What Methodologies are Needed to Study Group Communication?
A Bounded-Rationality Perspective
Torsten Reimer, Kirstin Dolick, Hayden Barber, & Jeonghyun Oh
Communication and Cognition Lab
Stephenson Beck, Joann Keyton, & Scott Poole (Eds.)
The Handbook of Group and Team Communication Research
The new millennium has seen several advances in the development of research
methodologies and statistical techniques for the study of group communication (e.g.,
Hollingshead & Poole, 2005; Pilny & Poole, 2017). Among the most prominent research
methods are computational methods and data analysis techniques that have advanced the field of
group communication by tailoring research methods to the context of groups and group-specific
questions. Innovations included the extension of new methods (e.g., text mining, Lambert, 2017;
and annotated codings of group interactions; Brauner, Boos, & Kolbe, 2018) and the adoption of
methods that have been used in other contexts (e.g., machine learning techniques, Bonito &
Keyton, 2018). Notable advancements include new developments in network analysis (e.g., Su &
Contractor, 2011), advances in multi-nominal analyses (e.g., Bonito & Keyton, 2019), and agent-
based simulations (Luan, Katsikopoulos, & Reimer, 2012; Smith & Conrey, 2007; Reimer &
Hoffrage, 2012). With the influx of new technologies, new techniques have been developed that
aim to capture the dynamic nature of team interactions (e.g., Braun et al., 2020; Pilny et al.,
2020) and bridge analyses of small interacting groups and larger systems of individuals, groups,
and organizations (e.g., Poole, 2013; Foote & Contractor, 2018). Notable also are new methods
used to study hybrid systems that include non-human agents and actors (e.g., Park, et al., 2006)
and immersed, virtual environments (e.g., Blascovich & Bailenson, 2012) including virtual
groups (Anderson et al., 2007).
Each of these advancements provides a unique tool that has been developed to test
specific assumptions about group processes and communication. Equally important is their
heuristic value in that each of these methods inspired the development of new theoretical
questions. For example, Bonito and Keyton’s (2019) advancement of multilevel analyses
provides a tool to distinguish empirically between individual constructs on the group level and
the group-member level. The authors show that an experimental manipulation—to communicate
efficiently or politely—accounted for differences in individual group members’ reported
satisfaction but did not account for the observed variation in group satisfaction. The distinction
between constructs on the group and individual level can be extended to other group constructs
and, thus, the developed method opens the door to new theoretical questions (e.g., which factors
affect satisfaction on the member level and which factors affect satisfaction on the group level).
In this commentary, a proposal in favor of a meta-theoretical approach to the study of
group communication is advanced, that has not received much attention in group communication
scholarship: The study of the bounded rationality of groups and teams. The proposal is meant as
an invitation to integrate and extend rather than replace existing methods. The notion of bounded
rationality comes with an invitation to analyze group communication from the vantage point of
an adaptation process that involves the communication processes that are employed by groups
along with characteristics of the environments in which groups are situated.
In the remainder, the general concept of bounded rationality is introduced and some
promises that this meta-theoretical lens offers to group communication scholarship are described.
Three methodological signature characteristics are highlighted: The development and test of
process models, the analysis and description of the ecological and social environments of groups,
and the development of representative designs in the study of groups. The concept of bounded
rationality has been most widely used in decision-making contexts. However, the general
approach is not restricted to decision-making groups but can be extended and applied to other
group tasks (such as problem solving and creative tasks) and include a variety of group concepts
(such as leadership and learning in groups; e.g., see Simon, 1991).
Methodological implications of studying group communication from a bounded-rationality
The concept of bounded rationality has originally been developed in cognitive
psychology and behavioral economics to study individual decision making (for an overview of
research on bounded rationality across various disciplines, see Viale, 2020; also see Hertwig,
Hoffrage, & the ABC Research Group, 2012; Todd, Gigerenzer, & the ABC Research Group,
2012). The concept of bounded rationality is based on the insight that we live in a fundamentally
uncertain world and must operate within the bounds of this uncertainty and our cognitive
limitations and environmental constraints. Unlike classical models of rationality that are built on
logical consistency, bounded rationality focuses on the match between the human mind and the
environment in which it operates highlighting that human reasoning and behavior is the result
from an adaptation of actors to their environment.
What does the concept of bounded rationality have to offer to group communication
scholarship and what are the methodological prerequisites to conduct research on bounded
rationality? Generally speaking, the concept of bounded rationality urges researchers to think in
terms of the ecology of actors by trying to understand how strategies may have developed as an
adaptation to specific information and social environments (e.g., see Gigerenzer, Todd, & the
ABC Group, 1999). One specific area of group research for which this perspective holds promise
refers to the evaluation of group performance. Historically, group research has often focused on
group performance and productivity describing situations in which groups suffer from process
losses. The vast majority of group studies measuring some type of group performance suggests
that groups are forming irrational decisions and do not perform as well as they could. The
concept of bounded rationality promises to broaden our view on process losses. The bounded-
rationality perspective suggests that at least some failures and process losses in groups that are
described in the literature may be limited to information environments that have been used in
laboratory experiments using atypical tasks. Some process losses observed in laboratory
experiments may result from otherwise adaptive behaviors in information environments that
groups typically encounter.
To explore if process losses prevail in groups when groups are exposed to environments
to which they adapted, a study employing a bounded-rationality perspective would ideally try to
answer the following three intertwined questions: 1) The environment question: What are the
characteristics of the decision task and the social and non-social environments in which groups
typically form these decisions? 2) The strategy question: Which strategies should groups use to
form decisions in this environment (prescriptive part) and which strategies do groups use to form
decisions (descriptive part)? 3) The adaptivity question: Do the decision strategies that groups
select and use match the structure of their social and non-social environments?
Communication plays a central role in each of the three questions. For example, in terms
of the information environment, the bounded rationality of groups depends on whether group
members exchange information about a task before the group deliberation process and to what
extent group members have shared mental models about the distribution of expertise, skills, and
preferences in their group. In terms of the decision strategies, communication plays a central role
as the choice of a decision strategy and the implementation of decision strategies are often based
on group interaction and discussions. Similarly, addressing the adaptivity question typically
requires a measurement of communication-related group constructs and group discussions.
Answering the three questions can help evaluate process losses in groups as respective studies
promise to provide insights about the underlying group processes and to identify tasks and
environments in which the processes that are used by groups are functional. The goal is not to
attest that groups are always rational; rather, the goal consists in understanding if and when the
strategies that groups use are adaptive in that they work well in environments that groups
typically and frequently encounter.
To be able to answer these questions, studies should embrace the development of viable
models of information processing in groups and an analysis of environments that can inform the
selection and specification of the used tasks. In the following, three signature characteristics are
highlighted that should be embraced by research that subscribes to a bounded-rationality
perspective: The development and test of process models; the analysis and description of the
ecological and social environments of groups; and the development of representative designs in
the study of groups.
Modeling individual groups: Process models vs. as-if models
The study of group communication and decision making from a bounded rationality
perspective aims to understand group behavior as the result of an adaptation process. Group
adaptivity refers to the match of the decision strategies that are employed by groups and the
structure of information in the environment. Adaptiveness has been described as a relevant
component of effective teamwork in group research before (e.g., see Kozlowski, 1998). The
ability to select and change strategies based on information in the environment has been
identified as an important skill in team decision making because team members must modify or
replace routine strategies when they detect that the characteristics of the environment and task
change (Reimer, Bornstein, & Opwis, 2005; Salas, Sims, & Burke, 2005). To be adaptive, teams
have to be able to focus their attention on relevant information to accurately understand the
situation and achieve a shared team situation model (Kaemmer et al., 2014; Kozlowski, 1998).
The notion of bounded rationality suggests that rather than an all-purpose tool, deciders have
access to an adaptive toolbox of decision strategies. It is important to describe viable strategies as
potential models of behavior and to study how deciders select the strategies they use and to what
extent they are able to adapt their strategies to the requirements of their decision environment.
Many group decision-tasks used in the literature can be represented in the form of the
information-processing cube displayed in Figure 1 (also see Adamowicz et al., 2005; Reimer &
The information-processing cube has three dimensions: the members of the group, the
choice alternatives, and the cues by which the alternatives are described. Consider a situation in
which a group that is composed of k members has to choose among i alternatives that are
described by j cues. The respective information-processing cube is composed of k x i x j smaller
cubes. Each of these smaller cubes refers to the knowledge a certain member has about a certain
Figure 1. The Information-Processing Cube
choice alternative on a certain cue. For example, group members may belong to a committee that
has to choose a startup-company for investment on behalf of their company (see Banerji &
Reimer, 2019). Each member has some knowledge about a set of startup companies. One group
member may know that the founders of one startup company are well connected, whereas
another group member may know which of the startup companies has the greatest experience in
the respective market. In short, the cube represents information the group has on the decision
task and how this information is distributed among its members. From a formal perspective, a
group decision rule can be defined as a mathematical function that maps such an information
cube into a single group decision (see Adamowicz et al., 2005; Reimer & Hoffrage, 2012).
However, not every logically possible aggregation rule is psychologically plausible.
In the group literature, two types of group decision mechanisms have been distinguished
that aggregate across the cube’s dimensions in different orders. Social combination rules such as
the majority rule assume that each group member first aggregates across the cues and alternatives
to form an individual decision. In a second step, the group aggregates across the preferences or
opinions of the individual members to form a group decision. Conversely, social communication
rules capture the idea that the members of a group may pool their knowledge on the decision
alternatives. For example, group members may first all aggregate their knowledge about each
candidate and then collectively choose the one with the best overall evaluation. A group may
also compare the alternatives cue-wise by first communicating to reach a consensus on which the
most important cues are and choosing the alternative that scores highest on the most important
cues (Reimer & Hoffrage, 2005). The representation of the cube acknowledges that group
discussions may alter the choice set (the set of alternatives), the cues that are considered, and the
group members’ knowledge about individual cue values as well as the decision strategies that are
employed by groups.
What do we know about the decision strategies that groups employ? Group research has
mainly studied social combination rules (such as the majority rule), but hardly any studies
described a social communication rule. Group research provides extensive support for as-if
models of group-decision making but only limited insight and support for potential process
models. As-if models describe a rule that yields a certain outcome; however, as-if models do not
claim to provide a viable description of an actual process. For example, the majority rule is mute
about the actual process that would describe how a majority rule is implemented in a group.
Conversely, process models describe a decision process. For example, voting would be an
example of a process model.
Group research has a long tradition in describing as-if models of decision making. Most
prominently, group researchers have developed, described, and tested several social decision
schemes that describe how groups can form a joint decision. The social-decision scheme
approach (Davis, 1973) proposes that a group’s collective decision can be predicted in
consideration of the distribution of members’ pre-discussion preferences and a decision rule such
as majority, truth-wins, proportionality, and equiprobability schemes. Some common social
decision schemes include averaging members’ estimations, voting for the majority’s preferences,
reaching consensus, and delegating an authority individual or subgroup (Hastie & Kameda,
Davis’ approach has been applied in various contexts and has served as a basis for many
group studies, which expanded the social decision schemes to, for example, expert-weighted
schemes (Bonner, Baumann, & Dalal, 2002), hidden-profile tasks (Stasser & Titus, 1985), and
collective induction theory (Laughlin & Ellis, 1986).
Arguably, the majority rule is the most prominent decision scheme: It describes group
decisions well in many situations, and it is also considered effective as it often yields accurate
decisions (Hastie & Kameda, 2005). People often pick the alternative favored by most group
members even if it is the wrong alternative (Ladbury & Hinsz, 2009). Typically, models that add
aspects of group discussions as predictors are not better able to predict group decisions than
models that are merely based on the distribution of preferences in a group and the use of a social
combination rule, such as the majority scheme. However, a desideratum of group research
consists in the lack of appropriate process models as the majority rule is almost exclusively
studied as an as-if model. Specifically, it is not clear how groups implement the majority rule
while deliberating. It is a promising working hypothesis to assume that group communication
and group discussions play a central role in the implementation of the majority rule.
Many potential processes would allow groups to implement a majority rule and
alternative rules that yield the same decisions. One possible process model would be voting.
However, groups only rarely engage in formal voting unless they are explicitly asked to do so. In
studies involving several hundreds of group decisions including hidden-profile tasks and other
choice tasks that were conducted by the authors of this commentary, groups explicitly engaged in
a voting process in less than one percent (Reimer et al., 2007; Reimer & Katsikopoulos, 2004;
Reimer et al., 2010). Alternative process models for implementing a majority rule include a
process by which individual group members express their preference for a specific choice early
in the group deliberation. Nonverbal signals such as nodding, and the lack of disagreement can
serve the function of communicating agreement. Another plausible mechanism consists in the
imitation of group members. Moreover, group members may discuss individual choice
alternatives until they come to a consensus. Future research may describe and test specific
process models used by groups to form a joint group decision.
When groups do not go with the majority, they follow at times the preference of one
group member. This may, for example, be the most senior or experienced member. The truth-win
principle is another decision scheme that can be implemented on the basis of several processes.
Laughlin and his collaborators developed a research program that identified conditions under
which groups select correct answers. Their research program identified the demonstrability of the
correct solution as a key variable that affects whether groups form a correct decision in situations
in which the majority prefers a wrong choice (see Laughlin & Ellis; 1986). It would be
worthwhile to develop and test process models that build upon the concept of demonstrability.
Developing process models of group decision-making that include a viable mechanism of how
groups form a decision is important for several reasons: It is a prerequisite to evaluate the
bounded rationality of groups as it provides insight into how groups form their decisions.
Moreover, the formulation and test of process models is also important from a methodological
perspective, as different decision schemes often yield identical decisions. For example, in
situations in which the majority of a group prefers the correct answer in a multiple-choice
situation, the majority and truth-wins rules yield identical choices. Specifying process models
will provide opportunities to disentangle several possible decision strategies. In this context, it is
important to see that models of bounded rationality provide models for individual groups. Models
of decision making are ideally based on the observation of a series of many decisions (e.g., see
Reimer & Katsikopoulos, 2004, as an example). In this sense, studies of bounded rationality
provide a methodology to conduct quantitative case studies of individual groups as well as
comparisons of groups of groups once each group is described by a decision model (e.g., see
Kaemmer et al., 2014, for an example).
Analysis and description of the environment
Beyond empirical models of decision making, studying the bounded rationality of groups
also requires a systematic analysis of the environment. For Simon (1956), the environment
includes all characteristics of the decision-making task and situation outside of a decider’s
cognition that are relevant for a decider. Common characteristics of environments that have been
studied for individuals refer to the structure of information such as the similarity of choice
alternatives and the similarity of the attributes that describe the choice alternatives (Gigerenzer &
Gaissmaier, 2011). In the context of groups and teams, the environment also includes group
characteristics, such as the distribution of knowledge about the choice alternatives (who knows
what?) and the distribution of preferences (who prefers which alternative?). Describing the
environment is important for methodological reasons: It is important as a systematic analysis of
the environment enables researchers to develop a representative design by guiding the selection
of decision tasks; and it is important to be able to evaluate the bounded rationality of the decision
processes that are used by groups and to provide a prescriptive model of decision making within
the bounds of a decider.
There is a long tradition in group communication scholarship to describe and reflect upon
characteristics of the task that groups face, which is one important dimension of the environment
(e.g., see McGrath’s (1984) task circumplex). Analyses of environments in the spirit of bounded
rationality go beyond a mere task analysis. Going back to the information-processing cube
presented in Figure 1, to understand which decision strategies are useful in a given situation may
very much depend on the similarity of the members of the group, the choice alternatives, and the
cues that are used to describe the alternatives. For example, in an environment in which cues are
highly correlated, it does typically not pay off to discuss and integrate a large amount of cue
information, but simple heuristics perform in such an environment just as well (see Reimer &
Hoffrage, 2012; Todd et al., 2012). Are groups better off using a majority rule or should they
follow their most experienced member?
The answer to this question depends on the structure of the environment. Reimer and
Hoffrage (2012) described several formal similarities between strategies of individual deciders
and social combination rules that allow extrapolating some of the lessons from the bounded
rationality of decision strategies for individuals to the bounded rationality of social combination
rules. For instance, in a situation in which group members vary greatly with respect to expertise,
knowledge, or decision accuracy, adopting the choice of the best member pays off (also see
Luan, Katsikopoulos, & Reimer, 2012). Conversely, in a situation in which members have by
and large the same level of expertise, the majority rule may yield better decisions than the best
member rule. Finally, in a situation in which all members have very high expertise, a group
would easily reach unanimity, and accuracy would be high irrespective of which social
combination rule the group uses. Therefore, it may be better to save resources and ask any
individual to decide on this issue.
At this point, we do not have much empirical knowledge about the distribution of
expertise and other important characteristics of groups outside of controlled laboratory studies.
Thus, a methodological quest for group communication research consists in systematic
descriptions of groups and their tasks in various environments. How many decisions do groups
typically make? How large are groups? Among how many choice alternatives do they choose?
How is the expertise of members and other important individual characteristics distributed in
groups? Having a broad empirical basis to answer these questions would facilitate analyses of
group environments and contribute to the development of representative designs that preserve
central properties of environments that groups typically encounter in empirical group research.
The bounded-rationality perspective suggests that not only characteristics of the task
(e.g., McGrath, 1984; Davis, 1973) but also characteristics of the information environment
influence which decision strategies groups may use and how well the used strategies perform.
Despite the insight that the study of a group’s information and social environments is necessary
to understand and evaluate group behavior, few studies have taken this quest seriously. Careful
analyses of the decision tasks that have been used by researchers studying the heuristics and
biases in individuals revealed that research on heuristics and biases itself is biased (Gigerenzer,
2018; Gigerenzer & Gaissmaier, 2011). It can be suspected that at least some studies on process
losses in groups can be partially attributed to the use of atypical and biased decision tasks and
environments. For example, an analysis of the information used in research on hidden profiles
revealed that studies on hidden profiles utilized highly atypical information distributions that
arguably prevent groups from using an effective strategy (Reimer, Barber, & Dolick, 2020;
Reimer, Reimer, & Hinsz, 2010). To evaluate the hidden-profile effect, it would be worthwhile
to understand how often groups face hidden-profile tasks. It is obvious that groups never
encounter one of the environments used in research on hidden profiles as these environments do
not allow groups to systematically compare choice alternatives on common characteristics
(Reimer et al., 2020; for a hidden-profile task including common characteristics, see Fraidin,
2004; Reimer et al., 2010). We also know that the chance of the occurrence of a hidden profile
depends on the distribution of cue validities in an environment (Reimer & Hoffrage, 2012).
However, we do not have systematic data and insights about the prevalence and characteristics of
hidden profiles that groups face outside of laboratories. These data would help understand
whether and how often natural groups encounter hidden profiles and how they could be solved.
When provided information that can be used to compare alternatives, groups can solve hidden
profile tasks under certain conditions in the laboratory (Reimer, Reimer, & Hinsz, 2010).
Studies that focus on bounded rationality have the goal to explore how simple mental
mechanisms and group processes can exploit the structure of the environment to yield adaptive
behavior. Box 1 displays typical steps of a study that subscribes to a bounded rationality
approach. The development of representative designs began with Brunswik’s (1956; see Dhami,
Hertwig, & Hoffrage, 2004) ambition for an alternative to systematic design that can overcome
the latter’s weakness in external validity. Systematic designs aim to control extraneous variables
to establish strong internal validity. Brunswik argued that generalizability is often limited in
factorial design, a variant of systematic design, due to the artificial, unrealistic combinations of
variables. Moreover, stripping tasks of the systematic relationship among variables can also
impair the internal validity of studies.
Brunswik (1956) claimed that systematic design often yields results that distort the
ecological functioning of the observed participants. Brunswik (1956) criticized the double
standard in generalization practice in psychology and stressed the need to carefully consider the
environment when conducting studies. The double standard is based on the fact that sampling is
almost exclusively discussed in terms of the selection of participants but is hardly ever discussed
in terms of the selection of stimuli and characteristics of the tasks that are used in research. This
critique also applies to the study of groups.
Studying the Bounded Rationality of Decision-Making Groups: Research Steps
• Choose Decision Tasks
Identify relevant decision tasks (e.g., decisions that groups face regularly;
consequential decisions; decisions the studied groups care about; theoretically
• Analysis of Decision and Communication Environment
Analyze the structure of the decision environment including characteristics of the
choice set (e.g., inter-cue correlation; similarity of choice alternatives; validities of
cues), characteristics of the decision situation (e.g., time constraints, access to
information), and the typical composition and structure of groups that face the
described decision problems (e.g., group size, distribution of expertise)
• Development of Process Models
Propose process models including simple heuristics and complex decision strategies
(e.g., combination-based and communication-based strategies; strategies integrating
cues that have been described as relevant in the literature; extensions of strategies that
are used by individuals)
• Simulation Studies
Use simulations to see if the strategies can work (e.g., systematically vary parameters
such as the validities of cues and the length of group discussions; simulations should
be based upon the identified characteristics of the decision environment)
• Systematic Comparison of Results and Specification of Boundary Conditions
Use systematic analyses to find out under which conditions strategies provide accurate
outcomes (e.g., systematically compare and classify the strategies based on their
accuracy across various environmental characteristics; describe strategies in terms of
their ecological rationality)
• Empirical Study Using Interacting Groups: Representative Design
Set up studies with interacting groups to test experimentally/empirically for evidence
that the strategies really are at work (e.g., select the decision characteristics that are
most common in the environment; ask a number of groups to form a series of choices
and model each individual group)
An alternative to systematic design is representative design. Representative design can be
achieved, most preferably, by random sampling of stimuli from a specified reference class to a
population, with each stimulus having an equal probability of being selected. As true random
sampling is often difficult to achieve in practice, Brunswik (1956) recommended using mixed
designs involving components of systematic and representative designs. Studies that subscribe to
a bounded rationality perspective try to avoid using artificial, orthogonal designs that distort
important characteristics of the decision environments (see Dhami et al. 2004). The concept of
representative design is based on the conviction that human behavior can only be studied in
situations that represent and retain key characteristics of the task and environment that deciders
typically encounter. Behaviors may look irrational if actors are confronted with situations that
are stripped of the characteristics of the environment to which strategies were adapted. The lack
of representative designs in group research may have produced a skewed view and
overrepresentation and overestimation of process losses in empirical group studies.
The commentary outlined methodological considerations that follow from studying
groups from a bounded-rationality perspective. The bounded rationality perspective offers a
novel meta-theoretical lens to the study of group communication. More knowledge is needed
about the information environments and social environments that groups encounter and more
process models of group-decision making are needed. This perspective offers untapped
The last twenty years have seen a number of significant advancements in group research
methods. When furthering these models, it is worth considering a bounded-rationality
perspective and asking the following three basic questions: (1) What are viable process models
that may describe the observed group behavior and how can groups be modeled? (2) What are
the relevant characteristics of the decision and communication environment, including
characteristics of the task and characteristics of groups that typically face the respective tasks?
(3) Can group behavior be understood as an adaptation process?
As the bounded-rationality perspective teaches us, these questions are intertwined as
adaptation can be best studied by looking at the match (or mismatch) of the strategies used and
the specific characteristics of the environment. For example, is it wise for groups to follow the
most experienced members in their group or use a communication-based decision strategy or use
voting and go with a majority? The answer to this question depends on several characteristics of
the environments in which groups form their decisions including the following characteristics:
The validity and distribution of cue validities, the extent to which valid information is shared
among group members, the accuracy of judgments of the most experienced member relative to
the accuracies of less experienced members, and the shape of the distribution of expertise in a
group (i.e., whether group members greatly vary in their level of expertise or not). At this point,
we have very little descriptive empirical knowledge about the frequencies and distributions of
these parameters in everyday groups and teams. The bounded-rationality perspective does not
only provide guidance in the development of theories but may also inspire methodological
innovations to explore and test assumptions about group communication.
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