In modern organizational settings, many tasks and projects are performed by teams. Due to technical developments, collaboration over spatial, temporal, and even organizational boundaries becomes normality (e.g., virtual teams; Hertel & Konradt, 2007). Although organizational psychology has focused on the facilitation of information exchange within teams (cf. Mesmer-Magnus & DeChurch, 2009), many teams report dysfunctional information exchange or information overload (IO) on account of too much and irrelevant information (cf. Eppler & Mengis, 2004). In this chapter, information overload (IO) is considered a dysfunctional team process occurring at the team level. Regarding information sharing in teams, several authors have suggested that electronic media can overload team members with information (Ellwart, Happ, Gurtner, & Rack, 2015; Miranda & Saunders, 2003). Especially simultaneity or fast and immediate answers in electronic communication settings facilitate the experience of IO (Thorngate, 1997), mainly in association with e-mails (Bawden, 2001; Speier, Valacich, & Vessey, 1999). Social media, such as Facebook or WhatsApp (which are based on pushing information), did not even exist when these early studies were conducted, and this might add to IO. Thus, IO in teams can be described on a quantitative dimension as too much information obtained and on a qualitative dimension if the information exchanged within the teams lacks novelty, is low in accuracy, is ambiguous, complex, or uncertain (cf. Evaristo, 1993).
There are manifold consequences of quantitative and qualitative IO in teams and organizations. Research discusses emotional and motivational consequences (stress, anxiety, or tiredness; Bawden & Robinson, 2009; Edmunds & Morris, 2000), as well as effects on performance and team efficiency (Ayyagari, Grover, & Purvis, 2011; Rutkowski & Saunders, 2010) which can lead to increasing organizational cost. Eppler and Mengis (2004) differentiate four main symptoms/effects of IO in their review: (1) limited information search and retrieval strategies (e.g. lower systematic search strategies, limited search directions), (2) arbitrary information analysis and organization (e.g. overlapping and inconsistent information categories, highly selective information disregard), (3) suboptimal decisions (e.g. loss of control over information, higher time requirements for information handling, lower decision accuracy) and (4) strenuous personal situations (e.g. inefficient work, demotivation, lowered job satisfaction, potential paralysis and delay of decisions). Especially in team decision making, efficiency decreases as the amount of information increases (e.g., Bawden, 2001). In their explorative interview study analyzing the main barriers and enablers of organizational virtual teamwork in multinational organizations, Rack, Tschaut, Giesser, and Clases (2011) found that virtual teams often exchange (a) too much information in an (b) unfiltered and (c) inaccurate way. Subsequently, IO led to detrimental effects, like delays in decision making and the subjective experience of strain.
How can teams successfully adapt to IO situations, avoid IO, and support functional information exchange? Most research on the causes of IO has focused on individual factors such as the handling of electronic correspondence and on task-related factors such as time, organization, or technical support (Eppler & Mengis, 2004). In a review of the relevant literature, Eppler and Mengis distinguished five antecedents that cause experience of IO: (1) individual factors (e.g., attitudes, motivation, age, experience), (2) information characteristics (e.g., quantity, uncertainty, and complexity of information), (3) task and process parameters (e.g., time pressure, interruptions, and interdependencies), (4) information technologies (e.g., push systems and access speed) as well as (5) organizational and team structural variables (e.g., group heterogeneity). Thus, it becomes apparent that most of these focus on structure, task, or technical variables. However, organizational team research underlines the importance of team cognitions on functional and dysfunctional processes in teams (DeChurch & Mesmer-Magnus, 2010a; Ellwart, 2011).
Thus, this chapter will introduce emergent team knowledge structures (team cognition) within teams as relevant mediators for explaining IO and adapting team processes to a more functional information exchange. Two concepts of shared and distributed team cognition are introduced: (1) Team Mental Models (TMM) and (2) Transactive Memory Systems (TMS) (see Figure 1). Empirical data will show the importance of both shared and distributed cognitions for effective information exchange and, in turn, for less IO. In the second section of this chapter, the processes and support tools for IO adaptation that have been tested in research and practice are introduced. It will become apparent that teams need a third type of shared team cognition, so-called Team Situation Awareness (TSA) to foster the recognition of IO in the team. Stepwise adaptation will help the team members to plan and execute efficient communication strategies by synchronizing and updating TMM and TMS. At the end, adaptation will guide teams in future interactions in order to reduce quantitative and qualitative IO.