Análisis de matriz DOFA

The unit of analysis refers to the level of aggregation of the data collected dur- ing the subsequent data analysis stage. If, for instance, the problem statement focuses on how to raise the motivational levels of employees in general, then we are interested in individual employees in the organization and would have to find out what we can do to raise their motivation. Here the unit of analysis is the

individual. We will be looking at the data gathered from each individual and

treating each employee‘s response as an individual data source. If the researcher is interested in studying two-person interactions, then several two-person groups, also known as dyads, will become the unit of analysis. Analysis of husband–wife interactions in families and supervisor–subordinate relationships at the work- place are good examples of dyads as the unit of analysis. However, if the prob- lem statement is related to group effectiveness, then the unit of analysis would be at the group level. In other words, even though we may gather relevant data from all individuals comprising, say, six groups, we would aggregate the indi- vidual data into group data so as to see the differences among the six groups. If we compare different departments in the organization, then the data analysis will be done at the departmental level—that is, the individuals in the department will be treated as one unit—and comparisons made treating the department as the unit of analysis.

Our research question determines the unit of anlaysis. For example, if we desire to study group decision-making patterns, we would probably be examin- ing such aspects as group size, group structure, cohesiveness, and the like, in try- ing to explain the variance in group decision making. Here, our main interest is not in studying individual decision making but group decision making, and we will be studying the dynamics that operate in several different groups and the factors that influence group decision making. In such a case, the unit of analysis will be groups.

As our research question addresses issues that move away from the individual to dyads, and to groups, organizations, and even nations, so also does the unit of analysis shift from individuals to dyads, groups, organizations, and nations. The characteristic of these ―levels of analysis‖ is that the lower levels are subsumed within the higher levels. Thus, if we study buying behaviors, we have to collect

UNIT OF ANALYSIS: INDIVIDUALS, DYADS, GROUPS, ORGANIZATIONS, CULTURES 133

data from, say, 60 individuals, and analyze the data. If we want to study group dynamics, we may need to study, say, six or more groups, and then analyze the data gathered by examining the patterns in each of the groups. If we want to study cultural differences among nations, we will have to collect data from dif- ferent countries and study the underlying patterns of culture in each country. Some critical issues in cross-cultural research are discussed in later chapters.

Individuals do not have the same characteristics as groups (e.g., structure, cohesiveness) and groups do not have the same characteristics as individuals (e.g., IQ, stamina). There are variations in the perceptions, attitudes, and behav- iors of people in different cultures. Hence, the nature of the information gath- ered, as well as the level at which data are aggregated for analysis, are integral to decisions made in the choice of the unit of analysis.

It is necessary to decide on the unit of analysis even as we formulate the research question since the data collection methods, sample size, and even the variables included in the framework may sometimes be determined or guided by the level at which data are aggregated for analysis.

Let us examine some research scenarios that would call for different units of analysis.

Example 6.18 INDIVIDUALS AS THE UNIT OF ANALYSIS

The Chief Financial Officer of a manufacturing company wants to know how many of the staff would be interested in attending a 3-day seminar on making appropriate investment decisions. For this purpose, data will have to be collected from each individual staff member and the unit of analysis is the individual.

Example 6.19 DYADS AS THE UNIT OF ANALYSIS

Having read about the benefits of mentoring, a human resources manager wants to first identify the number of employees in three departments of the organiza- tion who are in mentoring relationships, and then find out what the jointly per- ceived benefits (i.e., by both the mentor and the one mentored) of such a relationship are.

Here, once the mentor and the mentored pairs are identified, their joint per- ceptions can be obtained by treating each pair as one unit. Hence, if the man- ager wants data from a sample of 10 pairs, he will have to deal with 20 individuals, a pair at a time. The information obtained from each pair will be a data point for subsequent analysis. Thus, the unit of analysis here is the dyad.

Example 6.20 GROUPS AS THE UNIT OF ANALYSIS

A manager wants to see the patterns of usage of the newly installed Information System (IS) by the production, sales, and operations personnel. Here three groups of personnel are involved and information on the number of times the IS is used by each member in each of the three groups as well as other relevant issues will be collected and analyzed. The final results will indicate the mean

134 THE RESEARCH PROCESS

usage of the system per day or month for each group. Here the unit of analysis is the group.

Example 6.21 DIVISIONS AS THE UNIT OF ANALYSIS

Proctor and Gamble wants to see which of its various divisions (soap, paper, oil, etc.) have made profits of over 12% during the current year. Here, the profits of each of the divisions will be examined and the information aggregated across the various geographical units of the division. Hence, the unit of analysis will be the division, at which level the data will be aggregated.

Example 6.22 INDUSTRY AS THE UNIT OF ANALYSIS

An employment survey specialist wants to see the proportion of the workforce employed by the health care, utilities, transportation, and manufacturing indus- tries. In this case, the researcher has to aggregate the data relating to each of the subunits comprised in each of the industries and report the proportions of the workforce employed at the industry level. The health care industry, for instance, includes hospitals, nursing homes, mobile units, small and large clinics, and other health care providing facilities. The data from these subunits will have to be aggregated to see how many employees are employed by the health care industry. This will need to be done for each of the other industries.

Example 6.23 COUNTRIES AS THE UNIT OF ANALYSIS

The Chief Financial Officer (CFO) of a multinational corporation wants to know the profits made during the past 5 years by each of the subsidiaries in England, Germany, France, and Spain. It is possible that there are many regional offices of these subsidiaries in each of these countries. The profits of the various regional centers for each country have to be aggregated and the profits for each country for the past 5 years provided to the CFO. In other words, the data will now have to be aggregated at the country level.

As can be easily seen, the data collection and sampling processes become more cumbersome at higher levels of units of analysis (industry, country) than at the lower levels (individuals and dyads).

It is obvious that the unit of analysis has to be clearly identified as dictated by the research question. Sampling plan decisions will also be governed by the unit of analysis. For example, if I compare two cultures, for instance those of India and the United States—where my unit of analysis is the country—my sample size will be only two, despite the fact that I shall have to gather data from several hundred individuals from a variety of organizations in the differ- ent regions of each country, incurring huge costs. However, if my unit of analysis is individuals (as when studying the buying patterns of customers in the southern part of the United States), I may perhaps limit the collection of data to a representative sample of a hundred individuals in that region and conduct my study at a low cost!

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It is now even easier to see why the unit of analysis should be given serious consideration even as the research question is being formulated and the research design planned.

TIME HORIZON: CROSS-SECTIONAL VERSUS