Managing SADC Roads Agencies in the New Millennium: The Role of Road Asset Management Systems
The management of the Southern African Development Community’s (SADC) road network is a complex task which is often influenced by a variety of factors – technical, financial, social and political – which all enter into the decision making process at various levels of their roads agencies. In such an environment, the determination of optimal strategies requires the use of a rational “systems” approach to road asset management. This paper outlines the road management strategy that is being pursued in a number of countries in the SADC region. It then illustrates how these systems are being used at various levels of application to achieve the desired objectives of the road agency.
An Empirical Assessment of the Success of Road Asset Management System in Tanzania and Its Economic Value in Managing and Planning for Roads Pavement
The deployment of Information Communication Technology in the Road sector has contributed positively towards achieving the national goal of ICT for infrastructure development. However, the deployment of ICT software for Road infrastructure in underdeveloped countries has been done with duplication of efforts contributing to software failure. This study aimed in evaluating the effectiveness and economic values of the Road Maintenance Management System in Tanzania.  The study deployed System Usability Scale Framework in 26 regions of Tanzania, and Kruskal-Wallis test was used for significance testing. The result indicates positive response of adopting and scaling the Road Maintenance Management System to all 26 regions in the country with R2=0.863. The usability of the system remains steady for almost three years from 2017 to 2019. The economic value of system is found to be above average (61%), while the value for money is found to reach 76.5% of the expectation. It is therefore concluded that the use of ICT in planning for Roads Maintenance increases efficiency in delivery critical factors that facilitated decision making in road planning and also improves specific services delivery in government efficiency.
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.