New venture survival is tenuous at best, but those backed by Venture Capitalists (VCs) tend to achieve a higher survival rate than non VC backed businesses (Kunkel & Hofer, 1990; Sandberg, 1986; Timmons, 1994). Thus, many researchers have investigated how these new venture investment experts make their decisions (Wells, 1974; Poindexter, 1976; Tyebjee & Bruno, 1984; MacMillan, Seigel & Subba Narasimha, 1985; MacMillan, Zeman, & Subba Narasimha 1987; Robinson, 1987; Timmons, Muzyka, Stevenson, & Bygrave, 1987; Sandberg, Schweiger & Hofer, 1988; Hall & Hofer, 1993; Zacharakis & Meyer, 1995). The underling justification for these studies is that a better understanding of the process may lead to better decisions and thereby more successful ventures. However, the majority of these studies use post hoc methodologies, such as interviews and surveys, which may be subject to post hoc rationalization and recall biases (Barr, Stimpert & Huff, 1992; Sandberg, et al., 1988). Such biases tend to inhibit how accurately people can introspect about their own thought processes (Fischhoff, 1988). Experts, who tend to rely on intuition more than non-experts (Simon & Chase, 1973), are notoriously poor introspectors (Fischhoff, 1988). Since VCs often rely on intuition, or as they call it, "gut feel" (Khan, 1987; MacMillan, et al., 1987), post hoc methods may bias much of the past research in this area.

The current study uses policy capturing experiments common in cognitive psychology (Stewart, 1988, 1991) to test how well VCs understand their own decision making process. The paper proceeds as follows: First, the VC decision process is reviewed. Second, the paper looks at how biases and heuristics hinder the decision. Next, Social Judgment Theory and the associated lens model are used to provide a theoretical basis for exploring the decision. Then a series of testable hypotheses is derived from the lens model. The subsequent section explains the policy capturing methodology and the associated experiment. Finally, results of the current study are presented followed by conclusions and implications.


VC firms can be defined as "those organizations whose predominant mission is to finance the founding or early growth of new companies that do not yet have access to the public securities market or to institutional lenders" (Gupta & Sapienza, 1992; 349; Perez, 1986; Pratt, 1987). As such, Gupta and Sapienza (1992) suggest that VCs add value by:

1. bringing investors and entrepreneurs together in an efficient manner,
2. making superior investment decisions than limited partners would make, and
3. providing non-financial assistance which in turn enhances survival.

All other things equal, a VC firm's performance is a function of how well it makes the investment decision and how effective its management advice and services are after the investment decision has been made. Therefore, improving the investment decision can improve the VC's performance.

VCs attempt to assess the probability of success or failure by evaluating information surrounding the particular venture. To receive funding, new ventures must past an initial screening (typically a review of the business plan) followed by months of due diligence. A number of researchers have examined what information is critical to the VC's decision and the information appears to fit four categories: (1) entrepreneur/team capabilities, (2) product/service attractiveness, (3) market/competitive conditions, and (4) potential returns if the venture is successful (Wells, 1974; Poindexter, 1976; Tyebjee & Bruno, 1984; MacMillan, et al., 1985, 1987; Robinson, 1987; Timmons, et al., 1987; Hall & Hofer, 1993). Although insightful, these studies (with exception of Hall and Hofer likely suffer from introspection biases.

It is well recognized in the literature that decision makers are not perfectly rational, but boundedly rational (Cyert & March, 1963; Newell & Simon, 1972; Simon, 1955). It is impossible for decision makers to fully evaluate all information and they are typically biased by salient factors (Fiske & Taylor, 1991). Biases not only inhibit the decision process, but they also likely impede the VC's ability to accurately report on her/his decision process. For instance, the availability bias (Tversky & Khaneman, 1974) encourages decision makers to recall information from memory that is salient. Instead of recalling the actual information used to make typical decisions, VCs likely fixate on one or two past successes (Dawes, 1988; Dawes, Faust & Meehl, 1989) and recall information most salient (Fiske & Taylor, 1991) to those ventures. For example, the VC may fixate on the lead entrepreneur because of that person's dynamic personality. As such, VCs may be inclined to report entrepreneur characteristics as more important to the decision than they actually are.


Social Judgment Theory (SJT [Brunswik, 1956] from cognitive psychology provides a framework for understanding the VC decision process, as well as a basis for removing post hoc biases. SJT's underlying assumption is that decision makers do not have access to "real" information, but instead perceive that information through proximal cues (Strong, 1992). These cues quantitatively describe the relationship between someone's judgment and the information used to make that judgment (Stewart, 1988). Hence, SJT allows the capture of 'theories in use' as opposed to 'espoused theories' of action (Hitt & Tyler, 1991). Within SJT, human judgments are formally modeled via the lens model.

The lens model basically consists of two systems (cognitive and task) linked together by proximal information cues. The cues (see Figure 1 on next page) are the information factors that an individual considers when making a decision. These are represented by variables x1 through x4 which appear in the middle of Figure 1. The cognitive system is represented by the right side of the model. Cues are combined in some manner to make a judgment or decision (Ys); Ys captures the expert's judgment policy. In other words, Ys represents the judge's perception of the decision. The cues' correlation to the individual's judgment is represented by rsi. The larger the standardized rsi (assuming orthogonal cues), the more heavily the decision maker relies on that cue to make the decision (Stewart, 1988).

The task system is on the left side of Figure 1. The criterion variable is the actual outcome (Ye). Each of the cues is also correlated (rei) to the actual outcome. Thus, rei defines the relationship between the cues and the reality based condition of interest to the decision maker. Just as rsi indicates the relative importance of each cue to the decision maker, rei indicates which cues have the greatest predictive value to the actual outcome. Hammond sums up the lens model as follows.

"judgment is a cognitive process similar to inductive inference, in which the person draws a conclusion, or an inference, Ys, about something Ye, which he cannot see (or otherwise directly perceive). In other words, judgments are made from palpable events and circumstances" (1975: 73).

An example may better clarify the use of lens models. The lens model can depict a VC examining a new venture. The VC makes a judgment [(Ys) invest or not] of the venture's potential [(Ye) success/failure] based upon a number of information factors [(xk) strong team, proprietary protection, etc.]. The VC isn't directly observing the venture's ultimate outcome, but instead inferring the venture's potential based upon a number of observable current conditions. This brief example illustrates that judges make decisions about objects that they cannot directly perceive via a series of information factors that they can observe. The lens model provides the basis for a series of testable hypotheses.

VCs considering new venture proposals are inundated with information. For example, there is evidence about the entrepreneur (e.g. entrepreneur's industry and start-up experience), the market (e.g. size and growth), and the product/service (e.g. proprietary protection). Not only is there a lot of available information, but much of it is of a subjective nature. For example, VCs often discuss the "chemistry" between themselves and the entrepreneur. If the chemistry isn't right, the deal often falls through. Such intuitive, or "gut feel" (Khan, 1987, MacMillan, et al., 1987), decision making is difficult to quantify or objectively analyze. The added complexity from subjective information further clouds the decision making process and subjects the decision maker to more biases. Due to the decision's complexity and the VCs' intuitive approach, VCs may have a difficult time introspecting about their decision process (Fischhoff, 1988). In other words, VCs do not have a strong understanding of how they make the investment decision.

H1: VCs do not accurately introspect about their decision criteria.

Although decision makers believe they thoroughly consider all relevant information, most typically rely on only three to seven factors (Stewart, 1988). Moreover, people are apt to report using far more information than they actually use (Slovic & Lichtenstein, 1971). Thus, as more information becomes available to a particular decision, the VC's ability to introspect about that decision process diminishes.

H2: More information decreases the VC's ability to accurately introspect about her/his decision process.

Likewise, the type of information available to the decision also impacts the VC's ability to accurately introspect. To this point, the hypotheses are centered on the cognitive side of the lens model (what factors the VC feels most comfortable using to make the decision). However, information cues on the task side (left side of Figure 1) represent the optimal set of decision cues. These cues best discriminate between eventual outcomes and are statistically derived based on past, actual ventures. Therefore, the optimal set of cues may not fit the VC's intuitive understanding of the decision, although these cues ideally best discriminate between eventual success or failure, these may not be the same factors that the VC intuitively uses. The optimal cues may not be in a form with which the VC is familiar or comfortable. Since intuition interferes with introspection, using the optimal cues may increase the VC's understanding of her/his decision process. In other words, the unfamiliarity with the nature of each optimal factor may cause the VC to consciously examine each factor independent of the other factors. As such, VCs who use optimal information factors in a controlled experiment should introspect better than those who use intuitive cues.

H3: Using optimal information factors increases the VC's ability to accurately introspect about her/his decision process.

If VCs do not have a clear understanding of their decision process, an interesting question may be whether they are consistent in applying that process. In other words, does the inherent complexity, or the many potential biases, or the intuitive nature of most VC decision making negatively affect the VCs consistency in applying her/his decision process? Although decision making consistency may vary over time (Brehmer & Brehmer, 1988), it is likely that VC decision making is relatively consistent in the short run. In other words, the VC is likely to judge investments in relatively the same manner from one month to the next. However, if that VC's decisions is compared from one year to the next, it might not be consistent is the sense that a new criteria is used to judge venture potential. If the decision process is inconsistent in the short run, the random nature of VC decision making would impede systematic attempts to understand it. If, however, these factors do not result in random decision making, then a lack of self-understanding may not inhibit efforts to study and improve VC decision making.

H4: VCs are consistent in applying their decision policies.

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Last Updated 4/2/97 by Cheryl Ann Lopez

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