced by any means to give their responses. Only those who were willing to respond were selected for the survey analysis. Only the responses to the questionnaire are asked of the participants, and their private data or reports are not forced to be exposed by them. Since the study uses primary data for data analysis, it contains no false data. All the data gathered and organized would be kept highly confidential. These are the ethical considerations used by the scholar for the study analysis, which is accurate to their knowledge based upon this research study.

RESULTS

The data collected via survey questionnaires were examined with the software tool SPSS and analyzed for outcomes based on the variables used in the study. The results satisfy the objectives of the study through the research design. Moreover, a detailed analysis of the responses based on the different demographies is performed.

Graph 1 illustrates the age group of the participants. Several respondents are in the 36-45 age group. This group contributes more to the research study. Such a group has updated its knowledge of online shopping applications, enhancing the research to be more precise and accurate.

Graph 2 illustrates the gender of the participants. Most of the respondents are male. This group contributes more to the research study. Their contribution enhances the research to be more precise and accurate. In total, 94% of the respondents are male community. One of the prospective reasons for its majority of males is cultural significance since this research attempted to indicate the sort of Tamil Nadu conductance and the retail establishment of shopping chiefly depended on males more than females in the selected region. While adapting to local retailers from South Indian districts, the Tamil Nadu region contributed to increased male persons in the retail business. Hence, it shows a more significant difference in male dominance in gender groups.

The educational background of the retailers is analyzed. Nearly 33% of the respondents need to be more literate. 43% of respondents completed the undergraduate degree. Only 7% of the respondents are postgraduates. Undergraduate retailers contributed more to the research (Table 2).

Hypothesis 1

Frequency testing

It is utilized to identify the number of occurrences of specific variables and measure the reliability of prediction.

Table 3 illustrates the competitors of retailers in Tamil Nadu. Most of the respondents agree that online retailers are their competitors. The perception of retailers is depicted through frequency analysis. It has comprehended the relevance of undertaken cases and their validated conditions over offline and online retailing approaches, wherein the depiction of offline retail methods, including neighboring shops, shopping malls, and executive showrooms, were added, and aside from it, online retailers were moderately considered. The concluded quantified results have determined that hypothesis 1 has proven favorable.

H11: The above analysis proves that online shopping is more prevalent among consumers in Tamil Nadu, and the null hypothesis has been rejected.

Hypothesis 2

One-way ANOVA Test

It is utilized to determine the impact of independent factors and research objectives on dependent variables and to investigate variation (Liang et al., 2019).

Table 4 illustrates the impact of digital marketing on traditional retailers in Tamil Nadu. The one-way ANOVA outcome proves that most retailers agreed regarding the impact of online marketing on traditional retailers. Table 5 demonstrates the outcome of the ANOVA test. The outcome illustrates the p-value of .000, proving a noteworthy influence among digital marketing and traditional retailers.

Table 5 demonstrates the outcome of the ANOVA test. The outcome illustrates the p-value of .000, proving a noteworthy influence among digital marketing and traditional retailers. The numerical demonstration shows the significant relationship between online retail evolution and conventional retail techniques. The contemplation on marketing-based stratagems, the aspect with a prevailing retail approach, determined a higher efficacy and viable association along the nature of online retailers. So, it is conceived that digital marketing attributes will considerately influence the facets of traditional tactics that ensue in marketing procedures. Meanwhile, the test results from one-way ANOVA estimations have rejected the null hypothesis.

H21: The above analysis proves that digital marketing significantly impacts traditional retail marketing in Tamil Nadu, and the null hypothesis has been rejected.

Hypothesis 3

Correlation

The Pearson correlation method assesses the association between two study variables. The correlation value decides the association between the variables. If the correlation value is 1 or -1, it is considered to have an association between the variables. Hence, the present study utilizes the Pearson correlation to determine the significant association between online shopping issues and consumer behavior.

Table 6 illustrates the outcome of the correlation test for determining the association between digital marketing issues and consumers' purchasing patterns in Tamil Nadu. The p-value of correlation is .000, and the correlation value is positive, demonstrating the association between the two study variables. The outcome of the correlation test proves a significant association between digital marketing issues and consumers' purchasing patterns in Tamil Nadu. It has been recognized that the entrusted features of customers’ purchasing behavior are dependable while endorsing online shopping procedures in retail. Also, the signified interventional cause occurs because they lack reliable choice in customer preferences rather than offline marketing. Hence, the outcome rejects the null hypothesis.

H31: The above analysis proves a significant association between online shopping and consumer behavior.

Hypothesis 4

Table 7 demonstrates the outcome of the ANOVA test. The outcome illustrates that the p-value is .000, which proves the significant impact of socioeconomic and psychological factors on traditional retailers. Factors such as the lowest price, laziness, and status in online shopping influence the consumer to prefer online shopping over conventional retail shopping. At this moment, the perplexing characteristics of consumer behavior toward shopping preferences and economic aspects are also conceived as a significant impact factor on the positive effect of the traditional practices followed in retail marketing. The obtained outcome of one-way ANOVA evidenced that the null hypothesis had been rejected.

H41: The above analysis proves that socio-economic and psychological factors significantly impact traditional retail marketing.

DISCUSSION

Numerous researchers have congregated several factors in proposing the influence of the online shopping process on the retail business and screening traditional retailers' statuses involving customer insights. Remarkably, the current study’s outcome proves that online marketing influences the growth and profitability of traditional retailers by quantifying analysis tests. The subsequent test analyses, such as Correlation and ANOVA testing, demonstrate the significant association between challenges of online marketing and purchasing patterns among the consumers in Tamil Nadu. While contemplating customer satisfaction, the present study also highlights the socioeconomic and psychological factors that significantly impact consumers' purchasing intention in Tamil Nadu.

Nevertheless, the existing study (Maiti, 2021) analyses the primary aspects, which are psychological, economic, cultural, and social factors that affect the buying patterns of consumers. In the present research work, the denoted dependencies may oscillate the consumers’ buying preferences by online shopping initiatives. The results would support traditional retailers of readymade garments and online shopping sites in considering all the other aspects when farming the marketing strategies to satisfy their consumers and attain marketing objectives. Likewise, the present study concludes that socioeconomic and psychological factors influence the growth of traditional retail marketing in Tamil Nadu.

Similarly, the existing study (Jain, 2014) concludes that traditional retail has many advantages, such as home delivery, credit facilities, and availability of petty and small things, but is deprived of various fronts like an attractive image of the store, convenience when shopping, and great ambiance—the consumer behavior changes according to the challenges faced in the online marketing. The present study also acknowledges the challenges of online marketing and the fact that consumer intention will change due to the issues in digital marketing. The terminated results also indicated the limiting effects compared to traditional retailing strategies in markets.

Likewise, the existing study (Sudhakar Shukla, 2021) analyses the impacts of online shopping over traditional offline retail shops in the electronic products sector. However, the present research attempted to prioritize configured-based observation to elucidate the diverse perceptions for purposing broadened consideration. From the research’s analysis delivery, the conventional study recommends that the retail industry adapts to altering trends and comprehend the customers’ mentality, which will become a successful investment to enhance the business's profitability. The present study also recommends overcoming the challenges of the traditional retail industry and offering more beneficiaries to consumers, which will pave the way to compete in online retail marketing.

Limitation

The study's chief constraint is that the research participants are from Tamil Nadu. Hence, the consequences might lack generalizability. Human activities are an ever-changing module that cannot remain constant. Therefore, the study's outcome continuously varies with the modifications in consumer behavior. However, the inference provided by the research can be valuable in improving the marketing strategies of the traditional retail industry.

CONCLUSIONS

Online shopping has increased tremendously in the past few years, and most of the populace has become online buyers. Digital shopping has achieved speedy growth in India. It saves both time and money. The present study analyses the Influence of online retail shopping on the traditional retail industry in Tamil Nadu. Digital shopping affects the growth of the conventional retail sector. Several factors influence consumers to prefer online marketing rather than physical shopping.

The technology revolution has transformed the consumers' purchasing of products online. Even though online retail marketing has numerous beneficiaries, it also has the risk of fraudulent, insecure transactions, refund issues, and the inability to touch the products physically. Traditional retailers should focus on the challenges of online retail marketing. Retailers should adopt innovative technologies in their retail industry to attract consumers. The present study also recommends that traditional retailers improve their strategies for tackling the issues faced in digital shopping. This paves the way for online retail marketers to compete.

REFERENCES

Aashirwad, G. (2022). A Study on Impact of Online Marketing on Retail Textile Shops A Study with Special Reference to Chennai City. Bharath University. Link: http://hdl.handle.net/10603/437813

Ahlawat, P. K., Kumar, P., & Kumar, P. (2022). Antecedents of customers' attitude and intention towards online shopping of apparel in India. International Journal of Indian Culture and Business Management, 26(4), 460-484. https://doi.org/10.1504/IJICBM.2022.125216

Balaji, k. & Murugavel, R. (2022). A comparative study on digital shopping vs traditional shopping with special reference to Chennai city. https://doi.org/10.13140/RG.2.2.13518.64323

Banerjee, M. (2019). Development of Omnichannel in India: Retail Landscape, Drivers and Challenges. In: Piotrowicz, W., Cuthbertson, R. (eds) Exploring Omnichannel Retailing. Springer, Cham. https://doi.org/10.1007/978-3-319-98273-1_6

Bhat, S. A., Darzi, M., & Bhat, S. (2020). Sustainable business model in B2C online retailing: An Indian consumer perspective. In Technological innovations for sustainability and business growth (pp. 147-185). IGI Global. https://doi.org/10.4018/978-1-5225-9940-1.ch009

Billings, J. (2024). 0338 Consolidated Work Schedule: The Impact on Firefighters’ Sleep and Health. Sleep, 47 (Supplement_1), A145-A145. https://doi.org/10.1093/sleep/zsae067.0338

Chai, L., Duan, Y., & Huo, J. (2021). Pricing strategies for O2O business model considering service spillover and power structures. International Transactions in Operational Research, 28(4), 1978-2001. https://doi.org/10.1111/itor.12863

Chen, C., Hsiao, K., & Hsieh, C. (2019). Understanding usage transfer behavior of two way O2O services. Computers in Human Behavior, 100, 184-191. https://doi.org/10.1016/j.chb.2018.07.009

Denieffe, S. (2020). Commentary: Purposive sampling: complex or simple? Research case examples. Journal of Research in Nursing: JRN, 25(8), 662. https://doi.org/10.1177/17449871209281

Du, S., Wang, L., & Hu, L. (2019). Omnichannel management with consumer disappointment aversion. International Journal of Production Economics, 215, 84-101. https://doi.org/10.1016/j.ijpe.2018.05.002

Gupta, D. (2020). Digital Platforms and E-Commerce in India–Challenges and Opportunities. Available at SSRN 3577285. http://dx.doi.org/10.2139/ssrn.3577285

Halan, D., & Singh, E. P. (2023). Enemies to frenemies: coopetition between online and offline retailers amidst crises. International Journal of Retail & Distribution Management, 51(4), 425-443. https://doi.org/10.1108/IJRDM-06-2022-0208

Jain, A. (2014). A Study of Factor Influencing Retail Purchase Behaviour: A Comparative Analysis of Buyers of Organized and Unorganized Retailing in Rajasthan. The IIS University

Jung, Y. M. (2019). Data analysis in quantitative research. In Pranee Liamputtong (ed.), Handbook of Research Methods in Health Social Sciences. Springer Singapore. pp. 955-969. https://doi.org/10.1007/978-981-10-5251-4_109

Kamalesh, S. (2023). Impact of E-commerce on Traditional Business in India. International Journal of Creative Research Thoughts, 11, https://ijcrt.org/papers/IJCRT2304234.pdf

Kang, J., Lee, H., & Namkung, Y. (2018). The impact of restaurant patrons’ flow experience on SNS satisfaction and offline purchase intentions. International Journal of Contemporary Hospitality Management, 30(2), 797-816. https://doi.org/10.1108/IJCHM-09-2016-0537

Kapuria, P., & Nalawade, H. S. (2021). Digitising Indian Retail: Analysing Challenges and Exploring Growth Models. Observer Research Foundation, 304, 1-32.

Kaushik, A. K., Mohan, G., & Kumar, V. (2020). Examining the antecedents and consequences of customers’ trust toward mobile retail apps in India. Journal of Internet Commerce, 19(1), 1-31. https://doi.org/10.1080/15332861.2019.1686333

Kim, H., Ryu, M. H., Lee, D., & Kim, J. H. (2022). Should a small-sized store have both online and offline channels? An efficiency analysis of the O2O platform strategy. Journal of Retailing and Consumer Services, 64, 102823. https://doi.org/10.1016/j.jretconser.2021.102823

Kumar, V., & Ayodeji, O. G. (2021). Determinants of the success of online retail in India. International Journal of Business Information Systems, 37(2), 246-262. https://doi.org/10.1504/IJBIS.2021.115373

Lee, P. T. Y., E, F., & Chau, M. (2022). Defining online to offline (O2O): a systematic approach to defining an emerging business model. Internet Research, 32(5), 1453-1495. https://doi.org/10.1108/INTR-10-2020-0563

Liang, G., Fu, W., & Wang, K. (2019). Analysis of t-test misuses and SPSS operations in medical research papers. Burns & trauma, 7. https://doi.org/10.1186/s41038-019-0170-3

Lumadi, N. I. (2014). Measuring Leader Reputation Within the South African Business Context: a Study in Two Financial Industry Organisations. University of Johannesburg (South Africa).

Maiti, B. (2021). Factors influencing Consumer Buying Behaviour towards Traditional and Online Shopping of Readymade Garments. KINDLER–The Journal of AIMK, 9.

Ponraj, V. (2019). A study on impact of online shopping on the retail trade of tirunelveli district. Manonmaniam Sundaranar University

Reddy, M. (2015). E-Retailing in India: Opportunit Challenges. Innovations and Sustainable Growth in Business Management, 45.

Ryu, M., Kim, E., & Lee, S. (2022). How offline retailers adopt O2O: Neighboring star shops and their proximity effect. Telecommunications Policy, 46(3), 102278. https://doi.org/10.1016/j.telpol.2021.102278

Sarkar, R., & Das, S. (2017). Online shopping vs offline shopping: A comparative study. International Journal of Scientific Research in Science and Technology, 3(1), 424-431.

Shen, C.-w., Chen, M., & Wang, C.-c. (2019). Analyzing the trend of O2O commerce by bilingual text mining on social media. Computers in Human Behavior, 101, 474-483. https://doi.org/10.1016/j.chb.2018.09.031

Shi, R., Chen, H., & Sethi, S. P. (2019). A generalized count model on customers' purchases in O2O market. International Journal of Production Economics, 215, 121-130. https://doi.org/10.1016/j.ijpe.2017.11.009

Siddiqui, A., & Mehrotra, S. (2021). Impact of Online Shopping Over Offline Shopping during Covid-19 (with special reference to Kashipur, Uttarakhand). SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 13(2), 232-240. https://doi.org/10.18090/samriddhi.v13spli02.21

Sudhakar Shukla, D. V. P. (2021). Impact of online retailing on offline retail stores in electronics goods sector. PalArch's Journal of Archaeology of Egypt/Egyptology, 18(4), 1279-1292.

Swoboda, B., & Winters, A. (2021). Reciprocity within major retail purchase channels and their effects on overall, offline and online loyalty. Journal of Business Research, 125, 279-294. https://doi.org/10.1016/j.jbusres.2020.12.024

Thomas, F. B. (2022). The role of purposive sampling technique as a tool for informal choices in a social Sciences in research methods. Just Agriculture, 2(5), 1-8.

Upadhyay, A. (2015). The effect of socioeconomic factors on the buying pattern of urban youth in the retail market. Devi Ahilya Vishwavidyalaya

Vinhas, A. S., & Gibbs, R. (2018). Exclusive dealing without territory exclusivity in multichannel systems: managing channel conflict and driving commitment. Marketing Letters, 29(3), 291-305. https://doi.org/10.1007/s11002-018-9462-9

Vora, C. N. (2018). A Study on Consumer Buying Behaviour Towards Offline Shopping Vis A Vis Online Shopping. Maharaja Krishnakumarsinhji Bhavnagar University

Wang, C., Wang, Y., Wang, J., Xiao, J., & Liu, J. (2021). Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation. Journal of Retailing and Consumer Services, 61, 102565. https://doi.org/10.1016/j.jretconser.2021.102565