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\def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2013-01-15 (revised: 15 January 2013)} \def\TheID{\makeatother } \def\TheDate{2013-01-15} \title{Demographic Variables as Antecedents of Service Quality and Purchasing Intention Aspects in Retailing} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ \belowdisplayskip \abovedisplayskip \abovedisplayshortskip \z@ plus2\p@ \belowdisplayshortskip 4\p@ plus2\p@ minus2\p@ \def\@listi{\leftmargin\leftmargini \topsep 2\p@ plus1\p@ minus1\p@ \parsep 2\p@ plus\p@ minus\p@ \itemsep 1pt} } \makeatother \fvset{frame=single,numberblanklines=false,xleftmargin=5mm,xrightmargin=5mm} \fancyhf{} \setlength{\headheight}{14pt} \fancyhead[LE]{\bfseries\leftmark} \fancyhead[RO]{\bfseries\rightmark} \fancyfoot[RO]{} \fancyfoot[CO]{\thepage} \fancyfoot[LO]{\TheID} \fancyfoot[LE]{} \fancyfoot[CE]{\thepage} \fancyfoot[RE]{\TheID} \hypersetup{citebordercolor=0.75 0.75 0.75,linkbordercolor=0.75 0.75 0.75,urlbordercolor=0.75 0.75 0.75,bookmarksnumbered=true} \fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} \date{} \usepackage{authblk} \providecommand{\keywords}[1] { \footnotesize \textbf{\textit{Index terms---}} #1 } \usepackage{graphicx,xcolor} \definecolor{GJBlue}{HTML}{273B81} \definecolor{GJLightBlue}{HTML}{0A9DD9} \definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Ajmer Singh} \affil[1]{ Kurukshetra University} \renewcommand\Authands{ and } \date{\small \em Received: 9 December 2012 Accepted: 5 January 2013 Published: 15 January 2013} \maketitle \begin{abstract} This study is done to examine the perceived service quality and purchasing aspects in various retail stores. This study becomes an important study as it helps in examining the differences among many variables of perceived service quality and purchasing aspects in retailing across the various demographic profiles. This study was carried out in three states. These three states are Delhi, Haryana (Gurgaon & Faridabad) and U.P. (Noida & Ghaziabad). A total sample size of 600 customers was chosen from seven organized stores in these three states. Finally 540 responses were received from these states. It gave a response rate of 90% in total. The data was analyzed with the help of proper statistical tools like descriptive statistics, Mean and Kruskal-Wallis test with One Way ANOVA was used. This test is applied as it is a non-parametric test and it is very helpful in finding out the difference among the different variables of Retail Service Quality Scale being used in this study. The scale used in this study was developed by Dhabolkar, Thorpe and Rentz. This scale was tested through reliability and validity first and then it was being used in the study to check out the significance difference among the different variables. The findings of the study state that there exists a significant difference among many variables across the various demographic profiles in the study. Finally implications for the managers are formulated in the study. \end{abstract} \keywords{rsqs scale, service quality, demographic aspects, purchasing and recommending intentions.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{Introduction}]{Introduction}\par etailing is a growing business in India. Nowadays organized retailing is growing at a rate of 18-20\% per annum. It has become very important to provide good service quality for the growth of any retail store in our country. Customers are moving towards organized retail stores at a fast rate. It has become very important to understand the different aspects of service quality in retailing. The important aspects of services quality were identified and used in formulating the business strategies \hyperref[b1]{(Parasuraman, Zeithaml and} {\ref Berry, 1985, 1988)}. As per the AT Kearney's report of Global Retail Development Index, India and Russia tops the list which was further followed by China, Vietnam and Ukraine. From the KPMG report, it was found that organized retail sector in India is going to grow at a higher rate than GDP growth rate of this country. The formats like hypermarkets, supermarkets, specialty stores as well as through departmental stores. Malls have penetrated into Indian market and they are marching towards small towns in our country. Malls are providing a new way of shopping by providing food, entertainment and shopping at one place. The various organized stores which have penetrated in the Indian market are Big Bazaar, Pantaloon, Spencer's, Ebony, Westside, Vishal Mega-mart etc. Hence it becomes important to understand the aspects of service quality in retailing to meet the customers' expectation levels. \section[{II.}]{II.} \section[{Review of Literatures}]{Review of Literatures}\par From the review of literature, it is found that service quality aspects are very important in retailing. Retailers are finding out new ways for developing new products, process and technologies which increase the overall customer value (Morgan and Hunt, 1994 and Woodruf, 1997). Parasuraman, Zeithaml and Berry developed a scale which is known as SERVQUAL scale to understand the different aspects service quality in banking as well as in hospitality sector. On the same basis Dhabolkar, Thorpe and Rentz developed Retail Service quality scale for measuring the service quality aspects in retailing. This scale has been already tested and used in many countries like Canada, South Africa and many European countries. In India this scale was checked through its reliability and validity (Singh, . The various aspects of Retail Service Quality Scale are having a significant impact on overall customer satisfaction to the customer (Singh, \hyperref[b4]{Ajmer, 2013)}. The aspects of retail service quality scale are showing a positive impact on the customer purchasing intentions of the products and services. The aspects of retail service quality scale are showing positive impact on recommending the products and services to the other customers as well as to family friends and relatives (Singh, . The various aspects of perceived service quality are being perceived differently across different demographic variables like age, gender, income, education as well as profession etc. According to Hofstede the demographic aspects have a significant III. \section[{Research Methodology}]{Research Methodology}\par This study was conducted in three states of India. These three states are Delhi, Haryana (Gurgaon \& Faridabad) and U.P. (Noida \& Ghaziabad). These areas are selected on the judgemental basis of the researcher as more and more organized stores are coming up in these areas. These three states like Delhi and in Haryana (Gurgaon \& Faridabad) and U.P. (Noida \& Ghaziabad) are showing maximum penetration of organized retail stores in northern state of India. Sample sizes of 600 customers are chosen from these three states and 200 customers from each state. \section[{a) Objectives of the Study}]{a) Objectives of the Study}\par This study is having two main objectives. 1. To explore the different demographic aspects necessary for retail stores in India. 2. To examine and to compare the perceived service quality variables across different demographic aspects. 3. To examine and to compare the overall customer satisfaction variable across different demographic aspects. 4. To examine and to compare the Purchasing variables across different demographic aspects. \section[{b) Hypotheses of the Study}]{b) Hypotheses of the Study}\par The following hypotheses are being formulated in the study.\par 1. There exists a significant difference among the different aspects of service quality across the various demographic aspects. 2. There exists a significant difference among the customer satisfaction across the various demographic aspects. 3. There exists a significant difference among the different Purchasing aspects across the various demographic aspects. \section[{c) Statistical Methods Used}]{c) Statistical Methods Used}\par The data analysis was done with the help of descriptive statistics method as well as other statistical methods like Kruskal-Wallis test with one way ANOVA also being used in the study to tests the various hypotheses in the study. This test is applied as a nonparametric test to test the various hypotheses in the study. \section[{IV. Data Analysis \& Data Interpretation}]{IV. Data Analysis \& Data Interpretation}\par A total sample size of 600 customers was chosen for this study. It was further decided to choose 200 customers from Delhi, 200 customers from Haryana (Gurgaon \&Faridabad) and 200 customers from U.P. (Noida \& Ghaziabad). A total 540 filled-in complete questionnaire were collected. A response rate of (90\%) was achieved. Hence from the customers a total of 90\% response was achieved by collecting the 540 filled questionnaires from 600 customers in total. important for the retail stores to design more products in the retail stores which fit the requirement of male people in the stores. From the table (4.3) it is found that 162 respondents are having income between (15,001-to-30,000) per month, whereas 84 respondents belong to income group up-to-15,000 per month and 118 respondents belong to (30,001-to-45,000) income group. Rest of the 74 respondents are having an income above Rs. 75,000 per month and 42 respondents belong to income category between Rs. (60,001-to-75,000) and 60 respondents belong to (45,001-to-60,000) income group. From this we can analyze that the customers from all income groups are visiting to the organized retail stores for shopping. But from this analysis it was found that customers having income upto 30,000 per month are more in number as compared to the customers having a large income group. From the table (4.5), it is found that 240 respondents are in the professional and administrative type of profession, whereas 100 respondents are running their own business. Rest 50 respondents are academician and 44 are the students. Hence from this we can conclude that customers belonging to professional and administrative jobs and customers running their own business are more in number who are visiting to these retail outlets. From the above table 4.8, it is found that there exists a significant difference in the dimension of physical aspects of Retail Service Quality Scale being used in the study. The various demographic variables like age, gender, education, income, marital status, profession and duration of dealing with the store. From the above analysis it is found that there exists a significant difference in physical aspect dimension of the above scale being used in the duration of service being used by the customer. In the next dimension reliability, there exists no significant difference among the various demographic variables being used in the study. In the next dimension personal interaction also, there exist no significant difference among the various demographic variables being used in the study. In the dimensions of problem solving used in the retail service quality scale being used in the age and gender are showing a significant difference in the study. In case of policy dimension, different income groups are showing a significant difference in the scale. In the final in determining the overall service quality scale being used in the study, different professional groups shows a significant difference in the study. The professional groups are divided into many types like student, govt. employees, other professionals like doctors, engineers, architect etc. also being used in this study. From the analysis of the study, it was found that these groups showed a significant difference among the various groups being used in the study. This table {\ref 4}.9 helps us to find out the significant difference among the different demographic variables in overall customer satisfaction across the different groups. From the above analysis it is found that there exists a significant difference among the different age groups designed in the study in the level of satisfaction of the customers. Hence from the above table we can say that there exists a significant difference in different age groups. In other demographic variables like gender, education, income, marital status, profession and duration of dealing with the outlet shows no significant difference across the various groups in the overall level of satisfaction. From the above table 4.10, it is found that there exists a significant difference in the overall behavior of the customers in different age groups across the various retail outlets. It was again found that in recommending the outlet to the other customers, there still exists a significant difference among the different age groups. In the next aspect of encouraging the friends and relatives for purchasing from the outlet, age and gender found a significant difference. In the next aspect which is concerned with switching to another outlet, when I feel a problem with this outlet, it was found that education, income and profession showed a significant difference across the different groups. The next aspect of staying with the outlet despite increasing the prices of the products, the duration of dealing showed a significant difference. The final aspect is complaining behavior in which the different profession showed a significant difference. \section[{a) Profile of the Respondents Taken for the Study}]{a) Profile of the Respondents Taken for the Study}\par V. \section[{Conclusions and Findings of the Study}]{Conclusions and Findings of the Study}\par To find out the relationship between service qualities, customer satisfaction, behavioural intentions and demographic variables Kruskal-Wallis-test is being performed. It is a non-parametric test designed to detect the differences among the populations that do not require any assumptions about the shape of the population's distributions. The main findings of the study are given below. 1) From the analysis it is analyzed that across the various age groups, there is a significant difference in customer satisfaction and purchasing intentions. In purchasing intentions, it is found that there is a significant difference in encouraging the friends and relatives to purchase from this outlet. It is found no significant in other aspects of service quality, and behavioural intentions.\par 2) It is also analyzed from the table that in male and female there is a significant difference in the perception of problem solving and encouraging the friends and relatives to purchase from the outlet, whereas in other aspects of service quality and customer satisfaction no significant difference is found.\par 3) It is also analyzed from the table that there is a significant difference in the perception of the customer towards switching intentions to another outlet across the various education levels. In other aspects of service quality and customer satisfaction, it is found no significant across the various age groups. 4) As per the different income groups, there is a significant difference towards policy dimensions of service quality and switching intention to another outlet if a customer experiences a problem with this outlet. In the other aspects of service quality, customer satisfaction and behavioural intentions it is found no significant. 5) As per the marital status, it is analyzed from the table that there is no significant difference in various aspects of service quality, customer satisfaction and behavioural intentions. 6) It is also analyzed from the table that across the various professions there is a highly significant difference in complaining behaviour of the customer and further it is followed by the significant difference in the switching intention to another outlet and the overall perception of service quality across the various Professions. 7) From the table, it is found that there is a significant difference in Physical aspects and continue with the outlet even if the store increases the prices of its products. \section[{Global}]{Global}\par The main implications of the study for the managers are as given below. 1. It is found that age becomes an important factor in different aspects of quality, customer satisfaction as well as behavioural aspects in retail stores. So it becomes important for the marketer to design the products and service to fulfil the different age groups. By doing this it will be possible for the marketer to provide adequate level of service quality, customer satisfaction as well as purchasing in the store. 2. The another aspect of purchasing behavior is problem solving and it was found very important in recommending the outlets to friends and relatives for purchasing. So it becomes very important for the marketer to improve upon the aspects of problem solving which will contribute in improving the business performance of the company. Hence a marketer should improve upon problem solving aspects of the retail store for getting maximum sales. 3. Another important demographic variable is education. People behave differently with different level of education. From the study it is found that education level plays an important role in switching to other outlets. Hence to retain the customers with the same outlet, it becomes important for the marketer to serve the different levels of education with different products and services in the market. By doing this it will be possible for the marketer to retain them. 4. When a customer makes a complaint to the retailer, than it was found that profession plays a great role in complaining behavior as well as in switching to another outlet. As customer retention is an important aspect in retail store, so it becomes very important to deal with different profession groups in a different manner as per their requirements. It will lower the complaints rate and it will be helpful to retain the people with the same outlet. This will increase the sale of the retail store in future. 5. Another important aspect is physical aspects; it is a very important aspect in getting the loyalty of the customer with the same outlet. Hence marketer should focus on physical aspects of the retail store to retain the customers with the same store in more and more number.\begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.85\textwidth}} : Customers Responses\end{longtable} \par \caption{\label{tab_0}Table 1}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{P{0.3597674418604651\textwidth}P{0.0869767441860465\textwidth}P{0.35186046511627905\textwidth}P{0.019767441860465116\textwidth}P{0.011860465116279069\textwidth}P{0.019767441860465116\textwidth}} 2013\tabcellsep \tabcellsep \tabcellsep \\ ear\tabcellsep \tabcellsep \tabcellsep \\ Y\tabcellsep \tabcellsep \tabcellsep \\ Volume XIII Issue IX Version I\tabcellsep \tabcellsep \tabcellsep \\ ( )\tabcellsep \tabcellsep \tabcellsep \\ Global Journal of Management and Business Research\tabcellsep 1) Respondents Profile\tabcellsep \multicolumn{3}{l}{S. No. Gender No. of Respondents Percentage (\%) 1 Male 343 63.51\% 2 Female 197 36.49\%}\\ \tabcellsep \tabcellsep 3\tabcellsep Total\tabcellsep 540\tabcellsep 100\%\end{longtable} \par {\small\itshape [Note: From the table (4.1) out of 540 respondents, 343 respondents are male and 197 female. Hence we can say that more number of males is visiting for shopping in the outlet than females. So it becomes]} \caption{\label{tab_1}Table 2}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.2689873417721519\textwidth}P{0.19474683544303797\textwidth}P{0.08715189873417721\textwidth}P{0.18075949367088606\textwidth}P{0.11835443037974683\textwidth}} 2) Education Level\tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{4}{l}{S. No. Education Level No. of Respondents Percentage (\%)}\\ \tabcellsep 1\tabcellsep None\tabcellsep Nil\tabcellsep Nil\\ \tabcellsep 2\tabcellsep Matriculation\tabcellsep 32\tabcellsep 05.93\%\\ \tabcellsep 3\tabcellsep Diploma Holders\tabcellsep 60\tabcellsep 11.11\%\\ \tabcellsep 4\tabcellsep Degree Holders\tabcellsep 206\tabcellsep 38.15\%\\ \tabcellsep 5\tabcellsep Master Degree\tabcellsep 200\tabcellsep 37.03\%\\ \tabcellsep 6\tabcellsep Ph.D\tabcellsep 14\tabcellsep 2.60\%\\ \tabcellsep 7\tabcellsep Others\tabcellsep 28\tabcellsep 5.18\%\\ \tabcellsep 8\tabcellsep Total\tabcellsep 540\tabcellsep 100\%\\ \multicolumn{3}{l}{From the table (4.2) it is found that out of total}\tabcellsep \multicolumn{2}{l}{other courses. Hence from this we can conclude that}\\ \multicolumn{3}{l}{540 respondents, 200 respondents are having a master}\tabcellsep \multicolumn{2}{l}{educated category of customers are shopping from}\\ \multicolumn{3}{l}{degree, 206 respondents are graduates, 60}\tabcellsep these outlets.\\ \multicolumn{3}{l}{respondents are diploma holders, and 28 are having}\tabcellsep \\ \multicolumn{2}{l}{3) Monthly Income Category}\tabcellsep \multicolumn{2}{l}{Table 4}\\ S. No.\tabcellsep \multicolumn{2}{l}{Monthly Income Category}\tabcellsep No. of Respondents\tabcellsep Percentage (\%)\\ 1\tabcellsep \multicolumn{2}{l}{Up-to-15,000}\tabcellsep 84\tabcellsep 15.55\%\\ 2\tabcellsep \multicolumn{2}{l}{15,001-to-30,000}\tabcellsep 162\tabcellsep 30.00\%\\ 3\tabcellsep \multicolumn{2}{l}{30,001-to-45,000}\tabcellsep 118\tabcellsep 21.85\%\\ 4\tabcellsep \multicolumn{2}{l}{45,001-to-60,000}\tabcellsep 60\tabcellsep 11.12\%\\ 5\tabcellsep \multicolumn{2}{l}{60,001-to-75,000}\tabcellsep 42\tabcellsep 07.78\%\\ 6\tabcellsep \multicolumn{2}{l}{Above 75,000}\tabcellsep 74\tabcellsep 13.70\%\\ 7\tabcellsep Total\tabcellsep \tabcellsep 540\tabcellsep 100\%\end{longtable} \par \caption{\label{tab_2}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.6044959128065395\textwidth}P{0.0752724795640327\textwidth}P{0.018528610354223433\textwidth}P{0.04632152588555858\textwidth}P{0.10538147138964578\textwidth}} \tabcellsep \tabcellsep \tabcellsep \tabcellsep 2013\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep ear\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep Y\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep Volume XIII Issue IX Version I\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep ( )\\ \multicolumn{4}{l}{4) Marital Status From the table (4.4), it is found that out of 540 S. No. Marital Status No. of Respondents Percentage (\%) 1 Married 324 60\% 2 Single 216 40\% 3 Divorced Nil Nil 4 Total 540 100\% respondents, 324 respondents are married and 216 respondents are single. Hence from this table we can analyze that more number of married customers are visiting to the organized retail stores for shopping purpose. Table 6 5) Which Profession you belong to? S. No. Type of Profession No. of Respondents Percentage (\%)}\tabcellsep Global Journal of Management and Business Research\\ 1\tabcellsep Professional/Administrative\tabcellsep 240\tabcellsep 44.45\%\\ 2\tabcellsep Academic\tabcellsep 50\tabcellsep 09.25\%\\ 3\tabcellsep Student\tabcellsep 44\tabcellsep 08.15\%\\ 4\tabcellsep Own Business\tabcellsep 100\tabcellsep 18.52\%\\ 5\tabcellsep Others\tabcellsep 106\tabcellsep 19.63\%\\ 6\tabcellsep Total\tabcellsep 540\tabcellsep 100\%\end{longtable} \par \caption{\label{tab_3}Table 5}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{P{0.38838951310861425\textwidth}P{0.08064918851435705\textwidth}P{0.07322097378277154\textwidth}P{0.24088639200998754\textwidth}P{0.06685393258426967\textwidth}} \multicolumn{2}{l}{6) Duration of dealing with the outlet}\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{2}{l}{S. No. Number of Years}\tabcellsep \multicolumn{3}{l}{No. of Respondents Percentage (\%)}\\ 1\tabcellsep \multicolumn{2}{l}{Less than one Year}\tabcellsep 160\tabcellsep 29.63\%\\ 2\tabcellsep 1-to-2 Years\tabcellsep \tabcellsep 206\tabcellsep 38.15\%\\ 3\tabcellsep 2-to-3 Years\tabcellsep \tabcellsep 118\tabcellsep 21.85\%\\ 4\tabcellsep 3-to-4 Years\tabcellsep \tabcellsep 26\tabcellsep 04.81\%\\ \tabcellsep \tabcellsep \multicolumn{2}{l}{Table 8}\tabcellsep \\ Your Age\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep Frequency\tabcellsep Percent\tabcellsep Valid Percent\tabcellsep Cumulative Percent\\ 20-to-25 years\tabcellsep 138\tabcellsep 25.6\tabcellsep 25.6\tabcellsep 25.6\\ 25-to-35 years\tabcellsep 230\tabcellsep 42.6\tabcellsep 42.6\tabcellsep 68.1\\ 35-to-45 years\tabcellsep 84\tabcellsep 15.6\tabcellsep 15.6\tabcellsep 83.7\\ Above 45 years\tabcellsep 88\tabcellsep 16.3\tabcellsep 16.3\tabcellsep 100.0\\ Total\tabcellsep 540\tabcellsep 100.0\tabcellsep 100.0\tabcellsep \\ \multicolumn{3}{l}{From the table (4.7) it is found that out of the}\tabcellsep \multicolumn{2}{l}{respondents are in the age category of above 45 years.}\\ \multicolumn{3}{l}{total 540 respondents, 230 respondents are belonging}\tabcellsep \multicolumn{2}{l}{Hence from this table we can analyze that young}\\ \multicolumn{3}{l}{to age group between (25-to-35 years), 138}\tabcellsep \multicolumn{2}{l}{customers having age up-to-35 years are more rather}\\ \multicolumn{3}{l}{respondents between (20-to-25 years), whereas 84}\tabcellsep \multicolumn{2}{l}{than customers above 35 years.}\\ \multicolumn{3}{l}{respondents between (35-to-45 years) and 88}\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_4}Table 7}\end{figure} \begin{figure}[htbp] \noindent\textbf{9} \par \begin{longtable}{P{0.85\textwidth}} Demographic Variables\end{longtable} \par \caption{\label{tab_5}Table 9 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{10} \par \begin{longtable}{P{0.31024999999999997\textwidth}P{0.029750000000000002\textwidth}P{0.03825\textwidth}P{0.017\textwidth}P{0.051\textwidth}P{0.017\textwidth}P{0.03825\textwidth}P{0.017\textwidth}P{0.11900000000000001\textwidth}P{0.1275\textwidth}P{0.00425\textwidth}P{0.017\textwidth}P{0.04675\textwidth}P{0.017\textwidth}} Dimensions\tabcellsep Age\tabcellsep \multicolumn{2}{l}{Gender}\tabcellsep \multicolumn{2}{l}{Education}\tabcellsep \multicolumn{2}{l}{Income}\tabcellsep \multicolumn{4}{l}{Marital Status Profession}\tabcellsep \multicolumn{2}{l}{Duration}\\ X 2\tabcellsep Sig.\tabcellsep X 2\tabcellsep Sig.\tabcellsep X 2\tabcellsep Sig.\tabcellsep X 2\tabcellsep Sig.\tabcellsep X 2\tabcellsep Sig.\tabcellsep X\tabcellsep Sig.\tabcellsep X 2\tabcellsep Sig.\\ \multicolumn{9}{l}{Satisfaction 8.024 .046 .973 .324 7.659 .264 7.511 .185 .695}\tabcellsep \multicolumn{5}{l}{.404 3.668 .453 2.573 .632}\end{longtable} \par \caption{\label{tab_6}Table 10 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{11} \par \begin{longtable}{P{0.301204128440367\textwidth}P{0.23881880733944955\textwidth}P{0.02826834862385321\textwidth}P{0.013646788990825689\textwidth}P{0.008772935779816514\textwidth}P{0.06920871559633027\textwidth}P{0.0058486238532110095\textwidth}P{0.04581422018348624\textwidth}P{0.031192660550458717\textwidth}P{0.06628440366972477\textwidth}P{0.04094036697247706\textwidth}} \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 2013\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep ear\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Y\\ Dimension\tabcellsep \multicolumn{2}{l}{Age}\tabcellsep Gender\tabcellsep \multicolumn{2}{l}{Education}\tabcellsep \multicolumn{2}{l}{Income}\tabcellsep Marital\tabcellsep Profession\tabcellsep Duration\\ s\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Status\\ \tabcellsep X 2\tabcellsep Sig. X 2\tabcellsep \multicolumn{2}{l}{Sig. X 2}\tabcellsep Sig. X 2\tabcellsep \tabcellsep Sig. X 2\tabcellsep Sig. X 2\tabcellsep Sig. X 2\tabcellsep Sig.\\ Overall Behavior\tabcellsep 13.462\tabcellsep \multicolumn{3}{l}{.004 1.083 .298 9.331}\tabcellsep \multicolumn{4}{l}{.156 10.393 .065 1.292 .256 8.532}\tabcellsep .074 5.721 .221\\ Recommen\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ d the outlet to\tabcellsep \multicolumn{4}{l}{7.976 .047 2.141 .143 5.772}\tabcellsep \multicolumn{2}{l}{.449 5.194}\tabcellsep \multicolumn{2}{l}{.393 .944}\tabcellsep .331 3.645\tabcellsep .456 5.896 .207\\ customers Encouragin\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep ( )\\ g friends \&\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ relatives to\tabcellsep \multicolumn{4}{l}{7.753 .051 5.636 .018 3.284}\tabcellsep \multicolumn{2}{l}{.772 3.269}\tabcellsep \multicolumn{2}{l}{.659 .154}\tabcellsep .695 2.788\tabcellsep .594 5.747 .219\\ buy from\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ this outlet\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ I would like\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ to switch\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ to another outlet that\tabcellsep \multicolumn{4}{l}{4.156 .245 1.900 .168 9.252}\tabcellsep \multicolumn{2}{l}{.160 6.925}\tabcellsep \multicolumn{2}{l}{.226 3.140 .076 8.997}\tabcellsep .061 1.746 .782\\ offers\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ more\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ benefits\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Switching\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ to another\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ outlet if I\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ experience\tabcellsep \multicolumn{8}{l}{5.956 .114 .019 .891 13.145 .041 12.534 .028 3.453 .063 11.214 .024 7.417 .115}\\ problem\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ with this\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ outlet\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ continue\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ with the\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ outlet even\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ if the outlet increases\tabcellsep \multicolumn{8}{l}{6.617 .085 .005 .941 9.310 .157 5.154 .397 .539 .467 4.544 .337 9.871 .043}\\ the prices\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ of its\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ products\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_7}Table 11 :}\end{figure} \footnote{© 2013 Global Journals Inc. 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