A key question in decision making is whether groups make better decisions than individuals [1–3]. This question is highly relevant to biodiversity conservation. For instance, individual experts may be consulted on management decisions or policy issues whereas boards of directors may make decisions on conservation donations and local communities may use group-based decision making for natural resource management. In the past two decades there has been a pronounced shift towards using groups instead of individuals for decision making (e.g., in key financial institutions such as the Bank of England [4]). Recently, it has also been suggested that groups should be preferred over individual experts for providing science advice to governments [5]. These suggestions are often based on individual attempts to investigate the demerits and merits of group versus individual decision making. However, we are unaware of any studies that have compared group versus individual decision making in conservation. Moreover, there are no systematic reviews in any discipline on decision making by groups versus individuals (but see [1, 2, 6] for narrative reviews).

Thus far there has been very limited research on cognitive aspects of decision making in conservation [but see [7], though it has been studied extensively in other disciplines (e.g. social psychology). Conservation biologists typically approach decision making (and particularly conflict management) as biologists and not from a cognitive approach [8]. Hence, it is not surprising that the literature on decision making in conservation revolves around short term economic incentives (e.g. payment for crop losses due to wildlife, payment for carbon [9, 10]) or technical solutions (e.g., changes in agri-environment schemes, prioritization aspects [11]) or even legal measures (e.g., laws on hunting in protected areas). There is also a considerable body of literature on structured decision making and adaptive management [12], and the cost-effectiveness of conservation decisions [13]. Psychological biases or other cognitive aspects of the decision making process are rarely considered.

However, a review of 1048 business decisions, found that the process of decision making (e.g., level of participation) was more important (by a factor of six) than the analysis (e.g., detailed financial modelling) in determining the quality of decisions [14]. Thus, psychological factors play a pivotal role in decision making and there is ample evidence to suggest that decisions are often influenced by the context in which judgements are made [15]. In particular, decision making is fraught with psychological biases, as shown by the seminal work of Kahneman and Taversky [16]. The impact of such biases in decision making is considerable and has been the subject of extensive research [15]. Understanding these factors can have significant impact on improving the efficiency of the judgement process [15] and on furthering conservation goals [17] since efficient management interventions routinely require effective and rational decision making. Psychological aspects are particularly relevant for biodiversity decisions as they usually involve multiple stakeholders and often opposing viewpoints [17]. The complexity in decision making is often exacerbated by the political nature of the decision itself (e.g., conservation of hen harriers [17]). Furthermore, the urgency within which decisions need to be made (e.g., in the face of a natural calamity) adds to this complexity.

Different facets of decision making (e.g., gender, type of task, effect of biases etc.) have been compared between groups and individuals over the years but the merits of each are unresolved. Attempts at collating and analysing the evidence on decision making by groups versus individuals are limited to narrative reviews which suffer from lack of documentation of the review process itself (see [1, 2, 6, 18]). They are thereby prone to being biased, subject to inter-reviewer differences and hence not repeatable. A systematic review can provide unbiased insights that cannot be obtained otherwise from individual empirical studies. This leads to the motivation for the present systematic review.

In this systematic review, we will attempt to assess when, where, and to what extent, are group decisions different from individual decisions. Are groups more rational or are they more error prone? Rationality refers to the rational choice theory in economics. Error refers to deviation of responses from the “true” value for questions where a “true” value is already known or can be easily calculated (e.g., intellective tasks).

The expected outcomes of the present review could be useful to a range of decision makers or to those who facilitate decision making in the real world. For example, both the International Union for the Conservation of Nature (IUCN) and the New Zealand Department of Conservation have structured their delivery of conservation advice through a series of specialist groups or teams, who collectively develop advice and inform decisions on particular taxa [19]. Often these groups meet in person to define their advice. If the research reviewed here indicated that decisions made by individuals are actually more rational, or more likely to be correct than decisions made by groups, then these organisations might want to reconsider the group-based structure. Conversely, government policymakers often seek advice from independent experts individually [5]. If our review finds that decisions made by groups are consistently more rational, or more likely to be correct, than those made by individuals, then such processes could be redesigned. Our results will be actively communicated to conservation NGOs and policymakers, through our direct involvement in a range of conservation-related science-policy interfaces and networks (for example, the Cambridge Conservation Initiative, and the Eklipse project [20]). In addition, the review might be useful to the theory and practice of decision making as traditionally studied in disciplines such as economics or social psychology.

This systematic review aims to summarize the best available evidence for group and individual based decision making across a range of disciplines. The interdisciplinary nature of the review makes it vulnerable to intellectual turf wars between disciplinary boundaries. However, we have strived to make the aims, objectives and methodology of the review as transparent and explicit as possible. In doing so, we have made an effort to look beyond the disciplinary silos and search for patterns and processes that shape decision making in groups versus individuals.

An endnote database will be created for all the documents. Initially, separate lists will be compiled for each combination of search terms for each of the databases searched. Later these will be compiled into a combined list and sorted for relevance. The articles will be screened based on their titles and abstracts and then the full text in a two-step process. A subset of 200 articles from two different databases will be screened by two independent reviewers for title, abstract and full text screening. The aim is to assess the neutrality of the screening process and reduce between-reviewer differences in all three stages. The Kappa statistic will be used to measure the level of agreement. If the Kappa is less than 0.6 then the screening will be redone after discussing the differences in interpretation.

A note will be made of all hits for which the pdfs could not be found but were found to be relevant at the title and abstract level. In case the abstract is not available, the article will pass on to the next stage of full text screening. Figure 1 gives a schematic representation of the steps involved in the screening process. The number of articles at each step will be noted. If required the process will be iterated to refine the decision rules used for inclusion/exclusion. List of studies that are included at each stage will be added as Additional file 1.

After the initial selection of articles based on the title and abstract, the articles will be critically appraised for internal validity. Studies where the methodology has not been clearly described (e.g., not provided sample size) will be excluded. Studies where there was a bias in the study sample or have poor study design will be excluded. If the sample size is too low, then the study will be made a note of but not included in subsequent meta-analysis. Studies where the same data has been published twice in different journals by the same group of authors will be treated as only one study.

In the scoping exercise, we came across studies that have provided experimental results for ‘before/after’ (BA) the treatment (being in a group). However, for the purpose of this study we will focus on only ‘comparator/intervention’ (CI) part of the studies and not on the ‘BACI’ design. Firstly the main aim of this exercise is to compare group versus individuals. Hence whether a participant was in a group before or after is not of much consequence. Secondly, the BA comparison may not have been tested in majority of the studies. In order to be consistent we will adhere to the ‘comparator/intervention’ design throughout the analysis.

The studies will be screened for quality by one of the reviewers using the critical appraisal tool designed by the Critical Appraisal Skills Programme [27]. In the case of ambiguous studies, the team will take a decision by unanimity. A subset of 50 studies will be screened by two independent reviewers to assess inter reviewer variability. The kappa analysis will be repeated to test for inter-reviewer consensus of at least 0.6. In the case of disagreement, the study quality issues will be rechecked and differences resolved through consensus.

Rationale for exclusion of each article will be noted in a spreadsheet in a transparent way. This spreadsheet will be included as an appendix in the final review.

Within each category the decision rules used to arrive at the group decision will be used as subgroups (e.g., unanimity versus majority rule for group decisions, trustor versus trustee for trust games). Data extraction will be piloted for a subsample of the articles. Based on this initial analysis the data extraction strategy will be modified appropriately. In case there is missing data, the author of the original sources will be contacted by email requesting information for the data gaps. The full list of articles selected for the final review will be added as an Additional file 1.

This list was compiled based on the scoping review and consultation with experts.

The studies will be grouped according to the descriptor data. Data will be synthesized in the form of a narrative text with a table summarizing the findings from each paper based on the criteria outlined in the previous section. If adequate reliable data are available then we will proceed towards a meta-analysis. In such a scenario, both fixed effects and random effects models will be used to investigate the differences between groups and individuals within each procedure category (e.g., lottery game). Depending on the availability of the data, subgroup analysis will be carried out. The difference between groups and individuals (i.e. effect size) will be calculated using Hedges d and/or Odds ratio. The data will be presented as forest plots with accompanying information on heterogeneity (I² values) and p value. In addition, sensitivity analysis and publication bias will also be presented.