Disequilibrium and complexity across scales: a patch-dynamics framework for organizational ecology

Based on equilibrium assumptions, traditional ecological models have been widely applied in the fields of management and organization studies. While research using these models is still ongoing, studies have nonetheless struggled with ways to address multiple levels of analysis, uncertainty, and complexity in their analyses. This paper conceptualizes the dynamic co-evolution mechanisms that operate in an ecosystem across multiple organizational scales. Specifically, informed by recent advances in modelling in biology, a general 'patch-dynamics' framework that is theoretically and methodologically able to capture disequilibrium, uncertainty, disturbances, and changes in organizational populations or ecosystems, as complex and dynamically evolving resource environments are introduced. Simulation models are built to show the patch-dynamics framework's functioning and test its robustness. The patch-dynamics framework and modelling methodology integrates equilibrium and disequilibrium perspectives, co-evolutions across multiple organization levels, uncertainties, and random disturbances into a single framework, opening new avenues for future research on topics in the field of management and organization studies, as well as on the mechanisms that shape ecosystems. Such a framework has the potential to help analyse the sustainability and healthiness of the business environment, and deserves more attention in future research on management and organization theory, particularly in the context of significant uncertainty and disturbances in business and management practice. Overall, the paper offers a distinct theoretical perspective and methodology for modelling population and ecosystem dynamics across different scales.

When Normal is Not Normal: A Theory of the Non-Linear and Discontinuous Process of Desired Change and its Managerial Implications

Desirable change may appear chaotic, slow, or not sustainable. We may expect linear, continuous change, but it eludes us. Measurement and statistical analysis about behavior change often requires data showing continuity and having normal (i.e., Gaussian) distributions. When we encounter phenomenon that does not fit this expectation, we seek to transform the data to render it compatible with our method of analysis. We move from actual behavior to perception of it through surveys or transformations of the data. We believe this ignores “naturally” occurring data and what it says. Such techniques are convenient for statistics but may hide important features of the real phenomenon. Furthermore, desired behavior change is often nonlinear with a power curve distribution of the data. We explain why this occurs. We suggest how research and practice would be improved by using theories and methods that incorporate properties of non-normal distributions and discontinuous emergence.

Foreign to all but fluent in many: The effect of multinationality on shock resilience

The sudden COVID-19 pandemic sent shockwaves through international markets. This paper studies the relation between multinationality and risk. While IB literature agrees that internationalization, in times of relative stability, increases systematic risk, we argue that internationalization also improves resilience against exogenous shocks. Leveraging the sequential COVID-waves as a unique empirical laboratory, we show that although multinationality causes liability of foreignness that increases systematic risk, it also generates an asset of multinationality that enhances shock resilience. Yet this advantage of internationalized firms gradually erodes as less internationalized firms learn about the shock and investors adapt their valuations to the post-shock reality.

Team Performance: Nature and Antecedents of Nonnormal Distributions

Team research typically assumes that team performance is normally distributed: teams cluster around average performance, performance variability is not substantial, and few teams inhabit the upper range of the distribution. Ironically, although most team research and methodological practices rely on the normality assumption, many theories actually imply nonnormality (e.g., performance spirals, team composition, team learning, punctuated equilibrium). Accordingly, we investigated the nature and antecedents of team performance distributions by relying on 274 performance distributions including 200,825 teams (e.g., sports, politics, firefighters, information technology, customer service) and more than 500,000 workers. First, regarding their overall nature, only 11% of the distributions were normal, star teams are much more prevalent than predicted by normality, the power law with an exponential cutoff is the most dominant distribution among nonnormal distributions (i.e., 73%), and incremental differentiation (i.e., differential performance trajectories across teams) is the best explanation for the emergence of these distributions. Second, this conclusion remained unchanged after examining theory-based boundary conditions (i.e., tournament versus nontournament contexts, performance as aggregation of individual-level performance versus performance as a team-level construct, performance assessed with versus without a hard left-tail zero, and more versus less sample homogeneity). Third, we used the team learning curve literature as a conceptual framework to test hypotheses and found that authority differentiation and lower temporal stability are associated with distributions with larger performance variability (i.e., a greater proportion of star teams). We discuss implications for existing theory, future research directions, and methodological practices (e.g., need to check for nonnormality, Bayesian analysis, outlier management).

Participation in wiki communities: reconsidering their statistical characterization

Peer production online communities are groups of people that collaboratively engage in the building of common resources such as wikis and open source projects. In such communities, participation is highly unequal: few people concentrate the majority of the workload, while the rest provide irregular and sporadic contributions. The distribution of participation is typically characterized as a power law distribution. However, recent statistical studies on empirical data have challenged the power law dominance in other domains. This work critically examines the assumption that the distribution of participation in wikis follows such distribution. We use statistical tools to analyse over 6,000 wikis from Wikia/Fandom, the largest wiki repository. We study the empirical distribution of each wiki comparing it with different well-known skewed distributions. The results show that the power law performs poorly, surpassed by three others with a more moderated heavy-tail behavior. In particular, the truncated power law is superior to all competing distributions, or superior to some and as good as the rest, in 99.3% of the cases. These findings have implications that can inform a better modeling of participation in peer production, and help to produce more accurate predictions of the tail behavior, which represents the activity and frequency of the core contributors. Thus, we propose to consider the truncated power law as the distribution to characterize participation distribution in wiki communities. Furthermore, the truncated power law parameters provide a meaningful interpretation to characterize the community in terms of the frequency of participation of occasional contributors and how unequal are the group of core contributors. Finally, we found a relationship between the parameters and the productivity of the community and its size. These results open research venues for the characterization of communities in wikis and in online peer production.

Discussing the Use of Complexity Theory in Engineering Management: Implications for Sustainability

What is the state-of-the-art literature regarding the adoption of the complexity theory (CT) in engineering management (EM)? What implications can be derived for future research and practices concerning sustainability issues? In this conceptual article, we critically discuss the current status of complexity research in EM. In this regard, we use IEEE Transactions on Engineering Management, because it is currently considered the leading journal in EM, and is as a reliable, heuristic proxy. From this journal, we analyze 38 representative publications on the topic published since 2000, and extrapolated through a rigorous keyword-based article search. In particular, we show that: (1) the adoption of CT has been associated with a wide range of key themes in EM, such as new product development, supply chain, and project management. (2) The adoption of CT has been witnessed in an increasing amount of publications, with a focus on conceptual modeling based on fuzzy logics, stochastic, or agent-based modeling prevailing. (3) Many key features of CT seem to be quite clearly observable in our dataset, with modeling and optimizing decision making, under uncertainty, as the dominant theme. However, only a limited number of studies appear to formally adhere to CT, to explain the different EM issues investigated. Thus, we derive various implications for EM research (concerning the research in and practice on sustainability issues).

Complexity and leadership: the case of a military organization

Purpose

This paper aims to adopt the complexity theory (CT) as a frame of reference to analyze leadership action within a military organization. Through the CT framework, it considers a military organization as a complex adaptive system (CAS), which evolves and adapts to the environment to survive, similarly to a living organism. This case study identifies complex dynamics, which are proper to CAS and it proposes avenues to harness them to increase organizational performance. Ultimately, this paper provides insights on how a CT framework may be used in describing and understanding an effective leadership action and grant it with mechanisms to measure its effectiveness.

Design/methodology/approach

This paper rests on a single case study, which examines a leadership action in a military organization. Capitalizing on privileged access to top managers of an Air Force’s Major Command, the author carried out tailored surveys aimed at identifying organizational leadership effectiveness.

Findings

Based on these data, the study provides qualitative evidence that suggests a relevant relationship between CT-based leadership action and organizational effectiveness.

Originality/value

The CT-based leadership approach challenges the paradigm of ordered, hierarchical organizational design by proposing a more flexible, networked approach in relation to organizational effectiveness. The complexity-based approach to leadership proposed in this paper suggests an adaptive leadership model that better corresponds to complex human organizations, and helps leaders identify more effective management solutions.

Evidence-based medicine-Not a panacea for the problems of a complex adaptive world

The recent sacking of Peter Gøtzsche from the Cochrane Collaboration Board raised strong responses and highlights the neglected issue about priorities-maintaining the reputation of the organization or vigorously debating the merits of scientific approaches to find answers to complex problems? The Cochrane approach hales the randomized trial (RCT) as the gold standard research approach and affirms that meta-analysis provides the ultimate proof (or platinum standard) to settle contentious issues confronting the clinician. However, most published medical research is wrong, and critics coined the acronym GIGO (garbage in, garbage out) as a meme to highlight the risks of blind faith in the hyped-up procedures of the EBM movement. This paper firstly explores the differences between the prevailing scientific method arising from the linear cause-and-effect assumption and the complex adaptive systems science methods arising from observations that most phenomena emerge from nonlinearity in networked systems. Most medical conditions are characterized by necessary features that by themselves are not sufficient to explain their nature and behaviour. Such nonlinear phenomena require modelling approaches rather than linear statistical and/or meta-analysis approaches to be understood. These considerations also highlight that research is largely stuck at the data and information levels of understanding which fails clinicians who depend on knowledge-the synthesis of information-to apply in an adaptive way in the clinical encounter. Clinicians are constantly confronted with the linked challenges of doing things right and doing the right thing for their patients. EBM and Cochrane with their restrictive approaches are the antithesis to a practice of medicine that is responsive to constantly changing patient needs. As such, the EBM/Cochrane crisis opens a window of opportunity to re-examine the nature of health, illness and disease, and the nature of health care and its systems for the benefits of its professionals and their patients. We are at the cusp of a paradigmatic shift towards an understanding a praxis of health care that takes account of its complexities.

Diverse mobile users: the development of library experts

Purpose

The purpose of this paper is to undertake a formative evaluation of growth over time that would demonstrate diverse library users’ development as they interact with mobile digital library services.

Design/methodology/approach

This paper incorporated a server log analysis to evaluate first, the location of users. To study the nature of diverse user development, users from unique locations were identified and tracked over several years. The type of growth that this paper analyzes is the development of a library user from the beginning stages of use into one who is more experienced. For the purposes of this paper, the authors define library experts as experienced library users. These are users who have come back to the library over multiple sessions of learning and branched out into multiple areas of library functionality and services.

Findings

The findings of modular mobile use over time suggest that, while over half of users only utilized one module, 39 per cent of all users accessed more than one module. This formative approach to assessing student library engagement suggests alternative metrics for assessing outreach and distance learning.

Originality/value

The underlying departure point for this study is that formative models may introduce descriptive data valuable to the learning analytics toolkit. The library research literature on learning analytics, and perhaps library service offerings that support learning, may gain additional value by attending to students’ formative development as they interact with library resources. Describing the way in which mobile app users develop can yield insights about learning over time, both on campus and at a distance.

Relativistic complexity, adaptive governance and the intelligence leadership

Abstract Recognizing the inherent strengths and weaknesses of human agents and organizations, as well as changing characteristics and behavior of the interacting agents is the key fundamental to better adaptation, leadership, governance, resilience and sustainability. In all human organizations, the agents are human beings each embedded with an intrinsic intense intelligence source that could easily transform their behavioral schemata. Thus, contradictory to the Newtonian/design paradigm, the group/organizational dynamic of human agents is complex, nonlinear, constantly/continuously changing, and can be unpredictable. In addition, complexity in the human world can be relativistic. Consequently, human agent/organization may perceive certain spaces of complexity as spaces of relativistic order – relativistic complexity. In particular, due the presence of the intense mental dimension in humanity – complexity is in the mind of the beholder. In human existence, leadership and governance are spontaneously emerging key requirements – a primary trait for collective survival. Currently, with more knowledge-intensive and participative new agents (self-powered intrinsic leadership) who possess modified beliefs, values, norms, and expectations that are dissimilar from the older generations, governance and leadership need deeper analysis and redefinition. Traditional governance systems in all categories of organization are manifesting their constraint, vulnerability, and incompetency, in particular, incoherency due to new values and cultural pressure, and their associated self-organizing networks – especially informal networks that demand change, a more commonly observed worldwide phenomenon. In this respect, special attend has to be focus on the highly nonlinear relational parameter is beneficial. This study adopts the intelligence mindset that concurrently focuses on intelligence/consciousness-centricity, complexity-centricity, and network-centricity as the new strategic path towards better adaptive governance and the new leadership. It concentrates on the self-powered agents that are also intrinsic leaders/actors. The new intelligence leadership focal point include nurturing intense collective intelligence (more actors), the critical ability of self-organizing communications, immersion of leadership nodes in networks/clusters (including e-governance), increasing coherency of complex networks (interdependency of network of networks, network management), exploiting selected spaces of complexity (complexity management), and intelligence-driven self-transcending constructions that better facilitates emergence through ‘multi-lateral’ dynamics (minimizing ‘direct’ governance). This intelligence governance strategy emphasizes that mass lateral collectivity rather than selective enforced hierarchical empowerment is the more effective approach in the present contact. Fundamentally, optimizing the ‘everybody is in charge’ phenomenon frequently is a more viable option.

Agent-Based Modeling and Organization Studies: A critical realist perspective

The method of agent-based modeling raises philosophy of science issues that modelers have yet to resolve in a way that reconciles their work with that of other management and organization researchers. As a result, agent-based modelers have made only modest contributions to advancing organization theory and empirical research. In response, this study proposes critical realism as a philosophical perspective to understand and orient agent-based modeling research. A critical realist perspective clarifies the nature and purpose of agent-based modeling and indicates the potential complementarity between agent-based modeling and other approaches to theory building and testing in the field of management and organization studies. Key emphases within critical realism on mechanismic explanations, emergence, simplifying assumptions, and abductive reasoning support agent-based modelers’ practices. Critical realism carries implications for specifying models, clarifying ontology, evaluating model outcomes, validating models, triangulating, and identifying the limits of agent-based modeling. This study provides practical guidance from a critical realist perspective—to modelers and nonmodelers—to advance the contribution of agent-based modeling to management and organization research.

An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network

The purpose of this paper is to contribute to the empirical ‘world city network’ (WCN) literature by proposing an analytical framework that considers the significance of the positions of cities in the urban networks created by multinational corporations. To this end, we introduce an approach in which network centrality measures are interpreted against a randomized baseline model that retains the network's original degree distribution. Our framework is applied to Taylor's (2001 Geographical Analysis 33 181–194) specification of world cities being ‘interlocked’ through the office networks of globalized service firms. We thereby develop a new analytical take on Taylor's specification by using a primary-linkage algorithm that produces a one-mode directed graph based on the initial two-mode city and firm network data. We then randomize the resultant empirical network with a bootstrapping simulation approach, and compare the simulated parameters of this null model with our empirical network parameter, that is, betweenness centrality. We show the potential and limitations of our framework by discussing the position of cities such as Tokyo, Sydney, Melbourne, Almaty, and Karachi, which seem to hold more strategic and valuable positions than is suggested in Taylor's analyses. We discuss the wider significance of our approach by showing that the analytical strategy of interpreting measures against a randomized baseline model can also be adopted in other WCN approaches, including those using other data sources and network-related measures.

Epidemic protection zones: centred on cases or based on connectivity?

When an exotic infectious disease invades a susceptible environment, protection zones are enforced. Historically, such zones have been shaped as circles of equal radius (ER), centred on the location of infected premises. Because the ER policy seems to assume that epidemic dissemination is driven by a similar number of secondary cases generated per primary case, it does not consider whether local features, such as connectivity, influence epidemic dispersal. Here we explored the efficacy of ER protection zones. By generating a geographically explicit scenario that mimicked an actual epidemic, we created protection zones of different geometry, comparing the cost-benefit estimates of ER protection zones to a set of alternatives, which considered a pre-existing connecting network (CN) - the road network. The hypothesis of similar number of cases per ER circle was not substantiated: the number of units at risk per circle differed up to four times among ER circles. Findings also showed that even a small area (of <115 km(2) ) revealed network properties. Because the CN policy required 20% less area to be protected than the ER policy, and the CN-based protection zone included a 23.8% greater density of units at risk/km(2) than the ER-based alternative, findings supported the view that protection zones are likely to be less costly and more effective if they consider connecting structures, such as road, railroad and/or river networks. The analysis of local geographical factors (contacts, vectors and connectivity) may optimize the efficacy of control measures against epidemics.

A Fractal Approach to Industry Dynamism

The concept of industry dynamism claims a central role in models of organizational adaptation. However, the development of new ways to study it has waned. Building on the literatures on nonlinear dynamical systems and information complexity, we introduce a fractal approach as a useful lens to industry dynamism and a fresh alternative and complement to prevailing approaches. This differs conceptually from existing methods in highlighting nonlinearity and recognizing endogenous and stable sources of apparent unpredictability. Further, it uses the fractal dimension, a measure of the jaggedness in a time series, which offers several advantages over existing dispersion-based measures of unpredictability. We apply the fractal approach in an exploratory longitudinal study of the turbulent US network television industry and demonstrate its ability to uncover distinct aspects of industry dynamism.

Connectivity, Extremes, and Adaptation: A Power-Law Perspective of Organizational Effectiveness

Managers are often required to respond in adaptive ways to the threats and opportunities presented by rare, extreme outcomes. Given these, management scholars frequently face a stark choice: say something useful to practitioners using narratives in which dramatic effects are often achieved at the expense of academic rigor or maintain the latter by sacrificing practitioner relevance. Recent developments in complexity science offer a new perspective. The article distinguishes between the simplicities achieved by reductionism (equilibrium, law-like equations, linearity, and predictability) and the complexity triggered by initiating “butterfly events”—nonlinearity, scale-free causes, and power laws (PLs). Schema formation and adaptation within Gaussian and PL ontologies are framed in terms of Ashby’s law of requisite variety. Variety perceived to be requisite is sensitive to the type of ontological assumptions that are made. PL approaches to management inquiry focusing on rank/frequency distributions, fractal structures, and scale-free dynamics are outlined.