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Summer School in Advanced Research Methods 

Summer School 2014

This summer Aston Business School will be delivering a series of Advanced Research Methods courses designed to equip you with the specialist skills needed to become a leader in your chosen academic field.

Unlike most summer schools our programme is comprised of short, affordable courses, typically one to two days in length. The courses will be delivered by Aston’s internationally renowned faculty and will be highly practical in nature.

Courses are open to students (Research Masters and PhD) and faculty from any university, as well as industry researchers.  If required, an assignment can be completed as part of the course for those who need a grade in the subject area.  This will be in addition to a formal certificate of attendance.  The courses will be small enabling you to receive individual attention from our experts.

Further detail of the courses, including bibliographies where relevant are available for download from each course link.  Participants should do the basic reading for their courses in advance in order to maximise the learning.  All courses run from 9.00-5.00 each day.

All courses are subject to cancellation.  Applicants will normally be informed of any cancellation a minimum of one week prior to the course start date.

1 day work courses

  • Student £75
  • Academic £125
  • Industry/Other £175   

2 day work courses

  • Student £150
  • Academic £250
  • Industry/Other £350  

3 day work courses

  • Student £225
  • Academic £375
  • Industry/Other £525    

July

Dr Julien Schmitt
Date: 21 -22 July 2014

Pre-requisites/Target Audience:

The target audience for this course is early-career researchers and graduate students in Business and Management, Psychology, and other social sciences, with an interest in designing and conducting experiments. Participants should be familiar with basic statistics.

Overview:

The main objectives of this workshop are:

  • To familiarize participants with the key elements of experimental designs.
  • To enable participants to critically examine experimental settings encountered in research papers.
  • To enable participants to build experiments for their own research.

Full course outline

August

Dr Matti Jaakkola
Date: 11 -12 August 2014

Pre-requisites/Target Audience:

The target audience for this course is early-career scholars in Business and Management, and other social science disciplines, with an interest in set-theoretic methods. In addition to PhD students, members of faculty may also find the topic useful in helping broadening their methodological tool box. Participants are not expected to have prior knowledge of set-theoretic approaches. However, they should find previous exposure to set theory and corresponding analytical approaches useful.

Overview:

After completing this course, participants will:

  • be familiar with set-theoretic approaches in social sciences
  • understand the advantages and disadvantages of set-theoretic approaches in general, and qualitative comparative analysis (QCA) in particular
  • understand the analytical process of QCA 
  • be able to conduct different kinds of QCA with fs/QCA software, and report the findings 
  • be able to critically assess QCA-based research    

The objectives will be achieved when participants actively engage with the lectures, discussion of the supporting literature, and the data analysis sections of the course.

Full course outline

Kristina Schmidt
Date: 13 -14 August 2014

Pre-requisites/Target Audience:

This course is useful for people from various backgrounds, particularly for (1) those seeking a beginners’ to intermediate course in Structural Equation Modelling (SEM) and (2) those with previous experience who wish to learn about using R, specifically the “lavaan” package. A basic knowledge of introductory statistics (e.g., variance, covariance, correlation, and (multiple) regression analysis) will be advantageous to participants; however, no prior knowledge or experience with SEM or R is assumed. In general, this course may put more emphasis on basic or advanced topics in accordance with the level of participants.

Overview:

The objective of this two day course is that at the end, participants will (1) have a good understanding of the basic theory of SEM and (2) be able to implement SEM-type analyses with R. Hence, this course will be taught as part lecture and part applied workshop. 

Full course outline

Dr Andrew Farrell
Date: 20 - 21 August 2014

Pre-requisites/Target Audience:

The target audience for this course is early-career researchers and graduate students in Business and Management, Psychology, and other social sciences, with an interest in latent variable modelling. Participants should be familiar with exploratory and confirmatory factor analysis, and correlation and linear regression.

Overview:

After completing this course, participants will:

  • Be familiar with the theory of discriminant validity;
  • Understand how to assess discriminant validity using a number of techniques;
  • Understand the advantages and disadvantages of the various techniques;
  • Be able to calculate and report discriminant validity assessment for latent variable models, using popular software e.g. SPSS, LISREL, Lavaan/R   

Full course outline

From Research Design to Publication

Drs Stephanie Decker and  Carola Wolf
Date: 27 - 28 August 2014

Pre-requisites/Target Audience:

This course is targeting PhD students and academics with an interest in qualitative approaches to management and organization studies. We will discuss different traditions and templates for designing qualitative research, data collection and analytical strategies, and publishing results in management journals. The course requires all participants to have a basic understanding of qualitative research methodologies including basic research designs, data collection strategies and analytical techniques (e.g. Flick, 2009; Miles & Huberman, 1994).

Overview:  

Full course outline

September

Dr Ali Emrouznejad
Date: 1 - 2 September 2014

Pre-requisites/Target Audience:

Basic knowledge of calculus and statistics, quantitative skills would be an advantage

Overview:

The aim of this course is to introduce many of the important idea in data mining with focus of analysing big data, explain them as statistical framework, and describe some of their applications in Business, Finance, Marketing, and Management. Hence, this course covers data mining techniques and their use in managerial business decision making. 

Full course outline

Dr Ali Emrouznejad
Date: 3rd September 2014

Pre-requisites/Target Audience:

Basic knowledge of calculus and statistics, quantitative skills would be an advantage 

Overview:

The aim of this course is to introduce principles, issues, techniques and solutions connected with text mining. At the end of this course students will gain knowledge of how recent advances in text mining could help an organization to search for new knowledge by organising, characterising, finding and exploiting large scale textual/unstructured information.


Full course outline

Dr Breno Nunes
Date: 8 September 2014

Pre-requisites/Target Audience:

Introductory level of knowledge on Business & Management studies (in particular international business)

Recommended book: 

  • Charles W. L. Hill, International Business, 9th edition, McGraw-Hill Higher Education, 2013.   

Introductory level of knowledge on Business & Management research methodologies (either qualitative or quantitative):

Recommended books:

  • Lee, N., & Lings, I. (2008). Doing business research: a guide to theory and practice. Sage.
  • Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage.   

Overview:

By the end of this course, participants should be able to:

  • Identify the particularities of doing cross-country research
  • Develop a robust plan to conduct cross-country research
  • Recognise the value of cross-country investigation and deploy data analysis techniques that strengthen your research results.

 

Full course outline

Professor Emanuel Thanassoulis and Dr Ali Emrouznejad
Date: 9 - 10 September 2014

Pre-requisites/Target Audience:

Knowledge of linear programming will enable the participant to better understand the underlying theory of DEA but it is not a pre-requisite. The DEA method will be applied using software which automatically create and solve the models needed and so those unfamiliar with linear programming will still be able to carry out assessments and interpret the findings.

Overview:

The aim of this course is to provide an understanding of performance measurement and  management  using  Data Envelopment Analysis (DEA). The focus is on applications both in the private and public sector, enabling delegates to see how real situations can be modelled in the DEA framework to estimate the scope for input and output improvements, including productivity change over time and any scope for scale economies. The course would be of interest to those assessing performance of organisational units, for instance, banks, hospitals, retail companies, energy companies, water companies, hotels, schools, government departments.

The teaching is based on short interactive lectures with small group working  on hands on examples using appropriate software. The main objectives are to:

  • Learn about new methods in efficiency and productivity analysis;
  • Understand the principles behind DEA;
  • Get hands-on experience with  the “PIM-DEA”  software from the developers;
  • See how to improve the efficiency and productivity of decision making units;
  • Discussion of sample  applications  of DEA in the delegates’ workplace. 
Full course outline

Professor Emmanuel Thanassoulis and Dr Dimitris Giraleas
Date: 11 - 12 September 2014

Pre-requisites: 

Knowledge of basic statistics and regression analysis will enable the participant to better understand the underlying theory of econometric methods and initial introductory reading will be recommended for participants to undertake before joining the course.  However, knowledge of econometric modelling and prior experience with Stata, although beneficial, is not required.

Overview:

The aim of this course is to introduce participants to the econometric modelling of production and costs functions and to demonstrate how these concepts can be used to measure the efficiency of the relevant units that engage in these functions. The focus of this course will be on the practical applications of such techniques such as Corrected and Modified OLS (COLS and MOLS) and Stochastic Frontier Analysis (SFA), which is one of the most widely-used efficiency measurement approaches. The course includes a theoretical component, delivered mainly through short, interactive lectures, but the main focus is on a series of hands-on sessions that will allow the delegates to gain first-hand experience on how these techniques can be applied in practice.  The course would be of interest to those assessing performance of organisational units, both in the private but also in the public sector. The main objectives of this course are: 

  • To introduce the participants to the notions of production and cost functions and how these can be transformed to frontier for the purposes of benchmarking. 
  • To provide an overview of the most commonly used econometric techniques used for efficiency assessment and benchmarking. 
  • To provide hands-on experience in the use of Stata, one of the most widely used econometric software package, for the purpose of applying the aforementioned techniques and carrying out a benchmarking exercise. 

Full course outline 

Dr Yves Guillaume
Date: 15 - 16 September 2014

Pre-requisites/Target Audience:

Participants should understand basic concepts of statistical inference. The concepts will, however, be reviewed during the course.

Overview:

The course aims to provide participants with the understanding and experience to conduct a meta-analysis using the Hunter and Schmidt method. Specifically, participants will learn how to conduct a meta-analysis of correlations (e.g., field studies) and effects sizes (e.g., intervention studies), correct for common artifacts (e.g., sample size, measurement unreliability), and test for potential moderators. Teaching will be example-based, drawing on real data to demonstrate the use of meta-analysis. Conceptual understanding will be emphasized without necessary technical detail.

Full course outline

Contact Us

To find out more details, send an enquiry: abssummerschool@ aston.ac.uk

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