Supporting Quality Business School Research

Sponsored by:

• Research services, such as Wharton WRDS, can provide business schools with data platforms, tools, applications, customer support, computing power, and infrastructure.
• While many research commonalities exist in the larger academic community, business school scholars in certain geographic regions often have unique needs that need to be addressed differently.
• New tools are being developed to help researchers analyze unstructured data—long strings of text, voice recordings, images—so they can be more efficiently leveraged in empirical studies.

Transcript

Mireia Gine: [0:16] Wharton Research Data Services, WRDS, has been around for 25 years. The reason we've been around for so long is because we provide a solution to a very specific problem for business schools, which is helping business schools deliver good research.

[0:32] Research is hard to do. It takes resources, it takes time, there's a lot of uncertainty, but it's something that is essential to business schools because business schools are trying to be a space for creating new ideas, for debating ideas as well. If that is important to business schools, then we have to put an effort into delivering these research outcomes.

[0:59] WRDS provides the platform for the data, provides as well tools and applications to use on top of the data. Third, it provides an outstanding support system that you can use to ask questions from about the raw data.

[1:15] Why does the data look slightly weird or something that doesn't look correct, to more refined questions about how to implement research strategy using that specific data. The fourth element is that we provide the computation power. All researchers can use our computers, our machines, to run their programs. Schools do not have to make investments.

Research takes resources, it takes time, there's a lot of uncertainty, but it's something that is essential to business schools because business schools are trying to be a space for creating new ideas, for debating ideas as well.

[1:47] Obviously, with the use increase of machine learning, you may use cloud computing, but it is important for our users to know that they can use our computing facilities to run most of the research that they are trying to execute. 

[2:09] WRDS has been evolving over these 25 years. It's usually demand-driven. What I mean is that our users tell us, "Look, we need this specific data that is more suitable to us," or, "We would need this specific language that is vastly used in our region."

[2:28] We are very aware that although the academic community has very strong commonalities, so people tend to do research in the same fashion and use the same main databases, at the same time, there are things that are specific to each region. Some European schools have asked for specific European data. Asian schools have as well a wealth of Asian data.

We have this view that our different users around the globe are going to have different needs.

[2:54] In terms of programming language, for example, I can remember a few years ago. Europe tends to use more Stata than in other regions. We've put more emphasis into supporting Stata for certain European schools.

[3:11] We are very aware that although we are a product, a service that was developed at the Wharton School, we have this view that our different users around the globe are going to have different needs. We hope to service them differentially in that respect.

[3:28] A recent research topic that is gaining space among academics is certainly ESG topics, environmental, social, and governance topics. Mostly, specifically on the environmental side, I think that we've worked a lot on governance, a little bit less on the societal impact of corporations.

[3:51] The space that is gaining a lot of traction is the environmental aspects, externalities that firms have. For that research, it started a very empirically driven type of research. Therefore, we need a variety of databases. We are very aware that there is not a common standard on how to measure environmental impact.

[4:19] Therefore, it's very important to have different sets of databases that can give you this richness into measuring the problem. This has been an important element in our agenda, trying to support researchers that are trying to produce this type of research and have an impact in that sense.

Moving from unstructured data into research is something that we hope within WRDS to help researchers be able to organize this data and then use it for their empirical research.

[4:43] One of the frontier issues within research is the use of unstructured data. What do I mean by unstructured data? Currently, what we have in WRDS is a vast amount of data that is structured, which has columns and rows, quantitative information. Most of the information in the world is unstructured. It's text, long sentences, voice, image.

[5:10] How can we use this data to predict things in the space of finance, accounting, strategy? Moving from these unstructured data into research is something that we hope within WRDS to help researchers be able to organize this data and then use it for their empirical research.

[5:35] How do we do that within WRDS? We have created tools that allow you to examine text, and for example, examine the sentiment of a document, whether it has a more or less positive tone, whether it uses certain words that are important, that are informative, whether it masks information or it's informative.

[5:59] There are already ways into analyzing specifically text and be able to distill some of the characteristics to then use into your research question.