Beyond categorization: new directions for theory development about entrepreneurial internationalization

Categorizations emphasizing the earliness of internationalization have long been a cornerstone of international entrepreneurship research. Here we contend that the prominence of categories has not been commensurate with theory development associated with them. We draw on categorization theory to explain why earliness-based categories are persistent, and argue that a greater focus on notions related to opportunity can open new avenues of research about the entrepreneurial internationalization of business. We propose and discuss three directions for opportunity-based research on entrepreneurial internationalization, involving context, dynamics and variety

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH\u27s capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning

Microeconomic Structure determines Macroeconomic Dynamics. Aoki defeats the Representative Agent

Masanao Aoki developed a new methodology for a basic problem of economics: deducing rigorously the macroeconomic dynamics as emerging from the interactions of many individual agents. This includes deduction of the fractal / intermittent fluctuations of macroeconomic quantities from the granularity of the mezo-economic collective objects (large individual wealth, highly productive geographical locations, emergent technologies, emergent economic sectors) in which the micro-economic agents self-organize. In particular, we present some theoretical predictions, which also met extensive validation from empirical data in a wide range of systems: - The fractal Levy exponent of the stock market index fluctuations equals the Pareto exponent of the investors wealth distribution. The origin of the macroeconomic dynamics is therefore found in the granularity induced by the wealth / capital of the wealthiest investors. - Economic cycles consist of a Schumpeter 'creative destruction' pattern whereby the maxima are cusp-shaped while the minima are smooth. In between the cusps, the cycle consists of the sum of 2 'crossing exponentials': one decaying and the other increasing. This unification within the same theoretical framework of short term market fluctuations and long term economic cycles offers the perspective of a genuine conceptual synthesis between micro- and macroeconomics. Joining another giant of contemporary science - Phil Anderson - Aoki emphasized the role of rare, large fluctuations in the emergence of macroeconomic phenomena out of microscopic interactions and in particular their non self-averaging, in the language of statistical physics. In this light, we present a simple stochastic multi-sector growth model.Comment: 42 pages, 6 figure

State-space based mass event-history model I: many decision-making agents with one target

A dynamic decision-making system that includes a mass of indistinguishable agents could manifest impressive heterogeneity. This kind of nonhomogeneity is postulated to result from macroscopic behavioral tactics employed by almost all involved agents. A State-Space Based (SSB) mass event-history model is developed here to explore the potential existence of such macroscopic behaviors. By imposing an unobserved internal state-space variable into the system, each individual's event-history is made into a composition of a common state duration and an individual specific time to action. With the common state modeling of the macroscopic behavior, parametric statistical inferences are derived under the current-status data structure and conditional independence assumptions. Identifiability and computation related problems are also addressed. From the dynamic perspectives of system-wise heterogeneity, this SSB mass event-history model is shown to be very distinct from a random effect model via the Principle Component Analysis (PCA) in a numerical experiment. Real data showing the mass invasion by two species of parasitic nematode into two species of host larvae are also analyzed. The analysis results not only are found coherent in the context of the biology of the nematode as a parasite, but also include new quantitative interpretations.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS189 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Individual variation in behaviour

Wild animals show remarkable phenotypic variation despite natural selection eroding it. Phenotypic variation within populations is intriguing because all individuals are expected to be adapted to the same environmental conditions, and thus, to present similar phenotypic traits. However, when repeatedly measured, individuals have been observed to differ in the average expression of various behaviours across time and contexts. Consistent among-individual variation (called “animal personality”) has been proposed to be adaptively maintained if the fitness costs and benefits of behaviour vary with the environment or other phenotypic traits. Theory postulates that two key adaptive mechanisms could play a role: life-history trade-offs and spatiotemporal variation in selection (or heterogeneous selection). Empirical tests of the role of these mechanisms in the maintenance of individual variation in behaviour remain scarce and findings are ambivalent. My PhD thesis aimed at shedding light on the mechanisms allowing the persistence of animal personalities, thereby advancing our understanding of how animals adapt to variable environments. I investigated the role of life-history trade-offs and heterogeneous selection in the coexistence of alternative personalities in the wild. I also examined potential ecological drivers of heterogeneous selection. I used a passerine bird breeding in the wild in nest boxes (the great tit Parus major) as model. Individuals must trade-off investment among various phenotypic traits because they have limited amount of energy and time to acquire resources, grow and reproduce. The optimal resolution of trade-offs may depend on ecological conditions and/or the phenotypic traits of the individuals. Individuals differing in their behavioural phenotypes may thus resolve trade-offs differently. In Chapter 1, my colleagues and I tested this hypothesis by focusing on the trade-off between current reproduction and reproductive senescence. Specifically, we asked whether behavioural phenotypes differed in patterns of senescence. We found that faster explorers increased and subsequently decreased their reproductive investment with age. This finding suggests that faster explorers reproductively senesced later in life. By contrast, slower explorers laid similar clutch sizes through their lifetime; that is, they did not show reproductive senescence. Different behavioural phenotypes, thus, resolved the trade-off between current reproduction and reproductive senescence differently, which may allow them to coexist. Spatial and temporal variation in the environment may cause natural selection to favour different phenotypes in different environments. Spatial variation in selection may maintain phenotypic variation across environments, whereas temporal variation in selection (or fluctuating selection) may maintain phenotypic variation within environments. Though these processes co-occur and may have counteracting effects on phenotypic variation, both processes have rarely been investigated simultaneously. The relative importance of spatial and temporal variation in selection, and thus, the evolutionary potential of phenotypic traits under heterogeneous selection, remains unexplored. In Chapter 2, I studied heterogeneous selection on behaviour within and among great tit populations. To this aim, I gathered longitudinal data from five West European wild great tit populations breeding in nest boxes. In all these populations, behaviour was assayed with the same experimental design. Selection on behaviour varied primarily spatially. Temporal variation in selection was also important. The existence of phenotypic variation in all populations suggests that temporal variation played a key role in counteracting local adaption promoted by spatial variation. Temporal variation in selection was population-specific, which suggests that local ecological conditions also played a role in the evolution of phenotypic variation. This study thereby demonstrated the importance of considering both large- and small-scale geographical and temporal variation to understand the ecological mechanisms maintaining variation in animal behaviour. Previous studies found that variation in the social environment induced by variation in population density caused selection on behaviour to vary. However, we did not find such evidence in great tit populations. Another ecological factor that varies ubiquitously and that is crucial for survival and reproduction is food availability. Food availability also generally positively correlates with population density. Therefore, the effects of population density on fitness may be indirect through food availability. Variation in food availability may cause selection pressures on behaviour to vary because behavioural phenotypes differ in competitive abilities and foraging tactics. In Chapter 3, I studied whether winter food availability drove heterogeneous selection on activity in a novel environment. I experimentally manipulated food abundance outside the breeding season by providing supplementary food in multiple great tit nest box plots. Against expectations, I did not find evidence for fecundity selection on behaviour to vary with the experimental manipulation of food availability. Food availability may drive variation in fecundity selection but simultaneous changes in breeding density may counteract its action. Food- and density-dependent selection on behaviour need to be estimated simultaneously to disentangle their effects. Interestingly, on average, individuals were more active in high than in low food availability context. Moreover, high food availability context increased behavioural variation among individuals. These findings suggest greater plasticity and/or higher survival, recruitment or immigration rate of more active individuals. Future studies should investigate whether viability rather than fecundity selection vary with food availability. In the different projects of this PhD work, I focused on behaviour scored in different “novel environments”, which are all generally labelled “exploration behaviour”. However, “exploration behaviour” was not assayed with the same experimental design in Chapter 2 compared to Chapter 1 and 3. In Chapter 1 and 3, behaviour was assayed in the field in a portable cage. In Chapter 2, behaviour was assayed in a standardized laboratory room. We assumed that birds expressed the same behaviour in both assays because laboratory- and field-based behaviours have been shown to each correlate with other field-based behaviours. In Chapter 4, I tested this assumption and found that laboratory- and field-based behaviour did not correlate. Both assays may present different contexts to the birds, which elicited the expression of different behaviours. I also showed that the population sampled for the laboratory test was biased toward fast explorers. This study highlights the difficulty assaying behaviour in an unbiased and reproducible manner. It is therefore important to cross-validate behavioural assays before making biological assumptions. Overall, this PhD thesis contributed to understanding the role of adaptive mechanisms in individual variation in behaviour and their ecological drivers. This work showed that behavioural phenotypes contribute differently to population dynamics and should thus be considered in ecological and evolutionary studies. This work also exemplified the importance of long-term and collaborative projects. For a comprehensive understanding of phenotypic variation, the next challenge would be to simultaneously consider multiple traits, ecological factors and species that all interact through eco-evolutionary dynamics. Such integrative studies will embrace the complexity of ecological interactions and allow us to better understand how populations adapt to variable environments