Russ Marion

Leadership in complex organizations

Abstract This paper asks how complexity theory informs the role of leadership in organizations. Complexity theory is a science of complexly interacting systems; it explores the nature of interaction and adaptation in such systems and how they influence such things as emergence, innovation, and fitness. We argue that complexity theory focuses leadership efforts on behaviors that enable organizational effectiveness, as opposed to determining or guiding effectiveness. Complexity science broadens conceptualizations of leadership from perspectives that are heavily invested in psychology and social psychology (e.g., human relations models) to include processes for managing dynamic systems and interconnectivity. We develop a definition of organizational complexity and apply it to leadership science, discuss strategies for enabling complexity and effectiveness, and delve into the relationship between complexity theory and other currently important leadership theories. The paper concludes with a discussion of possible implications for research strategies in the social sciences.

Complexity Theory and Al-Qaeda: Examining Complex Leadership

(2003). Complexity Theory and Al-Qaeda: Examining Complex Leadership. Emergence: Vol. 5, No. 1, pp. 54-76.

Higher Education Leadership Roles in Knowledge Processing.

Purpose – To examine the critical roles of leadership in higher education and to define how such roles enable an environment that embraces the demands of a knowledge‐based organization.Design/methodology/approach – Through interviews with executive leadership in several higher education institutions, the ontology of knowledge management was established and the methods by which knowledge gaps were resolved were explored. The question of how leadership behaviors, policies, and programs enable or inhibit knowledge‐processing activities was analyzed.Findings – Leadership influence in six key areas emerged as significant in the study: environment manager, network manager, policy manager, crisis manager, knowledge gap manager, and future leader preparation. The authors confirmed that the leader has tremendous control over the knowledge‐processing environment and the role of leadership has broader influence than the resolution of knowledge gaps.Originality/value – By understanding leadership roles in knowledge m...

Complexity in Organizations: A Paradigm Shift

Summary. Complexity theory is applied to organizational sciences in this paper. The implications of this application are significant, so much so that they signal a paradigm shift in the way we understand organization and leadership. Complexity theory alters core perceptions about the logic of organizational behavior and, consequently, “discovers” the significant importance of firms’ informal social dynamics (informal behaviors have long been treated as something that should be suppressed or channeled). This altered perspective has implications for how we coordinate, motivate, and lead in firms. A complexity view of organizations is particularly useful and germane in light of recent movements among industrialized nations toward knowledge-based, rather than production-based, economies.

Chapter 16 Complexity and Strategic Leadership

The current strategic leadership literature tends to advocate a leader-centric (upper-echelon) approach to strategy, one in which the leader positions the organization competitively within an environment. Based on complexity theory, we argue that strategic leadership in a fast-paced environment works to organize both the environment and the organization in ways that enhance the firms adaptability, innovativeness, and fitness. We propose a two-pronged strategy: Foster cooperative relationships with the organizations environment, and enable adaptive organizations that are “partners” in the strategic leadership function.

“Breaking the frame” even farther: complexity science and lampe theory

Mackenzies LAMPE theory provides a new view of leadership that is multi-level, processual, and reflective of leadership as it actually occurs in practice. While we see this approach as representing a much needed frameshift for leadership research, we believe Mackenzie may be able to “break the frame” even farther by incorporating elements of complexity science into his thinking. We suggest how complexity science might help Mackenzie flesh out his ideas about distributed leadership, as well as consider leadership that is not only about alignment and control but also about enabling and releasing informal, interactive dynamics within the organization.

Academic Integrity from China to the U.S.: The Acculturation Process for Chinese Graduate Students in the U.S

The ethics-related beliefs of Chinese international graduate students are heavily influenced by their academic cultural background, and given the nature of that culture, they often face challenges when adapting to the U.S. academic environment. This qualitative study examines Chinese graduate students’ perceptions of the differences between Chinese and American academic integrity practices and the effects of those differences on their ethical practices and adaptations in a graduate program in the United States. Data were collected via semistructured interviews in a public university in the United States. Findings suggest that perceptions of academic integrity in Chinese universities are influenced by Confucian philosophy, collectivist assumptions, and a resultant convenience mind-set. These cultural premises clash with academic expectations in the United States. Participants describe how they, and their Chinese peers, navigate U.S. integrity standards and provide recommendations for ways that U.S. schools can help them better adjust. We expand on those and provide recommendations for university personnel.

Modeling the Effects of Educational Resources on Student Achievement Implications for Resource Allocation Policies

The convergence of standards, accountability, and school finance policies necessitates a systematic rethinking about how state-level resource allocation policies can be created to distribute resources in a manner that provides equal educational opportunities for all students. Given the demand for policymakers to distribute adequate resources to improve schools’ capacities to increase student learning, there is a need for evidence detailing the effects of those educational resources on student achievement. Therefore, the purpose of this study was to discern the effects of educational resources on student achievement using structural equation modeling. Using data from a southeastern state in the United States, the authors offer resource allocation policy recommendations that align with the state’s constitutional obligation to provide equality of educational opportunity, particularly for students living in poverty.

Evaluating Complex Educational Systems with Quadratic Assignment Problem and Exponential Random Graph Model Methods

This chapter has three objectives: (1) to describe how social network analyses (SNA) can be used to explore complexity dynamics in education; (2) to provide a primer on SNA methods; and (3) to explore statistical procedures for hypothesis testing with SNA. SNA has experienced increasing popularity in recent years, but resources available to researchers wanting to learn about this methodology are sparse. That which is available typically fails to link SNA to complexity theory, although this would seem an obvious context. This chapter briefly describes major principles of complexity theory and how network analyses are useful for exploring social dynamics. We then explain what SNA is, the types of analyses it performs, and its various uses. This section delves into issues such as designing SNA analyses, data collection procedures, and converting non-matrix data for use in SNA. Lastly, the chapter describes statistical procedures for analyzing network data. In particular, we explain how to conduct multiple regression quadratic assignment procedures and p* to test hypotheses about network dynamics. Issues of using network coefficients with traditional, variable-based statistics are discussed. Examples of applicable research questions and research studies are provided to help readers formulate questions and research designs.