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Identifying Relationships Among a Model’s Variables and Concepts in the Research

As with identifying the model’s concepts and variables, identifying relationships depends above all on the method the researcher adopts: qualitative or quantita­tive, inductive or deductive. Its aim is to determine whether there is a relation­ship between the model’s concepts (and variables), the nature of this relationship (causal or simple association) and the relationship’s sign

4 Comments

26
Jul
Evaluating and Testing the Research Model

Evaluating and testing a model does not simply mean testing the hypotheses or relationships between the model’s concepts or variables one after the other, but also judging its internal global coherence. 1. Qualitative Methods In some studies, researchers want to test the existence of a causal relationship between two variables without having recourse to

26
Jul
Classification and Structuring Methods in Data Analysis

Data analysis manuals (Aldenderfer and Blashfield, 1984; Everitt, 1993; Hair et al., 1992; Kim and Mueller, 1978; Lebart et al., 1984) provide a detailed pre­sentation of the mathematical logic on which classification and structuring methods are based. We have chosen here to define these methods and their objectives, and consider the preliminary questions that

26
Jul
Application Classification and Structuring Methods in Data Analysis

This section puts the principal methods into practice. We recommend researchers seeking a more detailed discussion of the practical application of these structuring and classifying methods refer to a specialized data analysis manual, such as Hair et al. (1992). 1. Cluster Analysis After clearly defining the environment from which the objects to be classified

2 Comments

26
Jul
General Presentation and Data Collection for Social Network Research

Network analysis essentially involves revealing the links that exist between units. These units can be individuals, actors, groups, organizations or projects. When researchers decide to use network analysis methods, and to look at links between units of analysis, they should be aware that they are implicitly enter­ing into the paradigm of structural analysis. Structural

26
Jul
Analysis Methods in Social Network Research

Once researchers have collected sociometric data (data that measures links between individuals), and so know which actors have links with which other actors, they then need to reconstitute the network, or networks, of actors before they can conduct a global network analysis (or analyses). The methods of analysis fall into two main categories. In

1 Comments

26
Jul
Fundamentals of Longitudinal Analyses

1. Definition and Role of Time Longitudinal analyses form a group of analyses focusing on the study of pheno­mena over the course of time. Longitudinal analyses are often contrasted with cross-sectional studies, by arguing that the data collected for longitudinal analyses relate to at least two distinct points in time, while for cross-sectional studies

1 Comments

26
Jul
Quantitative Longitudinal Analyses

A large number of quantitative longitudinal methods are not specific to longitu­dinal analysis, and therefore will not be developed in detail here. An example of this is regression. Nevertheless, often additional conditions have to be respected when applying these methods to longitudinal analyses – notably concerning error terms, which should be homoscedastic, and free

26
Jul
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

5 Comments

26
Jul
Analyzing Representations and Discourse

Research in management and organizational science often relies on the analysis of communications, either oral (conversations, individual or group interviews) or written (annual reports, strategic plans, letters to shareholders, etc.). Researchers may simply want to analyze the content or the structure of these communica­tions; or they may attempt to establish, through the text or

26
Jul
Methods of Discourse and Representation Analysis

Discourse and representation analysis methods generally require three major steps: data collection (Subsection 1), coding (Subsection 2), and analysis (Subsection 3). 1. Collecting Discourse or Representations There are two main types of methods for collecting representations or dis­course: structured (or a priori) and non-structured methods. 1.1. Structured or a priori methods The objective of

1 Comments

26
Jul
Content Analysis

Content analyses were developed to study newspaper articles and political speeches in the USA in the 1920s. They are based on the theory that repeating certain elements of discourse (words, expression or similar meanings) revealed the interests or concerns of the persons involved. Their purpose is to analyze the manifest contents of a communication.

1 Comments

26
Jul
Cognitive Mapping for Analyzing Representations and Discourse

As stated earlier, cognitive mapping is aimed at establishing and analyzing cognitive maps, that is, representations of a person or organization’s beliefs concerning a particular domain (Axelrod, 1976). A cognitive map is made up of two types of elements: Concepts, also known as constructs or variables. The links between these concepts. These links can

26
Jul
Communication Media for the Research

Communication of research work can be directed towards various readers. Research on organizations may be of interest to three particular kinds of readers: researchers, managers and other members of the organization, and, to a lesser extent, the general public. The same research project may then need to be adapted to different target audiences –

1 Comments

26
Jul
Writing the Research Articles

1. Structure The principal medium by which studies reach other researchers is the research article, published in an academic journal. The structure of these articles is very often identical, even where guidelines are not precisely defined. The structure that I outline below, which is almost universal for quantitative research, is equally well adapted to

26
Jul
The Research Writing Process

I examine here the questions of when to write, how to improve a text (by soli­citing feedback on the manuscript) and the revision process used by refereed journals. 1. When to Write On the issue of when to write, the principal advice we find repeatedly given is, begin as soon as possible (Richardson, 1990;

1 Comments

26
Jul
The Thesis Advisor

This story, which is probably as old as the academic world it comes from, partly illustrates the three main roles of a thesis advisor. The thesis advisor is first of all a guide. The researcher will profit from his or her greater experience, especially in defining the subject of the dissertation. The thesis advisor

1 Comments

26
Jul
Research Consortiums

At conferences held by research associations, researchers of different origins come together to discuss subjects connected to the writing of a dissertation and how to embark upon and construct an academic career. Because of the diversity of research questions, methodologies and experiences, participants often find these meetings very rewarding. The Academy of Management The

1 Comments

26
Jul
Academic Conferences

By taking part in academic conferences, a researcher has the opportunity to: present the results of research work and receive feedback from the academic community constructively integrate suggestions and critiques made by academic peers into the final work keep up with current developments in a specific research domain by becoming familiar with projects before

1 Comments

26
Jul
The Researcher’s Relationship with the Non-Academic World

In 1991, Fortune published a three-page article on the ‘third generation idiot’. By this provocative term, the review described a 28-year-old MBA student reporting to a 30-year-old assistant professor, himself supervised by a 35-year- old associate professor. None of the three had ever worked outside the academic world, or only for a very short

5 Comments

26
Jul
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