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All posts from Ph.D International Business Syllabus : Pondicherry University

University : Pondicherry University
Announcement : Syllabus
Degree : Ph.D
Subject : International Business

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International Business Syllabus :

Part – I :
Unit – I :
Introduction to research, research types – Overview of Research Process – Qualitative Research Studies and designs – Theory Building – Hermeneutics, Phenomenology and Action Research – Grounded Theory.

Related : Pondicherry University MBA Banking Technology Syllabus :

Unit – II :
Research Plan and design – Formulating a Research Problem, research questions – Plan for data analysis – Design of Instruments – Measurement and Scaling Techniques.

Unit –III :
Tools of qualitative data Collection : primary, and secondary; observation depth Interview, focus group discussion – Use of projective Techniques – Interviewing and moderation skills in qualitative Data Collection – Selecting Method of Data Collection – Data editing, processing & categorization.

Unit – IV :
Introduction to data analysis : quantitative – Traditional qualitative Data analysis – e.g. Content Analysis and Interpretation – Integration of qualitative and quantitative data analysis – Consumer Insight Mining (CIM) using Traditional and Non-traditional Methods (Narrative, Rhetorical, Text Analysis and Metaphor, Obituary, NLP)

Unit – V :
Application of software tools, use of library databases, review of articles, exploring various data sources, understanding bibliography, structuring of a thesis/report, use of different referencing styles e.g. APA, Report Writing, presentations, and Research Proposal.

Part – II :
Unit – I :
Basic statistics, probability, probability distributions, expectation, distributions-discrete, and continuous, parametric and non-parametric, sampling, sampling distribution, sampling methods, sample size determination, sampling errors, theory of estimation, correlation, simple regression model.

Unit – II :
Classical Linear Regression Models (CLRM), Generalized Regression Models and Issues Related Assumptions of Normal CLRM (heterscendastictiy, autocorrelation, multi- collienerity, structural stability, etc.), errors in variables, dummy variable regression analysis (probit / tobit / logit etc), non-linear regression models.

Unit – III :
Design of experiments, Repeated Design of Experiments, Discriminate Analysis
Unit – IV :
Introduction to multivariate Analysis, Factor Analysis, Cluster Analysis, Multi-dimensional Scaling Techniques (MDS), conjoint Analysis.

Unit – V :
Structural Equation Modeling (SEM) : Introduction to simultaneous equations-concept of structured form and reduced form-problem of identification, 2-stage least squares, Discrete Variable Analysis, Introduction to time series, Panel Data Model and Analysis.

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