Participate in Faculty Research

Advances in management practices are often made possible through the collaboration of business professionals and academic researchers. Partnering in School of Management research can provide you or your organization with keen insights, and your time commitment is generally minimal because research is often conducted through online surveys or interviews.  

• Sustainability - Aditya Vedantam, assistant professor of operations management and strategy, is looking for organizations involved in sustainability for two different engagement opportunities. For his research with the UB Plastics Center, he would like to connect with companies that deal with plastic scrap or use recycled plastics in their products to participate in case study-based research interviews. He is also looking for individuals involved in their company’s work towards sustainability, recycling, environmental certification, clean energy, energy efficiency, green manufacturing or social responsibility to speak to students in his course “Sustainable Operations.” If you can assist with either of these requests, contact Aditya Vedantam.
• Marketing Research - Indranil Goswami, assistant professor of marketing, is looking for individuals to share how their organization does research to inform business decision-making with his students. The research could entail primary research or the use of secondary data. If you are willing to share your experience, contact Indranil Goswami.
• Marketing Research - Arun Lakshmanan, associate professor of marketing, is conducting research on how structuring product displays and using different ways of depicting products affects consumer responses. If you are interested in studying different approaches to your product displays in advertising or retail, please contact Arun Lakshmanan.
  
• Accounting and AI - Sanjukta Smith, associate professor and chair of management science and systems, is looking for individuals engaged in accounting functions in business or government organizations to provide real accounting data sets. This data will help train an algorithm being created to identify plausible accounting errors via sophisticated AI/machine learning powered techniques to prevent regulatory missteps later on. Data does not need to include any personally identifiable or sensitive records and researchers will take steps to ensure anonymity. For more information, contact Sanjukta Smith.

Learn more about faculty interests by visiting their individual pages or visit our current list of faculty experts.