Management Research Methodology: Integration of Principles, Methods and TechniquesThe subject of management research methodology is enthralling and complex. A student or a practitioner of management research is beguiled by uncertainties in the search and identification of the research problem, intrigued by the ramifications of research design, and confounded by obstacles in obtaining accurate data and complexities of data analysis. Management Research Methodology: Integration of Principles, Methods and Techniques seeks a balanced treatment of all these aspects and blends problem-solving techniques, creativity aspects, mathematical modelling and qualitative approaches in order to present the subject of Management Research Methodology in a lucid and easily understandable way. |
Contents
Part A Scientific Method in Management Research | 1 |
Overview of Research in Management | 19 |
Suggested Readings | 42 |
Formulation of Research Problems | 68 |
1An Example of Taxonomy | 94 |
5System Study and Problem FormulationAllocation | 101 |
Research Proposal | 109 |
Experimental Research | 121 |
108 | 362 |
Bivariate Analysis and Hypothesis Testing | 370 |
Analysis of Experimental Data | 388 |
Multivariate Analysis of DataDependence Analysis | 408 |
Multivariate Analysis of Data IIInterdependence Analysis | 443 |
Multidimensional Scaling MDS | 456 |
Summary | 467 |
Appendix AlSystem Concept | 487 |
Ex Post Facto Research by Nature of Study | 164 |
Qualitative Research Methods | 170 |
Evaluation Research | 180 |
5An Example for Case Study Research | 186 |
Modelling Research IIHeuristics and Simulation | 219 |
Research Design for Data Acquisition | 259 |
Data Collection Procedures | 297 |
Part F Data Analysis and Reporting | 341 |
KolmogorovSmirnov Test | 360 |
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action research advertising algorithm ANNEXURE approach aspects behaviour causal cent cluster cluster sampling coefficient complex construct Contd correlation cost creative cross tabulation data collection data mining decision decision-making developed discussed distribution effect error estimate evaluation example experiment experimental design external validity factor analysis field study generalisation genetic algorithms heuristic methods hypothesis testing important independent variables interaction internal interviews inventory large number linear management research mathematical matrix means measurement meta-heuristics multidimensional scaling null hypothesis objective observation obtained operations optimal solution optimisation organisation output parameters participant observation performance population problem instances procedures programme qualitative research questionnaire questions random numbers random sample regression relationships reliability research design respondent scale selected significance simulation model situation social solving statistical structure subjects survey Table tabu search techniques tion treatment variance WHBS