Showing papers by "Alfred Taudes published in 2000"
TL;DR: This paper argues that traditional quantitative approaches to a cost-benefit analysis give only a partial picture of decision situations in IT investment situations, and compares different valuation techniques for this task and discusses their respective advantages and drawbacks.
Abstract: In recent years, the use of option pricing models to support IT investment decisions has been proposed in the MIS literature. In this paper, we discuss the practical advantages of such techniques for the selection of a software platform. First, we argue that traditional quantitative approaches to a cost-benefit analysis give only a partial picture of such decision situations: due to the long planning horizon required because of the time-consuming and resource-intensive implementation process, it is not possible to exactly predict which applications will, in fact, run on the system over time. Thus, the investor is faced with the problem of valuing "implementation opportunities." We then compare different valuation techniques for this task and discuss their respective advantages and drawbacks. The practical advantages of employing such models are demonstrated by describing a real-life case study where option pricing models were used for deciding whether to continue employing SAP R/2 or to switch to SAP R/3.
338 citations
04 Jan 2000
TL;DR: The paper discusses the formation of organizational knowledge of boundedly rational economic agents and studies the necessity of hierarchical coordination of economic agents as a function of the uncertainties the agents are facing.
Abstract: The paper discusses the formation of organizational knowledge of boundedly rational economic agents and studies the necessity of hierarchical coordination of economic agents. We consider a firm that consists of a management and N subordinated shops. The problem of the firm is to observe a signal from the environment, forecast future demands and distribute the correct amount of goods to each of the shops. There are two uncertainties involved: the aggregate demand follows a Brownian motion and the distribution of the aggregate demand to the shops varies stochastically. At the beginning of the simulation, the agents are ignorant about their actions. They learn how to choose their actions by probabilistic update. We study the importance of the organizational structures as a function of the uncertainties the agents are facing. It turns out that there is no need for a management if the environment is purely deterministic or if only the aggregate demand varies stochastically. However, if the disaggregate environment is stochastic, the management as a coordinator for the shops becomes important.
1 citations
01 Jan 2000
TL;DR: It is found that the House of Quality approach yields higher life cycle returns than the traditional search for new products, especially for a low number of search steps, which is an important finding recommending the application of theHouse of Quality.
Abstract: We study the effects of various incentive schemes on the learning behavior of teams in an artificial factory. Modeling the new product development process, we demonstrate, how production and marketing agents learn to coordinate their actions in order to produce the optimal product with respect to their incentive schemes. As a coordinating mechanism between marketing and production, we use the House of Quality Framework of H.J.R. Hauser and D. Clausing (1988). The House of Quality methodology, which is used by real firms, contains important information from marketing and production. It is a procedure that facilitates the search for new, promising (from market perspective), and feasible products (from a production/design perspective). We found that the House of Quality approach yields higher life cycle returns than the traditional search for new products, especially for a low number of search steps. This is an important finding recommending the application of the House of Quality since the number of search steps directly influences time to market. Thus, minimizing the number of steps could be an important competitive advantage in today's fast moving consumer markets.
1 citations
01 Jan 2000
TL;DR: In this paper, the authors study different incentive schemes by means of a two-stage model and derive an analytical solution for the bargaining process under uncertainty and compute Nash equilibria for a discrete set of possible actions.
Abstract: The knowledge required for decision making in a firm is distributed across various departments. In practice cross functional teams are used to integrate this distributed knowledge. Incentive schemes are of crucial importance to encourage departments to share knowledge. In this paper, we study different incentive schemes by means of a two stage model. In the first step departments have to choose between learning and sharing knowledge, in the second stage, they bargain about a new product feature. The outcome of the bargaining process in the second stage depends on the capabilities of the agents and their uncertainty about the opponent. The result of the second stage determines the agents' payoffs which in turn influence the time allocation. In a simulation study, we investigate different incentive systems and show to which extent a firm has to reward the sharing of knowledge in order to reach its overall objectives. Furthermore, we are able to derive an analytical solution for the bargaining process under uncertainty and compute Nash equilibria for a discrete set of possible actions. (author's abstract)
1 citations