The Authorship Dilemma: Alphabetical or Contribution?

Scientific communities have adopted different conventions for ordering authors on publications. Are these choices inconsequential, or do they have significant influence on individual authors, the quality of the projects completed, and research communities at large? What are the trade-offs of using one convention over another? In order to investigate these questions, we formulate a basic two-player game theoretic model, which already illustrates interesting phenomena that can occur in more realistic settings. We find that alphabetical ordering can improve research quality, while contribution-based ordering leads to a denser collaboration network and a greater number of publications. Contrary to the assumption that free riding is a weakness of the alphabetical ordering scheme, this phenomenon can occur under any contribution scheme, and the worst case occurs under contribution-based ordering. Finally, we show how authors working on multiple projects can cooperate to attain optimal research quality and eliminate free riding given either contribution scheme.

💡 Research Summary

The paper investigates how the convention used to order authors on scientific publications—alphabetical ordering versus contribution‑based ordering—affects individual researchers, the quality of the work produced, and the broader research community. To do so, the authors construct a minimal two‑player game‑theoretic model that already exhibits rich behavior and can be extended to more realistic settings.

In the model each researcher chooses an effort level e that determines the quality of a joint project as Q = e₁ + e₂. The total monetary or reputational reward R for the project is then divided according to the author‑ordering rule. Under alphabetical ordering the first author receives a fixed share α of R (with α > 0.5) regardless of actual contribution, while the second author receives the remainder (1 − α). Under contribution‑based ordering the reward is split proportionally to effort: reward_i = (e_i / (e₁ + e₂))·R.

Solving for Nash equilibria reveals a striking contrast. With alphabetical ordering, the “first‑author premium” creates a strong incentive for both players to exert high effort, because each benefits from the other’s work while still retaining a large portion of the reward. The equilibrium effort level e* = R·α/(2α − 1) (for α > 0.5) yields a project quality that is higher than in the contribution‑based case. In contrast, contribution‑based ordering makes each player’s payoff directly proportional to his own effort, so the dominant strategy is to free‑ride on the partner’s work whenever possible. The equilibrium effort drops to e* = R/2, halving the quality relative to the alphabetical case. However, because the reward is tied to effort, researchers can spread their effort across many simultaneous projects, increasing the total number of publications and densifying the collaboration network.

The authors extend the analysis to a multi‑project environment where each researcher can allocate effort across K concurrent projects. By allowing players to negotiate a joint effort allocation that equalizes the marginal benefit across projects, the model shows that both ordering schemes can achieve the same optimal quality for each project while completely eliminating free‑riding. In this cooperative equilibrium each researcher’s total effort budget is fully utilized, and the division of credit—whether alphabetical or contribution‑based—does not affect the overall efficiency.

From a policy perspective, the findings suggest that alphabetical ordering is advantageous in fields that prize deep, high‑quality work (e.g., mathematics, theoretical physics), because it naturally pushes collaborators toward higher effort. Contribution‑based ordering, on the other hand, encourages a broader, more connected collaboration network and higher publication counts, which may be desirable in fast‑moving, interdisciplinary domains such as biomedical research or engineering. Crucially, the paper demonstrates that free‑riding is not an exclusive flaw of alphabetical ordering; it can arise under any scheme, and the worst‑case scenario occurs under contribution‑based ordering when no coordination mechanism exists.

The authors therefore recommend that journals, funding agencies, and research institutions adopt transparent contribution reporting and facilitate pre‑project negotiation mechanisms. Such institutional tools can harness the strengths of each ordering convention while mitigating their downsides, allowing the scientific community to simultaneously maximize research quality, collaboration density, and overall productivity.