Explaining adoption and use of payment instruments by US consumers

Koulayev, Sergei; Rysman, Marc; Schuh, Scott; Stavins, Joanna

doi:10.1111/1756-2171.12129

Cited by 104 publications

(53 citation statements)

References 50 publications

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“…In this vein, a lot of research has been conducted. Some studies focus on the choice between cash and card (Carow and Staten 1999;Snellman, Vesala, and Humphrey 2001;Bergman et al 2007;Koulayev et al 2012;Kosse 2013;Schuh and Stavins 2013;Hernandez, Jonker, and Kosse 2014;Von Kalckreuth, Schmidt, and Stix 2014), with Foster et al (2011) and Jonker and Kosse (2013) using survey methods. Some articles study more precisely card payments (Rysman 2007;Sprenger and Stavins 2008;Kosse and Jansen 2013), others examine cheque payments (Schuh and Stavins 2010;Micheau and Houitte 2012) and a few focus on incentives (Simon, Smith, and West 2010;Arango, Huynh, and Sabetti 2011).…”

Section: Introductionmentioning

confidence: 99%

Consumers’ perceived risk and hold and use of payment instruments

2015

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ACL-2International audienceABSTRACTConsumer decisions regarding retail payment instruments entail private and social costs. Due to these social costs, policymakers are increasingly trying to understand the determinants of consumer payment choices as documented by the European Central Bank?s regular publications. This article contributes to this understanding by investigating the role of perceived risk. Based on an original survey of French consumers, we measure the effects of perceived risk on the decisions to hold and use the main retail payment instruments: cash, card and cheque. We point to the sequential dependence of the decisions to hold and use a payment instrument, and study jointly both decisions. The bivariate analysis based on risk factors shows that unavailability risk and time risk have the greatest transverse influence on holding and using payment instruments. Our results, robust to controlling for consumer characteristics, confirm their propensity for a quick-to-use and constantly available payment instrument. We discuss the relevance of our results for policy making purposes

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Section: Introductionmentioning

confidence: 99%

Consumers’ perceived risk and hold and use of payment instruments

2015

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“…The cost of using debit cards depends 4 on checking account maintenance fees charged by the card issuing bank. 2 For this reason, following Koulayev et al (2016), Huynh et al (2019) and Shy (2019), the analysis in this article uses respondent-specific assessments of each payment instrument to identify consumer-specific cost and benefit derived from using each payment instrument. 3 Table 2 shows that 66.7 (58.3 + 8.3) percent of unbanked respondents assess cash to be a low payment instrument.…”

Section: Measuring Consumers' Benefit and Cost Of Different Payment Mmentioning

confidence: 99%

Low-Income Consumers and Payment Choice

Shy

2020

SSRN Journal

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“…Stavins et al [6] have tried to discover whether U.S. merchants are using their recently granted freedom to offer price discounts and other incentives to steer customers to pay with methods that are less costly to merchants, and have found that only a very small fraction of transactions received a cash or debit card discount, and even fewer were subjected to a credit card surcharge. Koulayev et al [7] developed and estimated a structural model of adoption and use of payment instruments by U.S. consumers. After that, they utilized a cross-section from the Survey of Consumer Payment Choice.…”

Section: On Analysis Based On Scpc Datamentioning

confidence: 99%

Modeling the Trend of Credit Card Usage Behavior for Different Age Groups Based on Singular Spectrum Analysis

Nai¹,

Liu

Wang³

et al. 2018

Algorithms

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Credit card holders from different age groups have different usage behaviors, so deeply investigating the credit card usage condition and properly modeling the usage trend of all customers in different age groups from time series data is meaningful for financial institutions as well as banks. Until now, related research in trend analysis of credit card usage has mostly been focused on specific group of people, such as the behavioral tendencies of the elderly or college students, or certain behaviors, such as the increasing number of cards owned and the rise in personal card debt or bankruptcy, in which the only analysis methods employed are simply enumerating or classifying raw data; thus, there is a lack of support in specific mathematical models based on usage behavioral time series data. Considering that few systematic modeling methods have been introduced, in this paper, a novel usage trend analysis method for credit card holders in different age groups based on singular spectrum analysis (SSA) has been proposed, using the time series data from the Survey of Consumer Payment Choice (SCPC). The decomposition and reconstruction process in the method is proposed. The results show that the credit card usage frequency falls down from the age of 26 to the lowest point at around the age of 58 and then begins to increase again. At last, future work is discussed.

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Explaining adoption and use of payment instruments by US consumers

Cited by 104 publications

References 50 publications

Consumers’ perceived risk and hold and use of payment instruments

Consumers’ perceived risk and hold and use of payment instruments

Low-Income Consumers and Payment Choice

Modeling the Trend of Credit Card Usage Behavior for Different Age Groups Based on Singular Spectrum Analysis

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