The Rise of Online Fashion Sales

Chapter 1: Introduction

1.1 Background

Over the last few years, there has a significant shift in shopping patterns across the world. More and more customers today prefer to shop online rather than through traditional retail stores (Deepali, 2013). With the growing popularity of online shopping, online fashion sales have also shown a fluctuating to a stable trend.

The more open access to the internet and other related technologies in India is anticipated to have a significant impact on consumer behaviour, both offline and online. It has led to increasing online activities in India. Notably, a lot of online fashion retail websites have been launched in the last few years. They are always engaged in tight competition to gain more significant competitive advantage (Pani & Sharma, 2012). Accordingly, Gen Z includes people that are born in 1995 later (Fister-Gale, 2015)). Gen Y in India is estimated to be around 450 Million, and the Gen Z is identified to be 25% more than the Gen Y (Kantar IMRB, 2017; Aqumena Marketing Services, 2018). It is essential statistics because it has the potential to influence future demand and fashion trends. Moreover, it may require fashion companies to change the selection of their target market. Correspondingly, Gen Z is recognised to be the future contributor to the Indian economy. Additionally, Gen Z is ascertained to differ from its previous generation and have a unique set of opinions, preferences, attitudes and behaviour (Jain, Varsa and Jagani 2014). These differences are ascertained to have a direct impact on the strategies adopted by fashion companies. Hence, it is often argued that business organisations in India should not treat the Gen Z in the same manner as earlier generation. It is, therefore, essential for online fashion retailers to understand the buying behaviour and habits of Generation Z to develop effective marketing strategies.

1.2 Problem Statement

This study focuses on the analysis of Gen Z’s online shopping behaviour towards fashion in India. Accordingly, the marketers, until now have been increasingly concerned about the buying behaviours of on the Millennial, also known as Gen Y (Srinivasan et al., 2014). However, Gen Z population has grown significantly in India and are being viewed to play a dominant role in the fashion market in India (Black et al. .2017). Interestingly, not many research studies have been conducted so far to explore the online shopping behaviour of Gen Z customers towards fashion in India (Black et al. 2017). Thus, this study attempts to add to the existing knowledge base in this filed by exploring Gen Z’s online shopping behaviour towards fashion in India.

1.3 Research Aim and Objectives

1.4 Brief Methodology

This particular research study has been conducted following a quantitative research method where the findings obtained can be termed to be more accurate and to the point based on numerical statistical comprehension. The study will collect data based on a questionnaire survey from a set of target respondents to understand their responsiveness and trend about fashion. Only closed-ended questions have been considered within the survey questionnaire. Also, statistical tests such as correlation and regression have been found to validate the collected data based on SPSS tool.

1.5 Research Structure

This study is organised into six broad chapters, including introduction, literature review, research methodology, data analysis and findings, discussion, and Conclusion and suggestions for future research. Figure 2.0 below indicates the structure of this study.

Chapter 2: Literature Review

2.1 Generation Z and Their Characteristics

Generation Z or Gen Z is recognised as young adults who are born in 1995 or later (Bassiouni & Hackley, 2014). According to Schiffman & Wisenblit (2015), different generations have different characteristics that set them apart from other generations. Similarly, it has been argued that Gen Z has its characteristics that the marketers should recognise. Notably, Gen Z is argued to be surrounded by advanced technologies and is highly connected. Furthermore, it has been claimed that Gen Z can be divided into two groups that include teens and tweens. In this context, teens are those individuals that fall between the age group of 13-16 (OC&C Strategy Consultants, 2019). On the other hand, tweens are referred to the younger ones that fall in the age group of 8-12. An interesting aspect of the Gen Z that makes this generation different from earlier generation is argued to be related to their choice and preferences. In this context, it has been argued that the preferences of Gen Z tend to change very quickly and sometimes unpredictably (Schiffman & Wisenblit, 2015). Additionally, it has been argued that Gen Z customers appreciate companies that are engaged in direct delivery of messages to their age groups. At the same time, it has been argued that Gen Z customers tend to be more loyal towards the brands that they consume compared to the earlier generations that are more sceptical towards the brands (Schiffman & Wisenblit 2015). Additionally, it has been argued that the customers from this generation constantly exposed to marketing information because of the advancement in communication technologies such as social media. Thus they prefer short messages that are usually in the form of videos and pictures (Hulyk 2015). Similar view has also been postulated by Berkup (2014) who claimed that Gen Z is a tech addict and has great understanding and knowledge of internet technology than earlier generations. Thus, the people of Gen Z are claimed to actively use the internet for a variety of purposes such as entertainment and shopping. In another study, Jain et al. (2014) stated that Gen Z customers have realistic attitude compared to earlier generations and at the same time they are recognised to be more anxious for trying new fashion (Black et al. 2017). An important aspect of Gen Z customers is identified to be related with the fact that the customers of Gen Z value authenticity and are self-motivated than an earlier generation (Black et al. 2017; Williams & Page 2010). Solomon, Bamossy, Askegaard and Hogg (2014) claimed that Gen Z customers are optimistic and often look to create new experiences. It is because of the differences in the characteristics of Gen Z compared to previous generations; it has been argued that same marketing strategies cannot be used for the Gen Z and previous generations such as Gen X or Y (Schiffman & Wisenblit 2015; Williams & Page, 2010).

2.2 Consumer Behaviour of Gen Z

The field of consumer behaviour is one of the most widely researched subjects in the marketing and business domain. Accordingly, the consumer behaviour in its broad meaning refers to the process where individuals select, purchase and dispose of products and services to meet their needs and want (Schiffman et al. .2012). Several studies in the past have articulated that one of the major goal of the marketers to identify and meet the needs and preferences of the customers in the most effective manner. It has been thus argued that the marketers must understand how the target consumer behave as well as acquire knowledge about the potential factors influencing the purchase decision of the customers. In recent years, a variety of changes has been witnessed by the business in India. These changes are claimed to have fundamentally influenced consumer behaviour and their decision-making process in India (Priporas et al., 2017). Gen Z is claimed to have different characteristics from previous generations, and thus, they are viewed to demonstrate different buying behaviour. In this regard, it has been identified that Gen Z customers are even more digitalised and are greatly influenced by others like friends and family (Juodžbalis & Radzevičius, 2015). In other words, word of mouth is ascertained to play an important role in influencing their purchase decision. As per a report published by Accenture (2017), it has been stated that Gen Z places more importance on consumer online shopping experience such as delivery time, ease of returns and they are more likely to write reviews about their product and service experience than their previous generations.

2.3 Gen Z’s Online Shopping Behaviour towards Fashion

According to Juodžbalis & Radzevičius (2015), Gen Z is regarded as the most disruptive generation highly educated, technologically savvy and creative. Gen Z is further recognised to have born into a digital world that lives online. Additionally, Gen Z is claimed to be heavy users of technology, which signifies that Gen Z is more likely to prefer online shopping than any other previous generations (Priporas et al. 2017). It has been further observed that Gen Z customers are highly fashion conscious and demands for high-end fashion products. In a similar context, Jain et al. (2014) claimed that compared to previous generations, Gen Z is highly brand conscious and materialistic. Additionally, the Gen Z customers engaged in online shopping of fashion apparels and other products are ascertained to place considerable importance on the quality of the products which is followed by aesthetics/ On the other hand, the customers of this generation when engaged in online shopping of fashion products places little importance on the price of the fashion products (Goudeneche, 2012). In a study conducted by Jain et al.(2014), it has been found that the Gen Z customers that are engaged in the online shopping of the fashion apparels are more concerned about quality, fit, fabric, exclusivity, stylish and brand recognition. Moreover, it has been Juodžbalis & Radzevičius (2015) argued that Gen Z customers who prefer to shop online usually have the sophisticated attitude to fashion brands compared to earlier generations and they mainly look for convenience uniqueness, quality, and aesthetics. At the same time, it has been observed that when the Gen Z customers are engaged in the online purchase of the fashion brands, they often collect adequate information and compare before making their final purchase decision. Also, it has been argued that while the online purchase decision of the fashion brands by the previous generations was driven by the low-cost factor, the Gen Z are ascertained to place considerable importance on quality and convenience over the price of the fashion brand (Stoyanov & Stanoeva 2016). It is, therefore, Jain et al. (2014) in their study claimed that online fashion retailers that target Gen Z need to be creative and interactive on their digital platforms when marketing fashion brands towards Gen Z. Kick, Contacos-Sawyer and Thomas (2015) argued that Gen Z often wants to feel comfortable when shopping online or offline and thus it is important for the fashion brands to develop a relationship with the Gen Z customers.

2.4 Online Shopping Behaviours of Gen Z in Other Countries

Mulyani et al. (2019) conducted an empirical study examining the generation of z online shopping preferences in Indonesia. The authors conducted with 513 respondents (generation Z). In this study, the authors found that Gen Z has unique preferences compared to their previous generations. The study findings further suggest that the Gen Z customers that are engaged in online shopping are more “visual-person” which implies that they are highly engaged with pictures and images. Moreover, it has been found that Gen Z customers focuses highly on fairness, ease of use and seek clarity in the information offered to them online. In another empirical study conducted by Priporas et al. (2017) examined Generation Z consumers' expectations towards technological development in the UK. The authors conducted a series of in-depth interviews with 38 Gen students from a UK University. In this study, the authors found that Gen Z consumer’s behaviours are influenced significantly by new and smart technologies. The Gen Z customers are further exposed to expect the various new devices and electronic processes, as well as autonomy and faster transactions. However, it has further found that Gen Z customers in the UK feel uncomfortable and sceptical security issues during online shopping. A similar study has also been conducted by Hidvégi & Kelemen-Erdős (2016) examining the online purchasing decisions of generation Z in Hungry. Accordingly, in this study, the authors conducted an online survey with 1055 individuals (Gen Z) in Hungry. The study finding postulated that Gen Z is more actively involved in collecting information about products and services than their previous generations and are more likely to spend their considerable time surfing on the internet. At the same time, the study findings suggest that the decision of Gen Z to purchase online or offline in Hungry is primarily based on their shopping experiences in the past.

2.4 Gaps in Existing Literature

It has been observed from the review of literature that there are very few pieces of research dedicated to examining the Gen Z’s online shopping behaviour towards fashion in India. Although a few kinds of writing have partially focussed on the Gen Z consumer behaviour, the majority of these studies are conducted from different country perspectives. Also, a comparative understanding is necessary in terms of understanding how India can learn from the trend that is being followed in other nations of the world, which is not prevalent within the existing literature. There is a massive gap in the current literature concerning Gen Z’s online shopping behaviour towards fashion in India. In the light of growing online shopping market in India and enormous population of Gen Z people in the country, this study attempts to address this gap and contribute to the existing knowledge base by investigating Gen Z’s online shopping behaviour towards fashion in India.

2.5 Theoretical Framework and Hypothesis

This section involves the evaluation of the two critical theories of technology adoption that include the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT).

2.5.1 Technology Acceptance Model (Tam)

Technology Acceptance Model (TAM) is recognized as one of the most popular models of IT adoption, which has received considerable attention among the IT communities. The recent studies have postulated that this model can also be applied in online shopping and to the adoption of internet technology (Gefen & Straub, 2000). According to this model, online shopping adoption is influenced by two critical perceptions that include perceived usefulness and perceived ease of use. Accordingly, the perceived value relates to the extent to which an individual feels that the use of a particular system would contribute to enhancing their performance. On the other hand, the perceived ease of use relates to the extent to which an individual feels that the use of a particular system would “free of effort” (Davis, 1989). This model also includes two other variables that involve attitude and behavioural intention to use. The fundamental tenet of this model is that the external variable directly influences the perceived usefulness and the perceived ease of use. Figure 2.0 below indicates the TAM proposed by Davis et al. (1989).

2.5.2 Unified Theory of Acceptance and Use of Technology (UTAUT)

This research involves the use of UTAUT model to measure the Gen Z acceptance to online shopping. Notably, this model has been considered in this study because it is one of the most widely used models applied to measure customer’s acceptance of new technology. It is vital to note that this model has been proposed by Venkatesh et al. (2003) to explain and measure the user acceptance of new technology. This model has been used in several previous studies, such as Foon & Fah (2011) applied this model to estimate the behavioural intention of using internet banking. At the same time, Savić & Pešterac (2019) used this model to explain the behavioural purpose of using mobile banking. Thus, it can be argued that this model is a proven model that has been successfully applied in several previous research studies. The UTAUT involves four key constructs that are performance expectancy, effort expectancy, social influence, and facilitating conditions (Venkatesh et al., 2011). Also, this model includes moderating factors such as gender, age, experience and voluntariness of use which help explain the behavioural differences among the different groups. Below is the UTAUT model that is applied in this research study.

Performance Expectancy

This construct of performance expectancy relates to the extent to which the use of technology benefits the consumer in performing their activities. In this regard, studies in the past have argued that the performance expectancy serves as a strong predictor to online shopping in India (Tandon et al. 2016). In another study, Lian & Yen (2014) also found performance expectancy as a significant driver of online shopping. It is therefore to understand the Gen Z’s online shopping behaviour towards fashion in India, performance expectancy has a crucial variable influencing the online shopping behaviour of Gen Z. Sareen & Jain (2014), in their study, found no significant relationship between the performance expectancy construct and the behaviour intention to purchase online. Correspondingly, in this study following hypothesis will be tested.

Effort Expectancy

This construct of effort expectancy deals with the extent to which the use of a particular system provides ease of use. Accordingly, more comfortable is the online shopping more customers are likely to engage in online fashion shopping. Subsequently, Kadam, Gupta & Mishra (2015) conducted a quantitative descriptive study to analyse the online buying behaviour of Gen Z. However, scholars such as Baptista & Oliveira (2015); Zhang et al. (2012) argued that there is no significant relationship between effort expectancy variable and behaviour intention to purchase online. Correspondingly, the second objective that this study test is:

Social Influence

The third construct is social influence, which deals with the extent to which others believe him/her to be relevant after using the system (Venkatesh et al., 2003). According to Engel et al. (2000), entertainment and enjoyment as a social influence factor have the potential to exert influence on the consumer’s choice for online shopping. Thalgaspitiya & Hettiarachchi (2018) conducted an empirical study in which it has been found that shopping experience including enjoyment and pleasure of shopping serves as an essential factor influencing the behaviour of different generations including Gen Z. Nonetheless, the authors in this study have failed to clearly explain the research method including research design and data collection tools and techniques. Thus, the third hypothesis that this study test is:

Facilitating Conditions

Facilitating condition is the last construct of the UTAUT model considered in this study that deals with the extent to which “individual believes that an organizational and technical infrastructure exists to support the use of the system” (Venkatesh et al., 2003, p. 453). Studies such as Sareen and Jain (2014); Lian and Yen (2014) have found that facilitating condition has a statistically significant relationship with the adoption of new technologies such as behaviour intention to purchase online. Thus, the fourth hypothesis that this study test is:

Based on the Literature review, the following explanation has been developed for this study.

Chapter 3: Research Methodology

3.1. Research Philosophy

All research studies are underpinned by philosophical views and assumptions held by the researcher about the research subject. It is important to explicitly identify the philosophical beliefs to select research method and data collection tools. Two basic types of philosophical views are identified that include positivism and interpretivism (Bajpai, 2011). This research study can be termed as positivist research. The positivism paradigm has been considered to develop an understanding of Gen Z’s online shopping behaviour towards fashion in India because it involves the scientific investigation of the research issue in a structured manner. Moreover, the findings derived from positivist research are independent to the researcher, and thus, the chances of research bias are low while it has a high degree of generalizability (Saunders et al., 2009).

3.2. Research Method

Concerning the research method, two common types of research methods are usually applied in research that includes quantitative and qualitative research method. This research study is based on quantitative research method. The quantitative research method is considered to be an ideal choice because this method involves the logical investigation of the research method. Also, it consists of the collection of numerical data which are analyzed using statistical tools. Hence, the findings obtained from qualitative research are objective and verifiable (Castellan, 2010).

3.3. Research Design

Research design deals with the chronological plan of the study that helps the researcher to bring the different components of the research together to draw reliable inferences. Based on the purpose of the research study, research is categorized into three broad types that encompass exploratory, explanatory, and descriptive research design (Saunders et al., 2009). This research study is descriptive as it involves an in-depth description of the research subject that is gen Z’s online shopping behaviour and analyse the data to draw conclusive research inferences.

3.4. Data Collection

The data in this research study are collected from secondary and primary sources. The secondary data in this study are compiled from articles, books, and journals. On the other hand, the primary data is collected using a survey questionnaire. The questionnaire has been applied to obtain vital information because it is easy to use as well as a cost-effective method of collecting primary data (Hox & Boeije, 2005).

3.5. Sampling

To conduct the survey, 100 fashion-conscious customers born in 1995 or later were randomly selected and recruited after obtaining their informed consent. All the respondents were selected from four major metropolitan cities in India that include Mumbai, Delhi, Chennai and Kolkata. Moreover, purposive sampling technique was applied to recruit the sample participants (Sharma, 2017). Thus, only those customers were selected who were born in 1995 or later, and others were excluded from the study.

3.6. Data Analysis

Data analysis is an integral part of a research study which requires careful consideration. Accordingly, in this research, the collected data from the survey questionnaire are analyses using descriptive statistics and involves the use of graphs and charts as well to summarize the analysis of the data. Moreover, the hypotheses that have been formulated in this study were tested using correlation analysis technique. The correlation analysis technique has been applied to determine the linear relationship. All the quantitative analysis has been performed using SPSS data analysis software package.

3.7. Ethical Consideration

This study also places considerable attention on preserving research ethics throughout the study. Accordingly, all the participants were informed about the objectives of the study and their informed consent were sought for their voluntary participation in the study. The data collected from the survey were also stored safely in electronic format to prevent its misuse. Finally, the secondary data that were used in the study were correctly acknowledged by way of citation and referencing (Saunders et al., 2009).

Chapter 4: Findings and Analysis

In this particular chapter of the research, the focus has been mainly on analyzing the data that has been through a questionnaire survey, based on graphs, charts and other statistical means such as correlation and regression. The information has been presented hereunder in graphical form.

4.1. Presentation of Findings

As per the graph, as much as 40% are male respondents, while 60% of them are female. This shows the interest of female shoppers about online shopping.

As per the graph above, most of the respondents (45) are in between the age group of 31-40, while 18% of the respondents fall in the age bracket of 21-30.

As per the graph above, as much 28% of the respondents fall between the income bracket of 10000-20000 INR while another 26% has an income of more than 70000 INR.

About frequency of shopping via online medium, as much as 32% of the respondents have affirmed that they shop online once in 6 months while another 28% of the respondents depicted that they buy once every month via online.

With regard to total spending in fashion product for the respondents, around 62% assured that they contribute mere 5000 INR or less in online shopping for fashion products. In comparison, another 18% affirmed that their spending is in between 5000-10000. This shows that the level of speeding among people towards online shopping is marginally less or average.

About the fashion items people usually purchase frequently, the above graph shows that as much as 20% of the people are involved in the purchase of certain kind of dress while 18% is included with the purchase of jackets. As much as 14% of the people love purchasing accessories of some sort and 10% of them are buying jeans and suits equally. This figure shows that people purchase almost all kinds of fashion products online.

When the respondents were asked about their choice of the online platform, as much as 47% of the respondent's purchase products from Amazon while Paytm is also quite popular among the respondents. 13% of the respondents purchase from Flipkart. This shows that Amazon is the most preferred online application among online fashion buyers.

As per the pie given above, it is apparent that 54% of the respondents have purchased 4-6 products from their preferred online stores, while another 26% brought between 1-3 products from their preferred online platform. This shows that the number of online purchases is comparatively low for fashion products.

4.2. Statistical Analysis

4.2.1. Correlation Analysis

To understand the factors that influence purchase intent for Indian online shoppers, at first correlation is conducted between performance expectancy, effort expectancy, social influence, and facilitating condition with online shopping satisfaction.

From the above analysis, it can be observed that the value of correlation coefficient between performance expectancy, effort expectancy, social influence and facilitating likelihood with satisfaction are 0.625, 0.693 and 0.605 respectively, which are positive and much closer to 1. Therefore, it can be stated that a strong positive relationship exists between these variables. However, the correlation coefficient between social influence and satisfaction is observed as 0.089, which is positive but not closer to 1. Therefore, it can be stated that a weak positive relationship exists between these variables.

4.1.2. Regression Analysis

To understand the significance of those relationships, regression analysis is conducted. In this context, the key independent variables are performance expectancy, effort expectancy, social influence and facilitating condition, which is measured against the key dependent variable, which is purchasing behaviour, i.e. measured by customer satisfaction.

From the above analysis, it can be observed that the value of R2 is 0.634, which specifies that any changes in the aforementioned independent variables are related with about 63.4% changes in the dependent variable, which is quite significant. The P-value of the analysis is observed as 0.0001, which is less than 0.05, indicating that the relationship between the variables is statistically significant. Independently, the P-value of performance expectancy, effort expectancy, and facilitating condition is observed as 0.0001, 0.010 and 0.029 respectively, which are less than 0.05. Therefore, it can be stated that these factors have a significant relationship with customer satisfaction and hence purchase intent of customers. Therefore, the first, second and fourth hypothesis is accepted. Nevertheless, the P-value of social influence is observed as 0.426, which is more than 0.05. This indicates that the relationship between social influence and satisfaction is not statistically significant. Therefore, the third hypothesis is rejected.

4.3. Hypothesis Testing

This particular section of the study focuses on analyzing the findings in context to the research hypothesis that has been set in the initial phase in alignment with the purview obtained from the literature review.

H1: Performance expectancy has a statistically significant effect on behavioural intention to use online shopping for fashion in Gen Zen in India

As per the reviews done from the studies of Tandon et al. (2016), Lian & Yen (2014) and Sareen & Jain (2014) performance expectancy is linked with how Gen Zen perceive online shopping. The data from the questionnaire survey and statistics have shown that in terms of performance expectancy, online shoppers appreciate their convince in saving time and effort. Hence, this hypothesis can be accepted.

Effort expectancy has a statistically significant effect on behavioural intention to use online shopping for fashion in Gen Zen in India

About effort expectancy, past studies of Baptista & Oliveira (2015) and Zhang et al. (2012) shows that there is no significant relationship between the two factors. There is no direct or indirect relationship between the two factors in terms of influencing the buying behaviour of the customers. As per the statistical analysis, the correlation between the two factors is less than 1, which can be considered as very low, which further shows that this particular hypothesis is to be rejected.

H3: Social influence has a statistically significant effect on behavioural intention to use online shopping for fashion in Gen Zen in India

In terms of social influence, past studies claim a substantial relationship between social influence and customer buying behaviour. Thalgaspitiya & Hettiarachchi (2018) and Engel et al. (2000) has confirmed that the shopping experience of the customers involves pleasure and happiness, which is directly linked with influential social factors. This has also been confirmed from the strong Pearson correlation between the two factors, which proves this hypothesis to be positive.

H4: Facilitating condition has a statistically significant effect on behavioural intention to use online shopping for fashion in Gen Zen in India

As per the research conducted by Sareen and Jain (2014) and Lian and Yen (2014), it has been depicted that there is a strong relationship between facilitating condition and how technically competent the organization is within the online platform. Hence, better IT infrastructure of a particular online service can also be influential in influencing the purchase intention of the shoppers. Hence, this particular hypothesis can be approved on this basis.

Chapter 5: Conclusion

In this particular chapter, the focus has been mainly on analyzing the information collected from various researchers and likewise presenting or concluding them about answering the key research question in concern. Correspondingly, it can be noted that this research aims at getting a comprehension of how Gen Z’s shopping behaviour online platform in the Indian market. Correspondingly, in the process of attaining the aim of the research, the focus has been laid on understanding the difference in the mentality of Zen Z and ZEN Y customers in the Indian market along with understanding the preference of the Indian customers towards fashion purchase from the online platform. These key queries of the research have been attained based on information collected from both primary and secondary sources. As per the data collected from secondary sources through literature review, it was apparent that Gen Z is among the major contributor towards Indian economy in terms of online shopping in India, while Gen Y is the millennial customers. Gen Z is those customer born on or after the year 1995. In terms of their buying behaviour, it was noted that they are more digitally inclined and hence prefer more online shopping than offline purchase. Factors such as shopping experience, deliver time and hassle-free return policies further influence their buying pattern. This has also been affirmed from the findings of questionnaire survey where it was noted that performance expectancy has a major influence upon the buyers with a strong correlation between customer expectation with the way companies offers convenient and easy purchase experience for the Ge Z customers. Hence, it can indeed be concluded that Gen Z behaviour towards online shopping in the Indian market is quite positive and strongly correlated.

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