Testing the technology acceptance model across cultures: a three country study
Information and Management
The psychological origins of perceived usefulness and ease-of-use
Information and Management
The Diffusion of Electronic Data Interchange
The Diffusion of Electronic Data Interchange
Logistic Regression Using the SAS System: Theory and Application
Logistic Regression Using the SAS System: Theory and Application
Opening the "Black Box" of Network Externalities in Network Adoption
Information Systems Research
Research Report: Empirical Test of an EDI Adoption Model
Information Systems Research
The Corporate Digital Divide: Determinants of Internet Adoption
Management Science
A Stakeholder Perspective on Successful Electronic Payment Systems Diffusion
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
Journal of Management Information Systems - Special section: Managing virtual workplaces and teleworking with information technology
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
Cutting checks: challenges and choices in B2B e-payments
Communications of the ACM - Smart business networks
Designing Web Sites for Customer Loyalty Across Business Domains: A Multilevel Analysis
Journal of Management Information Systems
What Do You Know? Rational Expectations in Information Technology Adoption and Investment
Journal of Management Information Systems
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Despite much hype about electronic payments systems (EPSs), a 2004 survey establishes that close to 80% of between-business payments are still made using paper-based formats. We present a finite mixture logit model to predict likelihood of EPS adoption in business-to-business (B2B) settings. Our model simultaneously classifies firms into homogeneous segments based on firm-specific characteristics and estimates the model's coefficients relating predictor variables to EPS adoption decisions for each respective segment. While such models are increasingly making their presence felt in the marketing literature, we demonstrate their applicability to traditional information systems (IS) problems such as technology adoption. Using the finite mixture approach, we predict the likelihood of EPS adoption using a unique data set from a Fortune 100 company. We compare the finite mixture model with a variety of traditional approaches. We find that the finite mixture model fits the data better, controlling for the number of parameters estimated; that our explicit model-based segmentation leads to a better delineation of segments; and that it significantly improves the predictive accuracy in holdout samples. Practically, the proposed methodology can help business managers develop actionable segment-specific strategies for increasing EPS adoption by their business partners. We discuss how the methodology is potentially applicable to a wide variety of IS research.