Computational modeling of business processes: A coordination mechanism approach

Recent research on business process design has mainly focused either on technology or on workflow aspects of business processes. Technology efforts involve automating tasks that are time consuming and repetitious. On the other hand, workflow redesign efforts concentrate only on the flow of work or information. Either approach fails to fully capture all the aspects of a business process. The dissertation makes a threefold contribution to the existing literature on coordination in business processes. First, it presents an integrative approach to business process understanding that synthesizes economic, behavioral, and mechanistic concerns of different research streams in management. Second, it develops a computational modeling language for specifying the coordination mechanisms of organizational processes and describes an abstract machine that can simulate such process specifications. The novelty of the language lies in the modeling of agents as utility maximizing entities whose decision choices are influenced by incentive mechanisms. Third, it utilizes the modeling approach developed earlier to investigate the comparative performance of a number of commonly used incentive schemes in a delegated investment process. The computational study provides useful insights into the delegated investment problem on the issues of incentive design, effect of market uncertainties and the effect of risk aversion. The results also demonstrate the effect of the different incentives on the risk-return tradeoffs exhibited by the agents. The dissertation is organized into three main essays as follows.;In the first essay, the coordination framework is developed and two illustrative cases are described using this framework. The coordination mechanism framework recognizes workflow, decision, information, and agency structures as important aspects of a business process.;In the second essay the specifications of a modeling language which capture the various aspects of the coordination framework are presented. In this modeling approach, agents' decision choices are influenced by the design of the incentive mechanisms, through the agents' utility maximizing behavior. Facilities for modeling pools and groups of agents are also made available in this language.;In the third essay, simulation experiments are conducted to analyze the relative performance of incentive mechanisms in a delegated investment setting. The impact of a few alternative arrangements of performance incentive fee on the behavior of the investment managers and the resulting investment performance is examined. The computational results demonstrate the risk-return tradeoffs that agents exhibit in a delegated investment setting, and how such behavior is affected by the nature of incentive contracts.