THIS CHAPTER WILL DISCUSS:
1. How permanent characteristics are related to members' perceptions of leadership.
2. Lewin's distinctions between democratic, authoritarian, and laissez faire styles.
3. The later distinction between task and maintenance styles.
4. The influence of situations on leadership style.
5. The ways in which traits and situations interact to determine leadership effectiveness.
We have purposely delayed discussing group leadership until this point because leadership is a complex subject best approached after one has a grounding in the other topics that we have examined, such as conformity and power. However, the time has come for us to approach the topic head on and discuss it fully.
In this chapter, and the next, we will present a series of theoretical approaches to leadership. In this chapter, we will examine approaches in which communication is not given a central role in explanations for how leadership works. In the next, we will describe approaches that do give communication a critical role in explanations. To a greater or lesser extent, every approach we will discuss has made a contribution to our knowledge about leadership. It is best to examine all the theories to understand fully what scientists know about leadership. Interestingly, hindsight helps us to realize this. The contribution that each theoretical viewpoint made was not always apparent to the scientists who used them.
First, before we go any further, we need to define leadership.
What Is Leadership?
When we began examining groups in Chapter 1, we needed to define the term because scientists use different perspectives to study small groups, and each perspective has its own view of what a group is and how it works. We now need to define the term "leadership" for similar reasons. To reach our definition, we shall examine various perspectives in turn. Each has its own view of leadership.
Relational Definition Let us begin with the relational point of view. As we described earlier, this perspective holds that a group is a collection of people with interdependent goals. Members are able to promote one another toward the goals that each has. How would the concept of leadership fit into this idea?
We can use a matrix to diagram how the relational perspective defines leadership. Recall from Chapter 5 how we are able to represent the concept of "behavior control" through the use of these diagrams. Consider a two-person group, in which members Harold and Tim must choose between two options. Their possible choices are illustrated in the matrix shown in Figure 10.1. As you can see, each has some behavior control over the other.
According to the relational perspective, one of the men is the "leader" in the matrix. Let us describe why this is so. Both Tim and Harold receive their best returns when they make the same choice, both choosing "Yes" or both choosing "No." It is true that Tim has a slight preference for the simultaneous choice of "Yes." Similarly, Harold would be happiest if both group members decided on "No." Nevertheless, neither "Yes" nor "No" is intrinsically a better choice for either man. Something different happens, however, when the men make opposite choices. Tim will always receive some profit, no matter what. This is not true for Harold. Instead, Harold actually loses "points" when the men do not agree. This means that each choice affects Harold more than it affects Tim. In essence, Harold needs to try not to conflict with the choice that Tim makes. Tim has no such worries.
Thus, we can say that Tim has more behavioral control over Harold than Harold has over Tim. Tim has a power "differential." Tim can use this differential, for instance, by always choosing "Yes." This means that he rewards Harold for choosing "Yes" but punishes him if he chooses "No." If Harold does rebel and chooses "No," Tim still receives a score of two. Harold would prefer that both men decide on "No," but he will probably follow Tim's lead and say "Yes" in this situation. According to the relational perspective, the outcome is that Tim will be "leading" Harold. The matrix has shown how one person can be a "leader" over another.
This approach implies that a group's leader is the person who is able to act the most independently in relation to the other group members. He or she has the most to win and/or the least to lose from group interaction. This concept matches the intuitive notion of "power." However, this is not our natural idea of "leadership." For instance, we know that when a company goes bankrupt it is the owner who has the most to lose. Thus, the relational definition may not imply a satisfying definition of leadership. Thibaut and Kelley (1959) examined the relational approach to leadership.
According to the interactional approach, a group is a collection of individuals whose interaction has become interdependent. Let us again use the example of a two-person group to illustrate this idea. The two members in this situation can either ask each other questions or make comments to each other. Figure 10.2 is a diagram of the interact probabilities of the group.
As you can see, for whatever reason, Person B always makes comments after Person A asks questions. In contrast, when Person B asks something, Person A never replies with comments. Instead, Person A responds to questions by posing further questions. When this happens, his or her new questions receive comments again from Person B.
The result of this is that Person A appears to control the conversation. This is because he or she is "leading" the discussion, from an interactional perspective. Person A can control the conversation by refusing to answer questions. A police interrogation is an example of this kind of conversation. The interrogator is the "leader," according to the interactional point of view. He or she leads by controlling the interaction that can take place. This is a different definition of leadership than the one that the relational perspective provides. However, as with the relational definition it appears more in line with our idea of "power" than "leadership." This ut also may not imply a satisfying conception of leadership.
As you recall, a scientist who has a structural perspective conceives of a group according to the roles that members play. In a group, each person functions in a certain capacity. For example, a group might have "jokesters" or "organizers" and so on. In addition, the theorist with this viewpoint would expect each role to fulfill certain group norms. The norms describe the behaviors expected from a group member with that role. For example, the jokester should make people feel relaxed, the organizer should give the group an outline of tasks, and so on.
How does this perspective define leadership? The implication of the structural point of view is that groups need to have a member who plays the role of "leader." This person fulfills the group norms regarding leadership. In essence, he or she performs the behaviors that leaders are supposed to fulfill. For example, a leader may speak first at meetings, call for votes, and give praise to the group. This perspective is probably closest to how we naturally conceive of leadership.
Functional Perspective There is a functional version of the structural perspective, as we have discussed previously. The functional viewpoint maintains that a group is a social system. The system has certain goals, such as survival and goal attainment. To fulfill these goals, the social system must contain a set of properties. For example, a group might have the property that it contains four members who are very good at math. These properties have to be capable of performing certain "functions." Functions, like norms, are behaviors. The functions are necessary for the group to attain its goal. For instance, the group with members who are good at math may have the goal of winning a math prize. The talented members must function in a way that will help the group succeed at this goal.
Researchers with this perspective believe that some of the necessary functions in groups are leadership functions. Therefore, groups must exhibit the appropriate
properties so that the groups can perform these functions. What properties can fulfill the leadership behaviors? In essence, a group needs to have the property of a member or members who lead. Leaders could do things such as direct meetings and create rules. In this way, the group could fulfill its necessary leadership functions and help the group reach its goals.
Overall, the functional variant maintains that leaders are able to perform certain functions to help groups succeed. The functional viewpoint is an extremely valuable approach to leadership, as our discussion will reveal.
According to this point of view, a group is a collection of people who react to some force. Something drives or prompts them to act as they do. Scientists who hold this viewpoint think of a leader in a group as the person or persons associated with the force that guides the group. He or she either provides the drive itself or determines the means for satisfying it.
The perceptual perspective maintains that a group is a gathering of individuals who define and perceive themselves as a group. This group perception determines who is the group's leader. In essence, the members define a person as leader, and he or she then is so.
As you might expect, different perspectives have definitions of leadership that vary greatly. Which definition will we use as we examine the topic in this book? The answer is that we will not use a precise definition. Instead, we will be using all of the concepts that we have discussed above. However, we will rely on them to varying degrees because some of the perspectives we have discussed are more appropriate for our discussion than others. We can make some overall comments here as to why this is so.
The relational and interactional perspectives, as we have shown, do not sugest satisfactory definitions of leadership. Perhaps because of this, neither has had a great deal of influence on specific theories and research concerning leadership. On the other hand, the remaining four viewpoints have had a definite impact on the study of leadership. We will be making many references to the definitions that all four perspectives provide. Each has been important, in different ways, for the research that we shall examine.
THE TRAIT APPROACH TO LEADERSHIP
The first time that researchers attempted to use a scientific method to study leadership was in the 1920s. Taken as a group, these early scientists worked with a basic hypothesis regarding who leaders were. They assumed that leaders were people with personal characteristics, or traits, that set them above and apart from nonleaders. This assumption was consistent with a philosophical view that was popular in the nineteenth century.
The "Great Man Theory"
The 1800s philosophical outlook that created the trait approach is known as
the "Great Man Theory of Leadership." The theory states that certain people are born to be leaders. They have a special quality that sets them apart from "common" folk. The idea is that the great leaders of the world would have assumed a leadership role at any place or time in history. Thus, Julius Caesar or Napoleon would have been influential figures anywhere, at any time. Note that the "Great Man" title reflects the thinking of the times. Back then, most people did not consider women capable of possessing leadership qualities. We use the title here only because it is historically correct.
The Early Scientific Approach
In the 1920s, various leadership researchers occasionally took the "Great Man" hypothesis literally. They searched for characteristics that differentiated between leaders and followers. They thought that there were certain qualities that only a leader could possess, such as charisma. Usually, however, the scientists looked at the characteristics that all people possess to some degree. They then would cautiously attempt to discover which traits were particularly evident in leaders.
It was true that the idea that certain people would always be leaders, no matter what, intrigued researchers. However, it was not just the nineteenth century "Great Man" theory that caused scientists to examine leadership. In the 1930s, fascist governments in Europe and Asia grew increasingly belligerent. As they did so, the democracies of Europe and North America became fearful of impending war. In times of war, nations need leaders. They also need to find them quickly. Hence, these early scientists wanted to devise a psychological test that would allow them to recognize good leaders easily. If they could create such a test, countries could use it during the impending years of crisis. A leadership test would make it a relatively simple task for a country to place gifted people into the necessary leadership roles.
Early scientists created various types of leadership tests that they hoped would fulfill this need. Each test attempted to create a method to predict who would be a leader and who would not be. Before we describe the results of these tests, it is useful for us to discuss how the researchers performed their studies.
These early researchers were interested in discovering which traits contributed to a person's degree of leadership. To do this, they decided to compare measurements of leadership scores with measurements of other traits. The scientists used a particular method to compare various measurements. This technique allowed the researchers to discover how the different measurements were related. We shall discuss their methodology step by step.
For example, five people have taken an IQ test. The researchers designed
the IQ exam to measure the characteristic of "intelligence." The average score on this test is 100. A score above this mark means a person is more intelligent than the average person. The test participants have also taken an exam to measure leadership. The leadership test has 10 items. Their scores on the two examinations are shown in Table 10.1.
# of Leadership Items Correct
Positive correlation. As you can see, as one column increases, the other also increases. We call this relationship between the two columns a positive correlation. In addition, whenever the IQ score increases by 20 points, there is a corresponding increase of two correct items on the leadership test. Thus, the relationship between the two tests is perfect. They have an exact correlation of 20 IQ points for every two correct leadership items.
We could take this result and conclude, for instance, that an IQ test can measure leadership without error. We shall represent this relationship between IQ and leadership with the number +1.0.
Negative correlation. The study also created a column with the number of items that the participants answered incorrectly on the leadership exam. The researchers examined the relationship between the IQ scores and this new column. The data are shown in Table 10.2.
# of Leadership Items Wrong
In this case, there is still a perfect relationship between the two columns of data. Whenever the IQ score increases by 20 points, the number of leadership incorrect answers decreases by two. This is again a perfect correlation, but it is a negative one. As one score goes up, the other goes down. We use the number -1.0 to represent this perfect, negative correlation. Of course, the number of correct and incorrect answers on the leadership test are, by definition, inverses of each other. Hence, that the perfect negative correlation matches the perfect positive one, is no surprise in this research study.
Degree of correlation. The point is that there is a difference between the number of a correlation value and the sign of that value. The number shows the degree of correlation and it reflects the research data findings. The sign, on the other hand, reveals the way in which researchers have chosen to define the columns. Something has a "+" or a "-" value based on which data the scientists have chosen to examine together. The scientists essentially can control which research findings they compare and, in turn, whether the correlation has a negative or a positive sign. This means that scientists often are not very surprised about what sign a correlation might have.
Instead, it is usually the degree of association that researchers find of most interest. Whether positive or negative, this number is what reveals how well the data columns relate. This is information the scientists want most.
No correlation. Finally, the study compared one last pair of example columns as seen in Table 10.3. As you can see, there is no relationship between IQ levels and artistic ability. The former does not measure the latter. In this case, we can represent the relationship between these columns with the number 0.
Score on Artistic Ability Test
The correlation coefficient. What do scientists call a number, such as +1.0 or -1.0, that shows the degree of correlation? Such a number is a "correlation coefficient." It is a measure of the relationship between two sets of research data. Any coefficient has a possible range of +1.0 to -1.0. In "real life," correlations will never be perfect, as our first two examples were. A measurement of "1.0" is practically impossible. The only way researchers can achieve a perfect correlation is if they mistakenly relate two alternative measures of the same thing. For instance, they might accidentally compare columns of the number of correct items and the number of incorrect items from the same test. Such a comparison would create a perfect correlation.
Use of Correlation Coefficients
Researchers consider that any coefficient more extreme than .7, either positive or negative, is very strong. It is extreme enough so that the two measures are indistinguishable for most practical purposes. For example, in the example study that we reviewed, there was a perfect correlation, with the very large number of 1.0, between the column from the IQ test and the column from the leadership test. This means that scientists could interchange the tests. If they want to find out someone's IQ level, they could just as well give the person the leadership examination as the IQ exam, and vice versa.
Scientists could equate two tests that correlate at a level of .7 similarly. They could interchange them. Scientists have found that such extreme correlations are not necessary for their purposes, however. Any coefficient greater than +/.-5 can be quite useful.