1 Introduction

In recent years, experimental economics has seen a rise in the collection and analysis of data on choice-processes as diverse as team chat, brain activity, eye movements, response times and many others (see Cooper et al., Reference Cooper, Krajbich and Noussair2019, introducing a special issue on choice-process data in experimental economics). Depending on the intrusiveness of the method of data collection, these methods are at risk of changing subjects’ behavior by means of changing the underlying reasoning which is meant to be uncovered.Footnote ¹

In this study, we want to understand whether the collection of communication data via team chats influences individuals’ reasoning and behavior as they enter the team deliberation, even before hearing others’ arguments. Possible channels could include an altered sense of responsibility due to the presence of team partners (aspect 1), anxiety or encouragement due to the exposure of own suggestions and arguments to anonymous strangers (aspects 2–3), or an increased reflection of own arguments due to their verbalization (aspect 3). Pioneered by Cooper and Kagel (Reference Cooper and Kagel2003, Reference Cooper and Kagel2005), team communication is used increasingly as a means to understand both team and individual choice-processes (Kocher & Sutter, Reference Kocher and Sutter2005; Goeree & Yariv, Reference Goeree and Yariv2011; Burchardi & Penczynski, Reference Burchardi and Penczynski2014; Kagel & McGee, Reference Kagel and McGee2016; Penczynski, Reference Penczynski2016a; Sitzia & Zheng, Reference Sitzia and Zheng2019; Cooper & Kagel, Reference Cooper and Kagel2022). It is therefore important to know whether this method is capturing the underlying individual reasoning in an unbiased fashion.

Burchardi and Penczynski (Reference Burchardi and Penczynski2014) introduce a communication protocol for teams of 2, in which partners simultaneously send a suggested decision to each other, accompanied by a supporting written message. After viewing their partner’s suggestion and message, both make an individual final decision and one of the decisions is randomly implemented as the team’s action. Here, in four between-subject treatments involving variations of this intra-team communication protocol, we explore three aspects of team communication protocols separately: (1) belonging to a team, (2) actively suggesting an action to the team partner, and (3) justifying the suggestion in a written text to the team partner. This separation serves two purposes. First, it allows us to identify which element of team communication causes changes in suggestions, if any. Second, other communication protocols or choice-process methods which only feature a subset of the three aspects will be informed by our results. For example, the verbal ‘thinking aloud’ protocol investigated by Capra (Reference Capra2019) only features the third aspect of verbalization of reasoning and neither the team nor the suggestion aspects. Some protocols involve action suggestions but not free-form text communication (He & Villeval, Reference He and Villeval2017; Ertac & Gurdal, Reference Ertac and Gurdal2019).

For our purposes, we chose three tasks of different choice environments whose decisions informatively reflect underlying reasoning. Task 1 is an individual choice problem of guessing five cards from a deck of 100 colored cards (Rubinstein, Reference Rubinstein2002). Task 2 is the Colonel Blotto game, a resource allocation game with a large strategy space (Arad & Rubinstein, Reference Arad and Rubinstein2012). Task 3 is a two-player common-value first-price auction as adapted from Kagel and Levin (Reference Kagel and Levin1986) by Koch and Penczynski (Reference Koch and Penczynski2018).

Across these three different tasks, we find no systematic evidence of altered individual suggestions due to aspects (1)–(3) of team communication. This result implies that inferring the nature of individual reasoning from this type of team communication is valid and justifies the use of a team setup to explore both individuals’ and teams’ reasoning.

Our results on aspect 3 are in line with Capra (Reference Capra2019) finding no systematic evidence of any influence from verbal ‘thinking aloud’ reports. While our paper focuses on whether collecting communication data influences individual reasoning, it also relates to the experimental literature on team decision making, which attempts to reveal and understand the differences between individual behavior and team behavior in various contexts (see Kugler et al. (Reference Kugler, Kausel and Kocher2012) and Charness and Sutter (Reference Charness and Sutter2012) for reviews on teams’ strategic behavior). Most of the studies on teams compare individuals’ and teams’ behavior given a particular form of communication, usually free-form chat communication (e.g., Cooper & Kagel, Reference Cooper and Kagel2005; Luhan et al., Reference Luhan, Kocher and Sutter2009),Footnote ² but also face to face communication (e.g., Bornstein & Yaniv, Reference Bornstein and Yaniv1998; Kocher & Sutter Reference Kocher and Sutter2005),Footnote ³ and limited communication, where only a strategy proposal is sent (He & Villeval, Reference He and Villeval2017).

Several studies have attempted to understand the influence of different forms of communication within teams: full communication compared to no communication (e.g., Sutter and Strassmair, Reference Sutter and Strassmair2009; Cason et al., Reference Cason, Sheremeta and Zhang2012),Footnote ⁴ face to face communication compared to chat (Meub and Proeger, Reference Meub and Proeger2017; Christens et al., Reference Christens, Dannenberg and Sachs2019), structured compared to unstructured discussion (Park & DeShon, Reference Park and DeShon2018), and one-way messages, sent by some members, compared to no communication (Cooper & Kagel, Reference Cooper and Kagel2016; Ertac & Gurdal, Reference Ertac and Gurdal2019).

We do observe systematic and significant increases in sophistication when comparing suggestions before the communication to decisions after the communication. Specifically, we show that when one member is more sophisticated than another, there is a higher likelihood that the first will persuade the latter, which explains teams’ higher sophistication and replicates results from Penczynski (Reference Penczynski2016a). Furthermore, this effect is more pronounced when communication includes a written message, rather than just a suggested decision. That is, team communication that consists of free-form messages is more effective than limited communication, where only a decision is proposed.Footnote ⁵

2 Experimental design

The experiment consists of 4 treatments, in each of which 3 tasks are presented sequentially: task 1 is an individual decision and tasks 2 and 3 are strategic games. The outcomes of the tasks are revealed only at the end of the experiment.

4 Communication and revisited decisions

The revisited decisions allow us to better understand the team decision making process (see Penczynski, Reference Penczynski2016a) and, specifically in that context, the influence of a richer communication protocol when moving from BTS to BTSM.

A first set of insights can be gained when classifying both team members’ suggested and revisited decisions into the sophistication categories introduced for each task.Footnote ¹⁴ On the basis of both team members’ suggested decisions, we define the divergence in sophistication before communication. If the sophistication is not the same, we can identify the more sophisticated team member to be the partner or the player. On the basis of each player’s two decisions (suggested and revisited), we can understand whether the player corrected the sophistication upwards, downwards or not at all.

Fig. 5 Correction in sophistication by divergence in sophistication

Figure 5 shows the correction by task, treatment and divergence. The middle of both panels shows that a similar sophistication between players predominantly leads to no correction. In BTS, having a more sophisticated partner leads often to upwards correction and being more sophisticated sometimes leads to downwards correction. Moving from BTS to BTSM increases the richness of the communication. Interestingly, this induces the two effects to change in an asymmetric fashion. The correction towards higher sophistication increases and the correction towards lower sophistication decreases. This proves the usefulness of rich communication in teams.

Table 5 shows ordered logit and OLS results of the correction in sophistication as a function of a treatment dummy BTSM, the divergence in sophistication as well as an interaction of the two. The table shows clearly and robustly that the divergence is predictive of the direction of the correction. Likewise, the richer communication in BTSM significantly strengthens the effect of positive divergence, possibly thanks to the verbal demonstration of the superior suggested strategy. However, this richness does neither influence correction for negative divergence nor for no divergence cases.

Table 5 Ologit and OLS regression results

	Task (1)		Task (2)		Task (3)
	Ologit	OLS	Ologit	OLS	Ologit	OLS
	correction	correction	correction	correction	correction	correction
BTSM	0.018	0.033	$-$ 0.037	$-$ 0.042	0.013	0.026
	(0.022)	(0.044)	(0.046)	(0.051)	(0.009)	(0.017)
Player $\underset{\mathrm{soph}}{>}$ Partner	$-$ 0.058***	$-$ 0.288***	$-$ 0.058***	$-$ 0.287***	$-$ 0.018**	$-$ 0.619***
	(0.018)	(0.070)	(0.022)	(0.054)	(0.008)	(0.072)
Partner $\underset{\mathrm{soph}}{>}$ Player	0.627***	0.542***	0.577***	0.497***	0.558***	0.483***
	(0.046)	(0.094)	(0.058)	(0.063)	(0.039)	(0.046)
BTSM $\times$	$-$ 0.013	0.048	0.038	0.115	$-$ 0.012	0.234**
Player $\underset{\mathrm{soph}}{>}$ Partner	(0.022)	(0.069)	(0.044)	(0.086)	(0.009)	(0.092)
BTSM $\times$	0.268***	0.249**	0.174***	0.179**	0.182***	0.179***
Partner $\underset{\mathrm{soph}}{>}$ Player	(0.098)	(0.106)	(0.063)	(0.061)	(0.060)	(0.053)
Constant		0.000		0.071		$-$ 0.014
		(0.053)		(0.047)		(0.014)
Observations	350	350	343	343	338	338
(Pseudo) $R^2$	0.363	0.472	0.370	0.414	0.467	0.532

The ordered logit estimates represent marginal effects on the probability that a subject’s revisited decision is more sophisticated than the individually suggested one. Robust standard errors clustered at the session-level in parentheses. Correction takes the value +1, $-1$ , 0 for upwards, downwards and no change, respectively. *p < 0.10, **p < 0.05, ***p < 0.01

Fig. 6 Correlation between words’ predictiveness of sophistication and correction

The messages from BTSM allow us to explore the mechanism behind richer communication and to relate words both to a decision’s sophistication and to the correction they cause in the team partner’s decision. According to the text analysis, sent words that predict the sophistication of the suggested decision correlate with the received words that predict a correction in the direction of the partner. Figure 6 thus illustrates how the rich communication helps to make a team’s decision more sophisticated. For example in the card task 1, the word “green” is crucial for the sophisticated strategy and comfortingly is highly predictive of both sophistication and correction (Fig. 6a). In Blotto task 2, the correlation is less pronounced, but the word “just”, for example, is highly predictive of sophistication and among the most predictive words of correction (Fig. 6b).Footnote ¹⁵ In the auction task 3, a number of very reasonable words are in the top 10 of predicting both sophistication and correction, for example, “lowest”, “profit”, “bid”, “lower” (Fig. 6c).

5 Discussion and conclusion

We presented a rigorous analysis of the effects of different team communication aspects on the sophistication in individual and strategic decision making. Rather than looking at one specific task in isolation, our strategy was to uncover team communication effects in a more systematic way, namely by identifying shared patterns that would come to light across a variety of different tasks.

Across all 3 tasks, we observed that the revisited decisions were on average statistically more sophisticated than the individually suggested ones. In line with Penczynski (Reference Penczynski2016a), this shows that the communication is effective in improving the team’s sophistication because more sophisticated decisions are identified as superior and are thus more persuasive. This effect is increasing in the richness of the communication. These results also show that our analysis is sufficiently powered to detect systematic effects between our experimental conditions.

Note that by fixing beliefs about opponents’ behavior to the individual choices from treatment B we muted the potential influence that beliefs of playing against teams rather than individuals might have on reasoning and decisions. Studies using the intra-team communication design have not suggested that the individual reasoning against teams is different from the benchmark individual-against-individual results in the respective literatures (Burchardi & Penczynski, Reference Burchardi and Penczynski2014; Penczynski, Reference Penczynski2016a, Reference Penczynskib, Reference Penczynski2017; van Elten & Penczynski, Reference van Elten and Penczynski2020). Similar to our results, these studies rather have shown systematically that the decisions after the communication are more sophisticated, suggesting that the impact of team play does not derive from holding particular beliefs about the opposing teams, but rather from the pooling of arguments by the team members.

For each of the games and dimensions we considered, we ran a whole battery of tests by comparing individual decisions in each of the four treatments against one another in an attempt to uncover significant patterns in our data. As far as subjects’ individual decisions are concerned, we found very little to no evidence of effects due to any of the treatment manipulations that we applied in any of the tasks. These findings were moreover substantiated by additional robustness checks which we referred to in the footnotes of each respective section of the analysis.

By having shown that none of the aspects of our team communication protocol (belonging to a team, suggesting an action, reflecting verbally on one’s reasoning) seems to have affected behavior, we believe that such team communication protocols are capable of generating choice-process information in a way that does not distort the choice processes that are meant to be uncovered.