How do different payment methods deliver cost and credit efficiency in electronic commerce?

Highlights

• We derive retailer transaction cost functions of online payment instruments.

• Our analysis is based on a unique dataset consisting of 16 m sales transactions.

• Invoice is the most cost-efficient payment method for small transaction sizes.

• Prepayment is the preferable payment method for transactions above a value of €22.

• Credit card and PayPal cause higher costs and do not show scale efficiency.

Abstract

Using unique data consisting of more than 16.3 million sales transactions provided by a leading European fashion e-commerce company, this study evaluates several payment instruments, including invoices, credit cards, PayPal payments, and prepayments, from an online retailer’s perspective in terms of cost and credit efficiency. The authors identify the transaction size, allowance costs for fraudulent customers, and type of credit card provider that influence retailer transaction costs. Moreover, the results reveal that, for small transaction sizes, invoices are the most cost-efficient payment method, while prepayments dominate for large transaction sizes. Electronic payments in terms of both credit card and PayPal cause higher payment costs, and do not show scale efficiency in e-commerce. Furthermore, this research illustrates differences in the collection time of accounts receivable across payment methods, implying the cost of capital that arises for the retailer. The results lead to the conclusion that prepayments and PayPal payments are associated with the lowest cost of capital.

Introduction

The mode of payment that is offered to customers is important for a retailer’s marketing and financial objectives, and has direct implications for a firm’s profitability (Ingene and Levy, 1982). In particular, the increasing volume of worldwide transactions due to a still growing number of Internet shoppers (Pozzi, 2013), substantial innovations in payment technology and infrastructure (Kahn and Roberds, 2009), and significant changes in consumer payment habits (Pimentel, 2013, Schuh and Stavins, 2010) require new ways of handling payments in business-to-consumer markets in e-commerce (Stroborn et al., 2004).

Considering this background, it is not surprising that researchers have examined why individuals and firms use different payment instruments (Garcia-Swartz et al., 2006, ten Raa and Shestalova, 2004). Although this is highly relevant for academics and practitioners, empirical evidence regarding payment costs and its influence on the payment choice is scarce (Hancock and Humphrey, 1998, Klee, 2008). The perspective of a retailer has yet to be explored in depth due to the absence of appropriate data (Dahlberg et al., 2008, Grewal and Levy, 2007). Previous studies on the economics of payment instruments used survey data (Garcia-Swartz et al., 2006, Garcia-Swartz et al., 2006, Hayashi and Keeton, 2012) or aggregated statistics (ten Raa and Shestalova, 2004), but did not have access to transaction-level data (Kahn and Roberds, 2009). Depending on the granularity of the data available, prior research has reported a wide variance in cost rankings and contradictory results, as well as divergent managerial conclusions (Hayashi and Keeton, 2012, Shampine, 2009, Shampine, 2007). This topic has been identified as an important area for future research, since the two main questions “What does it cost to make a payment?” (Humphrey et al., 2003) and “Which payment instrument turns out to be the least expensive depending on the transaction size?” still have not been answered (Humphrey, 2010). Specifically, researchers have called for further research involving the collection of detailed data on an individual consumer and bank level to examine the complexity of financial payment instruments and consumer behavior (Scholnick et al., 2008). The dependency of the payment choice on the transaction value requires a detailed analysis of the market place and the associated transaction costs with regard to each payment method (Shy and Tarkka, 2002).

As a consequence, this study analyzes how retailers can provide cost and credit-efficient payment services in e-commerce. We offer three main contributions to the field.

From a conceptual viewpoint, we expand the well-established transactions demand for cash framework by Baumol (1952) and Tobin (1956) to an e-commerce environment by introducing Internet-specific payment instruments, such as invoices, credit cards, PayPal payments, as well as prepayments. We also include online payment systems-related transaction costs components, such as customer payment default costs and cost of capital. Compared to previous research, our estimation model gives a more holistic picture of the transaction costs retailers incur when providing payment services in their Internet businesses, and hence it offers opportunities for retailers in terms of lowering customer servicing costs and achieving greater efficiency (Kalaignanam et al., 2008, ten Raa and Shestalova, 2004). We also add to the Finance literature that has called for research into the relationship between different payment instruments, deposit reactions, and profitability (Bounie and Gazé, 2009, Santomero, 1984, Shy and Tarkka, 2002).

From an empirical viewpoint, we make a contribution by testing this theoretical model and deriving cost rankings of online payment instruments on the basis of a proprietary dataset from an online fashion retailer. It consists of more than 16.3 million actual customer sales transactions. This approach is unique, since existing research on the economics of payment instruments has not focused on the retailer’s perspective or electronic transaction methods due to the scarcity of proprietary, transaction-level, supply-side data (Kahn and Roberds, 2009, ten Raa and Shestalova, 2004).

Ultimately, this research explores the differences in the collection time of the accounts receivable across payment methods and its respective influence on a firm’s profitability. We consider the cost of capital as a component of the relevant transaction cost for retailers when they offer payment services in e-commerce. Thus, for the first time, we have connected payment and working capital management – two business disciplines often treated separately by operations management (Balakrishnan, 2011, Protopappa-Sieke and Seifert, 2010). Our regression results enhance retailer knowledge about how much capital is tied up in open customer transactions. This detailed knowledge is important in that it is useful towards initiating significant cost savings and working capital reductions to increase a firm’s profitability and shareholder value (Kieschnick et al., 2013, Lieber and Orgler, 1975).