Complexity of Leadership, Organizations and the Real Estate Industry: Disrupting Existing Systems

The existing anchored systems and layers of complexities involved in the interpretation of various leadership styles are discussed in this book. Smart power as a component within the systems in leadership styles is explained (Coutu, 2008; Nye, 2008; Nye & Armitage, 2007). Hard and soft powers are part of the smart power conceptualization. Academicians and learners are challenged to have firm gravitas from triggers and cameos emanating from leadership styles that are Disrupting Existing Systems (DES) elements. Leadership theories are disruptively challenged (Bass, 1985, 1996; Burns, 1978, 2006). Germinal and seminar leadership theories are used to conceptualize, interpret and rationalize why disruption of an existing system creates effective or ineffective leadership styles. Other elements in the systems are the value chains, supply chains, front and back offices, functional operable machines, disruptive technologies, manpower, capital or human capital and intellect that lead to optimal production of goods and services (Porter, 1980b, 1985, 1990; Porter & Stern, 2001). Part two dissects, analyzes, synthesizes and possibly amalgamates various organizational systems that were disrupted. Disruptions of the present systems in organizations such as Virgin Airways, Hewlett-Packard, UPS, Nokia, AOL Time Warner and Yahoo are used as case studies to explicate this phenomenon. Part three explains the housing market in California and in the United States. Current economy recession due to housing foreclosures in the United States is discussed. The United States contractions, recessions and recoveries periods are illuminated. Affordable housing in the sub-Saharan African region is also explained. For housing to be affordable and available for the middle-income populations worldwide, disrupting the anchored and entrenched existing policies remain a viable and pivotal option. In chapter 16, Professor Ossian Garraway uses narrative and statistical analysis to explain the phenomen