Factors affect account receivable management and its impact on business performance of Vietnamese enterprises

ness, or the profitability of the asset and the return on equity are greatest. This contributes to the assumption that Lewellen et al. (1980), in the imperfect competition market, would incur expenses related to credit assessments and contingency expenses, thus creating a premise for commercial credit policy affecting the efficiency of business operations. Thus, granting commercial credit can bring benefits such as increased revenue, expanded market share, but at the same time cause losses to businesses such as increased financial costs and opportunity costs. customers do not pay or pay late. If these costs exceed the benefits, they will reduce the efficiency of business operation. Thus, we can 658 conclude in practice that the relationship between customer receivables and business performance is inverted-U, there is an optimal level of receivability at which efficiency. The activity of the business is the greatest. At the low level, when the efficiency of the business increase and the optimal receivables is reduced, the efficiency of the business will decrease. Moreover, the deviation from the optimal value reduces the efficiency of the business. Thus, the implication in our study for researchers and business managers is that managing commercial credit policies is critical to business operations in order to increase operational efficiency through the profitability of assets and profitability of equity. Businesses should strive to ensure the optimum level of customer acquisition to maximize business performance. For the Vietnamese market, the average customer receivable margin of the industry is about 25% of the total assets. However, the limitation of this study is the cases for each industry with different characteristics and for different sizes of enterprises (large enterprises, small and medium enterprises) different commercial applications. 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Statistics describe the rate of customer receivables and business performance Factors that affect account receivables Experimental results of previous studies Expectations of our research Provision for doubtful receivables (PROVI) +/- Revenue growth (GROWTH) (+) Emery (1984) (+) Petersen and Rajan (1997) (+) Niskanen and Niskanen (2006) (-) Garcia-Teruel and Martinez-Solano (2010) (+) Vaidya (2011) +/- Size (SIZE) (+) Nadiri (1969) (+) Petersen and Rajan (1997) (+) Ng et al. (1999) (+) Danielson et al. Scott (2004) (+) Niskanen and Niskanen (2006) (+) Bougheas et al. (2009) (+) Garcia-Teruel and Martinez-Solano (2010) (+) Khan et al. (2012) (+) Shi et al. (2016) + Years of Operation (LAGE) (+) Petersen and Rajan (1997) (+) Niskanen and Niskanen (2006) (+) Bougheas et al. (2009) (Meaningless) Garcia-Teruel and Martinez- Solano (2010) (+) Khan et al. (2012) (+) Shi et al. (2016) + Short-term finance (STLEV) (+) Petersen and Rajan (1997) (+) Niskanen and Niskanen (2006) (+) Garcia-Teruel and Martinez-Solano (2010) (-) Vaidya (2011) +/- Financial cost (FCOST) (-) Petersen and Rajan (1997) (-) Garcia-Teruel and Martinez-Solano (2010) - 664 Factors that affect account receivables Experimental results of previous studies Expectations of our research Cash flow (CFLOW) (Meaningless) Niskanen and Niskanen (2006) (+/-) Garcia-Teruel and Martinez-Solano (2010) +/- Total assets turnover (TURN) (-) Long et al. (1993) (+) Garcia-Teruel and Martinez-Solano (2010) +/- Profits (GPROF) (+) Emery (1984) (+) Petersen and Rajan (1997) (+) Garcia-Teruel and Martinez-Solano (2010) + Inventory Ratio (INVEN) (-) Bougheas et al. (2009) (-) Vaidya (2011) - Liquidity (LIQ) (-) Nadiri (1969) (+) Ng et al. (1999) (-) Bougheas et al. (2009) (+)Vaidya (2011) +/- 665 APPENDIX 2. Table 3. Previous research on the impact of receivables on the value of the enterprise and results of the study on the impact of receivables on performance Independent variable Verification of the fit of the model Dependent variable REC REC2 GROWTH SIZE LEV Martínez-Sola et al. (2012) Enterprise value Tobin’s Q + - + Meaningless Meaningless AR (2)> 0.1 and Hansen test> 0.1 so the model is fit MBOOK + - + Meaningless + AR (2) <0.1 and Hansen test> 0.1 should have autocorrelation Expectations of our research Business performance ROA + - + +/- - AR(2) > 0.1 and Hansen test > 0.1 ROE + - + +/- - AR(2) > 0.1 and Hansen test > 0.1 APPENDIX 3 Table 4. A composite of previous studies on the impact of changes in receivables on the value of enterprises and results of the study on the impact of changes in receivables on performance Dependent variable Independent variable Verification of the fit of the model DEVIATION GROWTH SIZE LEV Martínez-Sola et al. (2012) Tobin’s Q - + Meaningless + AR (2)> 0.1 and Hansen test> 0.1 so the model is fit MBOOK - + Meaningless + AR (2) <0.1 and Hansen test> 0.1 should have autocorrelation Expectations of our research ROA - + +/- - AR(2) > 0.1 and Hansen test > 0.1 ROE - + +/- - AR(2) > 0.1 and Hansen test > 0.1