Research

Emerging markets represent the primary regions of rising productivity and economic growth today with more than 80% of the world population residing in these markets. With the value chains of many firms expanding to reach out to the consumer base in these countries and also tap into their expertise, the challenges associated with managing global supply chains have expanded significantly. This workshop sheds light on the growth of empirical OM research on emerging markets in recent years, highlighting important themes of research as well as useful datasets that have been used in published studies. It also discuss empirical research challenges and opportunities for further exploration in this domain.

Authors: Anant Mishra, Yongyi Shou

Behavioral Operations Management (BOM) is a field of study within Operations Management that incorporates insights from cognitive psychology, social psychology and behavioral economics to study how individuals behave and make decisions in operational settings. The individuals of interest can vary from managers making cognitively challenging managerial decisions, to workers performing tasks in operations systems, to customers reacting to operational policies. By better understanding what these individuals do and why, BOM can provide insight into how to improve operations systems in light of behavioral tendencies. The field of BOM has grown tremendously in recent years, broadening the types of operational settings explored and the research methodologies employed. In essence, this workshop aims at providing an overview of major developments, as well as inspiration for continued advancement in the BOM field. Workshop speakers include Prof. Enno Siemsen (University of Wisconsin-Madison), Prof. Ruth Beer (Baruch College, City University of New York), and Prof. Yinghao Zhang (University of Cincinnati).

Author: Yinghao Zhang

Social media has revolutionized how firms and individuals connect with one another. This workshop features a panel of experts that have made significant contributions to the developing literature on social media. They present their current research projects and review their experiences working with social media data. The workshop concludes with a moderated discussion on the future of social media research.

Author: Enuae Yoo

Organizations today are gathering and storing massive amounts of granular data about their processes and customers, mainly owing to low storage costs. The hope being that firms can identify useful information and extract value through superior analysis. Effective data management and visualization are vital steps to achieve these objectives. This workshop provides hands-on exposure to conducting data management and visualization activities on extensive real-world datasets in R/RStudio. Data management includes operations such as reading, cleaning, merging datasets and handling missing observations. Data and code files were shared with the participants before the commencement of the workshop.

Author: Pradeep Pendem

Empirical researchers increasingly rely on curating a unique dataset by using a variety of secondary data sources. One of the critical prerequisites to any such empirical research is to clean up data sources. This workshop explains general data management strategies, introduce typical situations where messy data arises, and provides practical tutorials on dealing with messy data. By the end of this workshop, you will be able to (1) identify when and why messy data arises, (2) understand why cleaning data is essential for analysis, (3) implement strategies that will help you with cleaning data using text mining tools and cloud-based services.

Author: Hyunwoo Park

Explosive growth in the number of users on various social networking platforms has transformed the way firms operate their businesses. Firms are developing strategies to leverage the vast size of online social networks and efficiently reach their customers. The first aim of this workshop is to provide an overview of current social networks research and discuss firms’ strategies in harnessing the potential of social networks. Next, the workshop discusses avenues for future research. The workshop also discusses the general methodological challenges in social networks research and provides a framework to address these challenges.

Author: Rakesh Mallipeddi

Industry 4.0 digital technologies, such as sensors and AI tools, have the potential to transform almost all aspects of product development, process delivery and supply chains configurations. These technologies have also engendered new business model creation through capabilities such as distanced work, eCommerce, and platforms that create two-sided markets. Yet, in many sectors, diffusion of technologies, and allied changes in processes and innovative practices, have been limited to pilot scale experimentation and point solutions. The panelists have been observing these phenomena at 54 ‘Lighthouses’, the world’s most advanced factories, which are leading the way in the adoption of i4.0 technologies through their work with World Economic Forum. They have also been collecting primary data on operating and business model evolution in some of these sites through the course of recent pandemic. This professional development workshop highlights some of their observations. The second half the workshop raises theory and methodological issues that seem to be emerging at this research frontier.

Authors: Nitin Joglekar, Geoffrey Parker, Jag Srai

Randomized experiments have been recently gaining traction in decision sciences and operations management. However, several internal and statistical validity threats can undermine the conclusions drawn from experimental studies. This tutorial briefly introduce some of these threats, as well as several potential solutions. After introducing the endogeneity problem typical of observational studies, it focus on major sources of endogeneity in experimental research.

Author: Sirio Lonati

This workshop is aimed at providing an overview of predictive analytics and the state of research using predictive analytics on complex and large datasets. The workshop discusses general topics related to predictive analytics such as the difference between explanatory causal modeling and predictive analytic modeling of data, characteristics of big data, and general methods that can be used for predictive analytics. This workshop will hopefully motivate researchers to look into predictive analytic methods as a potential tool for research in operations management.

Author: Ujjal Mukherjee

The Association for Supply Chain Management (ASCM) is the global supply chain organization and industry thought leader as demonstrated by their research program. This workshop discusses various ASCM research outlets: The ASCM Future of Supply Chains Grant Research Program, ASCM Top 10 Supply Chain Trends that will impact the industry in the next 3 years, and outputs from ASCM’s Research, Innovation and Sensing Committee. The goal is to help academics learn what is impacting practitioners and to provide research topic ideas that are relevant to industry.

Authors: Matthew Talbert, Mark Frolich, Pedro Neto