Qualitative Longitudinal Analysis

The mass of information collected when doing qualitative research can be impressive. But this mass of data cannot simply be analyzed directly – it must first be manipulated and put into usable form.

1. Preliminary Processing of Qualitative Longitudinal Data

Very often the first question for researchers using qualitative longitudinal data is how to reduce the copious amount of information they have amassed. The risk of drowning in data is real, and a number of authors have proposed simple techniques for consolidating and summarizing qualitative data, or reducing the amount of data, before analysis.

1.1. Monograph

The first preliminary step in processing qualitative longitudinal data is to write a monograph. A monograph traces the development of the phenomenon being studied, over the analysis period defined by the researcher. It gives a transver­sal view of the phenomenon while reducing the amount of information that has been accumulated during the data collection phase. Often taking the form of a descriptive narrative, a monograph can be accompanied by an initial analysis of the data (Eisenhardt, 1989); perhaps in the form of a graph of relationships between the events, in which chronological order will be respected.

When research focuses on several organizations (or on several case studies), monographs also provide the basic elements for comparison. They enable indi­vidual development patterns to emerge which, when compared with each other, facilitate the identification of common characteristics.

1.2. Time-ordered matrices

The time-ordered matrix proposed by Miles and Huberman (1994), presents information relating to a phenomenon by establishing a temporal relationship between the variables it is composed of. The aim is to understand quickly and easily what has happened. Such a matrix has its columns arranged in sequence, so that one can see when a given phenomenon occurred. The basic principle is chronology (Miles and Huberman, 1994).

In constructing time-ordered matrices, researchers begin by determining the specific components or aspects of the phenomenon they are studying. These form the rows of the matrix. The columns represent successive periods – that is, the period of analysis divided into subperiods, or successive stages of development. The intersection between the line and the column shows the changes that have occurred to a component or to an aspect of the phenomenon over the course of a given period.

This chronological matrix enables the researcher to pinpoint shifts or important modifications that have been experienced by components of the phenomenon.

Miles and Huberman (1994) also propose longitudinal variants of the basic time-ordered matrix: the role-by-time matrix and the time-ordered meta-matrix. In the first, the lines represent individuals. This matrix allows us to determine at which moment an action was carried out by a protagonist occupying a particular role in relation to the phenomenon being studied. The time-ordered meta-matrix compares the evolution of a particular phenomenon for several cases at the same time. The different case studies make up the rows and the time intervals of the period of analysis form the columns. This matrix can be constructed in relation to the studied phenomenon as a whole, or one of its components alone.

The tools presented above pave the way for the analysis. In fact, it is diffi­cult to determine which is an element of the preliminary processing of the data, and which forms part of the analysis itself.

2. Qualitative Analysis of Longitudinal Data

Qualitative longitudinal analysis methods are rarely formalized. However, cer­tain authors have proposed general procedures that can be used to analyze the evolution of a phenomenon.

2.1. Analyzing a phenomenon in terms of time

Van de Ven and Poole (1989) proposed a method that can be broken into four steps:

1. Put together a chronological list of events that occurred during the course of the studied phenomenon. An ‘event’ is understood to mean a change experienced by one of the conceptual categories studied.
2. Rearrange this list according to the conceptual categories of the research, in order to establish, for each category, a chronological series of events – which is called a trajectory. The set of trajectories gives us a description of the process studied.
3. Carry out a phase analysis. This consists in identifying discrete phases of activity and analyzing their sequences and properties. A phase is defined as being a meaningful set of simultaneous activities within the trajectories established in the second stage. Thus, a phase is a set of changes undergone by a certain number of conceptual categories.
4. Examine the order of sequences in the series of connected events.

2.2. Concepts describing evolution: stages, cycles, phases, and sequences

Stages We speak of a stage in the evolution of a phenomenon to characterize a moment in this evolution. The stage can sometimes signify a provisional stopping point. All evolution is essentially a succession of stages.

Cycles This can have two different meanings. A cycle can be seen as a recur­rent succession of steps giving cadence to the evolution of a system by always returning it to its original state, as in the cycle of the seasons. This is known as cyclical evolution. We can also describe as a cycle the evolution of a pheno­menon that follows a fixed order without necessarily being recurrent – as in the life cycle, where every creature is born, grows and dies. This is called an evolu­tion schema.

Both of these types of cycles have been identified in organizational theory. Cyclical evolution is found, for example, when successive periods of stability and change are observed. Evolution schema can be seen in the recognition of evolutionary constants in the life of organizations. The cycle then expresses a permanent organizational phenomenon. It can be broken up into phases that represent different stages of the evolution of the organization.

Phases The concept of the phase is very close to that of the cycle as understood in its second meaning: that is to say, as a succession of stages which always occur in the same order. Phases are temporary phenomena in the life of the organization (for example, the phases in the development of a new product). They generally follow on from each other in a given, irreversible, order, but they can overlap. Phases are composed of fairly unified activities that carry out a function necessary for the evolution of the phenomenon (Poole, 1983). By working from an overview of the phenomenon, the researcher tries to deter­mine a relatively limited number of phases that take place in a definite order.

Sequences A sequence is defined as an ordered succession of events or objects. This order, as defined by Abbott (1990), may be temporal or spatial (although we are here only concerned with temporal order). A sequence may be either continuous or discrete.

When the objects observed are phases in the evolution of a phenomenon, the development model obtained using sequence methods is identical to that obtained by phase analysis. However, the order of the events (or phases) is not irreversible and shows more complex evolutions, such as retroactive looping, permutations, recurrent and non-recurrent events, etc.

2.3. Concepts describing dynamics: dynamic factors rupture points

The passage from one event to another or from one phase to another within an evolving phenomenon is not always stable and linear. Evolving phenomena are subject to interference, cycles, rupture points, etc. These factors of dynamics can create accelerations, slowdowns, reversals, or ruptures within the evolution of a single phenomenon.

In their research on decision processes, Mintzberg et al. (1976) identify six dynamic factors:

• interrupts, which are caused by environmental forces, and cause a suspen­sion of the evolution of the phenomenon
• scheduling delays, which permit managers who are under strong time pres­sures to break complex processes down into manageable steps
• feedback delays. These characterize periods in which managers are waiting to see the results of actions that have already been engaged upon before undertaking other actions
• timing delays and speedups, which result from the intervention of managers wanting perhaps to seize an opportunity or to create a surprise effect, or to wait for more favorable conditions or gain time
• comprehension cycles, which enable a better understanding of a complex problem by going over it numerous times
• failure recycles, which lead the decision-maker to slow down the process while waiting for an acceptable solution when none have proved satisfactory so far, or to change the criteria relating to a problem to make one of the proposed solutions acceptable.

Rupture points, which represent transitions between the main trends in the development of a phenomenon, are also factors in the phenomenon’s dynam­ics. Poole (1983) distinguishes three types of rupture points:

• Normal points, which result from a process that can be described as ordi­nary. These include, for example, adjournments of a decision process opera­ting within a small group.
• Delays (or cycles of comprehension), which signify a period in which the observed phenomenon is suspended. These periods are important, as they can signal either the beginning of a difficult phase, or a time of great crea­tivity. The actors involved in the evolution of the phenomenon are generally unable to anticipate these rupture points.
• Ruptures (or interruptions), which characterize an internal conflict, or the arrival of unexpected results. Ruptures result in a reorientation of the evolution of the observed phenomenon..

Source: Thietart Raymond-Alain et al. (2001), Doing Management Research: A Comprehensive Guide, SAGE Publications Ltd; 1 edition.