Factors Affecting Online Shopping of Purchasing Fashionable Clothes among Adults in Klang Valley

The fast growth of internet facility and services has provided another great marketplace for clothes shopping in the era of globalization. Moreover, online shopping also become very famous currently. The way people purchase, evaluate products and services, and conduct business has changed because of technological improvements, notably in the information and communication technology fields. Fashionable clothes play an essential role, and many adult customers like to purchase through online shopping. Several factors can impact adult consumers purchasing fashionable clothes. The main aim of this study is to determine the factors affecting the online shopping of purchasing fashionable clothes among adults. In addition, there is also an investigation of the relationships between the independent variables which are privacy/security, website design, customer service, and product variety, and the dependent variable which is online shopping of purchasing fashionable clothes among adults. Data gathering which is primary data was collected through a survey questionnaire with 402 respondents with a response rate of 89 percent who have experience purchasing clothes through online stores. The target population consists of adult consumers from various backgrounds in Klang Valley. Besides that, convenience sampling of non-probability sampling was used for data collection. Based on the research results, there are four independent variables which are privacy/security, website design, customer service, and product variety had been established that have a positive and significant relationship with online shopping of purchasing fashionable clothes among adults according to the coefficient value, all variables are reported positively. Furthermore, there is a significant moderate positive relationship between privacy/security, website design, customer service and online shopping of purchasing fashionable clothes among adults. Then, there is a significant high positive relationship between product variety and online shopping of purchasing fashionable clothes among adults. where r = 0.762, p < 0.001. As the finding of this study, it can help online clothes store sellers to understand and build up suitable strategies and methods to gain profit and market share efficiently and effectively.


Introduction
Many individuals now utilise the Internet as part of their everyday routines. Learning, communication, amusement, and the acquisition of products and services are a few examples of these activities. Online shopping, also known as e-commerce, is the non-physical exchange of products and services using the Internet. extra two Online shopping is widely used, as evidenced by the estimate that billion people use the Internet and spend 5% of their time online purchasing (Heather, 2018). Online shopping has many benefits and is practical. The latter fact highlights the importance of understanding consumer behaviour regarding internet shopping.
Clothing is a person's fundamental necessity and people dress differently for various occasions ranging from casual to formal attire. Clothing may reflect a person's personality, taste, and style to society in addition to serving a practical purpose. According to Aaron (2022), the fashion industry is the biggest and world's largest e-commerce industry in clothes, accessories, and footwear. Clothing firms must understand the elements of shopping decisions to improve their market share and maximize earnings in the e-commerce sector.
Fashionable clothing is one of the most popular and rapidly developing industries. Over a decade, Malaysian family consumption's purchasing power fell by 16.7%. However, Clothing & Footwear (107%) is one of the two major groups with purchasing power greater than 100% (Malaysia Consumer Price Index, 2020). In 2022, the Apparel market will generate $4.66 billion in revenue. The market is predicted to expand by 7.48% each year (CAGR 2022(CAGR -2026. Previously, shoppers would shop for clothing at boutiques or traditional retail establishments. E-commerce has grown in popularity as technology and the internet has advanced, and it has become a commonly used approach for shopping.

Problem Statement
Some people wear different clothes with unique designs for different occasions based on their preferences and needs, which makes them look good and attractive. Currently of globalization, many adults prefer to dress in fashionable clothing that is both stylish and professional. Nowadays, fashion plays an important role in people's lives by providing the best outfit that transforms the look. Because of today's advanced Internet services, most adults prefer to buy fashionable clothes online.
Online clothing retailing currently accounts for a sizable portion of total online sales in Malaysia. Customers seeking satisfaction from online shopping should prioritize online service quality when visiting online stores. Customers are also concerned about the security of their personal information and the involvement of cash or debit/credit card transactions when they shop online. Arora and Sahney (2018) stated consumers perceived negative consequences and high risks when shopping online due to the violation of personal information and changing their mindset to go offline shopping. Website design is essential for only those stores that can entice customers to buy more products and persuade them to shop online at any time and from any location.
Customers will be dissatisfied and frustrated if the website design does not meet the customer's expectations and criteria. As a result, website design factors have a significant impact on customer satisfaction. Customer service should always provide prompt responses based on customer inquiries and needs. If customer service does not give their best effort and fails to communicate with customers, buyers will be disappointed and lose interest in ecommerce. Purwaningtyas and Rahadi (2021) stated that there were very few studies in their research on factors influencing people's clothing purchases through online channels and that more implementations were needed. Although several factors influenced customers to purchase clothing via online platforms, as mentioned in this study, there is still a lack of major factors that motivate customers to purchase clothing via online channels. Furthermore, there is no indication of which generation group of customers prefers to buy clothes online. As a result of the lack of information and issues in previous studies inspired us to conduct a thorough analysis of this research topic, motivating us to investigate it further.

Research Objective
To examine the relationship between privacy/security, website design, customer service, and product variety on online shopping of purchasing fashionable clothes among adults.
RO 1: To examine the relationship of privacy/security on online shopping of purchasing fashionable clothes among adults. RO2: To examine the relationship of website design on online shopping of purchasing fashionable clothes among adults. RO3: To examine the relationship of customer service on online shopping of purchasing fashionable clothes among adults. RO4: To examine the relationship of product variety on online shopping of purchasing fashionable clothes among adults.

Literature Review
In this research, there were four variables such as privacy/security, website design, customer service, and product diversity that were dependent and influencing one independent variable which is online shopping of purchasing fashionable clothing among adults. Many researchers pointed out that in the era of globalization, the internet has become so accessible that it influences online shopping among adults (Bucko et al., 2018;Tekin et al., 2018) through effective advertisement and social media platforms (Sumarliah et al., 2021;Ali et al., 2021;Nguyen et al., 2020). However, despite the common growing online shopping habits among young adults, there were four other important influencing factors that researchers found dependent on online shopping for purchasing fashionable clothing.
Firstly, privacy or security is an essential factor that helps to build and increase the confidence of buyers when purchasing through online platforms (Arief, 2021;Arora and Muttoo, 2018;Aboobucker, 2018). Echoing this, other researchers specified that safe online transaction such as how their payment is processed, how their bank card information is stored, and assurance that their website is not fraudulent are the main points of this influencing variable (Hendriana, 2021;Baghel, 2022;Ramli et al., 2020).
Besides privacy and security variable, the literature points out that website design is yet another variable that influences online shopping among young adults. Having a fantastic website that can assist in carrying out an effective marketing plan is the first crucial step in expanding an organization (Roshni Madhusudhan, 2018). Other researchers noted in agreement that an internet business's website design has the power to determine the success or failure of a business and it genuinely affects how their target audience perceives the brand and holds the reign in convincing them to become consumers (Ramli et al., 2020;John Hawley, 2018).
Thirdly, the literature highlights that good customer service, and quick and effective responsiveness are vital dependent variable in influencing young adults to become online shoppers. This includes ensuring that customers get their product worth, resolving their problems without any delay, and ensuring their overall satisfaction (Usmed, D.C. et al., 2021;Jain et al., 2020;Rita et al., 2019).
The product variety is the final dependent variable that influences online shopping among young adults. Product diversity plays an important role in online channels to satisfy customer needs and wants because they can find more choices according to their preferences (Maity, and Sandhu 2021;Sethi, 2018;and Baghel, 2022). Based on the review of the literature, it can be concluded that privacy/security, website design, customer service, and product diversity are dependent on and influences online shopping of purchasing fashionable clothing among adults.

Methodology
Primary data: An online Google Form survey was distributed to working adults via WhatsApp, email, and LinkedIn. A judgmental convenience random sampling method is followed for the selection of the sample.

Sampling plan:
The sample size is 402. The sample unit includes working adults between the ages of 21 and above.
The methodology adopted for this study was to use a quantitative method that emphasizes measurements to analyze the relationship between variables. The purpose of this study is to investigate the relationship between privacy/security, website design, customer service, and product variety in online shopping for fashionable clothing among adults in Klang Valley. The overall population was 1000000, and the respondents of this survey were adult consumers who had shopped and purchased fashionable goods through online stores via various online channels. The reason for selecting this group of people as the Klang Valley population is that it focuses on the greatest number of adults who prefer to wear fashionable apparel. Considerations are given to the type of population, categories of population, and the research questions before selecting the sampling technique and sample sizes. After identifying the type of research, sampling method, unit of analysis, and research instrument summarized the framework of data analysis.
This framework functions as guidance to convert the raw data into a summary form to answer the research question. Although online shopping is popular in other areas, Klang Valley was chosen because of its strong purchasing power among adults and widespread use of online shopping platforms. Choosing an appropriate sample size is the most critical aspect of statistical analysis. As a result, the excessively high sample size may be time-consuming and costly to conduct the research. According to Table in Determining Sample Size by Krejcie and Morgan (1970), the sample size necessary from a given population of 1000000 was 384 as shown in Table 1. Due to the risk of extreme answers, missing questionnaires, and incomplete responses, this study has chosen to increase the sample size required by 4% (Salkind et al., 2020). As a result, 450 questionnaires were delivered in total.

Table 1
Determining Sample Size by Krejcie & Morgan, (1970) The questionnaires are dispersed at random throughout the Klang Valley region, which comprises the five major cities of Kuala Lumpur, Klang, Gombak, Petaling, and Hulu Langat. The questionnaire was made up of questions that have been developed and delivered to respondents concerning their attitudes, experiences, or opinions about the topic. The tested result was obtained after a thorough analysis of the data using the SPSS software.
The questionnaire was divided into four sections, Sections A, B, and C as shown below:

Section A -Respondent Demographic Profile
Section A is curious about the demographic details of the targeted responders. There are five statements: gender, race, age, how often you browse online shopping websites, and whether you buy clothing from an online platform.

Section B -Relying Variable
This section had five assertions connected to online shopping for stylish clothing among adults.

Section C-Independent Variable
This section assesses aspects that influence motivation, such as privacy/security, website design, customer service, and product diversity. This section contains a total of 25 statements.
All statements in Sections B and C were closed-ended by using a 5-point Likert Scale with values 1 to 5: 1 = Strongly Disagree; 2 = Disagree; 3 = Neutral; 4 = Agree, 5 = Strongly Agree Table 2 Survey Instrument

Data Analysis Descriptive Analysis
According to Bhandari (2020), descriptive analysis is used to summarise and organize the characteristics of a data set. A data set is a collection of responses or observations from a subset or the entire population. The initial stage of statistical analysis in quantitative research after data collection is to identify features of the responses, such as the average of one variable or the relationship between two variables. The researchers will use descriptive analysis to uncover trends in the survey responses that best determine the factors encouraging consumers to make stylish purchases from internet shopping.

Inferential Analysis
According to Calvello (2020), inferential analysis is a collection of statistical techniques and processes that are used to draw conclusions about a population based on quantitative data from a sample of confirmatory data. The researchers used inferential statistics to make predictions from the collected replies, which helped them to conclude and test the hypotheses.

Correlation Analysis
According to Senthilnathan (2019), correlation analysis is used to investigate the degree of the link between two variables. The correlation coefficient is a statistic that investigates the efficiency of the relationship between the independent variables of privacy/security, website design, customer service, and product variety and the dependent variable of adult online fashion shopping. The correlation coefficient between the two variables was determined and ranged from -1 to +1.

Normality Tests
The normality tests were used to check if there were any extreme outliers in terms of privacy/security, website design, customer service, and product diversity. Observations for appropriately distributed data should be generally on a straight line. According to Zach (2021), if the data is not normal, the points form a curve that deviates from a straight line.  In the demographic profile, the results show that there are almost similar percentages of respondents among male and female respondents, where female respondents are slightly higher compared to male respondents out of a total of 402 respondents collected. There are 59.2% of female respondents and the percentage of male respondents is 40.8%.

Figure 3: Age Distribution of Respondents
In this research, most of the respondents from aged 26 -34 years old (35.8%) with 144 respondents followed by the age group below 25 years old with 119 respondents representing 29.6% of the study. The minority of the respondents are from the age group, 35-45 years representing 116 respondents representing 28.9%, and the age group above 46 years old with 23 respondents representing 5.7% respectively. Most of the respondents are from the age group of 26 -34 years old since this questionnaire is distributed amongst adults and office staff around Klang Valley via an online google form.

Figure 4: Percentage of Race
There are four types of ethnic race groups: Malay, Chinese, Indian, and others. There is a total of 402 respondents which 208 from them are Indians, 90 Malays, and 83 Chinese which represent 51.7%, 22.4%, and 20.6% respectively. There are also 21 respondents from others who represent Bumiputera Sabah and Bumiputera Sarawak who have contributed 5.2% of the study data. Figure 4 presents the percentage of the races of the respondents.

Figure 5: Educational Level of Respondents
Most of the respondents are bachelor's degree holders with 41.3%, or 166 bachelor's degree holders participating in this study. This is followed by the Diploma holders' group, with 126 respondents representing 31.3% of this study. Master's Degree respondents came in the third rank with 61 respondents (15.2%). The minority of the respondents for this study has only a secondary school education level which is 36 respondents representing 9.0% of the study. Ph.D. respondents came in the fourth rank with 11 (2.7%) and followed by Primary and others with 1 (0.2%). Figure 5 presents the percentage of the educational level of the respondents. Most of the respondents are Private Sector with 63.7%, or 256 participating in this study. This is followed by the Self-employed, with 55 respondents representing 13.7% of this study. Besides that, other working sector respondents came in the third rank with 51 respondents (12.7%). The minority of the respondents for this study are from the public sector which is 38 respondents representing 9.5% of the study. Those respondents for this study from the pension with 2 (0.5%). Figure 6 presents the percentage of the occupation level of the respondents. In this research, most of the respondents whose income level was above RM4,001 indicated 140, 34.8% received income, followed by 99 respondents, 24.6% received income between RM 3,001 to RM 4,000. Furthermore, of another 85 respondents, 21.1% received income below RM 2,000. Lastly, respondents who received income between RM 2,001 to RM 3,000 are 78, 19.4%. Figure 7 presents the percentage of the income level of the respondents. Based on the findings from the analysis of the research question for privacy/security in Table 4 indicated where r = 0.615, p < 0.01. Therefore, according to Zakaria (2019), there is a significant moderate positive relationship between privacy/security and online shopping of purchasing fashionable clothes among adults. The findings from the analysis of the research question for website design in Table 4 indicate where r = 0.684, p< 0.001. Therefore, according to Zakaria (2019), there is a significant moderate positive relationship between website design and online shopping of purchasing fashionable clothes among adults. The findings from the analysis of the research question of customer service in Table 4 indicate where r = 0.655, p < 0.001. Therefore, according to Zakaria (2019), there is a significant moderate positive relationship between customer service and online shopping of purchasing fashionable clothes among adults. The findings from the analysis of the research question of product variety in Table 4 indicate where r = 0.762, p < 0.001. Therefore, according to Zakaria (2019), there is a significant high positive relationship between product variety and online shopping of purchasing fashionable clothes among adults.

Normality Test by Q-Q Plot
A normality test was applied through Q-Q Plot as the evidence to determine if there were extreme outliers for privacy/security, website design, customer service, and product variety towards online shopping of purchasing fashionable among adults. Moreover, for normally distributed data, observations should lie approximately in a straight line. If the data is not normal, the points form a curve that scattered away from a straight line (Zach, 2021). Based on the overall findings as shown in Figures 8 to 12 below, it was found that all variables tested indicated normal distribution.
A reliability test was conducted, and the findings for the independent and dependent variables are shown in Table 5 below. The reliability test was used to indicate results obtained consistently free from random errors (Samuel, 2018). Table 4 below indicates the Interpretation of Cronbach's alpha (α) for Reliability Analysis (Hair et al., 2017). Table 5 Interpretation of Cronbach's Alpha (α) for Reliability Analysis Cronbach's alpha for online shopping of purchasing fashionable clothes among adults was 0.931. The results of the reliability analysis for privacy/security were 0.82, website design was 0.872, customer service was 0.911, and product variety was 0.92. The Cronbach alpha for the variables of privacy/security, website design, customer service, product variety, and online shopping of purchasing fashionable clothes among adults from 0.82 to 0.931. Table 6 shows the summary of Cronbach's alpha for all the variables in the study (Zach, 2021).  Table 7 shows the summary of the result of the hypotheses by using Pearson Correlation from the result of data generated by the SPSS. Hypothesis 1, 2, 3, and 4 reported correlations in the range of 0.6-0.76 which fall at strong correlation strength, and the P-value <0.001 which is at 0.01 at the high significance level of 99%. Therefore, it's shown that hypotheses 1, 2, 3, and 4 have a positive and strongly significant relationship affecting online shopping of purchasing fashionable clothes among adults. All these hypotheses were related to and supported by past research (Zakaria, 2019).

Conclusion and Recommendation
Consumer decision-making processes have changed because of the adoption of online shopping. It lets customers compare products, prices, information, and shopping experiences quickly and easily with others before making a purchase. Shopping is evolving because of technology. Not just how the Web changed how consumers make purchases, but also new developments in smart and linked products. Online fashion clothing purchases among adults can be affected by four factors that customers consider before making a purchase. From the research, it discovered that a total of four independent variables consisting of privacy, website design, customer service, and product variety had been verified that have a positive and significant relationship with online shopping of purchasing fashionable clothes among adults according to the coefficient value, all variables are reported positively. Moreover, among the four independent variables, there is a significant high positive relationship between product variety and online shopping of purchasing fashionable clothes among adults. This is because product variety in the online platforms was able to attract more customers because of more variety of choices which can give customers a pleasant experience.
Clothing online retailers should grab the opportunities and sell current fashion trends clothes to attract customers and boost sales in the long term. Online retailers should emphasize branded clothing, the newest clothing trends, and a selection of products. Online retailers should emphasize and advertise their well-known brands if they want to meet the buying needs of fashionista customers. They should also suggest brand new, distinctive clothing and accessories. In fact, the visual aesthetic of websites can emphasize either aesthetic formality (order, simplicity, and readability) or attractiveness (creativity, uniqueness, trendiness), relying on the shopper's orientation. The website's design should emphasize simplicity, organization, brand, pricing, and promotion information, as well as online ordering (Ladhari et al., 2019).
In addition, there is a limitation in this research study which is time constraints there were only a few weeks to conduct the survey, so it caused not sufficient time for respondents There is a significant relationship between product variety and online shopping of purchasing fashionable clothes among adults. 0.762 <0.001 Positive, high and significant to answer decisively time series data are hard to be obtained. Other than that, the lack of knowledge because of using SPSS software was challenging due to the lack of experience to analyze the collected data. There is a possible recommendation that can be adopted for future research that has been provided in this study which is to extend to the target population according to the category of urban and rural to understand customer behavior in detail which can provide a better evaluation of online sales strategies. The analysis scope can be widened to make a cross-comparison of the research variables between different demographic categories. Furthermore, this analysis extends to cross-comparison, so readers can understand the impact of various aspects on online purchases. For example, whether the higher salary range population has a different expectation of the services or how the purchase pattern differs among male and female buyers.
Besides that, Online shopping has been very popular recently and will certainly continue to grow in the future. Then, future studies can be conducted by including moderating variables consisting of demographic factors to identify whether the relationship between online shopping and the factors is moderated by external factors that can contribute readers to analyzing which moderating variable strengthens or weakens the relationship between the dependent and independent variables. Moreover, it is also recommended to include journal selection based on geographical regions in the future studies literature review segment whereby customer behavior across different places can be better understood.