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Business process modeling using hybrid simulation: A peer lending case study
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Industrial Engineering & Management

ISSN: 2169-0316

Open Access

Business process modeling using hybrid simulation: A peer lending case study


International Summit on Industrial Engineering

December 08-10, 2014 DoubleTree by Hilton Hotel San Francisco Airport, USA

Oloruntomi Joledo

YRF: Ind Eng Manage

Abstract :

Electronic markets (e-markets) have metamorphosed the process of ticket reservation, online shopping, online trading and many other industries by replacing traditional distribution channels and reshaping customer-supplier relationships. Processes can now be automated to eliminate the middle man and minimize unnecessary overhead. The most recent application of e-markets is to social lending. Social lending or peer-to-peer lending has gained popularity to counter the rigid lending practices and curb the excesses of conventional banking. Lenders pool their resources together online and make them available as loans at a premium to borrowers who need it. Evaluation of viability of the social lending business model has not been adequately addressed in literature from a supply chain perspective. By viewing the problem as a supply chain problem will help to identify the efficiencies in the business model, analyze the process and identify business process improvement opportunities. This paper maps the supply chain of the social lending space and implements it using a hybrid of system dynamics and agentbased modeling and simulation.

Biography :

Oloruntomi Joledo is a Doctoral candidate at the department of Industrial Engineering and Management Systems at University of Central Florida (UCF). She received her MS degree in Electrical Engineering from Southern Illinois University Edwardsville (SIUE) in 2010. She has four years experience developing software applications and also as a project engineer on various technological projects. Her main research interests include: hybrid simulations, software development and engineering management.

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Citations: 739

Industrial Engineering & Management received 739 citations as per Google Scholar report

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