\documentclass[11pt,twoside]{article}\makeatletter

\IfFileExists{xcolor.sty}%
  {\RequirePackage{xcolor}}%
  {\RequirePackage{color}}
\usepackage{colortbl}
\usepackage{wrapfig}
\usepackage{ifxetex}
\ifxetex
  \usepackage{fontspec}
  \usepackage{xunicode}
  \catcode`⃥=\active \def⃥{\textbackslash}
  \catcode`❴=\active \def❴{\{}
  \catcode`❵=\active \def❵{\}}
  \def\textJapanese{\fontspec{Noto Sans CJK JP}}
  \def\textChinese{\fontspec{Noto Sans CJK SC}}
  \def\textKorean{\fontspec{Noto Sans CJK KR}}
  \setmonofont{DejaVu Sans Mono}
  
\else
  \IfFileExists{utf8x.def}%
   {\usepackage[utf8x]{inputenc}
      \PrerenderUnicode{–}
    }%
   {\usepackage[utf8]{inputenc}}
  \usepackage[english]{babel}
  \usepackage[T1]{fontenc}
  \usepackage{float}
  \usepackage[]{ucs}
  \uc@dclc{8421}{default}{\textbackslash }
  \uc@dclc{10100}{default}{\{}
  \uc@dclc{10101}{default}{\}}
  \uc@dclc{8491}{default}{\AA{}}
  \uc@dclc{8239}{default}{\,}
  \uc@dclc{20154}{default}{ }
  \uc@dclc{10148}{default}{>}
  \def\textschwa{\rotatebox{-90}{e}}
  \def\textJapanese{}
  \def\textChinese{}
  \IfFileExists{tipa.sty}{\usepackage{tipa}}{}
\fi
\def\exampleFont{\ttfamily\small}
\DeclareTextSymbol{\textpi}{OML}{25}
\usepackage{relsize}
\RequirePackage{array}
\def\@testpach{\@chclass
 \ifnum \@lastchclass=6 \@ne \@chnum \@ne \else
  \ifnum \@lastchclass=7 5 \else
   \ifnum \@lastchclass=8 \tw@ \else
    \ifnum \@lastchclass=9 \thr@@
   \else \z@
   \ifnum \@lastchclass = 10 \else
   \edef\@nextchar{\expandafter\string\@nextchar}%
   \@chnum
   \if \@nextchar c\z@ \else
    \if \@nextchar l\@ne \else
     \if \@nextchar r\tw@ \else
   \z@ \@chclass
   \if\@nextchar |\@ne \else
    \if \@nextchar !6 \else
     \if \@nextchar @7 \else
      \if \@nextchar (8 \else
       \if \@nextchar )9 \else
  10
  \@chnum
  \if \@nextchar m\thr@@\else
   \if \@nextchar p4 \else
    \if \@nextchar b5 \else
   \z@ \@chclass \z@ \@preamerr \z@ \fi \fi \fi \fi
   \fi \fi  \fi  \fi  \fi  \fi  \fi \fi \fi \fi \fi \fi}
\gdef\arraybackslash{\let\\=\@arraycr}
\def\@textsubscript#1{{\m@th\ensuremath{_{\mbox{\fontsize\sf@size\z@#1}}}}}
\def\Panel#1#2#3#4{\multicolumn{#3}{){\columncolor{#2}}#4}{#1}}
\def\abbr{}
\def\corr{}
\def\expan{}
\def\gap{}
\def\orig{}
\def\reg{}
\def\ref{}
\def\sic{}
\def\persName{}\def\name{}
\def\placeName{}
\def\orgName{}
\def\textcal#1{{\fontspec{Lucida Calligraphy}#1}}
\def\textgothic#1{{\fontspec{Lucida Blackletter}#1}}
\def\textlarge#1{{\large #1}}
\def\textoverbar#1{\ensuremath{\overline{#1}}}
\def\textquoted#1{‘#1’}
\def\textsmall#1{{\small #1}}
\def\textsubscript#1{\@textsubscript{\selectfont#1}}
\def\textxi{\ensuremath{\xi}}
\def\titlem{\itshape}
\newenvironment{biblfree}{}{\ifvmode\par\fi }
\newenvironment{bibl}{}{}
\newenvironment{byline}{\vskip6pt\itshape\fontsize{16pt}{18pt}\selectfont}{\par }
\newenvironment{citbibl}{}{\ifvmode\par\fi }
\newenvironment{docAuthor}{\ifvmode\vskip4pt\fontsize{16pt}{18pt}\selectfont\fi\itshape}{\ifvmode\par\fi }
\newenvironment{docDate}{}{\ifvmode\par\fi }
\newenvironment{docImprint}{\vskip 6pt}{\ifvmode\par\fi }
\newenvironment{docTitle}{\vskip6pt\bfseries\fontsize{22pt}{25pt}\selectfont}{\par }
\newenvironment{msHead}{\vskip 6pt}{\par}
\newenvironment{msItem}{\vskip 6pt}{\par}
\newenvironment{rubric}{}{}
\newenvironment{titlePart}{}{\par }

\newcolumntype{L}[1]{){\raggedright\arraybackslash}p{#1}}
\newcolumntype{C}[1]{){\centering\arraybackslash}p{#1}}
\newcolumntype{R}[1]{){\raggedleft\arraybackslash}p{#1}}
\newcolumntype{P}[1]{){\arraybackslash}p{#1}}
\newcolumntype{B}[1]{){\arraybackslash}b{#1}}
\newcolumntype{M}[1]{){\arraybackslash}m{#1}}
\definecolor{label}{gray}{0.75}
\def\unusedattribute#1{\sout{\textcolor{label}{#1}}}
\DeclareRobustCommand*{\xref}{\hyper@normalise\xref@}
\def\xref@#1#2{\hyper@linkurl{#2}{#1}}
\begingroup
\catcode`\_=\active
\gdef_#1{\ensuremath{\sb{\mathrm{#1}}}}
\endgroup
\mathcode`\_=\string"8000
\catcode`\_=12\relax

\usepackage[a4paper,twoside,lmargin=1in,rmargin=1in,tmargin=1in,bmargin=1in,marginparwidth=0.75in]{geometry}
\usepackage{framed}

\definecolor{shadecolor}{gray}{0.95}
\usepackage{longtable}
\usepackage[normalem]{ulem}
\usepackage{fancyvrb}
\usepackage{fancyhdr}
\usepackage{graphicx}
\usepackage{marginnote}

\renewcommand{\@cite}[1]{#1}


\renewcommand*{\marginfont}{\itshape\footnotesize}

\def\Gin@extensions{.pdf,.png,.jpg,.mps,.tif}

  \pagestyle{fancy}

\usepackage[pdftitle={Influence of Factors on Female C onsumers' Fashion Apparel \textbackslash  Buying Behavior in Bangladesh},
 pdfauthor={}]{hyperref}
\hyperbaseurl{}

	 \paperwidth210mm
	 \paperheight297mm
              
\def\@pnumwidth{1.55em}
\def\@tocrmarg {2.55em}
\def\@dotsep{4.5}
\setcounter{tocdepth}{3}
\clubpenalty=8000
\emergencystretch 3em
\hbadness=4000
\hyphenpenalty=400
\pretolerance=750
\tolerance=2000
\vbadness=4000
\widowpenalty=10000

\renewcommand\section{\@startsection {section}{1}{\z@}%
     {-1.75ex \@plus -0.5ex \@minus -.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\Large\bfseries}}
\renewcommand\subsection{\@startsection{subsection}{2}{\z@}%
     {-1.75ex\@plus -0.5ex \@minus- .2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\Large}}
\renewcommand\subsubsection{\@startsection{subsubsection}{3}{\z@}%
     {-1.5ex\@plus -0.35ex \@minus -.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\large}}
\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@}%
     {-1ex \@plus-0.35ex \@minus -0.2ex}%
     {0.5ex \@plus .2ex}%
     {\reset@font\normalsize}}
\renewcommand\subparagraph{\@startsection{subparagraph}{5}{\parindent}%
     {1.5ex \@plus1ex \@minus .2ex}%
     {-1em}%
     {\reset@font\normalsize\bfseries}}


\def\l@section#1#2{\addpenalty{\@secpenalty} \addvspace{1.0em plus 1pt}
 \@tempdima 1.5em \begingroup
 \parindent \z@ \rightskip \@pnumwidth 
 \parfillskip -\@pnumwidth 
 \bfseries \leavevmode #1\hfil \hbox to\@pnumwidth{\hss #2}\par
 \endgroup}
\def\l@subsection{\@dottedtocline{2}{1.5em}{2.3em}}
\def\l@subsubsection{\@dottedtocline{3}{3.8em}{3.2em}}
\def\l@paragraph{\@dottedtocline{4}{7.0em}{4.1em}}
\def\l@subparagraph{\@dottedtocline{5}{10em}{5em}}
\@ifundefined{c@section}{\newcounter{section}}{}
\@ifundefined{c@chapter}{\newcounter{chapter}}{}
\newif\if@mainmatter 
\@mainmattertrue
\def\chaptername{Chapter}
\def\frontmatter{%
  \pagenumbering{roman}
  \def\thechapter{\@roman\c@chapter}
  \def\theHchapter{\roman{chapter}}
  \def\thesection{\@roman\c@section}
  \def\theHsection{\roman{section}}
  \def\@chapapp{}%
}
\def\mainmatter{%
  \cleardoublepage
  \def\thechapter{\@arabic\c@chapter}
  \setcounter{chapter}{0}
  \setcounter{section}{0}
  \pagenumbering{arabic}
  \setcounter{secnumdepth}{6}
  \def\@chapapp{\chaptername}%
  \def\theHchapter{\arabic{chapter}}
  \def\thesection{\@arabic\c@section}
  \def\theHsection{\arabic{section}}
}
\def\backmatter{%
  \cleardoublepage
  \setcounter{chapter}{0}
  \setcounter{section}{0}
  \setcounter{secnumdepth}{2}
  \def\@chapapp{\appendixname}%
  \def\thechapter{\@Alph\c@chapter}
  \def\theHchapter{\Alph{chapter}}
  \appendix
}
\newenvironment{bibitemlist}[1]{%
   \list{\@biblabel{\@arabic\c@enumiv}}%
       {\settowidth\labelwidth{\@biblabel{#1}}%
        \leftmargin\labelwidth
        \advance\leftmargin\labelsep
        \@openbib@code
        \usecounter{enumiv}%
        \let\p@enumiv\@empty
        \renewcommand\theenumiv{\@arabic\c@enumiv}%
	}%
  \sloppy
  \clubpenalty4000
  \@clubpenalty \clubpenalty
  \widowpenalty4000%
  \sfcode`\.\@m}%
  {\def\@noitemerr
    {\@latex@warning{Empty `bibitemlist' environment}}%
    \endlist}

\def\tableofcontents{\section*{\contentsname}\@starttoc{toc}}
\parskip0pt
\parindent1em
\def\Panel#1#2#3#4{\multicolumn{#3}{){\columncolor{#2}}#4}{#1}}
\newenvironment{reflist}{%
  \begin{raggedright}\begin{list}{}
  {%
   \setlength{\topsep}{0pt}%
   \setlength{\rightmargin}{0.25in}%
   \setlength{\itemsep}{0pt}%
   \setlength{\itemindent}{0pt}%
   \setlength{\parskip}{0pt}%
   \setlength{\parsep}{2pt}%
   \def\makelabel##1{\itshape ##1}}%
  }
  {\end{list}\end{raggedright}}
\newenvironment{sansreflist}{%
  \begin{raggedright}\begin{list}{}
  {%
   \setlength{\topsep}{0pt}%
   \setlength{\rightmargin}{0.25in}%
   \setlength{\itemindent}{0pt}%
   \setlength{\parskip}{0pt}%
   \setlength{\itemsep}{0pt}%
   \setlength{\parsep}{2pt}%
   \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{2014-01-15 (revised: 15 January 2014)}
\def\TheID{\makeatother }
\def\TheDate{2014-01-15}
\title{Influence of Factors on Female C onsumers' Fashion Apparel \textbackslash  Buying Behavior in Bangladesh}
\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]{Md. Mostafizur  Rahman}

             \author[2]{Md. Farijul  Islam}

             \author[3]{Md. Alamgir  Hossain}

             \affil[1]{  Hajee Mohammad Danesh Science and Technology University, Bangladesh}

\renewcommand\Authands{ and }

\date{\small \em Received: 16 December 2013 Accepted: 1 January 2014 Published: 15 January 2014}

\maketitle


\begin{abstract}
        


The trend of female branded fashion clothing is growing rapidly in retail industry across the globe. The study purpose is to examine Bangladeshi female consumers? fashion apparel buying behavior and key factors of branded clothing. The study nature is descriptive and primary data were collected from survey questionnaires using non probability judgmental sampling. Data were analyzed by descriptive statistics, ANOVA, multiple regression and factor analysis. The results observed that brand status, attitude, popularity, image, premium, self-respect, and reference groups were found to have positive effects on consumer buying behavior. The important findings help to highlight the factors influencing consumer involvement in purchasing fashion apparel. The study contribution is to make clear understanding for marketers about the preferences of consumers to attract and maintain target consumer groups and to understand the factors influencing the fashion apparel purchase to formulate diversified and innovative marketing strategies towards branded fashion industry in Bangladesh.

\end{abstract}


\keywords{brands, fashion, apparel, consumer, female.}

\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
ow a-days, Fashion apparel is a Billion-dollar industry that generates employment for millions of people all over the world. Throughout history fashion has greatly influenced the fabric of societies. Fashion is a general term for a popular style or practice, especially in clothing, footwear, accessories, makeup etc. Fashion refers to a distinctive and often habitual trend in the style with which a person dresses, as well as prevailing styles in behavior. Fashion also refers to the newest creations of textile designers. The industry is characterized by short product life cycles, erratic consumer demand, an abundance of product variety, and complex supply chains. Consumer market for fashion apparel has become more varied by in surge of designer brands, store brands, personalization, customs and advertisement in the global market place. Since the ancient age, there has been an intimate relationship between clothes and humans. Clothing reflects the culture and progress of a society and the personality of individuals.\par
That is why we see diversity in the design of clothing among different cultures and among individuals. As the design of clothes is important to consumers in terms of their taste and cultural orientation, fashion has appeared as the driving force. But fashion or design is shaped by dominant cultures as well as economic, environmental, religious and political forces of the time. In the background of fashion, each decade has seen the emergence of a new appear and before that trend settles down another appears. Bangladesh is proud to have a variety of handmade crafts like Jamdani, Rajshahi silk, Reshmi silk. Perhaps, the most famous yarn from this part of the subcontinent is Dhaka Muslin, a superfine silk yarn embellished with intricate hand embroidery. A clear understanding of preferences of consumers will help the marketer to attract and maintain their target consumer group. Clothing sector firms are competing to increase their profit share in the market and among these firms; branded clothing has shifted the conventional clothing interest of people. The increasing use of fashion clothing and the emerging market has intrigued foreign as well as local brands to provide services to its customers. It is today easy to buy highly fashionable apparel at a relatively low price, particularly regarding female garments. It is majorly seen that women view shopping as a fun, satisfying, hedonic and joyful activity. The female attitude towards shopping seems very positive and they look forward to this communal event with cheerful prospects. Clothing is an important part and parcel of women's life and plays an imperative role in building the identity of the women. The dynamic factors of branded clothing adoption are defined and their relationship is explored with consumer behavior namely: brand status, brand attitude, willingness to pay premium, self-respect, brand name, brand popularity, brand image, reference groups and cultural impact. Recently, in Bangladesh a significant amount of local Boutique houses and men's fashion houses have launching their products through targeting young college and university consumers and professionals. The study considers college and university students as a homogeneous market segment. There is limited literature available that clearly identifies the buying behavior of this particular group. Role of brand's on consumer buying behavior is a very dynamic matter and is of great significance in Bangladesh.  
\section[{Research Methodology}]{Research Methodology}\par
The research is conclusive in the form of descriptive design. Primary data were collected through face to face interview using survey questionnaire and secondary data were collected from published journals, books and websites etc. Sample size was 200 and non probability judgmental sampling was used to select sample. The measurement technique was noncomparative scaling in the form of itemized rating scaling technique through 5 point Likert scale ranging from 1 to 5 where 5= Strongly agree, 4=Agree, 3=Neutral, 2= Disagree and 1= strongly disagree. The reliability and validity were tested using Cronbach's alpha and KMO Bartlett's test of sphericity respectively. The study was confined to Rangpur division. The collected data were analyzed using descriptive statistics, one way analysis of variance (ANOVA), multiple regression, factor analysis, (principle component analysis) with the help of SPSS. includes cloth, footwear and other accessories like and Bohdanowicz, 1994). The focus of this research is on cloth segment. \hyperref[b6]{Mintel (2008)} initiates that 20-24 and 25-34 age groups are of utmost importance to the marketers as women are less anxious about quality than style in their cloth. In terms of spending on cloth, age is a stronger determinant of women's budget than their socio-economic status. Branding more or less for centuries has been a mean to differentiate goods of one producer from those of another. Brand can be seen from two perspectives one from companies point of view and other from consumer's point of view. Amber  {\ref (1992)} proposes the definition of branding as the promise of the bundles of attributes that someone buys and provides satisfaction. The study by \hyperref[b3]{Grant and Stephen (2005)} examines younger teenage girls purchasing decisions for fashion clothing and the impact of brands on their behavior. The attributes that make up a brand may be real or deceptive, rational or emotional, tangible or invisible. \hyperref[b8]{Vieira (2009)} proposes the fashion branding could be defined as a broadly based behavioral observable fact evidenced in a diversity of material and non material contexts. It shows the source of the product and help aware consumers to differentiate the product from its competitors. The core base of naming a brand is that it is unique; can be easily discriminated from other names; easy to remember and is eyecatching to customers. A victorious brand must corresponds a distinct benefit to the consumer and the more that it delivers what it promises, the greater will be the word of mouth recommendation from satisfied consumers to others. Brands put in a nutshell, a whole range of communication, learning, history, feeling about a product or company within a simple name and logo. 
\section[{a) A proposed model for female consumer fashion apparel buying behavior}]{a) A proposed model for female consumer fashion apparel buying behavior} 
\section[{b) Research question}]{b) Research question}\par
Do the factors influence on female consumer fashion apparel buying behavior? 
\section[{c) Hypotheses of the study}]{c) Hypotheses of the study}\par
H 1 = There is a relationship between brand status and female consumer fashion apparel buying behavior.\par
H 2 = There is a relationship between brand attitude and female consumer fashion apparel buying behavior. H 3 = There is a relationship between willingness to pay premium and female consumer fashion apparel buying behavior.\par
H 4 = There is a relationship between Self respect and female consumer fashion apparel buying behavior H 5 = There is a relationship between brand name and female consumer fashion apparel buying behavior. H 6 = There is a relationship between brand popularity and female consumer fashion apparel buying behavior H 7 = There is a relationship between reference group and female consumer fashion apparel buying behavior H 8 = There is a relationship between brand image and female consumer fashion apparel buying behavior. H 9 = There is a relationship between cultural impact and female consumer fashion apparel buying behavior. 
\section[{d) Equation of the proposed model}]{d) Equation of the proposed model}\par
Y=? 0 + ? 1 x 1 + ? 2 x 2 + ? 3 x 3 + ? 4 x 4 + ? 5 x 5 + ? 6 x 6 + ? 7 x 7 + ? 8 x 8+ ? 9 x 9+ ? Where, ? 0, ? 1?, ? 9 -intercept, x 1?, x 9 -variables and ?coefficient of error term. 
\section[{III.}]{III.} 
\section[{Objectives of the Study}]{Objectives of the Study}\par
The objective of the study is to identify the important factors of purchasing branded fashion apparel for female in Bangladesh and to find the impact of these factors on consumer buying behavior. More specifically, the study aimed to achieve the following specific research objectives: i) To analyze the key influences on female consumers buying behavior in Bangladesh.\par
ii) To appraise the impact of brand status, brand attitude, willingness to pay premium, self-respect, brand name, brand popularity, reference groups, brand image, cultural impact on consumer involvement in purchasing fashion apparel. 
\section[{IV.}]{IV.} 
\section[{Results of the Study}]{Results of the Study}\par
The table \hyperref[tab_2]{2} shows that the KMO measure of sampling adequacy and Bartlett's Test of Sphericity. \hyperref[b4]{Kaiser (1974)} advocated accepting values greater than 0.5. Furthermore values between 0.7 and 0.8 are good. So our KMO measure of sampling adequacy test is 0.861 or 86 \% is reliable and acceptable for further computation. For these data Bartlett's test is highly significant (p<0.05), and therefore factor analysis is appropriate for this study. The Cronbach's alpha reliability test has been used to identify the validity of items used in the survey. According to \hyperref[b2]{Hendrickson et al (1993)} and \hyperref[b5]{McGraw and Wong (1996)} the alpha of a scale should be greater than .700 for items to be used together as a scale. The value is .824 and can be regarded as quite large. This indicates that the 10 item scale is quite reliable. 
\section[{a) Multiple Regression Analysis}]{a) Multiple Regression Analysis}\par
The purpose of multiple regression analysis is to investigate the relationship between the independent variables and the dependent variable. The model summery provides the R, R 2 , adjusted R 2 , and the standard error of the estimate, which can be used to determine how well a regression model, fits the data. The value of R represents the multiple correlation coefficients. It is seen from the table that the value of R equals 0.761 indicates a good level of prediction. The R 2 value represents the coefficient of determination which is the proportion of variance in the dependent variable that can be explained by the independent variables and the value of R square is equivalent to 0.580 which means that 58\% of the variance in the dependent variable of buying behavior can be accounted for by a variation in the independent variables. The F-ratio in the ANOVA table tests whether the overall regression model is a good fit for the data. The table shows that the independent variables statistically significantly predict the dependent variable, F (8,191) = 32.348, p < .0005 (i.e., the regression model is a good fit of the data). The coefficient is significant at ?=0.05.here brand status, willing to pay premium, self-respect are not significant to female consumer fashion apparel buying behavior. Brand attitude, Brand name, brand popularity, reference group and brand image are significant to female consumer fashion apparel buying behavior. Unstandardized coefficients indicate how much the dependent variable varies with an independent variable, when all other independent variables are held constant. 
\section[{b) Communalities}]{b) Communalities}\par
This is the proportion of each variable's variance that can be explained by the factors. With principal factor axis factoring, the initial values on the diagonal of the correlation matrix are determined by the squared multiple correlation of the variable with the other variables. The values in extraction indicate the proportion of each variable's variance that can be explained by the retained factors. The communalities range from 0 to 1. Zero means that the common factors do not explain any variance and one means that the common factors explain all the variance .The communalities of the column leveled extraction reflect the common variance in the data structure. We say that 41.2 percent of the variance associated with question 6 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XIV Issue VIII Version I Year ( ) is common or shared variance. We see from the result that relatively high numbers that is a good result.  The component matrix indicates how each item of the analysis correlates with each of the three retained factors. Negative and positive correlations carry the same weight. At this stage SPSS has extracted 2 factors. All loadings less than .40 are suppressed in the output that's why there are blank spaces for many of the loadings. This table 5 contains the unrotated factor loadings, which are the correlations between the variable and the factor. Because these are correlations, possible values range from -1 to +1. 
\section[{d) Total Variance Explained}]{d) Total Variance Explained}\par
The initial number of factors is the same as the number of variables used in the factor analysis. However, not all factors will be retained. Initial Eigenvalues are the variances of the factors. Because we conducted our factor analysis on the correlation matrix, the variables are standardized, which means that the each variable has a variance of 1, and the total variance is equal to the number of variables used in the analysis, in this case 10. Total column contains the eigenvalues. The first factor will always account for the most variance (and hence have the highest eigenvalue), and the next factor will account for as much of the left over variance as it can, and so on. Hence, each successive factor will account for less and less variance. \% of variance contains the percent of total variance accounted for by each factor. Cumulative \% contains the cumulative percentage of variance accounted for by the current and all preceding factors. Rotation sums of squared loadings values in this panel of the table represent the distribution of the variance after the Varimax rotation. Varimax rotation tries to maximize the variance of each of the factors, so the total amount of variance accounted for is redistributed over 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XIV Issue VIII Version I Year ( )\par
the three extracted factors. The correlation matrix of all 9 variables has been further subjected to principal component analysis. Any factor that has an Eigenvalue less than one does not have enough total variance explained to represent a unique factor and is therefore disregarded. The Eigenvalues associated with each factor represent the variance explained by that particular linear component and SPSS displays the Eigenvalues in terms of the percentage of variance explained. These factors have accumulated for 43 \%, 13\% and 9\% of variation. This implies that the total variance accumulated for by all three factors is 63.66\% and remaining variance is explained by other factors. So factor 1 explains 43\% of total variance. It is clear that first few factors explain relatively large amounts of variance where as subsequent factors explain a small amount of variance. 
\section[{e) Rotated Factor Matrix}]{e) Rotated Factor Matrix}\par
This table contains the rotated factor loadings (factor pattern matrix), which represent both how the variables are weighted for each factor but also the correlation between the variables and the factor. Because these are correlations, possible values range from -1 to +1. The rotation of the factor structure clarified things considerably. There are three factors and variables load very highly onto only one factor. The rotated component matrix indicates how each item correlates with each factor. 
\section[{f) Scree plot}]{f) Scree plot}\par
A Scree plot is a graph that plots the total variance associated with each factor. It is a visual display of how many factors there are in the data. The Scree plot graphs the Eigenvalue against the factor number. We can see that although there are 9 principle components only three factors have Eigenvalues over one. So we can expect three principle components in the data. The curve indicates the inflexion on the curve.  
\section[{Managerial Implications}]{Managerial Implications}\par
The fashion related apparel businesses in Bangladesh are growing at an exponential rate and are increasingly fascinating the attention of the entire world through ensuring the standard and quality product. Consumer market for fashion apparel has become more varied by in surge of designer brands, store brands, personalization, customs and advertisement in the global market place of today. From the above analysis it is clear that females have particular perspectives and motives behind their purchases. A clear understanding of preferences of consumers will help the marketer to attract and maintain their target consumer group. It can be concluded that this study can be useful to marketers trying to promote products to consumers, because it adds to the knowledge base. The research findings contribute to the literature of consumer involvement in fashion apparel and dimensions of consumer buying behavior. Along with the discussion on the extant literature, hypotheses were developed to ascertain the consequential effect of brand status, brand attitude willingness to pay premium, self-respect, brand name, brand popularity, reference groups and brand image on consumer involvement in fashion apparel. We see that the majority of the values are greater than 0.05. So the relationships are correlated among variables. The result of the study highlights the pattern of relationship among variables that were proved by the analysis. The study finds that the female consumers who possess strong positive attitudes towards brands show high level of involvement in fashion apparel, along with that selfrespect is also the most important element as consumers use brand related product that matches with their own personality. Consequently, consumers who perceive higher self-respect will generally hold a high level of involvement in fashion or branded apparel. As a retailer of apparel, all these insights have to be embedded in the policy formulation to make the purchases a real time customer delight. However on the whole this study examined various brand related variables including brand status, brand attitude, willingness to pay premium, self-concept and reference groups using fashion apparel brands as the focal object showing their effect on consumer involvement in fashion apparel. It is proposed that for developing brand and related decision for the decision maker(s) and marketer(s) to know about fashion marketing concept and how fashion marketing works by using current trends in fashion to analyze, develop, and implement sales strategies. Fashion marketing investigates the relationship between fashion design and marketing including the development, promotion, advertising and retailing aspects. Successful fashion marketers understand that recognizing consumer trends, strong branding, and a desirable product image are all essential elements to build an effective and meaningful\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.09837962962962962\textwidth}P{0.1849537037037037\textwidth}P{0.09837962962962962\textwidth}P{0.09444444444444444\textwidth}P{0.2833333333333333\textwidth}P{0.09050925925925926\textwidth}}
Variable\tabcellsep Category\tabcellsep Frequency\tabcellsep Variable\tabcellsep Category\tabcellsep Frequency\\
Age\tabcellsep 21-30 31-40\tabcellsep 188 10\tabcellsep Occupation\tabcellsep Service Others\tabcellsep 15 6\\
\tabcellsep 41-50\tabcellsep 2\tabcellsep \tabcellsep Less than 10000\tabcellsep 139\\
Sex Occupation\tabcellsep Female Student Business\tabcellsep 200 172 7\tabcellsep Income\tabcellsep 10000-30000 31000-50000 51000-above\tabcellsep 44 16 1\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.32959183673469383\textwidth}P{0.20382653061224487\textwidth}P{0.07372448979591836\textwidth}P{0.18214285714285713\textwidth}P{0.06071428571428571\textwidth}}
\tabcellsep KMO and Bartlett's Test\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Kaiser-Meyer-Olkin Measure of Sampling Adequacy}\tabcellsep .861\tabcellsep \multicolumn{2}{l}{Reliability Statistics}\\
Bartlett's Test of Sphericity\tabcellsep Approx. Chi-Square\tabcellsep 515.697\tabcellsep Cronbach's Alpha\tabcellsep No. of Items\\
\tabcellsep Df\tabcellsep 36\tabcellsep .824\tabcellsep 10\\
\tabcellsep Sig.\tabcellsep .000\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.10786802030456852\textwidth}P{0.034517766497461924\textwidth}P{0.09060913705583756\textwidth}P{0.1380710659898477\textwidth}P{0.1596446700507614\textwidth}P{0.13375634517766496\textwidth}P{0.025888324873096447\textwidth}P{0.08629441624365482\textwidth}P{0.05609137055837564\textwidth}P{0.017258883248730962\textwidth}}
\multicolumn{2}{l}{Model Summary}\tabcellsep \tabcellsep \tabcellsep ANOVA b\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\tabcellsep \tabcellsep Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
\multicolumn{2}{l}{.761 a .580}\tabcellsep .562\tabcellsep .54185\tabcellsep \multicolumn{2}{l}{Regression 77.390}\tabcellsep 8\tabcellsep 9.674\tabcellsep \multicolumn{2}{l}{32.948 .000a}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Residual\tabcellsep 56.078\tabcellsep 191\tabcellsep .294\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Total\tabcellsep \multicolumn{2}{l}{133.469 199}\tabcellsep \tabcellsep \end{longtable} \par
  {\small\itshape [Note: a. Predictors: (Constant), Brand image, Willing to pay premium, Brand popularity, Reference group, Brand attitude, Brand status, Brand name, Self-respect and Dependent variable: female consumer fashion apparel buying behavior.]} 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.12582236842105263\textwidth}P{0.2921875\textwidth}P{0.15797697368421054\textwidth}P{0.02796052631578947\textwidth}P{0.09925986842105262\textwidth}P{0.07828947368421052\textwidth}P{0.06850328947368421\textwidth}}
Year\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
42\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Volume XIV Issue VIII Version I\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
( )\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Global Journal of Management and Business Research\tabcellsep Constant Brand status Brand attitude Willing to pay premium Self-respect\tabcellsep \multicolumn{2}{l}{Unstandardized Coefficients B Std. Error -1.041 .315 -.030 .067 .187 .065 .049 .049 .127 .071}\tabcellsep Standardized Coefficients Beta -.025 .164 .053 .107\tabcellsep t -3.305 -.440 2.856 .991 1.784\tabcellsep Sig. .001 .660 .005 .323 .076\\
\tabcellsep Brand name\tabcellsep .123\tabcellsep .058\tabcellsep .119\tabcellsep 2.113\tabcellsep .036\\
\tabcellsep Brand popularity\tabcellsep .183\tabcellsep .057\tabcellsep .169\tabcellsep 3.206\tabcellsep .002\\
\tabcellsep Reference group\tabcellsep .305\tabcellsep .058\tabcellsep .280\tabcellsep 5.260\tabcellsep .000\\
\tabcellsep Brand image\tabcellsep .292\tabcellsep .061\tabcellsep .269\tabcellsep 4.764\tabcellsep .000\\
\tabcellsep Cultural impact\tabcellsep .306\tabcellsep .570\tabcellsep .270\tabcellsep 5.160\tabcellsep .000\\
\tabcellsep \multicolumn{4}{l}{a. Dependent Variable: Female consumer fashion apparel buying behavior}\tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.34\textwidth}P{0.11393617021276595\textwidth}P{0.0651063829787234\textwidth}P{0.08319148936170213\textwidth}P{0.07595744680851065\textwidth}P{0.10489361702127659\textwidth}P{0.06691489361702127\textwidth}}
\multicolumn{2}{l}{Communalities}\tabcellsep \tabcellsep \multicolumn{2}{l}{Component}\tabcellsep \multicolumn{2}{l}{Rotated Comp. Matrix}\\
\tabcellsep \multicolumn{2}{l}{Initial Extraction}\tabcellsep 1\tabcellsep 2\tabcellsep 1\tabcellsep 2\\
Brand status\tabcellsep 1.000\tabcellsep .540\tabcellsep .610\tabcellsep .410\tabcellsep .226\tabcellsep .699\\
Brand attitude\tabcellsep 1.000\tabcellsep .517\tabcellsep .669\tabcellsep .263\tabcellsep .363\tabcellsep .621\\
Willing to pay premium\tabcellsep 1.000\tabcellsep .662\tabcellsep .494\tabcellsep .647\tabcellsep -.011\tabcellsep .814\\
Self-respect\tabcellsep 1.000\tabcellsep .575\tabcellsep .715\tabcellsep .253\tabcellsep .405\tabcellsep .641\\
Brand name\tabcellsep 1.000\tabcellsep .493\tabcellsep .646\tabcellsep -.274\tabcellsep .677\tabcellsep .184\\
Brand popularity\tabcellsep 1.000\tabcellsep .412\tabcellsep .581\tabcellsep -.272\tabcellsep .625\tabcellsep .145\\
Reference group\tabcellsep 1.000\tabcellsep .441\tabcellsep .626\tabcellsep -.223\tabcellsep .630\tabcellsep .211\\
Brand image\tabcellsep 1.000\tabcellsep .589\tabcellsep .664\tabcellsep -.386\tabcellsep .760\tabcellsep .107\\
Cultural impact\tabcellsep 1.000\tabcellsep .724\tabcellsep .816\tabcellsep -.240\tabcellsep .790\tabcellsep .316\\
\multicolumn{3}{l}{Extraction Method: Principal Component Analysis.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.07196796338672769\textwidth}P{0.08363844393592677\textwidth}P{0.18478260869565216\textwidth}P{0.10697940503432495\textwidth}P{0.15560640732265446\textwidth}P{0.02334096109839817\textwidth}P{0.02334096109839817\textwidth}P{0.15366132723112128\textwidth}P{0.02334096109839817\textwidth}P{0.02334096109839817\textwidth}}
Component\tabcellsep Total\tabcellsep \multicolumn{2}{l}{Initial Eigenvalues \% of Variance Cumulative \%}\tabcellsep \multicolumn{3}{l}{Extraction Sums of Squared Loadings Total \% of Variance Cumulative \%}\tabcellsep \multicolumn{3}{l}{Rotation Sums of Squared Loadings \% of Cumulativ Total Variance e \%}\\
1\tabcellsep 3.829\tabcellsep 42.547\tabcellsep 42.547\tabcellsep 3.829\tabcellsep 42.547\tabcellsep 42.547\tabcellsep 2.796\tabcellsep 31.067\tabcellsep 31.067\\
2\tabcellsep 1.125\tabcellsep 12.500\tabcellsep 55.047\tabcellsep 1.125\tabcellsep 12.500\tabcellsep 55.047\tabcellsep 2.158\tabcellsep 23.980\tabcellsep 55.047\\
3\tabcellsep .775\tabcellsep 8.614\tabcellsep 63.661\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
4\tabcellsep .743\tabcellsep 8.256\tabcellsep 71.917\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
5\tabcellsep .665\tabcellsep 7.386\tabcellsep 79.303\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
6\tabcellsep .555\tabcellsep 6.169\tabcellsep 85.472\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
7\tabcellsep .524\tabcellsep 5.823\tabcellsep 91.295\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
8\tabcellsep .463\tabcellsep 5.147\tabcellsep 96.442\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
9\tabcellsep .320\tabcellsep 3.558\tabcellsep 100.000\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{c) Component matrix}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}Table 6 :}\end{figure}
 			\footnote{© 2014 Global Journals Inc. (US) 1} 			\footnote{© 2014 Global Journals Inc. (US)} 		 		\backmatter  			 \par
campaign about fashion apparel in the global intense competitive market to uphold the image of Bangladesh as a hub of fashionable apparel industry.			 			  				\begin{bibitemlist}{1}
\bibitem[Park et al.]{b7}\label{b7} 	 		‘A structural model of fashion-oriented impulse buying behavior’.  		 			E J Park 		,  		 			E Y Kim 		,  		 			J C Forney 		.  	 	 		\textit{Journal of Fashion Marketing and Management}  		10  (4)  p. .  	 
\bibitem[Vieira ()]{b8}\label{b8} 	 		‘An extended theoretical model of fashion cloth involvement’.  		 			A A Vieira 		.  	 	 		\textit{Journal of Fashion Marketing and Management}  		2009. 13  (2)  p. .  	 
\bibitem[Kaiser ()]{b4}\label{b4} 	 		‘An index of factorial simplicity’.  		 			H F Kaiser 		.  	 	 		\textit{Psychometrika}  		1974. 39 p. .  	 
\bibitem[Grant and Stephen ()]{b3}\label{b3} 	 		‘Communicating culture: an examination of the buying behavior of 'tween age' girls and the key societal communicating factors influencing the buying process of fashion clothing’.  		 			Isabel J Grant 		,  		 			Graeme R Stephen 		.  	 	 		\textit{Journal of targeting, measurement and analysis for marketing},  				2005. 14 p. .  	 
\bibitem[Fashion Marketing: Rout ledge Clamp. Liz. And Bohdanowicz. J ()]{b1}\label{b1} 	 		‘Fashion Marketing: Rout ledge’.  	 	 		\textit{Clamp. Liz. And Bohdanowicz. J}  		1994.  	 
\bibitem[Mcgraw and Wong ()]{b5}\label{b5} 	 		‘Forming Inferences about Some Intra class Correlation Coefficients’.  		 			K O Mcgraw 		,  		 			S P Wong 		.  	 	 		\textit{Psychological Methods}  		1996. 1 p. .  	 
\bibitem[Ambler ()]{b0}\label{b0} 	 		\textit{Need-to-Know-Marketing". Century Business. London Apparel export statistics of Bangladesh. Fiscal year 2010-2011, Bangladesh Knitwear Manufacturers Exporters Association},  		 			T Ambler 		.  		1992.  	 	 (Published by IART) 
\bibitem[Hendrickson et al. (1993)]{b2}\label{b2} 	 		‘On the Test-Retest Reliability of Perceived Usefulness and Perceived Ease of Use Scales’.  		 			A R Hendrickson 		,  		 			P D Massey 		,  		 			T P Cronan 		.  	 	 		\textit{MIS Quarterly}  		1993. June. p. .  	 
\bibitem[Mintel (2008)]{b6}\label{b6} 	 		\textit{Women swear, United Kingdoms},  		 			Mintel 		.  		2008. March 2008.  	 
\end{bibitemlist}
 			 		 	 
\end{document}
