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\title{Export Behavior and Propensity to Innovate in Developing Country: The Case of Afghanistan}
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             \author[1]{Aimal  Mirza}

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\date{\small \em Received: 9 December 2019 Accepted: 2 January 2020 Published: 15 January 2020}

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\begin{abstract}
        


The paper is aimed at e xamining relation bet ween factors determining export behavior and propensity to innovate to fill Afghanistan specific literature gap. For this purpose, a number of 236 small and medium manufacturing firms were targeted as statistical unit of analysis. Required data were collected through questionnaire distributed to owner/manager of firms. Descriptive statistics as well as multivariate probit regression were utilized to analyze the data. Findings confirmed no significant relationship between export behavior and propensity to innovate. It further suggests that marketing innovation and technological advancement positively and significantly influence export behavior and propensity to innovate. Furthermore, and unlike result of many other similar studies there was insignificant influence of firm size and firm age on propensity to innovation.

\end{abstract}


\keywords{propensity to innovation, export behavior, firm, technological advancement, marketing innovation.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
he term propensity to innovate refers to firm's willingness and capability to adopt a new ideal (Morris, 2005, Sloan, 2008) from outside  {\ref (Cannon, 1985} {\ref , Hansen and Birkinshaw, 2007} {\ref , Sloan, 2008}) at a high level of risk  {\ref (Dobni, 2006} {\ref , Sloan, 2008)}. Whereas, the term export behavior refers to profile of firms with conjunction of their decision to export or not to export  {\ref (Cavusgil \& Tesar, 1979)} according to same author when the export objectives characteristics are combined, export profile becomes export behavior  {\ref (Cavusgil \& Tesar, 1979)}.\par
Economists mostly agree that export plays important role for any country's development and developing ones in particular. However, according ample studies in export has been less possible without innovation in this era. There are many evidences that proves this assert. Forbes latest ranking of high growth innovative companies is an example to name one of such evidences  {\ref (Forbes, 2018)}. According to this ranking majority of the innovative companies are based on a developed country. Therefore, examination of export and innovation at firm level has been an interesting research topic. However, most of studies have been conducted in context of developed countries and there only few ones on same about developing countries. For this purpose, this study attempts to improve our knowledge on relation between export behavior and propensity to in a developing country. 
\section[{a) Background to Study}]{a) Background to Study}\par
There is a debate if Afghanistan is least developed country (LDC) or developing one. According to United Nation Development Program Afghanistan holding fifth least developed country in terms human index development of rank in 2007 improved its positon to 20th in 2019. Furthermore, within same time frame there has been considerable GDP growth and infrastructure development. These positive changes indicate that Afghanistan is developing despite of instability and political unrest.\par
Earlier the study discussed that export was highly crucial for countries to sustain development, meanwhile we also argued that innovation was one of important element for export. Furthermore, we argued that Afghanistan was developing. These discussion and argument allows as to investigate relationship between both as area of research in this country on the basis of issue that there is a significant deficit in balance of trade in the country. According to figures reported by National Statistics and Information Authority (NSIA, 2020) of Afghanistan, import has been as large as USD 8.5 billion where export has been only 1.7 billion at maximum meaning that import for more outweighs export in this county.\par
To address the said issue-Afghanistan government recently has focused on promotion of some agro product such as dry and fresh fruit mainly by focusing on these products supply chain. Though there has been some achievement on value chain, analysis of supply chain considering the existing capacity at concerned organization in this county is complex to understand and seems not to bring significant changes. Parallel to this manufacturing industry deserve same attention for its development as experience of many countries indicate that manufacturing has been the prime driver of export development. On the basis of issue, argument and discussion next section proposes problem statement that lays a foundation for conduct of this study. 
\section[{b) The Problem}]{b) The Problem}\par
As discussed in previous sections it is highly important to address issue of lower export in Afghanistan. This issue lays a foundation for many researches. As the importance of innovation and export was discussed above one of research area is to examine relation between innovation and export in this  
\section[{Theoretical Background}]{Theoretical Background}\par
This section focusses the existing studies two strands. The first strand discusses determinants of export behavior. Sai, Sun and Liu (2018) unravels the effects of export and innovation on firm-level markup and productivity. The findings show that starting to export without innovation has negative affect on firm productivity and markup, while starting to innovate without export has a significant positive impact on productivity and ultimately to export. Radicic (2019) explore the extend in which the potential complementary relation exists between technological persistence innovation, feedback and export. Result suggests positive relation between three with no connection between past product and process innovation to export behavior of firms. Similarly, Azar and Ciabuschi (2017) examines relation between export performance and innovation type. Their study finds out that export enhances radicalness and extensiveness of technological innovation. On the other hand, a study of \hyperref[b5]{Crick and Crick (2016)} examines on what exist behind a firm export order and marketing innovation concentrating on risk/reward considerations in decisionmaking. Result of the study suggest that a variety of factors can affect the decision of owner/managers in small firms to start their internationalization path. Decisions are made in the context of perceived risk and reward with conjunction of different opportunities exploitation. Edeh, Obodoechi and Ramos-Hidalgo (2020) in their study explore heterogeneous effect of innovation type on SMEs export performance in developing countries finds out simultaneous technological and non-technological impact of innovation on firms' export performance. Study further finds out that product innovation is negatively related with export performance while process innovation is positively related with same. \hyperref[b12]{Lewandowska et al (2016)} in their study aim at examining to what extend innovation can influence export confirming need for application of network approach to research on between interrelationships internationalization of the firm and innovation. Similar to this, Oura, Zilber and Lopes (2016) comparing the effect of innovation capacity on export behavior and internationalization experience on export behavior suggests that internationalization has greater effect on export behavior than innovation capacity. Furthermore, Rodil, Vence and Carmen Sanchez (2016) examines the problem that what happens to innovation level of firm when export increases. Finding suggest that marketing innovation is crucial for export enhancement. Similar to this, \hyperref[b20]{Tavassoli (2018)} analyze role of product innovation on firms' export behavior. Findings suggests output of firm as result of innovation measured by sales has a positive and significant role on firm subsequent export behavior. Result of studies discussed as above point to importance of innovation toward export involving other variables such as internationalization, product quality, owner/manager perceived risk and marketing innovation.\par
The From the review of literature as document above one understand that innovation can lead to improvement of export behavior. Researches are mostly conducted in developed and European countries in particular. Researches have been generally quantitative and either data were collected through questionnaire or from databases. It further shows that most of researches  H8: Firm age significantly influence propensity to innovate. 
\section[{H9: Process innovation significantly influence propensity to innovate.}]{H9: Process innovation significantly influence propensity to innovate.}\par
H10: There is a positive relation between export behavior and propensity to innovate. 
\section[{III.}]{III.} 
\section[{Methodology}]{Methodology}\par
In order to address the defined research questions author applied quantitate method due to the large population size whereby qualitative study was practically impossible. Data were collected through data collection tool structured in light of available literature and conceptual model as shown in figure 2.1. Table  {\ref 3}.1. explains how variables were measured in questions/ statement included in data collection instrument on dichotomous scale i.e. Yes/No where 1 was assigned to "Yes" and 0 was assigned to "No" and values such as investment and expenditure. Study targeted a number of 236 manufacturing firms located in three major cities of Afghanistan (Kabul, Herat and Jalalabad) and questionnaires were distributed key person in firm (i.e. either owner/manager).  
\section[{Measure}]{Measure}? ? = [? ?? , ? , ? ?? ] ? ??? (?, ?) ?? ? ? = [? ?? , ? , ? ?? ] ? ???(? ? ?, ?)\textbf{(3)}\par
where i=1,...,N indicates observations, j=1,...,M indicates outcomes, Xi is a K-vector of exogenous covariates, the ui are assumed to be independent across i but correlated across j for any i, and "MVN" denotes the multivariate normal distribution.\par
IV. 
\section[{Results and Findings}]{Results and Findings}\par
Findings based on descriptive statistics (table \hyperref[tab_3]{4}.1) shows AFN 532,000 and AFN 474,000 on average basis and firms expenditure gain exposure to internationalization and train their labor force respectively. These amount respectively to equivalent USD 7000 and USD 6000 approximately 1 , which are considerable in view of firms size and age. Similarly, average size of firms has been AFN 6.2 million equivalent to USD 80,000 with an average age of 11. This indicates that half of manufacturing firms are medium in size according to SME definition of Afghan Ministry of commerce and industry. The age figure indicates that firms are still young. Probit regression analysis (table \hyperref[tab_3]{4}.3) result shows that majority i.e. 53\% of manufacturing firms were not involved in export. Finding further suggests that marketing innovation had higher impact (i.e. sig = 0.045 and coef =0.536) on export behavior whereas, rest of variables had insignificance influence on same.    
\section[{Discussion}]{Discussion}\par
Finding of data analysis is both surprising and interesting. It is surprising in a sense that most of important variables across literature were insignificant and interesting in a sense that innovation is less dependent to firm size and age. Therefore, leading to substantiating only hypothesis(s) 2 and 5. The findings lead to answer research questions one that marketing innovation explains export behavior. Answer to question number two asserts that technological advancement defines propensity to innovate and finally there is no relation between two. However, these findings are prone to some limitation such as higher log likelihood and insignificant R square. Due to nature of data (mixture of amounts and binary values) study applied multivariate probit regression nonetheless, descriptive statistics and predictors percentage analysis seem to be more reliable on the basis which risk-taking behavior managers/ owners, process innovation, product quality are more worthwhile for further examination and attention.\par
Apart from positive effect of marketing innovation and technological advancement on explained variables which agrees with findings of authors such as Crick and Crick (2016); Rodil, Vence and Carmen Sanchez (2016) and Hue (2019 the rest of findings (i.e. insignificant effect of other variable on explained variables) contradicts with majority of previous studies, which adds more to our surprise. 
\section[{Volume XX Issue VII Version I}]{Volume XX Issue VII Version I} 
\section[{( E )}]{( E )}\par
As policy implication this study suggest the government should not overlook quality control of product that may lead to process innovation as product improvement has been highly emphasized upon through research studies over the world. Besides, technological advancement-managerial implication of this study include attention to training and development which may positively affect product innovation through process improvement that ultimately leads to higher innovation.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\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{} \par 
\begin{longtable}{P{0.8244360902255639\textwidth}P{0.0023966165413533834\textwidth}P{0.008787593984962405\textwidth}P{0.0015977443609022555\textwidth}P{0.012781954887218044\textwidth}}
examining\tabcellsep the\tabcellsep differences\tabcellsep in\tabcellsep transformational\\
\multicolumn{5}{l}{leadership's effect on each dimension of innovation}\\
\multicolumn{5}{l}{capability, namely, product innovation and process}\\
\multicolumn{5}{l}{innovation. The findings indicate that knowledge sharing}\\
\multicolumn{5}{l}{mediates transforming leadership effects on innovation}\\
\multicolumn{5}{l}{capabilities. These findings are further similar to Hues'}\\
\multicolumn{5}{l}{(2019) study with aims at empirically analysis of}\\
\multicolumn{5}{l}{innovation decision determinants the result of study}\\
\multicolumn{5}{l}{indicates that besides firm size, a higher percentage of}\\
\multicolumn{5}{l}{skilled force representing technological factors and}\\
\multicolumn{5}{l}{which are based on technological intensive sector to be}\\
\multicolumn{5}{l}{critical factors of innovation decisions besides. Similarly,}\\
\multicolumn{5}{l}{Medase, (2020) confirm positive effect of firm size as}\\
\multicolumn{5}{l}{well as firm age on product innovation. Authors such as}\\
\multicolumn{5}{l}{Aziz and Samad (2016); Coad (2018) and Pellegrino}\\
\multicolumn{5}{l}{(2020) emphasize on positive role of firm age on}\\
\multicolumn{5}{l}{process and product innovation. From the studies}\\
\multicolumn{5}{l}{discussed above one can realize the importance of}\\
\multicolumn{5}{l}{variables such as training and development, technology,}\\
\multicolumn{5}{l}{firm size, firm age and finally product and process}\\
\multicolumn{3}{l}{quality on innovation.}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.5200976403580146\textwidth}P{0.08921887713588283\textwidth}P{0.035272579332790883\textwidth}P{0.1500813669650122\textwidth}P{0.05532953620829943\textwidth}}
\tabcellsep Scale\tabcellsep Dependent\tabcellsep Predicator\tabcellsep Constructs\\
\tabcellsep \tabcellsep Variable\tabcellsep \\
Firm Exports\tabcellsep Dichoto\tabcellsep Export\tabcellsep \tabcellsep ExpBeh\\
\tabcellsep mous\tabcellsep Behavior\tabcellsep \\
\tabcellsep \tabcellsep Propensity\tabcellsep \\
Growth in sales as result of\tabcellsep Dichoto\tabcellsep to\tabcellsep \tabcellsep PropInnov\\
product/process improvement,\tabcellsep mous\tabcellsep Innovate\tabcellsep \\
technological advancement and\tabcellsep \tabcellsep \tabcellsep \\
training \& development\tabcellsep \tabcellsep \tabcellsep \\
Firm exposure to\tabcellsep AFN\tabcellsep \tabcellsep Exposure to\tabcellsep ExpInt'l\\
Internationalization (Fair,\tabcellsep thousand\tabcellsep \tabcellsep Internationa\\
exhibition, Owner/manager\tabcellsep \tabcellsep \tabcellsep lization\\
business trips)\tabcellsep \tabcellsep \tabcellsep \\
Table continues to next page\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep owner/man\\
Is manager/owner risk averse?\tabcellsep Dichoto\tabcellsep \tabcellsep ager risk-\tabcellsep MgrRTB\\
\tabcellsep mous\tabcellsep \tabcellsep taking\\
\tabcellsep \tabcellsep \tabcellsep behavior\\
Did firm approach for marketing\tabcellsep Dichoto\tabcellsep \tabcellsep Marketing\tabcellsep MInnov\\
lead to change product or\tabcellsep mous\tabcellsep \tabcellsep Innovation\\
production process?\tabcellsep \tabcellsep \tabcellsep Product\\
Has there been changes in\tabcellsep Dichoto\tabcellsep \tabcellsep quality and\tabcellsep ProdQntQlt\\
quantity and quality of product\tabcellsep mous\tabcellsep \tabcellsep quantity\\
based on customer demand?\tabcellsep \tabcellsep \tabcellsep improvement\\
\tabcellsep \tabcellsep \tabcellsep technological\\
Firm's additional investment on technology after initial outlay. machinery and any other\tabcellsep Million AFN\tabcellsep \tabcellsep \multicolumn{2}{l}{advancement TAdv}\\
Firm's expenditure on technical and personal development training\tabcellsep AFN thousand\tabcellsep \tabcellsep Development Training and\tabcellsep TD\\
Change in production process as\tabcellsep \tabcellsep \tabcellsep \\
because of improvement in\tabcellsep Dichoto\tabcellsep \tabcellsep Process\tabcellsep ProInnov\\
product quality and quantity or\tabcellsep mous\tabcellsep \tabcellsep innovation\\
vice versa?\tabcellsep \tabcellsep \tabcellsep \\
total value of firms fixed asset\tabcellsep AFN\tabcellsep \tabcellsep Firm Size\tabcellsep FSize\\
(Machinery)\tabcellsep Million\tabcellsep \tabcellsep \\
Number of years since firm's\tabcellsep Number\tabcellsep \tabcellsep Firm Age\tabcellsep FAge\\
establishment.\tabcellsep of Years\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep (1)\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep (2)\end{longtable} \par
 
\caption{\label{tab_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.36960038058991435\textwidth}P{0.24343482397716462\textwidth}P{0.06874405328258801\textwidth}P{0.09866793529971456\textwidth}P{0.06955280685061846\textwidth}}
\tabcellsep \multicolumn{3}{l}{1: Data descriptive information}\\
Covariate\tabcellsep Exposure to Internationalization Manager/Owner Risk\tabcellsep \multicolumn{2}{l}{N Minimum Maximum Mean Std. Dev 236 0.00 994.00 531.59 286.56 236 0.00 1.00 0.54 0.50}\tabcellsep Year 2020\\
\tabcellsep Taking\tabcellsep \tabcellsep \tabcellsep 25\\
\tabcellsep \multicolumn{2}{l}{Behavior Marketing Innovation 236 Product Quantity and Quality 236 Technological Advancement 236 Training and Development 236 Process Innovation 236 Firm Size 236 2528.00 0.00 0.00 0.00 0.00 0.00 Firm Age 236 1.00}\tabcellsep 1.00 1.00 1.00 991.00 1.00 9,957.00 6281.28 2079.41 0.50 0.50 0.56 0.50 0.49 0.50 474.42 296.45 0.55 0.50 20.00 10.72 5.99\tabcellsep Volume XX Issue VII Version I ( E )\\
\multicolumn{3}{l}{Similarly, to descriptive statistic a percentage analysis of variables (table 4.2) indicates that majority of owner/mangers were risk-takers. Effect of marketing innovation on product and process development is equally likely. Majority of improvement in product quality and quantity has been based on customers' demand. And finally a large percentage of is due to product quantity and quality improvement which is further result of customer demand.}\tabcellsep \tabcellsep Global Journal of Human Social Science -\end{longtable} \par
 
\caption{\label{tab_3}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{42} \par 
\begin{longtable}{P{0.20626666666666665\textwidth}P{0.37173333333333336\textwidth}P{0.19720000000000001\textwidth}P{0.07479999999999999\textwidth}}
\tabcellsep Risk Averse\tabcellsep Risk taker\tabcellsep Total\\
Managers risk\tabcellsep 109\tabcellsep 127\tabcellsep 236\\
taking behavior\tabcellsep 46\%\tabcellsep 54\%\tabcellsep 100\%\\
Marketing\tabcellsep led to product and\tabcellsep \multicolumn{2}{l}{did not lead to Product and process}\\
Innovation\tabcellsep Process innovation\tabcellsep Innovation\tabcellsep \\
\tabcellsep 118\tabcellsep 118\tabcellsep 236\\
\tabcellsep 50\%\tabcellsep 50\%\tabcellsep 1\\
Product quality\tabcellsep \multicolumn{2}{l}{as result of customer demand}\tabcellsep \\
and quantity\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Yes\tabcellsep No\tabcellsep \\
\tabcellsep 132\tabcellsep 104\tabcellsep 236\\
\tabcellsep 56\%\tabcellsep 44\%\tabcellsep 100\%\\
process\tabcellsep \multicolumn{2}{l}{As result of improvement in product}\tabcellsep \\
innovation\tabcellsep \multicolumn{2}{l}{quantity and quality}\tabcellsep \\
\tabcellsep Yes\tabcellsep No\tabcellsep \\
\tabcellsep 130\tabcellsep 106\tabcellsep 236\\
\tabcellsep 55\%\tabcellsep 45\%\tabcellsep 100\%\end{longtable} \par
 
\caption{\label{tab_4}Table 4 . 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{43} \par 
\begin{longtable}{P{0.5948635634028893\textwidth}P{0.0682182985553772\textwidth}P{0.06958266452648475\textwidth}P{0.08186195826645265\textwidth}P{0.03547351524879615\textwidth}}
Probit Regression\tabcellsep \tabcellsep \multicolumn{2}{l}{Export Behavior}\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Total number of observation}\\
\tabcellsep Yes\tabcellsep No\tabcellsep \tabcellsep \\
\tabcellsep 112\tabcellsep 124\tabcellsep 236\tabcellsep \\
\tabcellsep 47.5\%\tabcellsep 52.5\%\tabcellsep 100.0\%\tabcellsep \\
log likelihood\tabcellsep 321.36\tabcellsep \tabcellsep \tabcellsep \\
Nagal Kerke R Square\tabcellsep 0.029\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Coef.\tabcellsep St.Er\tabcellsep Sig\tabcellsep Exp(B)\\
Exposure to Internationalization\tabcellsep -0.000\tabcellsep 0.000\tabcellsep 0.754\tabcellsep 1.000\\
Owner/Manager Risk-taking\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Behavior\tabcellsep 0.130\tabcellsep 0.267\tabcellsep 0.627\tabcellsep 1.139\\
Marketing Innovation\tabcellsep 0.536\tabcellsep 0.267\tabcellsep 0.045\tabcellsep 1.708\\
Product Quantity and Quality\tabcellsep -0.197\tabcellsep 0.267\tabcellsep 0.462\tabcellsep 0.822\\
\multicolumn{2}{l}{Similarly, probit regression of propensity to}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{innovation (table 4.4) indicates that technological}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{advancement has significant and positive influence over}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{propensity to innovate (i.e. sig=0.011 and coef=}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{0.6884). however, other variable defined has}\tabcellsep \tabcellsep \tabcellsep \\
insignificant effect on same.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table 4 . 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{44} \par 
\begin{longtable}{P{0.4399122807017544\textwidth}P{0.11333333333333333\textwidth}P{0.1774561403508772\textwidth}P{0.0730701754385965\textwidth}P{0.0462280701754386\textwidth}}
Logistic Regression\tabcellsep \multicolumn{3}{l}{Propensity to innovate}\tabcellsep \\
\tabcellsep Yes\tabcellsep No\tabcellsep \multicolumn{2}{l}{observation}\\
\tabcellsep 112\tabcellsep 124\tabcellsep 236\tabcellsep \\
\tabcellsep 47.5\%\tabcellsep 52.5 \%\tabcellsep 100.0\%\tabcellsep \\
log likelihood\tabcellsep \multicolumn{2}{l}{318.93}\tabcellsep \tabcellsep \\
Nagal Kerke R Square\tabcellsep 0.042\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Coef.\tabcellsep St.Er\tabcellsep Sig\tabcellsep Exp(B)\\
Technological Advancement\tabcellsep 0.684\tabcellsep 0.270\tabcellsep 0.011\tabcellsep 0.504\\
Training \& Development\tabcellsep 0.000\tabcellsep 0.000\tabcellsep 0.642\tabcellsep 1.000\\
Process Innovation\tabcellsep 0.330\tabcellsep 0.274\tabcellsep 0.229\tabcellsep 1.391\\
Firm Size\tabcellsep 0.000\tabcellsep 0.000\tabcellsep 0.634\tabcellsep 1.000\\
Firm Age\tabcellsep -0.003\tabcellsep 0.022\tabcellsep 0.883\tabcellsep 0.997\\
\multicolumn{2}{l}{A partial correlation analysis (table 4.5) between}\tabcellsep \multicolumn{3}{l}{In this analysis all predicators included in model}\\
\multicolumn{2}{l}{export behavior and propensity to innovate indicates}\tabcellsep \multicolumn{2}{l}{remained control variables.}\tabcellsep \\
\multicolumn{2}{l}{negative yet very insignificant relationship between two.}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}Table 4 . 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{45} \par 
\begin{longtable}{P{0.46104910714285713\textwidth}P{0.0720982142857143\textwidth}P{0.1347098214285714\textwidth}P{0.06830357142857144\textwidth}P{0.11383928571428571\textwidth}}
Control Variables\tabcellsep \tabcellsep \tabcellsep Export Behavior\tabcellsep Propensity to Innovation\\
1. Exposure to Internationalization\tabcellsep Behavior Export\tabcellsep Correlation\tabcellsep 1.000\tabcellsep -0.038\\
2. Manager/Owner Risk Taking\tabcellsep \tabcellsep Significance\tabcellsep .\tabcellsep 0.572\\
Behaviour\tabcellsep \tabcellsep (2-tailed)\tabcellsep \tabcellsep Table continues\\
3. Marketing Innovation\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
4. Product Quantity and Quality\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
5. Technological Advancement\tabcellsep \tabcellsep df\tabcellsep 0\tabcellsep 225\\
6. Training and Development\tabcellsep Propensity\tabcellsep Correlation\tabcellsep -0.038\tabcellsep 1.000\\
7. Process Innovation\tabcellsep to Innovation\tabcellsep Significance (2-\tabcellsep 0.572\tabcellsep .\\
\tabcellsep \tabcellsep tailed)\tabcellsep \tabcellsep \\
8. Firm Size\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
9. Firm Ag\tabcellsep \tabcellsep df\tabcellsep 225\tabcellsep 0\\
V.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 4 . 5 :}\end{figure}
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