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Can open access increase LIS research’s policy impact? Using regression analysis and causal inference

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Abstract

The relationship between open access and academic impact (usually measured as citations received from academic publications) has been extensively studied but remains a very controversial topic. However, the effect of open access on policy impact (measured as citations received from policy documents) is still unknown. The purpose of this study was to examine the effect of open access on the policy impact, which might initiate a new controversial topic. Research articles in the field of library and information science (LIS) were selected as the data sample (n = 48,884). Negative binomial regression models were used to examine the dataset. Furthermore, propensity score matching (PSM) analysis, a causal inference approach, was used to estimate the effect of open access on the policy impact based on a selected LIS journal (Scientometrics, n = 4019) that received the most policy citations among the LIS journals. Linear regression models, logit regression models, four other matching methods, open access status provided by different databases, and different sizes of data samples were used to check the robustness of the main results. This study revealed that open access had significant and positive effects on the policy impact.

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Acknowledgements

We are grateful to Overton for granting us access to the Overton database for the policy citation data. We would like to thank the reviewers for their time spent reviewing our manuscript and their insightful comments for hel** us improve the article.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Correspondence to Qian** Zong.

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The authors declare no conflict of interest.

Appendix

Appendix

See Tables

Table 18 Descriptive statistics of the control variables (n = 48,884)

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Table 19 The VIFs of the variables

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Table 20 The descriptive statistics of policy citations for the six LIS journals

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Table 21 The logit regression results of the journal Scientometrics

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Table 22 The results of a balance of covariates after matching for the journal Scientometrics

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Table 23 The results of negative binomial regression models on the DATA-Using-Unpaywall-Remove-Bronze.

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Table 24 The results of linear regression models on the DATA-Using-Unpaywall-Remove-Bronze

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Table 25 The results of logit regression models on the DATA-Using-Unpaywall-Remove-Bronze

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Table 26 The ATETs generated by removing bronze OA articles from the journal Scientometrics (OA status was provided by the Unpaywall)

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Table 27 The results of negative binomial regression models on the DATA-Using-Dimensions

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Table 28 The results of linear regression models on the DATA-Using-Dimensions

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Table 29 The results of logit regression models on the DATA-Using-Dimensions

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Table 30 The ATETs generated by using the OA status provided by the Dimensions for the journal Scientometrics

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Table 31 The results of negative binomial regression models on the DATA-Using-Dimensions-Remove-Bronze

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Table 32 The results of linear regression models on the DATA-Using-Dimensions-Remove-Bronze

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Table 33 The results of logit regression models on the DATA-Using-Dimensions-Remove-Bronze

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Table 34 The ATETs generated by removing bronze OA articles from the journal Scientometrics (OA status was provided by the Dimensions)

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Zong, Q., Huang, Z. & Huang, J. Can open access increase LIS research’s policy impact? Using regression analysis and causal inference. Scientometrics 128, 4825–4854 (2023). https://doi.org/10.1007/s11192-023-04750-1

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  • DOI: https://doi.org/10.1007/s11192-023-04750-1

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