The role of human capital in loan officers' decision policies.

Second, the predominant finding in our study concerns the heterogeneity in loan decisions based on the similarity between the loan officer's human capital and the borrower's human capital. Specifically, loan officers with a greater level of specific human capital are more attracted to entrepreneurs with a high level of specific human capital than are loan officers with a lesser degree of specific human capital. Conversely, loan officers with more general human capital place less emphasis on the importance of the business owner's venture related experience (specific human capital). This finding offers interesting insight into the complexity of the effect of human capital on decision making. It extends the similarity-attraction paradigm from interpersonal assessments primarily within an organization to assessments of individuals across organizational boundaries. Future research can further explore the implications of this finding and whether this represents a bias that negatively impacts the performance of the loan officer and/or the performance of the bank.

Third, we found marginal support for our hypotheses regarding the effect of human capital on the use of contingencies in the loan officers' decision-making policies. Loan officers with more specific human capital appear to be more likely to place weight on the relationship between the level of business risk and the independence of the business owner's collateral offered. Surprisingly, loan officers with a higher level of education place less weight on the risk x financial position contingency. These findings pique our interest in the use of contingencies in the loan approval process. As human capital theory suggests that more human capital can help decision makers to process and make sense of more information and to reach decisions quicker (Wozniak, 1987), it may be beneficial for future research to consider more complex contingencies that require the decision maker to process greater quantities of data. The addition of time pressures to the loan officers' decision-making process may also provide increased understanding about human-capital effects.

Fourth, these findings regarding the decision policies of loan officers complement our understanding of the decision policies of venture capitalists (e.g., Shepherd, 1999). It is beneficial to increase our understanding of the decision policies of resource providers of both debt and equity capital. While venture capitalists focus primarily on the "upside potential" of possible portfolio companies, loan officers focus on the possibility of downside loss and are attracted to those businesses where business risk is low or where high business risk is mitigated such that it is not directly transferred to the bank, i.e., the risk the business will default on the loan. Future research may profit from a closer look at the similarities and differences between the effects of human capital on decision policies of bank loan officers versus venture capitalists as a result of differing perceptions of risk.

Fifth, studies have argued that there are liquidity constraints among small businesses and that they have problems obtaining the bank loans that they need (e.g., Storey, 1994; Walker, 1989), and we offer some insight into the loan approval process for small businesses. Many small businesses wish to pursue relatively risky investments but do not have the growth potential to qualify for venture capital investments or do not wish to share equity with outsiders. These small businesses are often dependent on bank loans in order to be able to finance these investments. Because banks have a limit to the potential upside of an investment (the interest) and because of the difficulty in obtaining reliable data about small businesses, banks are risk averse. While loan officers generally follow decision policies, they are susceptible to some variation in personal judgments based on their human capital characteristics. If entrepreneurs can increase their understanding of how loan officers make decisions, they may be able to improve the effectiveness of their financing strategies.

Possible Limitations

Not unlike other techniques, conjoint analysis has limitations, although throughout the design and administration of this study, attempts were made to minimize these limitations. Nonetheless, a few of the drawbacks should be addressed. As with any experiment, the issue of reductionism must be considered. Although our hypothetical scenarios of business loan requests had face validity, the loan officers are exposed to a decision situation that does not perfectly mirror the "real-life" decision. Such a difference could cause concern over the validity of the experiment. However, professional judgment itself often involves some abstract coding of the cues, similar to that provided by the conjoint task (Brehmer & Brehmer, 1988). Moreover, because the loan officers' lending decisions have a large "paper" component in the real world, correlation between the experimental task and the "real-world" decision should be even higher.

The experiment also forces loan officers to make decisions based upon the information presented in the scenarios. In reality, loan officers would have access to other information and use interactive due diligence to clarify and assess the information provided by the entrepreneur in his or her loan request. There is also the possibility that respondents could attach importance to attributes merely because they are presented in the experiment. However, this is probably not a substantial problem. First, the information on the decision criteria presented was justified by theory and had face validity. Second, although other information might normally be considered, such information is controlled for in the instruction of the experiment or is applied equally across all the loan officer's assessments. Third, attaching importance to a decision criterion just because it is presented is unlikely with the professional loan officers of our sample (as demonstrated by the insignificant effect of the strategic plan variable). Although these criticisms of conjoint analysis have merit and do represent limitations of the technique, our approach is consistent with that of other conjoint (e.g., Shepherd, 1999) and policy-capturing studies (e.g., Zacharakis & Shepherd, 2005).

While the theoretical arguments for the hypotheses are not country specific, care must be taken to consider potential country effects such as culture and institutional frameworks when generalizing results to loan officers in other countries. For example, banks in more regulated economies may enforce stricter rules on their lending officers than banks in less regulated countries. Replication of the results in other countries would be helpful in increasing the generalizability of this study.

Conclusion

In this article we used human capital theory to explore differences among the decision policies of loan officers toward loan applications by small businesses. We found that loan officers' decisions are heterogeneous and the variation can be at least partially explained by human capital characteristics. In particular, loan officers are likely to place greater value on the business owners' human capital attributes that are similar to their own.

We acknowledge that, for many small businesses, bank loans are an essential source of funding, and this study makes a contribution to the field by investigating this important process. Understanding the use of decision policies by loan officers can help better explain why some businesses obtain debt funding and others do not. This study complements the many analyses of the decision policies of venture capitalists in the entrepreneurship literature. These findings will hopefully provide scholars the motivation to conduct future research to explain variability in the decision policies of loan officers, of other resource providers (such as venture capitalists or business angels), and of entrepreneurs.

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