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Majid Majzoubi

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Majid Majzoubi

Majid Majzoubi

Assistant Professor

majzoubi@schulich.yorku.ca

  • Area of Expertise

    • Strategic Management ›
    Download CV
  • Majid Majzoubi is an Assistant Professor in the Strategic Management area. He teaches the core Strategic Management course in the BBA program. Professor Majzoubi’s research is focused on the interface between firms’ strategic choices and audience evaluations. Specifically, he draws on strategic management, organization theory, and theories on the socio-cognitive foundations of social judgments to study how firms’ strategic positioning within markets influence stock market and security analysts’ evaluations. Through a series of studies, he has investigated optimal positioning strategies in markets with multiple benchmarks for comparison, the effects of change in firm positioning on analyst evaluations, and positioning strategies for gaining a more positive audience composition.

    Professor Majzoubi’s research has been published in Strategic Management Journal and presented in various conferences including The Academy of Management Annual conferences and Strategic Management Society’s conferences.

    He received his doctorate in Strategy from the University of Washington, MBA from the University of North Carolina, and Bachelors in Computer Science from Tehran Polytechnic.

    Recent Publications

    Majid Majzoubi, Eric Yanfei Zhao, Tiona Zuzul, Greg Fisher (2025), "The Double-Edged Sword of Exemplar Similarity", Organization Science, 36(1), 121-144.

    Keywords
    • category viability
    • exemplar similarity
    • NLP
    • optimal distinctiveness
    • security analysts

    View Paper

    Abstract

    We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and legitimacy, increasing the likelihood that it passes the initial screening stage and attracts analyst coverage. However, exemplar similarity may also prompt unfavorable comparisons with exemplar firms, leading to lower analyst recommendations in the assessment stage. We further argue that category coherence, distinctiveness, and exemplar typicality influence the impact of exemplar similarity on firm evaluation. Leveraging natural language processing (NLP) techniques to analyze a sample of 7,603 U.S. public firms from 1997 to 2022, we find robust support for our predictions. By highlighting the intricate role of strategic positioning vis-à-vis category exemplars in shaping audience evaluations, our findings have important implications for research on positioning relative to category exemplars, category viability, optimal distinctiveness, and security analysts.

    Majid Majzoubi, Eric Yanfei Zhao (2023), "Going Beyond Optimal Distinctiveness: Strategic Positioning for Gaining an Audience Composition Premium", Strategic Management Journal, 44(3), 737-777.

    View Paper

    Abstract

    A core question in strategy research is how firms should position themselves to gain favorable audience evaluations. Emphasizing the heterogeneity in audience predispositions, we propose that firms can gain an audience composition premium by strategically positioning themselves to gain more (less) attention from audiences with positive (negative) predispositions toward them. We argue that this approach to strategic positioning is more conducive for firms with high dispersion in their audience predispositions and that firms can increase their ability to gain an audience composition premium by engaging with audiences holding moderately diverse evaluative schemas. We employ recommender systems and topic modeling to analyze 152,312 firm-analyst-year observations from 1997 to 2018 and 297,931 earnings call transcripts of U.S. public firms and find strong support for our predictions.

    Managerial Summary
    A key question managers encounter is how to increase their firms’ evaluations from external evaluators such as security analysts. In this study, we show that firms can increase their aggregate analyst recommendations by influencing the composition of analysts who opt to cover them and gaining evaluations from analysts who have more favorable predispositions toward them (i.e., by gaining an audience composition premium). Our findings also suggest that gaining an audience composition premium is more important for enhancing a firm’s aggregate analyst recommendations when there is a higher dispersion in analyst predispositions toward the firm. To increase its ability to gain an audience composition premium, the firm should engage with analysts who exhibit a moderate degree of heterogeneity in their evaluative schemas.

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