Thesis on online shopping

Chapter 1: Introduction of The Rapid development of Technology

The Rapid development of Technology has introduced the new consumption model that is Electronic Commerce. Electronic Commerce is becoming an emerging technique and getting more attention from the customers in the society. The pillar of e-commerce in the globe is the United States of America. It is followed by other developed countries. Besides other countries, China is also growing and expanding e-commerce. The process of online shopping is relatively easier and enhances customer to business relations, trading models, the interaction of customers with the sellers directly, order and cancellation of the services, adjustment of quantity demanded, and home delivery services for the customers. Online shopping behavior can be defined as how people prefer to purchase online services through the internet (Javad et al. (2012). The online shopping process mainly consists of 5 steps related to the traditional shopping behavior are search engine optimization Services, searching through the internet about the information, assessing the right product, dealing with the service provider, and then ordering the product. The objective of the present work is to determine factors that affect the willingness of consumers and customers to purchase a product from the online stores. The criteria for selection are based upon the decision-making process for online purchasing. The principal component of the analysis confirmed accuracy and uncertainty in the factors (Khalifa & Limayem, 2003).

Background of the study of The Rapid development of Technology

The development of the Internet and the infrastructure of communication increase the bandwidth of Telecommunication and provide the ability for customers to purchase products online. Several consumers are identified, and for them, online shopping is part of their daily routine. Several organizations are also entered into the business and provides more choices to the customers about online shopping sites. Food products need to be focused on the required product the customers need to decide. The online companies are known for fast delivery as well as lower prices of the products with high quality (Hernández, Jiménez, & Martín, 2011). The analysis and understanding of consumer behavior in the decision-making process of the consumer for online stores can enhance online shopping services. The E-Commerce search engines, as well as online stores, are provided with the system to improve services, satisfy customers, and to stimulate the site traffic and sales volume (Javad, Dolatabadi, Nourbakhsh, & Poursaeedi, 2012). The present work explores and explaining the behavior of customers for online shopping and how they make decisions to purchase services from the internet (Agyapong, 2018). The study evaluates factors affecting the nature of consumer. There are different online platforms along with international companies such as eBay and Amazon.

Background of the factors driving the customers for e-shopping

The goal of the work is to determine the factors that impact the online purchasing system. In order to reach the objective of research and analysis, the factors affecting the decision-making process of customers for online services.

Background of the Company/Country of The Rapid development of Technology

In today’s world there are maximum customers who love to do shopping online because, in this way, consumers can get maximum benefits. Consumers can shop for products of their own choice. People in Saudi Arabia also focus on internet use, internet facilities, online shopping, etc. Online shopping becomes a habit now. The users of internet services for online shopping consider trustworthiness and positive effect of analysis on the decision to purchase products online.

The problem statements of The Rapid development of Technology

Instead of tremendous purchase offers in the physical stores, some uses of the Internet prefer to purchase products from online stores, even if the quality price and convenience are the same for both conditions. The present research work will explore the influential factors for the decision-making process and preference of customers for online shopping. The research provides a distinguished approach to the appropriate factors influencing the consumer behavior of product and purchasing decisions. Along with other factors, the positive findings of research and review after comparison of results suggest the important factors that alter the decision of customers.

The Objective of the Study of The Rapid development of Technology

The main objective of the research is to find factors influencing the online purchasing process. The study explains the behavior of online customers and the way in which they preferred to purchase things from online services. Although the study examined effective factors for online shopping behavior but at the same time, the research considered compound effects and drawbacks of online services there is a lack of generalizability. The research finding provides a comprehensive overview of the approach of online customers varies with the intentions, attitude, behavior believes, social influence, and deep insight of factors related to the E-Commerce vendors. The analysis in work provides clarification and explanation for the inconsistency of the conclusion drawn from previous researches. In general, the analysis of consumer behavior increases the knowledge of users and service providers for the online shopping process.

Research Questions of The Rapid development of Technology

The questions included in the research are listed below,

1)      What are the influencing factors that determine the decision-making process of customers?

2)      What are the significant characteristics of customers having online shopping and factors that influence purchase decisions?

3)      What is the type of behavior of the customer who is engaged in online shopping?

4)      What is the effect of online shopping facilities and offers on customer behavior?

The Relevance of the Study

Importance to about consumer’s perception about e-shopping

The research finds a correlation between the previous literature and present experimental work along with other factors such as website ethics, equality consumer behavior, and the decision-making process of consumers. The additional feature of influence and factors online shipping is based on the analysis and feedback of the consumers as well as the uses of e-commerce pricing tools. There is a difference between the importance of all the factors' degree of influence on the behavior.

Usefulness of Study of The Rapid development of Technology

The analysis of the questionnaire and survey provides collected data from online shoppers. After analysis of all the data, the next process is to identify the factor regarding the most influencing condition for the choice of online shopping. Finally, the present research defines the importance of each factor related to the influence of consumer behavior and choice for online shopping sites. The analysis proposes and optimizes the condition to develop an online shopping assistant tool that can enhance the online shopping system for all the customers. the usefulness of the study can be understood from the fact that the study explains the behavior of online customers and the way in which they preferred to purchase things from online services. Although the study examined effective factors for online shopping behavior but at the same time, the research considered compound effects and drawbacks of online services there is a lack of generalizability. The research finding provides a comprehensive overview of the approach of online customers varies with the intentions, attitude, behavior believes, social influence, and deep insight of factors related to the E-Commerce vendors

Chapter 2: Literature Review of online shopping

Barnes and Guo (2011) concluded the behavior of the customer in Virtual Worlds, and according to him and Empirical Investigation on the second life and the test of a conceptional model is considered in the research. The noticeable factors are the amount of money for shopping, consumer habits, motivator, pursued value, and social factors. The study demonstrated that habits and external motivators have a greater effect on the online shopping behavior of the consumer. In the research, the trade virtual items were considered, and it was based on the analysis of gap, development of the model, testing of conceptual model and combination of new and previously existing ways for online shopping. The research concluded the implication of new models, practices, and limitations for online shopping

Demange and Broderick (2007) work on conception analyzation of consumer behavior for the different environments of online shopping. The model based on concepts was related to the exploratory potential and sense of meeting the decision of consumers. The holistic approach is considered in the research about the online shopping environment. The conceptual model perceived exploratory potential and sense-making the influence of user involvement in shopping values and intentions. The survey administered 301 respondents who prefer shopping online through specific websites. The measures developed in the approach was based on structural equation modeling, and hypothesis validation was measured. The research findings were exploratory potential and relation between the involvement of customers with the services. The research suggested the distinction between framework and dimensions of markets and consumer-focused languages for the information system. The research explored the impact of online shopping environment on the consumers (Dange & Kumar, 2012)

Herna´ndez et al. (2011) researched about factors of income, Gender, and age consideration for the online shopping behavior. The analysis was based on socio-economic characteristics and variables. The condition of behavior was considered for the market and services given to the users (Hernández, Jiménez, & Martín, 2011). The research objective was to analyze the socio-economic characteristics of users and customers based on age, gender, and income influences. The perceived self-efficacy and use of the internet were based on broadened on the technology acceptance model. The influence of the internet, e-commerce, and e-shopper, and behavior of customers was considered. The independent behavior of customers for both genders was determined to sell certain products. The variable of socioeconomic characteristic was used to forecast online purchase development (Hernández, Jiménez, & Martín, 2011).

Khalifa and Limayem (2003) result in internet shopping system and drivers for behavioral theory implementation for internet consumers. The longitudinal study was based upon the survey and considered social influence, online shopping, and the attitude of consumer and service providers. The research conducted several opinion polls for consumers to find the concerns that resist the consumer from making purchases through online internet sources. The consumers are concern about the privacy of personal information. The theory of planned behavior was used to investigate the relationship between behavioral control and internet privacy. The data were collected to analyze the belief of consumers, and for analysis 193, college students were considered in the research. The beliefs of self-efficacy regarded a positive concern for behavioral control. The users of internet services for online shopping consider trustworthiness and the positive effect of analysis on the decision to purchase products online (Khalifa & Limayem, 2003).

Kim and Park (2003) also worked on similar contacts that are online shopping and factors affecting the behavior of consumers for the products.  The research classified online stores in four categories, including customer service, merchandising, navigation, and convenience. The real-world integration for shopping is based on the face to face activities and services. The study evaluated the relation between the characteristics of online shopping and the behavior of purchasers. The results of the online survey were concluded by considering 602 Korean customers of online stores. The information included in the research was about the quality of services, security perspectives, user interface quality and the satisfaction of consumers about the relational benefits and commitment of service providers. The significant research-related actual purchase behavior of consumer and site commitment of consumer

According to the research conducted by Dange and Kumar (2012), external and internal factors motivate and discourage buyers from making decisions about e-shopping. Researchers studied a number of conceptual models and concluded results on the basis of comparative studies of secondary research material. Research findings present that highly developed technologies used in the websites and marketing of brands influence buying decisions in e-commerce. However, the most influential factors are income and culture (Dange & Kumar, 2012).

Research study held by Khosla (2018) concluded that e-commerce provides the opportunity to the buyers to get their desired products and services from various retailers all over the world. An empirical research study was conducted based on quantitative data collected from questionnaires. Research findings support the concept that awareness and marketing influence the buying behavior of customers. Companies need to have research on customer's requirements and behavior to develop effective marketing strategies for business promotion (Khosla, 2018).

  Javadi, Dolatabadi, Nourbakhsh, Poursaeedi, and Asadollahi (2012) researched  on the topic of factors which has an impact on consumer buying decision at online platforms. According to the research findings, financial risk, attitude, and subjective norms all draw an impact on the decisions of consumers. Financial risk had a negative impact on buyers' attitudes, while on the other hand perceived safety about the product delivery system has a positive impact on the buyer's attitude. Additionally, innovation has a positive impact to some extent (Javadi, Dolatabadi, Nourbakhsh, Poursaeedi, & Asadollahi, 2012).

Swapna and Padmavathy (2017) organized research to study factors influencing the buying decisions of buyers through the use of conceptual models and implications. Research findings conclude that e-commerce website influence buying decisions as high safety standards of website and user-friendly interfaces encourage a buyer to rely on that e-commerce platform and buy something. The bad customer experience at an e-commerce website demotivates consumers regarding buying decisions (SWAPANA & PADMAVATHY, 2017).

According to the research findings of sen, e-commerce is providing a new platform for business and retail services. However, online buying decisions of consumers sometimes get influence from some factors which are a cost factor, product factor, seller factor, and convenience factor. Properly provided product-related information and a safe online payment system both can have an influence on the decisions of buyers at e-commerce platforms (Sen, 2014). Changes in the retail sectors of Olx and Flipcart (e-commerce platforms in India) have overcome these factors by promoting products through marketing.

Summarizing the research findings of Hasan, Harun, and Rashid (2015), it can be concluded that companies need to pay attention to three kinds of factors to promote business growth. Firstly, they need to provide useful information on websites regarding products. Secondly, companies need to focus on the simplicity of the website. Thirdly, retailers should have focus on brand name and website. Researchers claim that these three kinds of factors have a direct relationship with the buying decisions of consumers at online shopping platforms (HASAN, HARUN, & RASHID, 2015).

Farah, Ahmad, Muqarrab, Turi, and Bashir (2018) concluded in their research article that consumers concerns with the security system of the e-commerce website. Consumers cannot take the risk of their sensitive data. Therefore, websites with no proper measures of safety generate a negative image in the mind of consumers. research also concluded a significant relationship between consumer buying behavior and several factors, including privacy, reputation, functionality, and trustworthiness (Farah, Ahmad, Muqarrab, Turi, & Bashir, 2018). Data security is the most influential factor in this.

Bauboniene and Guleviciute (2015) analyzed consumer buying behavior by conducting an empirical research study. According to the findings of this research work, consumers buy from an e-commerce website for their easiness and lower prices. Although they perceive the disadvantages of security issues also. Websites providing services and products at highly secure websites encourage consumers to buy from them rather than visiting a website which has the possibility of the poor data security system  (Baubonienė & Gulevičiūtė, 2015).

Research study held by Bucko, Kakalejčík and Ferencova (2018)on the research topic of online shopping held a survey and collected information from the e-customers regarding the factors which encourage them most and discourage them most while taking a decision to buy or not to buy from a selected e-commerce platform. The researcher presented their findings that most consumers agreed that they have high importance for product details and social proof of security  (Bucko, Kakalejčík, & Ferencová, 2018).

To study the specific behavior of consumers Vaghela (2017) held a research study. The researcher collected data from a survey of 600 residents of Surat city. Research data were analyzed through the use of SPSS. Descriptive analysis and factor analysis research findings present that vendor characteristics, website design, and risk factors have a direct link with the change of buying decision towards products and services offered at e-commerce platform (Vaghela, 2017).   

Lima, Osman, Salahuddin, Romle, and Abdullah's (2016) research findings on the topic of factors having an influence on the online shopping behavior of consumers indicate that perceived values and intention direct relation to the change in buying decision. Subjective norms of consumers negatively influence buying decisions at e-commerce websites. Researchers controlled sampling bias and conducted statistical analysis. Analysis of data literature represented that consumer perception has an impact on his/her purchase intention.  (Lima, Osman, Salahuddin, Romle, & Abdullah, 2016)

According to research findings presented by the research article of Babar, Rasheed, and Sajjad (2014), key reasons because of which consumers change their minds towards offered products at an e-commerce website are risk factors and attitudes. Research findings conclude that useful information and ease of website use stimulate consumers to buy something from the offered products or services at an e-commerce platform. Excluding these prices also have a relation with consumer buying decisions (Babar, Rasheed, & Sajjad, 2014).

According to Anamika Datt (2018), electronic commerce has become the major source for sharing business information. It also plays an essential role in order to maintain the business relationship as well as for conducting the transactions of the business by using the various source business telecommunication networks. He also discusses that there is a lot of factors that can influence the Consumers’ Attitude towards Online Shopping. These variables can be related to the respondent’s demographic statuses by which the attitudes of the respondents can be affected (Anamika Datt, 2018).

As indicated in this study Anurag Pandeya, (2015), the attitudes of the consumers for suing the website has strong impacts on the purchasing intentions of the customer from all of this website. The perceived risk of consumers affects the purchasing intentions of the customer in bad ways. There is a positive and direct impact of the website quality on customer satisfaction because if the quality of the website will be good and accurate than it would be attractive for the customer, and their satisfaction level can be enhancing (Anurag Pandeya, 2015).

Kakalejčík, (2018) revealed that e-commerce is referred to as the kind of the business that is conducted for the online environment meanwhile the behavior of the internet is considered as the unified platform, which is the reason for connecting the sellers and buyers. E-commerce is also considered as the range of the possible commercial transactions which is conducted online. Every website is able to generate income, and it can be easily included in this category (Kakalejčík, 2018).

Chapter 3: Methodology and Data of online shopping

3.1 Type of study of online shopping

The initial consideration of research is to define the influencing factors related to customer preferences. The study is empirical and based on the feedback of users for online shopping services (Hernández et al. 2011). The primary methodology of the research is concentrated on the types of research approaches. There are two categories of research including qualitative and quantitative research. The quantitative research provides statistical analysis of characteristics, predictive conditions, and the diagnosis (Javad et al. 2012). The purpose of using this method is to identify the factors related to the problem. The present research is quantitative research, and deductive way is employed to collect numerical data and calculate the results through an accurate statistical process.

 3.2 The Model of online shopping

The research model was developed about the relational behavior of consumers about purchasing products through online services. The model is presented in figure 1 and consists of attributes of online stores, where:

·         E-shopping = Dependent Variable

·         Awareness and Perceived Usefulness = Independent Variable

·         Promotion and Low Prices = Independent Variable

·         Delivery Cost = Independent Variable

·         Accessibility = Independent Variable

·         Visual Marketing = Independent Variable

Figure 1: Research model

3.3 Hypothesis of online shopping

To evaluate the services information, the satisfaction of consumers with the services, membership information, and production information, the present work adopted six components for the information quality. The research measured influencing factors on the decision of customers to avail services, and the factors included in the research are consistency, relevancy, sufficiency, and playfulness (Javad, Dolatabadi, Nourbakhsh, & Poursaeedi, 2012). The hypothesis of research is mentioned below,

H1: There is a positive effect of the product information on the online services and satisfaction of consumers with the services.

H2: The effect of interface quality and information satisfaction is positive.

H3: The effect of relational benefits and security perceptions is positive.

H4: This is a positive effect of Visual Marketing on E-Shopping.

H5: The effect of delivery cost on E-Shopping is positive.

 

3.4  Data collection method of online shopping

Each individual consumer of the product is a unit of analysis who experiences the services and purchasing process of products from online stores. Since the focus of research is to target consumers of online services and to investigate the relationship between behavior of consumers and characteristics of information and services provided through online services (Javad, Dolatabadi, Nourbakhsh, & Poursaeedi, 2012). The important factor affecting behavior of consumer is the attributes of service providers. The behavior of customers depends on the psychological state related to online buying. The main approach of the study is inductive as well as deductive to formulate the behavior of users and to collect the data for testing of consumer behavior.

The questionnaire survey has been conducted with the buyer's intended aspect to examine the point of view of the purchaser. The users of online shopping system filled the questionnaire according to their own preferences about the services. The questions were designed with the perception of marketing, delivery options, quality of services, pricing of products and approach of research (Hernández, Jiménez, & Martín, 2011). The quantitative assessment was used as realistic approach to investigating the research context.

3.5  Sampling Design of online shopping

The structure of the questionnaire used in the study includes questions about the vision and preferences of users. The questions were aggregated into 1-5 index to facilitate the quantification of numerable conduct and consumer attitudes. The questions included in the research considered the closed-ended analysis and fixed responses. The consideration of the research was to evaluate the arithmetic process (Hernández, Jiménez, & Martín, 2011; Kim & Park, 2003). The required exclusive issues and the options in the exhaustive number were described fully for the ease of respondent. The questionnaire survey examined the experiences of customers about the shopping and considered interaction between the seller-oriented facilitator integration and purchaser of online services.

The interaction between the consumer and the service providers was related to marketing efforts, quality of services, and changes in the prices. The questionnaire was subdivided into two main sections that were focused on the demographical characteristics. The characterization of the shopping experience was measured through the seller operating dynamic (Javad, Dolatabadi, Nourbakhsh, & Poursaeedi, 2012). 

To improve the research accuracy, the questions include consideration between the reputation, reviews of services, rating of websites and the services, volume of sales of the service providers, stickiness factors, ability to fulfill the performance, and quality of products provided to the consumers. The survey methodology tends to use the original experiences of consumers. The approach of analysis was quantitative, and the data source considered “What people do?”, “How and what are the ways to fix the issues?”, “How many and how much,” “What people say about the services” (Demangeot & Broderick, 2007).

In order to access the important factors, the questionnaire includes a section of consumer’s opinions. The section of opinion was filed by the respondent, and they demonstrated their experiences about the services and quality of the product. The important factors are including in this section that derives the attention of analysis for the accuracy of services and trustworthy services provided to the consumers. In the previous researches, Bucko, Kakalejcik, & Ferencove, 2018 used a similar approach to investigate what people think about online shopping facilities

The general sample is collected through the survey and questionnaire (Javad, Dolatabadi, Nourbakhsh, & Poursaeedi, 2012). The research was based on the selection of samples and potential uses of the internet for considered as a group. In the group, individuals were internet users and online shopping consumers. The survey was conducted in mid-March 2019 and the questionnaire has consisted of 15 items. The analysis was done based upon the focus of responses provided by the individuals in the group. The questionnaire included for criteria of users to purchase products online, effect of price in comparison of price with brick and mortar Store, reviews about the particular product, reviews about the service provider, security certification, product picture and details of product, website graphics, navigation process of website, shipping discount and special offers at regular basis,  Limited quantity of product, sales, time-limited offers, and position of product in the search engine optimized website.

3.6 Statistical Analysis Tools and Technique  of online shopping

SPSS software will be used to analyze as well as interpret the data after collecting the data from interviewer-administered questionnaires. The software minimizes the chances of data manipulation. SPSS is particularly useful software to generate charts and graphs as well statistics to explore, present, and describe the trends and relationships within the quantitative data (Saunders et al., 2009). Data will be presented and summarized in the graphs and tables forms and main data types that might be involved in this research are ratios, interval, nominal, and ordinal. The respondents of the questionnaire in the present study were consumers of online shopping services. The questionnaire receives concerns of users, and then statistical analysis was carried out to measure the response of respondents through SPSS software.

 The data has been analyzed by using the SPSS software and the various techniques are adopted to the analyzing the data. There are two kinds of the Statistical techniques that are employed in this study in order to attain the research objective. These techniques are descriptive and inferential analysis.

Descriptive analysis of online shopping

Descriptive analysis leads towards the demographic profile of the respondents that are the age, gender, and education level and employment status of the respondents. The descriptive analysis provides the data for the demographics of the respondent’s means who have participated in the research study what was his education and how old he or she is. There are the four major questions that are analyzed in this analysis, and these are; age, gender, education level and designation of the professionals of the constriction company who are the participants of this study.

Inferential analysis of online shopping

   The inferential analysis includes as which is conducted for the analyzing the reliability of the data as well as for analyzing the relationship of the variable with their effects either its negative or positive effect of the one variable on another variable. The test of the chron bach alpha is used to analyzing the reliability of the data and correlation is applied analyzing the relationship of the variables and the regression is applied for analyzing the impact of the variables.

Chapter 4: Analysis of online shopping

This paper presents the two types of statistics, i.e. inferential and descriptive analysis, to precise the relationship between the dependent and independent variables that how awareness and perceived usefulness, promotion and low prices, delivery cost, accessibility, and visual marketing effects the e-shopping by applying descriptive and correlation analysis.

4.1 Frequencies of online shopping

Gender
	Frequency		Percent	Valid Percent	Cumulative Percent
Valid	Male	72	54.5	54.5	54.5
	Female	60	45.5	45.5	100
	Total	132	100	100
Age
	Frequency		Percent	Valid Percent	Cumulative Percent
Valid	Less than 26 Year	36	27.3	27.3	27.3
	26 - 35 Year	48	36.4	36.4	63.6
	36 - 45 Year	33	25	25	88.6
	46 - 55 Year	10	7.6	7.6	96.2
	More than 55 Year	5	3.8	3.8	100
	Total	132	100	100
Status
	Frequency		Percent	Valid Percent	Cumulative Percent
Valid	Married	83	62.9	62.9	62.9
	Single	49	37.1	37.1	100
	Total	132	100	100
Monthly Income
	Frequency		Percent	Valid Percent	Cumulative Percent
Valid	Less than 5,000 SAR	17	12.9	12.9	12.9
	5,000 - 9,999 SAR	46	34.8	34.8	47.7
	10,000-14,999 SAR	34	25.8	25.8	73.5
	More than 15,000 SAR	17	12.9	12.9	86.4
	Non fixed income	18	13.6	13.6	100
	Total	132	100	100

Interpretation: The above shows the frequencies of gender, it can be observed that total of 132 individuals responded to the survey; 72 respondents were males (54.5 percent of total respondents) and 60 respondents were females (45.5 percent of total respondents).The above table shows the frequencies of age; total of 5 groups of age was defined, and most of the respondents belong to the age group between 26 and 35, i.e. 48 respondents and 36.4 percent of total respondents. Only 5 respondents belong to age group more than 55 years, i.e. 3.8 percent of total respondents.

 The above table represents the marital status of the respondents; 62.9 percent of the total respondents are married i.e., 83 respondents and 37.1 percent of respondents are unmarried i.e., 49 respondents. The above table represents the monthly income; it can be observed that most of the respondents belong to income group between 5,000 - 9,999 SAR i.e. 46 out of 132 respondents and 34.8 percent while the least number of employees belong to income group less than 5,000 SAR and more than 15,000 SAR i.e. 12.9 percent and 17, 17 out of 132 respondents.

 .2 Descriptive Statistics of online shopping

Interpretation:  The above table represents the summary statistics of dependent and independent variables containing the number of observations, minimum data value, maximum data value, mean value, and standard deviation. It can be observed that all of the variables contains 132 number of observations; the minimum data value of e-shopping, awareness and perceived usefulness, delivery cost, and accessibility is 2.00, while minimum value of promotion and low prices and visual marketing is 1.33 and 1.50 respectively. In addition, the maximum value of all variables is 5.00. The data shows that e-shopping has minimum mean value i.e. 3.8773 and the rest of the variables have means value around 4.1. Following the mean values, promotion and low prices have highest value of standard deviation i.e. 0.82161 while accessibility has lowest value of standard deviation i.e. 0.64998.

Reliability statics of online shopping

Interpretation of online shopping

This table representing the reliability and inconsistency of the data that is conducted from the respondents after analyzing the literature review of the various authors. The literature review also measures the impacts of the consumer’s behaviors on E-shopping and there are several factors that are analyzed in this study and these all factors are affection the E-shopping. The value of the Chron bach’s Alpha in this table represents the consistency of data. The Chron bach’s Alpha value for E-Shopping is 0.828 it shows the data is highly reliable because the value is greater than 0.7. The Chron bach’s Alpha value for three variables Promotion and Low Prices, Delivery Cost and Accessibility is less than 0.7 which shows data is moderately reliable for further analysis.

Regression analysis of online shopping

 

Interpretation

For constructing the regression equation of the least square, it has found a = 054 and b = .123, -.467, .512, .80, and 10 in the regression analysis of the coefficient table. The regression equation for the least square is;

Y = .054+ .123X1+.467x2+.467+.512+.80+.10

In the above-given analysis the value of the coefficient of the variables is representing that there is positive relationship between all independent variables and dependent variable (E-Shopping). It shows by enhancing the input the output will be increased automatically. The level of the significance for all variables is highly significant except for one variable (VisualMarketing). Because the value of Visual Marketing is 0.503, and it greater than 0.05 meanwhile the values for several other variables are 0.000, and these are less than 0.05. It shows all of the independent variables have positive significant relationship with the dependent variables.

The module summary table represents the effect of independent variables on the dependent variable, and in this table the value of the Adjusted R square 0.965, which shows due to the 1% change in independent variables, the dependent variable E-shopping will be changed 96%.  It means by benhance9ing all of these factors, the trend of the E-shopping can be increased.

The F statistic is the regression mean square (MSR) divided by the residual mean square (MSE). If the significance value of the F statistic is small (smaller than say 0.05), then the independent variables do a good job explaining the variation in the dependent variable. The significance value of the F statics is 0.000.

If the significance value of F is larger than say 0.05, then the independent variables do not explain the variation in the dependent variable, and the null hypothesis that all the population values for the regression coefficients are 0 is accepted. After checking for the model fit, we might want to know the relative importance of each IV in predicting.

DV. The unstandardized (B) coefficients are the coefficients of the estimated regression model.

Factor Analysis of online shopping

The tables of the factor analysis are to larger due to this. All of these tables are not composed in this file. These tables are given in the appendix.

E-Shopping

 

In this table of the Component Matrix, the loadings of the factors are represented and it also shows extracted values of each item in this variable of E-shopping. For the six questions of these variables, two factors are extracted. There are several other factors that are contributing to this variable, and it also referred as the higher absolute value of loading. In this matrix the six items are divided into two components. The loadings are represented by the gap in the tables, which are less than 0.5 and due to this to read the table can be easier.    

Generally, in the factor analysis, the KMO is used to measure the adequacy of the sampling. It also utilized to measure either the response is adequate or not. It must be round about the 0.5 according to its satisfactory analysis. The Adequacy of the variables is recommended greater than 0.5. The value of the KMO is 0.775 it means responsible for this variable is adequate.  The significance level of Bartlett's Test of Sphericity test is less than 0.05. It shows the correlation matrix is not an identity matrix (see in Appendix).

Awareness and Perceived Usefulness

 In this table of the Component Matrix, the loadings of the factors are represented and it also shows extracted values of each item in this variable of Awareness and Perceived Usefulness. For the four questions of these variables, one factor is extracted. There are several other factors that are contributing to this variable, and it also referred as the higher absolute value of loading. In this matrix the four items are divided into two components. The loadings are represented by the gap in the tables, which are less than 0.5, and due to this to read the table can be easier.

Generally, in the factor analysis, the KMO is used to measure the adequacy of the sampling. It also utilized to measure either the response is adequate or not. It must be round about the 0.5 according to its satisfactory analysis. The Adequacy of the variables is recommended greater than 0.5. The value of the KMO is 0.476 it means responsible for this variable is adequate because it is roundabout 0.5.  The significance level of Bartlett's Test of Sphericity test is less than 0.05 it shows correlation matrix is not an identity matrix (see in Appendix).

Promotion and Low Prices

In this table of the Component Matrix the loadings of the factors are represented and it also shows extracted values of each item in this variable of Promotion and Low Prices. For the three questions of these variables, one factor is extracted. There are several other factors that are contributing to this variable, and it also referred as the higher absolute value of loading. In this matrix the four items are divided into two components. The loadings are represented by the gap in the tables, which are less than 0.5 and due to this to read the table can be easier.

 

Generally, in the factor analysis, the KMO is used to measure the adequacy of the sampling. It also utilized to measure either the response is adequate or not. It must be round about the 0.5 according to its satisfactory analysis. The Adequacy of the variables is recommended greater than 0.5. The value of the KMO is 0.480 it means responsible for this variable is adequate because it is roundabout 0.5.  The significance level of Bartlett's Test of Sphericity test is less than 0.05. It shows the correlation matrix is not an identity matrix (see in Appendix).

Delivery Cost

In this table of the Component Matrix the loadings of the factors are represented and it also shows extracted values of each item in this variable of Delivery Cost. For the three questions of these variables two factors are extracted. There are several other factors that are contributing to this variable, and it also referred as the higher absolute value of loading. In this matrix, the four items are divided into two components. The loadings are represented by the gap in the tables, which are less than 0.5, and due to this to read the table can be easier.

 

Generally, in the factor analysis, the KMO is used to measure the adequacy of the sampling. It also utilized to measure either the response is adequate or not. It must be round about the 0.5 according to its satisfactory analysis. The Adequacy of the variables is recommended greater than 0.5. The value of the KMO is 0.694 it means responsible for this variable is adequate because it is roundabout 0.5.  The significance level of Bartlett's Test of Sphericity test is less than 0.05 it shows the correlation matrix is not an identity matrix (see in Appendix).

Accessibility

 

 

In this table of the Component Matrix, the loadings of the factors are represented, and it also shows the extracted values of each item in this variable of Accessibility. For the three questions of these variables two factors are extracted. There are several other factors that are contributing to this variable, and it also referred to as the higher absolute value of loading. In this matrix the four items are divided into two components. The loadings are represented by the gap in the tables, which are less than 0.5 and due to this to read the table can be easier.

 

Generally, in the factor analysis, the KMO is used to measure the adequacy of the sampling. It also utilized to measure either the response is adequate or not. It must be round about the 0.627 according to its satisfactory analysis. The Adequacy of the variables is recommended greater than 0.5. The value of the KMO is 0.627 it means responsible for this variable is adequate because it is roundabout 0.5.  The significance level of Bartlett's Test of Sphericity test is less than 0.05. It shows the correlation matrix is not an identity matrix (see in Appendix).

Visual Marketing

 

 In this table of the Component Matrix the loadings of the factors are represented, and it also shows extracted values of each item in this variable of Visual Marketing. For the five questions of these variables one factor is extracted. There are several other factors that are contributing to this variable, and it also referred to as the higher absolute value of loading. In this matrix the five items are divided into one component. The loadings are represented by the gap in the tables which are less than 0.5 and due to this to read the table can be easier.

 4.3 Correlation

16. Correlations
		EShopping	AwarenessandPerceivedUsefulness	PromotionandLowPrices	DeliveryCost	Accessibility	VisualMarketing
EShopping	Pearson Correlation	1	.415**	.461**	.419**	.562**	.499**
	Sig. (2-tailed)		.000	.000	.000	.000	.000
	N	132	132	132	132	132	132
AwarenessandPerceivedUsefulness	Pearson Correlation	.415**	1	.447**	.485**	.512**	.409**
	Sig. (2-tailed)	.000		.000	.000	.000	.000
	N	132	132	132	132	132	132
PromotionandLowPrices	Pearson Correlation	.461**	.447**	1	.592**	.558**	.469**
	Sig. (2-tailed)	.000	.000		.000	.000	.000
	N	132	132	132	132	132	132
DeliveryCost	Pearson Correlation	.419**	.485**	.592**	1	.605**	.496**
	Sig. (2-tailed)	.000	.000	.000		.000	.000
	N	132	132	132	132	132	132
Accessibility	Pearson Correlation	.562**	.512**	.558**	.605**	1	.623**
	Sig. (2-tailed)	.000	.000	.000	.000		.000
	N	132	132	132	132	132	132
VisualMarketing	Pearson Correlation	.499**	.409**	.469**	.496**	.623**	1
	Sig. (2-tailed)	.000	.000	.000	.000	.000
	N	132	132	132	132	132	132
**. Correlation is significant at the 0.01 level (2-tailed).