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Academic copyright in the publishing game: a contest perspective

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Abstract

As scientists are motivated by readership rather than by royalties, one might doubt that academic copyright is required for stimulating research. Consequently, establishing an open access regime is currently intensively being discussed. We contribute to the literature by using a contest-model in which differently talented researchers compete for limited journals space. The contest perspective adds a rent-seeking motive into the publishing game which questions that private incentives for research are always too low due to the positive externalities of scientific progress. In our model, open access always leads to higher social welfare when incentives are too high. When incentives are too low, then open access is only superior if the benefits from larger readership is sufficiently high.

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Notes

  1. An extensive overview on the development of subscription prices in the academic publishing market is given by Ted Bergstrom. See http://www.econ.ucsb.edu/~tedb/Journals/jpricing.html.

  2. We do not deny the importance of intrinsic motivation. However, in particular empirical sports economics has demonstrated that intrinsic motivation and responding strongly to incentives in contests is not mutually exclusive; see e.g. the case studies discussed in Andreff andSzymanski (2006).

  3. See the seminal contribution on multi-tasking by Holmström and Migrom (1991), followed by a large body of literature showing that incentives are often distorted as only easily measurable activities are rewarded.

  4. A comprehensive overview on contest models is provided in Konrad (2009).

  5. Costs for a single publication, for example in a Public Library of Science (PLoS) journal, currently ranges from $ 1,350 (PLoS ONE) to $ 2,900 (PLoS Biology or PLoS Medicine). See http://www.plos.org/journals/pubfees.html. Besides, King (2007) estimates that the average fixed costs for publishing a single article is $ 3,000.

  6. Using the physics e-print archive “arXiv.org”, Brody et al. (2006) find a correlation of approximately 0.4 between readership and citations.

  7. In a study for the Joint Information Systems Committee in the UK, Houghton and Oppenheim (2010) argue that, in the long run, both open access journals and self-archiving platforms such as “arXiv.org” or “ssrn” will result in positive net benefits. Harnad et al. (2004) refers to open access journals as the “gold” and to self-archiving platforms as the “green” roads of open access. The advantage of the “gold” road is that peer-reviews may foster a quality selection process. As platforms such as “ssrn” coexist with closed access for quite some time, we restrict attention to comparing open access-journals to closed access.

  8. Another methodological problem concerns the self-selection of authors which challenges empirical findings; see Craig et al. (2007) and Gargouri et al. (2010) on this topic.

  9. See Stevan Harnad’s online bibliography at http://opcit.eprints.org/oacitation-biblio.html for an overview.

  10. In this regard, Eger et al. (2015) find significant differences in the usage of OA between disciplines which are primarily driven by journal reputation. Migheli and Ramello (2014) find that there are only few OA journals in economics with impact factor, which may explain why researchers in economics are rather reluctant to submit to OA venues.

  11. In the objective functions, publication costs are the only monetary variable. As usual, we assume that all other variables can be expressed as monetary equivalents, so that e.g. \(e_{i}\) expresses the costs of effort.

  12. This requires that the low type’s expected utility is positive for the efforts derived below. Substituting these efforts in the utility functions gives \(V_{L}^{C}=\frac{r^{C}}{\left( 1+\theta \right) ^{2}}\ge 0\) for closed access and \(V_{L}^{O}=\frac{\left( 1-g\right) ^{3}}{\left( 1+\theta -g\right) ^{2}}\ge 0\) for open access, so that efforts are indeed positive in equilibrium.

  13. As submission costs are only positive for the low type under open access, we will subsequently write g instead of \(g_{L}^{O}\) for short.

  14. Both properties also hold for the more general case where \(p_{H}=\frac{ \theta \left( e_{H}\right) ^{t}}{\theta \left( e_{H}\right) ^{t}+\left( e_{L}\right) ^{t}}\) and \(p_{L}=\frac{\left( e_{L}\right) ^{t}}{\theta \left( e_{H}\right) ^{t}+\left( e_{L}\right) ^{t}}\). In this more general version, t captures the degree of discrimination, that is the sensitivity of winning the contest to the efforts taken by the players.

  15. To see this just take the partial derivatives of the best response functions, i.e. \(\frac{\partial e_{H}}{\partial e_{L}}=\frac{1}{2e_{L}\theta ^{2}}\left( \sqrt{e_{L}r^{k}\theta ^{3}}-2e_{L}\theta \right)\) and \(\frac{ \partial e_{L}}{\partial e_{H}}=\frac{1}{2e_{H}}\left( \sqrt{e_{H}\theta \left( r^{k}-g\right) }-2e_{H}\theta \right)\).

  16. Recall from Proposition 1, part (iv) that the opposite holds for the low type.

  17. In non-strategic models such as Shavell (2010), the utility of readers is explicitly modelled from supply and demand. Incorporating this explicitly into a contest-model, however, yields a very convoluted model structure that can hardly be handled, but adds nothing to the points we wish to make.

  18. Superscript “f” denotes “first best”.

  19. The differences in the private and socially optimal efforts with open access are \(\Delta e_{L}^{O}\equiv e_{L}^{O}-e_{L}^{f}=\frac{\theta \left( 1-g\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}-\frac{\beta ^{2}}{4}\) and \(\Delta e_{H}^{O}\equiv e_{H}^{O}-e_{H}^{f}=\frac{\theta \left( 1-g\right) }{\left( 1+\theta -g\right) ^{2}}-\frac{\theta \beta ^{2}}{4}\) which gives derivatives of \(\frac{\partial \Delta e_{L}^{O}}{\partial g}=-\frac{2\theta ^{2}\left( 1-g\right) }{\left( \theta -g+1\right) ^{3}}<0\) and \(\frac{ \partial \Delta e_{H}^{O}}{\partial g}=-\frac{\theta \left( g+\theta -1\right) }{\left( \theta -g+1\right) ^{3}}<0\).

  20. Recall that \(r^{C}\) implicitly measures the readership with closed access relative to open access as \(r^{O}\) is normalized to one.

  21. See e.g. the overview in Konrad (2009).

  22. As for this, recall that one can reasonably assume that the contest’s loser can publish her paper in a less highly ranked journal. This is also the reason why we assume throughout that the readers’ utility depends on the quality of the papers, but not on the identity of the winner in the contest.

  23. If they also cared about the part paid by their employees, then \(g_{i}\) would cancel out, and only \(\frac{e_{H}}{e_{H}+e_{L}}H\) would remain e.g. for the objective function of high type’s institution.

  24. \(\zeta _{i}\) denotes institution i ’s net utility.

  25. See http://tool.handelsblatt.com/tabelle/index.php?id=135.

  26. Based on a survey, Eger et al. (2015) find that the presence and/or height of author fees are among the biggest obstacles towards open access.

  27. The questionnaire is available at http://marcscheufen.com/.cm4all/iproc.php/eQuestionnaire%202015?cdp=a&cm_odfile.

    As there is an overlap between the life-time- and the under 40-ranking and because some of the ranked researchers are no longer affiliated with research institutions, we could send 589 E-mails.

  28. To exclude an overlap of the two groups, we mentioned to top researchers that they might receive a similar E-mail from their deans and asked them to ignore this link.

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Acknowledgments

We are grateful to two anonymous referees whose comments considerably improved the paper. We also like to thank Tim Friehe, Gerd Mühlheußer, and conference participants in Hamburg, Barcelona and Bilbao for helpful comments and suggestions.

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Correspondence to Eberhard Feess.

Appendix

Appendix

Proof of Proposition 1

Part (i). Taking the partial derivatives gives

$$\begin{aligned} \frac{\partial e_{H}^{C}}{\partial \theta }= & {} \frac{\partial e_{L}^{C}}{ \partial \theta }=r^{C}\frac{1-\theta }{\left( 1+\theta \right) ^{3}}<0, \frac{\partial e_{H}^{O}}{\partial \theta }=-\left( 1-g\right) \frac{ \theta -1+g}{\left( 1+\theta -g\right) ^{3}}<0, \\ \frac{\partial e_{L}^{O}}{\partial \theta }= & {} -\left( 1-g\right) ^{2}\frac{ \theta -1+g}{\left( \theta -g+1\right) ^{3}}<0. \end{aligned}$$

Part (ii). Obvious. Part (iii). The ratio of efforts is \(\frac{ e_{H}^{*}}{e_{L}^{*}}=\frac{r^{k}}{r^{k}-g_{L}^{k}}\), and thus \(e_{H}^{*}=e_{L}^{*}\) for \(g=0\) while \(e_{H}^{*}>e_{L}^{*}\) for \(g>0\). Next,

$$\begin{aligned} \frac{\partial e_{H}^{*}}{\partial g}= & {} -\frac{\left( r^{O}\right) ^{2}\theta \left( r\left( \theta -1\right) +g\right) }{\left( r^{O}\left( \theta +1\right) -g\right) ^{3}}<0, \end{aligned}$$
(19)
$$\begin{aligned} \frac{\partial e_{L}^{*}}{\partial g}= & {} -\frac{2\left( r^{O}\right) ^{2}\theta ^{2}\left( r^{O}-g\right) }{\left( r^{O}\left( \theta +1\right) -g\right) ^{3}}<0. \end{aligned}$$
(20)

Part (iv). From the best response functions in the text, we get

$$\begin{aligned} \frac{\partial e_{H}}{\partial e_{L}}= & {} \frac{1}{2e_{L}\theta ^{2}}\left( \left( e_{L}r^{k}\theta ^{3}\right) ^{0.5}-2e_{L}\theta \right) \\ \frac{\partial e_{L}}{\partial e_{H}}= & {} \frac{1}{2e_{H}}\left( \left( e_{H}\theta \left( r^{k}-g_{L}^{k}\right) \right) ^{0.5}-2e_{H}\theta \right) . \end{aligned}$$

Substituting the equilibrium values into the right hand sides of the two equations gives

$$\begin{aligned} \frac{\partial e_{H}\left( e_{L}^{*}\right) }{\partial e_{L}}= & {} \frac{ r^{k}\left( \theta -1\right) +g_{L}^{k}}{2\theta \left( r^{k}-g_{L}^{k}\right) }>0. \\ \frac{\partial e_{L}\left( e_{H}^{*}\right) }{\partial e_{H}}= & {} -\frac{ \left( r^{k}\left( 1+\theta \right) -g_{L}^{k}\right) ^{2}}{2\left( r^{^{k}}\right) ^{2}\theta \left( r^{k}-g_{L}^{k}\right) }\left( r^{k}\theta \left( r^{k}-g_{L}^{k}\right) \frac{r^{k}\left( \theta -1\right) +g_{L}^{k}}{ \left( r^{k}\left( 1+\theta \right) -g_{L}^{k}\right) ^{2}}\right) <0. \end{aligned}$$

Proof of Proposition 2

Recall that we have normalized \(r^{O}=1\). Then, \(r^{C}<\frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}\) for the low type (part (i)) and \(r^{C}< \frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\) for the high type (part (ii)) follow immediately from \(e_{H}^{*}\) and \(e_{L}^{*}\) as given in the text. For the comparative statics in part (i), we have \(\frac{\partial \left( RHS1\right) }{ \partial \theta }=\frac{2g\left( 1+\theta -g\right) }{\left( \theta +1\right) ^{3}\left( 1-g\right) ^{2}}>0\), \(\frac{\partial \left( RHS1\right) }{\partial g}=-\frac{2\theta \left( 1+\theta -g\right) }{\left( \theta +1\right) ^{2}\left( 1-g\right) ^{3}}<0\). The comparative statics for part (ii) yields \(\frac{\partial \left( RHS2\right) }{\partial \theta }= \frac{2g\left( 1+\theta -g\right) }{\left( 1+\theta \right) ^{3}\left( 1-g\right) }>0\), \(\frac{\partial \left( RHS2\right) }{dg}=\frac{\left( 1+\theta -g\right) \left( \theta +g-1\right) }{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}>0\) where RHS1 and RHS2 denote the right hand sides in the inequalities stated in part (i) and part (ii) of the Lemma, respectively. Part (iii). For the low type, \(e_{L}^{O}>e_{L}^{C}\) iff \(r^{C}<\frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\). The RHS of the inequality is increasing in \(\theta\), \(\frac{\partial \left( \frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\right) }{ \partial \theta }=\frac{2g\left( 1+\theta -g\right) }{\left( 1+\theta \right) ^{3}\left( 1-g\right) }>0\) and in g, \(\frac{\partial \left( \frac{ \left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\right) }{\partial g}=\left( \frac{2\theta \left( 1+\theta -g\right) }{\left( \theta +1\right) ^{2}\left( 1-g\right) ^{3}}\right) >0\). For the high type, \(e_{H}^{O}>e_{H}^{C}\) iff \(r^{C}<\frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\). The derivatives of the RHS are \(\frac{\partial \left( \frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) }\right) }{ \partial \theta }=\frac{2g\left( 1+\theta -g\right) }{\left( \theta +1\right) ^{3}\left( 1-g\right) }>0\) and \(\frac{\partial \left( \frac{\left( 1+\theta -g\right) ^{2}}{\left( 1+\theta \right) ^{2}\left( 1-g\right) } \right) }{\partial g}=\frac{\left( 1+\theta -g\right) \left( \theta -1+g\right) }{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}>0\) as \(\theta >1\).

$$\begin{aligned} Part\ (iv).\frac{\frac{e_{H}^{O}}{e_{L}^{O}}}{\frac{e_{H}^{C}}{ e_{L}^{C}}}=\frac{\frac{\frac{\theta \left( 1-g\right) }{\left( \left( 1+\theta \right) -g\right) ^{2}}}{\frac{\theta \left( 1-g\right) ^{2}}{ \left( \left( 1+\theta \right) -g\right) ^{2}}}}{\frac{\frac{\left( r^{C}\right) ^{2}\theta }{\left( r^{C}\left( 1+\theta \right) \right) ^{2}}}{ \frac{\left( r^{C}\right) ^{2}\theta }{\left( r^{C}\left( 1+\theta \right) \right) ^{2}}}}=\frac{1}{1-g}>1{\text{iff}}\,g>0.\end{aligned}$$

Proof of Lemma 1

Part (i). The high type’s optimal effort with closed access is \(\frac{\left( r^{C}\right) ^{2}\theta \beta ^{2}}{4}\), while his equilibrium effort is \(e_{H}^{C}=\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}\). We get \(\frac{\left( r^{c}\right) ^{2}\theta \beta ^{2}}{4}-\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}>0\Leftrightarrow \beta >\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }\) as stated in the Lemma. The low type’s optimal effort with closed access is \(\frac{\left( r^{C}\right) ^{2}\beta ^{2}}{4}\), while his equilibrium effort is \(e_{L}^{C}=\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}\). Thus, \(\frac{\left( r^{C}\right) ^{2}\beta ^{2}}{4}-\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}>0\Leftrightarrow \beta >\frac{2\theta ^{0..5}}{\left( r^{C}\right) ^{0..5}\left( 1+\theta \right) }\) as stated in the Lemma. Part (ii). The high type’s optimal effort with open access is \(\frac{\theta \beta ^{2}}{4}\), while his equilibrium effort is \(e_{H}^{O}=\frac{\theta \left( 1-g\right) }{\left( 1+\theta -g\right) ^{2}}\). We get \(\frac{\theta \beta ^{2}}{4}-\frac{\theta \left( 1-g\right) }{\left( 1+\theta -g\right) ^{2}}>0\Leftrightarrow \beta >2\frac{\left( 1-g\right) ^{0.5}}{1+\theta -g}\) as stated in the Lemma. The low type’s optimal effort with closed access is \(\frac{\beta ^{2}}{4}\), while his equilibrium effort is \(e_{L}^{O}=\frac{ \theta \left( 1-g\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}\). Thus, \(\frac{\beta ^{2}}{4}-\frac{\theta \left( 1-g\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}>0\Leftrightarrow \beta >\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}\) as stated in the Lemma. Part (iii). Efforts are always too low if

\(\beta >\max \left( \frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\theta ^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g},\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}\right)\). Next, (a)\(\frac{2\theta ^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }>\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }\) as \(\theta >1\). (b) Define \(\Delta _{1}\equiv \frac{2\theta ^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }-\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}\). We show that \(\Delta _{1}>0\). As \(\frac{\partial \Delta _{1}}{\partial r^{C}}<0\) and \(\frac{\partial \Delta _{1}}{\partial g}>0\), we consider the maximum \(r^{C}=1\) and the minimum \(g=0\) to get \(\Delta _{1}=2\frac{\theta ^{0.5}-1}{ \theta +1}>0\). (c) Define \(\Delta _{2}\equiv \frac{2\theta ^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }-\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}\). We show that \(\Delta _{2}\ge 0\). As \(\frac{ \partial \Delta _{2}}{\partial r^{C}}<0\) and \(\frac{\partial \Delta _{2}}{ \partial g}>0\), we consider \(r^{C}=1\) and \(g=0\) to get \(\Delta _{2}=0\). Part (iv). Efforts are always too high if \(\beta <\min \left( \frac{2 }{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\theta ^{0.5}}{ \left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g},\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g} \right)\). We know that \(\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }<\frac{2\theta ^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }\). Next, define \(\Delta _{3}\equiv \frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }-\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}\). We show that \(\Delta _{3}\ge 0\). As \(\frac{\partial \Delta _{2}}{ \partial r^{C}}<0\) and \(\frac{\partial \Delta _{2}}{\partial g}>0\), we consider \(r^{C}=1\) and \(g=0\) to get \(\Delta _{2}=0\). Thus, we are left with the candidates \(\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}\) and \(\frac{ 2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}\). Define \(R_{1}\equiv \frac{ \frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}}{\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}}=\frac{1}{\theta ^{0.5}\left( 1-g\right) ^{0.5}}\) which is decreasing in g and above 1 iff \(g>1-\frac{1}{\theta }\). Then, \(\beta <\frac{2\theta ^{0.5}\left( 1-g\right) }{1+\theta -g}\) is the relevant condition and otherwise \(\beta <\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}\).□

Proof of Proposition 3

Define the ratios under the two regimes as

$$\begin{aligned} \hat{e}_{L}\equiv & {} \frac{e_{L}^{O}}{e_{L}^{C}}=\frac{\frac{\theta \left( 1-g\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}}{\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}}=\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}{r^{C}\left( 1+\theta -g\right) ^{2}} \end{aligned}$$
(21)
$$\begin{aligned} \hat{e}_{H}\equiv & {} \frac{e_{H}^{O}}{e_{H}^{C}}=\frac{\frac{\theta \left( 1-g\right) }{\left( 1+\theta -g\right) ^{2}}}{\frac{r^{C}\theta }{\left( \theta +1\right) ^{2}}}=\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) }{r^{C}\left( 1+\theta -g\right) ^{2}} \end{aligned}$$
(22)

From \(\hat{e}_{L}\) and \(\hat{e}_{H}\) we get

$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial \theta }= & {} -\frac{2g\left( \theta +1\right) \left( 1-g\right) ^{2}}{r^{C}\left( \theta -g+1\right) ^{3}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial \theta }=-\frac{2g\left( 1+\theta \right) \left( 1-g\right) }{r^{C}\left( \theta -g+1\right) ^{3}}<0 \end{aligned}$$
(23)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial g}= & {} -\frac{2\theta \left( \theta +1\right) ^{2}\left( 1-g\right) }{r^{C}\left( \theta -g+1\right) ^{3}}<0 , \quad \frac{\partial \hat{e}_{H}}{\partial g}=-\frac{\left( \theta +1\right) ^{2}\left( \theta -1+g\right) }{r^{C}\left( \theta -g+1\right) ^{3} }<0 \end{aligned}$$
(24)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial r^{C}}= & {} -\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}{\left( r^{C}\right) ^{2}\left( \theta -g+1\right) ^{2}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial r}=-\frac{ \left( \theta +1\right) ^{2}\left( 1-g\right) }{\left( r^{C}\right) ^{2}\left( \theta -g+1\right) ^{2}}<0. \end{aligned}$$
(25)

Recalling that all efforts are too low by definition of the case considered, the claim follows.□

Proof of Proposition 4

Recall first that we know from Lemma 1 that all efforts are too high if \(\beta <\frac{2\theta ^{0.5}\left( 1-g\right) }{ 1+\theta -g}\) for \(g\ge 1-\frac{1}{\theta }\) and \(\beta <\frac{2\left( 1-g\right) ^{0.5}}{1+\theta -g}\) for \(g<1-\frac{1}{\theta }\). Consider first the limit case where \(r^{C}\rightarrow r^{O}=1\), so that the only difference between open to closed access is that the low type needs to pay for her submission costs. Then, both efforts are higher under closed access as \(\hat{ e}_{L}=\frac{\left( 1-g\right) ^{2}\left( \theta +1\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}<1\forall g>0\) and \(\hat{e}_{H}=\frac{\left( 1-g\right) \left( \theta +1\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}<1\) where the last inequality follows from \(\frac{\partial \hat{e}_{H}}{\partial \theta }=\frac{-2g\left( 1-g\right) \left( \theta +1\right) }{\left( 1+\theta -g\right) ^{3}}<0\) and \(\frac{\partial \hat{e}_{H}}{\partial g}= \frac{\left( \theta +1\right) ^{2}\left( 1-\theta -g\right) }{\left( 1+\theta -g\right) ^{3}}<0\) together with \(\frac{e_{H}^{O}}{e_{H}^{C}}=1\) for the minimum values \(\theta =1\) and \(g=0\). Next, note that only the two efforts matter for the difference in the welfare of the two publishing modes for \(r^{C}=1\). And since social welfare is decreasing in efforts by definition of the case considered, welfare is higher for open access if audience is identical. Finally, social welfare for closed access is strictly increasing in \(r^{C}\) as

$$\begin{aligned} \frac{\partial SW^{C}}{\partial r^{C}}=\beta \left( \frac{\left( r^{C}\right) ^{0.5}\theta ^{0.5}+r^{C}\theta }{\left( 1+\theta \right) } \right) +\beta r^{C}\left( \frac{\left( r^{C}\right) ^{-0.5}\theta ^{0.5}+2\theta }{2\left( 1+\theta \right) }\right) -\frac{2\theta }{\left( 1+\theta \right) ^{2}}+1>0 \end{aligned}$$
(26)

due to the fact that \(\frac{2\theta }{\left( 1+\theta \right) ^{2}}\) is bounded above by 1 for \(\theta \ge 1\). Therefore, \(SW^{O}-SW^{C}(r^{C}=1)>0\Rightarrow\) \(SW^{O}-SW^{C}(r^{C})>0\) \(\forall r^{C}<1\).□

Proof of Lemma 2

Part (i). \(\frac{\partial e_{H}^{C}}{ \partial \theta _{l}}=-\frac{r}{\theta _{l}^{2}}<0\); \(\frac{\partial e_{L}^{C}}{\partial \theta _{l}}=-\frac{2r}{\left( \theta _{l}+1\right) ^{3}} <0\); \(\frac{\partial e_{H}^{O}}{\partial \theta _{l}}=-\frac{\left( 1-g\right) \left( g+\theta _{l}-1\right) }{\left( \theta _{l}-g+1\right) ^{3} }<0\); \(\frac{\partial e_{L}^{O}}{\partial \theta _{l}}=-2\frac{\left( g-1\right) ^{2}}{\left( \theta _{l}-g+1\right) ^{3}}<0\); \(\frac{\partial e_{H}^{O}}{\partial g}=-\frac{\theta _{l}\left( g+\theta _{l}-1\right) }{ \left( \theta _{l}-g+1\right) ^{3}}<0\); \(\frac{\partial e_{L}^{O}}{\partial g }=-\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}-g+1\right) ^{3}} <0\). For part (ii), just recall that \(e_{i}^{O}>e_{i}^{C}\), \(i=H,L\) for \(g\rightarrow 0\) as then only the effect of higher readership exists. Furthermore, \(e_{i}^{O}<e_{i}^{C}\), \(i=H,L\) for \(r^{C}\rightarrow 1\) as then only the effort-reducing effect of the low type’s submission costs exists. Thus, the overall impact depends on which effect dominates, just as in Proposition 2.□

Proof of Lemma 3

Parts (i) and (ii) follow directly from comparing the privately and the socially optimal effort levels.

Part (iii). Efforts are always too low if

\(\beta >\max \left( \frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) },\frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) },\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }, \frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }\right)\). We prove that \(\frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }>\max \left( \frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) },\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) },\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }\right)\), so that \(\beta >\frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }\) is the condition for all efforts being always too low:

  1. (a)
    $$\begin{aligned} \frac{\frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }}{\frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }}=\theta _{l}^{0.5}>1\,{\text {as}}\,\theta _{l}>1. \end{aligned}$$
    (27)
  2. (b)

    Define \(R_{1}\equiv \frac{\frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }}{\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }}\). As we want to show that \(R_{1}>1\) and since \(R_{1}\) is decreasing in \(r^{C}\), we consider the maximum \(r^{C}=1\). Then, \(R_{1}=\theta _{l}\frac{\left( 1-g\right) +\theta _{l}}{\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}\left( 1+\theta _{l}\right) }\). As \(\frac{\partial R_{1}}{\partial g}= \frac{\theta _{l}^{2}\left( \theta _{l}-\left( 1-g\right) \right) }{2\left( \theta _{l}\left( 1-g\right) \right) ^{\frac{3}{2}}\left( 1+\theta _{l}\right) }>0\), we need to consider the minimum g. Then, \(R_{1}=1+\frac{ 1+\theta _{l}}{\theta _{l}^{0.5}}>1\).

  3. (c)
    $$\begin{aligned} \frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }-\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }=2\theta _{l}\frac{\left( \theta _{l}+\left( 1-g\right) \right) -\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) \left( 1-g\right) }{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) \left( \theta _{l}+\left( 1-g\right) \right) }>0\text{:} \end{aligned}$$
    (28)

    The denominator is always positive. The numerator N is decreasing in \(r^{C}\) and simplifies to \(N=g\theta _{l}>0\) for the maximum \(r^{C}=1\).

Parts (a), (b) and (c) together prove that \(\beta >\frac{2\theta _{l}}{ \left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }\) is the critical condition.

Part (iv) Efforts are always too high if

\(\beta <\min \left( \frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) },\frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) },\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }, \frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }\right)\). We know from the proof of part (iii) that \(\frac{ 2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }< \frac{2\theta _{l}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }\). Define \(R_{2}\equiv \frac{\frac{2\theta _{l}^{0.5}}{\left( r^{C}\right) ^{0.5}\left( 1+\theta _{l}\right) }}{\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }}\). We show that \(R_{2}\ge 1\). As \(\frac{\partial R_{2}}{\partial r^{C}}<0\), we consider the maximum \(r^{C}=1\) to get \(R_{2}=\frac{\theta _{l}^{0.5}\left( \left( 1-g\right) +\theta _{l}\right) ^{0.5}}{\left( 1+\theta _{l}\right) }\) which is increasing in g. We hence consider \(g=0\) which gives \(R_{2}=1\). We are hence left with the comparison of \(\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }\) and \(\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }\) and define \(R_{3}\equiv \frac{\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }}{\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }}=\left( \frac{1}{\theta _{l}\left( 1-g\right) }\right) ^{0.5}\) which is increasing in g and above 1 iff \(g>1-\frac{1}{\theta _{l}}\). Then, \(\beta <\frac{2\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) }\) is the relevant condition and otherwise \(\beta <\frac{2\left( \theta _{l}\left( 1-g\right) \right) ^{0.5}}{\left( \theta _{l}+\left( 1-g\right) \right) }\).□

Proof of Proposition 5

Part (i). Define the ratios of the two types’ efforts under the two regimes as

$$\hat{e}_{L} \equiv {} \frac{e_{L}^{O}}{e_{L}^{C}}=\frac{\frac{\left( 1-g\right) ^{2}}{\left( \theta _{l}+\left( 1-g\right) \right) ^{2}}}{\frac{ r^{C}}{\left( 1+\theta _{l}\right) ^{2}}}=\frac{\left( 1-g\right) ^{2}\left( 1+\theta _{l}\right) ^{2}}{r^{C}\left( \left( 1-g\right) +\theta _{l}\right) ^{2}}$$
(29)
$$\hat{e}_{H}\equiv {} \frac{e_{H}^{O}}{e_{H}^{C}}=\frac{\frac{\theta _{l}\left( 1-g\right) }{\left( \theta _{l}+\left( 1-g\right) \right) ^{2}}}{ \frac{\theta _{l}r^{C}}{\left( 1+\theta _{l}\right) ^{2}}}=\frac{\left( 1-g\right) \left( 1+\theta _{l}\right) ^{2}}{r^{C}\left( \left( 1-g\right) +\theta _{l}\right) ^{2}}$$
(30)

to get

$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial \theta _{l}}= & {} -\frac{2g\left( 1-g\right) ^{2}\left( 1+\theta _{l}\right) }{r^{C}\left( \theta _{l}-g+1\right) ^{3}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial \theta _{l}}=-\frac{2g\left( 1-g\right) \left( 1+\theta _{l}\right) }{r^{C}\left( \theta _{l}-g+1\right) ^{3}}<0 \end{aligned}$$
(31)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial g}= & {} -\frac{2\theta _{l}\left( 1-g\right) \left( 1+\theta _{l}\right) ^{2}}{r^{C}\left( \theta _{l}-g+1\right) ^{3}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial g}=- \frac{\left( 1+\theta _{l}\right) ^{2}\left( g+\theta _{l}-1\right) }{ r^{C}\left( \theta _{l}-g+1\right) ^{3}}<0 \end{aligned}$$
(32)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial r^{C}}= & {} -\frac{\left( 1-g\right) ^{2}\left( 1+\theta _{l}\right) ^{2}}{\left( r^{C}\right) ^{2}\left( \theta _{l}-g+1\right) ^{2}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial r^{C}}=- \frac{\left( 1-g\right) \left( 1+\theta _{l}\right) ^{2}}{\left( r^{C}\right) ^{2}\left( \theta _{l}-g+1\right) ^{2}}<0. \end{aligned}$$
(33)

Recalling that all efforts are too low by definition of the case considered, the claim follows. Part (ii). Follows exactly the proof of Proposition 4 and is therefore omitted.□

Proof of Lemma 4

Parts (i) and (ii) follow directly from comparing the privately and the socially optimal effort levels.

Part (iii). Efforts are always too low if \(\beta >\max \left( \frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\left( r^{C}\theta \right) ^{0.5}}{lr^{C}\left( 1+\theta \right) },\frac{2\left( 1-g\right) ^{0.5}}{\left( 1+\theta -g\right) },\frac{ 2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }\right)\) (a). \(\frac{\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }}{\frac{ 2\theta ^{0.5}}{l\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }}=\frac{l }{\theta ^{0.5}}<1\) as \(l<1\) and \(\theta >1\). (b) Define \(R_{1}\equiv \frac{ \frac{2\theta ^{0.5}}{l\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }}{ \frac{2\left( 1-g\right) ^{0.5}}{\left( 1+\theta -g\right) }}\). We show that \(R_{1}>1\). As \(\frac{\partial R_{1}}{\partial r^{C}}<0\) and \(\frac{\partial R_{1}}{\partial g}>0\), we consider \(r^{C}=1\) and \(g=0\) to get \(R_{1}=\frac{ \theta ^{0.5}}{l}>1\). (c) Define \(R_{2}\equiv \frac{\frac{2\theta ^{0.5}}{ l\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }}{\frac{2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }}\). We show that \(R_{2}\ge 1\). As \(\frac{\partial R_{1}}{\partial r^{C}}<0\) and \(\frac{ \partial R_{1}}{\partial g}>0\), we consider \(r^{C}=1\) and \(g=0\) to get \(R_{1}=1\). Thus, \(\beta >\frac{2\theta ^{0.5}}{l\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }\) is the critical condition.

Part (iv). Efforts are always too high if \(\beta <\min \left( \frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) },\frac{2\left( r^{C}\theta \right) ^{0.5}}{lr^{C}\left( 1+\theta \right) },\frac{2\left( 1-g\right) ^{0.5}}{\left( 1+\theta -g\right) },\frac{ 2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }\right)\). We know from the proof of part (iii) that \(\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }<\frac{2\theta ^{0.5}}{l\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }\). Define \(R_{3}\equiv \frac{\frac{2}{\left( r^{C}\right) ^{0.5}\left( 1+\theta \right) }}{\frac{2\left( 1-g\right) ^{0.5} }{\left( 1+\theta -g\right) }}\). We show that \(R_{3}\ge 1\). As \(\frac{ \partial R_{3}}{\partial r^{C}}<0\) and \(\frac{\partial R_{3}}{\partial g}>0\), we consider \(r^{C}=1\) and \(g=0\) which gives \(R_{3}=1\). We are hence left with the comparison of \(\frac{2\left( 1-g\right) ^{0.5}}{\left( 1+\theta -g\right) }\) and \(\frac{2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }\) and define \(R_{4}\equiv \frac{\frac{2\left( 1-g\right) ^{0.5}}{ \left( 1+\theta -g\right) }}{\frac{2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }}=\frac{l}{\theta ^{0.5}\left( 1-g\right) ^{0.5}}\) which is increasing in g and \(R_{4}>1\) iff \(g>1-\frac{l^{2}}{\theta }\). Then, \(\beta <\frac{2\theta ^{0.5}\left( 1-g\right) }{l\left( 1+\theta -g\right) }\) is the relevant condition and otherwise \(\beta <\frac{l}{\theta ^{0.5}\left( 1-g\right) ^{0.5}}\).□

Proof of Proposition 6

Part (i) . Define the ratios of the two types’ efforts under the two regimes as

$$\begin{aligned} \hat{e}_{L}\equiv & {} \frac{e_{L}^{O}}{e_{L}^{C}}=\frac{\frac{\theta \left( 1-g\right) ^{2}}{\left( 1+\theta -g\right) ^{2}}}{\frac{r^{C}\theta }{\left( 1+\theta \right) ^{2}}}=\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}{r^{C}\left( 1+\theta -g\right) ^{2}} \end{aligned}$$
(34)
$$\begin{aligned} \hat{e}_{H}\equiv & {} \frac{e_{H}^{O}}{e_{H}^{C}}=\frac{\frac{l\left( 1-g\right) }{\left( l+\left( 1-g\right) \right) ^{2}}}{\frac{lr}{\left( 1+l\right) ^{2}}}=\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) }{ r^{C}\left( 1+\theta -g\right) ^{2}} \end{aligned}$$
(35)

to get

$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial \theta }= & {} -\frac{2g\left( 1+\theta \right) \left( 1-g\right) ^{2}}{r^{C}\left( \theta -g+1\right) ^{3}}<0,\frac{\partial \hat{e}_{H}}{\partial \theta }=-\frac{2g\left( 1+\theta \right) \left( 1-g\right) }{r^{C}\left( \theta -g+1\right) ^{3}}<0 \end{aligned}$$
(36)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial g}= & {} -\frac{2\theta \left( 1+\theta \right) ^{2}\left( 1-g\right) }{r^{C}\left( \theta -g+1\right) ^{3}}<0 ,\frac{\partial \hat{e}_{H}}{\partial g}=-\frac{\left( 1+\theta \right) ^{2}\left( g+\theta -1\right) }{r^{C}\left( \theta -g+1\right) ^{3}}<0 \end{aligned}$$
(37)
$$\begin{aligned} \frac{\partial \hat{e}_{L}}{\partial r^{C}}= & {} -\frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) ^{2}}{\left( r^{C}\right) ^{2}\left( \theta -g+1\right) ^{2}}<0,\quad \frac{\partial \hat{e}_{H}}{\partial r^{C}}=- \frac{\left( 1+\theta \right) ^{2}\left( 1-g\right) }{\left( r^{C}\right) ^{2}\left( \theta -g+1\right) ^{2}}<0. \end{aligned}$$
(38)

Recalling that all efforts are too low by definition of the case considered, the claim follows. Part (ii). Follows exactly the proof of Proposition 4 and is therefore omitted.□

Proof of Proposition 7

Part (i). From \(g_{i}^{*}\) as given in the text, we get \(\frac{\partial g_{H}^{*}}{\partial W_{H}}=- \frac{1-g_{L}}{2\sqrt{\left( 1-g_{L}\right) \left( 1+W_{H}\theta -g_{L}\right) }}<0\) and \(\frac{\partial g_{L}^{*}}{\partial W_{L}}=- \frac{\theta \left( 1-g_{H}\right) }{2\sqrt{\theta \left( 1-g_{H}\right) \left( W_{L}+\theta \left( 1-g_{H}\right) \right) }}<0\). Part (ii). From \(g_{i}^{*}\) as given in the text, we get

$$\begin{aligned} \frac{\partial g_{H}^{*}}{\partial g_{L}}=\frac{\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) }\left( \theta \left( 1+W_{H}-s\right) +2\left( 1-g_{L}\right) -2\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) } \right) }{2\theta \left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) } \end{aligned}$$

where the sign depends only on whether \(A\equiv \theta \left( 1+W_{H}-s\right) +2\left( 1-g_{L}\right) >B\equiv 2\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) }\). Taking the square on both sides and considering the difference gives \(A^{2}-B^{2}=\theta ^{2}\left( 1+W_{H}-s\right) ^{2}>0\). Analogous calculations yield \(\frac{\partial g_{L}^{*}}{\partial g_{H}}>0\). Part (iii). We get

$$\begin{aligned} \frac{\partial g_{H}^{*}}{\partial \theta }=\frac{\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) }\left( 2\left( 1-g_{L}\right) +\theta \left( 1+W_{H}-s\right) -2\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) } \right) }{2\theta ^{2}\left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) } \end{aligned}$$

where the sign depends only on whether \(A\equiv 2\left( 1-g_{L}\right) +\theta \left( 1+W_{H}-s\right) >B\equiv 2\sqrt{\left( 1-g_{L}\right) \left( 1+\theta \left( 1+W_{H}-s\right) -g_{L}\right) }\). Taking the square on both sides and considering the difference gives \(A^{2}-B^{2}=\theta ^{2}\left( 1+W_{H}-s\right) ^{2}>0\). Next,

$$\begin{aligned} \frac{\partial g_{L}^{*}}{\partial \theta }=-\frac{1}{2\theta }\frac{ \sqrt{\theta \left( 1-g_{H}\right) \left( 1+W_{L}-s+\theta \left( 1-g_{H}\right) \right) }\left( 1+W_{L}-s+2\theta \left( 1-g_{H}\right) -2 \sqrt{\theta \left( 1-g_{H}\right) \left( W_{L}-s+\theta -\theta g_{H}+1\right) }\right) }{1+W_{L}-s+\theta \left( 1-g_{H}\right) } \end{aligned}$$

which is negative if and only if \(C\equiv 1+W_{L}-s+2\theta \left( 1-g_{H}\right) >D\equiv 2\sqrt{\theta \left( 1-g_{H}\right) \left( W_{L}-s+\theta -\theta g_{H}+1\right) }\). Taking the square on both sides and considering the difference gives \(C^{2}-D^{2}=\left( 1+W_{L}-s\right) ^{2}>0\).□

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Feess, E., Scheufen, M. Academic copyright in the publishing game: a contest perspective. Eur J Law Econ 42, 263–294 (2016). https://doi.org/10.1007/s10657-016-9528-1

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