CONSIDERATIONS ON THE DEVELOPMENT OF POLITICAL METHODS FOR ABSORBING UNCERTAINTY
There is no "standard" method used as a panaceum to reduce decision-making uncertainty. The technocratic approach on management is only valid on a free-competition market, with equal chances for everyone. In practice, this is a utopia. Knowledge-based economy changes the exogenous environment of decision, where the dominant aspects are, for example: data amount sometimes exceeds data-processing capacity, main competitors have the same information sources. A knowledge-based economy has also disadvantages, i.e. lower predictability. In many cases, the most important decisions and actions are not anticipated by an organization’s strategies. Political methods for uncertainty absorption play an important part in defining the socio-economic dimensions of a knowledge-based society. Ever more often, regardless of their size, firms are interested in taking part, either individually or together with other stakeholders (economic or social partners), in activities through which they can control and influence the future events that would impact the firms. Both vulnerability and opportunity can only be defined as a result of a proper evaluation of the factors involved in the activity of a firm and directly influencing the way in which the operational and organizational optimum is defined. By methods using fuzzy number to evaluate the quality of various relationships within and outside the organization the knowledge workers can generate solutions based on logical criteria in conditions of high uncertainty.
Qualitative assessments and optimal decision under uncertainty using rectangular fuzzy numbers
In crisis situations, uncertainty emerges as a distinct phenomenon, in which case we face both the ineffectiveness of most theoretical models of decision-making and the inaccuracy and incompleteness of available information. It is therefore necessary to intensify theoretical efforts and to apply interdisciplinary approaches and transfers of methods in order to construct a set of procedures and techniques that should contribute to curbing this phenomenon in decision-making processes. The transition from the state of crisis to the state of opportunity becomes the ground on which technocratic, structural, cultural and political approaches make a difference in managing. The qualitative analysis of the level of uncertainty provides an optimal insight into the best management techniques and methods that may contribute to achieving development objectives under crisis conditions. To conduct such an assessment process, we propose the use of rectangular fuzzy numbers. In this paper, first we develop a personal analysis of the notion of rectangular fuzzy numbers with an associated variable center of gravity and specific mathematical operations. Our research continues by the theoretical and applicable development of the "optimistic method (max-max)". Acknowledgement This paper is supported by the Sectoral Operational Programme Human Resources Development (SOP HRD), financed from the European Social Fund and by the Romanian Government under the contract number POSDRU/89/1.5/S/56815.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.