Team Conflict – Organizational Conflict

I have a new open source book chapter that has just been published. The reference for this book chapter is listed below:

John R. Turner, Rose Baker and Mark Morris (August 1st 2018). Complex Adaptive Systems: Adapting and Managing Teams and Team Conflict, Organizational Conflict Ana Alice Vilas Boas, IntechOpen, DOI: 10.5772/intechopen.72344. Available from: https://www.intechopen.com/books/organizational-conflict/complex-adaptive-systems-adapting-and-managing-teams-and-team-conflict

The link for this book chapter can be found:

https://www.intechopen.com/books/organizational-conflict/complex-adaptive-systems-adapting-and-managing-teams-and-team-conflict

Abstract:
Complexity comes from dramatic structural changes to organizations and governments such as globalization, global competitions, workforce diversity, and continual innovations. Complex adaptive systems (CAS) are organizations that are a composite of the interconnected whole. Teams must manage and operate in emerging ecosystems, understand factors that lead to team effectiveness when managing and facilitating teams and team conflict, and understand the development of conflict models. This chapter provides an overview of teams, CAS, conflict stages, and conflict models. This chapter presents adaptive leadership as one leadership style that offers organizations with the capabilities of reacting to changing environments quickly. Adaptive leadership offers a prescriptive approach for managers and leaders to follow when dealing with organizational conflict while operating in today's complex and global environment.

Keywords:
teams, complex adaptive systems, conflict, intergroup conflict, intragroup conflict, conflict management

Leadership Theories Survey

Within the leadership paradigm there are a number of different leadership theories identified. There are leadership theories based on the leader’s personality (trait theory) and specific style (style theory). Others identify leadership as the interchanges between the leader and followers (leader-member exchange, LMX), as depending on the situation (situational leadership) and contingent on the environment and circumstances (contingency leadership theory). Providing rewards/punishment for performing one’s task ( transactional leadership theory) and providing moral and ethical vision for the followers (transformational leadership theory). Flashy and charismatic leaders are also identified (charismatic leadership theory) as well as those that provide service for the followers they serve (servant leadership theory). 

As a quick and non-scientific survey I am inviting everyone to participate in a quick survey on the above leadership theories. This survey asks for one or two words/adjectives that best describe each of the above theories. Results from this survey will be presented at a later time, granted enough participants volunteer and participate in the survey.

The link for the survey is provided below. Thank you in advance for participating in this survey.

https://unt.az1.qualtrics.com/SE/?SID=SV_5pBoL0lv8f4wQrr

Theory Worth Considering

I try to emphasize, to my students in Theory Development, the importance theory plays in research and how fields of study (disciplines) are defined by the theories they produce.  One example can be found in England's new theory of life from Wolchover's (2014) article titled A New Physics Theory of Life in Quanta Magazine.

According to England's theory (Wolchover, 2014), Darwin's theory of natural selection may be more than one organism's ability to adapt better than another organism. England's theory expands the second law of thermodynamics stating that one organism may be more capable of dissipating energy than other organisms, thus leading to Darwin's natural selection. 

In Wolchover's (2014) article, the following was mentioned regarding England's theory:

"England's theoretical results are generally considered valid. it is his interpretation - that his formula represents the driving force behind a class of phenomena in nature that includes life - that remains unproven. But already, there are ideas about how to test that interpretation in the lab" (para. 10).

Theories must be relevant and rigorous (Van de Ven, 2007). Relevance determines how well the theory addresses real-world problems or issues (Van de Ven, 2007), whereas rigorous theories meet the requirements of being empirically validated and challenged. In the example provided above, England's theory has been accepted by those in the fields of physics, biology, chemistry, and others. By being accepted other researchers do not necessarily have to agree with the theory, however, they do agree that England's theory holds merit and should be subjected to further testing. This is evident from the last sentence in the above quote stating that 'there are ideas about how to test' this theory. 

This theory has meet two thresholds that every new theory needs to meet in order to be considered relevant: it has been deemed worthy to consider by other researchers and it's validity is being subjected to further empirical testing. This begins the theory validation / refinement stage which begins to place this theory as a formal theory for the field of study that stands behind this theory.  

Formal theories are constantly being tested and challenged through research. Sometimes formal theories are replaced with new theories that better explain current phenomena, other times formal theories withstand the continuous empirical scrutiny. In Wolchover's (2014) article there are two examples of this continuous refinement process. The first is the beginning phases of a new theory that is being exposed to empirical tests. If the empirical tests provide support for England's theory then this theory will begin to become a formal theory. Secondly, formal theories are constantly being tested and refined, ultimately providing the best description of a phenomenon. One example of this can be found by the use of the second law of thermodynamics that was being utilized in the development of England's theory. The second law of thermodynamics is being tested as well as being validated from this line of testing.

All-in-all, when presenting a new theory one needs to consider is it worth considering and by whom?

References:

Van de Ven (2007). Engaged scholarship: A guide for organizational and social research. New York, NY: Oxford University Press.

Wolchover, N. (Jan. 22, 2014). A new Physics theory of life. Quanta Magazine. Retrieved from http://www.quantamagazine.org/20140122-a-new-physics-theory-of-life/?utm_source=pocket&utm_medium=email&utm_campaign=pockethits

Hierarchical Linear Modeling: Testing Multilevel Theories

In the previous post I provided information relating to a recent book chapter. This book chapter describes different techniques in developing and disseminating multilevel theories. In this article I present a new publication that identifies, briefly, how to test multilevel theories. This main statistical analysis methodology is commonly referred to Hierarchical Linear Modeling (HLM; Raudenbush & Bryk, 2002), but is also referred to multilevel regression analysis or random coefficient regression modeling (Cohen, Cohen, West, & Aiken, 2003), multilevel models (Hox, 2010), mixed models and random effects models (McCoach, 2010).

The online reference for the new article is provided below. This article will be available in print at the beginning of 2015.

Turner, J. R. (2014). Hierarchical linear modeling: Testing multilevel theories. Advances in Developing Human Resources [Published Online]. doi:10.1177/1523422314559808

Part of the structured abstract is provided below:

The Problem: While nested structures occur naturally in organizational and educational settings, past research has failed to recognize these nested structures. Ordinary least squares (OLS) methods assume independence of observation, fixing the intercepts and slopes across all groups. By not accounting for nested structures, errors of inference can occur with the risk of compromising the validity of the results.
The Solution: As new theories become more complex multilevel representations of phenomena, testing these complex theories require hierarchical linear modeling (HLM). HLM provides human resource development (HRD) practitioners with a better method to test multilevel theories while taking into account nested structures, providing a more accurate representation across the different levels.


References:

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). New York, NY: Routledge.

Hox, J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge.

McCoach, B. D. (2010). Hierarchical linear modeling. In G. R. Hancock & R. O, Mueller (Eds.), The reviewer's guide to quantitative methods in the social sciences: revise, accept, reject (pp. 123-140). New York, NY: Routledge.

Raudenbush, S. W., & Byrk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.

Building and Disseminating Multilevel Theories

New Book Chapter just published relating to building and disseminating multilevel theories.

Turner J., Firmery-Pretrunin, K., & Allen, J. (2014). Developing multilevel models for research. In V. C. X. Wang (Ed.), Handbook of research on scholarly publishing and research methods (p-p. 467-493). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-7409-1

Abstract:

In the past, a large number of research efforts concentrated on single-level analysis; however, researchers who only conduct this level of analysis are finding it harder to justify due to the advancements in statistical software and research techniques. The validation of research findings comes partially from other’s replicating existing studies as well as building onto theories. Through replication and validation, the research process becomes cyclical in nature, and each iteration builds upon the next. Each succession of tests sets new boundaries, further verification, or falsification. For a model to be correctly specified, the level of analysis needs to be in congruence with the level of measurement.  This chapter provides an overview of multilevel modeling for researcher and provide guides for the development and investigation of these models.