effects of liquidity management on operating performance of manufacturing firms evidence from japan

Abstract

　　The examined ex-post operating performance showed that the 2008‒2009 financial crisis hit Japanese firms through trade and liquidity channels (Claessens et al. 2012, Hosono et al. 2012), while the Great East Japan Earthquake affected supply chain networks (MacKenzie et al. 2012). Considering working capital management as a vital issue in explaining liquidity of firms, by employing a fixed effect LSDV model, the author analyzed the effects of components of working capital management like cash conversion cycle (CCC) on profitability of firms. The results revealed a significant negative relationship between firmsʼ performance and cash conversion cycle. It revealed that excess inventory significantly bared extra costs for just-in-time accustomed Japanese manufacturing firms. Moreover, in addition to handling inventories skillfully, distributing trade credits proficiently among buyers (AR) had important effects to better profitability. Both components together resulted in days of cash conversion cycle (CCC) to take strongly negative relationship with profitability. Other findings explain that the 2008‒09 financial crisis hit Japanese core manufacturing industries to a degree that the worsened profitability could not have been improved by managing payments to suppliers efficiently and by taking receivables as early as possible. However, it confirmed that dealing with inventories properly had significant effects even during the 2008‒09 financial crisis. The fact that days of accounting payables (AP) did not show any significance demonstrates the cash abundancy of Japanese manufacturing firms.

Key words: multinational firms, financial crisis, shocks, liquidity, working capital, cash conversion cycle; JEL: D21, F23, L25

1．Introduction1)

1. 1　Theoretical Foundations　　Working capital (WC) is the money spent for suppliers to create value and to regain from clients for sold

Effects of Liquidity Management on Operating Performances

of Manufacturing Firms: Evidence from Japan

Ashrafbek Olimov

　　　　　　　　　1）The precise instructions of my supervisor, Professor Sato, concerning the source and access to the Japanese firm

level data eased my workload, helped overcome language barriers, and, in general, saved me a lot of time. In addition, his comments and suggestions provided during my presentations in his seminars allowed me to explore a wide range of different aspects in this research field.

74 横浜国際社会科学研究　第 20 巻第 3号（2015 年 9 月）

products. WC is the investment of a firmʼs capital in current assets and the use of current liabilities to fund part of its investments (Napompech 2012).　　Working capital management is the ability of a manager to handle existing capital between the interval of payments for raw materials purchased and needed for the daily operations of the firm to pay for suppliers and to receive payments from clients. Textbooks explain it as the difference between current assets and current liabilities in the balance sheet of a firm (Figure 1). Managers should choose the capital structure that they believe will have the highest firm value because this capital structure will be most beneficial to the firmʼs shareholders (Hiller, 2010).2) Managersʼ primary task is handling an optimal level of working capital which maximizes profitability and keeps solvency at the best possible level in both the short and the long term.　　Working capital management (WCM) is a vital issue in a firmʼs overall financial management and it has implications for both liquidity and profitability (Bagchi et al. 2012). The objective of WCM is maintaining the optimum balance of each account―that is, receivables, inventory and payables―that influences a firmʼs performance (Filbeck et al. 2005). Textbooks explain that working capital (WC) has a driving role in a firmʼs liquidity and profitability. Simple interpretation of working capital management is linked to the understanding of working capital requirement. Furthermore, working capital under the supervision of a manager can be found in three processes: accounts receivables, inventories, and accounts payables, and the duration of time working capital is in one of the above forms has a direct impact on profitability. For instance, keeping inventories outstanding for a longer period of time may incur extra costs while delaying receivables may cause a suspension in payables. The combination of all working capital management is explained as the cash conversion cycle which is depicted in Figure 2. Whereas, the profit maximization is one of key priorities for majority firms in a long term, each round of cash conversion cycle may have a significant effect to the firmʼs profitability. When cash conversion cycle of the firm becomes shorter, such as through receiving receivables faster from its clients, the firm may have much actual cash and further may use it for other purposes such as buying new machinery or equipment, modernizing production and selling procedures as well as investing to advertisement or other goodwill purposes. Consecutively, it will increase firmʼs operating profitability. Conversely, if firmʼs cash conversion cycle becomes longer, such as through keeping its inventories too long or letting its clients longer trade credits, managers may face difficulties to find cash in investment activities. It may decrease firmʼs profitability. In this occasion, CCC is considered to have a negative relationship with profitability. Since, the CCC is the combination of three different procedures of cash circulation, it is highly possible that one or two may have negative while the other(s) have positive relationship in firmʼs profitability. For instance, by paying faster to its creditors, the firm may have a good credibility and reputation and might benefit from lower prices which will have a direct impact to its profitability. To understand better the firmʼs behavior in managing its working capital among cash conversion cycle procedures, one should define the actual differences between working capital and actual cash flow, another important financial variable in firmʼs investment and other activities. Actually, net working capital is directly linked with cash and equivalents, though it is not the same as actual cash flow of the firm. For instance, if the firm wants to increase its inventory, it should use cash. However, because both inventories and cash are considered to be current assets, this does

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　　　　　　　　　2）Hillier et al., 2010 “Corporate Finance”. Most of textbook explanations cited in this chapter are gotten from this

book.

75Effects of Liquidity Management on Operating Performances of Manufacturing Firms（Ashrafbek Olimov）

not affect net working capital. In this matter, an increase in inventory is linked with decreasing cash flow.

　　Current research has tried to examine the empirical evidence between working capital and the profitability of Japanese firms by analyzing panel data for 2008‒2013, during which, Japanese firms faced two consecutive different types of shocks. Using six years of disaggregated balance sheets, income statements and cash flow data of 609 Japanese manufacturing firms from the major four industries, and a total panel set of 2662 firm-year observations, the author tried to analyze how the decisions of managers to distribute working capital during shock periods affects firmsʼ profitability. Following previous studies, we applied both pooled OLS model and fixed effects least-squares dummy variable (LSDV) model in our research. Primarily, the literature tried to examine the disturbance channels to Japanese firms during demand shock by analyzing the changes in operating performance subsequent to the shock. The examined ex-post operating performance showed that the 2008‒2009 financial crisis hit Japanese firms through trade and liquidity channels while credit channel was not significant (Claessens et al. 2012, Hosono et al. 2012). Therefore, the author decided to more thoroughly analyze liquidity issues following the standard methodology (Deloof 2003).3) Investigating liquidity management and operating performance showed that only one component of working capital management, good inventory handling, was helpful during the financial crisis. Considering working capital management as a vital issue in explaining liquidity of a firm, by employing both fixed effects LSDV model and plain OLS, the author analyzed the effects of components of working capital management such as cash conversion cycle (CCC) on the profitability of firms. In order to bolster our findings, we ran all analyses for three sample periods, the first of which was the whole sample period from 2008 to 2013, the second of which captured the aftermath of the Great East Japan Earthquake (GEJE) period―from 2011 to 2013, and the third of which excluded 2008―the core financial crisis year from the first sample period (2009‒2013). The results revealed a significant relationship between firmsʼ performance and cash conversion cycle components. It revealed that excess inventory significantly bared extra cost for largely just-in-time4) accustomed Japanese manufacturers and showed significant negative relationships with profitability in all sample periods and in both types of regression models. The results also revealed that delayed receivables in the post crisis period consecutively resulted in a decline in investment, because, cash-rich Japanese firms did not suspend payables. As a result, it showed strong negative correlation with firmsʼ profitability. Therefore, fluctuations in accounts payables did not significantly affect the profitability of already popular, cash-rich Japanese manufacturing

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　　　　　　　　　3）Deloof (2003) applied both fixed effects and plain OLS models while majority other followers chose either.4）Just-in-time inventory strategy is a way to cut the costs through handling inventory skillfully. This system

adopted in early 1970s by Toyota, then widely spread during 70ʼs and 80ʼs among other Japanese and North American manufacturers. Just-in-time manufacturing focuses on producing the goods based on demand and in its best form, it decreases all work-in-progress to zero, and manufactures products that are immediately needed in the market. It has led to improving inventory management and better production flexibility among many manufacturers, which may have resulted in lower volatility of output (Kimura and Shiota 2009). Although just-in-time inventory system has not been accepted by all Japanese manufacturing firms, literature agrees that it has been widely used by many auto-manufacturers in broader sense while it has been adopted by machinery and electronics manufacturers to some extent to save their the costs and improve competitiveness (Nakamura et al. 1998, Kimura and Shiota 2009, Mia 2000). Since our sample contains four major core-manufacturing industries such as transportation equipment, electric appliances, precision equipment, and machinery, we assume that majority of firms are just-in-time adopted manufacturers.


firms. One of the prior findings of current research suggested that the 2008‒09 financial crises severely hit firmsʼ profitability to that extent that even handling receivables and payables did not show any significant effect on profitability. More simply, if we include the core financial crisis year―2008 data in our panel―the results did not show any significance between accounts-receivables-payables (AR and AP) and profitability. The results confirm that by moving inventory properly, firms could improve their profitability or, conversely, by keeping inventory for a long period because of a sharp decline in demand, firmsʼ profitability significantly declined.　　The remainder of this paper is constructed as follows: After discussing the survey of literature in the next paragraph of this section, data sources and samples will be discussed in Section 2. Section 3 presents the framework of research including the hypothesis and methodology employed and introduces variables, while we discuss descriptive statistics in Section 4. Section 5 discusses the paperʼs findings while finally, Section 6 provides a conclusion.

1. 2　Survey of Literature　　There exists a wide range of literature linking working capital management and firmsʼ profitability. Following Shin and Soenenʼs (1998) landmark findings of the strong relationship between a firmʼs profitability and working capital management, Deloof (2003) suggested that managers can create value for their shareholders by reducing the number of days of accounts payables and receivables to a reasonable minimum while Lazaridis and Tryfonidis (2007) found that there is a statistically significant negative relationship between profitability, measured through gross operating profit, and the cash conversion cycle and suggested that, “Suggesting that managers could increase the profitability by lengthening the payable deferral period.” Jose et al. (2003) found that a lower cash conversion cycle is significantly connected with higher profitability for some industries including manufacturing. Particularly for Japan, Nobanee et al. (2014) analyzed 2123 non-financial Japanese firms for the 1990‒2004 period and found a strong negative relationship between cash conversion cycle (CCC) (and its components) and returns on investment. However, their test was based on a bivariate regression analysis. Wang (2000) analyzed liquidity managementʼs relationship with operating performance for Japanese and Taiwanese firms for 1985‒1996 and found that aggressive liquidity management eases operating performance and associated with higher corporate values for both Japan and Taiwan despite their structural differences. Her paper was limited to a sole cash conversion cycle without going further into its components.　　Many Japanese companies have been recognized as being more profitable because of the adoption of just-in-time production systems (Nakamura et al. 1998). Mia (2000) empirically tested and found that firms that adopted just-in-time manufacturing systems are significantly more profitable than those that did not. Many Japanese firms try to decrease their raw-materials, merchandise, and all other inventories to the minimum level to cut production costs. It is a successful policy, though it may create disadvantages once there are suddenly accumulated inventories which bear extra costs. Considering the nature of the 2008‒2009 financial crisis and the 2011 natural disaster, we tried to examine the relationship between working capital (WC) management and firmsʼ profitability.

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2．Data Sources and Samples

　　1. (data sources) By using disaggregated accounting data of Japanese manufacturing firms collected from annual securities report (Yuka-Shouken Houkoku-sho) and from Pronexus database sources, we constructed 2687 year-firm observation panel data from balance sheets, cash flow, income statements and management indices. The numbers of observations for 2012 stands for 574 firms. The whole panel sample period covers data of financial years from 2008 to 2013. For instance, the 2008 data capture firmsʼ closing date of financial reports which ended on March 31, 2009, while the 2009 data capture firms which closed their accounting by March 31, 2010 and so on. Therefore, the last year period of our sample depicts financial report data which ended by March 31, 2014. The firms come from the four main manufacturing industries, including transportation equipment, electric appliances, precision equipment, and machinery. Initial descriptive statistics are shown in Tables 3, 4, and 5.　　2. (Samples) The reason we chose a sample period from 2008 to 2013 was to include the latest double consecutive shocks, the former being the 2008‒09 financial crisis and the latter being the 2011 Great East Japan Earthquake. However, we also decided to see how working capital management affected the manufacturing firmsʼ profitability after the Great East Japan Earthquake only, which was why we ran our regressions for the period 2011 to 2013 with our second sample, or simple subsample. Moreover, observing that the 2008‒09 financial crisis deteriorated firmsʼ profitability far beyond the handling effective working capital policy, we omitted core financial crisis period―20085) from our main sample and ran our regressions for the period 2009 to 2013. The following table shows the details of the sample periods:

　　In the current analysis, the sample data have not been winsorized in order to clean outliers which are considered to be the results of effects of the financial crisis and natural disaster. Since the primary purpose of the current analysis is examining the impact of crises on operational performance, we applied the data as they were, though we checked and corrected data for possible data-input mistakes and outliers. In the next section, we discuss our framework and variables.

3．Framework and Variables

　　The story of liquidity dry-up during the financial crisis is explained as follows: After a sudden drop in

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　　　　　　　　　5）As mentioned above, the 2008 sample data capture financial statements as of March 31, 2009, which is consistent

with the core 2008‒09 financial crisis period.

Table 1　Details of Samples

Sample Name Period Firm-year observations Empirical Models Empirical Results

Main Sample 2008‒2013 2662 Fixed effects LSDV, Plain OLS Table 7,10

Subsample 1 2011‒2013 1116 Fixed effects LSDV, Plain OLS Table 8,11

Subsample 2 2009‒2013 2216 Fixed effects LSDV, Plain OLS Table 9,12


demand, there was a high possibility of delay in payments from worldwide clients of Japanese multinational firms. Beyond this, there was a possibility of increases in the inventories of Japanese manufacturers, which are accustomed to the just-in-time system. The above two factors would then increase the “receivables” in the “current assets” side of the balance sheet, resulting in the shortage of payments to the suppliers, which in turn may consecutively cause a boost in “payables” in the “current liabilities” side of the balance sheet unless the firm found some way to solve the shortage of working capital. Thus, a further analysis of working capital issues of manufacturing firms was needed.　　Textbooks explain that prior endogenous factors which directly affect working capital requirements include the following: (1)Working capital management policy or management over cash conversion cycle, (2) investing capacities, (3) dependence on external finance, credit, (4) firm size and sales growth rates, and (5) structure of the firm. Therefore, by determining the above factors we can examine the relationship between working capital management and profitability of the firm. In order to achieve our goal, we carefully pick up the most consistent variables which represent the internal factors of working capital.　　We capture the working capital components with the following variables:　　(1) Cash Conversion Cycle and its components:

AR=Number of Days Accounts Receivable= Accounts ReceivableSales ×365

INV=Number of Days Inventories= InventoriesCost of Goods Sold ×365

AP=Number of Days Accounts Payable= Accounts PayableCost of Goods Sold ×365

CCC=Cash Conversion Cycle=AR+INV–AP　　(2) Investing Capacities:

FFA = Fixed Financial Asset Ratio = Fixed Financial AssetsTotal assets

　　(3) Dependence on external finance:

FD=Financial Debt Ratio = (Short-Term Loans + Long-Term Loans)Total assets

　　(4) Firm size and sales growth rates:　　We capture firm size and sales growth with logarithmic sales value and sales growth rate ratios6） respectively.　　(5) Structure of the firm　　We also use industry dummies assuming similarity in firmsʼ structures within the industry.　　Beforehand going into our regression equation, we carefully define our hypotheses. In this paper, the following questions we are trying to answer may serve to define our research hypotheses:　　－　　 Is there a relationship between working capital management, solvency, and profitability? What is

the nature and the extent of this relationship.　　－　　Do different components of working capital management differently influence profitability? 　　－　　Does that relationship significantly differ during different periods?

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　　　　　　　　　6）Sales growth ratet=

Sales(t)-Sales(t-1)Sales(t-1)


　　On the basis of these research questions, we constructed the following hypotheses to be tested:　　・　　 Hypothesis 1: There exists a significant relationship between CCC components and profitability,

and the testing hypotheses of each CCC components are as follows: 　　　　　－　　H1.1: There exists a significant relationship between days of accounts receivables and

profitability.　　　　　－　　H1.2: There exists a significant relationship between days of inventories and profitability.　　　　　－　　H1.3: There exists significant relationship between days of accounts payables and

profitability.　　　　　－　　H1.4: There exists a significant relationship between days of cash conversion cycle and

profitability.　　・　　Hypothesis 2: 　　　　　－　　H2: There exists a strong relationship between financial debt ratio and profitability.　　・　　Hypothesis 3:　　　　　－　　H3: The existing relationships significantly differ for different periods.

　　In order to test the above hypotheses, we ran both fixed effect LSDV and plain OLS regressions with time and industry dummies in the latter and used the following empirical specification, which is widely used in the literature to test the relationship between working capital components and profitability (Deloof 2003, Padachi 2006, Nobanee 2009). In order to test three cash conversion cycle components separately as well as CCC itself, while keeping all other independent and control variables unchanged, we ran the following empirical expression:

GROSSit = β0 + β1 CCCCjit + β2 FDit + β3FFAit + β4lnSalesit + β5Salesgrowthi +β6 Industrys + ηi + λi + εit 　　　　　　　　　　　　

　　Where, dependent variable GROSS stands for

Gross Operating Profit Margin= (Sales - Cost of Goods Sold)(Total assets - Financial Assets)

　　Wherein the first independent variable CCCC stands for “cash conversion cycle components” and takes four variables depending on the change in j, j takes values from 1 to 4 and in each value it represents one of CCC components such as AR – Days of Accounting Receivables (j=1), INV – Days of Inventory outstanding (j=2), AP – Days of Payables (j=3) and finally CCC – Cash Conversion Cycle (j=4) correspondently. Other independent variables are defined as follows:　　・　　FD―Financial Debt Ratio = (Short Term Loans + Long Term Loans)/Total Assets　　・　　FFA―Fixed Financial Asset Ratio= Fixed Financial Assets/Total assets　　・　　lnSales―Firm Size(LnSales) = Natural Logarithm of Sales

　　・　　SalesGrowtht=Sales(t)-Sales(t-1)

Sales(t-1)

　　・　　Industrys―industry dummy which is equal to 1 if firm i falls industry S. 　　・　　ηi―unobservable heterogeneity, measures the particular characteristics of each firm　　・　　λt―time dummy variables.　　・　　ε ―error term

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　　In the next paragraph, we show our initial descriptive statistics then skip to our empirical findings.

4. Descriptive Statistics

　　Initial descriptive statistics for the main sample (2008‒13) is shown in Table 3, while Table 4 and Table 5 depict those for the subsamples for 2011‒2013 and 2009‒2013 respectively. Descriptive statistics suggest that firms waited for around 94 days to receive payments from their clients on average while they paid their suppliers sooner, in 69 days on average, which indicates that Japanese firms were richer in cash. The average days to sell inventory was three months. Overall, the average cash conversion cycle was 115 days. Those indicators slightly increased during the post-crisis period. Moreover, an average 10.0% of total assets were fixed financial assets and they did not vary over periods, which suggest that firms did not change their short-term investment policies drastically during and after the crisis. Firmsʼ financial debt ratios were on average 15%, which did not show significant changes over periods in terms of average share. Major changes can be observed in average sales growth ratios while it is showing a negative －0.96% average during the whole period. However, when we exclude the core-crisis year, it is positive and in growing trend, while its average is 2.31% and 1.32% during the first and the second subsample periods, respectively. Lastly, the average gross profit was around 40% during all sample periods. Next, we discuss our empirical findings.

5. Estimation Analysis

　　(Tests before test) We employed both fixed effects least square dummy variable (FE-LSDV) model and plain OLS model with year and industry dummies. Since we are trying to explore firmsʼ profitability through the variables such as the CCC components, we were concerned that some firm-specific endogenous variables may affect such predictor variables, therefore causing a bias in determining the outcome of our regression, which was why we employed the FE-LSDV model. By applying the FE-LSDV model, we tried to rule out the effects of such time-invariant characteristics; consequently, we were able to obtain a much clearer prediction of profitability through our explanatory variables. However, worrying that firmsʼ error terms and constants that capture firm-specific characteristics might be correlated with others, we applied the Hausman test to determine whether the unique errors are correlated with the regressing variables. Therefore, the Hausman test showed that the p-value (chi square value) was lower than 0.05, as a result we were assured these were not random effects. We also calculated modified Wald statistics for groupwise heteroskedasticity in the residuals of our FE-LSDV model. Therefore, because homoscedasticity was rejected, all standard errors are calculated by employing the Huber/White sandwich estimator for heteroskedasticity.　　(Correlation analysis) Initial findings for all variables from the Pearson regression analysis are displayed in Table 6.7) Pearson regression coefficients showed a positive relationship between days for accounts receivable and solo dependent variable, gross operating profit margin (GROSS), and so did the cash conversion cycle itself. However, GROSS was negatively correlated with day of inventories and accounts payables. It can be interpreted that as the number of firms keeping inventories increases, the less profitable they will be and the later they pay their suppliers, the less profit they gain. Since none of the cash conversion cycle components

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　　　　　　　　　7）All Pearson correlation coefficients were checked for 5% level significance.


was significantly correlated with profit in head-to-head correlation, we expected more feasible results from regression analysis where we determine dependent variables with multiple explanatory variables. GROSS showed a negatively significant relationship with fixed financial assets ratio and financial debt ratio, which is consistent with the presumption that the more firms invest or the more debt they incur, the less gross profit they gain in the short term. Dependent variables were also highly-positively correlated with sales growth, which is fully reliable with the initial precondition that firms with more sales growth can generate more gross profit.　　(Empirical results) Empirical results of the FE-LSDV model are presented in Tables from 7 to 9, each for one of the three samples respectively, while those for OLS are shown in Tables 10 to 12. Each time, we only varied the cash conversion cycle components (AR-column 1, INV-column 2, AP-column 3 and CCC-column 4), which made differences in the columns of the empirical result tables, while other explanatory variables were the same in all tables. Dependent variables were also the same across all tables. Overall, both the FE-LSDV and the OLS tests showed similar significant results. 　　(Empirical results for cash conversion cycle components) In order to simplify our explanation and interpret the economic effects of our evaluations, we discuss significant variables. Therefore, we made the following table that depicts significant coefficients of CCC components: AR, INV, AP, and CCC. In other words, columns 1 to 6 in the below table present the significant results of CCC components from all tables 7 to 12, respectively. Since all CCC variables were set in days, coefficients shown in this table were already converted to interpret the impact of each variable when there was a 10-day change in any of them. For instance, －0.466 for INV in column 1 was interpreted as possessing inventories for an additional 10 days, with gross profit margin declining by 0.47% for 2008‒13.

　　(Main sample) Among the CCC components, only days of inventories in column 1 showed a negative significant result (－0.466) when the sample period included the core financial crisis year―2008. The mathematical interpretation of the coefficient is that keeping an inventory for an extra 10 days will decrease gross profit margin by 0.46% or vice versa. We did not insist on our numerical findings as being an accurate indication, though it evidently confirmed the negative impacts of prolonged work in process and outstanding inventories on the profitability of manufacturing firms across the sample period. It might be due to the fact that

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Table 2　 Impact of CCC components to firms’ profitability (regression coefficients were converted as effects in % for 10 day changes)

FE-LSDV model Plain OLS

Main 1st subsam. 2nd subsam. Main 1st subsam. 2nd subsam.

2008‒13 2011‒13 2009‒13 2008‒13 2011‒13 2009‒13

1 2 3 4 5 6

AR －0.421 * －0.416 ** －0.951 *** －1.05 ***

INV －0.466 ** －0.8 ** －0.317 * －0.164 * －0.224 **

AP

CCC －0.492 *** －0.358 *** －0.335 *** －0.432 ***


Japanese manufacturing firms are too sensitive to inventories, while most of them implemented “keeping least inventories” through the “just-in-time system”. Other CCC components did not show significance when our sample included 2008 year data. 　　(1st subsample) When panel data covered only the 2011‒13 period, two CCC components and CCC itself showed a strong negative relationship with firmsʼ performance. The economic interpretation of the coefficient for AR in column 2 is that a 10 day delay of payment by clients (receivables) would result in a 0.42% drop in gross operating income during 2011‒2013. Or, generating trade-credits 10 days faster than usual could improve their profitability by 0.42%. Moreover, if firms keep their inventories for 10 days more across the period, their gross operating income would decrease by 0.8%. Therefore, the effects of the above two components are reflected in the negative relationship between CCC and profitability. Simply, if a firmʼs total cash conversion cycle increases by 10 more days, it would cause a 0.49% decline in its profitability. Again, we relied heavily on the significant impact of CCC components on profitability rather than their mathematical interpretations, while the above variables were too specific for each firm. 　　(2nd subsample) Interestingly, our results for the second subsample (2009‒2013) in column 3 also showed strongly significant results when we excluded just one year data―2008―from our main panel data. It can be explained as follows: the impact of 2008―the core crisis year‒was so severe that it deteriorated firmsʼ profitability to the extent said profitability could not be improved just by handling payments to suppliers or gathering trade credits faster. Similar to the first subsample, AR and INV showed a significantly negative relationship with firmsʼ operating performance. Therefore, during 2009‒2013, shortening CCC by 10 days could increase a firmʼs gross operational income by 0.36%.　　(Empirical results for other independent variables) Fixed financial assets (FFA) did not show any significant relationship for the main sample, though it did show a significantly negative relationship during the first and second subsample periods. This is consistent with the presumption that the more firms invested, the less profit they generated in the short-term. Another noteworthy finding is that the financial debt ratio (FD) showed a strong negative relationship for all sample periods. This is also an intuitive prediction, where firms having more external debt will generate less profit.　　Plain OLS regression model also showed similar results to the FE-LSDV model in terms of significant variables.

6. Conclusions

　　We found a strong relationship between net cash conversion cycle and profitability. Above all, we found that Japanese firms are more sensitive to proceeding inventories (INV), while inventory cycle showed a strong negative relationship with firmʼs profitability in all samples. Particularly, we also found that, in addition to handling inventories skillfully, distributing trade credits proficiently among buyers (AR) had important effects in generating better business outcomes. Both components together resulted in days of cash conversion cycle (CCC) to take a strongly negative relationship with profitability. Our findings in this research were fully consistent with the existing literature of this field. Therefore, we significantly confirmed all of our alternative hypotheses except for H1.3 where Japanese manufacturing firmsʼ policies in paying suppliers (AP) did not show any remarkable relationship with their profitability. Firms with more external debts (FD) also faced more difficulties in generating better gross net income. Our overall results suggest that managers, by arranging

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inventory proceeding knowledgeably and scheduling trade receivables knowledgably, taking fully into consideration other endogenous and exogenous factors, can generate more value for their shareholders.　　Moreover, we also discovered several new aspects of shocks about which our empirical findings disclosed interesting phenomena that have not been observed among prevailing researches in this field. For instance, one of our noteworthy findings explains that the 2008‒09 financial crisis hit Japanese core manufacturing industries to a degree at which profitability could not have been improved by managing payments to suppliers efficiently and taking receivables as early as possible. However, it confirmed that dealing with inventories properly had significant effects even during the 2008‒09 financial crisis, the worst economic hardship in modern Japanese history since WWII. Another finding suggested that since the days of accounting payables (AP) did not show any significance, it signaled the cash abundancy of Japanese manufacturing firms. This demonstrates an empirical confirmation of an intuitive presumption. 　　Moreover, we initially expected similar results from all samples since the data comes from the same economy and industries. Interestingly, main sample which contained the core financial crisis year, showed significantly different outcomes which can be interpreted as a crisis-effect. While, latter two samples disclosed intuitively expected results. Main sample results ruled out the effects of accounts receivables and payables as a result that of cash conversion cycle as a whole. However, because of similarities of findings through our first and second sub-samples which the former covered aftermath period of Great East Japan Earthquake and the latter excluded core-crisis year-2008 respectively, though not fully but fairly we can conclude that our findings from first sub-sample represents the pure effect of natural disaster from the hysteresis effect of the financial crisis at least in the firmsʼ working capital management.

References

Afza,T., and Nazir, M. S. (2007). Is it better to be Aggressive or Conservative in Managing Working Capital, Journal of Quality and Technology Management, 3 (2), 11‒21.

Afza, T., and Nazir, M. S. (2009). Impact of Aggressive Working Capital Management Policy on Firmʼs Profitability. The IUP Journal of Applied Finance, 15 (8), 19‒30.

Ali, A., and Ali, S. A. (2012). Working Capital Management: Is It Really Affects the profitability? Evidence from Pakistan. Global Journal of Management and Business Research, 12 (17), 74‒78.

Akinlo, O. O. (2011). The Effect of Working Capital on Profitability of Firms in Nigeria: Evidence from General Method of Moments (GMM). Asian Journal of Business and Management Sciences, 1 (2), 130‒135.

Ali, S. (2011). Working Capital Management and the Profitability of the Manufacturing Sector: A case study of Pakistanʼs Textile Industry. The Lahore Journal of Economics, 16 (2), 141‒178.

Alipour, M. (2011). Working Capital Management and Corporate Profitability: Evidence from Iran. World Applied Sciences Journal, 12 (7), 1093‒1099.

Bagchi, B., Chakrabarti, J., and Roy, P. B. (2012). Influence of Working Capital Management on Profitability: A Study on Indian FMCG Companies. International Journal of Business and Management, 7 (22), 1‒10.

Belt, B. (1979). Working Capital Policy and Liquidity in Small Business. Journal of Small Business Management, 17 (3), 43─51.

Bieniasz, A., and Golas, Z. (2011). The Influence of Working Capital Management on the Food Industry Enterprises Profitability. Journal of Contemporary Economics, 5 (4), 68‒81.

Deloof, M. (2003). Does Working Capital Management Affect Profitability of Belgian Firms. Journal of Business Finance and Accounting, 30 (3 and 4), 573‒587.

Eljelly, A. M. A. (2004). Liquidity-Profitability Tradeoff: An Empirical Investigation in an Emerging Market.

（235）


International Journal of Commerce and Management, 14 (2), 48‒61.Filbeck, G., and Krueger, M. T. (2005). An Analysis of Working Capital Management Results across Industries. Mid-

American Journal of Business, 20 (2), 11‒18.Gill. A., Biger, N., and Mathur, N., (2010). The Relationship between Working Capital Management and Profitability:

Evidence from the United States. Business and Economics Journal, 10, 1‒9.Gill, A. (2011). Factors that influence the Working Capital Requirements in Canada. Economics and Finance Review,

1 (3), 30‒40.Gitman, L. J. (2005). Principles of Managerial Finance (11th ed.). Pearson Education. USA.Hillier, D., Ross, S., Westerfield, R., Jaffe, J., and Jordan, B,. (2010). Corporate Finance: European Edition (1st ed.).

McGraw-Hill.Jose, M. L., Lancaster, C., and Stevens, J. L. (1996). Corporate Returns and Cash Conversion Cycle. Journal of

Economics and Finance, 20 (1), 33‒46.Kimura, T. and Shiota, S. (2008). Stabilized Business Cycles with Increased Output Volatility at High Frequencies.

Journal of the Japanese and International Economies, 23 (1) 1‒19.Lazaridis, D. I., and Tryfonidis, D. (2005). The relationship between Working Capital Management and Profitability

of listed companies in the Athens Stock Exchange. Journal of Financial Management and Analysis, 19 (1), 1‒12.Mathuva, D. M. (2010). Influence of Working Capital Management Components on Corporate Profitability: A Survey

on Kenyan Listed Firms. Research Journal of Business Management, 4 (1), 1‒11.Mia, L. (2000). Just-in-time manufacturing, management accounting systems and profitability. Accounting and

Business Research, 30 (2), 137‒151.Nakamura, M., Sakakibara, S., and Schroeder, R. (1998). Adoption of Just-in-Time Manufacturing Methods at U.S-

and Japanese-Owned Plants: Some Empirical Evidence. IEEE Transactions on Engineering Management, 45 (3), 230‒240.

Napompech, K., (2012). Effects of Working Capital Management on the Profitability of Thai Listed Firms. International Journal of Trade, Economics and Finance, 3 (3), 227‒232.

Nobanee, H., and Haddad, A. E. (2014). Working Capital Management and Corporate Profitability of Japanese Firms. The Empirical Economics Letters, 13 (1). Available at SSRN: http://ssrn.com/abstract=2385351

Nyamao, N. R., Patrick, O., Martin, L., Odondo, A. J., and Simeyo, O. (2012). Effect of Working Capital Management Practices on Financial Performance: A Study of Small Scale Enterprises in Kissi South District, Kenya. African Journal of Business Management, 6 (18), 5807‒5817.

Padachi, K. (2006). Trends in Working Capital Management and its Impact on Firmsʼ Performance: An Analysis of Mauritian Small Manufacturing Firms. International Review of Business Research Papers, 2 (2), 45‒58.

Raheman, A., and Afza,T. (2010). Working Capital Management and Corporate performance of Manufacturing Sector in Pakistan. International Research Journal of Finance and Economics, 47, 151‒163.

Samiloglu, F., and Dermigunes, K. (2008). The effect of Working Capital Management on Firm Profitability: Evidence from Turkey. The International Journal of Applied Economics and Finance, 2 (1), 44‒50.

Sharma, A. K., and Kumar, S. (2011). Effect of Working Capital Management on Firm Profitability: Empirical Evidence from India. Global Business Review, 12 (1), 159‒173.

Shin, H., and Soenen, L. (1998). “Efficiency of Working Capital and Corporate Profitability” , Financial Practice and Education, 8 (2), 37‒45.

Valipour, H., Moradi, J., and Farsi, F. D. (2012). The Impact of Company Characteristics on Working Capital Management. Journal of Applied Finance and Banking, 2 (1), 105‒125.

Vural, G. Sokmen, A. H., and Cetenak, E. H. (2012). Affects of Working Capital Management on Firmʼs Performance: Evidence from Turkey. International Journal of Economics and Financial Issues, 2 (4), 488‒495.

Wang, Y. J. (2002). Liquidity Management, Operating Performance, and Corporate Value: Evidence from Japan and Taiwan. Journal of Multinational Financial Management, 12, 159‒169.

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16

Current AssetsNet Working Capital

Current Liabilities

Figure 2. Cash Conversion Cycle

Source: www.strategy-at-risk.com

Table 3. Initial Descriptive Statistics for 2008–-2013 years Variable Obs Mean Std. Dev. Min Max

Figure 1　Net Working Capital

　Source: STRATEGY@Risk Ltd. (www.strategy-at-risk.com/2010/10/18/working -capital-strategy-2/)

Figure 2　Cash Conversion Cycle

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Table 3　Initial Descriptive Statistics for 2008‒2013 years

Variable Obs Mean Std. Dev. Min Max

AR 2687 94 41 0 460

INV 2687 90 61 0 532

AP 2687 69 36 0 516

CCC 2687 115 73 (332) 499

Fixed financial Assets 2687 0.10 0.07 0 0.77

Financial debt 2687 0.15 0.14 0 0.75

Sales growth 2662 (0.96) 24.37 (86.25) 326.90

Ln Sales 2687 10.59 1.59 4.19 16.08

Gross operating profit margin 2687 0.40 0.54 (0.26) 24.53

　　　　Source: Authorʼs calculation based on sample data

Table 4　Initial Descriptive Statistics for first subsample―2011‒2013 years

Variable Obs. Mean Std. Dev. Min Max

AR 1129 97 41 9 407

INV 1129 92 61 3 424

AP 1129 71 39 0 516

CCC 1129 117 73 (332) 439

Fixed financial Assets 1129 0.10 0.08 0.00 0.77

Financial debt 1129 0.14 0.14 - 0.72

Sales growth 1116 2.31 19.04 (73.23) 218.77

Ln Sales 1129 10.55 1.60 4.32 16.08



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Table 5　Initial Descriptive Statistics for second subsample―2009‒2013 years

Variable Obs Mean Std. Dev. Min Max

AR 2239 97 40 - 407

INV 2239 91 61 - 532

AP 2239 71 36 - 516

CCC 2239 116 74 (332) 499

Fixed financial Assets 2239 0.10 0.07 0.00 0.77

Financial debt 2239 0.15 0.14 - 0.75

Sales growth 2216 1.32 25.12 (86.25) 326.90

Ln Sales 2239 10.54 1.59 4.19 16.08



Table 6　 Pearson Correlation Table. 574 Manufacturing Japanese firms, 2008‒2013, six-year observations (Significance at 5% level also shown with*)　　　　　　　　　　　　　　　　　　　　

AR INV AP CCC FFA FD Sales gr. Ln Sales

INV 0.1057*

0

AP 0.4248* 0.1238*

0 0

CCC 0.4381* 0.8255* －0.1489*

0 0 0

Fixed fin. Assets0.0021 －0.0440* －0.0794* 0.0036

0.912 0.0225 0 0.854

Financial debt Ratio －0.0881* 0.0413* －0.0135 －0.0085 －0.1573*

0 0.0323 0.4854 0.6607 0

Sales Growth －0.0135 －0.0087 0.0980* －0.0627* －0.0235 －0.0446*

0.4852 0.6539 0 0.0012 0.2252 0.0214

Ln sales －0.2278* －0.1815* 0.0004 －0.2775* 0.0392* 0.0375 0.0469*

0 0 0.982 0 0.0419 0.0519 0.0154

Gross Operation Profit Margin0.0208 －0.0151 －0.0028 0.0005 －0.0674* －0.1047* 0.0757* －0.021

0.2809 0.4344 0.8853 0.9792 0.0005 0 0.0001 0.276

　Source: Authorʼs calculation based on sample data

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Table 7　Working capital management relationship with profitability Sample period―2008‒2013

1 2 3 4

VARIABLES Gross Operating profit margin

Gross Operating profit margin



AR 0.0047

－0.00458

INV －0.000466**

－0.00023

AP －0.000457

－0.000626

CCC 0.00219

－0.00243

Fixed ass. Ratio 0.598 0.0474 0.0441 0.293

－0.979 －0.468 －0.457 －0.728

Fin.debt Ratio －0.883* －0.880* －0.903* －0.994

－0.496 －0.507 －0.537 －0.625

Sales growth －0.000509 8.02E－05 0.000189 0.000343

－0.00107 －0.000495 －0.000393 －0.00027

Ln sales 0.518** 0.290*** 0.295*** 0.425**

－0.239 －0.0369 －0.0317 －0.166

Constant －5.466* －2.511*** －2.565*** －4.238**

－2.985 －0.364 －0.304 －2.011

Observations 2,662 2,662 2,662 2,662

R-squared 0.056 0.024 0.024 0.038

Number of company 609 609 609 609

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1


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Table 8　Working capital management relationship with profitability Sample period―2011‒2013

1 2 3 4

VARIABLES Gross Operating profit margin




AR －0.000421*

－0.000236

INV －0.000801**

－0.000312

AP －3.53E－05

－0.000282

CCC －0.000492***

－0.000142

Fixed ass. Ratio －0.522** －0.565 －0.472 －0.579*

－0.214 －0.345 －0.358 －0.351

Fin.debt Ratio －0.332*** －0.362*** －0.341*** －0.307**

－0.0949 －0.123 －0.123 －0.125

Sales growth 0.000557** 0.000437 0.000538 0.000497

－0.000234 －0.0004 －0.000449 －0.000403

Ln sales 0.286*** 0.257*** 0.304*** 0.272***

－0.0336 －0.0579 －0.0582 －0.0513

Constant －2.478*** －2.134*** －2.709*** －2.311***

－0.371 －0.623 －0.621 －0.547

Observations 1,116 1,116 1,116 1,116

R-squared 0.296 0.316 0.292 0.31



*** p<0.01, ** p<0.05, * p<0.1


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Table 9　Working capital management relationship with profitability with Fixed effects Sample period―2009‒2013

1 2 3 4

VARIABLES GROSS GROSS GROSS GROSS

AR －0.000416**

－0.000211

INV －0.000317*

－0.000169

AP 1.51E－06

－0.000199

CCC －0.000358***

－0.000125

Fixed ass. Ratio －0.437* －0.395 －0.39 －0.423*

－0.232 －0.245 －0.241 －0.237

Fin.debt Ratio －0.360*** －0.376*** －0.372*** －0.349***

－0.0724 －0.0733 －0.0737 －0.0713

Sales growth 0.000467*** 0.000438*** 0.000460*** 0.000422***

－0.000144 －0.000142 －0.000147 －0.000142

Ln sales 0.298*** 0.300*** 0.312*** 0.291***

－0.0308 －0.035 －0.0318 －0.0337

Constant －2.612*** －2.648*** －2.803*** －2.547***

－0.335 －0.385 －0.347 －0.367

Observations 2,216 2,216 2,216 2,216

R-squared 0.436 0.436 0.432 0.44



*** p<0.01, ** p<0.05, * p<0.1


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Table 10　Working capital management relationship with profitability with plain OLS Sample period―2008‒2013

1 2 3 4


AR 0.000301

－0.00121

INV －0.000164*

－9.00E－05

AP －3.04E－05

－0.000167

CCC －1.24E－05

－0.000396

Fixed assets Ratio －0.589*** －0.599*** －0.594*** －0.592***

－0.112 －0.101 －0.103 －0.101

Fin.debt Ratio －0.440*** －0.444*** －0.446*** －0.446***

－0.0329 －0.0377 －0.0374 －0.0373

Sales growth 0.00177*** 0.00174*** 0.00175*** 0.00174***

－0.000323 －0.000319 －0.000326 －0.000322

Ln sales －0.000986 －0.00262 －0.00204 －0.00219

－0.00602 －0.00354 －0.00346 －0.00514

Industry dummies Estimated Estimated Estimated Estimated

Time dummies Estimated Estimated Estimated Estimated

Constant 0.619*** 0.675*** 0.657*** 0.658***

－0.123 －0.0554 －0.0556 －0.0622

Observations 2,662 2,662 2,662 2,662

R-squared 0.037 0.037 0.037 0.037


*** p<0.01, ** p<0.05, * p<0.1


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1 2 3 4


AR －0.000951***

－0.00021

INV －3.99E－05

－0.00016

AP －1.44E－05

－0.000246

CCC －0.000335***

－0.000128


－0.112 －0.113 －0.115 －0.113

Fin.debt Ratio －0.456*** －0.430*** －0.431*** －0.431***

－0.0528 －0.0507 －0.0512 －0.0512

Sales growth 0.00194*** 0.00209*** 0.00210*** 0.00201***

－0.00059 －0.000619 －0.000619 －0.000598

Ln sales －0.0104* －0.00729 －0.00718 －0.00955

－0.00578 －0.0057 －0.00565 －0.00583



Constant 0.810*** 0.685*** 0.681*** 0.744***

－0.0812 －0.0736 －0.0735 －0.0772

Observations 1,116 1,116 1,116 1,116

R-squared 0.169 0.152 0.152 0.159


*** p<0.01, ** p<0.05, * p<0.1


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1 2 3 4


AR －0.00105***

－0.000155

INV －0.000224**

－9.54E－05

AP －0.000176

－0.000173

CCC －0.000432***

－8.23E－05


－0.075 －0.0754 －0.0765 －0.0744

Fin.debt Ratio －0.446*** －0.423*** －0.428*** －0.425***

－0.036 －0.0352 －0.0355 －0.0352

Sales growth 0.00139*** 0.00152*** 0.00153*** 0.00146***

－0.000308 －0.000311 －0.000317 －0.000304

Ln sales －0.00749* －0.00436 －0.00335 －0.00731*

－0.00397 －0.00392 －0.00384 －0.00399



Constant 0.760*** 0.641*** 0.623*** 0.702***

－0.0568 －0.0513 －0.0517 －0.0534

Observations 2,216 2,216 2,216 2,216

R-squared 0.184 0.166 0.164 0.175


*** p<0.01, ** p<0.05, * p<0.1


［アシュラフベック　オリモヴ　横浜国立大学大学院国際社会科学研究科博士課程後期］　

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effects of liquidity management on operating performance of manufacturing firms evidence from japan

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