Pre-Conference Workshops

We will conduct following workshops before commencement of the conference:

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1 DAY HANDS ON WORKSHOP ON PLS SEM USING SMARTPLS

Basic concepts of Structural Equation Modeling (SEM) Measurement Model: Formative and Reflective Indicators reliability Internal consistency reliability Convergent validity Discriminant validity Structural Model Testing hypothese

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Series 4: Research Methods (RM)

Course Title

Use of statistics for managers

Course Code

RM4.1

Duration

3 days

Course overview

Decision making is everyday job of all managers. However, not every decision hit the target. It is attributed to poor decision making. One of the major reasons of poor decision making is associated with the quality of data/information used for decision making. The Prospect Theory posits that managers can settle with lesser outcomes than seeking higher benefits either due to time pressure or due to complexity of data or both. It happens because managers often lack ability to handle complex information hence resort to their judgement for making decisions. This training course will empower the participants with certain statistical tools which they can use in analysing complex information sets and making informed decision. That is what we call evidence based decision making. The participants will also learn how to conduct statistical analysis with SPSS.

Objectives

The training will guide the voyage of learning through exploring following questions:

·         What is evidence based decision making?

·         How to framing the problem and identify data requirements?

·         How to analyze data?

·         How to interpret results?

·         How to report results?

Target Groups

Researchers, Faculty Members, Managers, Senior Managers, General Managers, Vice Presidents

Target Sectors

CS, DS, PB and AS

Methodology

A series of lectures, individual and group exercises with SPSS, case studies and issue-specific discussions will guide the participants to acquire learning. Since statistical analysis will be done with SPSS, hence, it is recommended that the participants should bring their laptops with SPSS installed.

Lecture

Exercises

Case study

Discussion

Software

 

Workshop Outline

Major themes covered by training will include:

·         Evidence based decision making

·         Framing the problem and preparing list of data requirements

·         Use of statistics by managers

·         Descriptive Statistics

·         Inferential Statistics

·         Variables

·         Percentiles

·         Measurement

·         Normal distributions

·         T-statistics

·         ANOVA

·         Correlation Analysis

·         Linear Regression

·         Linear Transformations

·         Interpretation and reporting of results (with graphs and other tools)

·         Focusing on Big Picture

·         Backing Judgments

·         Action-planning

 


 

Course Title

Use of SPSS in Statistical Analysis

Course Code

RM4.2

Duration

3 days

Course overview

SPSS is a powerful tool of statistical analysis. It is equally useful for the managers, researchers, consultants and academia. They can analyze complex data (quantitative) by using a variety of statistical methods – grouped mainly into two categories i.e. descriptive statistics and inferential statistics. The participants will also learn how to conduct statistical analysis with SPSS.

Objectives

The training will guide the voyage of learning through exploring following questions:

·         What does SPSS offer you?

·         How to process and enter data into SPSS?

·         How to analyze data?

·         How to interpret results?

Target Groups

Researchers, Faculty Members, Managers, Management Consultants, Research Students

Target Sectors

CS, DS, PB and AS

Methodology

The participants will be guided step by step how to prepare, enter and process data in SPSS, analyze it and report it. Several exercises and case studies will be used to assist the participants in learning the contents. It is recommended that the participants should bring their laptops with SPSS installed.

Lecture

Exercises

Case study

Discussion

Software

 

Workshop Outline

Major themes covered by training will include:

·         Preparing data

·         Setting up a file for data entry – for the defined variables, defining variable properties

·         Identifying and treating missing values and outliers

·         Computing and recoding variables

·         Distributions of data

·         Descriptive statistics: mean, mod, median, skewness, kurtosis

·         Creating box-plots and histograms

·         Testing hypothesis

·         T-statistics

·         ANOVA

·         Correlation Analysis

·         Linear Regression

·         Factor Analysis

·         Generalized Linear Models

·         Action-planning

 

 

Course Title

Use of AMOS for data analysis

Course Code

RM4.3

Duration

3 days

Course overview

Structural Equation Modelling (SEM) is a multivariate data analysis technique. It involves testing of complex relations among variables.  It is being extensively used by researchers in disciplines like Management Sciences, Marketing, Finance, HR, Psychology, Economics, Sociology, Health, Education etc. There are two approaches to do SEM i.e. 1) Covariance-Based SEM (CB-SEM); and 2) Partial Least Square – SEM (PLS-SEM). AMOS is widely used for CB-SEM. This workshop will follow CB-SEM approach.

Objectives

The training will guide the voyage of learning through exploring following questions:

·         What does AMOS offer you?

·         How to prepare data in SPSS for analysis in AMOS?

·         How to draw measurement model in AMOS and load data?

·         How to run CFA in AMOS?

·         How to examine goodness of fits (GoF) and finalize measurement model?

·         How to analyse structural model, refine it and test hypotheses?

·         How to test mediation and moderation with AMOS?

·         How to interpret results?

Target Groups

Researchers, Faculty Members, Managers, Management Consultants, M and PhD Research Students

Target Sectors

CS, DS, PB and AS

Methodology

The participants will be guide step by step how to develop, test, refine and finalize measurement models and structural models and testing hypotheses by using AMOS. Several exercises and case studies will be used to assist the participants in learning the contents. It is recommended that the participants should bring their laptops with AMOS installed.

Lecture

Exercises

Case study

Discussion

Software

 

Workshop Outline

Major themes covered by training will include:

·         Introduction to SEM

·         Examining suitability of data for SB-SEM

·         Exploratory Factor Analysis

·         Confirmatory Factor Analysis

·         Pattern Matrix Model Builder

·         SEM Analysis

·         Mediation Analysis

·         Moderation Analysis

·         How to interpret and report results

·         Action-planning

 

 

 

Course Title

Use of SmartPLS for data analysis

Course Code

RM4.4

Duration

3 days

Course overview

Structural Equation Modeling (SEM) is a multivariate data analysis technique. It involves testing of complex relations among variables.  It is being extensively used by researchers in disciplines like Management Sciences, Marketing, Finance, HR, Psychology, Economics, Sociology, Health, Education etc. There are two approaches to do SEM i.e. 1) Covariance-Based SEM (CB-SEM); and 2) Partial Least Square – SEM (PLS-SEM). SmartPLS is widely used for PLS-SEM. This workshop will follow PLS-SEM approach. This course is being organized in collaboration with the company owning the SmartPLS. All registered participants of this course will get a 2-month free license of SmartPLS. Besides, certain discount will also be available for those registered participants who are interested to purchase license beyond two month free period. 

Objectives

The training will guide the voyage of learning through exploring following questions:

·         What does SmartPLS offer you?

·         How to prepare data in MS Excel (CSV – Comma Delimited) for analysis in SmartPLS?

·         How to draw measurement model in SmartPLS?

·         How to carry out PLS Path Model estimation?

·         How to assess measurement model results and refine it?

·         How to assess structural model and test hypotheses?

·         How to test mediation and moderation with SmartPLS?

·         How to interpret results?

Target Groups

Researchers, Faculty Members, Managers, Management Consultants, M and PhD Research Students

Target Sectors

CS, DS, PB and AS

Methodology

The participants will be guide step by step how to develop, test, refine and finalize measurement models and structural models and testing hypotheses by using SmartPLS. Several exercises and case studies will be used to assist the participants in learning the contents. It is recommended that the participants should bring their laptops with SmartPLS installed.

Lecture

Exercises

Case study

Discussion

Software

 

Workshop Outline

Major themes covered by training will include:

·         Introduction to SEM

·         Examining suitability of data

·         Preparing data in MS Excel (CSV – Comma Delimited)

·         Convergent Validity

·         Discriminant Validity

·         Testing and refining measurement model

·         Bootstrapping

·         Blindfolding

·         f2 effect size, Omission distance (D), Q2 effect size

·         Assessing structural model and testing hypotheses

·         Mediation Analysis

·         Moderation Analysis

·         Interpretation and reporting of results

·         Action-planning

 


 

Course Title

Research Methods for Managers

Course Code

RM4.5

Duration

3 days

Course overview

Successful managers adopt the approach of evidence based decision making instead of following conventional opinion-based approach of decision making. However, it requires the managers to understand basics of research methods so that they can appropriate frame the decision problem, devise valid and reliable measures, collect data with minimal influence of biases, analyze the data and infer the results needed for making decisions. This training workshop will empower the participants with basics of research methods in all the afore-mentioned areas. Major focus of this training will be on quantitative approach.

Objectives

The training will guide the voyage of learning through exploring following questions:

·         Why research methods for the managers?

·         What are stages of research?

·         What are the protocols for conducting research?

·         How to framing the problem and identify data requirements?

·         How to devise data collection instruments?

·         How to analyse data?

·         How to interpret results?

·         How to report results?

Target Groups

Managers, Senior Managers, General Managers, Vice Presidents, Students, Researchers

Target Sectors

CS, DS, PB and AS

Methodology

A series of lectures, individual and group exercises, case studies and issue-specific discussions will guide the participants to acquire learning. Since statistical analysis will be done with SPSS, hence, it is recommended that the participants should bring their laptops with SPSS installed.

Lecture

Exercises

Case study

Discussion

Software

 

Workshop Outline

Major themes covered by training will include:

·         Introduction to research

·         Research process

·         Relationship between theory and research

·         Quantitative and qualitative research methods

·         Framing the problem and identifying variables

·         Sampling and measurement

·         Constructing an effective questionnaire

·         Data collection

·         Data analysis

·         Interpretation of results and use in decision making

·         Action-planning

 

 

 

Course Title

Case Writing

Course Code

RM4.6

Duration

3 days

Course overview

Writing cases is a fun. Many people have good stories and want to write case studies. But many of them don’t because they feel that they lack skills to write cases. This training workshop will assist them in developing attitude and ability to write cases. They will gain experiential learning about writing cases studies. They will learn to identify a hook in a story, develop a case synopsis, then prepare case and write teaching manual.

Objectives

The training will guide the voyage of learning through exploring following questions:

·         What is a case and what elements of a good case?

·         How to identify a hook in a business story?

·         How to prepare a case synopsis?

·         How to prepare a case?

·         How to prepare a case manual?

Target Groups

Trainers, faculty members, managers, senior managers, general managers, vice presidents, students, researchers

Target Sectors

CS, DS, PB and AS

Methodology

A series of lectures, individual and group exercises, case studies and issue-specific discussions will guide the participants to acquire learning. The participants are recommended to bring any good business story and supporting material.

Lecture

Exercises

Case study

Discussion

-

 

Workshop Outline

Major themes covered by training will include:

·         Introduction to case writing

·         Framing the problem

·         Identification of hook

·         Research work for case writing

·         Writing case synopsis

·         Preparing case

·         Preparing teaching notes

·         Refining case

·         Abstracts

·         Editing and proofreading

·         Fine tuning it for publication

·         Action-planning

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