Essay For Medical School Application Samples

Essay For Medical School Application SamplesAn essay for medical school application samples should be prepared carefully. It is better to be a little bit vague and creative rather than it being too definite and detailed. To help you with this, there are some tips you can follow.Most sample essays include important information that will help you as a future doctor. But be sure to highlight all the details as this will help you when filling out the rest of the application. The essay will likely be used as an interview part. It is important to be specific when describing your interests, career goals, and other things. Be sure to highlight these details as well as any special aspects or accomplishments that you would like the admissions officer to know about you.Most medical school applicants are very eager to know about their strengths and weaknesses. These will most likely be reviewed during the interview part of the essay. Be sure to be honest about your strengths and weaknesses and w hat you intend to do to correct them. And be sure to mention why the medical school has a special place in your heart. Make a strong case for your desire to become a doctor.In general, medical school application samples will include questions that ask about the applicants' hobbies, interests, talents, and leadership skills. These questions are important because the admissions officer will use them to gauge your suitability for a challenging environment. Have fun and don't hesitate to show your creativity in answering these questions.The essay may also include data entries. These entries are used to reflect the applicant's academic history, internships, and professional credentials. This can be very detailed, but be sure to detail your achievements and strengths. Data entries should also have a strong connection to your personal interests and experiences.Most medical school application samples include questions for the students to answer. You can either write the questions and then a nswer them yourself or you can have someone else write them for you. Depending on your choice, your answers will be used as the basis for your essay. Whether you write them yourself or you have someone else do it, it is best to write them as specifically as possible.One key idea to keep in mind while writing the essay is to stay as true to yourself as possible. Keep your answers factual and give as much information as possible. It's okay to be creative, but make sure that you aren't writing a scholarly essay. Write for a medical school application samples for people who will actually be interested in becoming a doctor.Medical school application samples can be found online and are easy to read. It is best to read the essays without corrections or editing. When doing so, you can pinpoint any grammar or spelling mistakes you may have made. In addition, the essays should be formatted properly so that they can be submitted and printed quickly. Don't put too much thought into it unless yo u are a student who is applying for medical school.

Implications for the development of sainsburys in the future - Free Essay Example

Implications for the development of sainsburys in the future 1. Introduction The retail industry is one of the oldest industrial sectors of UK having its roots based in the 19th century. An article in The Financial Times about Sainsburys dropping sales and consequently market shares triggered the research topic and we drove ourselves to the history of supermarkets to reveal the secret behind the big giants (Tesco, Sainsburys and ASDA) fighting for the top position in the market. The reason to select Sainsburys rather than other two foes from the flock was the interesting reign of Sainsburys in past 100 years of business. l The article first illustrates the supermarket retailers background and outlines the present problems. l Secondly, it analyzes the perception of customers towards the current supermarkets and the extent to which their needs are satisfied by Sainsburys. l Finally, the possible solutions are evaluated and it indicates some recommendations for implementation. The work established in the following research is purely based on a quantitative data collection and scrutiny with a wide implementation of literature and marketing research tools. In the following research work, we, group of five students, have cloaked the role of researchers and reaped a considerable amount of sagacious know-how about conducting a research and using marketing research gears in different areas of research. 2. Background to the problem 2.1 About Sainsburys Sainsburys Supermarket is the longest standing major food retailing chain in the UK, with their first store opened in 1869. The mission and policy of Sainsburys is to provide customers with healthy, safe, fresh and tasty food. The quality and fair prices of Sainsburys is taking responsibility to their business. Sainsburys stores have particularly emphasized on fresh food and they devote themselves to create continuous innovation. Moreover, they are concerned about customer needs and based on these needs improve products regularly. Its market share is around 16 % and now they serve over 18 million customers a week. Sainsburys own 455 supermarkets and 301 convenience stores, the type of these stores are categorized into 3 types, which are Main Mission outlets, Main Plus format stores (hypermarkets),and Mixed mission format shops (Sainsburys Central and Local). The large stores offer approximately 30,000 products and offer and support the non-food products and services in many of t heir stores. Around 88% of British households are provided by the internet-based home delivery shopping service. At present, Sainsburys is the third biggest supermarket chain in Britain after the countrys largest retailer Tesco and Wal-Mart owned ASDA. Their business mission is to be the consumers first choice for food, delivering products of outstanding quality and great service at a competitive cost working faster, simpler and together.'(https://www.sainsburys.co.uk/sol/index.jsp, N.D) 2.2 Describe the problem Sainsburys used to take the biggest slice of the whole retail market in the UK. However, since 1995, Tesco started with their membership cards, and out of blue their sales have increased rapidly. Sainsburys became the third biggest supermarket chain in Britain after the countrys largest retailer Tesco and Wal-Mart owned Asda. (https://news.bbc.co.uk/1/hi/business/4694974.stm, N.D, BBC News) 2.3The main reasons for exploring the problem The formula of Sainsburys success could be concluded in the points which are listed below: à ¢Ã¢â€š ¬Ã‚ ¢ High quality products quality assurance à ¢Ã¢â€š ¬Ã‚ ¢ Wide range of products à ¢Ã¢â€š ¬Ã‚ ¢ Different customer segmentations (https://www.foodprocessing-technology.com/features/feature56457/, ND) Although Sainsburys still follows these points to manage the company, but according to the reduction of the market share, the profit of managing Sainsburys has been more seriously affected. Although Sainsburys could retain the balance of revenue and expenditure, moreover, it remained permanent. It still needs to attract more customers and raise its market share. Furthermore, the needs of its customers should be valued and respected. We need to do marketing research to explore the possible factors which affect customers satisfaction and then use marketing strategies to improve these factors to increase customers shopping demands and enhance their loyalty. 3. Problem Definition An extensive study of market conditions and retail industry in United Kingdom gave us a brief idea about the status of Sainsburys in the retail industry. The largest retailer in the UK till mid 1990s suddenly dropped to the third position loosing its hold on market and decrement in the potential market customers. The decline in market shares and a low rate of sales returns was enough to define the problem for Sainsburys in the present market scenario. With new retailers emerging in the sector deploying all their marketing strategies to be the best in the race, it is very important for Sainsburys to take a brave step now to protect their current position and then to improvise on their hold in the industry. 3.1 Management Decision Problem What can Sainsburys doto regain the market share in retailing industry? The management team now require to sit down and discuss the failure points and the current shortcoming to establish a conclusion to why there is a constant downfall in the shares of the company and why it is being overtaken by a company (ASDA) which has its central operating sector based in a country (USA) which is thousands of miles away from UK. As per a latest study, the retail industry is expected to show an increase in 15% annually and Sainsburys needs to identify the market requirement till they become history for the consumers. (sources) 3.2 Marketing Research Problem The Management Problem was turned into a Research Problem which more specifically tackles the aim of this study. l To determine the various needs of shoppers and the extent to which current Sainsburys experiences were satisfying those needs compared to the competitors. The conversion of the management problem into a research problem makes the concept easier to understand and tackle. It gives a broader prospective of the problem and alongside makes a simple way to handle and implement the desired implications. 3.3 Research Components The research components further diversify the purpose of research and explain the problem in detail. The following components define the research problem: * What is the demographic and psychographic profile of the customers? * What do customers expect when going shopping in the stores? * How well does Sainsburys existing products and service offering meet customers needs compared to Tesco and ASDA? * Are there any customer needs that are not being adequately met by Sainsburys? * How often do customers go shopping per week? 4. Research Approach Development In this section, it reveals the Exploratory Research conducted and the Conceptual Model. 4.1 Exploratory Research 4.1.1 Literature Reviews This section concerns some available information extracted from Literature Reviews. Based on literature reviews, service quality, is seen as an important factor, and closely related to a retail companies performance. Service quality is perceived by customers as the result of comparing the expectations about the service they are going to receive and their perceptions of the retail companys actions. (Rodolfo Vazquez et al, 2001). It is of great help to demonstrate how to assess the service performance of a retail company and it carries some implications itself as well, which is beneficial when making the model of this study. According to Yan Lu et al (2008) there are five dimensions of service quality in a retail store setting, including: physical aspects, reliability, personal interaction, problem solving and policy. In addition, Rodolfo Vazquez et al. (2001) found that service quality in retail companies adopting the commercial format of supermarkets has a four factor structure (physical aspects, reliability, personal interaction and policies). Physical Environment Physical environment incorporates the inward and outward appearance of the store. According to Rodolfo Vazquez et al (2001), physical environment involves the simplicity and importance of shopping from the internal appearance of the sales outlet. Based on this, Rodolfo Vazquez et al states that there are two physical aspects of supermarkets: store appearance, which includes: decoration, fixtures, equipment, cleanliness, design of product and services publicity leaflets and the convenience of shopping, which includes: interior design and store layout of sections and product shelf position. According to Poping Lin (2005), traditional wisdom teaches that one key to win market share is offering a wide variety of products, which can be helpful for attracting a wider variety of customers. Providing products and services at a close and most convenient location, is the very core of deriving the best return from investments, also the ambience a store maintains can influence a customers purc hase decisions to a great extent. (Prakash Gupta, year) Reliability According to A.Parasuraman et al. (1988), to be reliable is being able to perform the promised service dependably and accurately. Based on his research, A.Parasuraman et al. found out that reliability is the most important factor taken into consideration by customers when they evaluate a retail companys overall service quality. This has also been supported by many researches in other studies. Dabholker et al. (1996) indicate that reliability in the eyes of customers is a combination of keeping promise and doing it well. Keeping promise means that a retail company should stock enough products to satisfy customers needs and guarantee the products quality as well as allowing returns and exchanges and being willing to dealing with any problems from customers. On the other side, in the terms of doing it well, a company is expected to be able to provide customers with fast sales transactions and precise information, such as sales promotions, price and sales slips. (Rodolfo Vazquez et al, 2001) Personal Interaction Based on existing literature, it is noted that customers are not only interested in the product offerings and physical environment, but also on the service provided by staffs. Personal interaction involves the process followed in order to obtain the sale and the service encounters where the need arises while coming in contact with the retail company employees. (Rodolfo Vazquez et al, 2001) According to Prakash Gupta (year), consumers look for help whenever they are in an emergency. In that situation, store employees helpful advice and assistance will help to reduce the attrition rate of customers and enhance shopping experience. Policy Policy captures aspects of service quality affected by the strategies of the prices and brand assortment. Brand assortment policy must be established with great care and also a large and wide-ranging assortment of well-known brands is needed. (Rodolfo Vazquez et al, 2001) In addition, retail stores should be able to come up with an attractive pricing policy. According to Siu and Cheung, policy has a great impact on customers repeat purchase intention. (Yan Lu, Yoo-Kyoung Seock, 2008) Customer Satisfaction Customer satisfaction is a measure of how an organizations total product performs in relation to a set or customers requirement (Nigel Hill, Jim Alexander, 2006). There is no better advertisement than a Satisfied Customer and nothing worse than a Dissatisfied Customer (Phillip Kotler et al, 2008). Marketing Researchers and Managers have realized how important customer satisfaction is. According to Robert Heller (2006), customer based strategy is the only important form of strategy, product and producer driven strategies are fast dying. Similarly, Customer Satisfaction is the ultimate goal, and an investment that often doesnt produce result in a short term, but leads to Customer loyalty in a medium or long term (Craig Cochran, 2003). The lack of attention to customer Satisfaction costs companies money because there is an intractable connection to high level of customer satisfaction and increased share holder value (Chris Denove, James D. Power IV, 2007) Loyalty It is believed that maintaining the current customers costs less than attracting new customers, in the light of this; it is wise for companies to pay close attention to retaining their current customers. There are efficiencies in dealing with existing customers rather than new customers. (Ruth N.Bolton, 2000) Relative retention has been shown to explained profits better than market share, scale, cost position, or any of the other variables usually associated with competitive advantage. (Niren Sirohi et al, 1998) In general, the customers loyalty is indicated by an intention to perform a diverse set of behaviors that signal a motivation to maintain a relationship with focal firm, including allocating a higher share of the category wallet to the specific service provider, engaging in positive word-of -mouth, and repeat purchasing. (Ulrich R. Orth, Mark T.Green, 2009) According to Zeithaml et al., favorable assessment of service quality leads to favorable behavioral intentions such as positive word-of-mouth and preference for one company over others. (Yan Lu, Yoo-Kyoung Seock, 2008). In other word, higher satisfaction relates to higher loyalty. (Ulrich R. Orth, Mark T.Green, 2009) 4.2 Conceptual Model On the basis of the literature reviews, a final model has been defined (Refer to figure 1), which consists of two parts. In the first part of the model, there are 4 Independent variables (namely Physical Environment, Reliability, Personal Interaction, Policy), consisting of several aspects respectively, that may have an impact on the Dependent variables (Customer Satisfaction as shown in the model). As regard to the second part of the model, we assume that the Independent variable, Satisfaction, is connected with Loyalty, Dependent variable. Table 1: Summary of Research Questions and Hypothesis Research Question 1: What are the factors that influence customers satisfaction when shopping in the supermarkets? H1: There is a significant relationship between physical environment and customer satisfaction. H2: There is a significant relationship between reliability and customer satisfaction. H3: There is a significant relationship between personal interaction and customer satisfaction. H4: There is a significant relationship between policy and customer satisfaction. Research Question 2: What is the relationship between customer satisfaction and customer loyalty? H5: There is a significant relationship between customer satisfaction and customer loyalty. Specification of information needed Depending upon each component of the problem and the conceptual model, research questions and hypothesis, the information needed can be defined as follows: Component 1: To determine the factors customers are apprehensive about when selecting a store for shopping. Perceptions of customers on factors that influence choice of supermarkets Component 2: To determine how well do existing service offering meet customers needs. Evaluation of customers on the performance of ASDA. Evaluation of customers on the performance of Sainsburys. Evaluation of customers on the performance of Tesco. 5. Research Design and Methodology 5.1 Research Design In order to obtain the required information to solve the marketing research problems, research design was carried out for the further step. The research design is the framework or blueprint for conducting the marketing research project that specify the procedures necessary to obtain the information needed. (Malhotra, 2009) There are two basic types of research designs available which are classified in terms of the research objectives: exploratory and conclusive. (Malhotra, 2009) In this report, both exploratory and conclusive research designs were conducted for Sainsburys. 5.1.1 Exploratory research design In order to understand and gain insight to the problem that the company is facing now, a detailed literature review was prepared. 5.1.2 Conclusive research design After gaining understanding of current situation and management-decision problem of the company from exploratory research, the conclusive research was designed to make the management decision, testing hypotheses and also examining relationships between factors influencing the supermarket selection and customer satisfaction of Sainsburys as compared to its competitors. Furthermore, the descriptive research was used to describe the market characteristics and determine those relationships. Due to time constraint, the single cross-sectional design was used and a selected group of respondents were measured at one time. The data-collection technique used in this report was the survey conducted by a predesigned questionnaire. 5.2 Methodology 5.2.1 Secondary research methodology In order to collect data about the companys problem in general, two types of the secondary research were collected. The first one is the internal secondary data. Obtaining information from companys annual report provided the background of the company and fundamental data about its market shares. The second one is the external secondary data. In research approach development step, literatures have been reviewed. The information was retrieved from many sources including census data that provided elementary background of demographic data of UK households and consumption behaviors of UK consumers. In addition, abstracts in form of bibliographic databases have been retrieved from the University of Leeds Portals library. Gaining information from above secondary data can help us to understand the companys situation, define the research problem and also develop an approach to that problem. Journal articles and books provide knowledge in defining the variables in the research model which led to formulate the hypotheses and forming questionnaire design. 5.2.2 Primary research methodology 5.2.2.1 Research approach The major research approach chosen in this report is questionnaire survey. A detailed survey selecting a large sample was conducted to support the literature to get a deeper understanding of factors in choosing supermarkets. Furthermore, surveys were chosen in order to gain insights into the consumer behaviors pattern and consumers perceptions of UK supermarkets. 5.2.2.2 Sampling design Due to budget and time limitation, sample surveys were selected based on direct questioning. A sample is a subgroup of the elements of the population selected for participation in the study. (Malhotra, 2009) In this report, the sample group was selected from the total population in the UK. In determining the sample size, the statistical method was chosen. The sample size was calculated as follows: 2500 * N * Z2 n = ____________________ [25(N-1)] + [2500 * Z2] Where n = sample size required N = population size Z = number of standard errors The total population size (N) is 41,020,711 which are derived from the estimated people aged at 15-64 years in the United Kingdom as of July 2009. The source of information is The Central Intelligence Agency (CIA). In this case, the most commonly used 95% confidence level is applied. When the variables are taken, the result obtained from the formula could be as below: 2,500 * 41,020,711 * 1.962 n = ________________ __________ 25(41,020,711 -1) + (2,500 * 1.962) = 384 Due to time and cost constraints, 40% of the total sample size was taken into consideration, therefore adding up to 154 samples could be collected in conducting the survey. For the sampling method used in the surveys, the data collected through a survey of 154 respondents was divided into two proportions equally. The probability sampling techniques used in this report is Simple Random Sampling (SRS) in which each sample in the total population has an equal probability in selecting. (Malhotra, 2009) Therefore, half of the total questionnaires were executed by people living in Leeds and the rest was from people living outside Leeds. Moreover, two ways in distributing the questionnaires were conducted: paper based and online based survey. 5.2.2.3 Questionnaire Design (Refer to Appendix 1) The division of research problem into components made the way to design the questionnaire to analyze the market scenario and the customer needs. The background of the questionnaire design was the basic study of the component and sub-dividing the components into various similar factors which are considered to select or prefer any retail industry. The Physical Factors were classified as size, location, layout, and etc. of the store and mentioned as questions in the draft. 12 broad questions were decided on the basis of relevance and availability of time for the participant to come out with rational answers without any external or internal influence of reviewer or the industry. The intention was to collect some primary data about the general perception of people and then segmenting them as per their responses and choices. As required questionnaire was designed in 4 major segments in five pages including the introduction and purpose of study, literature was consulted to find out the best blue print of the questionnaire. It was also considered that all the questions are easy to understand and the response is useful for the analysis of the components. The questionnaire was designed with both multiple choice and dichotomous questions with all the scales referred as per the 5 Point Likert Scale l The first section dealt with the general introduction of the respondents to the retail industry, the shopping habits and the familiarity with the retail market. l Section 2 were the general factors affecting the selection of supermarkets and respondents preference of retail stores, continued with the acuity of three major supermarkets in the UK namely ASDA, Sainsburys and Tesco. l Section 3 covered the satisfaction and loyalty level of the participants towards their favorite retail store. l The final section was the personal information about the respondent assisting with the demographical and segmentation of the participants. The sentences of the questionn aire were made simple and all the options and questions were double checked for any offence in the questions. It was specially taken care that every response should be informative and two open questions were also provided in the questionnaire in order to find depth know-how about the stance of people towards Sainsburys irrespective they are loyal members of Sainsburys shopping club or not. 5.2.2.4 Field work The data was collected between the 18th and the 22th of November, 2009. The questionnaires were collected in different times and different places, targeting all supermarket shoppers throughout the UK; starting from University of Leeds, city centre, flat residents and people outside Leeds. The questionnaire delivering method was personal interviews in order to control the response rate and clarify the complex questions. 5.2.2.5 Analytical issues A diversity of analytical methods was used to gather the data and analyze the results. To analyze the basic statistics, descriptive statistics has been used. Furthermore, graphical representations and one-sample tests were applied to present the demographic and psychographic profile of respondents and also examine the influential factors when choosing a supermarket. To analyze the relationship between independent and dependent variables, the regression analysis has been used. Bivariate regressions were used to test the hypotheses H1, H2, H3, H4, and H5 while multiple regression analysis was used to test whether or not there is collective relation between all hypothetical factors and customer satisfaction. 6. Results and Analysis In this part, SPSS was used to represent the basic statistics, graphical representations and one-sample tests in order to answer the five problem components. Also, it was used for testing whether or not the results support the hypotheses. 6. 1. Analysis of Problem Components 6.1.1 Examining demographic and psychographic profile of respondents There are 154 questionnaires have been completed which 60 % is female and the other 40% is male. (Refer to Appendix 2) More than 50% of respondents aged between 18-24 years old and they are all students. The second most majority is people aged between 25-34 years old. The minority is people aged more than 65 years old. (Refer to Appendix 3) By far the most of respondents are single due to the fact that they are students. One-fifth of them are married and there is no widowed who filled in the questionnaires. (Refer to Appendix 4) More than a half of respondents are students and nearly 30% of all respondents are working and employed by the company. (Refer to Appendix 5) Nearly half spend between  £20 40 when going shopping while the average household annual income is below  £ 15,000. (Refer to Appendix 6 and 7) 6.1.2 Examining factors affecting supermarket selection Table 2: One-sample T-test statistics results One-Sample Statistics N Mean Std. Deviation Std. Error Mean Variety of Products 154 4.4091 .77218 .06222 Operating Hours 154 4.2468 .90973 .07331 Location/Nearness 154 4.4870 .82634 .06659 Size of Store 154 3.7013 .91559 .07378 Price 154 4.5065 .83429 .06723 Layout of Store 154 3.7727 .93949 .07571 Wide Selection of Brand 154 4.1948 .83296 .06712 Quality of Products 154 4.4481 .74133 .05974 Queuing Time 154 4.1169 .92848 .07482 Customer Service 154 4.0519 1.01487 .08178 One-Sample Test Test Value = 3 95% Confidence Interval of the Difference t df Sig. (2-tailed) Mean Difference Lower Upper Variety of Products 22.646 153 .000 1.40909 1.2862 1.5320 Operating Hours 17.007 153 .000 1.24675 1.1019 1.3916 Location/Nearness 22.331 153 .000 1.48701 1.3555 1.6186 Size of Store 9.505 153 .000 .70130 .5555 .8471 Price 22.408 153 .000 1.50649 1.3737 1.6393 Layout of Store 10.207 153 .000 .77273 .6232 .9223 Wide Selection of Brand 17.800 153 .000 1.19481 1.0622 1.3274 Quality of Products 24.240 153 .000 1.44805 1.3300 1.5661 Queuing Time 14.928 153 .000 1.11688 .9691 1.2647 Customer Service 12.863 153 .000 1.05195 .8904 1.2135 One sample T-test were carried out to test the extent to which the mean scores are significantly higher than the mid point 3 on the scale ranging from 1 = the least important to 5 = the most important. Results summarized in the table indicate that customers evaluate the Independent variables positively when choosing which supermarket to shop in, but at different levels. It is also obvious from the table that Price, Location/Nearness, Quality of Products, Variety of Products have the strongest mean. It is important to note that the 4 Independent variables Physical Environment, Reliability, Personal Interaction and Policy are important factors that customers would take into account when choosing supermarkets. 6.1.3 Examining customers perception of Sainsburys, compared to ASDA and TESCO This component is tested by comparing the mean score of the service quality factors of Sainsburys with that of Tesco and ASDA. (Refer to Appendix 8) Variety of products Based on the research, Sainsburys mean score for product variety is 3.967 which is low compared to that of Tesco 4.1883 and slightly higher than ASDAs 3.9091. This means that the respondents feel Sainsbury doesnt have as many product offering and variety to choose from as Tesco and have slightly more product offerings than ASDA. Operating Hours Based on the research, Sainsburys mean score for operating hours is 3.7727 which is low compared to that of Tescos 4.1299 and ASDAs 3.9870. This means that the respondents feel Sainsbury doesnt have a flexible operating hours compared to that of Tesco and ASDA. Location/Nearness Based on the research, Sainsburys mean score for Location/nearness is 3.8117 which is higher compared to that of Tescos 3.5260 and ASDAs 2.9091. This means that our respondents feel Sainsburys store is more accessible based on location and nearness than Tesco and ASDA. Size of Store Based on the research, Sainsburys mean score for size of store is 3.6623 which are lower compared to Tescos 3.8831 and ASDAs 3.9675. This means that the respondents feel Sainsburys stores are not as big as Tesco and ASDA stores, based on size and store space. Price Based on the research Sainsburys mean score for price is 3.2727 which is lower compared to Tesco 3.9610s and ASDAs 4.974. This means that the respondents feel Sainsburys price offering is not as satisfying as Tesco and ASDAs price offerings. Layout of Store Based on the research Sainsburys mean for store layout is 3.7078 which is higher compared to Tescos 3.7922 and ASDAs 3.6234. This means that the respondents feel that Sainsburys stores are not as organized and arranged as Tesco stores but better than ASDA stores. Wide selection of Brand Based on the research Sainsburys mean for wide selection of brands is 3.7273 which is low compared to that of Tescos 4.0325 and ASDAs 3.8636. This means that the respondents feel Sainsburys doesnt provide a wide selection of brands of a particular product compared to what Tesco and ASDA are offering. Quality of product Based on the research Sainsburys mean for product quality is 4.1364 which is quite high compared to that of Tescos 3.8312 and ASDAs 3.6364. This means that the respondents feel that the quality of products found in Sainsbury stores is better and more reliable than those in Tesco and ASDA stores. Queuing time Based on the research Sainsburys mean for queuing time is 3.6169 which is higher than that of Tescos 3.5325 and ASDAs 3.4286. This means that the respondents feel that they spend lesser time on the queue in a Sainsburys store than in Tesco and ASDA stores Customer Service Based on the research Sainsburys mean for customer service is 3.7403 which is higher than Tescos 3.6688 and ASDAs 3.4870. This means that the respondents feel that they are more satisfied with the customer service provided in a Sainsburys store than in a Tesco or ASDA store. 6.1.4 Examining factors that are not being satisfied and needs to be improved. Given feedback by using open-ended question, responses can be categorized into 5 factors that should be improved for Sainsburys. They are price, promotion, location, operating hours, and parking lot. Not surprisingly, price factor is by far the most important things need to be improved. This reflects in the price policy of Sainsburys that they always keep price high while offering high quality of product, though it results in customer dissatisfaction. More promotion and location of supermarket respectively are the second and third factors that should be enhanced. (Refer to Appendix 9) 6.1.5 Examining the frequency of customer going for shopping in supermarket Nearly half of respondents go for shopping once a week and more than one-third of them go more than once a week. A slight of all responses goes for shopping only once a month. (Refer to Appendix 10) 6.2 Hypothesis Testing Hypothesis 1: There is a significant relationship between Physical Environment and Customer Satisfaction. The hypothesis was tested using by a Bivariate Regression Analysis. Table 3: Bivariate regression analysis result (Hypothesis 1) (Refer to Appendix 11) R Square B Beta Sig. (Constant) Physical .056 3.029 .287 .237 .003 The R Sq value of 0.056 shows a slight correlation between the predictor variable (Physical Environment) and the criterion variable (Customer Satisfaction). We can define the formula for the regression line: Y=0.287 X + 3.029 The regression line has a positive slope, reflecting a positive a correlation (.237) between the predictor and the criterion. This means that more improved the physical environment is, higher would be the customers satisfaction. The significance score of .003 shows that the association is significant at p .01. Hypothesis 2: There is a significant relationship between Reliability and Customer Satisfaction. Table 4: Bivariate regression analysis result (Hypothesis 2) (Refer to Appendix 12) R Square B Beta Sig. (Constant) Reliability .047 3.372 .196 .218 .007 The R Sq value of 0.047 shows a slight correlation between the predictor variable (Reliability) and the criterion variable (Customer Satisfaction). We can define the formula for the regression line: Y=0.196 X + 3.372 The regression line has a positive slope, reflecting a positive a correlation (.218) between the predictor and the criterion. This means that higher the reliability, higher would be the customers satisfaction. The significance score of .007 shows that the association is significant at p .01. H3: There is a significant relationship between Personal Interaction and Customer Satisfaction. Table 5: Bivariate regression analysis result (Hypothesis 3) (Refer to Appendix 13) R Square B Beta Sig. (Constant) Personal Interaction .026 3.792 .104 .162 .045 The R Sq value of 0.026 shows a slight correlation between the predictor variable (Personal Interaction) and the criterion variable (Customer Satisfaction) . We can define the formula for the regression line: Y=0.104 X + 3.792 The regression line has a positive slope, reflecting a positive a correlation (.162) between the predictor and the criterion. This means that the customer service is directly proportional to the customers satisfaction. The significance score of .045 shows that the association is significant at p .05. H4: There is a significant relationship between Policy and Customer Satisfaction. Table 6: Bivariate regression analysis result (Hypothesis 4) (Refer to Appendix 14) R Square B Beta Sig. (Constant) Policy .065 3.141 .246 .256 .001 The R Sq value of 0.065 shows a slight correlation between the predictor variable (Policy) and the criterion variable (Customer Satisfaction) . We can define the formula for the regression line: Y=0.246 X + 3.141 The regression line has a positive slope, reflecting a positive a correlation (.256) between the predictor and the criterion. This means that the better the policy, higher is the customers satisfaction. The significance score of .001 shows that the association is significant at p .01. Multiple Regression Analysis Hypothesis: There is a collective relation between all hypothetical factors (Physical Environment, Reliability, Personal Interaction and Policy) and complete Customer Satisfaction. Table 7: Multiple regression analysis result (Refer to Appendix 15) Adjusted R Square Beta Sig. Physical Environment .055 .095 .371 Reliability 070 .539 Policy .148 .166 Personal interaction .027 .789 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 5.163 4 1.291 3.247 .014a Residual 59.228 149 .398 Total 64.391 153 a. Predictors: (Constant), Personal Interaction, Policy, Physical, Reliability b. Dependent Variable: Satisfaction In order to test the above hypothesis, a multiple regression analysis using Enter Method was used to measure the correlations between four independent variables (Physical Environment, Reliability, Personal Interaction and Policy) and the dependent variable (Customer Satisfaction). A significant model emerged (F4,149= 3.247, p0.05, adjusted R square = .055) Predictor variable Beta P Physical Environment .095 P.05 Reliability .070 P.05 Policy .148 P.05 Personal Interaction .027 P.05 From the Correlations Table, the inter-dependability between the multiple factors and the dependent variable is very minimal, and therefore there is no certain correlation established between the independent variables and dependent variable. The results indicate that all four independent variables are not the predictors of dependent variable (Customer Satisfaction) in the model, hence not supporting the hypothesis. Hence, in order to find some significance, a multiple regression analysis using the Stepwise Method was used to measure the above hypothesis: Table 8: Multiple regression analysis result (Refer to Appendix 16) Adjusted R Square Beta Sig. Physical Environment .059 .126 .211 Reliability .112 .230 Policy .256 .001 Personal interaction .084 .119 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 4.205 1 4.205 10.621 .001a Residual 60.186 152 .396 Total 64.391 153 a. Predictors: (Constant), Policy b. Dependent Variable: Satisfaction According to the results above, a significant model emerged (F1,152= 10.621, p0.01, adjusted R square 0.059) Predictor variable Beta P Physical Environment .126 P.01 Reliability .112 P.01 Policy .256 P.01 Personal Interaction .084 P.01 The results indicate that three out of four independent variables are not the predictors of dependent variable (Customer Satisfaction) in the model, but Policy relates with the customer satisfaction variable. The findings of the Multiple Regression (Stepwise Method) are as follows: All independent variables have a slight relation with the dependent (Customer Satisfaction) variable. The adjusted R square value is again found to be lower, but a significant relation is being established between the Policy and Customer satisfaction. However all other three variables namely, Physical Environment, Reliability and Personal Interaction plays no significant role in customer satisfaction and hence regarded as excluded variab les. The ANOVAs results of the regression also depicts that the complete model is significant. Hypothesis 5: There is a significant relationship between Customer Satisfaction and Loyalty Table 5: Bivariate Regression analysis result (Hypothesis 5) (Refer to Appendix 17) R Square B Beta Sig. (Constant) Satisfaction .433 .403 .793 .658 .000 The R Sq value of 0.433 shows a regular correlation between the predictor variable (Customer Satisfaction) and the criterion variable (Loyalty). We can define the formula for the regression line: Y=0.793 X + 0.403 The regression line has a positive slope, reflecting a positive a correlation (.658) between the predictor and the criterion. This means that the higher the customer satisfaction is, higher would be the loyalty. The significance score of .000 shows that the association is significant at p .01. 7. Limitation: The complete model was tested using SPSS and different regression models and unfortunately it didnt prove as reliable as it should have been. The R square index was very nominal and the significance was also not sufficient with the entire hypothesis. Further analyzing the model and studying the project from basics the following limitations were concluded which are as follows: Unproductive Sample: The total population of retail shoppers was used and calculated a sample of 384 potential respondents for the quantitative research, whereas due to financial limitations only 40% of the total sample i.e. 154 were introspected and results were analyzed. It is assumed that the sample size and the participants were not enough to conclude the hypothesis and researchers should keep the sampling factor in consideration while conducting any research work. Sample Segmentation: The sample should have been demographically distributed to all age groups and genders, whereas a majority of respondents belonged to similar age groups and professional set. This unwanted segmentation of participants influenced the responses to a large extent and consequently the reliability of data was in vain when generalized to the complete market scenario. In the nutshell a very convenient sample was selected rather than a representative one. Questionnaire Design: The questionnaire was designed after hours of literature review and days of homework. But we still feel that it was very early for us to come out with a productive and informative questionnaire which would have eliminated the error of significance form the data. The graphical model and the previous retail studies supported the hypothesis and it is strong to believe that the questionnaire designing required more professionalism. Ethno-Centric Sample: The study of retail industry is very explicit and wide studies with the perceptions of all around the country were to be considered. But the respondents were mostly based locally whereas the distribution should have been national. Time Constraint: The most noteworthy factor for the complete research study was time and finance. Starting from the basic primary research and the literature review required more time and deep introspection. The psychology of respondent plays an important role in authenticity of data, which was not deemed. Moreover, after the research we feel like that a detailed in-depth focus group interview would have yielded more results and facilitated us to compile more reliable data. 8. Recommendation For Sainsburys to have an increase in market share, and perhaps return to its former position as the No 1 retail store in the United Kingdom, the following is recommended: * This research has shown that price is an important factor to the respondent. Therefore it is recommended to reduce their pricing based on the preference especially for product that can easily be purchased in other stores at a lesser price. Also, considering the current scenario of global economic recession price definitely plays an important role in the buying behavior of consumers. * From the above analysis, it can be seen that operating hours and store size are important factors to the respondents. Therefore, it is recommended to have more flexible operating hours and bigger stores across the United Kingdom. * A wider brand selection, with different price range is recommended so everyone has an option to pick from regardless of ones levels of income. References A.Parasuraman et al., (1988), SERVQUAL: A Multiple-item Scale for Measuring Customer Perceptions of Service Quality BBC News,[online],à £Ã¢â€š ¬?accessed 31.10.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://news.bbc.co.uk/1/hi/business/4694974.stm Bized, ,[online] , à £Ã¢â€š ¬?accessed 1.11.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://www.bized.co.uk/compfact/sainsbury/sainsindex.htm Chris Denove, James D. Power, IV, Satisfaction: How Every Great Company Listens to the Voice of the Customer Craig Cochran, Customer satisfaction: tools, techniques, and formulas for success Dabholkar et al., (1996), A measure of service quality for retail stores: scale development and validation Foodprocessing-technology [online],à £Ã¢â€š ¬?accessed 31.10.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://www.foodprocessing-technology.com/features/feature56457/ Kotler, Gray Armstrong, Veronica wong John Saunders, Principles of Marketing Robert, Duke, (1988), A structural an alysis of the UK grocery retail market, University of Leeds School of Business and Economic Studies, Leeds Prakash Gupta, Retail customer satisfaction Model RCSM,[online],à £Ã¢â€š ¬?accessed 6.11.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://www.evancarmichael.com/Small-Business-Consulting/3444/RETAIL-CUSTOMER-SATISFACTION-MODEL-RCSM.html Poping Lin, 09.06.2005, When product variety backfires, [online],à £Ã¢â€š ¬?accessed 15.11.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://hbswk.hbs.edu/archive/4980.html Robert Heller, 2006-07-08,Customer Satisfaction: Develop your strategy for achieving customer satisfaction and sustaining it, [online] , à £Ã¢â€š ¬?accessed 5.11.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://www.thinkingmanagers.com/management/customer-satisfaction.php Rodolfo Vazquez et al., (2001), Service quality in supermarket retailing identifying critical service experiences Ruth N.Bolton, (2000) A dynamic model of the duration of the customers rela tionship with a continuous service provider, The role of satisfaction Sainsburys SWOT analysis [online],à £Ã¢â€š ¬?accessed 31.10.09à £Ã¢â€š ¬Ã¢â‚¬Ëœ Available from: https://www.swot-pest-porter.co.uk/index.php?action=vthreadforum=1topic=5 Nigel Hill, Jim Alexander, The handbook of customer satisfaction and loyalty measurement Niren Sirohi et al., (1998), A model of consumer perceptions and store loyalty intentions for a supermarket retailer Ulrich R. Orth, Mark T. Green., (2009), Consumer loyalty to family versus non-family business: The roles of store image, trust and satisfaction Yan Lu, Yoo-Kyoung Seock, (2008), The influence of grey consumers service quality perception on satisfaction and store loyalty behavior Appendix 1: Questionnaire ________________________________________________________ Questionnaire on Perceptions of UK Supermarkets Name (Optional):________ Gender: Male/ Female Location:___________ Section1: General shopping behavior Please indicate the answers that apply to you. Q1. How often do you go for shopping in a retail supermarket? Once a week à ¢Ã¢â‚¬â€œÃ‚ ¡ More than once a week à ¢Ã¢â‚¬â€œÃ‚ ¡ Once a fortnight à ¢Ã¢â‚¬â€œÃ‚ ¡ Once a month à ¢Ã¢â‚¬â€œÃ‚ ¡ Q2. In your opinion, what time of the day is best suitable for you to go shopping? Before 12:00 noon à ¢Ã¢â‚¬â€œÃ‚ ¡ Between 12:00 4:00 pm à ¢Ã¢â‚¬â€œÃ‚ ¡ Between 4:01 8:00 pm à ¢Ã¢â‚¬â€œÃ‚ ¡ After 8:00 pm à ¢Ã¢â‚¬â€œÃ‚ ¡ Section2: Factors affecting supermarket selection Q3. Please rate the following factors using the Five-point Scale as your priorities to select a retail supermarket, where 1 represents the least important and 5 represents the most important. Least Important Most Important a Variety of Products 1 2 3 4 5 b Operating Hours 1 2 3 4 5 c Location/Nearness 1 2 3 4 5 d Size of Store 1 2 3 4 5 e Price 1 2 3 4 5 f Layout of Store 1 2 3 4 5 g Wide Selection of brand 1 2 3 4 5 h Quality of Products 1 2 3 4 5 i Queuing Time 1 2 3 4 5 j Customer Service 1 2 3 4 5 Q4. Please rate your perception of the following retail shops using the Five-point Scale as their performance in the areas mentioned below: (Where 1 represents Poor and 5 represents Excellent). ASDA Sainsburys Tesco Poor Excellent Poor Excellent Poor Excellent a Variety of Products 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 b Operating Hours 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 c Location/Nearness 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 d Size of Store 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 e Price 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 f Layout of Store 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 g Wide Selection of brand 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 h Quality of Products 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 i Queuing Time 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 j Customer Service 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Section3: Brand Loyalty Q5. Which amongst the following is your most favorite store for retail shopping? ASDA à ¢Ã¢â‚¬â€œÃ‚ ¡ Sainsburys à ¢Ã¢â‚¬â€œÃ‚ ¡ Tesco à ¢Ã¢â‚¬â€œÃ‚ ¡ Other à ¢Ã¢â‚¬â€œÃ‚ ¡ Please specify Q6. Please rate your perception as regards to your most favorite retail shop; using the Five-point Scale where 1=Strongly Disagree, 2= Disagree, 3= Neutral, 4= Agree and 5= Strongly Agree Strongly Disagree Strongly Agree a) I am very happy with the overall shopping experience with the store 1 2 3 4 5 b) I am happy to shop in the same store again 1 2 3 4 5 c) I would recommend the store to all my friends and family 1 2 3 4 5 d) I would consider myself as a highly loyal customer to this store 1 2 3 4 5 Q7. (a) What do you like most about Sainsburys compared to other retailers? (b) Please give one suggestion of improvement for Sainsburys compared to other retailers. Section4: Personal Information Please indicate the answers that describe your current situation best. Q8. Age group: 18-24 à ¢Ã¢â‚¬â€œÃ‚ ¡ 25-34 à ¢Ã¢â‚¬â€œÃ‚ ¡ 35-44 à ¢Ã¢â‚¬â€œÃ‚ ¡ 45-54 à ¢Ã¢â‚¬â€œÃ‚ ¡ 55-64 à ¢Ã¢â‚¬â€œÃ‚ ¡ 65+à ¢Ã¢â‚¬â€œÃ‚ ¡ Q9. Marital status: Single à ¢Ã¢â‚¬â€œÃ‚ ¡ Married à ¢Ã¢â‚¬â€œÃ‚ ¡ Divorced/Separated à ¢Ã¢â‚¬â€œÃ‚ ¡ Widowed à ¢Ã¢â‚¬â€œÃ‚ ¡ Q10. What option best describes your current occupation? Self-Employed à ¢Ã¢â‚¬â€œÃ‚ ¡ Employed à ¢Ã¢â‚¬â€œÃ‚ ¡ Student à ¢Ã¢â‚¬â€œÃ‚ ¡ Unemployed à ¢Ã¢â‚¬â€œÃ‚ ¡ Other à ¢Ã¢â‚¬â€œÃ‚ ¡ Q11. How much is your total average expenditure when you go into a supermarket? Less than  £20 à ¢Ã¢â‚¬â€œÃ‚ ¡ Between  £20 to  £40 à ¢Ã¢â‚¬â€œÃ‚ ¡ Between  £41 to  £60 à ¢Ã¢â‚¬â€œÃ‚ ¡ Above à ‚ £60 à ¢Ã¢â‚¬â€œÃ‚ ¡ Q12. Household annual income: Below  £15,000 à ¢Ã¢â‚¬â€œÃ‚ ¡  £15,000 25,000 à ¢Ã¢â‚¬â€œÃ‚ ¡  £25,001 40,000 à ¢Ã¢â‚¬â€œÃ‚ ¡ Above  £40,000 à ¢Ã¢â‚¬â€œÃ‚ ¡ We, University of Leeds Student, thank you very much for your cooperation. Appendix 2: Appendix 3: Appendix 4: Appendix 5: Appendix 6: Appendix 7: Appendix 8: Sainsburys Descriptive Statistics N Mean Std. Deviation Variety of Products 154 3.9675 .83563 Operating Hours 154 3.7727 .82860 Location/Nearness 154 3.8117 .92014 Size of Store 154 3.6623 .93039 Price 154 3.2727 1.01796 Layout of Store 154 3.7078 .88506 Wide Selection of Brand 154 3.7273 .91661 Quality of Products 154 4.1364 .75032 Queuing Time 154 3.6169 .92318 Customer Service 154 3.7403 .87675 Valid N (listwise) 154 ASDA Descriptive Statistics N Mean Std. Deviation Variety of Products 154 3.9091 .93839 Operating Hours 154 3.9870 .90739 Location/Nearness 154 2.9091 1.23861 Size of Store 154 3.9675 .79557 Price 154 4.0974 .83054 Layout of Store 154 3.6234 .90082 Wide Selection of Brand 154 3.8636 .90798 Quality of Products 154 3.6364 .97564 Queuing Time 154 3.4286 .94182 Customer Service 154 3.4870 .99828 Valid N (listwise) 154 Tesco Descriptive Statistics N Mean Std. Deviation Variety of Products 154 4.1883 .85382 Operating Hours 154 4.1299 .79788 Location/Nearness 154 3.5260 1.17822 Size of Store 154 3.8831 .96979 Price 154 3.9610 .89211 Layout of Store 154 3.7922 .91947 Wide Selection of Brand 154 4.0325 .86636 Quality of Products 154 3.8312 .87675 Queuing Time 154 3.5325 .87200 Customer Service 154 3.6688 .92923 Valid N (listwise) 154 Appendix 9: Appendix 10: Appendix 11: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .237a .056 .050 .63237 a. Predictors: (Constant), Physical Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.029 .397 7.637 .000 Physical .287 .095 .237 3.004 .003 a. Dependent Variable: Satisfaction Appendix 12: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .218a .047 .041 .63526 a. Predictors: (Constant), Reliability Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.372 .309 10.897 .000 Reliability .196 .071 .218 2.749 .007 a. Dependent Variable: Satisfaction Appendix 13: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .162a .026 .020 .64228 a. Predictors: (Constant), Personal Interaction Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.792 .214 17.745 .000 Personal Interaction .104 .051 .162 2.023 .045 a. Dependent Variable: Satisfaction Appendix 14: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .256a .065 .059 .62925 a. Predictors: (Constant), policy Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.141 .332 9.458 .000 policy .246 .075 .256 3.259 .001 a. Dependent Variable: Satisfaction Appendix 15: Correlations Satisfaction Physical Reliability Policy Personal Interaction Pearson Correlation Satisfaction 1.000 .237 .218 .256 .162 Physical .237 1.000 .527 .627 .416 Reliability .218 .527 1.000 .541 .623 Policy .256 .627 .541 1.000 .346 Personal Interaction .162 .416 .623 .346 1.000 Sig. (1-tailed) Satisfaction .002 .003 .001 .022 Physical .002 .000 .000 .000 Reliability .003 .000 .000 .000 Policy .001 .000 .000 .000 Personal Interaction .022 .000 .000 .000 N Satisfaction 154 154 154 154 154 Physical 154 154 154 154 154 Reliability 154 154 154 154 154 Policy 154 154 154 154 154 Personal Interaction 154 154 154 154 154 Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate 1 .283a .080 .055 .63048 a. Predictors: (Constant), Personal Interaction, Policy, Physical, Reliability b. Dependent Variable: Satisfaction Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 (Constant) 2.773 .418 6.629 .000 Physical .116 .129 .095 .898 .371 .546 1.831 Reliability .063 .102 .070 .616 .539 .477 2.097 Policy .143 .102 .148 1.393 .166 .544 1.839 Personal Interaction .017 .065 .027 .269 .789 .599 1.670 a. Dependent Variable: Satisfaction Appendix 16: Descriptive Statistics Mean Std. Deviation N Satisfaction 4.2110 .64874 154 Physical 4.1234 .53588 154 Reliability 4.2825 .72067 154 Policy 4.3506 .67429 154 Customer Service 4.0519 1.01487 154 Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate 1 .256a .065 .059 .62925 a. Predictors: (Constant), Policy b. Dependent Variable: Satisfaction Correlations Satisfaction Physical Reliability Policy Customer Service Pearson Correlation Satisfaction 1.000 .237 .218 .256 .162 Physical .237 1.000 .527 .627 .416 Reliability .218 .527 1.000 .541 .623 Policy .256 .627 .541 1.000 .346 Customer Service .162 .416 .623 .346 1.000 Sig. (1-tailed) Satisfaction .002 .003 .001 .022 Physical .002 .000 .000 .000 Reliability .003 .000 .000 .000 Policy .001 .000 .000 .000 Customer Service .022 .000 .000 .000 N Satisfaction 154 154 154 154 154 Physical 154 154 154 154 154 Reliability 154 154 154 154 154 Policy 154 154 154 154 154 Customer Service 154 154 154 154 154 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF 1 (Constant) 3.141 .332 9.458 .000 Policy .246 .075 .256 3.259 .001 1.000 1.000 a. Dependent Variable: Satisfaction Excluded Variablesb Model Beta In T Sig. Partial Correlation Collinearity Statistics Tolerance VIF Minimum Tolerance 1 Physical .126a 1.256 .211 .102 .607 1.646 .607 Reliability .112a 1.205 .230 .098 .707 1.414 .707 Personal interaction .084a 1.000 .319 .081 .880 1.136 .880 a. Predictors in the Model: (Constant), Policy b. Dependent Variable: Satisfaction Appendix 17: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .658a .433 .429 .59099 a. Predictors: (Constant), Satisfaction Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .403 .314 1.283 .201 Satisfaction .793 .074 .658 10.772 .000 a. Dependent Variable: Loyalty