Outcomes

After attending this module the attendees should be able to:

• Make participants well aware of the practical problems which are to be confronted during higher degree dissertation
• Have a clear understanding of planning the research proposal and developing a research report/dissertation
• Develop scientific attitude and broad understanding of the use of research
• Develop succinct hypothesis based on relevant research gap, support it empirically, theoretically and econometrically and tie results to outcomes viable for practitioners
• Understand qualitative and quantitative research methods and their application to research
• Develop and validate primary research instrument for data collection and to manage field operations
• Develop an understanding regarding importance of theory development
• Participants will develop a basic understanding of the relationship between specific research designs and statistical approaches
• Operate SPSS software, step by step, starting from the initial level till the advanced inferential statistical analysis and interpretation
• Reference data using online and offline software’s
• Attendees will appreciate the basic elements of the publishing process

Workshop Content

Topic Selection & Problem Identification

• The challenges of managing self & research environment
• Basic factors to select research topic
• Focusing on research problem
• Delimitating research

Literature Reviewing Techniques

• Literature reviewing techniques
• Drafting structure of Literature Review
• Identifying controversies & GAP
• Writing Literature review (Citation styles, paraphrasing, Language focus, Reporting verbs)

Theoretical and Conceptual Framework Development

Methodological Framework

• Sampling technique selection, Sample size calculation, Sample to generalizability
• Variable type & Data collection technique
• Scale development techniques

SPSS

Introduction Stage

• SPSS basics; Output and data view, Data coding, Defining Variable & data entry, right scale allocation

Data Preparation Stage

• Computing Variables
• Dealing with missing variables
• Creating dummy variables
• Variable re-specification
• Scale transformation
• Dealing with unreliable data (reliability and validity analysis); factor analysis

Data Analysis Stage

Equip attendees with the understanding of the relationship between specific research designs,
advanced statistical and econometric approaches, analysis, interpretation and managerial implications.

Advanced Data Analysis Techniques

• Time Series Analysis (stationarity, cointegration, forecasting models)
• Panel Data Analysis (fixed effects, random effects, pooling models)
• Volatility Modeling (GARCH, EGARCH and related models)
• Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA)
• Partial Least Squares Structural Equation Modeling (PLS-SEM)
• Advanced Regression Techniques (logistic regression, hierarchical regression, moderation & mediation analysis)
• Multivariate Analysis (MANOVA, MANCOVA and discriminant analysis)
• Handling econometric issues such as endogeneity, heteroskedasticity and autocorrelation
• Model diagnostics, robustness checks and validation of results

Software for Advanced Analysis

• SPSS
• SmartPLS (for PLS-SEM modeling and analysis)

Selling your Research & Impact Factor Publication

• Citation & referencing in research using Endnote (X4)
• Ways of writing abstract
• Tips to get impact factor publication
• Techniques of getting fund for conference/ research paper publication
• Selling your research work

Workshop Duration:

2–3 days maximum

Note:

Send email at
register@abmconferemces.com
to register for research workshop, before/after conference.

We also arrange customized “research workshop” for universities/institutes, on special request.
For further details, send email at
register@abmconferemces.com.