The intellectual structure of the strategic management field: an author co‐citation analysis

By Sridhar P. Nerur, Abdul Rasheed, Vivek Natarajan. 2008

677 citations recorded by the source corpus.

Subfields: Statistics and Probability, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/8784b7e2b11b3a741e153349f3695ff2dd6aeb40

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Citations in the corpus

Theory of value co-creation: a systematic literature review (2014, methodology): “Methods and data Our analysis follows a mainstream bibliometric methodology, namely co-citation analysis (e.g. Acedo et al., 2006; Nerur et al., 2008)[2].”
Advances in Social Media Research: Past, Present and Future (2017, methodology): “Author Co-Citation Analysis (ACA) is a bibliometric technique that has been widely used to explicate the conceptual structure of disciplines (for example, see White and Griffith 1981; McCain 1984; Culnan 1986; Nerur et al. 2008).”
Thinking inside the box? Intellectual structure of the knowledge base of innovation research (1988–2008) (2013, methodology): “…(Culnan, O’Reilly, and Chatman, 1990), consumer research (Hoffman and Holbrook, 1993), operations management (Pilkington and Liston-Heyes, 1999; Pilkington and Meredith, 2009), and strategic management (Ramos-Rodriguez and Ruiz- Navarro, 2004; Nerur, Rasheed, and Natarajan, 2008), to mention a few.”
Knowledge structure in international marketing: a multi-method bibliometric analysis (2012, neutral): “50 (Hair et al. 1998; Kuhn 1996; McCain 1990; Nerur et al. 2008; Yadav 2010).”
Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis (2015, methodology): “The co-citation analysis methods that CiteSpace provides are document co-citation analysis (Chen 2006; Leydesdorff 2005), author co-citation analysis (Chen and Carr 1999; Nerur et al. 2008; White and McCain 1998) and journal co-citation analysis (Hu et al.”
Mergers & acquisitions research: A bibliometric study of top strategy and international business journals, 1980–2010 (2014, background): “Moreover, longitudinal bibliometric analysis covering a long period of time help better understand the most influential works, ideas, scholars and schools of thought, and topics (Nerur et al., 2008).”