A FIELD-BASED INVESTIGATION INTO THE EFFECT OF EXPERT SYSTEM USE ON THE INFORMATION PROCESSING CAPACITY OF THE FIRM

To date, there have been many reports on the use of decision support systems (DSS) and knowledgebased systems (KBS) in organizations. Little of this research evaluates the impact of commercial systems on the performance of the organization using the system. This study attempts to shed some light on this intellectual domain. This paper reports on a field-based investigation into the effects of the use of MUDMAN™ (a commercial expert systems product) on the information-processing capacity of N.L. Baroid, an oil services firm. The study uses the notions of organizational programs as defined by March and Simon and operationalizes the information processing capacity framework £ut forth by Galbraith to show how information-processing capacity was affected when the MUDMAN system was used at Baroid

People-to-People Lending: The Emerging e-Commerce Transformation of a Financial Market

This paper provides an overview of the concept of people-to-people (P2P) lending, a relatively new e-commerce phenomenon that has the potential to radically change the structure of the loan segment of the financial industry. P2P lending creates a marketplace of individuals and a social fabric through which these individuals interact. It provides efficient information transfer, thus perhaps creating more perfect markets. P2P lending requires information systems support to make it function, and to provide a social network mechanism that may be crucial for its success. We discuss different P2P lending marketplace models, and how information systems support the creation and management of these new marketplaces, and how they support the individuals involved. We conclude by providing some important research questions and directions, and issues for which further investigation is called

Does Gender Affect Investors' Appetite for Risk? Evidence from Peer-to-Peer Lending

This study investigates the role of gender in financial risk-taking. Specifically, I ask whether female investors tend to fund less risky investment projects than males. To answer this question, I use real-life investment data collected at the largest German market for peer-to-peer lending. Investors' utility is assumed to be a function of the projects expected return and its standard deviation, whereas standard deviation serves as a measure of risk. Gender differences regarding the responses to projects' risk are tested by estimating a random parameter regression model that allows for variation of risk preferences across investors. Estimation results provide no evidence of gender differences in investors' risk propensity: On average, male and female investors respond similarly to the changes in the standard deviation of expected return. Moreover, no differences between male and female investors are found with respect to other characteristics of projects that may serve as a proxy for projects' risk. Significant gender differences in investors' tastes are found only with respect to preferred investment duration, purpose of investment project and borrowers' age

Addressing information asymmetries in online peer-to-peer lending

Digital technologies are transforming how small businesses access finance and from whom. This chapter explores online peer-to-peer (P2P) lending, a form of crowdfunding that connects borrowers and lenders. Information asymmetry is a key issue in online peer-to-peer lending marketplaces that can result in moral hazard or adverse selection, and ultimately impact the viability and success of individual platforms. Both online P2P lending platforms and lenders seek to minimise the impact of information asymmetries through a variety of mechanisms. This chapter discusses the structure of online P2P lending platforms and reviews how the disclosure of hard and soft information, and herding can reduce information asymmetries. The chapter concludes with a discussion of further avenues for research