DECISION MAKING IN NEW BUSINESS

Decision Making In New Business Startups

Table of Contents

Chapter - I3

Introduction3

Literature Review6

The new venture investment decision problem6

Description of the decision support system9

Database description10

AHP model generator12

Knowledge base20

Forecast generator21

Role of the Decision Maker23

Aspects of Sequential Decision Making24

The Utility of Operations Research25

Model Solutions: Decision Making In Operations Research27

Mathematical Tools28

Operations Research Techniques30

Chapter - II33

Methodology33

Performance evaluation criteria33

LM-1. Benchmark model34

QV-1. Qualitative model35

QQ-1. Integrated quantitative and qualitative model36

Reference38

Chapter - I

Introduction

An important decision problem for portfolio managers, institutional/retail investors, and policy makers is to develop an evaluation system to guide investment decisions in new ventures. The obvious decision criteria in any investment are the viability of the company as a profitable venture, both at the present time and in the long run. The investment decision in the case of an established company is guided by a number of performance indicators arising from the company's own track record, analyst's forecasts, and industry attractiveness. For new ventures much of this data is absent as the company is new to the public and does not have a track record and hence, few quantitative indicators can be derived. The decision to invest in new ventures is to be made at a point in time when the firm goes public through an Initial Public Offering (IPO). The decision needs to be made based on information supplied by the firms in their prospectuses with little or no independent analysis from analysts and other sources. Decision-makers have to depend on combinations of quantitative, qualitative and subjective assessments in evaluating whether or not to invest in the IPO of the firm. In this paper, we develop the framework of a knowledge based decision support system which attempts to incorporate all these factors in recommending a decision.

The need for decision aids to improve the quality of decision-making is apparent in the IPO market since it has become a major source of capital in the U.S. economy and elsewhere. For instance, Business Week (April 4, 1994) reports that IPO issuing firms within the U.S. raised a staggering 40 billion dollars in 1993 alone. Further, the IPO phenomenon is not confined to U.S. markets and has taken a global dimension with a flood of new issues coming from the newly emerging economies. Adding to the momentum is the wave of privatizations sweeping across the globe resulting in a large number of IPOs. Business Week reports that in China, everything from smoke belching chemical companies to taxi cab firms are attempting to go public. Since the danger of failure among new ventures is high, it is clear that a decision support model capable of improving the quality of the new venture selection problem has considerable economic significance. The need for a dynamic decision model to guide decisions in selecting successful new ventures arises primarily due to the need to simultaneously incorporate quantitative, qualitative and subjective estimation in the analysis. Traditional management science decision event models such as constrained optimization, scoring and forecasting, generally do not perform well in situations similar to the new venture selection ...