Selecting Research Sample Elements

1. Sampling Methods External validity can be achieved by employing one of two types of inference: statistical or theoretical. Statistical inference uses mathematical properties to generalize from results obtained from a sample to the population from which it was taken. Theoretical inference (or analytical generalization) is another form of generalization, but one that is

Determining Research Sample Size

Determining the size of a sample really comes down to estimating the mini­mum size needed to obtain results with an acceptable degree of confidence. For samples destined for quantitative data processing this means determining the size that enables the study to attain the desired degree of precision or signi­ficance level; for qualitative research it

The Sample Selection Process

Sample selection can follow a number of different procedures, many of which are related to two generic approaches: the traditional approach, typical of proba­bility sampling, and the iterative approach, such as that applied for grounded theory (Glaser and Strauss, 1967). The sample selection process also includes certain procedures that are carried out after data

Data Collection and Managing the Data Source

Data collection is crucial to all research. Through this process researchers accumulate empirical material on which to base their research. But before they begin putting together their empirical base, researchers should ask themselves whether any suitable data is already available. Secondary data (or secondhand data) can offer real advantages, as it relieves researchers from

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Collecting Primary Data for Quantitative Research

The most developed method of collecting primary data for quantitative research is the questionnaire. We take a particularly close look at mailed ques­tionnaires, as these are used very frequently in management research and necessitate particular techniques. We then present other methods of collecting primary data for quantitative research: observation and experimentation. 1. Surveys A

Collecting Primary Data for Qualitative Research

Primary data collection cannot be a discreet step in the research process, par­ticularly in qualitative research, which requires prolonged investigation in the field. This being the case, managing the interaction between the researcher and the data sources is a vital issue. We will conclude this section by presenting seve­ral approaches and source management strategies

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Collecting Secondary Data

Secondary data is data that already exists. It is advisable to systematically begin a research project by asking whether any appropriate secondary data is available. Use of such data presents numerous advantages. It is generally inex­pensive, it has already been assembled, and it does not necessarily require access to the people who supplied it.

Data-Source Confidentiality

Management research is carried out in a context that can be ‘sensitive’, and the degree of sensitivity can vary. The researcher’s investigation may constitute a threat to the organizations being studied and their members. This potential threat can be internal, relating to the risk of actors’ attitudes or behavior being revealed, which can have

Research Validity and Reliability

One of the questions researchers often ask is how their research can be both precise and of practical use to other researchers. To what extent can their results contribute to the area of science in which they work? To answer these questions researchers need to evaluate their work in relation to two criteria, that

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Construct Validity in the Research

1. Definition and Overview The concept of construct validity is peculiar to the social sciences, where research often draws on one or several abstract concepts that are not always directly observable (Zaltman et al., 1973). These can include change, performance, or power. Concepts are the building blocks of propositions and theories used to describe,

Research Reliability and Validity of the Measuring Instrument

1. Definition and Overview In the social sciences, measurement can be defined as the process that enables us to establish a relationship between abstract concepts and empirical indica­tors (Carmines and Zeller, 1990). Through measurement, we try to establish a link between one or several observable indicators (a cross in a questionnaire, a sentence in

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Internal Validity of the Research

1. Definition and Overview Internal validity consists in being sure of the pertinence and internal coherence of the results produced by a study; researchers must ask to what degree their inferences are correct, and whether or not rival explanations are possible. They must assess, for example, whether variations of the variable that is to

Reliability of the Research

Doing research takes time and involves a community of researchers. However, it would be very prejudicial if the soundness or precision of results produced in this way were dependent on the individual method of each researcher in conducting a project, or again, on conditions peculiar to that study. The relia­bility of research results, over

External Validity of the Research

1. Definition and Overview To assess the external validity of a research project we examine the possibilities and conditions for generalizing and appropriating the model to other sites. There are two facets to external validity, which we present in the following dis­cussion; these correspond to a logical progression in two stages in assessing research

Comparison Tests in the Research

Researchers in management often find they want to test hypotheses. For example, a researcher may want to test the hypothesis that the introduction of formalized strategic planning improves the financial performance of banks (Robinson and Pearce, 1983). Comparison tests are powerful tools for testing such a research hypothesis. Statistical tests generally fall into one

Statistical Tests in the Research

In this section we explore the general context in which researchers carry out statistical tests. We define the essential concepts involved and outline the gene­ral steps followed when using this type of test. 1. Inference and Statistics Inference has a very important place in management research. Conclusions or generalizations often have to be established

Parametric Tests in the Research

1. Tests on Means 1.1. Comparing the mean m of a sample to a reference value μ0 when the variance σ2 of the population is known Research question Does the mean m, calculated from a sample taken from a population with a known variance of σ2, differ significantly from a hypothetical mean μ0? Application

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Practicing Non-Parametric Tests in the Research

Non-parametric tests use statistics (that is, calculations) that have been estab­lished from observations, and do not depend on the distribution of the cor­responding population. The validity of non-parametric tests depends on very general conditions that are much less restrictive than those that apply to para­metric tests. Non-parametric tests present a number of advantages, in

Specifying the Phenomenon or System to be Modeled in the Research

Models can be defined as abstract representations of real phenomena. They represent the components of the phenomena studied as much as they do the interrelationships among these components. Identifying the phenomenon or system to be modeled is a three-step process. The first step is to determine its components. The interrelationships between these components must

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Specifying Variables and Concepts of the Research

Specifying a model’s different concepts and variables is, above all, dependent on the researcher’s chosen approach, which can be inductive or deductive, qualita­tive or quantitative. There are two levels of specification. One is conceptual, and enables researchers to determine the nature of concepts. The other is opera­tional, and enables researchers to move from concepts

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