Using Simulation in Information Systems Research

Like all other scientific research methodologies, simulation has its strengths and limitations. When used properly, simulation can be a powerful tool for developing new theoretical insights into IS phenomena of interest. Although simulation methods are not new in the IS field, there has been no systematic discussion about which simulation methods are suitable for IS research, when simulation is the most appropriate methodological choice for IS research, and how to evaluate simulation research. In this editorial, I provide an overview of simulation methods that may be used in IS research and discuss how they are typically used. More importantly, I provide guidelines for IS researchers on how to choose simulation among alternative methodologies and highlight six key criteria for evaluating simulation research. Overall, this editorial can provide useful guidance to IS researchers, editors, and reviewers when choosing, conducting, and assessing simulation research

A Survey of Simulation Research in Information Systems Discipline

Along with the increasing number of companies introducing Enterprise Social Networks (ESN) in recent years, research on ESN user behaviour has proliferated. Yet, a detailed analysis of factors driving ESN user behaviour, that is, how users participate in ESN, is missing. Addressing this gap, in this paper, we explore ESN user behaviour and factors influencing usage in an Australian professional services firm. Based on a case study including 14 interviews with regular users of the case company’s ESN, we identify and characterise six general dimensions of ESN user behaviour. In addition, our analysis indicates ESN user behaviour to be influenced by a mix of individual factors and organisational factors. The contributions of this paper include a conceptualisation of user behaviour as well as a set of factors shaping ESN usage. For the management of ESN communities, our findings are hoped to inform initiatives aiming at reinforcing user engagement over time

ON COMPUTER SIMULATION AS A COMPONENT IN INFORMATION SYSTEMS RESEARCH

Computer simulation is widely regarded as a useful activity during various phases of research. However, depending on its context, the meaning, definition, and focus of the term can vary: In traffic planning, for example, simulation is used to determine useful configurations of a road network, thus focusing on the environment. An entirely different perspective is used within multi-agent systems. In such settings, the environment of the agents remains static, while the interesting research questions concern the behavior of the agents themselves. The research focuses on the microscopic level and the resulting emergent behavior. This article puts such diverse meanings in the context of a research process that treats descriptive and prescriptive research as two sides of the same coin. We develop a framework to classify different types of simulation, based on the actual research activity they are intended to be used for. Two case studies supplement the framework

Rotor systems research aircraft: Fixed-wing simulations results

The setup, validation, and results of the Rotor Systems Research Aircraft (RSRA) fixed-wing, moving-base simulation performed in May 1983 are covered. The emphasis of the simulation was to familiarize the pilots with the RSRA's fixed-wing configuration. Additional information concerning stall speeds, minimum control speed, and various gross weights were recorded and included in the report

Introduction to SIMRAND: Simulation of research and development project

SIMRAND: SIMulation of Research ANd Development Projects is a methodology developed to aid the engineering and management decision process in the selection of the optimal set of systems or tasks to be funded on a research and development project. A project may have a set of systems or tasks under consideration for which the total cost exceeds the allocated budget. Other factors such as personnel and facilities may also enter as constraints. Thus the project's management must select, from among the complete set of systems or tasks under consideration, a partial set that satisfies all project constraints. The SIMRAND methodology uses analytical techniques and probability theory, decision analysis of management science, and computer simulation, in the selection of this optimal partial set. The SIMRAND methodology is truly a management tool. It initially specifies the information that must be generated by the engineers, thus providing information for the management direction of the engineers, and it ranks the alternatives according to the preferences of the decision makers

Information Systems-based Real Estate Macrocontrol Systems

With the continuous increase of marketization and normalization in the Chinese real estate market, the market mechanism now plays an important role in market regulation. The existing macro-control system for the real estate market, however, appears to lack the ability to regulate it. Thus, an effective and efficient information-oriented tool is needed to guide the development of China’s real estate market. The research reported herein constructs a new macro-control system for this market that is based on information systems, specifically, a real estate warning system, a confidence index system, and a simulation system. This paper first presents the framework of the new information systems-based macro-control system, and its functions are analyzed. The methods of constructing the system are then discussed. Based on these methods, the index systems of the respective information systems are established, and the main models are presented. Finally, a case study that is based on survey data from the Shenzhen real estate market is described to demonstrate the applicability of the new macrocontrol system.Real estate; Macro-control system; Warning system; Confidence index; System simulation

Horticultural weed control in organic systems – a modelling approach

This report was presented at the UK Organic Research 2002 Conference. Weed control is an important yet mainly unaddressed research issue in organic systems. At present there is little agronomic support to underpin weed management decisions. Computer modelling and simulation techniques may provide a valuable tool for understanding the nature and processes of the organic system thus generating knowledge and information of direct benefit to growers, which will aid in short and long term weed management strategies