Giuseppe (Joe) Labianca (Umass-Amherst/DRP)

20 January 2022

Social Network Analysis

27 January 2022

3 Feburary 2022

22-23 Feburary 2022

Formal Modeling for Management

23-24 March 2022

Econometrics of Matching Games

28 March 2022

Policy Careers

3 April 2022

Niels Van Quaquebeke

5 January 2021

2:00 to 3:00pm

Respectful inquiry: The story and the story behind the story

Hannes Leroy

6 January 2021

3:00 to 4:00pm 

Story behind the paper: Publishing in Journal of Applied Psychology

Berrin Erdogan

7 January 2021

2:00 to 4:00pm 

Story behind the paper: How to respond to reviewer comments

Tom Vanacker

14 January 2021

2:00 to 4:00pm 

How to frame papers that draw data from financial databases

Priya Kannan, Ronit Kark

27 January 2021

2:30 to 4:00pm  

Action research and taking research into practice 

Jessica Methot, Jill Perry-Smith, Stefano Tasselli

3 Feburary 2021

2:30 to 4:00pm (Panel Workshop)

Tips on writing theory papers

Jamie Ladge

9 Feburary 2021

2:30 to 3.30pm

Developing interview protocols

Joe Labianca

18 Feburary 2021

2:00 to 4:00pm

Tips on being a reviewer

Alessandro Lomi

26 Feburary 2021

3:00 to 4:00pm 

Best practices in network modelling

Ana Ortiz de Guinea Lopez de Arana

2 March 2021

1:30 to 3:30pm

Topic TBC, probably meta-analysis 

Ana Ortiz de Guinea Lopez de Arana

3 March 2021

2:30 to 4:00pm

Topic TBC, probably meta-analysis 

Joe Labianca, Stefano Tasselli

9 March 2021

1:00 to 3:30pm   

Research design and action research within organizations 

Hannes Leroy

25 March 2021

3:00 to 4:00pm 

How to frame and develop a literature review 

Gabriel Katz

29 March 2021

9:00am to 5:00pm

R training (part 1)

Gabriel Katz

30 March 2021

9:00am to 5:00pm

R training (part 2)

Ben Meehan

31 March 2021

9:00am to 5:00pm

NVIVO training (part 1)

Ben Meehan

01 April 2021

9:00am to 5:00pm

NVIVO training (part 2)

Iulia Cioroianu (Institute for Policy Research, University of Bath)

01 April 2021

Introduction to Python

Language Processing / Machine learning in Python

Introduction to Nvivo

Iulia Cioroianu

22 April 2021

9:00am to 5:00pm

Python training (part 1)

Iulia Cioroianu

23 April 2021

9:00am to 5:00pm

Python training (part 2)

Jonas Lang

4 May 2021

1:30 to 3:30pm

Multilevel models (basic)

Jonas Lang

11 May 2021

1:30 to 3:30pm

Multilevel models (intermediate 1)

Jonas Lang

18 May 2021

1:30 to 3:30pm

Multilevel models (intermediate 2)

Jonas Lang

25 May 2021

1:30 to 3:30pm

Multilevel models (advanced)

Jonas Lang (Ghent/DRP)

13 September 2021

Structural Equation Modeling

Greg Molecke

11 October 2021

Herman Aguinis (George Washington/DRP)

25 October 2021

Colleen Cunningham (LBS)

15 November 2021

Elena Spatoulas Patel

22-23 November 2021

John Antonakis

(Editor-in-chief: The Leadership Quarterly)

The Endogeneity problem in mediation analysis 

Random effects assumption in multilevel models 

Introduction to R/ Regression analysis in R (Stata)

Gabriel Katz (Q-Step Centre, University of Exeter)

31 March 2020

Factor analysis / Structural equation modelling in R (Stata)

Jill Perry Smith, Berrin Erdogan

30 September 2020

Jill: 2:30 to 3:10pm,                  

Berrin: 3:20 to 4:00pm

Meet the editor: Insights from an Associate Editor of Academy of Management Journal and Editor-in-Chief of Personnel Psychology

Our first Research Methods Centre workshop will feature two of our Distinguished Research Professors.

Jill Perry-Smith was an Associate Editor, Academy of Management Journal (2016-2019), and has been a board member of Organization Science, Journal of Applied Psychology, Academy of Management Review, and Academy of Management Journal. Jill will present ideas on how to tackle journal revisions and common reasons that articles get rejected and how to address them. There will be the opportunity to ask questions at the end.

Berrin Erdogan is the Editor-in-Chief of Personnel Psychology. Berrin will provide information about publishing in Personnel Psychology. These unique insights are relevant for publishing in other psychology and management journals. The talk will contain tips relating to idea generation, research design, writing, and revising articles to increase success in the publication process. There will be the opportunity to ask questions at the end.

Jessica Methot, Jamie Ladge

06 October 2020

2:00pm to 3:30pm (Panel Workshop)

Practical implications of research and getting media attention

An important element of our job as academics is to conduct research that builds and extends knowledge of a vast range of management-oriented phenomena. However, some scholars struggle to understand the practical significance of their work and how to translate and disseminate their research to practitioners. This presentation is designed to help scholars talk about the relevance of their work to non-academic audiences – including practice-based business magazines and journals as well as the popular press. Professors Ladge and Methot will describe their experiences sharing their research with these various outlets. They will discuss approaches to writing and connecting with practitioner audiences, and methods of “translating” academic insights in ways that spark interest with practicing managers. They will also offer strategies for how to leverage the use of practice-oriented writings and media attention (e.g. for classroom use, research, and/or to gain credibility in the field).

Markus Fitza

15 October 2020

2:30 to 4:00pm

Current approaches to publishing quantitative analysis (e.g., replication, p-values)

In recent years a variety of voices raised concerns about the reproducibility of results in management studies (e.g., Banks et al.,2016; Bettis, 2012; Bettis, Helfat, and Shaver, 2016; Goldfarb and King, 2016). These concerns echo a discussion in other scientific fields. For example, Ioannidis (2005) estimates that more than 50% of studies in the clinical sciences may be false positives (type I errors) and will thus not reproduce. At the core of this discussion are concerned about how traditional statistical model fitting techniques are used in management research. But progress has already been made, for example, the Strategic Management Journal dropped the practice of using p-value cutoffs and now encourages replications. In this workshop, I will discuss some of the issues underlying this discussion, what suggestions have been made to tackle the problem and what the emerging changes in various journals mean for our research practice.

Tom Vanacker

22 October 2020

2:00 to 4:00pm

Creative use of databases (relevant to HR, finance, entrepreneurship, organisational behaviour)

Scholars in a wide range of fields often focus on publicly traded firms—generally pushed by data availability. While publicly traded firms were all once young, small, and privately held, we cannot simply generalize what we know from publicly traded firms to privately held firms. Moreover, privately held firms represent 97.5% of all incorporated entities in the United Kingdom. Data availability (and quality) related to privately held firms has increased dramatically in recent years. In this seminar, I will discuss some interesting databases on privately-held firms; how they might be used to develop new theory; highlight common (sometimes false) critiques on these databases; and, how they might be used creatively (based on my own experience) to get published in a broad range of journals, including Academy of Management Journal, Strategic Management Journal, Organization Science, Entrepreneurship Theory and Practice, Journal of Business Venturing, Journal of Banking and Finance, and Journal of World Business. ​

Nils Van Quaquebeke, Jonas Lang

29 October 2020

2:30 to 4:00pm (Panel Workshop)

Meet the editor: Beyond the questionnaire at Leadership Quarterly and insights from the publication process at Journal of Applied Psychology and Organizational Research Methods

The Journal of Applied Psychology and The Leadership Quarterly are top journals in management and applied psychology. Join this Q&A session with Jonas W. Lang (Associate Editor at JAP) and Niels Van Quaquebeke (Senior Associate Editor at LQ) and ask them everything you always wanted to know about how best to navigate the publication process in these journals? What do the editors look for in manuscripts? What can you as a submitter do to increase the likelihood of your manuscript getting into review and ultimately accepted? This session is yours. So take ownership. A week before a slid.do link will be posted here where you can (anonymously) post your questions.

Markus Fitza

05 October 2020

2:30 to 4:00pm

Variance decomposition analysis

Variance decomposition is frequently used in management research. It is usually used to determine the impact of a given effect class on a dependent variable. An example might be useful to illustrate the utility of this approach relative to more conventional approaches such as linear regression: One use of variance decomposition in management studies was to determine the importance of CEOs for firm performance (e.g., Ahn et al., 2004; Lieberson and O'Connor, 1972; Mackey, 2008; Thomas, 1988; Wasserman et al., 2001). While some studies try to answer this question by analyzing the performance effect of certain CEO characteristics (such as age, experience or education etc…) a variance decomposition follows a more general approach. Because CEO characteristics are a complex set of features, some of which can increase performance while others can decrease it, it is difficult to determine the overall magnitude of the impact of CEOs with a regression analysis that uses proxies for the full set of all possible underlying CEO features that may affect performance.

Rather a variance decomposition study of CEO influence captures the performance effect of CEOs in its totality. Instead of asking which features of a CEO effect firm performance it asks what is the overall impact of CEOs. This approach helps to answer a fundamental question: If we want to understand differences in firm performance, how much can studies of for example CEOs help us towards that goal? In the past this approach was use to measure the impact of a variety of effect classes on firm performance such as the effect of industry, region, corporate parent, business group, CEOs, VCs, etc. While performance is usually the main dependent variable of interest variance decomposition can also be used to investigate alternative DVs, for example to estimate how much certain effect classes influence the degree of diversification or M&A activities.

In this workshop I will discuss the use of variance decomposition in management research: What types of research questions it can help answer, various methodological approaches, and how one can manage the review process for variance decomposition paper given that the method is not necessarily known to all reviewers.

Anthony Heyes

12 November 2020

2:30 to 4:00pm

Research design for causal inference: Methods from economics for non-economists (part 1)

Much empirical research coming out of business schools presents evidence of correlation (X is associated with Y) but is written up in a way that implies a causal relationship (X causes Y).

Economics has moved decisively away from correlational analysis towards methods that explicitly allow for causal inference. Much of this work is very creative, making clever use of ‘natural experiments’. Now the norm in economics, such designs are increasingly prominent in top journals in other business school disciplines. The presentation will sketch the methods (IV, RDD and DiD) in a non-technical manner and explore how they might make your own empirical research more marketable. Focus will be on research design – setting up a study that has causal interpretability “baked in” from the start – and we will touch on lots of examples. The talks are mainly for people less familiar with these approaches, but everyone is welcome.

Anthony Heyes

19 November 2020

2:30 to 4:00pm

Research design for causal inference: Methods from economics for non-economists (part 2)

Much empirical research coming out of business schools presents evidence of correlation (X is associated with Y) but is written up in a way that implies a causal relationship (X causes Y).

Economics has moved decisively away from correlational analysis towards methods that explicitly allow for causal inference. Much of this work is very creative, making clever use of ‘natural experiments’. Now the norm in economics, such designs are increasingly prominent in top journals in other business school disciplines. The presentation will sketch the methods (IV, RDD and DiD) in a non-technical manner and explore how they might make your own empirical research more marketable. Focus will be on research design – setting up a study that has causal interpretability “baked in” from the start – and we will touch on lots of examples. The talks are mainly for people less familiar with these approaches, but everyone is welcome.

Priya Kannan

25 November 2020

3:00 to 4:00pm 

Developing research questions and construct clarity

Theoretically, how individuals reconstruct available resources to effect new opportunities has been at the heart of entrepreneurship and innovation research for the past two decades (e.g. Baker and Nelson, 2005, Feldman, 2004; Feldman and Worline, 2011, Garud and Karnoe, 2003). Practically, nothing highlights the need to reconstruct resources quickly and effectively to pursue new opportunities such as unexpected crises, the most recent case being the pandemic. Entrepreneurial firms, as well as, large organizations swiftly reconfigured their resources and shifted them to pursue new entrepreneurial opportunities brought forth by the pandemic. For example, General Motors swiftly reconfigured their resources and shifted them to producing ventilators while some award winning, high end dining restaurants foresaw new opportunities in burgers, take outs, and reconfigured resources to pursue these unexpected opportunities. Resource reconstruction is addressed by several terms such as effectuation (Sarasvathy, 2001), bricolage (Baker &Nelson, 2005), and resourcing (Feldman, 2004) and others. Based on a working paper, the purpose of this talk is to delineate the differences in how resources can be understood and constructed differently based on the phenomenon that is under consideration.

Ronit Kark

01 December 2020

1:00 to 2:00pm   

Publishing qualitative research: Success, rejections and lessons learned

Giuseppe Cavaliere

08 December 2020

1:00 to 3:30pm   

Bootstrap methods for economists (part 1)

Iulia Cioroianu, University of Bath

1 April 2019

Introduction to Python

Iulia Cioroianu, University of Bath

2 April 2019

Collecting and analysing social media data using Python

Required: Intro to Python

Eva Neitzert, London School of Economics and Just Economics

3 April 2019

Evaluation and impact assessment 

Julian Jamison, University of Exeter, Economics

4 April 2019

Experimental methods

Pikakshi Manchanda, CSAM, University of Exeter

5 April 2019

Introduction to Natural Language Processing in Python

Required: Intro to Python

Ben Meehan, QDA Training

8 April 2019

Introduction to NVivo

Ben Meehan, QDA Training

9 April 2019

NVivo Underway – analysing your data NVivo

Required: Intro NVivo. Max 16 people

Gabriel Katz, Q-Step Centre, University of Exeter

10 April 2019

Multilevel Models in R and Stata

Iulia Cioroianu (University of Bath)

8 July 2019

Online surveys in Qualtrics, survey experiments, and causal inference

Mike Gill (University of Oxford)

9 September 2019

Of qualitative methods and phenomenology (Canceled)

Intermediate social network analysis

Required: Intro to Social Network Analysis

Advanced NLP and Machine Learning for text analysis

Required: Intro to Python

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