Rent 9780470744796 | Research Methods for Business: A Skill Building Approach, 5th Edition | Uma Sekaran (Southern Illinois Univ.); Roger Bougie (Roger Bougie, Tilburg University, The Netherlands ) @knetbooks.com

Summary Table of Contents Author Biography

Research Methods for Business: A Skill Building Approach, Fifth Edition is a concise and straightforward introduction for students to the world of business research. The skill building approach provides students with practical perspectives on how research can be applied in real business situations. Maintaining Uma Sekaran's popular and accessible style of writing, Roger Bougie draws upon his extensive experience of the field to present an up-to-date guide on business research for the aspiring future manager.The fifth edition has a new chapter o... MORE

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About the authors
Preface
Introduction to Research
What is research?
Business research
Definition of business research
Research and the manager
Types of business research: applied and basic
Applied research
Basic or fundamental research
Managers and research
The manager and the consultant-researcher
The manager-researcher relationship
Internal versus external consultants/researchers
Internal consultants/researchers
External consultants/researchers
Knowledge about research and managerial effectiveness
Ethics and business research
Summary
Discussion questions
Scientific Investigation
The hallmarks of scientific research
Purposiveness
Rigor
Testability
Replicability
Precision and confidence
Objectivity
Generalizability
Parsimony
Some obstacles to conducting scientific research in the management area
The hypothetico-deductive method
The seven-step process in the hypothetico-deductive method
Review of the hypothetico-deductive method
Other types of research
Case studies
Action research
Summary
Discussion questions
The Research Process: The Broad Problem Area and Defining the Problem Statement
Broad problem area
Preliminary information gathering
Nature of information to be gathered
Literature review
Conducting the literature review
Defining the problem statement
What makes a good problem statement?
The research proposal
Managerial implications
Ethical issues in the preliminary stages of investigation
Summary
Discussion questions
Practice projects
Appendix
Some online resources useful for business research
Bibliographical databases
APA format for referencing relevant articles
Referencing and quotation in the literature review section
The Research Process: Theoretical Framework and Hypothesis Development
The need for a theoretical framework
Variables
Types of variables
Theoretical framework
The components of the theoretical framework
Theoretical framework for the example of air safety violations
Hypothesis development
Definition of a hypothesis
Statement of hypotheses: formats
Directional and nondirectional hypotheses
Null and alternate hypotheses
Hypothesis testing with qualitative research: negative case analysis
Managerial implications
Summary
Discussion questions
Practice project
The Research Process: Elements of Research Design
The research design
Purpose of the study: exploratory, descriptive, hypothesis testing (analytical and predictive), case study analysis
Exploratory study
Descriptive study
Hypothesis testing
Case study analysis
Review of the purpose of the study
Type of investigation: causal versus correlational
Extent of researcher interference with the study
Study setting: contrived and noncontrived
Unit of analysis: individuals, dyads, groups, organizations, cultures
Time horizon: cross-sectional versus longitudinal studies
Cross-sectional studies
Longitudinal studies
Review of elements of research design
Managerial implications
Summary
Discussion questions
Measurement of Variables: Operational Definition
How variables are measured
Operationalization of variables
Operationalization: dimensions and elements
Operationalizing the (multidimensional) concept of achievement motivation
What operationalization is not
Review of operationalization
International dimensions of operationalization
Summary
Discussion questions
Measurement: Scaling, Reliability, Validity
Scales
Nominal scale
Ordinal scale
Interval scale
Ratio scale
Review of scales
Rating scales
Dichotomous scale
Category scale
Semantic differential scale
Numerical scale
Itemized rating scale
Likert scale
Fixed or constant sum scale
Stapel scale
Graphic rating scale
Consensus scale
Other scales
Ranking scales
Paired comparison
Forced choice
Comparative scale
International dimensions of scaling
Goodness of measures
Item analysis
Validity
Reliability
Reflective versus formative measurement scales
What is a reflective scale?
What is a formative scale and why do the items of a formative scale not necessarily hang together?
Summary
Discussion questions
Appendix
Examples of some measures
Data Collection Methods
Sources of data
Primary sources of data
Secondary sources of data
Data collection methods
Interviewing
Questionnaires
Other methods of data collection
Multimethods of data collection
Review of the advantages and disadvantages of different data collection methods and when to use each
Setting from which data are gathered
International dimensions of surveys
Special issues in instrumentation for cross-cultural research
Issues in data collection
Managerial implications
Ethics in data collection
Ethics and the researcher
Ethical behavior of respondents
Summary
Discussion questions
Experimental Designs
The lab experiment
Control
Manipulation of the independent variable
Controlling the contaminating exogenous or "nuisance" variables
Internal validity of lab experiments
External validity or generalizability of lab experiments
The field experiment
External validity
Trade-off between internal and external validity
Factors affecting the validity of experiments
History effects
Maturation effects
Testing effects
Selection bias effects
Mortality effects
Statistical regression effects
Instrumentation effects
Identifying threats to validity
Internal validity in case studies
Review of factors affecting internal and external validity
Types of experimental design and validity
Quasi-experimental designs
True experimental designs
Simulation
Ethical issues in experimental design research
Managerial implications
Summary
Discussion questions
Appendix
Further experimental designs
Sampling
Population, element, sample, sampling unit, and subject
Population
Element
Sample
Sampling unit
Subject
Parameters
Reasons for sampling
Representativeness of samples
Normality of distributions
The sampling process
Defining the population
Determining the sample frame
Determining the sampling design
Determining the sample size
Executing the sampling process
Probability sampling
Unrestricted or simple random sampling
Restricted or complex probability sampling
Review of probability sampling designs
Nonprobability sampling
Convenience sampling
Purposive sampling
Review of nonprobability sampling designs
Examples of when certain sampling designs would be appropriate
Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
Area sampling
Double sampling
Convenience sampling
Judgment sampling: one type of purposive sampling
Quota sampling: a second type of purposive sampling
Sampling in cross-cultural research
Issues of precision and confidence in determining sample size
Precision
Confidence
Sample data, precision, and confidence in estimation
Trade-off between confidence and precision
Sample data and hypothesis testing
Determining the sample size
Importance of sampling design and sample size
Efficiency in sampling
Sampling as related to qualitative studies
Managerial implications
Summary
Discussion questions
Quantitative Data Analysis
Getting the data ready for analysis
Coding and data entry
Editing data
Data transformation
Getting a feel for the data
Frequencies
Measures of central tendency and dispersion
Relationships between variables
Excelsior Enterprises - descriptive statistics part 1
Testing goodness of data
Reliability
Validity
Excelsior Enterprises - descriptive statistics part 2
Summary
Discussion questions
Quantitative Data Analysis Part 2: Hypothesis Testing
Introduction
Type I errors, type II errors, and statistical power
Choosing the appropriate statistical technique
Testing a hypothesis about a single mean
Testing hypotheses about two related means
Testing hypotheses about two unrelated means
Testing hypotheses about several means
Regression analysis
Standardized regression coefficients
Regression with dummy variables
Multicollinearity
Testing moderation using regression analysis: interaction effects
Other multivariate tests and analyses
Discriminant analysis
Logistic regression
Conjoint analysis
Two-way ANOVA
MANOVA
Canonical correlation
Excelsior Enterprises - hypothesis testing
Data warehousing, data mining, and operations research
Some software packages useful for data analysis
Summary
Discussion questions
Qualitative Data Analysis
Introduction
Data reduction
Data display
Drawing conclusions
Reliability and validity in qualitative research
Some other methods of gathering and analyzing qualitative data
Content analysis
Narrative analysis
Summary
Discussion questions
The Research Report
The report
The written report
The purpose of the written report
The audience for the written report
Characteristics of a well-written report
Contents of the research report
Integral parts of the report
Oral presentation
Deciding on the content
Visual aids
The presenter
The presentation
Handling questions
Summary
Discussion questions
Appendix
Report 1: Sample of a report involving a descriptive study
Report 2: Sample of a report where an idea has to be "sold"
Report 3: Sample of a report offering alternative solutions and explaining the pros and cons of each alternative
Report 4: Example of an abridged basic research report
A final note to students
Statistical tables
Glossary of terms
Bibliography
Index
Table of Contents provided by Publisher. All Rights Reserved.

Uma Sekaran is Professor Emerita of Management, Southern Illinois University at Carbondale (SIUC), Illinois.

Dr Roger Bougie lectures in Marketing and Business Research Methods at the Department of Marketing at Tilburg University, The Netherlands.

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