I am the Andersen Professor of Business Information Technology at the Pamplin College of Business at Virginia Tech. My research interests primarily focus on problem-solving and data analytics related to the interactions among business organizations, information systems, and decision makers. I have published more than 40 refereed articles in various journals including Information Systems Research, Production and Operations Management, Journal of Management Information Systems, Decision Support Systems, Journal of the AIS, Communications of the ACM, IEEE Transactions of Systems, Man and Cybernetics (Part A), and IEEE Computer.
As of August 2024, my research has received over 6,000 citations (h-index=33; i10-index=57) according to Google Scholar. My ResearchGate Interest Score is 2,443, higher than 97% of all RG members.
I have been advising doctoral students in both the full-time BIT Ph.D. program and the Executive Ph.D. program. In 2019, I received the Pamplin Outstanding Faculty in Doctoral Education Award.
Most recent publication date:
1. Measuring Customer Agility from Online Reviews Using Big Data Text Analytics
Times Cited: 7 (Web of Science Core Collection)
2. By the numbers: The magic of numerical intelligence in text analytic systems
Times Cited: 0 (Web of Science Core Collection)
3. Project description and crowdfunding success: an exploratory study
Times Cited: 10 (Web of Science Core Collection)
My research aims to help decision makers, such as managers, policymakers, employees, and customers, find effective solutions to their problems and make better decisions. Given my cross-disciplinary backgrounds in engineering and management, I am committed to problem solving by designing new IT artifacts, including constructs, methods, and frameworks. The problems that I focus on are socio-technical in nature and impactful to people and communities.
Data analytics, programming, web development, database, data mining, social media analytics, management science
"Professor Wang, was a very organized and helpful professor. He kept canvas very up to date and everything was organized in a structured manner which made accessing assignments very routine and convenient. He was very knowledgable of the material and gladly provided help when students needed it. In multiple instances, I had a hard time understanding assignments or debugging my code and he sat down with me and either explained it to me in a kind way or went through the assignment with me until it was debugged. I feel as though I learned the most material in this course throughout these past few semesters here at Tech. The course/material is very fast-paced; however, his lectures are detailed enough to guide students and prepare them with the material that theyneed. I really enjoyed this class and appreciate all professor Wangs hard work!"
The objective of management science is to solve the decision-making problems by developing mathematical models of those problems. We will go through the modeling techniques used extensively in the business world, and learn how to apply computer and information technology based tools to solve those problems more efficiently. Topics include linear programming, network flow models, project management, multicriteria decision making, nonlinear programming, and forecasting.
This course introduces the construction of business applications using an advanced business programming language, Microsoft VB.NET. It covers the following topics: Fundamental programming terminologies such as variables, procedures and modules; User interface design; Software development life cycles (SDLC); Error handling and debugging; Database applications; and Object Oriented Programming (OOP).
This course will focus on current technologies and tools that are used to develop web applications in a business environment. It covers a wide range of client-side and server-side web development technologies, including HTML5, CSS, DOM, JavaScript, jQuery, Bootstrap, PHP, Ajax, MySql, and web-based data analytics. Knowledge about relational databases is necessary for you to work on data related projects.
This course provides students with the knowledge and tools to evaluate a business situation and build a database application. The students will learn the fundamentals of database design, writing queries to extract data from databases, database application development, and database administration. In addition, advanced database topics, such as analytical processing, data mining and data warehousing, are introduced.
This course is focused on systematic knowledge of the Design Science Research (DSR) methodology in the context of Information Systems (IS). A primary objective is to help students evaluate other DSR research works and become a more discerning consumer of both the methodology and their contributions. The students are guided through a Design Science Research project, which leads to a high-quality publishable research paper.