Interview Report

A

Abhishek Kumar

a**********[email protected]

Interviewed on Jan 26, 2026

Completed
Flagged for suspicious behaviour
77SCORE

Overall performance

Marketing Professor

Good fit for roleAcademic

Candidate demonstrates strong teaching and research alignment with role.

Summary

Report summary

Candidate Snapshot

The candidate demonstrates a clear and structured reasoning style, with a strong focus on leveraging prior academic and research experiences. Their approach to problem-solving is systematic, using established methodologies and frameworks. They exhibit a deep engagement with their domain, particularly in marketing, technology adoption, and sustainability, while actively incorporating experiential learning and digital tools into their teaching methods.

Primary Challenges

Could you discuss your research experience and publications, particularly in Marketing Analytics or Services Operations Management?

The candidate was asked to elaborate on their research experience and publications related to Marketing Analytics or Services Operations Management.

The candidate highlighted their 10 research papers, including publications in ABDC and Acta Psychologica. They discussed a focus on digital financial frauds, green teaching, and technology adoption, particularly UPI-based payment systems. They also mentioned work on the women's segment, NFC-based payment systems, and green marketing, along with case studies that intersect marketing, consumer behavior, and services domains.

Demonstrated

  • Breadth of research experience
  • Focus on current and relevant topics like digital financial frauds and green marketing
  • Use of ABDC and other recognized publications

Partially Demonstrated

  • Specific alignment with Services Operations Management

Missing or Unclear

  • Explicit examples of Marketing Analytics applications

What specific methodologies or tools have you employed in your research to analyze consumer behavior or user inclination?

The candidate was asked to specify methodologies and tools used in their research.

The candidate mentioned using PLS-SEM, NCA analysis, ANN, and mixed methods techniques. They described applying these methods in studies involving NFC-based payment systems and consumer behavior analysis.

Demonstrated

  • Use of advanced methodologies like PLS-SEM, NCA, and ANN
  • Application of mixed methods for comprehensive analysis

Partially Demonstrated

  • Depth of explanation for each methodology

Could you elaborate on your approach to delivering specialized courses in marketing, ensuring both clarity and engagement for students?

The candidate was asked to explain their teaching approach for specialized marketing courses.

The candidate emphasized experiential learning, dividing classes into 50% theoretical and 50% practical components. They incorporate techniques like case studies, role plays, flipped classrooms, jigsaw activities, and videos. They also integrate neuromarketing and AI concepts into their teaching.

Demonstrated

  • Innovative teaching methods
  • Focus on experiential learning
  • Integration of digital technologies like AI and neuromarketing

Partially Demonstrated

  • Specific examples of neuromarketing or AI concepts applied in classes

How do you evaluate students while ensuring critical thinking and applied understanding in your courses?

The candidate was asked about their student evaluation methods.

The candidate described using quizzes, prompting questions, presentations, and in-class discussions for continuous evaluation. They also mentioned incorporating final examinations to assess students' understanding comprehensively.

Demonstrated

  • Diverse evaluation techniques
  • Focus on student engagement and critical thinking

Partially Demonstrated

  • Details on how quizzes or presentations are structured to ensure applied understanding

Could you provide an example of a project you've supervised, emphasizing your role in mentoring and steering the research?

The candidate was asked to describe a specific research project they supervised.

The candidate shared an example of guiding students in researching mobile-based payment adoption among small retailers. They described mentoring students through problem identification, literature review, conceptual model design, sampling, data collection, and analysis using PLS-SEM. They emphasized promoting student independence while providing guidance.

Demonstrated

  • Structured mentorship approach
  • Guidance on research methodologies and tools like PLS-SEM

Partially Demonstrated

  • Integration of theoretical and practical insights during the project

Observed Capabilities

Demonstrated

  • Advanced research methodologies
  • Innovative teaching methods
  • Structured mentorship
  • Focus on experiential learning
  • Engagement with emerging technologies

Partially Demonstrated

  • Direct alignment with Marketing Analytics
  • Explicit industry consultancy experience

Missing or Unclear

  • Examples of impact from neuromarketing and AI integration in teaching

Real-World Indicators

  • Experience with student projects involving real-world applications
  • Publications on relevant and emerging topics like digital financial frauds and sustainability
  • Mentorship involving practical problem-solving and tool usage

Contextual Gaps

  • Direct consultancy or industry project experience
  • Explicit contribution to Marketing Analytics

Strength Areas

Research and Publications
  • Diverse topics like digital payment systems, sustainability, and consumer behavior
  • Use of advanced methodologies like PLS-SEM and ANN
Teaching and Pedagogy
  • Experiential learning methods
  • Integration of technologies like AI and neuromarketing
Mentorship
  • Structured guidance on research projects
  • Focus on promoting student independence

Recording

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Transcript

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Technical skills

4
Primary Data Analysis through Smart-PLS, SPSSKnowledge of PLS-SEM, Neural Networks, Necessary Condition AnalysisSecondary data analysis through Microsoft Excel, E-viewsPolicy analysis

Soft skills

3
TeachingResearchCoordination

Detected events

  • 0:00Multiple Monitors

Speakers

2 speakers · suspicious

Face preview

Face analysis

Resume score

Resume

Resume.pdf

75