Summer Undergraduate Research Mentored Experience

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Dr. Amit Lopes

Department of Industrial, Manufacturing & Systems Engineering

Social media applications in supply chain management

Preferred major field of study or minimum required skills

Industrial Engineering, Manufacturing Engineering, Social Media Proficiency, Data Mining, Basic Programming Skills

Scholarly significance/intellectual merit

Global manufacturing operations has mandated evolution of traditional Supply Chain Management (SCM) principles. Current SCM principles utilize methodologies and tools to predict the dynamic nature of a global supply chain, but is still room for improvement to achieve a more accurate product delivery algorithm while addressing uncertainty in the SCM. Social media applications currently utilized around the world present an intriguing possibility in the information flow aspect of global SCM modeling. Supply chain participants can utilize social media to keep track of current situations, such as a delay in shipping or a carrier failed to pick-up a shipment by monitoring supply chain events and transactions. Data mining for information relevant to the supply chain within global social media can provide timely and insightful information about risks and events and enable real-time adaptation and modification to ensure a more robust SCM model. Currently, the use of social media as a verifiable information flow artifact within a glob SCM model has not been sufficiently investigated.

Research question(s)

  • Determine information flow parameters important to the development of an optimum predictive SCM model
  • Determine the level of applicability of data mining methods to gather verifiable information from accessible global social media
  • Adapt current SCM architectures to include real-time verifiable information from social media to potentially improve responsiveness and reduce uncertainty?

Methods/techniques/instruments to be learned/utilized

A wide range of research techniques will be used, including literature reviews to understand global SCMs limitations, data mining tools, architecture modeling, and analysis of actual SCM process realization involving real-time information flows. Thus, summer undergraduate students will be exposed to innovative methodologies and techniques in the fields of Industrial and Manufacturing Engineering.