Strategy for testing a proposition that expresses a deterministic relation
4.4.4 Strategy for testing a proposition that expresses a probabilistic relation
The experiment is the preferred research strategy for testing a prob- abilistic relation. The effect of an independent concept causal factor A is investigated by comparing the change in value of a dependent concept effect B in an experimental group which was exposed to the causal factor A with the change in value of B in a control group which was in the same condition as the experimental group but with- out the independent concept A causal factor. Different experimen- tal conditions, with different values of A, might be created and the range of values of B in each of these conditions is measured. Differences in the values of B between the different experimental groups are analysed, usually statistically, in order to draw a conclusion about how the values of B co-vary probabilistically i.e. on average with the values of A. If such an experiment is not feasible, the survey is the next best strat- egy for testing a probabilistic relation. In a survey, the co-variation between the values of two or more concepts is observed in a group of real life non-experimental instances. These are usually cross- sectional measurements i.e. at one point in time, but sometimes it is possible to design a prospective and longitudinal survey, allowing the researcher to observe how changes in the dependent concept follow in time upon changes in the independent concept. If a survey is not feasible, a comparative case study is the next best option see Box 9. In this type of case study the principles of a good survey are followed as closely as possible “quasi-survey case study”. This implies that a population is specified in which the proposition is tested, and that the sample is representative for that population and should be selected randomly. Box 9 How the survey can become a case study An essential characteristic of any survey is probability sampling, e.g. random sampling of instances from the population in which each instance of the population has an equal chance of being selected. This is the only guarantee that a co-variation that is observed in the group of observed instances in the sample also exists in other instances than those included in the sample. Probability sampling is only possible if the sampling frame is specified, i.e. if there is a list of members of a population or a set of directions for identifying each of them. Because there is never or very rarely a sampling frame for all members of an entire theoretical domain, a theory-testing survey is always conducted in a specified population of instances from within that domain. The propo- sition is tested in that population and this test will be followed by other tests in other populations in a replication strategy, in order to achieve generalizability to other parts of the domain. If no population of instances can be identified in the domain no sampling frame is available, it is not possible to test the proposition with a survey. However, this problem can be solved by specifying a smaller population within a domain for which a frame for probability sampling can be defined. It is, for instance, not likely that there is a sampling frame list of innovation projects in general, or of such projects in Europe, or in an economic sector in a country, but it is likely that there is a list of projects for which an EU subsidy was requested or a list of projects within a large company. Such often small populations are not “representative” of the domain, but no population ever is. A consumer behaviour theory, for instance, is always tested in a specific population of consumers say Rotterdam housewives or Toronto students and then replicated in other populations see Chapter 3.2.3. Another problem may then arise with such strategy: the number of available instances from the domain is too small for conducting a statistical analysis of the data, which is the main characteristic of a survey. This problem exists, for instance, in the field of compar- ative politics research when propositions about nations with specific characteristicsParts
» BUKU | SAIDNA ZULFIQAR BIN TAHIR (VIKAR)
» Our definition of a case study
» Chapter 2: Case studies in business research
» Chapter 3: Principles of research Chapter 4: Theory-testing research general
» Chapters 10–11: Practice-oriented research Overview of the book
» Reading specific topics Overview of the book
» Suggestions for students How to read this book
» References BUKU | SAIDNA ZULFIQAR BIN TAHIR (VIKAR)
» Types of case study research
» Objectives of case study research
» Guidelines for case study research
» Evaluations of case study research
» Conclusion BUKU | SAIDNA ZULFIQAR BIN TAHIR (VIKAR)
» General research objectives of theory-oriented and practice-oriented research
» Orientation: how to choose between theory-oriented or practice-oriented research
» Theory Principles of theory-oriented research
» Theory-oriented research: contribution to theory development
» Replication Principles of theory-oriented research
» Representativeness, external validity, and generalizability
» Exploration of theory Exploration for theory-oriented research
» Exploration of practice for finding a proposition
» Exploration of practice for confirming the relevance of a proposition
» Contributions to theory development
» Practice Principles of practice-oriented research
» Practice-oriented research: contribution to a practitioner’s knowledge
» Exploration of practice Exploration for practice-oriented research
» Research objectives in theory-testing research
» Propositions that express a sufficient condition
» Propositions that express a necessary condition
» Propositions that express a deterministic relation
» Propositions that express a probabilistic relation
» Business relevance of propositions
» Strategy for testing a proposition that expresses a sufficient condition
» Strategy for testing a proposition that expresses a necessary condition
» Strategy for testing a proposition that expresses a deterministic relation
» Strategy for testing a proposition that expresses a probabilistic relation
» Testing more complex conceptual models
» Outcome and implications BUKU | SAIDNA ZULFIQAR BIN TAHIR (VIKAR)
» Summary BUKU | SAIDNA ZULFIQAR BIN TAHIR (VIKAR)
» Introduction How to test a sufficient or a necessary condition with a case study
» Candidate cases How to test a sufficient or a necessary condition with a case study
» Case selection How to test a sufficient or a necessary condition with a case study
» Hypothesis How to test a sufficient or a necessary condition with a case study
» Measurement How to test a sufficient or a necessary condition with a case study
» Data presentation Data analysis
» Replication strategy How to test a sufficient or a necessary condition with a case study
» Domain Conceptual model Theory
» Research objective Case Study 1: Theory-testing research: testing a necessary condition
» Research strategy Case Study 1: Theory-testing research: testing a necessary condition
» Candidate cases Case selection
» Hypotheses Case Study 1: Theory-testing research: testing a necessary condition
» Measurement Case Study 1: Theory-testing research: testing a necessary condition
» Radical innovation projects Data presentation
» Incremental innovation projects Data presentation
» Data analysis Case Study 1: Theory-testing research: testing a necessary condition
» Replication strategy Case Study 1: Theory-testing research: testing a necessary condition
» Theory Methodological reflection on Case Study 1
» Research objective Methodological reflection on Case Study 1
» Research strategy Methodological reflection on Case Study 1
» Candidate cases Methodological reflection on Case Study 1
» Case selection Methodological reflection on Case Study 1
» Hypothesis Measurement Methodological reflection on Case Study 1
» Data presentation Methodological reflection on Case Study 1
» Data analysis Methodological reflection on Case Study 1
» Replication strategy Methodological reflection on Case Study 1
» Research strategy Case Study 2: Theory-testing research: testing a necessary condition
» Candidate cases Case Study 2: Theory-testing research: testing a necessary condition
» Case selection Case Study 2: Theory-testing research: testing a necessary condition
» Hypothesis Case Study 2: Theory-testing research: testing a necessary condition
» Measurement Case Study 2: Theory-testing research: testing a necessary condition
» Theory Methodological reflection on Case Study 2
» Candidate cases Methodological reflection on Case Study 2
» Case selection Methodological reflection on Case Study 2
» Hypothesis Methodological reflection on Case Study 2
» Measurement Methodological reflection on Case Study 2
» Data presentation Methodological reflection on Case Study 2
» Data analysis Methodological reflection on Case Study 2
» Replication strategy Methodological reflection on Case Study 2
» Introduction How to test a deterministic relation with a case study
» Candidate cases How to test a deterministic relation with a case study
» Case selection How to test a deterministic relation with a case study
» Hypothesis How to test a deterministic relation with a case study
» Data analysis How to test a deterministic relation with a case study
» Replication strategy How to test a deterministic relation with a case study
» Introduction Case Study 3: Theory-testing research: testing a deterministic relation
» Research objective Case Study 3: Theory-testing research: testing a deterministic relation
» Research strategy Case Study 3: Theory-testing research: testing a deterministic relation
» Hypotheses Case Study 3: Theory-testing research: testing a deterministic relation
» Measurement Case Study 3: Theory-testing research: testing a deterministic relation
» Theory Methodological reflection on Case Study 3
» Research objective Research strategy
» Candidate cases Methodological reflection on Case Study 3
» Case selection Hypotheses Methodological reflection on Case Study 3
» Measurement Data presentation Methodological reflection on Case Study 3
» Introduction How to test a probabilistic relation with a case study
» Introduction Case Study 4: Theory-testing research: testing a probabilistic relation
» Research objective Case Study 4: Theory-testing research: testing a probabilistic relation
» Research strategy Case Study 4: Theory-testing research: testing a probabilistic relation
» Candidate cases Case Study 4: Theory-testing research: testing a probabilistic relation
» Case selection Case Study 4: Theory-testing research: testing a probabilistic relation
» Hypotheses Measurement Case Study 4: Theory-testing research: testing a probabilistic relation
» Data presentation Case Study 4: Theory-testing research: testing a probabilistic relation
» Data analysis Case Study 4: Theory-testing research: testing a probabilistic relation
» Theory Methodological reflection on Case Study 4
» Specifying the relation between known concepts
» Discovering a not yet known concept
» Discovering concepts and their relation
» Discovering concepts Principles of theory-building research
» Research strategies in theory-building research
» Outcome and implications Summary
» Introduction How to design and conduct a theory-building case study
» Candidate cases How to design and conduct a theory-building case study
» Case selection How to design and conduct a theory-building case study
» Extracting relevant evidence How to design and conduct a theory-building case study
» Coding How to design and conduct a theory-building case study
» Data presentation How to design and conduct a theory-building case study
» Sufficient condition Data analysis
» Necessary condition Data analysis
» Deterministic relation Data analysis
» Sufficient condition An example of data analysis
» Necessary condition An example of data analysis
» Deterministic relation Probabilistic relation
» Outcome How to design and conduct a theory-building case study
» Introduction Case Study 5: Theory-building research
» Candidate cases Case Study 5: Theory-building research
» Case selection Extracting relevant evidence
» Coding Case Study 5: Theory-building research
» Outcome Case Study 5: Theory-building research
» Justification of a theory-building case study
» Candidate cases Methodological reflection on Case Study 5
» Data analysis Methodological reflection on Case Study 5
» Outcome Methodological reflection on Case Study 5
» Research objective in hypothesis-testing research
» Research strategy in hypothesis-testing research
» Research objective in hypothesis-building research
» Research objective of descriptive practice-oriented research
» Research strategy of practice-oriented descriptive research
» Introduction How to design and conduct a practice-oriented case study
» Case selection How to design and conduct a practice-oriented case study
» Implications of the research results
» Introduction Case Study 6: Hypothesis-testing practice-oriented research
» Hypothesis Case Study 6: Hypothesis-testing practice-oriented research
» Measurement Case Study 6: Hypothesis-testing practice-oriented research
» Data analysis Case Study 6: Hypothesis-testing practice-oriented research
» Results and implications Case Study 6: Hypothesis-testing practice-oriented research
» Practice Methodological reflection on Case Study 6
» Research objective Methodological reflection on Case Study 6
» Case selection Methodological reflection on Case Study 6
» Measurement Methodological reflection on Case Study 6
» Data presentation Methodological reflection on Case Study 6
» Data analysis Methodological reflection on Case Study 6
» Implications for practice Methodological reflection on Case Study 6
» Introduction Case Study 7: Descriptive practice-oriented research
» Absence of guidelines or criteria
» Measurement Case Study 7: Descriptive practice-oriented research
» Data presentation Case Study 7: Descriptive practice-oriented research
» Concept definition Case Study 7: Descriptive practice-oriented research
» Implications Case Study 7: Descriptive practice-oriented research
» Practice Research objective Methodological reflection on Case Study 7
» Case selection Measurement Methodological reflection on Case Study 7
» Data presentation Methodological reflection on Case Study 7
» Data analysis Methodological reflection on Case Study 7
Show more