Drivers and outcomes of supply chain finance adoption: An empirical investigation in China

Journal Pre-proof Drivers and Outcomes of Supply Chain Finance Adoption: An Empirical Investigation in China

Zhiqiang Wang, Qiang Wang, Yin Lai, Chaojie Liang PII:

S0925-5273(19)30263-4

DOI:

https://doi.org/10.1016/j.ijpe.2019.07.026

Reference:

PROECO 7453

To appear in:

International Journal of Production Economics

Received Date:

30 October 2018

Accepted Date:

24 July 2019

Please cite this article as: Zhiqiang Wang, Qiang Wang, Yin Lai, Chaojie Liang, Drivers and Outcomes of Supply Chain Finance Adoption: An Empirical Investigation in China, International Journal of Production Economics (2019), https://doi.org/10.1016/j.ijpe.2019.07.026

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Journal Pre-proof

Drivers and Outcomes of Supply Chain Finance Adoption: An Empirical Investigation in China

Zhiqiang Wang School of Business Administration, South China University of Technology, Guangzhou, China Email: [email protected] Qiang Wang* School of Management, Xi’an Jiaotong University, Xi’an, China Email: [email protected] Yin Lai School of Management, Xi’an Jiaotong University, Xi’an, China Email: [email protected] Chaojie Liang Ping An Bank, Shenzhen, China Email: [email protected]

*Corresponding Author

Acknowledgements The work described in this paper was substantially supported by the National Natural Science Foundation of China (grant numbers 71602159, 71473087, 71420107024).

Journal Pre-proof Drivers and outcomes of supply chain finance adoption: an empirical investigation in China

ABSTRACT This study develops a supply chain finance adoption model to investigate the key drivers and corresponding outcomes of supply chain finance adoption decisions. We examine the impacts of perceived capital pressure, order fulfillment cycle, and inventory turnover cycle on three types of supply chain finance adoption (accounts receivable finance, inventory finance, accounts payable finance). In addition, we examine the impacts of three types supply chain finance adoption on the performance of supply chain cost reduction. We use data collected from 683 companies of eight industries in China to test our proposed relationships. The results show that perceived capital pressure and order fulfillment cycle are significant predictors of supply chain finance adoption decisions. Accounts receivable finance and inventory finance significantly influence supply chain cost reduction. This study is one of the first attempts to conduct large sample empirical investigation in supply chain finance research. Our findings enhance the understanding of supply chain finance adoption for both academics and practitioners.

Keywords: Supply chain finance; Accounts receivable finance; Accounts payable finance; Inventory finance; Supply chain cost; Empirical research

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Journal Pre-proof 1. Introduction In recent economic downturn, firms who rely heavily on bank loans or corporate borrowing have been under great liquidity pressures (Benmelech et al., 2017; DeYoung et al., 2015; Lee et al., 2015). Supply chain finance (SCF) is an alternative and preferred finance solution that can benefit supply chain partners by solving financial pressures with lower interest rates, extended payment terms, and more working capitals (Wuttke et al., 2016). SCF is a new trend to optimize financial flows along with the flows of goods and information in supply chain management (SCM) (Gelsomino et al., 2016). Although SCM scholars and practitioners suggest the collaboration and coordination among supply chain partners in goods, information, and finance flows (Mentzer et al., 2001), the theories and practices of finance flow management in SCM lag behind comparing with goods and information flow management (Hofmann, 2005). The goods flow along supply chain may be interrupted if the financial flow is not properly managed along the supply chain (Wuttke et al., 2013b). For example, companies cannot maintain a sustainable level of supply if they only reduce cash-to-cash cycles by setting long payment terms for suppliers. Such simple extension of payment terms will lead to high risk for suppliers with less short-term financing (Hofmann and Kotzab, 2010). Thus, the boom of SCF in industries reflects the needs to ease the financial tensions between supply chain partners. In practice, different financial solutions are implemented to resolve the financial flow management in supply chain such as factoring, reverse factoring, inventory financing, and vendor-managed inventory (Caniato et al., 2016; Hofmann and Kotzab, 2010; Lekkakos and Serrano, 2016). 2

Journal Pre-proof Supply chain finance research attracts academics from both supply chain and finance disciplines. Gelsomino et al. (2016) categorized these studies as “supply chain oriented” and “finance oriented” literature. The finance oriented perspective focuses on accounts payable and receivable, which are usually short-term solutions provided by financial institutions; the supply chain oriented perspective extends this focus to include inventories as well, and it may not involve a financial institution. Lam et al. (2019) further suggested that the finance oriented perspective “is associated with financial elements and considers the SCF strategy as a set of financial tools, frequently offered by financial institutions”, while the supply chain oriented perspective “relates to the business and financing process that connects the various supply chain participants in a transaction – the suppliers, buyers and financial service providers – to optimize working capital and lower financing costs” (p. 228). We adopt the supply chain oriented perspective in this study and SCF is defined as an approach for consecutive supply chain partners to jointly optimize working capital in terms of accounts payable, accounts receivable, and inventories. Although plenty of studies have been conducted in understanding SCF, two research gaps still exist. First, most of the prior studies focus on different specific solutions of SCF (Caniato et al., 2016). There is lack of holistic framework and general understanding of the SCF adoptions (Gelsomino et al., 2016; Martin and Hofmann, 2018). Other than specific solution-based SCF research, a comprehensive adoption model of SCF solutions originated from the fundamental features of supply chain is needed to facilitate the theoretical development and practical implementation of SCF from a supply chain oriented perspective. Three kinds of collaterals exist in the supply chain 3

Journal Pre-proof transactions such as accounts payable, accounts receivable, and inventories. The financial arrangements of the three collaterals represent the main types of SCF solutions excluding fixed assets financing (Chakuu et al., 2019). Second, most of the findings are based on analytical models (Wuttke et al., 2016) or case evidences (Moretto et al., 2018; Wuttke et al., 2013b). Very few attempts have been conducted to analyze the adoptions of SCF based on large sample empirical investigation (Gelsomino et al., 2016; Wuttke et al., 2013b). A recent literature review on SCF also calls for more empirical studies on the drivers and outcomes of SCF applications (Xu et al., 2018). Zhang et al. (2019) showed that there are clear differences on effectiveness of SCF for different industries. The potential benefits of SCF adoptions need empirical verification and it is interesting to investigate the role of SCF across multiple industries (Zhang et al., 2019). To fulfill the gaps in the literature, we build a holistic framework including the accounts payable finance, accounts receivable finance, and inventory finance adoption decisions. The three types of supply chain finance solutions are classified according to the main types of collaterals in supply chain transactions. We consider both the drivers and outcomes of these three types of SCF adoption decisions in our model. We use the data collected from 683 companies in China and test the hypothesized relationships between proposed drivers and impacts. Our findings contribute to the SCF literature in the following ways. First, we conduct an empirical investigation to answer a fundamental research question: What are the drivers of a company adopting a certain type of SCF solutions? Our results can provide concrete evidence to clarify how different drivers simultaneously influence one of the three types of SCF adoption decisions and how these 4

Journal Pre-proof SCF adoption decisions influence supply chain performance. Second, our findings could contribute to SCF literature by connecting operational drivers and financial decisions with empirical evidences in multiple industries. Our findings also complement current SCF literature by providing empirical evidence for SCF adoptions in China. 2. Literature Review

2.1 SCF SCF has long been known as a significant intersection of trade finance and SCM fields. Enabled by technological advancements such as digitalization in recent years, there is a movement of converting the integrative initiatives of materials and information flows into deliverable benefits in terms of better financial flows for related players along the supply chain (Hofmann and Belin, 2011). Therefore, providing finance to trade along the supply chain is becoming a fundamental business of banks, creating real value to both the suppliers and buyers who not only need timely manufacturing and delivery of goods, but also need well-structured SCF solutions to free up more cash at a reasonable financial cost. SCF research can be traced back to 1970s, when Budin and Eapen (1970) and Haley and Higgins (1973) published their articles on the trade credit and inventory policy. The discussion over goods and information flows has dominated the prior SCM literature (Lee et al., 2000), while issues regarding financial flows in supply chains have become the new trend of research focus (Basu and Nair, 2012; More and Basu, 2013). Moreover, SCF has been found to reduce operational costs and create profit for upstream/downstream players in the supply chain (e.g., Brick and Fung, 1984; Dye and Yang, 2015; Gong et al., 2018), improve firms’ financial performance (e.g., Caniato et 5

Journal Pre-proof al., 2016), and promote supply chain sustainability. We have summarized related research into different research topics in Table 1 based on three themes—tools/solutions, adoptions and outcomes. The summary identifies the commonly used SCF solutions/tools (traditional and emerging) and the factors that affect the adoption of such solutions. It also illustrates the benefits of SCF adoption. Earlier studies of SCF focused on mathematical modeling method to figure out optimal inventory decisions, mostly based on EPQ/EOQ model (Huang, 2007; Huang and Hsu, 2008); then research focusing on various SCF solutions/tools emerged. Table 1 also shows that the current understanding on drivers of SCF adoption is limited and fragmented. To understand the drivers that companies adopt different SCF solutions is an important issue for both SCF providers and adopters. --- Insert Table 1 about Here --2.2 Types of SCF solutions Previous studies have examined different SCF solutions and their effects on supply chain performance and decisions. Among these solutions, trade credit, factoring, and reverse factoring are the most commonly used solutions (Abad and Jaggi, 2003; Guariglia and Mateut, 2006). For trade credit, the majority of early practices establish the optimal decisions models based on cost reduction purpose of SCF (e.g., Huang, 2007; Huang and Hsu, 2008; Liao, 2008). Ferris (1981) developed a transactions theory of trade credit to optimize the timing of cash flow and decrease the joint costs of exchange raised from trading uncertainty. In general, focal firm can accelerate cash flow and decrease operational cost 6

Journal Pre-proof by increasing the payment delay to upstream partner or tightening credit period offered to downstream customer (Dye and Yang, 2015; Protopappa-Sieke and Seifert, 2010). Furthermore, the trade credit can be applied to increase the revenue of upstream/downstream partners and affect the whole chain. Zhou et al. (2012) proposed a model to illustrate that offering trade credit can increase the profitability of the overall chain and each member, but only when the interest charge of suppliers is smaller than that of retailers at a certain threshold. Further research investigated trade credit more specifically and classified it into account receivables and payables. Bougheas et al. (2009) recognized that trade credit offered/received by a firm (i.e., account receivable and payable) is positively related to firm’s profitability level. Long et al. (1993) found that smaller suppliers with longer production lead time and quality evaluation time rely more on extended trade credit. The literature explained other positive effects of trade credit such as mitigating informational asymmetries (Biais and Gollier, 1997; Smith, 1987) and reducing tax burden (Brick and Fung, 1984; Hsu and Zhu, 2011). However, cash strapped firms in a lack of fixed assets as collateral cannot always get support from conservative financial institutions and banks (Soufani, 2002). With such constraints, factoring is a better and easier-accessed type of debtor finance to improve the working capital and cash-flow positions compared to payment delay strategy. Factoring enables a firm to sell its account receivable to a third party to receive immediate cash; then the customer becomes the debtor and need to pay the third party directly. Summers and Wilson (2000) found evidence that a demand for asset-based finance from small companies is the main incentive to use factoring, while firm-level 7

Journal Pre-proof organizational structure is not a significant determinant. Soufani (2002) evaluated the type of businesses using factoring as a financing source in UK. It has been found that the main users of factoring are smaller, younger and limited companies that may experience financial difficulties with high value of collateral and loan. Klapper (2006) viewed factoring as a risk-transferring channel, which allows suppliers’ high credit risk transfers to high-quality customers especially in weak credit availability and inefficient bankruptcy enforcement environment. Reverse factoring is an alternative factoring mechanism for downstream customers who cooperate with banks to offer loans to upstream suppliers. The mechanism of reverse factoring is similar with that of factoring. Seifert and Seifert (2011) found that many customers can reduce the net working capital through reserve factoring. Compared with customers’ advanced payment strategy, reverse factoring can better promote supply chain sustainability and efficiency. The higher the production cost, the higher the significance of reverse factoring influences supply chain sustainability (Zhan et al., 2018). Van der Vliet et al. (2015) explored the costs and benefits of reverse factoring when customers provide reverse factoring to upstream suppliers in return of payment term extension. The model shows that creditworthy buyers with strong bargaining power may favor the use of reverse factoring. The firm’s payment term extension cost will decrease with lower demand uncertainty, higher net profit margin and operating leverage. 2.3 A classification from the supply chain oriented perspective The studies summarized in prior section have analyzed various specialized SCF solutions (e.g. trade credit, factoring, and reverse factoring), several factors related to the adoption 8

Journal Pre-proof of these SCF solutions, and the outcomes of SCF adoption. Apart from the specificsolution-based research, our study attempts to provide a holistic analysis of the SCF adoption. Based on the supply chain oriented perspective, three types of SCF solutions are included as those synthesized in a systematic literature review (Chakuu et al., 2019), which considers the nature of supply chain components and the general adoption level of different types of SCF solutions. The flow of financial resources in supply chain adds value to firms through inventory management, process management and cash management (Pfohl and Gomm, 2009). In accord with Gelsomino et al. (2016) and Lam et al. (2019), we delimit accounts receivable finance, inventory finance, and accounts payable finance as three main types of SCF adoption. It is noteworthy that any specified solutions, if they are suitable, could be categorized into these three types. Prior studies focus on accounts receivable financing using receivables as the underlying collaterals for financing (Basu and Nair 2012; Silvestro and Lustrato 2014). For example, factoring also belongs to accounts receivable finance although some researchers regard factoring as an independent SCF mode (Martin and Hofmann 2017; Tang et al. 2018). Besides, account payable financing may also help the supply chain players avail funding. The common solutions include but are not limited to payables extension finance and approved payables financing (Marak and Pillai, 2019). Unlike accounts receivable and payable (such as factoring and reverse factoring) which require the understanding of the business between the focal firms and their suppliers or customers, inventory-based finance does not necessarily involve the focal firm because inventory-based finance can operate independently and need information 9

Journal Pre-proof of the focal firm. Therefore, sometimes this type of solution is more like traditional finance than supply chain finance mechanism. However, inventory-based finance can be used to connect account payable and receivable using inventory as an underlying asset (Li et al. 2011; Chen and Kieschnick 2018; Tang et al. 2018), enabling financial institutions and banks to extend their businesses into SCF. Therefore, we consider inventory-based finance as the third type of SCF solutions. 2.4 Divers of SCF adoption While the different types of SCF solutions have been well defined, it is worth noting that the drivers of a company adopting a certain type of SCF solutions remain unclear, and existing empirical studies are insufficient. Caniato et al. (2016) identified that the main objectives driving the SCF adoption are improving the adopter’s financial performance and securing the upstream/downstream supply chain’s financial performance. Marak and Pillai (2019) further summarized that the influential factors include operational factors, financial factors, relationship factors, technological factors, and informational factors. In this study, we see the drivers of SCF adoption in a more generalizable and applicable approach. The key feature of finance upon supply chain can be depicted by cash-to-cash cycle, which is calculated as the average turnover period plus period of receivables and then minus period of payables (Pfohl and Gomm, 2009). This cycle captures the period of time needed to transform the cash paying to suppliers into the cash gaining from customers through inventory processing. Capital pressure, order fulfillment cycle, and inventory turnover cycle are closely related to the cash-to-cash cycle. As such, we include them into our conceptual model as the main drivers of SCF adoption. This is also in line 10

Journal Pre-proof with our interviews with SCF practitioners in China and supported by our data from SCF adopters in this study. 3. SCF Adoption Model We define supply chain cost reduction as outcome of SCF adoption, and further examine the interactions between SCF drivers and types of SCF as well as their corresponding influences upon SCF outcomes. The proposed SCF adoption model is shown in Figure 1. --- Insert Figure 1 about Here --3.1 Drivers of SCF adoption 3.1.1 Perceived capital pressure As one of the main drivers in our SCF adoption model, perceived capital pressure is defined as the degree to which the cash of fund is perceived as strain by a company in the industry that it operates. Companies with high perceived capital pressure face high liquidity risk of working capital, motivating the companies to hold more cash and reduce the financial risk (Bates et al., 2009). Previous studies have suggested the potential relationship between perceived capital pressure and SCF adoption. For example, Wuttke et al. (2013b) proposed that weak working capital position in supply chain is closely related to the use of SCF solutions for reducing perceived liquidity risk. The perceived working capital pressure can be raised by practices such as payment terms extensions, expediting receivables collections, or uncontrolled inventory management (Pohlen and Goldsby, 2003). As financial solutions in different supply chain positions, accounts

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Journal Pre-proof receivable finance, inventory finance, and accounts payable finance can mitigate the liquidity risks of different supply chain partners. The need of liquidity in the supply chain operations facilitates the use of SCF solutions because they involve relatively lower financial cost compared with other types of financial solutions (Gelsomino et al., 2016). Moreover, the capital pressure can come from the powerful suppliers or customers. For example, the customers in a leading position of the supply chain may try to extend their payment schedule. From the focal firm’s perspective, the extended payment schedule leads to tensions in terms of working capital. As such, a flexible treatment of their accounts receivable will be an appropriate choice. To deal with the working capital stress, accounts receivable, accounts payable, and inventories can be flexibly pledged to the third parties. Although other solutions may also exist for companies, the three types of SCF solutions with relatively low cost are more likely to be used to ease the working capital pressure. Therefore, we propose that: H1a/b/c: The higher perceived capital pressure is, the higher possibility that companies would adopt SCF in terms of accounts receivable finance/inventory finance/accounts payable finance. 3.1.2 Order fulfillment cycle Order fulfillment cycle refers to the duration of time between the initial product requested and the product delivered (Hult et al., 2002). Order fulfillment cycle is an indicator that measures supply chain processes from customers’ perspective, and reflects the pressure from customer for goods delivery. A company is more responsive to customers if the order fulfillment cycle is short, while a company needs more time for cash-to-cash cycle 12

Journal Pre-proof with a long order fulfillment cycle. Thus, using financial solutions is appropriate in this situation. Moreover, during the period of order fulfillment cycle, companies have to manage the supply chain processes from material purchasing to product delivery. At the same time, the financial issues should be managed appropriately along the flow of goods. For example, companies should make decisions on the payment terms when they plan for the order fulfillment (Croxton, 2003). The financial cost would be high if the payment terms are inappropriate for the companies. The increased financial cost will induce companies to adopt SCF solutions to reduce capital cost (Gelsomino et al., 2016; Randall and Theodore Farris, 2009). More importantly, the long order fulfillment cycle also indicates high risk in supply. Uncertainty is a critical issue inherent in supply chain transactions. Longer order fulfillment cycle indicates higher potential risks. The lack of information transparency leads to the needs for SCF solutions, which are important optimization tools in reducing investment risks and capital costs systematically. Existing literature shows that SCF could deal with the high risk in supply by optimizing the purchasing and inventory decisions with supply chain partners (Valentini and Zavanella, 2003; Waller et al., 1999). Therefore, supply chain finance is a viable method to resolve the risks generated by a long order fulfillment cycle. Thus, we argue that: H2a/b/c: The possibility of companies to adopt SCF in terms of accounts receivable finance/inventory finance/accounts payable finance is positively related to order fulfillment cycle. 3.1.3 Inventory turnover cycle As an internal element to determine the SCF adoption, inventory turnover cycle refers to 13

Journal Pre-proof the total time from inventory acquisition to the use and sales of inventory. The liquidity of a company deteriorates with long inventory turnover cycle because of the low working capital efficiency (Gaur et al., 2005). In order to increase the liquidity, companies with long inventory turnover cycle intend to borrow money from outside, which hinders the financial performance improvement of the focal companies (Randall and Theodore Farris, 2009). In this situation, SCF could be a possible solution in resolving capital needs. A longer inventory turnover cycle increases the tensions in companies’ working capital, and lower efficiency of working capital associates with higher level of inventories. The proper management of cash-to-cash cycle related inventory, receivable and payable terms will help reduce the inventory carrying cost (Randall and Theodore Farris, 2009). In contrast, the fast inventory turnover cycle inhibits companies’ intention to reduce inventory carrying cost by adopting SCF. Higher efficiency of working capitals indicates smooth supply chain operations in coordinating finance and goods flows. Thus, we propose that: H3a/b/c: The longer inventory turnover cycle is, the higher possibility that companies would adopt SCF in terms of receivable finance/inventory finance/payable finance. 3.2 Benefits of SCF adoption Plenty of studies argue for the benefits of SCF adoption (e.g., Caniato et al., 2016; Pellegrino et al., 2018; Wuttke et al., 2013b). It requires collaborations among supply chain partners in managing financial issues such as cash-to-cash cycles and average cost of capital (Randall and Theodore Farris, 2009). The main purpose of SCF is to reduce 14

Journal Pre-proof the total supply chain cost, especially the capital cost. Companies can obtain cost reduction advantage in following aspects. First, companies can lower inventory cost through SCF solutions. For example, the vendor-managed inventory method reduces the inventory holding and managing cost of the focal firms (Dong and Xu, 2002; Waller et al., 1999). The improved accuracy can further decrease the inventory holding (Dong et al., 2007; Sari, 2007). Moreover, SCF applications can mitigate the stockout issues due to the secure of supply chain (Valentini and Zavanella, 2003). Second, companies can lower the capital cost by adopting SCF solutions. The cash-to-cash cycle is determined by the arrangements of inventory, account receivables, and account payables (Randall and Theodore Farris, 2009). Therefore, the capital cost can be greatly minimized if the cash-to-cash cycle decreases to zero or negative through SCF applications (Theodore Farris and Hutchison, 2002; Wuttke et al., 2013a). Moreover, suppliers often have limited access to financing opportunities and suffer from high financing interest cost, leading to the potential high cost of final products delivered to customers. By adopting SCF, the supply chain partners can collaborate to optimize the cash flow, share the financial risk and lower financing interest cost along the whole supply chain (Berger and Udell, 2006; Klapper, 2006). This collaboration model enables managers to reduce supply chain total cost and create values to final customers. Last, companies can reduce operational cost through SCF adoption by minimizing the suppliers’ cash flow risk, supply chain disruption risk, and transaction costs (Wuttke et al., 2013a). SCF also uses information visibility as a governance mechanism to secure 15

Journal Pre-proof the supply chain coordination and control the potential opportunism in financial management, which also helps to reduce other hidden costs. Therefore, we propose that: H4a/b/c: The adoption of SCF in terms of receivable finance/inventory finance/payable finance enhances supply chain cost reduction performance. 4. Research Methodology 4.1 Data collection We obtain our data from China Supply Chain Management (Supply Chain Finance) survey, a national wide survey jointly conducted a leading commercial bank in SCF business and a professional survey company, with the help from other organizations include supply chain and logistics institutes, other commercial banks, and medias in business and logistics. The bank was the first one to start SCF in China, and is seen as the most successful one in SCF business and understands the market quite well. The target sample companies are the potential SCF adopters from eight selected industries in mainland China. They randomly selected around 2000 companies (many of them already had connections with the bank) to send questionnaires, and out of 821 questionnaires returned in total, 683 are completed in terms of the variables covered in this research. The questionnaires were designed to collect different information from the top management in organizations such as CEO, as well as department managers in charge of accounting, supply chain, information technology, marketing and sales. Table 2 shows the sample distributions based on the companies’ characteristics in terms of industry type, annual sales, and ownership. --- Insert Table 2 about Here --16

Journal Pre-proof 4.2 Measures There are three independent variables in our model. We measure perceived capital pressure by a five-points scale describing the capital tensions that are perceived by a company in the industry that it operates (1= very high capital tensions, 5= very sufficient of capital). Order fulfillment cycle is measured by a five-point scales describing the days needed for completing the orders (1= less than 7 days, 5 = more than 120 days), and inventory turnover cycle is measured by a five-point scales describing the days of inventory turnover (1= within 30 days, 5 = more than 1 year), both based on the understanding of the real practices in China. Next, we define account receivable finance, account payable finance and inventory finance as three dummy variables (1 for having adopted the certain SCF and 0 for having not adopted) in our SCF adoption model. We focus on supply chain cost reduction by a four-points scale, indicating the significance of SCF adoption in reducing cost (1 = significant overall cost reduction in all parts of supply chain, 4 = no obvious overall cost reduction in all parts of supply chain). To control for various firm and industry characteristics that may affect SCF adoption, the regressions include annual sales, total assets, industry, and ownership as control variables. We also control the factor influencing the cash flow of the company using loan demand. 5. Data Analysis and Findings In order to determine which SCF solution is adopted by companies, the respondents were asked to answer whether they have adopted receivable finance, inventory finance, and 17

Journal Pre-proof payable finance. We calculate the percentage of SCF adoptions for all three types of SCF in Table 3. The results show that the three types of SCF have an around 30% adoption level. It shows that SCF is still not widely adopted by companies in China compared with other supply chain practices, indicating a great growing potential for SCF adoption in the future of SCM. --- Insert Table 3 about Here --To analyze the key drivers of SCF adoption, we use logistic regression analysis to test the impact of drivers on the SCF adoption decisions. In logistic regression analysis, the dependent variable is dichotomous and independent variables are continuous or categorical. We use dummy variable to describe categorical date (industry and ownership). Table 4 shows the results of three logistic regressions for three SCF adoption variables. The goodness-of-fit Chi-square values are 96.349, 78.158, and 78.009 for accounts receivable finance adoption, inventory finance adoption, and accounts payable finance adoption, respectively. The test results show that all three models are significant, and companies in some industries are more likely to adopt SCF. The logistic regression results show that three drivers have different impacts on the adoption of each type of SCF solutions. In Model 1, perceived capital pressure marginally and negatively influences accounts receivable finance adoption. Order fulfillment cycle has a positive impact on accounts receivable finance adoption, while there is no significant impact of inventory turnover cycle on accounts receivable finance adoption. Therefore, the results support H1a and H1b, but not H1c. For inventory finance adoption, the coefficients of perceived capital pressure and order fulfillment cycle are negatively 18

Journal Pre-proof and positively significant, respectively, showing that H2a and H2b are supported while H2c is not. The results of Model 3 show that only order fulfillment cycle is positively related to accounts payable finance adoption. Therefore, our findings only support H3b. --- Insert Table 4 about Here --We further conduct robust test for the three models. It is suggested that shorten receivable collection and extend payable settlement times might negatively affect the values from SCF adoption (Hofmann and Kotzab, 2010). We introduce more control variables such as accounts receivable time and amount, accounts payable time and amount into our model. Most of the results are consistent with those in Table 4. Only perceived capital pressure has more significant impact on receivable finance adoption. Such test secures the robustness of our findings. We also test the impacts of three SCF adoptions on supply chain cost reduction using linear regression model in Table 5. The results show that both accounts receivable finance adoption and inventory finance adoption have significant impacts on supply chain cost reduction, while accounts payable finance adoption does not. Therefore, H4a and H4b are supported and H4c is not supported. --- Insert Table 5 about Here --6. Discussions In this study, we examine the impacts of three drivers (perceived capital pressure, order fulfillment cycle, and inventory turnover cycle) on three types of SCF adoptions (account receivable finance, inventory finance, and account payable finance) and the impacts of these SCF adoptions on supply chain cost reduction. Our findings and significance are 19

Journal Pre-proof discussed as follows. First, our results show that perceived capital pressure is an important driver of SCF adoption. Although the effect of perceived capital pressure on accounts payable finance adoption is not significant, the sign of coefficient is the same as the other two significant results. Thus, it verifies the case evidences in Caniato et al. (2016) that one of the objectives for SCF adopters is to resolve their financial issues. The results suggest that managers are more likely to adopt accounts receivable finance and inventory finance if they feel pressures from insufficient working capital. This finding is consistent with the general arguments in prior literature that financial pressure is the key enabler of SCF decisions (Wuttke et al., 2013b). However, our empirical evidence shows that accounts payable finance may not be in accordance with this prediction. It seems that downstream SCF solutions are more appropriate to mitigate the capital tensions. For the accounts payable in upstream SCF solutions, companies may be more likely to use other financial terms. As suggested by one of the managers we interviewed, they would like to use the extended payment term when they have late payment from their customers. Existing studies also suggested that the buyers prefer supplier financing to bank financing under trade credit (Jing et al., 2012). Second, we identify consistent results regarding the impacts of order fulfillment cycle on all three types of SCF solutions. Companies with long order processing time have potential working capital issues and face supply chain risks, which are proved by our findings as key determinants of SCF (Pellegrino et al., 2018; Wuttke et al., 2013b). As suggested by Caniato et al. (2016), one purpose of SCF adoption is to secure the 20

Journal Pre-proof supply chain. Our findings demonstrate that the possibility of SCF adoption increases with longer order fulfillment cycles. The long order fulfillment cycle indicates a long cash-to-cash cycle, and it has been confirmed that SCF solutions benefit the supply chain by shortening cash-to-cash cycle (Randall and Theodore Farris, 2009). Third, our findings show that inventory turnover cycle is not significantly related to all SCF adoption decisions. This finding is counterintuitive and not consistent with our predictions. Although inventory turnover cycle is an internal operational indicator, it seems that companies do not connect this indictor with SCF adoption decisions. This may explain the insufficient use of SCF solutions (Gelsomino et al., 2016). A latest research conducted by Zhang et al. (2019) showed that SCF is not effective on inventory management efficiency. The main role of SCF is to stabilize the supply chain to reduce the risk of bankruptcy. There are still unclear and complex relationships between inventory holding of focal firms and financial liquidity of the supply chain (Zhang et al., 2019). Last, it is interesting to find that accounts receivable finance and inventory finance contribute greatly to supply chain cost reduction. This is consistent with the finding that resolving the liquidity issue along the supply chain may improve the focal firm’s operating efficiency (Zhang et al., 2019). However, accounts payable finance only explains the improvement of supply chain cost reduction at a minimal level among the three SCF solutions. The results indicate that the other two SCF solutions play more important roles in supply chain performance improvement than accounts payable finance does. This finding partially corroborates our conjecture that other financial terms may be 21

Journal Pre-proof superior to upstream SCF solutions. The purpose of accounts payable finance may be not related to the supply chain efficiency but the risk mitigation in the supply chain. Van der Vliet et al. (2015) found that the benefits of accounts payable finance will decrease with higher demand uncertainties. Zhan et al. (2018) also suggested that the role of accounts payable finance is contingent on the production cost. 7. Conclusions and Implications There is no doubt that SCF is a promising solution for companies in recent economic downturn and financial crisis. It is imperative for managers to understand the benefits of adopting SCF and make rational SCF decisions. In this study, we propose a SCF adoption model to investigate the three drivers of SCF adoption decisions and the performance implications of these adoptions. Our empirical results provide insights to both academics and practitioners. 7.1 Theoretical and managerial implications This study has three theoretical contributions. First, this study has developed a general SCF adoption model that helps to guide empirical research investigating drivers and outcomes of SCF decisions. Based on different components of SCM, we simplify the different SCF methods into three general practices and test the impacts of three potential drivers for decision-making. This approach is theoretically straightforward coupled with practical relevance in that the approach broadens the niche of SCF adoption research. The SCF adoption model is impervious to current and future SCF solutions if they can fit into accounts receivable, accounts payable and inventory finance categories. Second, our study is one of the first attempts to provide large sample empirical 22

Journal Pre-proof investigation of SCF adoption in emerging economies. We not only describe the current status of three types of SCF adoptions in China, but also verify the drivers and outcomes of SCF adoption. We fill the research gap suggested by Xu et al. (2018) that empiricalbased holistic analysis on SCF implementation is needed, and we address this issue by conducting statistical analyses based on solid data to balance the overemphasis on conceptual and mathematical modeling work in this research field. Last, this study contributes to the financial SCM literature. Combining the operational factors in supply chain with SCF decisions, we enrich the understanding of the interfaces between SCM and financial management. Our empirical investigation complements analytical research on the relationships between operational decisions and financial decisions (Protopappa-Sieke and Seifert, 2010). The findings further substantiate that the adoption of SCF is influenced by key features of a supply chain. This study also has some implications for managers. The findings can be applied to assist the decision-making process in coordinating goods, capital, and information along the supply chain. Finance managers should closely work with supply chain managers to reduce supply chain cost by emphasizing on the integrated management of financial flows along supply chains. Our findings imply that the insufficiency of capital and the longer order fulfilling time can stimulate managers to make SCF adoption decisions. On the other hand, the internal efficiency factor such as inventory turnover cycle does not show direct effect on managers’ decisions in SCF. Therefore, managers should be careful in SCF decisions if they consider inventory operation factors in financial decisions. Moreover, our findings suggest to managers that there is significant supply chain cost 23

Journal Pre-proof reduction for receivable finance and inventory finance adoptions, but not for account payable finance adoptions. Therefore, managers may focus on the roles of accounts receivable finance and inventory finance for cost-saving purpose. 7.2 Limitations and future research directions Although this study is one of the very few empirical investigations in SCF adoption, it has several limitations and the topic remains exploratory. First, our empirical test is based on data collected from companies in China. The context may limit the generalizability of our findings. Future research can test our model using data from other counties or developed economies. Second, only three drivers are considered in our SCF adoption model. Other drivers, enablers, or even barriers of SCF adoption should be investigated in further research. Also, we only consider supply chain cost performance in general as the benefit of SCF adoption. Other specific dimensions of supply chain cost performance could be introduced in future research and more interesting findings are expected. Due to the practice-based and exploratory nature of current SCF research, future research needs more theoretical understanding of SCF adoption models and confirmation of the knowledge derived from analytical models. A potential direction is to consider the impacts of moderators and understand the boundaries of theories in SCF research. Moreover, we use cross-sectional data to analyze the relationships, which are limited in inferring causal relationship. Future research could design experiments or use longitudinal data to verify the causal relationships among our key variables.

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Journal Pre-proof Production Economics 216, 227-238. Lee, C.H., Rhee, B.-D., 2010. Coordination contracts in the presence of positive inventory financing costs. International Journal of Production Economics 124, 331-339. Lee, H.L., So, K.C., Tang, C.S., 2000. The value of information sharing in a two-level supply chain, Management Science 46, 626-643. Lee, N., Sameen, H., Cowling, M., 2015. Access to finance for innovative SMEs since the financial crisis. Research policy 44, 370-380. Lekkakos, S.D., Serrano, A., 2016. Supply chain finance for small and medium sized enterprises: the case of reverse factoring. International Journal of Physical Distribution & Logistics Management 46, 367-392. Li, Y.X., Wang, S.Y., Feng, G.Z., Lai, K.K., 2011. Comparative analysis of risk control in logistics and supply chain finance under different pledge fashions. International Journal of Revenue Management 5,121-144. Liao, J.-J., 2008. An EOQ model with noninstantaneous receipt and exponentially deteriorating items under two-level trade credit. International Journal of Production Economics 113, 852-861. Long, M.S., Malitz, I.B., Ravid, S.A., 1993. Trade credit, quality guarantees, and product marketability. Financial Management, 117-127. Mahata, G., Goswami, A., 2007. An EOQ model for deteriorating items under trade credit financing in the fuzzy sense. Production Planning and Control 18, 681-692. Mahata, G.C., 2012. Analysis of partial trade credit financing in a supply chain by EOQbased inventory model for exponentially deteriorating items. International Journal of Operational Research 15, 94-124. Marak, Z.R., Pillai, D., 2019. Factors, outcome, and the solutions of supply chain finance: Review and the future directions. Journal of Risk and Financial Management 12, 3. Martin, J., Hofmann, E., 2018. Towards a framework for supply chain finance for the supply side. Journal of Purchasing and Supply Management 25, 157-171. Martin, J., Hofmann, E., 2017. Involving financial service providers in supply chain finance practices: Company needs and service requirements. Journal of Applied Accounting Research 18, 42–62. Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., Zacharia, Z.G., 2001. Defining supply chain management. Journal of Business Logistics 22, 1-25. More, D., Basu, P., 2013. Challenges of supply chain finance: A detailed study and a hierarchical model based on the experiences of an Indian firm. Business Process Management Journal 19. 624–647. Moretto, A., Grassi, L., Caniato, F., Giorgino, M., Ronchi, S., 2018. Supply chain finance: From traditional to supply chain credit rating. Journal of Purchasing and Supply Management. Pellegrino, R., Costantino, N., Tauro, D., 2018. Supply Chain Finance: A supply chainoriented perspective to mitigate commodity risk and pricing volatility. Journal of Purchasing and Supply Management. Pfohl, H.C., Gomm, M,. 2009. Supply chain finance: optimizing financial flows in supply chains. Logistics Research 1,149–161. Pohlen, T.L., Goldsby, T.J., 2003. VMI and SMI programs: How economic value added 27

Journal Pre-proof can help sell the change. International Journal of Physical Distribution & Logistics Management 33, 565-581. Protopappa-Sieke, M., Seifert, R.W., 2010. Interrelating operational and financial performance measurements in inventory control. European Journal of Operational Research 204, 439-448. Qin, J., Bai, X., Xia, L., 2015. Sustainable Trade credit and replenishment policies under the cap-and-trade and carbon tax regulations. Sustainability 7, 16340-16361. Randall, W.S., Theodore Farris, M., 2009. Supply chain financing: using cash-to-cash variables to strengthen the supply chain. International Journal of Physical Distribution & Logistics Management 39, 669-689. Sari, K., 2007. Exploring the benefits of vendor managed inventory. International Journal of Physical Distribution & Logistics Management 37, 529-545. Seifert, R.W., Seifert, D., 2011. Financing the chain. International Commerce Review 10, 32-44. Silvestro, R., Lustrato, P., 2014. Integrating financial and physical supply chains: The role of banks in enabling supply chain integration. International Journal of Operations & Production Management 34, 298–324. Smith, J.K., 1987. Trade credit and informational asymmetry. The Journal of Finance 42, 863-872. Soufani, K., 2002. On the determinants of factoring as a financing choice: evidence from the UK. Journal of Economics and Business 54, 239-252. Summers, B., Wilson, N., 2000. Trade credit management and the decision to use factoring: an empirical study. Journal of Business Finance & Accounting 27, 37-68. Tang, C.S., Yang, S.A., Wu, J., 2018. Sourcing from suppliers with financial constraints and performance risk. Manufacturing & Service Operations Management 20, 70-84. Teng, J.-T., Chang, C.-T., 2009. Optimal manufacturer’s replenishment policies in the EPQ model under two levels of trade credit policy. European Journal of Operational Research 195, 358-363. Theodore Farris, M., Hutchison, P.D., 2002. Cash-to-cash: the new supply chain management metric. International Journal of Physical Distribution & Logistics Management 32, 288-298. Valentini, G., Zavanella, L., 2003. The consignment stock of inventories: industrial case and performance analysis. International Journal of Production Economics 81, 215-224. Van der Vliet, K., Reindorp, M.J., Fransoo, J.C., 2015. The price of reverse factoring: Financing rates vs. payment delays. European Journal of Operational Research 242, 842-853. Waller, M., Johnson, M.E., Davis, T., 1999. Vendor-managed inventory in the retail supply chain. Journal of Business Logistics 20, 183-204. Wuttke, D.A., Blome, C., Foerstl, K., Henke, M., 2013a. Managing the innovation adoption of supply chain finance—Empirical evidence from six European case studies. Journal of Business Logistics 34, 148-166. Wuttke, D.A., Blome, C., Heese, H.S., Protopappa-Sieke, M., 2016. Supply chain finance: Optimal introduction and adoption decisions. International Journal of Production Economics 178, 72-81. 28

Journal Pre-proof Wuttke, D.A., Blome, C., Henke, M., 2013b. Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management. International journal of production economics 145, 773-789. Xu, X., Chen, X., Jia, F., Brown, S., Gong, Y., Xu, Y., 2018. Supply chain finance: a systematic literature reivew and bibliometric analysis. International Journal of Production Economics 204, 160-173. Zhan, J., Li, S., Chen, X., 2018. The impact of financing mechanism on supply chain sustainability and efficiency. Journal of Cleaner Production 205, 407-418. Zhang, T., Zhang, C.Y., Pei, Q., 2019. Misconception of providing supply chain finance: its stabilising role. International Journal of Production Economics 213, 175-184. Zhou, Y.-W., Zhong, Y., Li, J., 2012. An uncooperative order model for items with trade credit, inventory-dependent demand and limited displayed-shelf space. European Journal of Operational Research 223, 76-85.

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Journal Pre-proof Appendix A: Key measures in survey questionnaire

Supply chain cost reduction: Please evaluate the performance of your company’s supply chain in reducing cost? 1.Cost reduction in all parts of supply chain is very significant. 2.Cost reduction in some parts of supply chain is very significant. 3.Cost reduction in all parts of supply chain is not significant but the total cost is reduced. 4.Total cost reduction is not significant. SCF adoption: Please indicate whether your company use the following supply chain finance business? Accounts receivable finance: Yes or No. Inventory finance: Yes or No. Accounts payable finance: Yes or No. Perceived capital pressure: Please choose the statement describing your financial strain in the industry? 1. Very high financial strain; 2. High financial strain; 3. Normal; 4. Sufficient capital; 4. Very sufficient capital. Order fulfillment cycle: Please choose the days for order fulfillment of your company (including purchasing, manufacturing, and delivery). 1. (Less than 7 days); 2. (7 days to 29 days); 3. (30 days to 59 days); 4. (60 days to 119 days); 5. (more than 120 days). Inventory turnover cycle: Please choose the days for product inventory turnover of your company？ 1. (Less than 30 days); 2. (30 days to 90 days); 3. (91 days to 180 days); 4. (181 days to 365 days); 5. (more than 1 year).

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Accounts receivable finance Capital Pressure

Order fulfillment cycle

Inventory finance

Supply chain cost reduction

Accounts payable finance

Control variables: Industry, Ownership, Total assets, Annual sales, Loan demand

Inventory turnover cycle

Figure 1: Research framework

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Journal Pre-proof Table 1. Summary of SCF research Research focus

Research topics

Key insights

Indicative studies

Traditional SCF solutions/ tools

How do SCF solutions affect inventory decisions?

Optimal inventory decisions (optimal ordering, product quantity and replenishment frequency) based on classical models with assumptions of uncertainty and fuzziness.

Budin and Eapen (1970), Haley and Higgins (1973), Huang (2007), Huang and Hsu (2008), Liao (2008), Mahata and Goswami (2007), Mahata (2012), Teng and Chang (2009)

Emerging SCF solutions/ tools

What are the emerging SCF solutions and how are their applied in supply chains?

Boyabatlı et al. (2011), Klapper (2006), Lee and Rhee (2010), Soufani (2002), Van der Vliet et al. (2015)

Drivers of SCF adoption

What factors will affect the adoption of different SCF solutions?

Outcomes of SCF adoption

How does supply chain finance services/benefi ts the whole supply chain?

Trade credit: permissible delays in payment, two-level trade credit, date terms, full or partial policy, discounted cash flows; Factoring: risk transfer, cash-flow improvement; Reverse factoring: credit risk become default risk, low-risk financing; Different contracts: long-term, short-term and window contracting. The willingness to improve the focal firms’ financial performance; The needs to secure upstream and downstream players’ financial performance; Good intra-company collaboration; trade process digitalization and the financial attractiveness of focal companies. Operational costs reduction and profit increase for upstream/downstream players; Supply chain sustainability in terms of financial, social and environment considerations; Better managerial decisions regarding export/import, tariff, and different tax code.

32

Caniato et al. (2016), Fabbri and Klapper (2016), Houston et al. (2016)

Brick and Fung (1984), Dye and Yang (2015), Gong et al. (2018), Hsu and

Zhu

(2011),

Protopappa-Sieke and Seifert (2010), Qin et al. (2015), Zhan et al. (2018).

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Table 2. Profile of respondent company Frequency

Percentage

111 113 102 110 115 44 44 44 683

16.3 16.5 14.9 16.1 16.8 6.4 6.4 6.4 100.0

136 189 108 62 37 30 120 682

19.9 27.7 15.8 9.1 5.4 4.4 17.6 100.0

65 22 319 105 161 11 683

9.5 3.2 46.7 15.4 23.6 1.6 100.0

Industry types Machinery Electronics Retail Pharmaceutical Chemical Coal Steel Automobile Total

Annual sales (RMB million) Less than 10 10-50 50-100 100-300 300-500 500-1000 More 1000 Total

Ownership State-owned Collective-owned Private-owned Foreign Share-holding Others Total

Table 3. SCF adoption level

Accounts receivable finance Inventory finance Accounts payable finance

Adoption N % 213 32.7 206 31.6 194 29.8

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No adoption N % 438 67.3 445 68.4 457 70.2

Table 4. Drivers of SCF adoption using logistic regression analysis Model 1: Accounts receivable finance adoption Coefficients Standard Wald error statistic Control variables Machinery Electronics Retail Pharmaceutical Chemical Coal Steel State-owned Collective-owned Private-owned Foreign Share-holding Total assets Annual sales Loan demand Independent variables Perceived capital pressure Order fulfillment cycle Inventory turnover cycle

Model 2: Inventory finance adoption Coefficients

Standard error

Wald statistic

Model 3: Accounts payable finance adoption Coefficients Standard Wald error statistic

1.106 0.646 1.387 1.357 0.260 -1.756 1.661 -0.462 -1.572 -1.340 -0.632 -0.524 -0.284 0.451 0.007

0.554 0.577 0.603 0.546 0.562 0.736 0.665 0.832 1.037 0.792 0.804 0.811 0.102 0.113 0.015

3.990+ 1.250 5.293* 6.172* 0.214 5.689* 6.242* 0.309 2.295 2.866+ 0.619 0.417 7.678** 15.899*** 0.199

0.544 0.829 0.266 0.881 0.870 0.445 1.738 1.039 0.836 0.237 0.150 0.557 0.021 0.152 0.029

0.516 0.531 0.603 0.503 0.500 0.559 0.634 0.910 1.024 0.882 0.894 0.894 0.093 0.104 0.031

1.115 2.438 0.195 3.070+ 3.024+ 0.632 7.504** 1.304 0.666 0.072 0.028 0.388 0.050 2.153 0.844

1.549 0.783 1.117 1.090 0.422 -2.866 -2.961 0.322 0.345 0.065 0.088 0.348 0.066 0.108 0.001

0.507 0.530 0.566 0.503 0.509 1.117 1.147 0.840 0.960 0.792 0.805 0.818 0.092 0.104 0.014

9.313** 2.183 3.897* 4.696* 0.687 6.584* 6.659* 0.147 0.129 0.007 0.012 0.181 0.513 1.065 0.008

-0.202 0.011 0.015

0.108 0.006 0.157

3.464+ 4.114* 0.009

-0.255 0.013 0.198

0.101 0.007 0.152

6.362* 4.281* 1.705

-0.082 0.011 -0.016

0.105 0.005 0.150

0.612 3.914* 0.011

34

Chi-square (d.f.) -2 Log Likelihood

96.349 (18)*** 505.273***

78.158 (18)*** 538.751***

Notes: +p<0.1, *p<0.05, **p<0.01, ***p<0.001

35

78.009 (18)*** 517.484***

Journal Pre-proof Table 5. Linear regression model Variables

Model 1 Model 2 Supply chain cost reduction

Control variables Machinery Electronics Retail Pharmaceutical Chemical Coal Steel State-owned Collective-owned Private-owned Foreign Share-holding Total assets Annual sales Predictors Receivable finance Inventory finance Payable finance

0.171*

0.187**

0.088

0.111

0.094

0.118+

0.201**

0.223**

0.196**

0.212**

-0.036

-0.039

0.178**

0.229***

-0.229*

-0.229*

-0.138*

-0.143*

-0.366*

-0.392*

-0.328**

-0.340**

-0.328*

-0.331*

-0.280***

-0.299***

0.045

0.099 -0.133**

F value R squared Adjusted R squared Increased R squared

6.241*** 0.121 0.102 0.121***

Notes: +p<0.1, *p<0.05, **p<0.01, ***p<0.001

36

-0.096* 0.032 6.498*** 0.149 0.126 0.028***