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INFORMS Journal Highlights from April 2018
AUTHOR SPOTLIGHT
PARAM VIR SINGH
“A few years ago, my coauthors, Quan Wang and Beibei Li, recommended me to try a mobile app game called Candy Crush. They thought it was too much fun. I had also heard about it, so I proceeded to download it from iTunes but got confused. There were just too many games that appeared to be the Candy Crush game. I could not figure out which one I should download. When I discussed this with Quan and Beibei, we all were confused as to which one is the original. This acted as a seed for our paper where we thought if we were having a problem identifying the original, so would other users. This could be bad for the developers who create original apps. In fact, when we searched online, we found numerous media and blog reports where practitioners and developers of original apps claimed that copycats steal the original app’s idea and potential demand, and were calling for app platforms to take action against such copycats. Surprisingly, however, we also found that there was little rigorous research analyzing whether and how copycats affect an original app’s demand. The primary deterrent to such research was the lack of an objective way to identify whether an app is a copycat or an original. This is when we decided to develop a method to identify which app is the original and which is a copycat and how a copycat affects the demand of the original.”Read Param's Latest Article
“Achievable Performance of Blind Policies in Heavy Traffic”
in Information Systems Reasearch
More by this Author
Inventing with Machines: Generative AI and the Evolving Landscape of IS Research
Unequal Impact of Zestimate on the Housing Market
Personalization, Consumer Search, and Algorithmic Pricing
When Does Beauty Pay? A Large-Scale Image-Based Appearance Analysis on Career Transitions
Algorithmic Transparency with Strategic Users
Associate Editor, Management Science (areas: Entrepreneurship and Innovation; Information Systems); Senior Editor, Information Systems Research
Gautam Ahuja
Organization Science
“In recent years there have been many changes in the employment context of individuals that place more of their income ‘at risk.’ These changes arise from a variety of corporate decisions such as moving work to contractors rather than employees, moving to defined contribution pension plans rather than defined benefit plans, more incentive-based variable pay. These organizational arrangements have often been adopted following the argument that they would reduce organizational costs. Meuris and Leana’s study draws attention to a potentially serious flaw in this argument — as individuals take on more of the compensation risk in their work relationship, it may potentially increase financial worry. In turn, financial worry can limit the cognitive resources available to work, leading to poorer work performance. By identifying the theoretical mechanisms through which the financial worry–work performance relationship operates and by documenting the detrimental impact of such worries on organizational performance, the authors raise a basic question about the true realization of cost savings through such practices. I strongly endorse the article as a must-read for both scholars and practitioners interested in the organization of employment or the well-being of employees.”
The Price of Financial Precarity: Organizational Costs of Employees’ Financial Concerns
Jirs Meuris, Carrie Leana
78
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Call for Papers—Special Issue of Information Systems Research Fintech – Innovating the Financial Industry Through Emerging Information Technologies
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Editorial—Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research
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Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery
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JOURNAL SPOTLIGHT
Mathematics of Operations Research
Editor-in-Chief: J.G. "Jim" Dai
Impact Factor: 1.157
5-year Impact Factor: 1.724
Impact Factor: 1.157
5-year Impact Factor: 1.724
“Mathematics of Operations Research (MOR) publishes innovative foundational articles having significant mathematical content and relevance to operations research and management science. Mathematics of Operations Research has added Learning Theory as a new subject area this year, which is led by Area Editors Shie Mannor and Benjamin Van Roy.
The Learning Theory area seeks rigorous papers that aim to make deep and lasting contributions to the mathematical foundations of this field. Topics include but are not limited to unsupervised, supervised, active, and reinforcement learning, as well as learning for decision making and operations.
The new area will serve a growing subset of the community who are doing fundamental research involving machine learning. Associate Editors for this new area are as follows: Sebastien Bubeck, Constantin Caramanis, Mohsen Bayati, Huan Xu, Assaf Zeevi, Peter Bartlett, Shipra Agrawal, Gilles Stolz, and Yishay Mansour.
For more information about Mathematics of Operations Research and this new area, visit http://pubsonline.informs.org/journal/moor.