Articles

Does Superposition Influence the Success of FLOSS Projects? Examining Open Source Software Development by Organizations and Individuals

P. MEDAPPA, S. C. SRIVASTAVA

Information Systems Research

Forthcoming

Departments: Information Systems and Operations Management, GREGHEC (CNRS)


Does Technostress Inhibit Employee Innovation? Examining the Linear and Curvilinear Influence of Technostress Creators

S. CHANDRA, A. SHIRISH, S. C. SRIVASTAVA

Communications of the Association for Information Systems

Forthcoming

Departments: Information Systems and Operations Management, GREGHEC (CNRS)


Dynamic Monitoring of Service Outsourcing for Timed Workflow Processes

X. LI

IEEE Transactions on Engineering Management

Forthcoming

Departments: Information Systems and Operations Management, GREGHEC (CNRS)


Optimal Feed-In Tariff Policies: The Impact of Market Structure and Technology Characteristics

S. GOODARZI, S. AFLAKI, A. MASINI

Production and Operations Management

Forthcoming

Departments: Information Systems and Operations Management, GREGHEC (CNRS)

https://onlinelibrary.wiley.com/doi/10.1111/poms.12971


This paper models a multi‐player environment consisting of a grid operator responsible for meeting electricity demands, a photovoltaic (PV) manufacturer, customers who might install (solar) PV systems, and a regulator who must set an optimal feed‐in tariff (FIT). The grid operator must meet exogenous electricity demand and also buy back all electricity (produced by PV systems) at the FIT set by the regulator. Customers decide whether or not to invest in a PV system. Adoption rates affect the manufacturer and operator by (respectively) establishing the demand for PV systems and determining how much PV electricity is fed into the grid. The PV manufacturer's decision variable is the sales price per PV unit. The decisions of all players in the model are intertwined in a way that clearly affects their respective welfare. We demonstrate in particular how technology and market characteristics—including PV manufacturing cost and market competition—change the optimal decisions of players and thereby influence the effectiveness of FITs, the number of PV adopters, and the cost to provide the social benefit of on‐demand electricity. Our findings confirm the importance of considering technology manufacturers when devising schemes to incentivize the adoption of PV systems

Using Polynomial Modeling to Understand Service Quality in E-government Websites

R. NISHANT, S. C. SRIVASTAVA, T.S.H. TEO

MIS Quarterly

Forthcoming

Departments: Information Systems and Operations Management, GREGHEC (CNRS)



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