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Research on multinational corporations (MNCs) shows that they have tried various structural solutions to solve the dilemma of trying to “balance” global control and efficiency with local country-specific sensitivity, autonomy, and innovation, with the Transnational form preferred. Failings of the strategy-structure sequence lend credence to the emerging strategy-process perspective. To date, the best lesson for MNC strategy-process concerns pertaining to the global vs. country dilemma comes from March's classic paper on “balancing” exploitation vs. exploration. 21st century MNCs exist in a more rapidly changing world, however, where static “balance” solutions may be insufficient. The tradition of “circular organizing” is one alternative to the failing “balance” solution; it offers a dynamic strategy-process approach to MNC management. Another is Dupuy's concept of “tangled hierarchies” where top-down and bottom-up influence forces are interwoven such that global exploitation or country-specific exploration dominates in timely fashion. It calls for clearly defined control and autonomy regimes, with space given for emergent rules governing the rotation rate. Key questions are: What is the optimal rate at which they should rotate supremacy, and how to get this to happen and persist? Since normal quantitative methods can’t track complex, nonlinear, emergent phenomena, an in-depth longitudinal case analysis was conducted of a global MNC in the cosmetics industry, as it progressed through its early years of formation. Our case covers twelve years, during which the MNC goes through several kinds of tangled hierarchies. The dynamics in our case are rich enough to illustrate many aspects of the “tangled hierarchy” approach, while also offering new clues about oscillation rates. A number of implications for managers are discussed. Principal among these is the “edge of chaos” idea, in which managers have to avoid too-fast or too-slow oscillation rates. Very fast rates can degenerate into chaos and then collapse into the exploitation or exploration “traps.” Firms also fall into the traps simply because managers don’t understand or can’t tolerate the idea of oscillation dynamics.

The contemporary workplace is characterized by transience: Organizational members frequently turn over and careers span multiple organizations. Consequently, workplace friendships that were once close become less close and intimate, that is they become peripheral and can deteriorate. While research has examined the benefits for employees who move on to new opportunities, less clear is how stayers, or employees who remain behind in the work setting, are affected. To understand stayers’ experiences and how they manage, we draw on theories of belongingess and to offer a three-part episodic process model, which explains how stayers’ engagement in the task and social domains are influenced. In doing so, we (1) present a dynamic view of the deterioration of dyadic relationships, highlighting how workplace relationships can change over time; (2) discuss both the depth and breadth of emotions involved for stayers; and (3) integrate a positive organizational scholarship perspective by considering both strength of friendships with other present coworkers and coping approaches of stayers as important boundary conditions, which can facilitate their recovery process. We draw attention to the broader implications of our theorizing for research on relationships and emotions, and practical implications for management.

Climate change during the next century is likely to significantly influence forest ecosystems in the western United States, including indirect effects on forest and shrubland fire regimes. Further exacerbation of fire hazards by the warmer, drier summers projected for much of the western U.S. by climate models would compound already elevated fire risks caused by 20th century fire suppression. This has potentially grave consequences for the urban–wildland interface in drier regions, where residential expansion increasingly places people and property in the midst of fire-prone vegetation. Understanding linkages between climate variability and change, therefore, are central to our ability to forecast future risks and adapt land management, allocation of fire management resources, and suburban planning accordingly. To establish these linkages we review previous research and draw inferences from our own retrospective work focused on 20th century climate–fire relationships in the U.S. Pacific Northwest (PNW). We investigated relationships between the two dominant modes of climate variability affecting the PNW, which are Pacific Decadal Oscillation (PDO) and El Niño/Southern Oscillation (ENSO), and historic fire activity at multiple spatial scales. We used historic fire data spanning most of the 20th century for USDA Forest Service Region 6, individual states (Idaho, Oregon, and Washington), and 20 national forests representative of the region's physiographic diversity. Forest fires showed significant correlations with warm/dry phases of PDO at regional and state scales; relationships were variable at the scale of individual national forests. Warm/dry phases of PDO were especially influential in terms of the occurrence of very large fire events throughout the PNW. No direct statistical relationships were found between ENSO and forest fires at regional scales, although relationships may exist at smaller spatial scales. However, both ENSO and PDO were correlated with summer drought, as estimated by the Palmer Drought Severity Index (PDSI), and PDSI was correlated with fire activity at all scales. Even moderate (±0.3°C decadal mean) fluctuations in PNW climate over the 20th century have influenced wildfire activity based on our analysis. Similar trends have been reported for other regions of the western U.S. Thus, forest fire activity has been sensitive to past climate variability, even in the face of altered dynamics due to fire suppression, as in the case of our analysis. It is likely that fire activity will increase in response to future temperature increases, at the same or greater magnitude as experienced during past climate variability. If extreme drought conditions become more prevalent we can expect a greater frequency of large, high-intensity forest fires. Increased vulnerability to forest fires may worsen the current fire management problem in the urban–wildland interface. Adaptation of fire management and restoration planning will be essential to address fire hazards in areas of intermingled exurban development and fire-prone vegetation. We recommend: (1) landscape-level strategic planning of fire restoration and containment projects; (2) better use of climatic forecasts, including PDO and ENSO related predictions; and (3) community-based efforts to limit further residential expansion into fire-prone forested and shrubland areas.

To reconcile theoretical discrepancies between discrete emotion, dimensional emotion (positive vs. negative affect), and the circumplex model, we propose the bifurcation model of affect structure (BMAS). Based on complexity theory, this model explores how emotion as an adaptive complex system reacts to affective events through negative and positive feedback loops, resulting in self-organizing oscillation and transformations between three states: equilibrium emotion, discrete positive and negative emotion in the near-equilibrium state, and chaotic emotion. We argue that the BMAS is superior to the extant models in revealing the dynamic connections between emotions and the intensity of affective events in organizational settings.

This chapter introduces electroencephalography (EEG), a measure of neurophysiological activity, as a critical method for investigating individual and team decision-making and cognition. EEG is a useful tool for expanding the theoretical and research horizons in organizational cognitive neuroscience, with a lower financial cost and higher portability than other neuroimaging methods (e.g., functional magnetic resonance imaging). This chapter briefly reviews past work that has applied cognitive neuroscience methods to investigate cognitive processes and outcomes. The focus is on describing contemporary EEG measures that reflect individual cognition and compare them to complementary measures in the field of psychology and management. The authors discuss how neurobiological measures of cognition relate to and may predict both individual cognitive performance and team cognitive performance (decision-making). This chapter aims to assist scholars in the field of managerial and organizational cognition in understanding the complementarity between psychological and neurophysiological methods, and how they may be combined to develop new hypotheses in the intersection of these research fields.

In this chapter we highlight a neurodynamic approach that is showing promise as a quantitative measure of team performance.

During teamwork the rapid electroencephalographic (EEG) oscillations that emerge on the scalp were transformed into symbolic data streams which provided historical details at a second-by-second resolution of how the team perceived the evolving task and how they adjusted their dynamics to compensate for, and anticipate new task challenges. Key to this approach are the different strategies that can be used to reduce the data dimensionality, including compression, abstraction and taking advantage of the natural redundancy in biologic signals.

The framework emerging is that teams continually enter and leave organizational neurodynamic partnerships with each other, so-called metastable states, depending on the evolving task, with higher level dynamics arising from mechanisms that naturally integrate over faster microscopic dynamics.

The development of quantitative measures of the momentary dynamics of teams is anticipated to significantly influence how teams are assembled, trained, and supported. The availability of such measures will enable objective comparisons to be made across teams, training protocols, and training sites. They will lead to better understandings of how expertise is developed and how training can be modified to accelerate the path toward expertise.

The innovation of this study is the potential it raises for developing globally applicable quantitative models of team dynamics that will allow comparisons to be made across teams, tasks, and training protocols.

The mathematical models used to describe the dynamical behaviour of a group of closely-spaced road vehicles travelling in a single lane without overtaking are known as car-following models. This paper presents a novel car-following model, which differs from the traditional models by having an equilibrium solution that corresponds to consecutive vehicles having not only zero relative velocity, but also travelling at a certain desired distance apart. This new model is investigated using both numerical and analytical techniques. For many parameter values the equilibrium solution is stable to a periodic perturbation but, for certain parameter values, chaotic motion results. This shows that in congested traffic, even drivers attempting to follow a safe driving strategy, may find themselves driving in an unpredictable fashion.