Fast Facts

  • Event Date: 5 July
  • Extended Registration Deadline: 31 May 2023 (Formerly 1 May)
  • Point of Contact: Emma Gardner, University of Birmingham, e.c.gardner@bham.ac.uk

RM-SIG Workshops

Machine Learning for International Business Research

Masterclass Leads: Thomas Lindner (University of Innsbruck), Laurenz Tinhof (Vienna University of Economics and Business)

Time and Date: 5 July, 10am-1pm CET

In this workshop, we cover the conceptual foundations of machine learning (ML), and how ML complements the battery of empirical methodologies usually applied in IB research. After having established the conceptual basics, we will proceed to implementing simple ML methodologies in the script language R, using recent machine learning packages. In the last part of the workshop, we will introduce workshop participants to an ML architecture we developed for predicting subsidiary profits abroad, and participants will be able to edit and improve the ML architecture in a case study of using ML for IB research. We will close with Q&A about applications in current research projects and teaching.

Surviving the Review Process: Behind the Scenes of Submitting Qualitative Papers to IB Journals

Masterclass Lead: Rebecca Piekkari (Aalto University School of Business)

Time and Date: 5 July, 10am-1pm CET

In this workshop we will cover the issues involved in publishing qualitative research in IB journals. Professor Rebecca Piekkari, an Area Editor of Journal of International Business Studies (JIBS), will discuss the process with editors and author teams of papers that have recently been published in JIBS and JWB. Workshop participants will get a behind-the-scenes understanding of the key challenges that the authors faced, lessons they learned, and the key turning points and insights they obtained during the review process. Participants will also hear advice from editors about how authors can maximize the chances of their papers making it through the review process. The workshop will provide opportunities for workshop participants to pose questions of the presenters and reflect on the workshop content.

RM-SIG Masterclasses

Ethnography

Masterclass Lead: Fiona Moore (Royal Holloway, University of London)

Time and Date: 5 July, 2-5pm CET

Drawing on my experience of more than 25 years as an anthropologist of business and organisations, we will begin with a discussion of what makes a study “ethnographic”, and about how ethnography in business draws on, and develops, work done in more traditional settings. We will consider various theoretical and practical traditions in ethnography and their relevance to business and management. We will then engage in various practical exercises aimed at developing participants’ skills as ethnographers and at instilling an “ethnographic mentality” for use in fieldwork.

Partial Least Squares Structural Equation Modeling (PLS-SEM) and the Necessary Condition Analysis (NCA) in IB Research

Masterclass Leads: Nicole Richter (University of Southern Denmark), Christian Ringle (Hamburg University of Technology)

Time and Date: 5 July, 2-5pm CET

This workshop introduces and encourages the combined use of partial least squares structural equation modeling (PLS-SEM) and the necessary condition analysis (NCA) that enables researchers to explore and validate hypotheses following a sufficiency logic, as well as hypotheses drawing on a necessity logic.

PLS-SEM belongs to a family of regression-based methods for estimating models with latent variables developed by the Swedish econometrician Herman Wold (1985). Since the 2000s, PLS-SEM has gained widespread popularity in a variety of disciplines among them (international) marketing and management research. The method estimates theoretically established causal-predictive relationships between latent variables (i.e. constructs measured by observed indicators). The results can empirically substantiate the determinants (X) that lead to an outcome (Y). Authors who interpret their PLS-SEM findings often use expressions such as “X increases Y” or “a higher X leads to a higher Y”. The interpretation, therewith, follows a sufficiency logic. Understanding relationships in terms of sufficiency logic is extremely relevant. Researchers, for instance, aim to understand the factors that lead to a stronger intention to use certain technology by applying different theories of technology acceptance; or they aim to understand the factors that contribute to a higher loyalty of their customers.

In contrast, the NCA is a relatively novel research methodology that has attracted much attention in the academic community in recent years. The NCA follows a necessity logic (“X is necessary for Y”) and can identify necessary conditions in data sets. A necessary condition is a critical factor for an outcome: if the necessary cause is not in place the outcome will not materialize. Hence, the necessary condition can be a bottleneck, critical factor, constraint, disqualifier, etc. The right level of a necessary condition must be put and kept in place to avoid guaranteed failure. By adding a different logic and data analysis approach, an NCA adds both rigor and relevance to theory, data analysis, and publications.

Against this background, with a combined use of PLS-SEM and NCA, we can determine the factors that produce the best possible outcome (i.e. the should-have factors; sufficiency logic) and those that are critical for an outcome (i.e. the must-have factors; necessity logic). Importantly, the should-have factors can only increase an outcome after the must-have factors have been taken care of. If necessary conditions are ignored or neglected in a field where we theoretically assume they exist, the result will be incomplete findings and recommendations. PLS-SEM is an approach to identify the determinants that can increase an outcome. NCA identifies the necessary level of a determinant that is needed to enable the outcome (Richter et al., 2020).

In this workshop, we will, therefore, introduce sufficiency and necessity logic as well as the foundations of a combined PLS-SEM and NCA use. For a case study illustration we use the SmartPLS 4 software. We provide insights into the logic, assessment, challenges and benefits of a combined use of PLS-SEM and NCA.