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Large-scale bibliometric review of diffusion research

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Abstract

Despite the fact that diffusion research has existed for more than a century, a quantitative review covering this subject in a broad and general context is still lacking. This article reviews diffusion research by providing an extensive bibliometric and clustering analysis. In total, we identified thirteen clusters comprising 6,811 publications over the period of 2002–2011, and thereby describe the characteristics of diffusion research in an extensive and general way based on quantitative bibliometric methods. The analysis reveals that diffusion research is highly interdisciplinary in character, involving several disciplines from ethnology to economics, with many overlapping research trails. The concluding section indicates that diffusion research seems to be data driven and relies heavily on solely empirical studies. Consequently, influential publications rely on empirical data that support and change theories in modest ways only. In this contribution, we propose a review method that produces a fairly good overview of the research area and which can be applied to any knowledge field to replace or complement the traditional literature review.

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Notes

  1. We strived to include 10 years of diffusion research. We started conducting this research in 2012. Thus, we included all the data dated back from 2011. In addition, having 2011 as the ending year allowed us to implement age-normalized citations up until 2014.

  2. We used a probability based and field normalized percentile model with six classes (cf. Bornmann 2013). The idea behind the percentile model is neatly expressed by Bornmann and Marx (2014: p. 207): “Percentiles normalize the impact of papers with respect to their publication year and field without using the arithmetic average”.

  3. We used age-normalized citations in accordance with age weighted citation record (AWCR), which is similar to the contemporary h-index proposed as an alternative to the original h-index (Harzing 2010; Sidiropoulos et al. 2007). We implemented a citation window for these publications until August 1, 2014. Three publications were removed because they were in one instance an editorial misclassified as article (document type) and in the second instance considered as off-topic.

  4. Author names indicated as the most cited scholars under section “Cluster analysis” represent only the first authors.

  5. The location of clusters in the map has no intrinsic meaning; we use it here in order to structure the text.

  6. The analysis of some clusters is complemented with review articles that we manually selected in order to enhance our understanding of the research areas.

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Acknowledgments

We are grateful to the participants of the INDEK Working Paper Seminar in Stockholm, 2013. In particular, the opponents—Anders Broström and Pernilla Ulfvengren—along with the editors—Kristina Nyström and Charlotte Holgersson—offered useful and constructive comments on an earlier version. We also thank Staffan Jacobsson for his insightful recommendations and Qi Wang for her review on the methodology part. Staffan Laestadius has provided advice throughout the entire study. Additionally, we thank David House for language review on an earlier version. Lastly, we thank anonymous reviewers whose valuable comments significantly improve the quality of our paper.

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Authors and Affiliations

  1. Department of Industrial Economics and Management, KTH Royal Institute of Technology, Stockholm, Sweden

    Pranpreya Sriwannawit & Ulf Sandström

  2. School of Business, Orebro University, Orebro, Sweden

    Ulf Sandström

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  1. Pranpreya Sriwannawit
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  2. Ulf Sandström
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Correspondence to Pranpreya Sriwannawit.

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Sriwannawit, P., Sandström, U. Large-scale bibliometric review of diffusion research. Scientometrics 102, 1615–1645 (2015). https://doi.org/10.1007/s11192-014-1448-7

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  • DOI: https://doi.org/10.1007/s11192-014-1448-7

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