1. Home »
  2. Supervisor: Dr. Osman Sadiq Paracha
Supervisor: Dr. Osman Sadiq Paracha

 

Advancing Business Analytics through Emerging Technologies

 

Supervisor: Dr. Osman Sadiq Paracha (Professor)

Campus/School/Dept: Business and Marketing Department, Bahria Business School

Supervisory Record:          

  • PhD Produced:                        6
  • PhD Enrolled:                         Nil.
  • MS/MPhil Produced:              20
  • MS/MPhil Enrolled:               4.

 

Theme: Business Analytics

  1. Quantum Computing and Optimization for Business Decisions
  2. Blockchain and Supply Chain Analytics
  3. HR Analytics
  4. Marketing Analytics
  5. Fintech (Financial Analytics)
  6. AI in Business
  7. Decision Sciences and Business
  8. Technology and innovation in Business Analytics

 

Advancing Business Analytics through Emerging Technologies

  1. Introduction

Business Analytics, a field that leverages data to inform strategic decision-making, is undergoing a rapid transformation due to advancements in technology. This proposal outlines a research agenda focused on exploring the intersection of emerging technologies and business analytics. By delving into areas such as quantum computing, blockchain, AI, and advanced analytics techniques, this research aims to contribute to the development of innovative solutions for complex business challenges.

 

  1. Research Objectives
  • Quantum Computing and Optimization for Business Decisions: To investigate the potential of quantum computing algorithms to solve complex optimization problems in business, such as supply chain optimization, portfolio management, and pricing strategies.
  • Blockchain and Supply Chain Analytics: To explore the application of blockchain technology to enhance supply chain transparency, traceability, and security, leading to improved efficiency and risk mitigation.
  • HR Analytics: To utilize data-driven insights to optimize human resource management practices, including talent acquisition, performance management, and employee retention.
  • Marketing Analytics: To leverage advanced analytics techniques to understand customer behavior, personalize marketing campaigns, and measure the impact of marketing initiatives.
  • Fintech (Financial Analytics): To apply data science and machine learning to revolutionize the financial industry, including fraud detection, risk assessment, and algorithmic trading.
  • AI in Business: To explore the transformative potential of AI in various business domains, such as customer service, sales, and operations, to automate tasks, improve decision-making, and enhance customer experiences.
  • Decision Sciences and Business: To investigate the application of decision theory and statistical modeling to support evidence-based decision-making in complex business environments.
  • Technology and Innovation in Business Analytics: To stay at the forefront of technological advancements and identify emerging trends that can shape the future of business analytics.

 

  1. Research Questions
  • How can quantum computing accelerate the solution of complex optimization problems in business?
  • What are the potential benefits and challenges of blockchain technology in supply chain management?
  • How can HR analytics be used to improve employee engagement, productivity, and retention?
  • What are the most effective marketing analytics techniques for customer segmentation, targeting, and personalization?
  • How can AI and machine learning enhance the accuracy and efficiency of financial forecasting and risk modeling?
  • What are the ethical implications of AI-powered decision-making in business?
  • How can decision science techniques be applied to optimize strategic decisions in uncertain environments?
  • What are the emerging technologies that will have the most significant impact on business analytics in the future?

 

  1. Candidate Eligibility Profile
  • Academic Qualifications: MS/MPhil/Equivalent degree in Management, Business Analytics or a related field with a strong quantitative, programming background with a CGPA > 3.5
  • Technical Skills: Proficiency in programming languages (e.g., Python, R, SQL), statistical software (e.g., SPSS, SAS), and machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Research Experience: Candidate must have 1 Impact Factor or 3Y/2X HEC publication as 1st author in the domain of Business Analytics
  • Domain Knowledge: A solid understanding of business concepts, such as finance, marketing, and operations.
  • Interpersonal Skills: Excellent communication and teamwork skills to collaborate with researchers and industry practitioners.