Application of statistical physics approaches to complex organizations

The first part of this thesis studies two different kinds of financial markets, namely, the stock market and the commodity market. Stock price fluctuations display certain scale-free statistical features that are not unlike those found in strongly-interacting physical systems. The possibility that new insights can be gained using concepts and methods developed to understand scale-free physical phenomena has stimulated considerable research activity in the physics community.; In the first part of this thesis a comparative study of stocks and commodities is performed in terms of probability density function and correlations of stock price fluctuations. It is found that the probability density of the stock price fluctuation has a power law functional form with an exponent 3, which is similar across different markets around the world. We present an autoregressive model to explain the origin of the power law functional form of the probability density function of the price fluctuation. The first part also presents the discovery of unique features of the Indian economy, which we find displays a scale-dependent probability density function.; In the second part of this thesis we quantify the statistical properties of fluctuations of complex systems like business firms and world scientific publications. We analyze class size of these systems mentioned above where units agglomerate to form classes. We find that the width of the probability density function of growth rate decays with the class size as a power law with an exponent beta which is universal in the sense that beta is independent of the system studied. We also identify two other scaling exponents, gamma connecting the unit size to the class size and gamma connecting the number of units to the class size, where products are units and firms are classes. Finally we propose a generalized preferential attachment model to describe the class size distribution. This model is successful in explaining the growth rate and class size probability density functions. The model provides a clear understanding of the emergence of: (i) Zipf's law for the class size distribution; (ii) The empirically observed exponential cutoff of Zipf's law; (iii) The influence of initial conditions on class size probability density function; (iv) The probability density function of the growth rates.