3 DATA AND METHODOLOGY
3.4 The creation of the Regional Entrepreneurship and Development Index
3.4.4 The penalty for bottleneck methodology
We have defined entrepreneurship as the dynamic interaction of entrepreneurial attitudes, abilities, and aspiration across different levels of development. One issue this definition raises is how to bring system perspective dynamism into the model. Configuration theory provides a useful way of thinking about this issue (Miller, 1987, 1996). Configurations are defined as “represent[ing] a number of specific and separate attributes which are meaningful collectively rather than individually.
Configurations are finite in number and represent a unique, tightly integrated, and therefore relatively long-lived set of dynamics.” (Dess et al., 1993, pp. 775-776.)
Two closely related theories, the Theory of Weakest Link (TWL) and the Theory of Constraints (TOC), provide us another way to view the interrelationship of the elements. These theories argue that the performance of the system depends on the element that has the lowest value in the structure.
According to the TOC, improvement can only be achieved by removing the weakest link, which constrains the performance of the whole system (Goldratt, 1994). The TWL claims that there is no perfect substitution among the elements of the system, only a partial one Tol and Yohe (2006), Yohe
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and Tol (2001). Whereas both principles are mainly applied in the production process and operation management, a few are applied in the humanities.6 According to the popular Six Sigma management theory, the production process can be improved by removing the causes of mistakes (weakest link) and reducing variation in the system (Nave, 2002, Stamatis, 2004). The notion of constraints is also present in the institutional literature, implying that economic development or growth depends on improving the binding institutional barriers North (1990), Rodrik (2008).
The weakest link postulate in entrepreneurship is also present. According to Lazear, entrepreneurs perform many tasks and therefore must be generalists—“jacks-of-all-trades.” (Lazear, 2004). Lazear claims that the performance of a venture depends on the entrepreneur’s weakest skills, therefore, developing a business can be achieved by improving the entrepreneur’s worst skill. We argue that the generalist perspective can be applied not only to entrepreneurial traits but to other aspects of business and entrepreneurship.
A practical application of the TWL and TOC theories is the penalty for bottleneck methodology. A bottleneck is defined as the worst performing link or a binding constraint in the system. With respect to entrepreneurship, bottleneck means a shortage or the lowest level of a particular entrepreneurial pillar, relative to other pillars. This notion of a bottleneck is important for policy purposes. Our model suggests that pillars interact; if they are out of balance, entrepreneurship is inhibited. The pillar values should be adjusted in a way that takes into account this notion of balance. After normalizing the scores of all the pillars, and equalizing the averages of the pillars, the value of each pillar of a region is penalized by linking it to the score of the pillar with the weakest performance in that region. This simulates the notion of a bottleneck; if the weakest pillar were improved, the whole REDI would show a significant improvement. Moreover, the penalty should be higher if differences are higher. From the perspective of either the configuration or the weakest link, it implies that stable and efficient configurations are those that are balanced (have about the same level) in all pillars.
Following Tarabusi and Palazzi (2004) and Szerb et al. (2011) we use the following penalty function:7
(7)
where is the modified, post-penalty value of pillar j in region iis the normalized value of index component j in region i
is the lowest value of for region i.
i = 1, 2,……n = the number of regions j= 1, 2,.… ..m= the number of pillars
A note that there is no objective criterion exists about the selection of the size or the calibration of the penalty. An intermediate solution seems to be useful for our purposes. It is shown in Figure 3.
6 In a public choice paper, Harrison – Hirshleifer (1989) present a model where the individual social composition function is constructed by taking into account the weakest link. The financial system can also be described by the weakest link postulate (Rajan – Bird, 2001).
7 For a more detailed description about the selection method and the properties of the penalty function see Appendix E.
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Figure 3. The penalty function, the penalized values and the pillar values with no penalty (ymin =0)
In this case the maximum penalty is 0.368. This maximum penalty that is around a third loss of the original value looks reasonable. Larger penalty values rearrange the ranking of the regions considerably by closing the REDI values to the minimum value pillar of that region. It is much more important to include the concept of penalization in the index building than the size of the penalty itself.
We suggest that this dynamic index construction is particularly useful for enhancing entrepreneurship in a particular region. Although one could argue that entrepreneurship is a horizontal policy concept with relevance across a number of traditional policy domains (e.g., trade policy, regulatory policy, fiscal policy), the application of the dynamic index construction would allow measurement of the effectiveness of different policy steps toward entrepreneurship. This method could rearrange the ranking of the countries for a particular feature. The level of the rearrangement would depend on the relative position of a region in terms of how its bottlenecks compare to the bottlenecks of the others. If every country has similar differences in terms of the features, then the ranking does not change much;
if one country is much less balanced than the others, then a lower rank for that particular country can be expected. The policy message is that a weak performance on a particular feature, such as a bottleneck, should be handled first because it has the most negative effect on all the other features.
There are two potential drawbacks to the PFB method. One is the arbitrary selection of the magnitude of the penalty. There is no research that can determine how big the penalty should be, which is why we applied a conservative estimate. Comparing the correlation between the GDP per capita and the REDI, calculated as the simple average of the indicators (r = 0.89) and the PFB methodology (r = 0.89), provides about the same correlation coefficient, with no statistically significant differences. The other problem is that we cannot fully exclude the possibility that a particularly good feature can have a positive effect on the weaker performing features. While this could happen, most of the entrepreneurship policy experts hold that policy should focus on improving the weakest link in the system. Overall, then, we claim that the PFB methodology is theoretically better than the arithmetic
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1
0 0,2 0,4 0,6 0,8 1
Penalized value Penalty function Values with no penalty
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average calculation. However, the PFB-adjusted REDI is not necessary an optimal solution, since the magnitude of the penalty is unknown.