Klibel5 econ 5_

Proceeding - Kuala Lumpur International Business, Economics and Law Conference Vol. 3.
November 29 - 30, 2014. Hotel Putra, Kuala Lumpur, Malaysia. ISBN 978-967-11350-4-4
36
THE IMPACT OF NETWORKING ON THE SMES’ ABILITY TO ACCESS FINANCIAL GOVERNMENT SUPPORT IN MALAYSIA
Mustafa Gunto
PhD candidate, Faculty of Economics and Muamalat USIM
Email: mustafa_junto@yahoo.com
Prof. Dato’ Dr. Mohammad Haji Alias
Professor, Faculty of Economics and Muamalat USIM
Email: mohdhjalias@usim.edu.my
ABSTRACT
The need to strengthen SMEs development in Malaysia is crucial, because SMEs are expected to be an essential element of economic growth, employment creation and transformation towards developed country by year 2020. Consequently, the government has given priority to SMEs and has put in place policies and institutional framework that address their developmental needs. This study investigates the impact of SMEs networking with officers in SME Corp. Malaysia on access to financial government support provided through SME Corp. Malaysia. The study aims also to examine the influence of financial government support on the ability of SMEs to access to different financial resources in Malaysia.
The study conducted on manufacturing small and medium enterprises registered under SME Corp. Malaysia. The e- mail survey was used by researchers to collect data from respondents. 500 enterprises were selected, and 182 replied. To analyse the data, the Structural Equations Modelling (SEM) technique was applied by using SmartPLS software.
The results of study showed there is a significant and positive effect of networking with officers in SME Corp. Malaysia on the ability of SMEs to gain financial government support. Furthermore, the results confirmed the existence of a significant and positive influence of the ability of SMEs to gain financial government support on the capability of SMEs to access to different financial resources provided by financial institutions in Malaysia.
Key words: networking, financial government support, access to finance, SMEs.
1. INTRODUCTION
Small and medium enterprises have attracted the attention of a lot of scholars and researches over last few decades in developed and developing countries. That was because the SMEs were considered as an engine of economic growth. SMEs have an important role to play in a country's economy (Baba Md Deros et al., 2006), through their abilities of innovations, which leads to an enhancement in a country's competitive position. They provide significant resources of generating of jobs (Storey 1994). What is more; they are more constant in times of economic instability due to their ability to work in niche markets (Barkham et al. 1996). SMEs represent a large proportion of businesses contributing to the mobilization of resources, employment and poverty alleviation. Consequently these firms are seen as dominant forces for economic development and industrialization.
The Malaysian government has given priority to SMEs and has put in place a policy and institutional framework that addresses their developmental needs (UNDP, 2007). To ensure implementation of the policy, the government set up in 2004 a National SME Development Council chaired by the Prime Minister. Also, in the Third Industrial Master Plan (2006-2020), which is currently under development, is scheduled to commit to a variety of technical and financial assistance policies targeting improved market accessibility for SMEs, the promotion of activities involving technical innovation and information technologies, and the promotion of linkages with key industries. In addition, the SME Development Council has acknowledged the importance of policy-based lending support in facilitating access to capital markets. Moreover, given the fact that the framework of the “Fund for Small and Medium-Scale Industries” is still in place, this project, which aims to develop SMEs via the provision of financial assistance, continues to have relevance. The Government’s programs and initiatives for SME development will be focused on achieving some targets, especially in the areas of developing human capabilities and the necessary enabling infrastructure that will allow for the establishment of high performance and high value-added SMEs.
The paper is structured as follows. Following the introduction is review of the relevant literature. The third section is on the methodology adopted in this study. The fourth section discusses the findings of the study followed by the concluding section.

37
2. LITERATURE REVIEW
Access to Finance
Accessibility to finance is defined as receiving sufficient and affordable financing over an appropriate schedule (Tagoe et al., 2005). Lacking of accessibility to bank's finance could mean inadequacy of financial resources to the small businesses. Reviewing the growing body of empirical analyses, Levine (2004) found a strong positive link between the functioning of the financial system and long-run economic growth. Many previous studies on critical success factors for small businesses have indicated that access to finance was among the necessary factor for success and development of small businesses (Yusuf, 1995). This is basically true as difficulties in obtaining finance often lead to illiquidity and cash flow difficulties particularly for the duration of initial years of operation. Without sufficient capital, they are unable to develop new products, conduct research and development (R & D), invest in information and communication technology (ICT), get more working capital for growth and meet the growing demand of the market. Such problems would also cause businesses not being able to pursue market opportunities, thereby obstructing their progress and growth as well as making them defenceless to failure (Moha and Siti Khadijah, 2010). Ayyagari et al. (2008) debated that the weak legal and financial systems have led to private enterprises to depend mainly on unconventional financing networks, such as loans from informal sources for short-term financing. They showed that enterprises who had access to the formal financial system developed more rapidly than enterprises with inadequate finance, additional evidence to advocate that improved legal and financial systems benefit the macroeconomic improvement of an economy.
Government Support in Finance
Policy makers should think through what can be prepared to incentivise SMEs to be more transparent in their financial dealings and adopt more formal accounting systems. This should assist them in getting better access to external sources of finance and could be done in a number of ways. Initially, the accounting regulations could be further strengthened in order to ensure more accurate financial reporting by SMEs. Local governments should also consider providing training programmes to help enterprises develop more formal management and accounting systems (Fagan and Zhao, 2009). Harvie et al. (2010) illustrated that majority of SMEs in both quality groups in production networks reported having received assistance. “Financing”, “Overall improvement in investment climate” and “Technology development and transfer” are reported to be effective for those that are in lower quality production networks. Whilst in Vietnam, policies support including financial aids play a critical role to SMEs’ growth (Harvie, 2001).
According to a questionnaire survey of 161 small manufacturing and commercial enterprises which has been done by Tan and Tay (1994) showed that the factors associated significantly and positively to firm success are financial support by the government; the entrepreneur's prior experience; a quality product ; good customer service; and being larger among small-scale firms. The study of 220 small firms in the island nations of the South Pacific showed that good personal qualities of the entrepreneur and satisfactory government support were perceived by the responding owner-managers as the most important critical success factors in their businesses (Yusuf, 1995).
Networking with Officers
Different types of networking ties between firms or individuals have been categorized in a variety of ways. Network ties are divided into formal ties, informal ties, and intermediary ties. Informal ties are related to social relationships, for instance with friends and family members (Coviello, 2006). Wu and Leung, (2005) said that networks ties refer to a firm’s aggregated relationships with its business partners, government offices, and financial institutions. Kusumawardhani et al. (2009) illustrated that networks can be distinguished into two broad categories, namely (1) personal networks or informal networks, and (2) business networks or organisational networks. The former refers to informal relationships that involve relatives, friends, and acquaintances. The latter is concerned with relationships between actors that control business activities, such as customers, distributors, suppliers, competitors, and government.
Networking means having connection between entrepreneurs and government officers in charge of business assistance besides establishing networks with financial institutions and other business associations (Kader et al., 2009). Zhou (2008) argued that the government related ties divided as those network ties between host country firms and the local government, as well as firms owned by state.
Also Deakins et al. (2003) have argued about the capability to access to network could affect access to finance through the ability to call on recommendations. Networking linkages with governments, agencies and other firms assist the process (Welch et al., 1998). By another perspective, Zizah et al. (2010) illustrated that the networking or relationship was perceived as the most important influence on the internationalization process. Zizah (2010) found

38
that the links with the government agencies and other institutions motivate SMEs to internationalise because they can access relevant and update information where having appropriate knowledge gives the Malaysian SMEs easier and faster ways to promote their products abroad. Further to that, in the absence of formal market supporting institutions, managerial ties-ties with managers at other firms and ties with government officials-have long argued to be an area commanding managers' attention in emerging economies. Scholars argue that the more market-supporting institutions are developed, the less need managers may feel about devoting time and resources to cultivate managerial ties (Ismail et al., 2012).
Nurbani et al. (2010) suggested that government officials provide training for these micro entrepreneurs for them to understand the procedures involved in the loan or grant application. In terms of the accounting procedures, many of these micro enterprise entrepreneurs especially those who are from the rural areas do not have proper accounting know how. The officials from the government agencies need to conduct periodical monitoring so that these entrepreneurs will not be left stranded.
Finally two hypotheses are developed for this study:
H1: Networking with officers of SME Corp. Malaysia will influence the ability of firm to access to financial government support.
H2: Access to financial government support impact the access of firm to finance.
Framework of Study
3. Methodology
This study used the quantitative approach to analyse the data to gain the results that explain the relationship between the variables. The study relied on primary data collected though survey and analysed quantitatively. Sample respondents in this study are firms who are registered with Small and Medium Enterprise Corporation Malaysia (SME Corp. Malaysia).
According to Cooper and Schindler (2003), a mail survey takes place when the researcher selects a sample of names and addresses and sends questionnaires to these respondents with the aim of collecting data. A mail survey is regarded as the cheapest data collection method, applies the least pressure on respondents, is easy to administer and increases the likelihood that respondents provide honest responses to questions.
The questionnaires were e-mailed to the respondents over a period from 1st Feb 2013 till the end of Aug 2013. Likert scales were used to minimize executive response time and effort (Knight and Cavusgil, 2004). A five-point scale has been adopted because some researches indicate that a five-point scale is as good as any, and that an increase from five to seven or nine points on rating scale does not improve the reliability of the ratings (Jon and Stanley, 2010). Networking indicators measured the cooperation and connections with officers in SME Corp. Malaysia. Financial government support indicators measured the satisfactory, adequacy and efficiency of assistances. Finance indicators measured the source of initial capital (own saving, family and friends, loan, government assistances and other resources), source of working capital (own saving, family and friends, loan, government assistances and other resources), availability of information about finance and difficulty of obtaining finance.
Using e-mail survey as a methodology instrument is not only cost effective but it is also appropriate for a relatively large sample.
The hypothesized relationships depicted in the research model were empirically tested using structural equation modelling (SEM). Unlike the traditional statistical methods that can examine only a single relationship at a time, the structural equation modelling (SEM) method greatly expands the researchers' capability to study a set of interrelated relationships simultaneously. Structural Equation Models (SEM) provides a combination of confirmatory factorial analysis and regression models (Cordeiro, et al., 2010). The process of SEM analysis involves up to three model estimations. First, the researcher’s conceptual model is created. Second, the conceptual model is then converted into a
Financial Government support
Networking with officers
Access to finance

39
path diagram which specifies the relationships between variables. Third, the path model is converted into a structural model for testing of the model’s fit to the data. If all variables under study in the theoretical model are observed, the path diagram is simply translated into a series of structural equations for modelling. Each dependent variable, referred to as endogenous constructs, is depicted by an arrow pointing toward the dependent variable in the model. Independent variables (exogenous variables) are depicted by an arrow pointing away from the variable and toward the dependent variable in the model.
4. Results
Assessment Measurement Model
The hypotheses were tested using a partial least squares (PLS) structural equation model. PLS provides a latent variable structure similar to LISREL structural models, but it is based on components instead of the covariance matrix, which makes it more flexible for small sample sizes. Partial Least Squares (PLS) model analyses and interprets in two stages. In the first stage measurement model evaluates and in the second stage structural model evaluates. The measurement model evaluates the relations between observed items and latent variables. The measurement model examines through assessment of validity and reliability of the construct measures in the model. This ensured that only reliable and valid constructs’ measures were used for assessing the nature of relationships in the overall model (Hulland, 1999).
Reliability Test for Reflective Measurements
The method to assess reliability is employing a Cronbach’s alpha (Table1). The construct can be identified as good reliability if its value is more than 0.70. In Table (1), shown that the constructs: Financial Government Support (0.972) and Networking (0.843) contains a good reliability because its Cronbach’s alpha is more than 0.70, indicating that the constructs are internally consistent and hence reliable. In addition to Cronbach’s (1951) alpha, Composite Reliability of Financial Government Support (0.982) and Networking (0.927) was assessed through Fornell and Larcker (1981) criteria. This measure is preferred over Cronbach’s alpha because it offers a better estimate of variance shared by the respective indicators (Hair et al., 2006). In this study the composite factor reliability coefficients of the constructs exceeded 0.80 (see Table 1), which met the standard of ≥ 0.80 as suggested by Fornell and Larcker (1981).
Table 1: Factor Loading,Cronbach's alpha,Composite reliability and AVE
Factor Loading
Cranach’s Alpha
Composite Reliability
Financial Government Support
0.972
0.982
GSF1= (satisfactory about assistance)
0.984
GSF2=(adequacy of assistance)
0.979
GSF3=(efficiency of assistance)
0.959
Networking
0.843
0.927
OF1=(the extent of cooperation with officers)
0.922
OF2=(the extent of connections with officers)
0.937
Validity Test for Reflective Measurements
Convergent Validity
Convergent validity refers to the degree of agreement in two or more measures of the same construct (Camines and Zeller, 1979). Some researchers suggest that convergent validity is attained the Average Variance Extracted for each factor component is ≥ 50% (Anderson and Gebing 1988). Average Variance Extracted (AVE) reflects the overall amount of variance in the items accounted for by the latent construct (Cheung and lee, 2001). Thus, from table (2), it is found that all of the AVE values are greater than the acceptable threshold of 0.50; thus, convergent validity is confirmed for Financial Government Support (0.978) and Network (0.864).

40
Table 2: Factor Loading and AVE
Factor Loading
AVE
0.978
GSF1
0.984
GSF2
0.979
GSF3
0.959
Networking
0.864
OF1
0.922
OF2
0.937
Discriminant Validity
Discriminant validity is the degree to which any single construct is different from the other constructs in the model (Carmines and Zeller, 1979). Discriminant validity is to compare the Square Root of Average (AVE) for each construct and as the correlations between constructs with other constructs in the research model. The model has sufficient discriminant validity if the Square Root of AVE for each construct is greater than the correlation between the constructs and other constructs in the model. If the value is the root of AVE is higher than the correlations between other constructs, so it can be inferred constructs have a good level of validity. Therefore, it can be seen from the Square Root of AVE is higher than the value of the correlation between other constructs (Table 3).
Table 3: Fornell-Larcker Criterion Analysis for Checking Discriminant Validity
Network
0.989
0
Network
0.446
0.930
Assessment Formative model
Convergent Validity for Formative Model (Finance)
We examined convergent validity using redundancy analysis. That is achieved by correlating Access to finance as formative construct with an access to finance-global measure for that construct. The access to finance is modelled as the independent variable and the access to finance-global measure is the dependent variable.
Table 4: Path coefficient between Access to Finance and finance- global measure
Access to Finance
Finance-global
Access to Finance
0
0.903
Finance-global
0
0
By looking to the results obtained from this analysis (Table 4) we found that the path coefficient (0.903) above the threshold of 0.80 and that provides support for convergent validity of the formative construct.
Collinearity for Formative Model
The collinearity test aims to assess the assumption of no Multicollinearity, Tolerance Value or Variance Inflation Factor (VIF) of Access to finance is evaluated. A Tolerance is defined as the amount of variability of the selected independent variable not explained by the other independent variables (Hair et al, 2010). Variance Inflation Factor (VIF) which is calculated simply as the inverse of the Tolerance Value (Hair et al, 2010). VIF is less than (3.3) that shows an excellent value (Diamantopoulos and Siguaw, 2006) and Tolerance Value above the threshold value of (0.2) (Ken Kwong, 2013) indicate that no Multicollinearity for the constructs.

41
Table 5: Collinearity Analysis of Finance Construct
Coefficients
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
Collinearity Statistics
B
Std. Error
Beta
Tolerance
VIF
Constant
2.264
0.212
10.656
0
F1
0.027
0.097
0.025
0.274
0.784
0.624
1.603
F2
0.023
0.089
0.024
0.256
0.798
0.594
1.683
F3
0.138
0.092
0.165
1.5
0.135
0.441
2.265
F4
0.089
0.087
0.115
1.02
0.309
0.422
2.367
Table (5) presented that all indicators of access to finance have Variance Inflation Factor (VIF) <3.3 and Tolerance Value above the threshold value of (0.20). Thus, that indicates the Multicollinearity does not exist for Access to finance.
Significance and Relevance of Outer Weights for Formative Model
The third step in evaluating formative measurement model is to examine the statistical significance of the Outer Weights (not the loadings). This is done with the bootstrapping option of Smart PLS. Results for our model are given in Table 6.
Table 6: Statistics Significance of Outer Weights (Formative constructs)
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
F1 -> FINANCE
0.239
0.235
0.115
0.115
2.086
F2 -> FINANCE
0.317
0.315
0.103
0.103
3.072
F3 -> FINANCE
0.346
0.339
0.112
0.112
3.093
F4 -> FINANCE
0.331
0.331
0.112
0.112
2.964
By reviewing the above table we notice that all these formative indicators F1 (t=2.086), F2 (t=3.07), F3 (t=3.093), F4 (t=2.964), T2 (t=2.309) and T4 (t=2.957) are significant because they all have t-values above 1.96 at p<0.05.
Assessment Structural Model
Once the reliability and the validity of the measures are assured, path coefficients can be reported based on the results of a PLS structural model. The structural measurement shows in (Table 7). After assessing the measurement model we found that the measurement model reliable and valid for PLS-SEM analysis and we can estimate the path coefficients between the constructs in structural model. The next step is to assess the structural model results. This involves examining the relationships between the constructs and the model’s predictive capabilities.
Assess the Significance and Relevance of the Structural Model
The path coefficients for the structural model are shown in the next table. These results were obtained from the Smart PLS Default Report. Before examining the sizes of the path coefficients we will first examine their significance. To do so, we must first use the Bootstrapping technique.
Table 7: Assess the Significant and Relevance of the Structure Model
Original Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
Standard Error (STERR)
T Statistics (|O/STERR|)
Network ->Financial Government Support
0.668
0.667
0.042
0.042
15.576
Financial Government Support- >Finance
0.608
0.612
0.047
0.047
12.821

42
The above results show the significance of the path coefficients. The t-values can be compared with the critical values from the standard normal distribution to decide whether the coefficients are significantly different from zero. For instance, the critical values for significance levels of 5% (α= 0.05) probability of error is 1.96 (two-tailed test). In this study the Table 7 presents that the relationship between networking with officers and the ability of firm to gain financial government support is positive with coefficient (0.668) and significant with t=15.576 which is >1.96 at p<0.05. That indicates the H1 is supported. In addition, the ability of firm to access financial government support impact positively and significantly the ability of firm to access finance. The path coefficient of this relationship is (0.608) with t=12.821 which is >1.96 at p<0.05; Hence, the H2 is supported.
Assess the level of R2
The term R2 refers to the fraction of variance explained by a model. R2 is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination, or the coefficient of multiple determinations for multiple regressions (Frost, 2013).
Table 8: the level of R2
R Square(R2)
Finance
0.369
0.446
Network
0.000
The R² values of the endogenous latent variables are available in the PLS Algorithm default report, as shown in Table 8. The results obtained from the analysis of the data revealed that the R2 values of Financial Government Support (0.446) can be considered as moderate, which means the Network with Officers explained 44.6% of variance in Financial Government Support. The R² value of Finance (0.369) can be considered as weak that where the Financial Government Support (as a predictor of Finance) explained just 36.9% of variance in Finance.
Assess the Predictive Relevance Q2
The Q² measure applies a sample re-use technique that omits part of the data matrix and uses the model estimates to predict the omitted part. Specifically, when a PLS-SEM model exhibits predictive relevance, it accurately predicts the data points of the indicators in reflective measurement models of multi-item as well as single-item endogenous constructs and the procedure does not apply to formative endogenous constructs (Hair, 2006). So in this study, the procedure can be applied for Financial Government Support. For SEM models, Q² values larger than zero for a specific reflective endogenous latent variable indicate the path model's predictive relevance for a particular construct; Q² values of zero or below indicates a lack of predictive relevance (Hair et al, 2013).
Table 9: Predictive Relevance Q2 for Government Support in Finance
Total
SSO
SSE
1-SSE/SSO
Finance
708
549.124
0.224 Financial Government Support 531 308.2658 0.420
As shown in the table above the result of cross-validated redundancy indicated that the (1-SSE/SSO) for the path model the predictive relevance Q2 of Financial Government Support has value of 0,420 which indicates the model has large predictive relevance for this construct.
5. CONCLUSION
This study examined the influence of networking with officers on financial government support and examined the influence of financial government support on the ability of firm to access finance. The results of this study supported the hypotheses which are that the networking with officer in SME Corp. Malaysia enhances positively and significantly the ability of firm to gain financial government support; also, financial government support improves positively and significantly the ability of firm to gain more finance. This study offers practical implications from its findings, both to the Malaysian SMEs and policy-makers. For Malaysian SMEs, the findings of this study would enable them to understand more on the impact of connection and interactions with officers in SME Corp. Malaysia. Networking may benefit those SMEs who are actually taking steps to network. Others may not. But a broad based training of SMEs by the SME Corp. will enhance existing networking and create/develop new ones. Networking will

43
enable the SMEs’ owners/mangers to gain knowledge and information about the availability of assistances provided by Malaysian government. Without such knowledge the SMEs will lose opportunities to utilizing the government supports. Also the networking with officers will provide SMEs’ owners/mangers vital information about the main stream of the government policy about supporting SMEs. Hence, the economic opportunities for extend the size of enterprises within these circumstances will be increased. In addition, the networking with officers in SME Corp. Malaysia will make the SMEs’ owners/mangers aware about the benefits of government supports and its effect on growth of SMEs, competitive position; overcome the challenges which they are facing, enhancing their capability and capacities. What more, the interaction with officers in SME Corp. will make SMEs’ owners/mangers more conversant on how to apply for government support and how to fulfil all requirements to gain the government support and thus to use these assistances efficiently.
REFERENCES
Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modelling in practice: Areview and recommended two-step approach. Psychological Bulletin, 103 (3), 411-423.
Ayyagari, M. Demirguc-Kunt, A. and Maksimovic, V. (2008). Formal versus informal finance: Evidence from China. Working Paper No 4665. Washington: The World Bank.
Baba Md Deros, Nizaroyani Saibani, BahrimYunos, Mohd Nizam Ab. Rahman, and Jaharah, A. Ghani.(2012). Evaluation of Training Effectiveness on Advanced Quality Management Practices, ICTLHE. RCEE. RHED2012. avialable at: http://tree.utm.my/wp-content/uploads/2013/03/1569533395.pdf.
Barkham, R., Gudgin, G., Hart, M. and Hanvey, E.(1996). The Determinants of Small Firm Growth: An Inter- Regional Study in the United Kingdom 1986-1990. Regional Policy and Development Series. London: Jessica Kingsley Publishers.
Levine, R. (2004). Finance and Growth: Theory and Evidence. In: Handbook of Economic Growth.
Carmines, E. G., and Zeller, R. A. (1979).Reliability and validity assessment. Beverly Hills and London: Sage.
Cheung, C. M. K., and Lee, M. K. O.(2001). Trust in Internet Shopping: Instrumental Development and Validation through Classical and Modern Approach. In Felix, B. T. Advance Topics in Global Information Management.IDEA Group Publishing. USA. 2002.
Cooper, D. R., and Schindler, P. S. (2003).Business Research Methods.(8th edition). USA: McGraw-Hill.
Cordeiro, C., Machas, A., and Neves, M.M. (2010). A Case Study of a Customer Satisfaction Problem: Bootstrap and Imputation Techniques. in: Vincenzo Esposito Vinzi, Wynne W. Chin, JörgHenseler, Huiwen Wang. 2010. Handbook of Partial Least Squares: Concepts, Methods and Applications. Springer Heidelberg Dordrecht London New York, pp: 279 - 287.
Coviello, N.(2006). The network dynamics of international new venture. Journal of International Business Studies, 37 (5), 713-731.
Deakins, D., Ram, M.,Smallbone. D and Fletcher, M. (2003). Ethnic Minority Entrepreneurs and the Commercial Banks in the UK: Access to Formal Sources of Finance and Decision-Making by their Bankers. In Stiles, C. and Galbraith, C. (eds) Ethnic Entrepreneurship: Structure and Process, Elsevier: Oxford. pp. 293-314.
Diamantopoulos, A. and Siguaw, J. A.(2006). Formative versus Reflective Indicators in Organizational Measure Development: A Comparison and Empirical Illustration. British Journal of Management.17, 263.
Fagan, M. and Zhao, S.(2009). SME financing in China: The current situation, problems and possible solutions. International Journal of Entrepreneurship and Small Business. 8 (2): 171-185.
Fornell, C., and Larcker, D. F. (1981).Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research.18 (1) 39-50.

44
Frost, J. (2013). Regression Analysis: How Do I Interpret R-squared and Assess the Goodness-of-Fit? Available on: http://blog.minitab.com/blog/adventures-in-statistics/regression-analysis-how-do-i-interpret-r-squared-and- assess-the-goodness-of-fit.
Hair, J. F. , Black, W. C. , Babin, B. J. and Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New Jersey, NJ: Pearson Prentice Hall.
Hair, J. F. ,Ringle, C. M. , and Sarstedt, M. (2013). PLS-SEM: Indeed a Silver Bullet, Journal of Marketing Theory and Practice, vol. 19, no. 2 (spring 2011), pp. 139-151.
Harvie, C. (2001). Competition policy and SMEs in Vietnam. Working paper series 2001, WP 01-10, University of Wollongong, Department of economic.
Harvie, C., D. Narjoko and S, Oum. (2010).Constraints to Growth and Firm Characteristic Determinants of SME Participation in Production Networks. In Vo, T. T., D. Narjoko and S. Oum (eds.), Integrating Small and Medium Enterprises (SMEs) into the More Integrate East Asia. ERIA Research Project Report 2009-8, Jakarta: ERIA. pp.68-115.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal. 20 (2), 195-204.
Jon, A. K. and Stanley, P. (2010).Question and Questionnaire Design. Handbook of Survey Research, Second Edition Copyright r 2010 by Emerald Group Publishing Limited. ISBN: 978-1-84855-224-1
Kader, R. A., Mohamad, R. M., and Ibrahim, C. A. (2009). Success Factors for Small Rural Entrepreneurs under the One-District-One-Industry Programme in Malaysia. Contemporary Management Research. Vol. 5 (2), pp. 147-162.
Ken Kwong-Kay Wong. (2013) .Partial Least Squares Structural Equation Modelling (PLS-SEM) Techniques Using SmartPLS. Marketing Bulletin, 2013, 24, Technical Note 1. Pp 1-32. available on : http://marketing- bulletin.massey.ac.nz.
Knight, G. A., and Cavusgil, S. T. (2004). Innovation, organizational capabilities, and the born-global firm. Journal of International Business Studies, 35: 124-141.
Kusumawardhani, A., McCarthy, G. and Perera, N. (2009). Framework of entrepreneurial orientation and networking: a study of SMEs performance in a developing country.
Moha A. Abdullah and Siti Khadijah A. Manan.(2010). Adequacy of Financial Facilities for Small-Medium Businesses: Empirical Findings from Malaysia. Journal of International Review of Business and Research Papers. Vol.6. No. 4.(September).
Nurbani Binti Hassan, Jian Ai Yeow, Susan Tee Suan Chin, and Noor Ashikin Binti Mohd Rom. (2010). Financial Constraints and Opportunities of Micro Enterprise Entrepreneurs: A Theoretical Framework. International Conference on Business and Economics Research. vol.1 (2011 ), IACSIT Press, Kuala Lumpur, Malaysia.
Storey, D. J. (1994). Understanding the small business sector. London: Thomson Learning.
UNDP, United Nations Development Programme. (2007). Malaysia Small and Medium Enterprises Building an Enabling Environment. United Nations Development Programme (UNDP), Malaysia. January: pp 8-13.
Tagoe, N., E. Nyarko and E. Anuwa-Amarh.(2005). Financial Challenges Facing Urban SMEs Under Financial Sector Liberalization in Ghana. Journal of Small Business Management 43 (3), pp. 331-343.
Wu, W. P. and Leung, A. (2005). Does a micro-macro link exist between managerial value of reciprocity, social capital and firm performance. Asia-Pacific Journal of Management 22 (4): 445-463.
Yusuf, Attahir. (1995). Critical Success Factors for Small Business: Perceptions of South Pacific Entrepreneurs. Journal of Small Business Management. 33(1): pp. 68-73.

45
Zhou, Y.(2008). Do Network Connections with Foreign Investment Enterprises Help Host Country Firm Innovations? ; Presented in Partial Fulfilment of the Requirements for The Degree Doctor of Philosophy in the Graduate School of The Ohio State University.
Ziza Che Senik. (2010). Models, Processes and factors influencing internationalisation: the case of Malaysian SMEs, the thesis submitted for degree of doctor of philosophy of Murdoch Univercity.
Zizah Che Senik, Rosmah Mat Isa, Brenda Scott-Ladd and Lanny Entrekin. (2010). Influential Factors for SME Internationalization: Evidence from Malaysia, Journal of Economics and Management 4 (2): 285 - 304 (2010).

Klibel5 econ 5_

More Related Content

What's hot (20)

Viewers also liked (17)

Similar to Klibel5 econ 5_ (20)

More from KLIBEL (20)

Recently uploaded (20)

Klibel5 econ 5_