Fast Facts

  • Registration Deadline: June 15, 2020
  • Clinic Organizers:
    • RM-SIG President: Stewart Miller, University of Texas at San Antonio (USA)
    • RM-SIG VP – External Relations: Bo Nielsen, University of Sydney (Australia)
    • RM-SIG VP – Communications: Catherine Welch, University of Sydney (Australia)
    • RM-SIG VP – Treasurer: Roberta Aguzzoli, Durham University (UK)
    • RM-SIG VP – Program: Aggie Chidlow, University of Birmingham (UK)
    • Consortium for the Advancement of Research Methods and Analysis
  • Contact Info:

Sponsored By

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Workshops

Introduction to Structural Equation Models (SEM)

Course Instructor: Larry J. Williams, Texas Tech University (USA)

Time and Date: July 1, 12 pm – 3 pm GMT

This workshop includes an introduction to SEM, including confirmatory factor analysis and structural equation methods with latent variables. We will discuss special issues related to the application of these techniques in organizational research, and compare these techniques with traditional analytical approaches. We will cover the conceptual and statistical assumptions underlying theses methods, how to implement data analysis techniques using software program, and how to interpret results using the contemporary software programs.

Introduction to Multi-level Analysis

Course Instructor: Robert Vandenberg, University of Georgia (USA)

Time and Date: July 1, 4 pm – 7 pm GMT

This workshop is introductory in nature. It starts with a brief overview of the historical roots resulting in the need to consider multilevel issues in our research designs. We then discuss the issues underlying aggregation and disaggregation as this is at the heart of multilevel modeling. The latter in turn forces us then to consider some of the analytical challenges (e.g., interdependence vs. independence of observations; intra-class correlations and variance partitioning, etc.) resulting from multilevel thinking. We then move into the basic multilevel models such as random intercept, and random slopes models. Considerable time will be spent on the latter as understanding these makes actually conducting the analyses much easier. After completing it, the topic will switch to multilevel conceptualization. Finally, we end this workshop discussing aggregation indices and their importance.

Qualitative Comparative Analysis

Course Instructor: Ursula F. Ott, Nottingham Trent University (UK)

Time and Date: July 1, 2 pm – 5 pm GMT

In this workshop, the aim is to provide participants with an understanding of Qualitative Comparative Analysis. The fuzzy set QCA approach is built upon the set-theoretic comparative technique, primarily Boolean algebra, and has been introduced as a tool for integrating the strengths of qualitative and quantitative methods while overcoming the key concerns inherent in both approaches. The first part concentrates on theoretical underpinning to understand the logic behind the case and variable-oriented approaches. The second part of the module concentrates on calibration of qualitative into quantitative data derived from primary research. The outcome will be truth table, Venn Diagram, empirical and configurational analyses. The third part is direct application to the student’s practical applications.   This workshop should contribute to knowledge and understanding of the development and operation of using qualitative data and analyzing it with a quantitative tool to derive results which would not be possible with the qualitative tools only.   Further, the workshop will help to develop the ability to think critically and analyze results, the ability to solve complex configurations, the ability to use information and knowledge effectively as well as quantitative skills.

Grounded Theory

Course Instructor: Tine Köhler, University of Melbourne (Australia)

Time and Date: July 1, 12 pm – 3 pm GMT

The purpose of this workshop is to introduce researchers to the underlying tenets of the grounded theory approach and to get them started in designing and conducting a grounded theory study. In the workshop, I will provide an overview of the following three major topics: (a) Understanding the approach and different methodological traditions, (b)  core design characteristics of a grounded theory study, (i.e., purposive sampling, iterative data collection and analysis, triangulation and use of different sources and data), and (c) analysing data following the grounded theory method (i.e., different approaches to coding, constant comparison, memoing, triangulation, theoretical saturation, etc.). We will use some concrete examples throughout the workshop to provide hands-on advice and practical guidance.

Intermediate Structural Equation Models: Model Evaluation

Course Instructor: Larry J. Williams, Texas Tech University (USA)

Time and Date: July 2, 12 pm – 3 pm GMT

This workshop assumes participants have some introductory knowledge of SEM, and techniques for model evaluation will be the main focus. The workshop will first cover how to build measurement models, including use of items and parcels as indicators. A second topic to be addressed is model comparison techniques, including the use of goodness of fit indices.  Finally, CFA models for common method variance as an alternative explanation for findings will be discussed. The workshop will focus on how these issues arise in organizational research, and examples will be emphasized. A focus will be placed on what IB researchers should know to conduct and review research that includes these three topics.

Meta-Analysis

Course Instructor: Ahmet Kirca, Michigan State University (USA)

Time and Date: July 2, 3 pm – 6 pm GMT

This introductory level workshop focuses on methods for conducting a quantitative research synthesis using meta-analysis. Ultimately, the objective of this seminar is to develop participants’ practical and methodological understanding of the research synthesis process and to cover the most fundamental data analysis techniques employed in this process. Specifically, we will cover critical issues in conducting meta-analyses, such as formulating a meta-analytic research question, locating the relevant literature, calculate effect sizes and coding study characteristics/contexts, analyzing effect sizes, as well as writing and presenting the results with several examples from the literature.

Intermediate Multi-Level Analysis

Course Instructor: Robert Vandenberg, University of Georgia (USA)

Time and Date: July 2, 5 pm – 8 pm GMT

This workshop assumes participants have some introductory knowledge of multilevel modeling. In summary, this workshop uses the Mplus statistic package to analyze a number of random coefficients multilevel models. While I use Mplus, some of the models may be evaluated using other statistical packages. There is a progression in this workshop from analyses used to test the assumptions for aggregation to complex ones involving mediation, cross-level interactions, and models in which there are variables only at the between and within levels of analyses. The examples illustrate both the random vector of means and of coefficients/slopes. None of the examples in this module are structural equation models using latent variables. The examples in this module incorporate observed variables only. Participants will be given a comprehensive handout with all the examples including syntax.

Masterclasses

Quantitative Research: Discrete-choice Modeling

Masterclass Lead: William Greene, New York University (USA)

Masterclass Lead Introduction: Agnieszka Chidlow, University of Birmingham (UK)

Time and Date: July 2, 4 pm – 6 pm GMT

The aim of the masterclass is to examine both the theory as well as applications of discrete choice models in empirical research. More specifically, based on participation, location decisions and survey data, an analytical attention will be drawn to rigorous application of both binary and discrete models that could be applied in the international business (IB) context. What is more, with references to the recent applications, the appropriate model specifications and inference procedures for such models will also be examined. The masterclass is intended for IB scholars interested in the application of discrete choice models in their empirical research. Due to the limited number of places available for this masterclass and as part of the registration process, you will be asked to outline the  data collection and quantitative research you are either planning to do or/are currently doing in order to explain your motivation for attending this masterclass.

Fieldwork and Text Work

Masterclass Lead: John Van Maanen, MIT (USA)

Masterclass Lead Introduction: 
Catherine Welch, University of Sydney (Australia)
Rebecca Piekkari, Aalto University (Finland)

Time and Date: July 2, 6 pm – 8 pm GMT

In this masterclass, John Van Maanen will encourage you to reflect on your ‘fieldwork’ and ‘text work’ practices. The masterclass will include in-depth discussion of selected examples of exemplary ethnographic texts. As well, you will be encouraged to consider possible research designs and fieldwork options in your own area of interest. You will gain insight into how texts based on qualitative research persuade, and of current practices and styles for writing up international business research. Pre-readings and discussion questions have been set, so you will be expected to come to the session well prepared, and ready to join in the group discussion. Space in the masterclass is limited, so as part of the registration process, you will be asked to outline the qualitative research you are currently doing and/or planning, and to explain your motivation for attending this masterclass.

Introduction to Structural Equation Models (SEM)

Course Instructor: Larry J. Williams, Texas Tech University (USA)

Time and Date: July 1, 12 pm – 3 pm GMT

This workshop includes an introduction to SEM, including confirmatory factor analysis and structural equation methods with latent variables. We will discuss special issues related to the application of these techniques in organizational research, and compare these techniques with traditional analytical approaches. We will cover the conceptual and statistical assumptions underlying theses methods, how to implement data analysis techniques using software program, and how to interpret results using the contemporary software programs.

Introduction to Multi-level Analysis

Course Instructor: Robert Vandenberg, University of Georgia (USA)

Time and Date: July 1, 4 pm – 7 pm GMT

This workshop is introductory in nature. It starts with a brief overview of the historical roots resulting in the need to consider multilevel issues in our research designs. We then discuss the issues underlying aggregation and disaggregation as this is at the heart of multilevel modeling. The latter in turn forces us then to consider some of the analytical challenges (e.g., interdependence vs. independence of observations; intra-class correlations and variance partitioning, etc.) resulting from multilevel thinking. We then move into the basic multilevel models such as random intercept, and random slopes models. Considerable time will be spent on the latter as understanding these makes actually conducting the analyses much easier. After completing it, the topic will switch to multilevel conceptualization. Finally, we end this workshop discussing aggregation indices and their importance.

Qualitative Comparative Analysis

Course Instructor: Ursula F. Ott, Nottingham Trent University (UK)

Time and Date: July 1, 2 pm – 5 pm GMT

In this workshop, the aim is to provide participants with an understanding of Qualitative Comparative Analysis. The fuzzy set QCA approach is built upon the set-theoretic comparative technique, primarily Boolean algebra, and has been introduced as a tool for integrating the strengths of qualitative and quantitative methods while overcoming the key concerns inherent in both approaches. The first part concentrates on theoretical underpinning to understand the logic behind the case and variable-oriented approaches. The second part of the module concentrates on calibration of qualitative into quantitative data derived from primary research. The outcome will be truth table, Venn Diagram, empirical and configurational analyses. The third part is direct application to the student’s practical applications.   This workshop should contribute to knowledge and understanding of the development and operation of using qualitative data and analyzing it with a quantitative tool to derive results which would not be possible with the qualitative tools only.   Further, the workshop will help to develop the ability to think critically and analyze results, the ability to solve complex configurations, the ability to use information and knowledge effectively as well as quantitative skills.

Grounded Theory

Course Instructor: Tine Köhler, University of Melbourne (Australia)

Time and Date: July 1, 12 pm – 3 pm GMT

The purpose of this workshop is to introduce researchers to the underlying tenets of the grounded theory approach and to get them started in designing and conducting a grounded theory study. In the workshop, I will provide an overview of the following three major topics: (a) Understanding the approach and different methodological traditions, (b)  core design characteristics of a grounded theory study, (i.e., purposive sampling, iterative data collection and analysis, triangulation and use of different sources and data), and (c) analysing data following the grounded theory method (i.e., different approaches to coding, constant comparison, memoing, triangulation, theoretical saturation, etc.). We will use some concrete examples throughout the workshop to provide hands-on advice and practical guidance.

Intermediate Structural Equation Models: Model Evaluation

Course Instructor: Larry J. Williams, Texas Tech University (USA)

Time and Date: July 2, 12 pm – 3 pm GMT

This workshop assumes participants have some introductory knowledge of SEM, and techniques for model evaluation will be the main focus. The workshop will first cover how to build measurement models, including use of items and parcels as indicators. A second topic to be addressed is model comparison techniques, including the use of goodness of fit indices.  Finally, CFA models for common method variance as an alternative explanation for findings will be discussed. The workshop will focus on how these issues arise in organizational research, and examples will be emphasized. A focus will be placed on what IB researchers should know to conduct and review research that includes these three topics.

Meta-Analysis

Course Instructor: Ahmet Kirca, Michigan State University (USA)

Time and Date: July 2, 3 pm – 6 pm GMT

This introductory level workshop focuses on methods for conducting a quantitative research synthesis using meta-analysis. Ultimately, the objective of this seminar is to develop participants’ practical and methodological understanding of the research synthesis process and to cover the most fundamental data analysis techniques employed in this process. Specifically, we will cover critical issues in conducting meta-analyses, such as formulating a meta-analytic research question, locating the relevant literature, calculate effect sizes and coding study characteristics/contexts, analyzing effect sizes, as well as writing and presenting the results with several examples from the literature.

Intermediate Multi-Level Analysis

Course Instructor: Robert Vandenberg, University of Georgia (USA)

Time and Date: July 2, 5 pm – 8 pm GMT

This workshop assumes participants have some introductory knowledge of multilevel modeling. In summary, this workshop uses the Mplus statistic package to analyze a number of random coefficients multilevel models. While I use Mplus, some of the models may be evaluated using other statistical packages. There is a progression in this workshop from analyses used to test the assumptions for aggregation to complex ones involving mediation, cross-level interactions, and models in which there are variables only at the between and within levels of analyses. The examples illustrate both the random vector of means and of coefficients/slopes. None of the examples in this module are structural equation models using latent variables. The examples in this module incorporate observed variables only. Participants will be given a comprehensive handout with all the examples including syntax.

Masterclasses

Quantitative Research: Discrete-choice Modeling

Masterclass Lead: William Greene, New York University (USA)

Masterclass Lead Introduction: Agnieszka Chidlow, University of Birmingham (UK)

Time and Date: July 2, 4 pm – 6 pm GMT

The aim of the masterclass is to examine both the theory as well as applications of discrete choice models in empirical research. More specifically, based on participation, location decisions and survey data, an analytical attention will be drawn to rigorous application of both binary and discrete models that could be applied in the international business (IB) context. What is more, with references to the recent applications, the appropriate model specifications and inference procedures for such models will also be examined. The masterclass is intended for IB scholars interested in the application of discrete choice models in their empirical research. Due to the limited number of places available for this masterclass and as part of the registration process, you will be asked to outline the  data collection and quantitative research you are either planning to do or/are currently doing in order to explain your motivation for attending this masterclass.

Fieldwork and Text Work

Masterclass Lead: John Van Maanen, MIT (USA)

Masterclass Lead Introduction: 
Catherine Welch, University of Sydney (Australia)
Rebecca Piekkari, Aalto University (Finland)

Time and Date: July 2, 6 pm – 8 pm GMT

In this masterclass, John Van Maanen will encourage you to reflect on your ‘fieldwork’ and ‘text work’ practices. The masterclass will include in-depth discussion of selected examples of exemplary ethnographic texts. As well, you will be encouraged to consider possible research designs and fieldwork options in your own area of interest. You will gain insight into how texts based on qualitative research persuade, and of current practices and styles for writing up international business research. Pre-readings and discussion questions have been set, so you will be expected to come to the session well prepared, and ready to join in the group discussion. Space in the masterclass is limited, so as part of the registration process, you will be asked to outline the qualitative research you are currently doing and/or planning, and to explain your motivation for attending this masterclass.