Cognitive Diversity Research Articles

Strategic Diversity and Organisational Resilience among Small and Medium-sized Enterprises in Lagos State

This study delves into the relationship between strategic diversity and organisational resilience among Small and Medium-sized Enterprises (SMEs) operating in Lagos State, Nigeria. SMEs are pivotal drivers of economic development, particularly in regions like Lagos State, where they contribute significantly to economic growth and employment opportunities. Resilience, the ability to weather disruptions and adapt swiftly, is paramount for SMEs facing a dynamic and often challenging business environment. Strategic diversity, encompassing various approaches and tactics, emerges as a crucial factor influencing resilience. Despite the importance of this relationship, there is a notable research gap regarding Lagos State SMEs. This study, based on a sample of 500 individuals from diverse SME sectors, employs a structured questionnaire to gather primary data. Findings reveal a robust and positive correlation between strategic diversity and organisational resilience, signifying the significance of strategic planning for SMEs. This aligns with previous research emphasising the role of long-term strategic diversity planning in achieving SME growth and success. The study underscores the importance of effective diversity management, including demographic, cultural, educational, functional, cognitive, experience, and innovation diversity. Overall, it provides valuable insights for policymakers, entrepreneurs, and stakeholders aiming to enhance SMEs resilience, thus driving economic growth and employment opportunities in Lagos State.

A Cognitive Semiotic Interpretation of Chinese Culture Through Digitalized Reading

Cultural differences and geopolitical disputes severely impede the globalization process. As a method of eliminating cross-cultural misunderstandings and fostering mutual respect, it is crucial to increase cross-cultural awareness through cross-cultural education to support the world's peaceful and healthy development. This article investigates, from the perspective of cognitive semiotics, how the integration of digitization and language learning through reading can provide foreign language learners with a more immersive and stimulating learning experience. Questionnaires and interviews demonstrate that digital reading has exerted more significant learning effects on cross-cultural education than traditional paper reading. Digital reading reflects cognitive communication, cognitive subjectivity, and cognitive diversity more accurately. The integration of digital reading and cross-cultural education makes language learning more accessible and effective and can encourage students to grasp the target language while simultaneously promoting Chinese culture.

Modeling complex problems by harnessing the collective intelligence of local experts: New approaches in fuzzy cognitive mapping

Developing system understanding and testing interventions are critical steps to addressing wicked problems. Fuzzy cognitive mapping (FCM) can be a useful participatory modeling tool that enables aggregation of individual perspectives to build system models that represent groups’ collective intelligence (CI). However, current FCM aggregation methodologies for creating CI models have rarely been tested and compared. We conducted 51 FCM interviews with local experts in the Flint, MI food system to map their mental models about how different food system sectors influenced desirable outcomes. Using four differing aggregation techniques, based on experts’ identity diversity and cognitive diversity, we generated four CI models. The models were compared based on their similarity to real-world complex systems using performance metrics like network structure, micro-motifs, cognitive distance, and scenario outcomes. We found that using cognitive diversity to group individuals was better suited for modeling systems with diverse holders of knowledge.

Epistemic Inclusion as the Key to Benefiting from Cognitive Diversity in Science

ABSTRACT Throughout scientific history, there have been cases of mainstream science dismissing novel ideas of less prominent researchers. Nowadays, many researchers with different social and academic backgrounds, origins and gender identities work together on topics of crucial importance. Still, it is questionable whether the privileged groups consider the views of underprivileged colleagues with sufficient attention. To profit from the diversity of thoughts, the scientific community first has to be open to minority viewpoints and epistemically include them in mainstream research. Moreover, the idea of inclusive science poses stronger requirements than the paradigm of open science. We argue that the concept of integration of different opinions is insufficient because the process of integration assumes adjusting oneself to the majority view and fitting into the dominant paradigm while contributing only with smaller amendments. Epistemic inclusion, on the other hand, means dynamically changing the research paradigm during the interaction with diverse methods and hypotheses. The process of inclusion preserves marginalized views and increases epistemic justice.

Measuring board diversity: A systematic literature review of data sources, constructs, pitfalls, and suggestions for future research

AbstractThe purpose of this systematic literature review is to provide a comprehensive overview of the methods used to measure board diversity. We develop a framework to structure empirical studies and develop an agenda for future research. We selected 61 empirical articles from an initial sample of 1035. This study discusses the different data collection methods. We group director and board attributes into the constructs of structural, demographic, and cognitive diversity. We identify four different approaches to combining and measuring diversity: non‐index, single‐index, cross‐indices, and inter‐indices. We find that measuring board diversity requires a mixture of archival and primary research, as well as various methods such as applying indices, constructing heterogeneity scores, and using machine learning approaches to infer directors' attributes. We contribute to research by providing a framework that structures measuring techniques for board diversity, a future research agenda, and insights on potential window‐dressing.

Exploring the theoretical and practical implications of eigenbehavior at the intersection of second-order cybernetics and ecosystem management

PurposeIn this conceptual paper the authors aim to discuss the implications of a second-order cybernetic approach and eigenbehavior in ecosystem management. The authors argue that traditional management practices rely on the agreement of stakeholders, but this approach cannot satisfy multiple-objective realities, making radical constructivism necessary.Design/methodology/approachThe authors examined this conjecture using a multi-agent simulation exercise. Agents display individual behavior consistent with the organizing principles proposed by von Foerster (eigenform and eigenbehavior), Hoffman (perception and fitness) and Maturana (domains of realization). This exercise is complemented with an ecosystem management classification exercise to show how convergence is achieved when a team of trained professionals describes entities of low versus high complexity in a spatially explicit domain.FindingsThe authors showed that eigenforms can diverge significantly depending on the complexity of the problem. The capacity of observers to stabilize an eigenform and create a common ground for understanding depends on the complexity of the problem at hand and their cognitive diversity. The authors highlighted the difficulties that arose when observation and modification through the intervention of the environment cannot be detached. The authors argue that this situation deeply permeates ecosystem resource management due to the unpredictable outcomes displayed by entities embedded into open system dynamics.Originality/valueFinally, the authors propose that the association between indication and transformation can be operationally interconnected as Eigenperception, which corresponds to a novel dynamic state bridging the gap between noise and eigenform. This concept of Eigenperception encapsulates entities that arise from eigenbehavior, encompassing observations, meanings, human transformative actions and ecological processes, all in a simultaneous manner.

A realist review of health passports for Autistic adults.

Autism is a normal part of cognitive diversity, resulting in communication and sensory processing differences, which can become disabling in a neurotypical world. Autistic people have an increased likelihood of physical and mental co-occurring conditions and die earlier than neurotypical peers. Inaccessible healthcare may contribute to this. Autism Health Passports (AHPs) are paper-based or digital tools which can be used to describe healthcare accessibility needs; they are recommended in UK clinical guidance. However, questions remained as to the theoretical underpinnings and effectiveness of AHPs. We undertook a systematic literature search identifying studies focused on AHPs for adults (aged over 16 years) from five databases. Included literature was subjected to realist evaluation. Data were extracted using a standardised form, developed by the research team, which considered research design, study quality for realist review and the Context, Mechanisms and Outcomes (CMOs) associated with each AHP tool. 162 unique records were identified, and 13 items were included in the review. Only one item was considered high quality. Contextual factors focused on the inaccessibility of healthcare to Autistic patients and staff lack of confidence and training in supporting Autistic needs. Interventions were heterogeneous, with most sources reporting few details as to how they had been developed. The most frequently included contents were communication preferences. Mechanisms were often not stated or were inferred by the reviewers and lacked specificity. Outcomes were included in four studies and were primarily focused on AHP uptake, rather than Outcomes which measured impact. There is insufficient evidence to conclude that AHPs reduce the health inequalities experienced by Autistic people. Using an AHP tool alone in a healthcare Context that does not meet Autistic needs, without the inclusion of the local Autistic community developing the tool, and a wider intervention to reduce known barriers to health inequality, may mean that AHPs do not trigger any Mechanisms, and thus cannot affect Outcomes.

Introduction to this special issue on intelligent systems for people with diverse cognitive abilities

ABSTRACT This special issue highlights state-of-the-art research in intelligent systems and technology for people with diverse abilities. To control scope, we pay particular attention to cognitive diversity, including but not limited to, neurodevelopmental disorders and autism, cognitive and learningdisabilities, and dementia. We introduce the papers in this special issue by contextualizing them according to different research areas. By curating leading-edge contributions in this area, we aim to raise awareness about research challenges and requirements inherent in the development and assessment of systems designed for these categories of users.

Cognitive Diversity or Cognitive Polarization? On Epistemic Democracy in a Post-Truth World

ABSTRACT Pessimism over a democracy’s ability to produce good outcomes is as longstanding as democracy itself. On one hand, democratic theorists consider democracy to be the only legitimate form of government on the basis that it alone promotes or safeguards intrinsic values like freedom, equality, and justice. On the other, skepticism toward the ordinary citizen’s cognitive capacities remains a perennial concern. Qualms about the epistemic value of democracy have only been made more pertinent by a fundamental problem of deep epistemic disagreement which underlies the post-truth phenomenon. I argue that the democratic theorists who have sought to defend democracy on epistemic grounds have thus far neglected such deep and intractable disagreements. Without addressing this oversight, the epistemic democrat will find that collective decision-making processes quickly become paralyzed and will not be able to yield the epistemic benefits they promise. Hence, the work for epistemic democrats is to recognize and take into account the ramifications of epistemic disagreements so as to make a stronger case for epistemic democracy.

The Social Route to Abstraction: Interaction and Diversity Enhance Performance and Transfer in a Rule-Based Categorization Task.

Capacities for abstract thinking and problem-solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in fact be contingent on human-specific modes of collaboration, dialogue, and shared attention. In an experimental study, we test the hypothesis that social interaction enhances cognitive processes of rule-induction, which in turn improves problem-solving performance. Through three sessions of increasing complexity, individuals and groups were presented with a problem-solving task requiring them to categorize a set of visual stimuli. To assess the character of participants' problem representations, after each training session, they were presented with a transfer task involving stimuli that differed in appearance, but shared relations among features with the training set. Besides, we compared participants' categorization behaviors to simulated agents relying on exemplar learning. We found that groups performed superior to individuals and agents in the training sessions and were more likely to correctly generalize their observations in the transfer phase, especially in the high complexity session, suggesting that groups more effectively induced underlying categorization rules from the stimuli than individuals and agents. Crucially, variation in performance among groups was predicted by semantic diversity in members' dialogical contributions, suggesting a link between social interaction, cognitive diversity, and abstraction.

Edge‐centric functional network reveals new spatiotemporal biomarkers of early mild cognitive impairment

AbstractMost neuroimaging studies of the pathogenesis of early mild cognitive impairment (EMCI) rely on a node‐centric network model, which only calculates correlations between brain regions. Considering the interaction of low‐order correlations between pairs of brain regions, we use an edge‐centric network model to study high‐order functional network correlations. Here, we compute edge time series (eTS) to obtain overlapping communities and study the relationship between subnetworks and communities in space. Then, based on the overlapping communities, we calculate the normalized entropy to measure the diversity of each node. Next, we compute the high‐amplitude co‐fluctuation of the eTS to explore the pattern of brain activity with temporal precision. Our results show that the normal control and EMCI patients differ in brain regions, subnetworks, and the whole brain. In particular, entropy values show a gradual decrease, and brain network co‐fluctuation increases with disease progression. Our study is the first to investigate the pathogenesis of EMCI from the perspective of spatiotemporal flexibility and cognitive diversity based on high‐order edge connectivity, further characterizing brain dynamics and providing new insights into the search for biomarkers of EMCI.

Causal maps in the analysis and unsupervised assessment of the development of expert knowledge: Quantification of the learning effects for knowledge management purposes

This study proposes an application of cognitive maps in the representation of cognitive structures of the experts and assessment of their development/modification as a result of a (computer or expert system-assisted) learning process. It strives to identify information needed for the guidance of the process of creation and management of expert knowledge by formal modeling tools. Changes in experts’ cognitive structures are assumed to stem from individual and collaborative (group-level) learning. The novel approach to assessing the outcomes of learning reflected as changes in the cognitive structures of experts or groups of experts, modeled by cognitive maps, does not assume any correct or desired outcome of the learning process to be known in advance. Instead, it identifies and analyzes the changes in (or robustness of) the constituents of the cognitive maps from different points of view and allows for quantifying and visualizing the actual effect of the learning. The proposed methodology can identify changes in cognitive diversity, causal structures in terms of causal relations and concepts, and the perceived importance of strategic issues over the learning period. It can also detect which cause–effect relationships have appeared/disappeared considering the pre-/post-mapping design. Thus, it provides an exploratory account on the changes in the cognitive structures of the expert(s) as a result of learning. The applicability of the proposed methods is illustrated in the assessment of the learning outcomes of a group of 71 graduate students who participated in an eight-week business simulation task. The results of the empirical analysis confirm the viability of the proposed methodology and indicate that the students’ understanding of the utilized concepts and associated relationships in the decision-making process improved throughout the learning activity, ultimately showing that the course learning has considerably improved students’ perception and knowledge. Based on the results, it can be concluded that the proposed approach has the potential to be effective in assessing learning outcomes in teaching–learning activities.

Cognitive Diversity Within Entrepreneurial Teams: Contingencies of Their Cost and Benefit

Cognitive Diversity Within Entrepreneurial Teams: Contingencies of Their Cost and Benefit

Complementing Diversity with Design: Cognitive Diversity, Organizational Structure, and Exploration

Complementing Diversity with Design: Cognitive Diversity, Organizational Structure, and Exploration

Cognition Diversity, Repeated Cooperation and Collective Intelligence in Dynamic Cooperative Network

Cognition Diversity, Repeated Cooperation and Collective Intelligence in Dynamic Cooperative Network

Constructing a Knowledge Graph for the Chinese Subject Based on Collective Intelligence

Knowledge graphs are a valuable tool for intelligent tutoring systems and are typically constructed with a focus on objectivity and accuracy. However, they may not effectively capture the subjectivity and complex relationships often present in the humanities. To address this issue, a dynamic visualization of subject matter knowledge graph was developed using a collective intelligence approach that integrates the individual intelligence of learners and considers cognitive diversity to construct and evolve the knowledge graph. The approach resulted in the construction of 722 knowledge associations and the evolution of 584 triples. A survey assessed the effectiveness and user-friendliness, revealing that this approach is effective, easy to use, and can improve subject matter knowledge ontology. In conclusion, combining individual and collective intelligence is a promising approach for building effective knowledge graphs in subject areas with subjectivity and complexity.

The Diversity Heuristic: How Team Demographic Composition Influences Judgments of Team Creativity

Despite mixed evidence for the relationship between demographic diversity and creativity, we propose that observers hold a lay belief that demographic diversity increases creativity and apply this lay belief in judgments about teams and their creative work. Across eight preregistered studies (n = 5,530), we find that observers judge teams diverse in terms of race and gender to be more creative than teams homogeneous in terms of race and gender, including in incentive-compatible predictions made about real teams competing in a creativity challenge. We also find that products attributed to demographically diverse teams are evaluated as more creative compared with identical products attributed to demographically homogenous teams. Mediation analyses provide evidence consistent with the notion that people perceive demographic diversity (i.e., social category differences) to be correlated with cognitive diversity (i.e., difference of perspectives), and this belief contributes to attributions of greater creativity to diverse teams and the ideas they generate. We can also turn off the perceived association between demographic diversity and creativity by directly manipulating people’s perceptions of team cognitive diversity. Furthermore, we find evidence of a curvilinear relationship between the proportion of racial minorities or women in a group and judgments of the group’s creativity. Together, our results suggest that the popular uptake of the belief that diversity boosts creativity may impact how creativity is identified in organizational contexts. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: This research was supported by funds from the School of Industrial and Labor Relations, Cornell University, and Harvard Business School, Harvard University, including a grant from the Cornell Center for Advanced Human Resource Studies. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4862 .

Social and cognitive diversity in science: introduction

Social and cognitive diversity in science: introduction

Board diversity and corporate propensity to R&D spending

Drawing on collective contributions and group performance perspectives, this paper examines the role of board diversity in firms' R&D investment decisions. Building on a fault-line argument about a team's demographic attributes, this study also decomposes the impact of demographic and cognitive diversity on R&D spending. The study sample contains UK data of non-financial companies covering the period between 2005 and 2018. We employ panel data analysis techniques and control for potential endogeneity issues through the application of the two-step system Generalised Method of Moments (GMM) estimations. The findings demonstrate a positive and significant relationship between board diversity and level of corporate R&D spending. The findings also show cognitive diversity as significantly positively associated with corporate R&D investments. Demographic diversity, however, has an insignificant relationship with corporate spending on R&D. The results further show that demographic diversity negatively moderates the relationship between cognitive diversity and spending on R&D. Our main findings document that the board's attributes as a group significantly influence decisions of strategic importance such as, investment in R&D projects. The findings on sub-dimensions of board diversity imply that as compared to demographic diversity, functional/cognitive diversity is more relevant to strategic decisions and related outcomes. The study has practical implications for shareholders in documenting the importance of board diversity, and policy implications for regulators in highlighting the separate roles of behavioural and cognitive diversity in shaping firms' strategic investment decisions.

Diverse types of expertise in facial recognition

Facial recognition errors can jeopardize national security, criminal justice, public safety and civil rights. Here, we compare the most accurate humans and facial recognition technology in a detailed lab-based evaluation and international proficiency test for forensic scientists involving 27 forensic departments from 14 countries. We find striking cognitive and perceptual diversity between naturally skilled super-recognizers, trained forensic examiners and deep neural networks, despite them achieving equivalent accuracy. Clear differences emerged in super-recognizers’ and forensic examiners’ perceptual processing, errors, and response patterns: super-recognizers were fast, biased to respond ‘same person’ and misidentified people with extreme confidence, whereas forensic examiners were slow, unbiased and strategically avoided misidentification errors. Further, these human experts and deep neural networks disagreed on the similarity of faces, pointing to differences in their representations of faces. Our findings therefore reveal multiple types of facial recognition expertise, with each type lending itself to particular facial recognition roles in operational settings. Finally, we show that harnessing the diversity between individual experts provides a robust method of maximizing facial recognition accuracy. This can be achieved either via collaboration between experts in forensic laboratories, or most promisingly, by statistical fusion of match scores provided by different types of expert.