The dynamics of competition

Consider an environment in which competing organized structures evolved because of the appearance of the first self-replicating molecules described earlier.

The next step is to analyze the competition between various organized structures such a supra- molecular structures like organism or, for that matter, organizations such as firms. Clearly, we need to take into account at least the following features:

x Reproduction or communication of information.

x Introduction of variation in information by imperfect copying.

x Translation of the information in the structure or organization corresponding to it.

x Competition between the various organized entities.

x Selection of more competitive entities by competition for scarce resources.

To illustrate this in more detail we reproduce Fig. 6.8 as fig. 6.11 for the reader’s convenience.

The information needed to reconstruct a complex dissipative structure, such as a macromolecule, an organism, a human being, a technology or competence, an industrial organization, an

Information

Organization Variation

Resources

Competition Selection

Fig. 6.11. The dynamics of competition.

75 economy, fully characterizes it. An observer of the organized structure, even if he is an observer inside the structure, does not avail of all the information to characterize the detailed microscopic workings of the structure. The statistical entropy of the macroscopic picture quantifies this lack of information. In a living organism, an observer without any additional information would need the amount of information allowing him to select the specific DNA structure from all the possible combinations corresponding to the size of the genome.

Note 6.3

The amount of information needed to understand the details underlying the genetic structure of even a relatively small organism like the enteric organism E. coli is very large indeed. If we take into account a genome size of 5.10⁶DNA bases, and realize that at each position four nucleic acid “letters” can appear, the amount of information needed would be 10,000,000 bits.

In the case of an industrial organization, this information is more difficult to grasp. It includes all information needed for the operations of the company, such as the information contained in its products, its captive market knowledge, the blueprints of its tangible assets, the information characterizing its competence and technology base, the information regarding its strategies and future plans. Some of this information exists in a written form or in computer files, some of it is in the heads of its human resources, tacit knowledge, some of it represents cultural aspects of the company.

When considering the human genome we note that it contains 6,000,000,000 bits of information.

This corresponds to a choice of one out of the order of 102,000,000,000 DNA-base combinations.

Even if in a much simpler case, the magnitude of the selection problem becomes apparent. A single hemoglobin molecule, the oxygen carrying protein in blood, consists of four chains of amino acids (polypeptides) twisted together. One of these chains contains 146 amino acids. Each amino acid is one out of the natural 20 that occur in proteins in organisms. The total amount of possible combinations is equivalent to 10¹⁹⁰, this compares to the 10¹⁰⁰ that could simultaneously exist in the universe if the mass present in the universe allows filling it up in a closest packing of molecules.

Taking the estimated mass present in the universe into account, the number of molecules that can simultaneously exist decreases to about 10²³ , minute if compared to the total number of

Fig. 6.12. Exploiting a source of economic value by products of increasing sophistication.

1

2

3 Harvested

Economic Value

Time

76

combinations possible.

If we extrapolate this discussion to an organism or an enterprise, the significance of the limitations to the magnitude of the amount of information that we can obtain, becomes apparent (Eigen (1971)).

As soon as a potential source of economic value appears in the system, such as the demand for a product, a development takes place by which entities appear that satisfy the demand and feed on the economic value associated with it in an increasingly sophisticated way. Generally, this also leads to increasingly potent sources of economic value to harvest. Typically, a development as depicted in Fig. 6.12 takes place.

Fig. 6.12 depicts a typical life cycle of the way in which the supply of products develops. A single innovative information set triggers a development in which, after it emerges, it goes through a phase of growth into maturity and final decay. This is the trajectory labeled 1 in Fig 6.12. The phases of emergence and growth represent the gradual, evolutionary, phase of the development. The decay is often results from a second innovation going through the same life cycle that replaces the existing one due to its increased sophistication. This development is labeled 2 in the figure. The emergence of the new, more competitive structure, induces an

“unexpected” revolutionary change in the evolution of the system. This process repeats again when an additional innovation emerges.

There exist a number of additional complications when we apply the theory to systems of a more involved complexity. The first one stems from the observation that, in almost all advanced systems, the information coding for the dissipative structure and the physical form of the dissipative structure are different entities. The information coding for the dissipative structure acts as a blueprint for the actual form of the structure. This leads to questions of cause and effect.

What causes the formation of complex structures? Is it the information or is it the functional structure? This question becomes meaningless once the evolution progresses towards a point where the information carrier and the functional structure divorce. Once the cycle depicted in Fig. 6.11 closes, the evolution becomes truly cyclical and both the information set and the functional structure select simultaneously. Both the information set and the functional structure compete with other information sets and structures. This also changes the environment. Both the environment and the structures become cause and effect. In addition, the concepts of chance and necessity appear in the theory. Evolution of increasingly complex structures is a necessity if the macroscopic branch becomes unstable. If the information coding for the structure becomes large the exact path the evolution takes becomes fundamentally unknown because of the vast number of possibilities. The path becomes unknown to an outside observer that has a reduced information picture; it is also unknown to the actors inside the system as they may have more information but can never obtain complete information.

The divorce of the information and the functional structure is an example of a division of labor type of specialization. If these functions become separate, better-suited structures develop. In fact, division of labor is a characteristic of industries.

A feature that is also of great interest is the balance between stability and complexity. On the one hand, in system of increasing complexity the number of possible innovations that challenge the existing structures increases. On the other hand, it appears that, certainly if the structure has aged, only a large fluctuation in terms of competitive advantage allows displacement of the entrenched structure.

The foregoing discussion highlights the intimate relation between the structures and the environment and vice versa. This introduces a new problem in modeling. One of the first steps in modeling is to decide what the environment is and what the system is. In modeling, we assume the environment given and this assumption becomes dubious if the system and the environment start to interact and become part of a cycle. This results in the need to include an increasing part of the environment in the system, otherwise the modeling exercise becomes futile and leads to

77 erroneous predictions. To the opinion of the author, this complication applies to many of the models used in the analysis of the socioeconomic system. Our discussion also reveals that sustained evolution becomes inevitable in an environment where sufficiently large sources of economic value exist or develop. To complete this chapter we briefly return to biological evolution and its relation to elements of human society such as industries and economies. We also discuss the relevance of exogenic evolution.