UNIVERSITI UTARA MALAYSIA123825187960RESEARCH METHODOLOGY(BPMN3134)GROUP SRESEARCH PROJECT:FACTOR INFLUENCING CUSTOMER SATISFACTION IN ONLINE SHOPPING AMONG COB STUDENTPREPARED BY:NO. NAME MATRIC NO.SANTHIYA A/P ELANGOH 237636NUR ADIBAH AQILAH BINTI MOHD ALI 238015NURUL IZZATI BINTI ZAINAL 238162MUHAMMAD ANWAR BIN SHAHARIN 238167SITI NURSHAFIQAH BINTI JAFFRI 238181NUR AELY NAJWA BINTI RADZUAN 238675LECTURER: DR. MOHAMMED SIAMABSTRACTOn-campus online shopping were the first choice for university students to purchase the item.
Therefore, to maintain student satisfaction towards online shop, as a university have to monitored and improve periodically. This study will discuss about issue of advertisement, product quality, brands and shopping experiences. This study highlights with 6 outcomes in the view of the following objectives (1) to examine the relationship between product advertisement and customer satisfaction in online shopping, (2) to examine the relationship between product quality and customer satisfaction in online shopping, (3) to examine the brand of product play an important role in customer satisfaction in buying online shopping, (4) to examine the relationship between online shopping experience and customer satisfaction in online shopping, (5)to examine that customer satisfaction differs according to gender and (6)to examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction. The data was collected through a questionnaire survey that targeting student from UUM on COB students among University Utara Malaysia and analyse with SPSS statistical techniques. This study is a quantitative research by using a questionnaire that involve a sample consisted of 100 respondents. The methodology used in this research is statistical analysis descriptive and inferential. Studies on these online shopping only the beginning and researcher shall do future research for other retailer shop online in UUM, to ensure that the all retailer shop online in UUM able to deliver high degree of service quality.
Key word: Advertisement, product quality, brands, shopping experiences and customer satisfaction.Table of ContentsCHAPTER 1 INTRODUCTION1.1 Background of study 1- 61.2 Problem of Statement…………………………………………………………………7- 81.3 Research Question and Research Objective……………………………………………9-101.3.
1 Research Question(RQ)9 1.3.2 Research Objective (RO)…………………………………………………………9- 101.4 Scope of Study………………………………………………………………………….101.5 Relevance of Study……………………………………………………………………..10CHAPTER 2 LITERATURE REVIEW2.
1 Concept and Measurement of Investigated variables………………………………11- 122.2 Theoretical Background……………………………………………………………12- 152.3 Theoretical Framework…………………………………………………………………162.4 Development of Research Hypothesis………………………………………………..
17- 182.5 Operationalization of variables……………………………………………………….18- 21CHAPTER 3 METHODOLOGY3.
1 Research Design………………………………………………………………………….223.2 Population, sample, and unit analysis……………………………………………………233.3 Sampling Design ……………………………………………………………………..…233.4 Data sources………………………………………………………………………………233.
5 Data Collection methods………………………………………………………………….243.6 Data analysis………………………………………………………………………….24-25 3.6.1 Descriptive : mean and standard deviation24 3.6.2 Correlation: Person’s Correlation Analysis…………………………………….
25 3.6.3 Regression: Multiple Regression Analysis………………………………………25 3.6.4 T-Test Analysis………………………………………………………………..25CHAPTER 4 DATA ANALYSIS AND FINDINGS4.0 Introduction…………………………………………………………………………….
.264.1 Demographic Background (Descriptive analysis)……………………………………26- 30 4.1.1 Respondent Profile……………………………………………………………26- 29 4.1.2 Mean and standard deviation of variables…………………………………………304.
2 Goodness of Measures (Reliability analysis)………………………………………31- 354.3 Interpretation of result from data analysis…………………………………………36- 41 4.3.1 Is there any relationship product advertisement and customer satisfaction in online shopping?….
…….
…
….
……..
…….
……..
……
…
….
…….
…
…….
…..
….
…….
…
….
…….
…
….
….
……364.
3.2 Is there any relationship between product quality and customer satisfaction in online shopping?…
…….
……..
…
….
……..
……..
…..
……
…..
…
…
…..
…..
…….
…
…….
…
……
….
…
.364.3.3 Does the product brand play an important role to the customer satisfaction in buying online shopping?…
……
…….
……..
…….
……
……..
…
…..
……..
…..
……
…….
…..
….
…..
..364.3.4 Is there any relationship between online shopping experience and customer satisfaction in online shopping………………………………………………….
..37- 384.3.5 Does customer satisfaction differs according to gender?..
…….
…..
…..
……
…….
….394.3.6 Do advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction?.
…..
…
…….
….
……..
…….
…
…….
……..
….
…..
….
…….
…..
….
40-41CHAPTER 5 DISCUSSION, CONCLUSION AND RECOMMENDATION5.0 Introduction425.1 Discussion42- 455.
1.1Objective 1: To examine the relationship between product advertisement and customer satisfaction in online shopping……………………………………………425.1.2Objectives 2: To examine the relationship between product quality and customer satisfaction in online shopping……………………………………………………..435.
1.3Objective 3: To examine the brand of product, play an important role in customer satisfaction in buying online shopping………………………………………………435.1.4Objective 4: To examine the relationship between online shopping experience and customer satisfaction in online shopping………………………………….44 5.1.5 Objective 5: To examine that customer satisfaction differs according to gender…………………………………………………………………………………44 5.1.
6 Objective 6: To examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction……………………………………455.2 Conclusions45-465.3 Research Implication475.4 Recommendations48REFERENCES: 49- 52APPENDIXQuestionnaireSPSS outputJournal articleLIST OF TABLESTable 2.5.2: Operationalization of variable 19-21 Table 4.
1.1: Demographic Background Data 28-29Table 4.1.2: Descriptive Analysis (Mean ; Standard Deviation of Variables) 30Table 4.2.0: Summary Table of Reliability Data Analysis 31Table 4.2.1: Advertisements Table of Reliability Data Analysis 31Table 4.
2.2: Product quality Table of Reliability Data Analysis 32Table 4.2.2.1: improved in Product quality Table of Reliability Data Analysis 32Table 4.2.3: Brands Table of Reliability Data Analysis 33Table 4.
2.4: Shopping experiences Table of Reliability Data Analysis 33Table 4.2.
4.1: improved in shopping experiences Table of Reliability Data Analysis 34Table 4.2.5: Customer Satisfaction Table of Reliability Data Analysis 35Table 4.3.4.1: correlations 37Table 4.3.5.1: T- test 39Table 4.3.6.1: Multiple Regression 40- 41LIST OF FIGURESFigure 2.3:Research Framework16LIST OF ABBREVIATIONSUUMUniversity Utara MalaysiaNCCC National Consumer Complaints CentreCOB College of Business SchoolSPSS Statistical Package for Social Science CHAPTER 1 INTRODUCTION1.1 Background of Study Online shopping is a process in which buy goods or services through the Internet .With large of consumer using Internet for online shopping, it is not clear what drives them to shop online (Monsure et al., 2006). The Internet and World Wide Web have made it easier, simpler, cheaper and easily accessible for businesses of all sizes and consumers to interact and conduct commercial transactions electronically as compared with the traditional approach of using private value-added networks (Margherio, 1998). As a result, ecommerce through the Internet dramatically shrinks the distance between producers and consumers, who can make their purchases directly without involving traditional ‘middlemen’ such as retailers, wholesalers and distributors. Although new intermediaries are required (for example network access providers, electronic payment system, and authentication and certification services), these are far less labor-intensive than traditional channels (Wyckoff, 1997). Nowadays, online shopping has become trend in this world. People in today’s world are preferring buying online rather than traditionally going to shop for the products that they need. It can save time because they do not need to drive to the stores to purchase what you want. They can simply log into the website of a retail store from their computer or mobile to start shopping. They also can even shop from multiple stores at one time. Since online shopping can assist people to save their precious time, it has received much attention on the past. Most of the stores are open only during the daytime. Some of these people may not have enough time of the day to go out especially for those working from morning to evening and because of other commitments. In such a situation, online shopping would come to rescue. The online shopping stores are open to 24 hours of the day. Therefore, they can think about shopping for what you want from these stores at any convenient time. The ordered products would be delivered to the doorstep as well so this really helps the busiest person save their time. Products available in online stores generally tend to be cheaper when compared to the physical stores. On the other hand, they are provided with some exciting opportunities to save money as well. For example, seller at Shoppe always does shocking sale, even they do it every days. This can save a considerable amount of money on what you purchase. You will never be able to get such amazing discounts from physical stores. People would never like to spend they precious time while standing on queues. Unfortunately, it would not be possible for them to avoid queues while they are shopping in offline stores. But when they go online, they will get the opportunity to avoid queues. They just need to add what they want to buy into the cart and directly proceed towards the checkout as simple as that. In addition, crowded stores never create a pleasant experience of the people that shop. Therefore, some people must be looking to avoid crowded stores as much as possible. That’s where the online shopping stores can assist them with. When they are shopping online, they would never have to deal with the frustration in crowded stores. Therefore, shopping would become a smoother experience to them because they can easily access online stores through their personal computers or mobile devise and order what they want. Besides, online shopping also may cause delay in delivery where this issue is still lingering in this era. Nair (2009) in his study of Bangalore metropolitan area found that major perceived problems in online shopping are lost orders, security and privacy getting compromised, unsatisfactory quality of products inadequate grievance-handling mechanisms, delay in obtaining products and a non-existing goods return policy. Although this study was done in Bangalore, delay in delivering goods is a common issue that faced by online shopper. Therefore, delay in delivering product may affect customer satisfaction as it defined the company services performance. Alam and Yasin (2010) recognized website design, product variety and delivery performance as important antecedents of customer satisfaction in online shopping. Image posted by the seller on the online page must be the same as the item to be ship out to the customer because the picture plays an important role when buying online. Some cases happen when the item is not same as the picture on the advertisement and it lead customer dissatisfied with the service by seller. Displaying a real product image is very important because cause as buyers we will buy for what they see. Providing clear product pictures from different angles will be more convincing, and it’s also allows customers to zoom in and out. “Picture worth a thousand words”. Next, quality and completeness of product presentation in online retail has a quantifiable and direct impact on product sales. But, often data is inaccurate, inconsistent, incomplete and even outdated, leading to increased returns, serious brand erosion and lost sales, all of which have significant financial ramifications for both retailers and manufacturers. To better gauge the impact of product information on online retail sales, Chicago-based Shotfarm surveyed more than 1,500 consumers about their online shopping habits and the importance they place on content in making purchase decisions (S. Berg, 2016). The 2015/2016 Shotfarm Product Information Report shows that consumers place a significant value on high-quality product content, regardless of product type, price or purchasing channel (S. Berg, 2016). Retail trading partners can maximize sales, minimize returns, optimize speed to market and enhance brands by improving the quality of product information they provide to digital shoppers. To achieve this goal, retailers and manufacturers will need to more efficiently develop, manage and share this data. Product information impacts brand equity and future purchase decisions. Fraud is one problem of online shopping that defined as an act using deceit such as intentional distortion of the truth of misrepresentation or concealment of a material fact to gain an unfair advantage over another in order to secure something of value or deprive another of a right (Gilbert, 1997). The customers of online shopping definitely exposed to this problem. The Star Online on 6 December 2016 reported that online shopping fraud is on the rise. Fraud can be occur in various ways. First, some of the websites offered luxury items such as popular brands of clothing, jewelries and electronics at very low prices. Sometimes the customers will receive the item that they paid for but the item will be fake, or maybe receive nothing at all. There is also a new version of online shopping scams involves the use of social media platforms to set up fake online stores. Their strategy is they open the store for a short time, often selling fake branded clothing or other items. After making a number of sales, the store disappear. They also use social media to advertise their fake website. So the customers should be aware and not trust a site just because they have seen it advertised or shared on social media. The best way to detect the fake trader or social media online shopping scam is to search for reviews before purchasing. There is another report regarding fraud of online shopping. The New Straits Times on 4 June 2017 reported that the e-commerce sector to top the list of complaints by Malaysian consumers, with the National Consumer Complaints Centre (NCCC) finding that an increasing number of Malaysians are falling victim to unscrupulous online merchants. So, fraud in online shopping is something that need to emphasize by all parties otherwise it will turn more serious in the future. Oliver (1980) defined customer satisfaction as customer’s evaluations on a product or service with regard to their needs and expectations. The main goal of any business firm being pursuit of customer satisfaction so that they can raise their profit. The other factor that influence the satisfaction toward online shopping is expectation of the product. This includes the design, appearance, packaging and quality of the product. According to Haslinda Musa (2015), in terms of quality, it is refers to the group of features and characteristics of a saleable good which determine its desirability and which can be controlled by a manufacturer to meet certain requirements. Basically, all customers tend to choose high quality product. According to Brenninkmeijer et,al (2004), high quality is the superiority meaning innate excellence, unarguably desirable thus always non-arguably being pursued by all customers. Based on Sharon Rudansky (2014), the online shopper cannot physically see or try the product in order to judge whether it is actual characteristics match the stated one on the website. Basically, the online customer only be able to read the description of the product and also the pictures provided by the website. So, we can say that it is possible to have several problems especially different expectation behalf of the customers. The customers will be dissatisfied when they feel or discover the products falls below their expectation and vice versa. It happened often in Malaysia when the online customers received the product that they had ordered from the website were totally different from their expectation especially in term of size, quality and design of the product. New technologies have already simplified and smoothed business-to-business and business-to-customer experiences with mobile payments, e-wallets, and contactless cards. As the online payment processing market grows, user demands for additional payment features and options lead growth in multiple directions. Providers are under pressure to provide peer-to-peer payments beyond traditional banking models, and to facilitate a cashless society that can enable any purchase, even mechanical transactions such as parking meters or vending machines. These demands create technical challenges for merchants, processors, and users up and down the transaction path. Whether a customer is paying by credit or debit card, net banking, or one of the several digital wallets that exist today, the failure of digital payments always looms overhead while making online transactions. A faltering internet connection or a technical glitch often results in the payable amount being debited from a customer’s account without being credited to the selling party. The retrieving process for this amount is anything but a quick process; one must inform the site and then wait around 7-10 days before the amount is refunded to their bank accounts. But this situation is steadily improving as the sector is focusing more on cashless transactions and customers are getting more informed about making payments online. So, the digital payment landscape is changing both online and offline at a brisk pace. Brick-and-mortar consumers are pushing retailers for an easier and more seamless way to pay using NFC and magnetic communication and online consumers are looking at alternative payment options including emerging payment services and crypto currencies. Digital payments will likely continue to be a catalyst for digital innovation in the coming years and may have a significant impact in how the retail industry evolves over the next decade. 1.2 Problem of Statement Online store and its quality plan an important role in determining customer’s satisfaction and can be one of the factor influencing their purchasing and proudness to be customer loyalty. Customer satisfaction can be defined as when the product and services meet expectation of the customer. To become customer satisfaction have the most lead customers keep setting ever higher standard because customer needs and expectation are always changing (Langerak et al., 1997). To become a conductive ecommerce of higher marketing, student’s satisfaction with the quality of the online shopping services in ecommerce should be accomplished to a satisfactory level. However, a few numbers of student were dissatisfied that influenced by a factor of advertisement, product quality, brand and shopping experiences. It is because the customer will get different expectation than the customer need. On the other hand, the customer were dissatisfied of advertisement because lack of relevance product information in website (Kim, Kim, and Lennon, 2011) such as the different size of product, different colour effect of product so the student will get the different expectation than appearances in a website. To satisfy the customer, the website advertisement should more attractive to the customer and must clear information. Besides that, product quality is customer’s overall evaluation of the excellence of the performance of good or service (John, Mowen; Michael, 1977). When the student make get an unwanted product such as product may be damage, not working, wrong or not durable so they will dissatisfy. It is because the product does not match what it described or expected (Comegys et al., 2009). So to satisfy this problem, it should increase the product quality to match the customer expected such as give a long time of warranty to their product. In addition, the student were unsatisfied the brand. It is because the customer get the fake product. The customer must evaluate in detail before purchasing to know that brand it original and that website has licensed to satisfy the customer. Decreased of shopping experiences toward the satisfaction of customer. It because the lack of system security, additional charge and other. To satisfy that shopping experiences, maybe it can give discount if any problem happen to increasing trust of customers. If the customer were dissatisfied it can be a serious ramification through word of mouth or in social media on ecommerce business. The student have to bear with such problems that happened due to quality toward online shopping. The purpose of study to investigate by using advertisement, product quality, brand and shopping experiences for making the service of online shopping more quality and fulfill the customer’s satisfaction. The study focusing on online shopping, students of College Business School (COB) located at University Utara Malaysia (UUM).1.3 RESEARCH QUESTION (RQS) AND RESEARCH OBJECTIVE (ROS)1.3.1 Research Question (RQs)1.3.1.1 Is there any relationship between product advertisement and customer satisfaction in online shopping?1.3.1.2 Is there any relationship between product quality and customer satisfaction in online shopping?1.3.1.3 Does the product brand play an important role to the customer satisfaction in buying online shopping?1.3.1.4 Is there any relationship between online shopping experience and customer satisfaction in online shopping?1.3.1.5 Does customer satisfaction differs according to gender?1.3.1.6 Do advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction?1.3.2 Research Objective (ROs)1.3.2.1 To examine the relationship between product advertisement and customer satisfaction in online shopping.1.3.2.2 To examine the relationship between product quality and customer satisfaction in online shopping.1.3.2.3 To examine the brand of product play an important role in customer satisfaction in buying online shopping.1.3.2.4 To examine the relationship between online shopping experience and customer satisfaction in online shopping.1.3.2.5 To examine that customer satisfaction differs according to gender.1.3.2.6 To examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction.1.4 Scope of this studyThe study focuses that factors influencing student’s satisfaction toward online shopping in College business school (COB), University Utara Malaysia, Sintok, Kedah. The respondents will be student in UUM. The study correlation using survey method and individual as unit analysis. The student inside UUM are considered as the element of the analysis. This research can give benefits to COB student and also to community because good quality service can lead to more successful market.1.5 Relevance of studyResearch is a very important for the online store operator, researcher, and community and for student. A good research can be general guide to the online store operator, community, student and future research. This study is important because it is going to measure student’s satisfaction toward quality of service online shopping store among COB student. The results from the study can be used to give valuable information for organization, future researcher and for the student. This study is important because it going to measure the level of service quality and the level of satisfaction among the students as have been dissatisfied toward online shopping.CHAPTER 2LITERATURE REVIEW2.1 CONCEPT AND MEASUREMENT OF INVESTIGATED VARIABLESMeaning of the customer is as the person who are buying the product and satisfaction can be defined as the customer’s feeling of disappointed or pleasure from that result comparing outcome with their expectations. Customer satisfaction is a customer feeling happy after they get a product from their good services and quality of product.AdvertisementAdvertisement can refer to the features of graphing image that from website to make the customer overlook the information about the product and to interact the customer to purchase the product. The advertisement can meet the customer need if the advertisement have their relevant information about the product in detail.Product qualityProduct quality can refer to the customer’s overall evaluation of the excellences of the performance of good or service (John, Mowen& Michael, 1997). When the product quality is good from the customer expectation such as the product in good condition, durable so it can make the customer satisfied with product quality.BrandBrand can be the defined as the product that have their personality and identify, name, vision, emotion and intelligence. Brand satisfaction can be defined as the evaluation of the customer’s overall based on their experiences whether the brand same as the actual performance or not. To meet the customer satisfaction of the brand, the brand must originally to make the customer have trust of the brand and make them feel enjoyable and satisfied.Shopping experiencesShopping experiences refer to the feeling emotion of the customer during the using of a product and services. Shopping experiences is the most important nowadays. If the customer satisfied the product so the customer make to tell the other customer to buy the product and can make the customer repeat the product again.2.2 THEORETICAL BACKGROUNDThe previous chapter, identify the problem that be effect of customers satisfaction toward online shopping. Focused on potential growth of online shopping has triggered the idea of conducting a study on factor affecting customer attitude towards online shopping( Joshi, 2015).Nowadays, there are a lot of customers looking for easier ways to purchase that can save time and save energy. Therefore, the customers want to get the item that they wants quickly without bargaining on price or quality so the e-shopping become the most important to customer (Yomnak, 2007). Online shopping is indoor shopping so no need to go outside. Online shopping is rapid access because just click the button to choose one of customer want then get the items as customer want. Online shopping eliminate of physical appearances. On overall, online shopping is easier way to purchase.Online shopping is something news to all but for Malaysian it very big challenging. Therefore, the transaction using online store in Malaysia is very limited. According to Ahasanul Haque and Ali Khatibi (2007), Malaysian people believe that online shopping transaction are not secured enough to protect the payment such as credit card, disclosure of information and other.In online shopping, sometimes customer dissatisfied with manner in which product and services that sold in the online store. Sometimes item purchased by customer not deliver on time although online message is very clear to deliver the item within 24 hours to the customer. According to Day and London (1977), the strategy use by the company store online is using not adequate addressed the changing demands to ensure customer satisfaction. Furthermore, logical measurement of success in market exchanges must accept the customer satisfaction and recognize by many research. 2.2.1 Relationship between product advertisement and the customer satisfaction.A possible source of information that consumers can make use of to inform themselves about price, especially in the early stages of decision making processes, is advertising (Estelami, 1997). Some of the customers would like to have a good advertising like seeking for promotion and sales advertisement. In a consumer context, most of the people want to purchase good products, and marketers want consumers to consider their products “good”. However, “good” is in the eye of the beholder – those with a promotion focus might seek out products that offer luxury and enjoyment, whereas those with a prevention focus might seek out products that guarantee safety and reliability (Cesario et,al;2004). The advertisements are in the form of a slam rectangular graphic image that is linked to a target advertisement which generally appears at the top or the bottom of web site and contain a short text or graphical message that can be customized for target audiences. According to Kierzkowski, McQade, Waltman, ; Zeisser, (1996), this can be achieved by billboard advertisement, links from other sited and leveraging on existing marketing communication, termed piggy-back advertising. Companies need to develop website with customer service in mind (Karakaya, 2001).Therefore, advertisement that include promotion and sales are one of the good ways to increase sale and increase the customer satisfaction. Advertising is composed of six dimensions including relevant news, brand reinforcement, stimulation, empathy, familiarity, and confusion that influence customers’ satisfaction (Schlinger, 1979). Therefore, satisfaction influences perceived value which in turn has impact on customers’ behavior (Schwarz and Clore, 1988; Zajonc, 1980).2.2.2 Relationship between quality of product and the customer satisfaction.Product quality refers to customers’ overall evaluation of the excellence in the performance of the good or service (John, Mowen & Michael, 1997). The most businesses that produce goods of product quality for sale or assurance department that monitors outgoing products for consumer acceptability. Product quality means the features that have a capacity to meet consumer needs and gives customer satisfaction by improving products and making them free of any deficiencies or damage. Students are satisfied when they meet the expectation of the product. They are dissatisfied when they feel the service falls below their expectations. Quality and customer satisfaction has provided some insights into determining the levels of satisfaction for product experience. The more quality information provided by the online retailers, the better the decisions could be done satisfactorily (Ludin & Cheng, 2014). Customer service and a positive customer experience are critical to sales in the e-commerce marketplace. 2.2.3 Relationship between brand of product and the customer satisfaction.Brand management in the twenty-first century has become almost synonymous with building and managing customer relationships (Story & Hess, 2010). A brand is likely a living being that need to have an identity and personality, name, culture, vision, emotion and intelligence. All these are conferred by the owner of the brand and needs to be continually looked at to keep the brand relevant to the target and to sell it. According to He, Li and Harris (2012), satisfaction occurs when the performance of a brand meets the expectations of the purchaser. Brand satisfaction refers to the evaluation summary of direct consumption experience, based on the different between prior expectation and the actual performance after receiving the product. According to Chiu, Huang and Yen (2010), highly satisfied consumers tend to reflect the brand personality traits by using some symbols related to the brand as an expression of their attachment to that brand. Similarly, students who trust a brand are willing to improve and sustain an affective bond with the brand that makes them feel warm and enjoyable.2.2.4 Relationship between shopping experiences and customer satisfaction. A Shopping experiences refer to the feeling emotion of the customer during the using of a product and services. A few ideas on shopper’s fulfilment have likewise experienced changes over the most recent couple of decades. Shopper’s fulfilment, in the examination, is characterized in alternate points of view. Student’s fulfilment idea has been acknowledged by numerous in wide extent of research, in spite of the fact that fulfilment is a compelling reaction took after by understanding and desire affirmed with including intellectual process. Besides, it is clarified that purchaser’s fulfilment is an assessment on benefit execution; the student contrasts yield and their desire before obtaining or expending. Purchaser’s fulfilment in conveying exchange is named student’s assessment on their experience and response towards specific item in executing or responding on benefit. Then, different specialists saw two distinct ideas towards buyer’s fulfilment. As indicated by them, when a more particular fulfilment in leading exchange was asked, the buyers tended to give remarks on certain occasion in exchange benefit (for example, certain representative’s activity). Then again, the purchasers tended to give remark on general impression and involvement with organization (like organization’s genuineness) when they were asked on the general fulfilment. Fulfilment in exchange is a mental response that item or specialist organization purchaser ought to be arranged on specific long haul execution.2.3 THEORETICAL FRAMEWORKFigure 2.3 Theoretical Framework43819356235Advertisement00Advertisement19075391120090-12065231264Product quality00Product quality18651637795403204837180216Factors influencing customer satisfaction in online shopping(COB students)00Factors influencing customer satisfaction in online shopping(COB students)18167353439790059055264811Brands00Brands182753033885105707596413Shopping experiences00Shopping experiencesIndependent variable (IV) Dependent variable (DV)2.4 DEVELOPMENT OF RESEARCH HYPOTHESIS 2.4.1 HO: There is no significant relationship between advertisement and customer satisfaction in online shopping among COB student. 2.4.2 H1: There is significant relationship between advertisement and customer satisfaction in online shopping among COB student.2.4.3 HO: There is no significant relationship between product quality and customer satisfaction in online shopping among COB student. 2.4.4 H2: There is significant relationship between product quality and customer satisfaction in online shopping among COB student. 2.4.5 HO: There is no significant relationship between brands and customer satisfaction in online shopping among COB student. 2.4.6 H3: There is significant relationship between brands and customer satisfaction in online shopping among COB student. 2.4.7 HO: There is no significant relationship between shopping experiences and customer satisfaction in online shopping among COB student. 2.4.8 H4: There is significant relationship between shopping experiences and customer satisfaction in online shopping among COB student. 2.4.9 HO: customer satisfaction is not significant differs according to gender. 2.4.10 H5: customer satisfaction is significant differs according to gender2.4.11 HO: Advertisement, product quality, brands, and shopping not able to predict customer satisfaction. 2.4.12 H6: Advertisement, product quality, brands, and shopping able to predict customer satisfaction2.5 OPERATIONAL OF VARIABLES2.5. 1 Key definition2.5.1.1 Product qualityAccording to Haslinda Musa (2015), in terms of quality, it is refers to the group of features and characteristics of a saleable good which determine its desirability and which can be controlled by a manufacturer to meet certain requirements. It can make the customer’s overall to evaluation of the excellence of the performance of good or service (John, Mowen& Michael, 1977).2.5.1.2 Customer satisfactionOliver (1980) defined customer satisfaction as customer’s evaluations on a product or service with regard to their needs and expectations. In this study, the customer satisfaction was measured toward service quality of the student in college business school, University Utara Malaysia.2.5. 2 Operationalization of variableA student satisfaction questionnaire is a useful performance measurement format that should help an institution to understand a student’s viewpoint of a firm’s performance on a completed project (Rondeau, et al., 2006).Table 2.5.2: Operationalization of variableVariable References Items(Questionnaires) ScaleAdvertisement Belch , 1998After watching the advertisement, I want get more information about this productI like this product after I watch this online advertisementThis advertisement is very attractive to meThe online advertisement contains a huge amount informationI think the advertised product is in accord with the real product Likert scaleProduct Quality Shodhaganga (2016)Higher creadibility of the online seller better quality of productProduct quality is important to me when I shop onlineI do not mind the real product have differences between the photos of the product when I shop onlineOverall, the quality of products sold online have lower quality than product sold at solid shopsLikert scaleBrands Tu, Wang and Chang (2012)I feel very comfortable purchasing brand onlineI purchase a lot of this brand’s service onlineI consider this clothes brand is my first choice if I buy same product through onlineThis clothing brand is a name I can always trust Likert scaleShopping experiences Kim, J .(2004)I have negative experiences with internet purchase in the pastI have searched for a product on the internet beforeI have purchased a product from an online store beforeThe product I purchased looks exactly alikeWhen shopping on the internet, I am satisfied with the service given Likert scaleCustomer satisfaction Yuan Bing (2015) My choice to purchase from this website was a wise oneI have truly enjoyed purchasing from this websiteI am satisfied with my most recent to purchase from this websiteIf I had to do it over again, I’d make my recent online purchase at this websiteWhen I purchased from this website, I am never disappointed Likert scaleCHAPTER 3METHODOLOGY3.1 RESEARCH DESIGNThis research is a cross- sectional in nature where the purpose is to determine the level of students’ satisfaction towards online shopping in UUM. Other than that, this research also include descriptive study and hypothesis testing are used for this research. Descriptive is undertaken in order to ascertain and be able to describe the characteristics of the variables of interest in a situation. Meanwhile, hypothesis testing is conducted to identify the important factors associated with the variables of interest and determining the relationship of advertisement, product quality, brands, shopping experiences between students’ satisfaction. Moreover, study setting that been used for this research is non-contrived which the natural environment where work proceeds normally. As the study is a correlational study, the study setting will be on the non-contrived setting. It is called a field study, in which the study will be conducted without the interference or normal working routine. The extent of researcher interference is minimal as it has no manipulation on independent variable. This research include unit of analysis that describes what or whom being studied. In social science research, the most typical unit of analysis are individual people (Babbie, 2011 pg. 101) In this research, unit of analysis is individual as satisfaction study also measured on individual itself rather than generalization because “descriptive studies with individuals as their unit of analysis typically aim to describe the population to discover the social dynamism operating within that population” (Babbie, 2011, p. 95). Hence, individual level is selected as unit of analysis of this research. The data is collected from COB student’s as an individual data 100 students are randomly selected for having use in online shopping. 3.2 POPULATION, SAMPLE, AND UNIT OF ANALYSISThe population of this study is 30,000 in undergraduate students with sample size of 2000 students from UUM that have use online shopping in COB school. Due to the huge number of students, data collection becomes difficult for entire population because of limited time and budget. In order to increase respond rate, a total of 100 questionnaires were distributed to the students. At the end of data collection period, this study successfully collected 100 useful questionnaires. 3.3 SAMPLING DESIGNIn this research, non-probability sampling is used. In this sampling design, all individuals in the population do not have equal chance for being selected. This method is less complicated to use compared to probability sampling. The respondents can be randomly picked by using this method. . It is used to study from the large population of University Utara Malaysia and student in College of Business who does online shopping are used as sample.3.4 DATA SOURCEIn this study, the data is collected through primary data and secondary data. Firstly, the primary data is through questionnaire by using online Google form. This method is the best way for this study to get full respond from the respondents in a short period of time. Not just that, it also help to clarify if the respondents might have any doubt. The number of respondents that have been collected is 100 respondents as the number of population is small. Besides, this study also use only one type of research data which is external sources.For this study, the external sources that is use by the researcher are from UUM library, internet journals, articles and online publications. 3.5 DATA COLLECTION METHODIn this study, the data is collected with two methods. The first method is observation. This can be shown by a lot of parcels received by each residential hall’s office. Majority of the owners are students. So, in this scenario, it is proved that students are tend to purchase online. The second method is survey. The survey is done through questionnaire by using online Google form. This is the best method to get full respond from the respondents. The questionnaire by using online Google form is easier for the respondents to answer the questions provided instead of using manual questionnaires. The number of respondents that have been collected is 100 respondents as the number of population is small. 3.6 DATA ANALYSISIn this research, type of analysis that be used which are descriptive, correlation and regression. That can used to analyse by using SPSS (Statically Packages for social science) version 25.0. This SPSS that can be used to analysed data collected, test, observation or even secondary data. The questionnaires was distributed to respondent randomly. After the respondent has completed answering questionnaires then were collected back to perform data analysis based on research question such as profile, mean, Standard deviation, Pearson’s correlation analysis, Multiple Regression Analysis and T- Test analysis.3.6.1 Descriptive: Mean and Standard DeviationDescriptive analysis that carry out from personal background as the data analysis by the respondent. According to Sekaran (2003), descriptive analysis basically involve information to describe of factor in a situation. Also, to examine the relationship between the level of students’ satisfaction explained by all combination of independent variables towards online shopping in UUM.3.6.2 Correlation: Pearson’s Correlation AnalysisTo examine the relationship between independent and dependent variable understudied the Pearson’s correlation analysis will be done. Person’s correlation coefficient is used to illustrate the degree of linear relationship between independent and dependent variables. It also show the strength, direction and significant of the relationship between all the variable. The correlation coefficient range is from 0.00 to 1.00. 3.6.3 Regression: Multiple Regression AnalysisThe aim of creating this analysis is to see how much of the variance in the dependent variables that are being affected by the independent variable. The value of R square is used to interpret the data in terms of variance explained of both variables (Gliner et al., 2009). Multiple regressions analysis was applied to analyse the best factor among the independent variable which consist of advertisements, product quality, brands and shopping experiences.Besides that, to identify the most influence of independent variable on dependent variables, it can be seen through the significant value provided in the regressions table. If the value is less than 0.05, it means that the independent variable influences the dependent variable. If the value is above the sign value, it designates that there is no influence between the independent and dependent variables (Gliner et al,. 2009). 3.6.4 T-Test AnalysisAccording to Utah, the t-test sample analysis refers to one statistical analysis used to see a significant difference for the mean value of the two group or two sets of data to be tested, there are three types of t-test analysis known One-sample t-test, paired sample t-test and Independent Sample t-test .The t-test sample analysis is used to see the difference between genders on online shopping in College Of Business at UUM. The researchers will use the Independent Simple test.CHAPTER 4DATA ANALYSIS AND FINDINGS4.0 INTRODUCTIONThis chapter will highlight and discuss the results and findings based on the analysis done on the data collected from respondents. This research focuses on the factors of customer’s satisfaction in online shopping on College of Business (COB) student at University Utara Malaysia. The discussion then will try to accomplish all the objectives outlined in chapter 1 and also will attempt to answer the research questions as well as proving the hypothesis presented in chapter 3. In this instance, for simplicity of analysis and findings, the chapter will divided into three parts: Demographic background (descriptive analysis) such as gender, age, highest education, programmed, financial support and often of shop online. Goodness of measures (reliability analysis), and Interpretation of results from data analysis (hypothesis testing result).4.1 DEMOGRAPHIC BACKGROUND (DESCRIPTIVE ANALYSIS)4.1.1 Respondent ProfileBased on the table 4.1.1 shows respondents from University Utara Malaysia of COB Students. There were 100 respondents. 38 respondents (38.0%) were male and 62 respondents (62.0%) are female. So, the most contribution in this study is female. The age of the participants or respondents divided by three group. Based on that table, it show those 21 respondents (21.0%) were student from between 19-21 years old and from between 22-24 years old were 76 respondents (76.0).Then, only 3 respondent (3.0%) from between 25 and above. From the data, the major contribution is respondent around 22-24 years old. As we can see from the table of highest education category involved respondent are from foundation by 4 respondents (4.0%) respondents, undergraduate 95 respondents (95.0%) participants contributed in this research, and post-graduated only 1 respondents (1.0%) student . The results show that undergraduate students the most contributed in this study. In term of programmed, Muamalat Administration course which is 30 respondents (30.0%), Economic course which is 21 respondents (21.0%), risk management and insurance course which is 31 respondents (31%), Islamic and finance course which is 7 respondents (7.0%),Banking which is 2 respondent, Logistics and transportation which is 3 respondents (3.0%) and lastly only 1 respondent (1.0%) for course international business management, marketing, business administration, Accounting Information system, Agribusiness Management and finance. The mostly programmed which is risk management and insurance course. As we can see from financial support, 57 respondent (57.0%) which use PTPTN. MARA which is 7 respondents(7%),YAYASAN which is 15 respondents (15%), Parents which is 2 respondents (2%),JPA which is 14 respondents (14.0%),PINJAMAN Selangor which is 2 respondents (2%), only 1 respondents(1%) for PBU (JPA),BIASISWA and Zakat. The most of financial support which is PTPTN. For the table often shop online, Majority of the respondent in yearly which is 34 respondents student (34%). Minority respondents in a monthly and every 6 weeks which are 33 respondent student (33%).Table 4.1.1: Demographic Background DataDemographic Categories Frequency Percentage (%)Gender MaleFemale 3862 38.062.0Age 19-2122-2425 and above 21763 21.076.03.0Highest Education FoundationUndergraduatePost-graduated 4951 4.095.01.0ProgramedFinancial SupportOften shop onlineMuamalat AdministrationEconomicRisk management and insuranceIslamic and FinancingBankingInternational Business managementLogistics and TransportationMarketingBusiness AdministrationAccounting Information systemAgribusiness ManagementFinancePTPTNMARAYAYASANParentsJPAPinjaman SelangorPBU (JPA)BIASISWAZakatA monthlyEvery 6 weeksYearly Source: SPSS output302131721311111577152142111333334 30.021.031.07.02.01.03.01.01.01.01.01.057.07.015.02.014.02.01.01.01.033.033.034.0-359597-11692494.1.2 Descriptive Analysis (Mean ; Standard Deviation of Variables)This section measures the level of customer’s satisfaction, advertisements, product quality, brands, shopping Experiences found on COB students. According to the table below shows the level of customer of the student for the mean value is 3.8740% followed by the advertisement of the shop online for the mean value is 4.0000%. Next, mean value for product quality of shop online is 3.3850% as much and the mean value for brands is 3.8900%. For the mean value of shopping experiences is 3.7560%.For the standard deviation based on customer satisfaction was 60.6% followed by 73.1% for standard deviation value of advertisements. Standard deviation for product quality and brands of shop online which follow value are 45.7% and 83.7%. Lastly, value for standard deviation of shopping experiences is 44.9%. Based on this data, it show clearly that advertisements, product quality, brands, shopping experiences and customer’s satisfaction of COB student in UUM is reaching the level by the student.Table 4.1.2: Descriptive Analysis (Mean ; Standard Deviation of Variables)Descriptive StatisticsN Minimum Maximum Mean Std. DeviationAdvertisements 100 2.40 5.00 4.0000 .73085Product Quality 100 2.75 4.75 3.3850 .45702Brands 100 1.25 5.00 3.8900 .83735Shopping Experiences 100 2.60 5.00 3.7560 .44909Customer Satisfaction 100 1.60 5.00 3.8740 .60613Valid N (list wise) 100 Source: SPSS output4.2 GOODNESS OF MEASURES (RELIABILITY DATA ANALYSIS)Table 4.2.0: Summary Table of Reliability Data Analysis Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedAdvertisements 14.9050 2.697 .677 .602Product Quality 15.5200 4.416 .120 .788Brands 15.0150 2.421 .665 .611Shopping Experiences 15.1490 4.143 .279 .750Customer Satisfaction 15.0310 2.901 .768 .577 Source: SPSS outputTable 4.2.1: Advertisements Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alpha N of Items.890 5Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB1.1 15.77 9.835 .628 .888B1.2 16.00 8.667 .760 .859B1.3 15.91 9.052 .754 .862B1.4 16.07 8.490 .758 .860B1.5 16.25 7.866 .779 .857 Source: SPSS outputBased on this table, the cronbach’s alpha of this 5 item in advertisement section which is good because 0.7 to 0.9 (Nunnaly, 1978). Table 4.2.2: Product quality Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alphaa N of Items-.291 4Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB2.1 9.48 3.646 -.316 .123B2.2 8.96 3.776 -.340 .037B2.3 11.41 1.739 .036 -.728aB2.4 10.77 1.593 .090 -.947a Source: SPSS output Based on this table, the cronbach’s Alpha of 4 item in product quality is poor because the total of reliability statistics have get negative. So to improve the product quality, deleted the item B2.1 and B2.2 to increase the Cronbach’s alpha.Table 4.2.2.1: improved in Product quality Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alpha N of Items.695 2Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB2.3 2.77 1.472 .532 .B2.4 2.13 1.488 .532 . Source: SPSS outputTable 4.2.3: Brands Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alpha N of Items.911 4Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB3.1 11.55 7.038 .787 .891B3.2 11.78 5.628 .832 .879B3.3 11.74 6.437 .796 .886B3.4 11.61 6.887 .815 .882 Source: SPSS outputBased on this table, the brands toward shopping online on cronbach’s alpha which is excellence. This is because the total cronbach’s alpha in 4 item have get above 0.9.Table 4.2.4: Shopping experiences Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alphaa N of Items-.172 5Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB4.1 15.38 5.571 -.362 .366B4.2 14.43 4.167 .189 -.377aB4.3 14.47 4.252 .119 -.322aB4.4 15.45 3.321 .018 -.313aB4.5 15.39 3.553 -.014 -.237a Source: SPSS outputBased on this table, shopping experiences toward shopping online on cronbach’s alpha which is poor. This is because the total cronbach’s alpha in 5 item have get below 0.7 and negative. So to improve the total of cronbach’s alpha need to deleted the item of B4.1 because to increase the cronbach alpha. But it still poor because have get below 0.6 which is 0.366.Table 4.2.4.1: improved in shopping experiences Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alpha N of Items.366 4Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB4.2 11.03 5.181 .000 .443B4.3 11.07 5.136 -.008 .454B4.4 12.05 2.290 .424 -.074aB4.5 11.99 2.576 .361 .051a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings. Source: SPSS outputTable 4.2.5: Customer Satisfaction Table of Reliability Data Analysis Reliability StatisticsCronbach’s Alpha N of Items.662 5Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB5.1 15.45 6.432 .420 .609B5.2 15.34 5.823 .709 .490B5.3 15.26 5.629 .765 .463B5.4 15.28 5.739 .709 .486B5.5 16.15 8.250 -.086 .886 Source: SPSS outputBased on this table, customer satisfaction toward shopping online on cronbach’s alpha which acceptable (Nunnally, 1978) is. This is because the total cronbach’s alpha in 5 item have get 0.7. 4.3 INTERPRETATION OF RESULTS FROM DATA ANALYSIS (HYPOTHESIS TESTING RESULTS)This section will discuss the results of data analysis by using inference analysis. The inferential is to test hypothesis is accepted or rejected in this study. In the inferences analysis will conduct T-test, Correlation Pearson analysis and Multiple Regression Analysis.4.3.1 Is there any relationship between product advertisement and customer satisfaction in online shopping? H1: There is significant relationship between advertisement and customer satisfaction in online shopping among COB student.4.3.2 Is there any relationship between product quality and customer satisfaction in online shopping? H2: There is significant relationship between product quality and customer satisfaction in online shopping among COB student.4.3.3 Does the product brand play an important role to the customer satisfaction in buying online shopping? H3: There is significant relationship between brands and customer satisfaction in online shopping among COB student.4.3.4 Is there any relationship between online shopping experience and customer satisfaction in online shopping? H4: There is significant relationship between shopping experiences and customer satisfaction in online shopping among COB student.Table 4.3.4.1: correlations CorrelationsAdvertisements Product Quality Brands Shopping Experiences Customer SatisfactionAdvertisements Pearson Correlation 1 .041 .758** .137 .653**Sig. (2-tailed) .687 .000 .175 .000N 100 100 100 100 100Product Quality Pearson Correlation .041 1 -.025 .293** .184Sig. (2-tailed) .687 .804 .003 .067N 100 100 100 100 100Brands Pearson Correlation .758** -.025 1 .145 .704**Sig. (2-tailed) .000 .804 .149 .000N 100 100 100 100 100Shopping Experiences Pearson Correlation .137 .293** .145 1 .351**Sig. (2-tailed) .175 .003 .149 .000N 100 100 100 100 100Customer Satisfaction Pearson Correlation .653** .184 .704** .351** 1Sig. (2-tailed) .000 .067 .000 .000 N 100 100 100 100 100**. Correlation is significant at the 0.01 level (2-tailed). Source: SPSS outputa) Relationship between Customers Satisfaction with AdvertisementTo examine the correlation between customer satisfaction and advertisement. Customer satisfaction and advertisements are significantly correlated. Therefore, customer satisfaction and advertisement are significantly correlated at **r = 1.000 (p = 0.000 or p < 0.01).It mean exactly perfect (positive) linear relationship.b) Relationship between customers Satisfaction with Product qualityTo examine the correlation between customer Satisfaction and Product Quality. Customer Satisfaction and Product quality are significantly correlated. Therefore, customer satisfaction and Product Quality are significantly correlated at **r = 0.041 (p = 0.000 or p < 0.01).It mean no linear relationship.c) Relationship between customers Satisfaction with brands.To examine the correlation between customer satisfaction and brands. Customer satisfaction and brands are significantly correlated. Therefore, customer satisfaction and brands are significantly correlated at **r = 0.758* (p = 0.000 or p < 0.01).It means strong (positive) linear relationship.d) Relationship between customers Satisfaction with shopping experiences.To examine the correlation between customer satisfaction and shopping experiences. Customer satisfaction and shopping experiences are significantly correlated. Therefore, customer satisfaction and shopping experiences are significantly correlated at **r = 0.137 (p = 0.000 or p < 0.01). It mean weak (positive) linear relationship.4.3.5Does customer satisfaction differs according to gender?HO: customer satisfaction is not significant differs according to gender.Table 4.3.5.1: T- test Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the DifferenceLower UpperCustomer Satisfaction Equal variances assumed 1.264 .264 2.732 98 .007 .33056 .12099 .09046 .57066Equal variances not assumed 2.712 76.557 .008 .33056 .12188 .08785 .57327 Source: SPSS outputBased on the table independent sample test, the value of significant is 0.264, which should be under 0.10. So, there is not significant different in customer satisfaction in the two different gender. 4.3.6Do advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction? H6: Advertisement, product quality, brands, and shopping able to predict customer satisfactionTable 4.3.6.1: Multiple RegressionModel SummarybModel R R Square Adjusted R Square Std. Error of the Estimate Change StatisticsR Square Change F Change df1 df2 Sig. F Change1 .776a .602 .586 .39023 .602 35.962 4 95 .000a. Predictors: (Constant), Shopping Experiences, Advertisements, Product Quality, Brandsb. Dependent Variable: Customer Satisfaction Source: SPSS outputR2 = 60.2% variance of customers satisfaction is explained by the 4 independent variables which are advertisement, product quality, brands and shopping experiences while the rest in unknown. Adjusted R2 is 58.6% after deducting error. The model is significant at value (p = 0.000 / p ; 0.05; 4, 95) = 35.962.ANOVAaModel Sum of Squares df Mean Square F Sig.1 Regression 21.906 4 5.476 35.962 .000bResidual 14.467 95 .152 Total 36.372 99 a. Dependent Variable: Customer Satisfactionb. Predictors: (Constant), Shopping Experiences, Advertisements, Product Quality, Brands Source: SPSS outputThis table based on the regression model predict dependent variable significantly well. This because by look significant in that table get 0.000 (p ; 0.0005 which less than 0.05).CoefficientsaModel Unstandardized Coefficients Standardized Coefficients t Sig.B Std. Error Beta 1 (Constant) .053 .425 .124 .902Advertisements .207 .083 .250 2.509 .014Product Quality .166 .090 .125 1.838 .069Brands .352 .072 .487 4.864 .000Shopping Experiences .282 .093 .209 3.047 .003a. Dependent Variable: Customer Satisfaction Source: SPSS outputBased on the table, Customer satisfaction = 0.053 + 0.207(advertisement)Positive sign indicates that customer satisfaction increase as advertisements increase but significance value of 0.014 ; 0.05 indicates a significant relation.Customer satisfaction = 0.053 + 0.166 (product quality)Positive sign indicates that customer satisfaction increase as product quality increase but significance value of 0.069 ; 0.05 indicates an insignificance relationCustomer satisfaction = 0.053 + 0.352 (brands)Positive sign indicates that customer satisfaction increase as brands increase but significance value of 0.000 ; 0.05 indicates a significance relationCustomer satisfaction = 0.053 + 0.282 (shopping experiences)Positive sign indicates that customer satisfaction increase as shopping experiences increase but significance value of 0.003; 0.05 indicates a significance relation.CHAPTER 5DISCUSSION, CONCLUSION, IMPLICATIONS AND RECOMMENDATION5.0 INTRODUCTIONThis chapter will elaborate the discussion, recommendation and conclusion of the study. In this chapter will gives a brief overview of the introduction, review of related literature, methodology, and data analysis and findings of the study. It also makes inferences from the findings which will conclude with final conclusion on the overall study at the end.5.1 DISCUSSION5.1.1 Objective 1: To examine the relationship between product advertisement and customer satisfaction in online shopping.The first factor is advertisement. The relationship of advertisement with the customer satisfaction shows that it is achieving the student satisfaction. It is because at that stage the significance value is exactly (perfect positive) linear relationships. One of the most tangible and fundamental measures of the marketing process and one of the most widespread areas of the marketing system is advertising. Before conducting any advertising, efforts should be made for identification of economic-social factors effective in influencing online shopping through different marketing methods (Mahmoud Mohamadian ; Mohammad Mehdi Parhizgar, 2007).5.1.2 Objective 2: To examine the relationship between product quality and customer satisfaction in online shopping.The second factor is product quality have poor relationship with the customer satisfaction. The result for the second factor shows that it is poor. The significance value below 0.60 but is still acceptable because the significance value positive. It is because at that stage is still need an improvement their service through the product quality. In order hand, quality and customer satisfaction has provided some insights into determining the levels of satisfaction for product experience. The more quality information provided by the online retailers, the better the decisions could be done satisfactorily (Ludin ; Cheng, 2014).5.1.3 Objective 3: To examine the brand of product, play an important role in customer satisfaction in buying online shopping. The third factor is brands also have a very strong positive relationship with the customer satisfaction. The result for the third factor show that it is also acceptable. Therefore, it is agreed that brands of shop online does influence the student satisfaction. According to Story and Hess, (2010) said, Brand management in the twenty-first century has become almost synonymous with building and managing customer relationships. However, highly satisfied consumers tend to reflect the brand personality traits by using some symbols related to the brand as an expression of their attachment to that brand (Chiu; Huang ; Yen, 2010).5.1.4 Objective 4: To examine the relationship between online shopping experience and customer satisfaction in online shopping.The forth factor shopping experiences have positive relationship with the customer satisfaction. At the level of forth factor shows that the result are weak but it still positive. Therefore, it is agreed that shopping experiences does influence the student satisfaction According to Nelson, (2012) said, when customers are satisfied with a company or service, there is high possibility that they will share their experience with other people. For example, in Motorola Company, the retailers need to offer their customers the best possible customer service as well as ensure a smooth transition between shopping on the Internet and in the store if they want to provide a unique shopping experience and resulting customer retention to ultimately increase sales. According to Alam and Yasin, 2010, satisfied customers are most likely to have the intention to repurchase if the service provider reached or exceeded their expectation. Thus, the more experienced consumers are with online shopping and the more satisfied they are with past online transaction experiences, the higher their purchase amounts and the more likely they are to be repeated purchasers and the lower likelihood of them aborting an intended online transaction. 5.1.5 Objective 5: To examine that customer satisfaction differs according to gender.The fifth objective of the study are to examine the customer’s satisfaction differs according to gender. Based on the data finding at the coefficient table shows that the variables are not significant. Therefore, it is disagreed that the customer’s satisfaction is cannot differs according to gender.5.1.6 Objective 6: To examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction.The sixth objective of the study are to examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction. Based on the data finding in Multiple Regression analysis shows that the four independent variables are influenced the customer satisfaction. Variance of the student satisfaction is explained by forth independent variable which are advertisement, product quality, brands and shopping experiences. Therefore, it is agreed that the advertisement, product quality, brands and shopping experiences were able to predict customer satisfaction.5.2 CONCLUSIONSThe study focuses that student’s satisfaction towards quality of service on online shopping among student COB (College of business), University Utara Malaysia, Sintok, Kedah. The specific objectives are (i) to examine the relationship between product advertisement and customer satisfaction in online shopping, (ii) to examine the relationship between product quality and customer satisfaction in online shopping, (iii) to examine the brand of product play an important role in customer satisfaction in buying online shopping, (iv) to examine the relationship between online shopping experience and customer satisfaction in online shopping, (v)to examine that customer satisfaction differs according to gender and (vi)to examine advertisement, product quality, brands, and shopping experiences able to predict customer satisfaction.This study is a quantitative study and cross sectional (one- shot) technique were executed. A survey conducted and use structured questionnaire as a tool to measure variables in this study such as advertisements, product quality, brands, shopping experiences and customer satisfaction. Moreover, the researcher must choose the most relevant method that can be used to collect the data such as observation, interview and questionnaire. Besides, the researcher must ensure that the questionnaire that they want to distribute is reliable so that the instrument and measurement for the research will be valid and acceptable. They also must make sure that the questionnaire is understandable and will not confusing the respondent so that it helps them to easily get the information. Apart from that, the researcher also learns how to use the SPSS for the data analysis method. Through the SPSS, the researcher learns how to interpret the data that have been collected. The researcher also will be able to check the validity of the data. So that, the researcher will know either the results of the data are normal or not. The normality of the data will show that the data is correct and valid. Next, reliability of the data also can be determined by using the SPSS. Therefore the same study also can be done by future researchers at other online retailer found in other institutions or organizations, as well as other respondents such as workers and staff at the institution. Researchers are also advised to identify other factors that are thought to be related to satisfaction with food services. Hence, this research can be use and referred in the future to improve any disadvantages in the online shop service that provide in University Utara Malaysia. From the research it will help the online shop service to any solution of the problem that influence customer satisfaction. Thus, it is important to conduct a good research so that the objective of the research will be achieve. 5.3 RESEARCH IMPLICATIONThe findings and analysis of this research will provides precision on what factor that will drives the customer satisfaction towards online shopping in College of Business (COB), University Utara Malaysia, Sintok, Kedah. It is confirmed that the product advertisement, the quality of product, the brands of product and online shopping experience influence the customer satisfaction. The online shopping seller need to make sure that the advertisement of the product that will be posted in their social media and online website should be very interesting and the information regarding the product should be correct and provide a truth information in order to prevent the customer to not trust the online seller again. Besides, the online seller also need to make sure that the quality of product that will be send to the customer is always in a good condition. The online seller should make a double check up on the products before posting the product to the customer. If the customer receive a defect product the online seller should be refund the product back to the customer. By serving this good service to the customer, this may increase the customer loyalty to the online seller and also online seller can achieve a high sale as many customer love to deal with the online seller.Furthermore, the online seller should improve the brands such as keep a good name about the product by always updating on the design of the product and following the most trending trend so that the customer would be interested in buying it and feel enjoyable and proud with the carried brand. Not just that, online seller also should make sure that the customer have a good online shopping experience with the service that been provided by the online seller. This is important to the online seller as with the best experience that the customer get it can influence the customer to buy the product again with the same online seller and therefore it will increase the profit of their sales eventually. 5.4 RECOMMENDATIONSuggestions for online dealers primarily based upon the findings and dialogue of this look at, the hints are provided for the net dealers to make online buying more famous, convenient, dependable and honest. Transaction safety and purchasers records protection are predominant concerns of online customer buying products or services on line. Therefore online carriers can assure their purchasers with the aid of providing private records privacy safety coverage and guarantee for transaction safety by means of improving their technological systems. Retailers must be cautious about the disturbing elements of online buying which include being unable to get admission to the internet site, lengthy delays in completing on-line orders, inconsistencies in the gadgets available online, errors in filling orders, and the trouble of returning items. Online dealers can be extra worried approximately shipping times and delivery charge and product go back policies. They are able to make it simpler, faster and reliable, so that purchasers can enjoy the web shopping experience.References BIBLIOGRAPHY Angelova, B. (2011). Measuring Customer Satisfaction with Service Quality Using. International Journal of Academic Research in Business and Social Sciences, 232-257.Archakova, A. (2013). Service Quality and Customer Satisfaction. Case. Thesis 2013 , 1-44.Bernard, R. J. (December 2009). The Effects of Materialism, Brand Image, and Ad Appeal Type. 5-7.by Nicki Lisa Cole, P. (n.d.). Different Types of Sampling Designs in Sociology and How to Use Them. Retrieved from thoughtco.: https://www.thoughtco.com/sampling-designs-used-in-sociology-3026562Cesario J, G. H. ( 2004). Regulatory fit and persuasion: Transfer from ‘Feeling Right’. Journal of Personality and Social Psychology, 388–404.Chiu, C. M. (2010). Antecedents of online trust in online auctions. electronics commerce reasearch ad application,9, 148-159.Ela Goyal et, a. (2011). Study of satisfaction and usability of the Internet on student’s. International Journal of Education and Development using Information and Communication Technology, 111-117.Estelami, H. (1997). Consumer perceptions of multi?dimensional prices. Advances in Consumer Research,Vol. 24, Association for Consumer Research, Provo, UT, 392?9.Felix, E. ( 2015 ). Marketing Challenges of Satisfying Consumers Changing Expectations. International Journal of Marketing Studies, 42-45.Ghose, s. (n.d.). Consumer Behaviour. Retrieved from Advertisements: http://www.yourarticlelibrary.com/marketing/consumer-behavior/consumer-behaviour-an-overview/50863Hasina Momtaz et, a. (2011 ). Customers Satisfaction on Online Shopping in Malaysia . International Journal of Business and Management , 162-169.Haslinda Musa et, a. (n.d.). Factors Affecting Customer Satisfaction towards Online Shopping. 1-17.He, H. L. (2012). Social identity perspective on brand loyalty. Journal of Business Research, 648–657.hero, C. (n.d.). multiple regression. Retrieved from Course hero: https://www.coursehero.com/file/p5m279r/353-Multiple-Regression-Analysis-The-purpose-of-performing-this-analysis-is-to/Izyan Hizza et, a. (2014). Factors influencing customer satisfaction and E-loyalty: online shopping among young adults. Management Dynamics in the Knowledge Economy, 463-471.Jamaludin, N. I. (n.d.). Improve the customer’s buying behaviour by using online shopping. scribd, 1-5.John C. Mowen, &. M. (1997). Consumer behaviour: A Framework.Jung Lee, J.-N. L. (n.d.). QUALITY VS. PREFERENCE: THE IMPACT OF ONLINE. 1-12.Kabu Khadka et, a. (2017). CUSTOMER SATISFACTION AND CUSTOMER LOYALTY. CENTRIA UNIVERSITY OF APPLIED SCIENCES, 1-73.Karakaya, F. (2001). Electronic commerce current and future practices. Managerial finance.Khawaja Khalid et, a. (2012). GET ALONG WITH QUANTITATIVE RESEARCH PROCESS. International Journal of Research in Management, 15-29.Kierzkowski, A. S. (1996). Marketing to the digital customer. The mckinsey quarterly. Ludin, I. H. (2014). Factors Influencing Customer Satisfaction and E-Loyalty: Online Shopping Environment among the Young Adults. Management Dynamics in the Knowledge Economy, 462.Mahsa Abayia et, a. (2015). Study of the Impact of Advertising on Online Shopping Tendency. International Conference on Applied Economics and Business, 533-539.Measuring the effectiveness of online shopping. (n.d.).methodology. (n.d.). Retrieved from course hero: https://www.coursehero.com/file/30621483/3docx/(2016). Online shopping fraud is on the rise. PHILADELPHIA: the star online.Rajesh, R. (2018). EVALUATING THE FACTORS INFLUENCING ONLINE. International Journal of Social Sciences, 55-76.Richard Chinomona et, a. (2013). Brand Service Quality, Satisfaction, Trust and Preference as Predictors of consumer brand loyalty. Mediterranean Journal of Social Sciences, 181-190.Richard Chinomona et, a. (2013). The influences of brands experiences on brand satisfaction,trust and attachment in south Africa. international business& economic research journal, 1303-1305.routio, p. (2007, August 3). Descriptive Observation and Experiment. Retrieved from contents: http://www2.uiah.fi/projekti/metodi/162.htmRudansky-Kloppers, S. (2014). Investigating Factors Influencing Customer Online Buying Satisfaction In Gauteng, South Africa. International Business & Economics Research Journa, 1187-1197.Schlinger, M. (1979). A profile of responses to commercials. Journal of Advertising Research.Schlinger, M. (1979). Attitudinal reactions to advertisements. Attitude research under the sun chicago.Schwartz, N. &. (1988). How do I feel about it?Informative function of affective state. Affect, cognition and behaviour, 44-62.Shodhganga. (n.d.). Fraud.Simplify the online checkout process. (2016, october 12). Retrieved from business.gov: https://www.business.gov.au/news/simplify-the-online-checkout-process-part-twoStory, J. &. (2010). Ethical brand management: customer relationships and ethical duties. Journal of Product & Brand Management.teing, c. h. (August 2014 ). FACTORS AFFECTING ONLINE SHOPPING OF. 37-38.Vilasini Jadhav et, a. (2016). Factors Influencing Online Buying Behavior of. The Qualitative Report, 1-15.Appendix 11957052914651 COLLEGE OF BUSINESS QUESTIONNAIRESFACTORS INFLUENCING CUSTOMERS SATISFACTION IN ONLINE SHOPPINGDear Respondents,Thank you for participating in this research which is related to the factors influencing satisfaction of customer toward online shopping. The study aim to identify the factors influencing of satisfaction customers in online shopping. As we know, online shopping is the item that easier to purchase during online. In addition, it can save time and energy because just doing transaction.We would appreciate very much if you could spend about 15-20 minutes of your precious time to complete this survey form. This data collected from this survey will be used for academic research purpose in order to gain better understanding pertaining to above mentioned research.Your participation is voluntary and all information will be kept strietly confidential. We sincerely hope you will answer these question with utmost honest.Thanks you very much for your kind cooperation.PART A: DEMOGRAPHIC BACKGROUNDPlease tick ( ) an appropriate box.1407287239522266700238125Gender Male Female25045672556511419860255270273939243459Age 19- 21 22-24 25>30168852368551529080236220347091236474Highest level of education Foundation undergraduate post graduated2675128250698Programmed337718410464834671010795157797511684 Muamalat economic other: 27974292293621663065234950304800232537Financial Support411441933782 PTPTN Mara Yayaysan otherOn every, how often you shop online? 176276262763 Everydays 17589519685A monthly164465235585 Every 6 week158115241046 yearlyPART B: RESPONDENT’S VIEW ON FACTOR INFLUENCES CUSTOMERS SATISFACTION IN ONLINE SHOPPING.1 2 3 4 5EXTREMLY DIASAGREE DISAGREE NEUTRAL AGREE EXTREMLY AGREE For each of the following statement, please circle the relevant number on its right based side which represent your choice above the rate:PART 1: ADVERTISEMENT1.1 After watching the advertisement , I want get more information about this product 1 2 3 4 51.2 I like this product after I watch this online advertisement 1 2 3 4 51.3 This advertisement is very attractive to me 1 2 3 4 51.4 The online advertisement contains a huge amount information. 1 2 3 4 51.5 I think the advertised product is in accord with the real product 1 2 3 4 5PART 2: PRODUCT QUALITY2.1 Higher credibility of the online seller better quality of product 1 2 3 4 52.2 product quality is important to me when I shop online 1 2 3 4 52.3 I do not mind the real products have differences between the photos of the product when I shop online 1 2 3 4 52.4 Overall, the quality of products sold online have lower quality than product sold at solid shops 1 2 3 4 5PART 3: BRANDS3.1 I feel very comfortable purchasing brand online 1 2 3 4 53.2 I purchase a lot of this brand’s service online 1 2 3 4 53.3 I consider this clothes brand is my first choice if I buy same product through online 1 2 3 4 53.4 This clothing brand is a name I can always trust 1 2 3 4 5PART 4: SHOPPING EXPERIENCES4.1 I have negative experiences with internet purchase in the past 1 2 3 4 54.2 I have searched for a product on the internet before 1 2 3 4 54.3 I have purchased a product from an online store before 1 2 3 4 54.4 The product I purchased looks exactly alike 1 2 3 4 54.5 When shopping on the internet, I am satisfied with the service given 1 2 3 4 5PART 5: CUSTOMER SATISFACTION5.1 My choice to purchase from this website was a wise one. 1 2 3 4 55.2 I have truly enjoyed purchasing from this website 1 2 3 4 55.3 I am satisfied with my most recent decision to purchase from this website 1 2 3 4 55.4 If I had to do it over again, I’d make my most recent online purchase at this website 1 2 3 4 55.5When I purchased from this website, I am never disappointed 1 2 3 4 5APPENDIX 2DATASET ACTIVATE DataSet1.SAVE OUTFILE=’C:UsersUserDownloadsdemographic.sav’ /COMPRESSED.RELIABILITY /VARIABLES=B1.1 B1.2 B1.3 B1.4 B1.5 /SCALE(‘Advertisements’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.ReliabilityDataSet1 C:UsersUserDownloadsdemographic.savScale: AdvertisementsCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alpha N of Items.890 5Item StatisticsMean Std. Deviation NB1.1 4.23 .750 100B1.2 4.00 .876 100B1.3 4.09 .805 100B1.4 3.93 .913 100B1.5 3.75 1.019 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB1.1 15.77 9.835 .628 .888B1.2 16.00 8.667 .760 .859B1.3 15.91 9.052 .754 .862B1.4 16.07 8.490 .758 .860B1.5 16.25 7.866 .779 .857Scale StatisticsMean Variance Std. Deviation N of Items20.00 13.354 3.654 5RELIABILITY /VARIABLES=B2.1 B2.2 B2.3 B2.4 /SCALE(‘Product Quality’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: Product QualityCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alphaa N of Items-.291 4a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.Item StatisticsMean Std. Deviation NB2.1 4.06 .851 100B2.2 4.58 .622 100B2.3 2.13 1.220 100B2.4 2.77 1.213 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB2.1 9.48 3.646 -.316 .123B2.2 8.96 3.776 -.340 .037B2.3 11.41 1.739 .036 -.728aB2.4 10.77 1.593 .090 -.947aa. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.Scale StatisticsMean Variance Std. Deviation N of Items13.54 3.342 1.828 4RELIABILITY /VARIABLES=B2.3 B2.4 /SCALE(‘Improve of Product Quality’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: Improve of Product QualityCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alpha N of Items.695 2Item StatisticsMean Std. Deviation NB2.3 2.13 1.220 100B2.4 2.77 1.213 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB2.3 2.77 1.472 .532 .B2.4 2.13 1.488 .532 .Scale StatisticsMean Variance Std. Deviation N of Items4.90 4.535 2.130 2RELIABILITY /VARIABLES=B3.1 B3.2 B3.3 B3.4 /SCALE(‘Brands’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: BrandsCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alpha N of Items.911 4Item StatisticsMean Std. Deviation NB3.1 4.01 .835 100B3.2 3.78 1.106 100B3.3 3.82 .957 100B3.4 3.95 .845 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB3.1 11.55 7.038 .787 .891B3.2 11.78 5.628 .832 .879B3.3 11.74 6.437 .796 .886B3.4 11.61 6.887 .815 .882Scale StatisticsMean Variance Std. Deviation N of Items15.56 11.219 3.349 4RELIABILITY /VARIABLES=B4.1 B4.2 B4.3 B4.4 B4.5 /SCALE(‘Shopping Experiences’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: Shopping ExperiencesCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alphaa N of Items-.172 5a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.Item StatisticsMean Std. Deviation NB4.1 3.40 1.303 100B4.2 4.35 .626 100B4.3 4.31 .677 100B4.4 3.33 1.280 100B4.5 3.39 1.246 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB4.1 15.38 5.571 -.362 .366B4.2 14.43 4.167 .189 -.377aB4.3 14.47 4.252 .119 -.322aB4.4 15.45 3.321 .018 -.313aB4.5 15.39 3.553 -.014 -.237aa. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.Scale StatisticsMean Variance Std. Deviation N of Items18.78 5.042 2.245 5RELIABILITY /VARIABLES=B4.2 B4.3 B4.4 B4.5 /SCALE(‘Shopping Experiences’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: Improve of Shopping ExperiencesCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alpha N of Items.366 4Item StatisticsMean Std. Deviation NB4.2 4.35 .626 100B4.3 4.31 .677 100B4.4 3.33 1.280 100B4.5 3.39 1.246 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB4.2 11.03 5.181 .000 .443B4.3 11.07 5.136 -.008 .454B4.4 12.05 2.290 .424 -.074aB4.5 11.99 2.576 .361 .051a. The value is negative due to a negative average covariance among items. This violates reliability model assumptions. You may want to check item codings.Scale StatisticsMean Variance Std. Deviation N of Items15.38 5.571 2.360 4RELIABILITY /VARIABLES=B5.1 B5.2 B5.3 B5.4 B5.5 /SCALE(‘Customer Satisfaction’) ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIVE SCALE /SUMMARY=TOTAL.Scale: Customer SatisfactionCase Processing SummaryN %Cases Valid 100 100.0Excludeda 0 .0Total 100 100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbach’s Alpha N of Items.662 5Item StatisticsMean Std. Deviation NB5.1 3.92 .907 100B5.2 4.03 .797 100B5.3 4.11 .803 100B5.4 4.09 .818 100B5.5 3.22 1.244 100Item-Total StatisticsScale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach’s Alpha if Item DeletedB5.1 15.45 6.432 .420 .609B5.2 15.34 5.823 .709 .490B5.3 15.26 5.629 .765 .463B5.4 15.28 5.739 .709 .486B5.5 16.15 8.250 -.086 .886Scale StatisticsMean Variance Std. Deviation N of Items19.37 9.185 3.031 5COMPUTE Advertisements=(B1.1 + B1.2 + B1.3 + B1.4 + B1.5) / 5.EXECUTE.COMPUTE ProductQuality=(B2.1 + B2.2 + B2.3 + B2.4) / 4.EXECUTE.COMPUTE Brands=(B3.1 + B3.2 + B3.3 + B3.4) / 4.EXECUTE.COMPUTE ShoppingExperiences=(B4.1 + B4.2 + B4.3 + B4.4 + B4.5) / 5.EXECUTE.COMPUTE CustomerSatisfaction=(B5.1 + B5.2 + B5.3 + B5.4 + B5.5) / 5.EXECUTE.DESCRIPTIVES VARIABLES=Advertisements ProductQuality Brands ShoppingExperiences CustomerSatisfaction /STATISTICS=MEAN STDDEV MIN MAX.DescriptivesDescriptive StatisticsN Minimum Maximum Mean Std. DeviationAdvertisements 100 2.40 5.00 4.0000 .73085ProductQuality 100 2.75 4.75 3.3850 .45702Brands 100 1.25 5.00 3.8900 .83735ShoppingExperiences 100 2.60 5.00 3.7560 .44909CustomerSatisfaction 100 1.60 5.00 3.8740 .60613Valid N (listwise) 100 FREQUENCIES VARIABLES=Gender /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.FrequenciesStatisticsGender N Valid 100Missing 0Mean 1.62Median 2.00Mode 2Std. Deviation .488Variance .238Range 1Minimum 1Maximum 2Percentiles 25 1.0050 2.0075 2.00GenderFrequency Percent Valid Percent Cumulative PercentValid male 38 38.0 38.0 38.0female 62 62.0 62.0 100.0Total 100 100.0 100.0 FREQUENCIES VARIABLES=Ages /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.StatisticsAges N Valid 100Missing 0Mean 1.82Median 2.00Mode 2Std. Deviation .458Variance .210Range 2Minimum 1Maximum 3Percentiles 25 2.0050 2.0075 2.00AgesFrequency Percent Valid Percent Cumulative PercentValid 19-21 21 21.0 21.0 21.022-24 76 76.0 76.0 97.025 and above 3 3.0 3.0 100.0Total 100 100.0 100.0 FREQUENCIES VARIABLES=Education /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.StatisticsHighest education N Valid 100Missing 0Mean 1.97Median 2.00Mode 2Std. Deviation .223Variance .050Range 2Minimum 1Maximum 3Percentiles 25 2.0050 2.0075 2.00Highest educationFrequency Percent Valid Percent Cumulative PercentValid Foundation 4 4.0 4.0 4.0Undergraduate 95 95.0 95.0 99.0post-graduated 1 1.0 1.0 100.0Total 100 100.0 100.0 FREQUENCIES VARIABLES=Programmed /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.StatisticsProgrammed N Valid 100Missing 0Mean 2.80Median 2.00Mode 3Std. Deviation 2.165Variance 4.687Range 11Minimum 1Maximum 12Percentiles 25 1.0050 2.0075 3.00ProgrammedFrequency Percent Valid Percent Cumulative PercentValid Muamalat Administration 30 30.0 30.0 30.0Economic 21 21.0 21.0 51.0Risk management and Insurance 31 31.0 31.0 82.0Islamic and Finance 7 7.0 7.0 89.0Banking 2 2.0 2.0 91.0International Business Management 1 1.0 1.0 92.0Logistic and Transportation 3 3.0 3.0 95.0Marketing 1 1.0 1.0 96.0Business Administration 1 1.0 1.0 97.0Accounting Information System 1 1.0 1.0 98.0Agribusiness Management 1 1.0 1.0 99.0Finance 1 1.0 1.0 100.0Total 100 100.0 100.0 FREQUENCIES VARIABLES=Financial /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.StatisticsFinancial support N Valid 100Missing 0Mean 2.30Median 1.00Mode 1Std. Deviation 1.850Variance 3.424Range 8Minimum 1Maximum 9Percentiles 25 1.0050 1.0075 3.00Financial supportFrequency Percent Valid Percent Cumulative PercentValid PTPTN 57 57.0 57.0 57.0MARA 7 7.0 7.0 64.0YAYASAN 15 15.0 15.0 79.0Parents 2 2.0 2.0 81.0JPA 14 14.0 14.0 95.0Pinjaman Selangor 2 2.0 2.0 97.0PBU (JPA) 1 1.0 1.0 98.0Biasiswa 1 1.0 1.0 99.0Zakat 1 1.0 1.0 100.0Total 100 100.0 100.0 FREQUENCIES VARIABLES=Often /NTILES=4 /STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM MEAN MEDIAN MODE /ORDER=ANALYSIS.StatisticsOften shop online N Valid 100Missing 0Mean 3.01Median 3.00Mode 4Std. Deviation .823Variance .677Range 2Minimum 2Maximum 4Percentiles 25 2.0050 3.0075 4.00Often shop onlineFrequency Percent Valid Percent Cumulative PercentValid Amonthly 33 33.0 33.0 33.0Every 6 week 33 33.0 33.0 66.0Yearly 34 34.0 34.0 100.0Total 100 100.0 100.0 CORRELATIONS /VARIABLES=Advertisements ProductQuality Brands ShoppingExperiences CustomerSatisfaction /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.CorrelationsCorrelationsAdvertisements ProductQuality BrandsAdvertisements Pearson Correlation 1 .041 .758**Sig. (2-tailed) .687 .000N 100 100 100ProductQuality Pearson Correlation .041 1 -.025Sig. (2-tailed) .687 .804N 100 100 100Brands Pearson Correlation .758** -.025 1Sig. (2-tailed) .000 .804 N 100 100 100ShoppingExperiences Pearson Correlation .137 .293** .145Sig. (2-tailed) .175 .003 .149N 100 100 100CustomerSatisfaction Pearson Correlation .653** .184 .704**Sig. (2-tailed) .000 .067 .000N 100 100 100ShoppingExperiences CustomerSatisfactionAdvertisements Pearson Correlation .137 .653**Sig. (2-tailed) .175 .000N 100 100ProductQuality Pearson Correlation .293** .184Sig. (2-tailed) .003 .067N 100 100Brands Pearson Correlation .145 .704**Sig. (2-tailed) .149 .000N 100 100ShoppingExperiences Pearson Correlation 1 .351**Sig. (2-tailed) .000N 100 100CustomerSatisfaction Pearson Correlation .351** 1Sig. (2-tailed) .000 N 100 100**. Correlation is significant at the 0.01 level (2-tailed).T-TEST GROUPS=Gender(1 2) /MISSING=ANALYSIS /VARIABLES=Advertisements /CRITERIA=CI(.95).T-TestGroup StatisticsGender N Mean Std. Deviation Std. Error MeanAdvertisements male 38 4.3421 .72769 .11805female 62 3.7903 .65429 .08310Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. t dfAdvertisements Equal variances assumed 1.989 .162 3.922 98Equal variances not assumed 3.822 72.025Independent Samples Testt-test for Equality of MeansSig. (2-tailed) Mean Difference Std. Error DifferenceAdvertisements Equal variances assumed .000 .55178 .14070Equal variances not assumed .000 .55178 .14436Independent Samples Testt-test for Equality of Means95% Confidence Interval of the DifferenceLower UpperAdvertisements Equal variances assumed .27257 .83099Equal variances not assumed .26401 .83956T-TEST GROUPS=Gender(1 2) /MISSING=ANALYSIS /VARIABLES=ProductQuality /CRITERIA=CI(.95).Group StatisticsGender N Mean Std. Deviation Std. Error MeanProductQuality male 38 3.3487 .43705 .07090female 62 3.4073 .47095 .05981Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. t dfProductQuality Equal variances assumed .023 .879 -.620 98Equal variances not assumed -.631 82.927Independent Samples Testt-test for Equality of MeansSig. (2-tailed) Mean Difference Std. Error DifferenceProductQuality Equal variances assumed .537 -.05857 .09445Equal variances not assumed .529 -.05857 .09276Independent Samples Testt-test for Equality of Means95% Confidence Interval of the DifferenceLower UpperProductQuality Equal variances assumed -.24601 .12886Equal variances not assumed -.24307 .12592T-TEST GROUPS=Gender(1 2) /MISSING=ANALYSIS /VARIABLES=Brands /CRITERIA=CI(.95).Group StatisticsGender N Mean Std. Deviation Std. Error MeanBrands male 38 4.4013 .71551 .11607female 62 3.5766 .75149 .09544Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. t dfBrands Equal variances assumed .324 .571 5.423 98Equal variances not assumed 5.488 81.380Independent Samples Testt-test for Equality of MeansSig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the DifferenceLowerBrands Equal variances assumed .000 .82470 .15207 .52293Equal variances not assumed .000 .82470 .15027 .52573Independent Samples Testt-test for Equality of Means95% Confidence Interval of the DifferenceUpperBrands Equal variances assumed 1.12647Equal variances not assumed 1.12367Group StatisticsGender N Mean Std. Deviation Std. Error MeanShoppingExperiences male 38 3.7000 .47363 .07683female 62 3.7903 .43371 .05508Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. tShoppingExperiences Equal variances assumed .825 .366 -.976Equal variances not assumed -.955Independent Samples Testt-test for Equality of Meansdf Sig. (2-tailed) Mean DifferenceShoppingExperiences Equal variances assumed 98 .331 -.09032Equal variances not assumed 73.094 .343 -.09032Independent Samples Testt-test for Equality of MeansStd. Error Difference 95% Confidence Interval of the DifferenceLower UpperShoppingExperiences Equal variances assumed .09254 -.27397 .09333Equal variances not assumed .09454 -.27873 .09808Group StatisticsGender N Mean Std. Deviation Std. Error MeanCustomerSatisfaction male 38 4.0789 .59827 .09705female 62 3.7484 .58049 .07372Independent Samples TestLevene’s Test for Equality of Variances t-test for Equality of MeansF Sig. tCustomerSatisfaction Equal variances assumed 1.264 .264 2.732Equal variances not assumed 2.712Independent Samples Testt-test for Equality of Meansdf Sig. (2-tailed) Mean DifferenceCustomerSatisfaction Equal variances assumed 98 .007 .33056Equal variances not assumed 76.557 .008 .33056Independent Samples Testt-test for Equality of MeansStd. Error Difference 95% Confidence Interval of the DifferenceLower UpperCustomerSatisfaction Equal variances assumed .12099 .09046 .57066Equal variances not assumed .12188 .08785 .57327OnewayDescriptivesAdvertisements N Mean Std. Deviation Std. Error 95% Confidence Interval for MeanLower Bound Upper Bound19-21 21 4.0286 .76233 .16635 3.6816 4.375622-24 76 3.9763 .71701 .08225 3.8125 4.140225 and above 3 4.4000 1.03923 .60000 1.8184 6.9816Total 100 4.0000 .73085 .07308 3.8550 4.1450DescriptivesAdvertisements Minimum Maximum19-21 3.00 5.0022-24 2.40 5.0025 and above 3.20 5.00Total 2.40 5.00ANOVAAdvertisements Sum of Squares df Mean Square F Sig.Between Groups .540 2 .270 .500 .608Within Groups 52.340 97 .540 Total 52.880 99 .DescriptivesProductQuality N Mean Std. Deviation Std. Error 95% Confidence Interval for MeanLower Bound Upper Bound19-21 21 3.2619 .43644 .09524 3.0632 3.460622-24 76 3.4145 .46107 .05289 3.3091 3.519825 and above 3 3.5000 .50000 .28868 2.2579 4.7421Total 100 3.3850 .45702 .04570 3.2943 3.4757DescriptivesProductQuality Minimum Maximum19-21 2.75 4.0022-24 2.75 4.7525 and above 3.00 4.00Total 2.75 4.75ANOVAProductQuality Sum of Squares df Mean Square F Sig.Between Groups .424 2 .212 1.015 .366Within Groups 20.254 97 .209 Total 20.678 99 DescriptivesBrands N Mean Std. Deviation Std. Error 95% Confidence Interval for MeanLower Bound Upper Bound19-21 21 4.0357 .80345 .17533 3.6700 4.401422-24 76 3.8191 .84222 .09661 3.6266 4.011525 and above 3 4.6667 .57735 .33333 3.2324 6.1009Total 100 3.8900 .83735 .08374 3.7239 4.0561DescriptivesBrands Minimum Maximum19-21 2.50 5.0022-24 1.25 5.0025 and above 4.00 5.00Total 1.25 5.00ANOVABrands Sum of Squares df Mean Square F Sig.Between Groups 2.638 2 1.319 1.916 .153Within Groups 66.777 97 .688 Total 69.415 99 DescriptivesShoppingExperiences N Mean Std. Deviation Std. Error 95% Confidence Interval for MeanLower Bound Upper Bound19-21 21 3.6762 .52717 .11504 3.4362 3.916222-24 76 3.7763 .43077 .04941 3.6779 3.874825 and above 3 3.8000 .40000 .23094 2.8063 4.7937Total 100 3.7560 .44909 .04491 3.6669 3.8451DescriptivesShoppingExperiences Minimum Maximum19-21 2.60 4.8022-24 2.60 5.0025 and above 3.40 4.20Total 2.60 5.00ANOVAShoppingExperiences Sum of Squares df Mean Square F Sig.Between Groups .171 2 .085 .419 .659Within Groups 19.795 97 .204 Total 19.966 99 DescriptivesCustomerSatisfaction N Mean Std. Deviation Std. Error 95% Confidence Interval for MeanLower Bound Upper Bound19-21 21 3.9238 .52336 .11421 3.6856 4.162022-24 76 3.8553 .63800 .07318 3.7095 4.001125 and above 3 4.0000 .34641 .20000 3.1395 4.8605Total 100 3.8740 .60613 .06061 3.7537 3.9943DescriptivesCustomerSatisfaction Minimum Maximum19-21 3.00 5.0022-24 1.60 5.0025 and above 3.60 4.20Total 1.60 5.00ANOVACustomerSatisfaction Sum of Squares df Mean Square F Sig.Between Groups .126 2 .063 .169 .845Within Groups 36.246 97 .374 Total 36.372 99 RegressionVariables Entered/RemovedaModel Variables Entered Variables Removed Method1 ShoppingExperiences, Advertisements, ProductQuality, Brandsb . Entera. Dependent Variable: CustomerSatisfactionb. All requested variables entered.Model SummarybModel R R Square Adjusted R Square Std. Error of the Estimate Change StatisticsR Square Change F Change df1 df2 Sig. F Change1 .776a .602 .586 .39023 .602 35.962 4 95 .000a. Predictors: (Constant), ShoppingExperiences, Advertisements, ProductQuality, Brandsb. Dependent Variable: CustomerSatisfactionANOVAaModel Sum of Squares df Mean Square F Sig.1 Regression 21.906 4 5.476 35.962 .000bResidual 14.467 95 .152 Total 36.372 99 a. Dependent Variable: CustomerSatisfactionb. Predictors: (Constant), ShoppingExperiences, Advertisements, ProductQuality, BrandsCoefficientsaModel Unstandardized Coefficients Standardized Coefficients t Sig.B Std. Error Beta 1 (Constant) .053 .425 .124 .902Advertisements .207 .083 .250 2.509 .014ProductQuality .166 .090 .125 1.838 .069Brands .352 .072 .487 4.864 .000ShoppingExperiences .282 .093 .209 3.047 .003a. Dependent Variable: CustomerSatisfactionResiduals StatisticsaMinimum Maximum Mean Std. Deviation NPredicted Value 2.5869 4.7660 3.8740 .47039 100Residual -1.13443 1.07946 .00000 .38227 100Std. Predicted Value -2.736 1.896 .000 1.000 100Std. Residual -2.907 2.766 .000 .980 100a. Dependent Variable: CustomerSatisfaction
