An integrative cognitive-behavioural framework for predicting collective intelligence in small teams
Leaders’ capability to empower their employees to form small intelligent teams will profoundly impact the competitiveness of their organisations, considering that unrelenting disruption and fierce competition are the norms in today’s business landscape. In part, owing to this reason, the study of collective intelligence (CI) has emerged as a notable interdisciplinary body of knowledge in recent years. Scholars have regarded CI as the socio-psychological concept that accounts for how team members can derive superior ideas leading to higher performance when working together as collectives instead of as individuals. The study of CI in adults is relatively new ground for management science and various research gaps persist. Not only does a well-validated CI predicting framework not exist, many CI studies were not carried out in settings that closely resemble the real-life organisational context. Some researchers even contest the legitimacy and the existence of CI. To study CI in small teams can be challenging. One of the pertinent challenges is that factors attributing towards the development of individual adults’ intelligence are not well-understood. Newly emerged studies have further highlighted the poor correlation between scores generated from widely-adopted intelligent quotients (IQ) tests and adults’ intelligence. Other studies have asserted that one cannot simply assign adults’ IQ as the results of their biological attributes and further advocate that it is more accurate to study what the cognitive-behaviours are that influence the intelligence of adults in the day-to-day context. In a similar trend of logic, CI researchers have greatly accentuated that an integrative cognitive-behavioural framework that can predict the CI of the small teams is well-needed but has not yet been established. Taking these scholarly recommendations as the basis for the research design, this study regards CI as an emergent asset that arises from the cognitive-behaviours between team members during the problem-solving and decision-making processes. This study assessed the causal relations between twenty hypotheses of three cognitive-behavioural clusters, viz. resource acquisition and utilisation (RAU), strategic thinking (ST) and team members exchange (TMX), and the CI of the Action Learning Project (ALP) teams based on the outcomes of ALP competitions. The lack of academic consensus on how these twenty cognitive-behaviours impact the CI of small teams provides added novelty to this research. Considering that ALP teams are subjected to an environment that shares a fair amount of similarities with the real-life corporate scenarios but with less interference by other complex issues, the empirical findings allow researchers to further their scholarly knowledge, practitioners to design better ALP content and leaders to empower their teams. A questionnaire was developed and tested before inviting research participants to rate their own cognitive-behaviours as individuals and concurrently to assess the same cognitive-behaviours of their teams as collectives. Seeing that CI studies commonly rely on participants’ self-reporting data about the perceptions on their own cognitive-behaviours only but hardly having been probed and compared against the outcome of the participants’ perceptions of their teams as collective, contrasting two surveying approaches allow this study to conclude which approach is more appropriate for CI related studies. The responses of 406 delegates from 12 programmes were deemed fit for use, and the datasets were subjected to various statistical calculations. The findings revealed that the two datasets obtained from the two surveying approaches produced two slightly different structural path models after they were subjected to both descriptive and inferential statistic techniques. The hypotheses were reassigned into different factor dimensionalities, and subsequently, the partial least squares structural equation modelling calculations were applied to these two models. The statistical results indicated that the H-null for one of the 20 hypotheses must be rejected. An explanation was offered. Subsequently, the factors accepted were ranked according to the degree of potential impact on the overall CI of the ALP teams. The plausible rationales and the implications of this ranking are discussed. In addition, it was found that the datasets obtained from the “Rate Team” surveying approach produced a slightly better CI predictability than the ones obtained from the “Rate Self” surveying approach. The suitability of the surveying approach for CI related study is then discussed. Despite the differences between these two structural path models being marginal, this study observed a profound contrast of the key insights of each model. For the model generated from “Rate Self” surveying approach, it underscores the importance of the RAU cognitive-behaviours. Whereas the model generated from “Rate Self” surveying approach advocates that small teams must pay equal emphasis to all three types of cognitive-behaviours (RAU, ST and TMX) in order to boost overall CI of the ALP teams. The findings challenge the popular management philosophy of “culture eats strategy for breakfast”. Instead, the outcome of the study draws attention to the equal importance of gathering and utilising resources, thinking strategically and harnessing helpful styles of interaction among team members. The limitations and contributions were discussed. Recommendations for future studies are also proposed based on the findings uncovered.
A thesis submitted in fulfilment of the requirement for the degree Doctor of Philosophy to the Faculty of Commerce, Law and Management, The Graduate School of Business Administration, University of the Witwatersrand, Johannesburg, 2020
Collective intelligence, Team innovation, Strategic thinking