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Multi-level issues in evolutionary theory, organization science, and leadership☆

Francis J. Yammarino a,⁎, Fred Dansereau b,1

a Center for Leadership Studies and School of Management, State University of New York at Binghamton, Binghamton, NY 13902-6000, United States b Jacobs Management Center and School of Management, State University of New York at Buffalo, Buffalo, NY 14226, United States

a r t i c l e i n f o a b s t r a c t

Available online 19 October 2011 Multi-level issues are critical in the physical, social, and behavioral sciences. We articulate issues related to multiple levels of analysis in theory building and theory testing and explore them from evolutionary theory (ET) and organization science and leadership (OSL) perspec- tives. Specifically, analogous multi-level concepts and notions in ET and OSL are identified, aligned, and illustrated. Ideas from evolutionary psychology are included in the ET perspec- tive, while notions from the varient approach are included in the OSL perspective. Several exemplars in OSL that incorporate ET and multi-level perspectives are presented. Numerous examples and lessons learned from ET and implications of multi-level issues and multiple levels of analysis for future theory building and theory testing in OSL are discussed as well.

© 2011 Elsevier Inc. All rights reserved.

Keywords: Multi-level theory building Multi-level theory testing Multiple levels of analysis issues Evolutionary theory Organization science Leadership Evolutionary psychology Varient approach Fallacies False dichotomies Analytic tools

1. Introduction

Multi-level issues, or multiple levels of analysis in both theory building and theory testing, are critical in research in the physical, social, and behavioral sciences (see Dansereau & Yammarino, 2003, 2005, 2007; Dansereau, Yammarino, & Kohles, 1999; Futuyma, 2005; Gould, 2002; Klein & Kozlowski, 2000; Miller, 1978; Rousseau, 1985; Wilson, 1980, 2002; Wolfram, 2002; Yammarino & Dansereau, 2002, 2004, 2006, 2008, Yammarino & Dansereau, 2009a, 2009b). Work on multi-level issues in organization science and leadership (OSL) (e.g., Anderson, 1999; Dansereau, Alutto, & Yammarino, 1984; Dansereau, Cho, & Yammarino, 2006; Dansereau & Yammarino, 1998a, 1998b, 2003, 2007; Dansereau, Yammarino, & Markham, 1995a, 1995b, Dansereau et al., 1995b; Dansereau et al., 1999; DeChurch, Hiller, Murase, Doty, & Salas, 2010; Gupta, Tesluk, & Taylor, 2007; Klein & Kozlowski, 2000; Markham, 2010; Meyer, Gaba, & Colwell, 2005; Mumford, Hunter, & Bedell-Avers, 2008; Peterson, 1998; Rousseau, 1985; Yammarino & Dansereau, 2002, 2004, 2008, 2009a, 2009b; Yammarino, Dionne, Chun, & Dansereau, 2005) has been influenced by research on levels of analysis from other scientific fields (e.g., Gould, 2002; Miller, 1978; Wolfram, 2002). In particular, evolutionary theory (ET) (Darwin, 1859, 1871; Dawkins, 1976; Futuyma, 2005; Galton, 1869; Gould, 2002; Sober & Wilson, 1998; Wilson, 1980, 2002), a comprehensive, well-established interdisciplinary theory, can provide important insights for organization science and leadership on multi-level issues.

The Leadership Quarterly 22 (2011) 1042–1057

☆ We thank Chet Schriesheim, the LQYR Editor, and the anonymous reviewers for their helpful comments. ⁎ Corresponding author. Tel.: +1 607 777 6066; fax: +1 607 777 4422.

E-mail addresses: [email protected] (F.J. Yammarino), [email protected] (F. Dansereau). 1 Tel.: +1 716 645 3236; fax: +1 716 645 2863.

1048-9843/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.leaqua.2011.09.002

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While there have been attempts to infuse evolutionary theory ideas into the field of organization science and leadership (e.g., Kniffin, 2009; Kniffin & Wilson, 2010; Luxen & Van De Vijer, 2006; Markoczy & Goldberg, 1998; Nicholson, 1997, 2008; Nicholson & White, 2006; Pierce & White, 1999, 2006; Van Vugt, Hogan, & Kaiser, 2008), this prior work has primarily focused on variables and some processes and has typically ignored levels of analysis issues. Multi-level issues in ET offer in- sights regarding those same issues in OSL. As such, via an alignment, discussion, and illustration of analogous multi-level notions from ET and OSL, we hope to enhance the transfer or translation of knowledge on these topics from a mature and established field of work (ET) to a newer and developing one (OSL). Simply, knowledge of the use of multi-level notions in ET can facilitate the understanding of their use in OSL, providing lessons learned, and thus enhance multi-level theory building and theory testing in the latter field of study.

Thus, our purpose here is to identify, explore, and align a set of multi-level issues from the different disciplinary perspectives of ET and OSL. Multi-level concepts from evolutionary psychology (e.g., de Waal, 2002; Nicholson, 1997, 2008; Nicholson & White, 2006; Pierce & White, 1999, 2006; Sober & Wilson, 1998) are included in the ET perspective, while notions from the varient approach (e.g., Dansereau et al., 1984, 1999, 2006; Yammarino & Dansereau, 2009a) are included in the OSL perspective, to provide additional insights on multi-level issues and facilitate the transfer or translation of learning from one field to the other.

The key multi-level concepts and issues of focus are summarized in Table 1. For each of these prominent multi-level ideas, as shown in the table, a direct alignment can be established between evolutionary theory and organization science and leadership perspectives. After an articulation of primary notions in evolutionary theory and the subfield of evolutionary psychology, these multi-level issues in ET and OSL are explicated and illustrated in subsequent sections (organized around Table 1). Implications and examples for a better understanding of multi-level issues, including multiple levels of analysis in theory building and theory testing, in organization science and leadership are then discussed.

2. Evolutionary theory

2.1. Fundamental notions

Evolutionary theory is supported by literally thousands of research studies from all areas of biology (e.g., botany, genetics, molecular biology, and zoology) and numerous other fields (e.g., anthropology, archeology, ecology, economics, and sociology). The key ideas and concepts from ET have been very well developed (see Darwin, 1859, 1871; Dawkins, 1976; Futuyma, 2005; Galton, 1869; Gould, 2002; Nicholson, 1997, 2008; Nicholson & White, 2006; Sober & Wilson, 1998; Wilson, 1980, 2002) and can be summarized here.

Table 1 Multi-level issues in evolutionary theory, organization science, and leadership.

Multi-level issue/concept Evolutionary theory Organization science and leadership

Levels of analysis (entities) Genes, cells, organisms, demes, species, clades

Persons, dyads, groups, organizations, strategic groups, industries

Units of analysis (perspectives on entities) Organism level Species level Person level Group level Wholes (homogeneity) Organism Species Person Group Parts (heterogeneity) Gene, cell Organism, deme Gene, behavior Person, dyad Collective (higher level) Deme, species Clade Dyad, group Organization

Adjacent (multiple) levels (multi-level effects) Interact in synergy, orthogonally, or in opposition (homology, reductionism, and emergent properties; multi-level selection theory)

Interact in alignment, misalignment, or opposition (cross-level, level-specific, and emergent effects; multi-level and meso theories)

Level or entity changes over time Selection, drift, and drives (Lamarckism, anagenesis, cladogenesis, punctuated equilibrium, catastrophic mass extinction, mutation pressure, directional speciation)

Stability of wholes, parts, and lower level; emergent, level ends, transformation up or down, level change up or down

Fallacies Ecological Organisms are not just disaggregated

species Persons are not just disaggregated groups/organizations

Individualistic Species not just aggregated organisms Groups/organizations are not just aggregated persons

False dichotomies Individual–environment Individual–environment Nature–nurture Person–situation Free will–determinism Gene–learning and development

Analytical tools Preserved results analysis, frequency analysis, heritability (h2), and dynamic computational modeling and simulation to assess variation within and between organisms, species, etc.

Multi-level analysis (RCM, HLM, MLSEM, WABA), heritability (h2), and dynamic computational modeling and simulation to assess differences within and between persons, groups, etc.

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Darwin's notion of “descent with modification” is a powerful explanatory principle (Nicholson & White, 2006) and quite straightforward. Gould (2002, p. 13) indicates that “natural selection” is based on three undeniable facts—overproduction of offspring, variation, and heritability. As noted by Wilson (2002, p. 7), only a single paragraph is needed to explain Darwin's simple theory of adaptations:

Evolution explains adaptive design on the basis of three principles: phenotypic variation, heritability, and fitness conse- quences. A phenotypic trait is anything that can be observed or measured. Individuals in a population are seldom identical and usually vary in their phenotypic traits. Furthermore, offspring frequently resemble their parents, sometimes because of shared genes but also because of other factors such as cultural transmission. It is important to think of heritability as a correlation between parents and offspring, caused by any mechanism . . . Finally, the fitness of individuals—their propensity to survive and reproduce in their environment—often depends on their phenotypic traits. Taken together, the three principles lead to the seemingly inevitable outcome—a tendency for fitness-enhancing traits to increase in frequency over multiple generations.

ET describes adaptive changes of populations primarily by combining the mechanisms of variation (e.g., genetic mutations and recombinations) and natural selection. In evolution, variation generally enhances the diversity (i.e., more heterogeneity) and explorative capability of a population, while possibly reducing its immediate adaptiveness. By comparison, selection (primarily natural selection, but also sexual selection) eliminates less adaptive individuals (organisms) and promotes more adaptive individuals (organisms), increasing the average adaptiveness of the population, while narrowing its diversity (i.e., more homogeneity). Successful adaptation of populations requires both of these mechanisms (variation and selection) and in some type of balance, depending on the nature of the fitness landscape (see Futuyma, 2005; Gould, 2002). Thus fitness (i.e., probability of surviving or reproducing in a given environment) is both a relative concept (e.g., one organism relative to another) and a local concept (e.g., domain-specific to one or some but not necessarily all locations) (Wilson, 2002).

Evolution comprises the cumulative effect of these three independent processes: replication (heritability or reproduction), variation (random changes or mutations), and selection (the “best”-adapted organisms survive and pass on their characteristics to subsequent generations). Evolution is the response of a population to environmental (external) change (broadly defined) when the characteristics of the organisms vary, variation is heritable, and variation influences reproduction and survival. Variation can be caused by spontaneous mutation from the exchange of genetic material in reproduction or by random or systematic environ- mental impairments or enhancements. Essentially, organisms (individual or group) are a product of natural selection. They acquire properties and behaviors, through many generations of variation and selection, which enable them to reproduce and survive in their environments. Evolution selects for the properties and behaviors, and those that confer survival advantages upon an organism have meaningful implications for evolution. Any heritable property or behavior that increases the relative frequency of the gene(s) related to them in subsequent generations is (are) a survival advantage. As such, gene frequency has a great deal to do with mating, survival of offspring, and reproductive success.

Darwin (1859), who believed that selection acted primarily on organisms, had no idea that genes were the causal mechanism that makes heritability possible. The work of many others (e.g., Dawkins, 1976; Galton, 1869; Mayr, 1942) subsequently sheds light on this issue. Genes, which serve as the medium that transmits properties and behaviors (attributes) from generation to generation, are encoded in DNA in cells. Through their complex interaction with the environment, genes control the production of amino acids, which in turn regulate the development of cells, hormonal and neurochemical release, and, ultimately, properties, cognitions, emotions, and behaviors (Dawkins, 1976).

Dawkins (1976) argued for a “gene's eye view” of evolution, asserting that genes—and not organisms or species—were the targets of natural selection and that evolution was about “replicators” (genes) as mediated at each generation by “interactors” (organisms interacting with the environment). Others (see Gould, 2002) have insisted that evolution also can occur at the organism, species, and other levels of analysis or biological organization. Beyond long-term (and even short-term) genetic evolutionary processes, nongenetic evolutionary processes, characterized by psychological and cultural mechanisms of inheritance and often resulting in rapid responses to environmental change, are also possible. These alternative processes facilitate “group- level” selection (Wilson, 2002).

The “modern synthesis” in ET indicates that mutations to DNA create new variants of existing genes within a species. Natural selection permits the best-adapted individuals to produce the greatest number of surviving offspring, ensuring that adaptive variants of those genes become more common. While selection can be viewed as a process of removing poorly adapted individuals, it can also be a creative process. Comparative studies of development indicate how genes operate and evolve; research in ecology has highlighted the role organisms play in creating their own environments; studies of fossils question the role of competition per se; and various scholars (e.g., Gould, 2002; Wilson, 1980) have endorsed a multi-level view of evolution, with selection occurring at many levels of analysis (e.g., genes, organisms, social groups within species), including the between-species level (e.g., groups of different species). Most species appear to modify their environment, and this species–environment interaction can change how selection affects them. Essentially, species at least partially construct their own environment.

2.2. Evolutionary psychology

Although not without critics (e.g., Buller, 2009; Ehrlich, 2000; Panksepp & Panksepp, 2000; Sewell, 2004; Usher, 1999), the goal of evolutionary psychology (de Waal, 2002; Nicholson, 1997, 2008; Nicholson & White, 2006) is to apply the various ideas

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from ET to provide an evolutionary explanation of human behavior. According to Pierce and White (1999), “members of our species are born with a large repertoire of genetically encoded psychological mechanisms, which are the foundation of human behavioral responses. Psychological mechanisms are not preprogrammed behaviors; rather, they are activated by perceptions of our environment” (p. 843). Thus human and social behavior is a consequence of the interconnections between heritable psycho- logical mechanisms, which are likely domain-specific, and environmental cues.

Evolutionary psychology does not focus solely on genetic explanations of behavior and so is not genetically deterministic, but rather includes the key idea that important aspects of human behavior have been naturally selected and adapted (see de Waal, 2002; Nicholson & White, 2006). Moreover, just because something is genetically influenced does not mean it must have a purpose, must be “good” or “positive,” or is not a by-product of other traits or characteristics (de Waal, 2002). As such, traits, behaviors, and characteristics should not be considered in isolation, but rather as a set and in terms of the development and ancestral forms that produced them.

Nicholson (1997) summarizes evolutionary psychology in terms of four key assumptions: evolutionary psychology provides a biogenetic conception of humans; humans have adapted physically and also have an adapted mind; human bodies and minds are adapted for an ancestral environment; and specific adaptations can be used for more than one purpose (extended adaptation of unchanged biological functions to new uses). As an old species in a modern world, humans have retained our ancient psychology but use it in new ways in the current environment.

The implications of these assumptions, according to Nicholson (1997), are twofold: misfit consequences, as many of our expe- riences and problems are outcomes of misfits between our ancient psychology and the modern environment; and use of ancient instincts in an attempt to create and shape social relations and systems consistent with our nature. As such, only domain-specific adaptations are possible, multiple causes (e.g., multiple genes) may be involved, and genetic determinism is not a given because environments also play a role in the process. In general, evolutionary psychology “provides an integrated and inclusive account of human nature as a bridge, designed by natural selection, between biological imperatives and environmental contingencies” (Nicholson, 1997, p. 11).

3. Multi-level issues and concepts

3.1. Levels of analysis

With this background, we can now consider a variety of prominent multi-level issues and concepts from both evolutionary theory and organization science and leadership perspectives. Across the sciences, scholars have noted the importance of clearly specifying the levels of analysis at which phenomena are expected to exist theoretically, and that it is critical to ensure the measurement of constructs and data analytic techniques correspond to the asserted levels of analysis, so that inference drawing is not misleading or artifactual (Dansereau & Yammarino, 2003, 2005, 2007; Dansereau et al., 1999; Futuyma, 2005; Gould, 2002; Markham, 2010; Miller, 1978; Rousseau, 1985; Wilson, 1980, 2002; Wolfram, 2002; Yammarino & Dansereau, 2002, 2004, 2006, 2008, 2009a, 2009b). Levels of analysis are inherent in theoretical formulations—implicit or assumed, used to develop the boundary conditions under which a theory is expected to hold, or explicitly incorporated. Understanding how and if levels are specified permits an examination of the potential or degree of prevalence of theoretical misspecification. Moreover, identification of relevant levels-of-analysis issues may help account for mixed, inconsistent, and contradictory findings in prior research. Without explicit incorporation of levels-of-analysis issues, incomplete understanding of a construct or phenomena may lead to faulty measures, inappropriate data analytic techniques, and erroneous conclusions.

Theoretical revolutions in science often occur when other levels of analysis are considered. For example, a revolution in biology occurred when some scholars suggested, and subsequently demonstrated, that evolution can occur at a level of analysis higher than the organism level (see Gould, 2002; Wilson, 1980, 2002). A well-known revolution in physics occurred when some scholars asserted, and subsequently demonstrated, that quantum mechanics operates at a level of analysis lower than the atomic level (see Wolfram, 2002). Likewise, we can advance OSL theory building and theory testing by including lower and higher levels of analysis in theory development and hypothesis generation, measurement, data analysis, and inference drawing.

Levels of analysis are the entities or objects of study. Entities are typically arranged in hierarchical order such that higher levels (e.g., species and groups) include lower levels (e.g., organisms and persons, respectively), and lower levels are embedded in higher levels. They are “banded together in a rising series of increasingly greater inclusion, one within the next” (Gould, 2002, p. 674). Although there is “nesting,” there can be “decoupling” among levels as processes and properties at one level may differ from those at other levels (Gould, 2002; Miller, 1978).

3.1.1. ET and levels In ET work, genes, cells, organisms, demes, species, and clades are six typical entities of interest, also referred to as levels

of selection or levels of organization (Gould, 2002). As noted by Gould (2002), “individuals are made of parts and aggregate into collectivities … genes in cells, cells in organisms, organisms in demes, demes in species, species in clades … and we may choose to direct our evolutionary attention to any of the levels” (p. 674).

Genes are regions or subunits of DNA that control hereditary characteristics via sequences or segments used to produce spe- cific proteins or RNA. The sum total of genes in a cell or organism is called the genome. Cells are one of the most basic units of life, consisting of multiple genes; they are the structural and functional units of living organisms. Organisms are living things, plant or animal, composed of one or more cells, with the ability to function or act independently; they are the traditional units of selection

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in classical Darwinian microevolution (Gould, 2002). Demes are a local population of interbreeding organisms of the same species that share a distinct gene pool. Species are typically defined as an interbreeding group, capable of producing fertile offspring that does not or cannot productively breed with another group; they are the fundamental taxonomic units of biological classification and are the basic unit of macroevolutionary change (Gould, 2002). Clades are a group of organisms (e.g., a species) derived from a single common ancestor and all descendents of that ancestor. Members of a clade share common or homologous features derived from those ancestors.

3.1.2. OSL and levels In OSL work, we are interested in human beings in work organizations and various clusterings of organizations. Four key levels

of analysis of human beings are relevant (e.g., Yammarino & Dansereau 2009a; Yammarino et al., 2005). First, individuals or persons (independent human beings) (e.g., leaders or followers) allow for the exploration of individual differences. Second, dyads (two-person groups and interpersonal relationships) (e.g., leader-follower dyads) involve one-to-one interdependence between individuals. Third, groups (workgroups and teams) are a collection of individuals who are interdependent and interact on a face-to-face or “virtual” (non-co-located) basis with one another. Fourth, collectives are clusterings of individuals that are larger than groups and whose members are interdependent based on a hierarchical structuring or a set of common or shared expectations. Collectives can include groups of groups, departments, functional areas, strategic business units, and organizations per se, as well as firms, strategic groups or alliances of organizations, and industries.

These four levels of analysis represent different perspectives on the human beings who constitute organizations. They can be thought of as different lenses through which human beings can be observed. Given the embeddedness of levels, as one views human beings from increasingly higher levels of analysis, the number of entities decreases (e.g., there are fewer collectives than groups in an organization) and the size of the entity increases (e.g., there are a larger number of human beings in collectives than in groups).

3.2. Units of analysis

There are three alternatives to consider for each level of analysis. The physical sciences (e.g., Gould, 2002; Lerner, 1963) and social sciences (e.g., Dansereau et al., 1984; Yammarino & Dansereau, 2009a) distinguish conceptually between two different (relevant) views of any level of analysis—wholes and parts. The third view (independent) indicates that the focal entities are not relevant and other entities are plausible.

A wholes view is defined as a focus between entities but not within them; differences between entities are viewed as valid, and differences within entities are viewed as error (random). This perspective can be viewed as a between-units case in which members of a unit are homogeneous, the whole unit is of importance, entities display similarity among members, and relation- ships among members of units with respect to constructs of a theory are positive. Relationships among theoretical constructs are a function of differences between units.

A parts view is defined as a focus within entities but not between them; differences within entities are valid, and differences between entities are erroneous. This perspective can be viewed as a within-units case, also known as a “frog pond” effect, in which members of a unit are heterogeneous, a member's position relative to other members is of importance, entities display complementarity among members, and relationships among members of units with respect to constructs of a theory are negative. Relationships among theoretical constructs are a function of differences within units. Whether from an ET or OSL perspective, the “glue” of parts, depending on the level of analysis, is interdependence, functional integration, or social structure and behavioral interaction (Dansereau et al., 1984; Gould, 2002; Miller, 1978; Yammarino & Dansereau, 2009a).

Across the sciences, various authors indicate that effects also may not be evidenced at a focal level (Dansereau et al., 1984; Gould, 2002; Lerner, 1963; Miller, 1978; Yammarino & Dansereau, 2009a). In this case of independence, two possibilities for a focal level are a focus both between and within entities, or error between and within entities. In both cases, the focal level of analysis does not clarify understanding of the constructs, variables, or phenomena of interest, and other levels must be considered. The members of a unit are independent, free of the unit's influence, and relationships among members of units with respect to constructs of a theory are independent. Relationships among theoretical constructs are a function of differences between members (e.g., persons) independent of higher-level units (e.g., groups).

3.2.1. ET and units In evolutionary theory, when “organism” is the focal level of analysis, the organism (wholes) and the interdependent cells or

genes (parts) within the organism are the potential units of analysis. If the entities are independent at this level, potential higher levels (collective) are the deme or species. When “species” is the focal level of analysis, the species (wholes) and the interdepen- dent organisms or demes (parts) within the species are the potential units of analysis. If the entities are independent at this level, a potential higher level (collective) is the clade.

In ET, wholes, a homogeneous perspective, can also imply a focus on “selection,” either positive (replication) or negative (subtractive) selection, such as homogeneous species that have adapted to a simple environment. Parts, a heterogeneous perspec- tive, can also imply a focus on “variation” via random mutation, recombination, and random generation, such as diverse organisms that have adapted to various niches in a complex environment (see Futuyma, 2005). In microevolution, at the organism level, the proliferation of one part to crowd out others results in “cancer;” in macroevolution, at the species level, it often results in adaptation by “anagenesis” (see below and Gould, 2002).

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3.2.2. OSL and units In organization science and leadership, when “person” is the focal level of analysis, the person (wholes) and the interdepen-

dent genes or properties and behaviors over time (parts) within the person are the potential units of analysis. If the entities are independent at this level, potential higher levels (collective) are the dyad or group. When “group” is the focal level of analysis, the group (wholes) and the interdependent persons or dyads (parts) within the group are the potential units of analysis. If the entities are independent at this level, potential higher levels (collective) are the organization, strategic group, or industry.

In OSL, wholes, a homogeneous perspective, can also imply a focus on “stability,” such as person (e.g., leader) traits that remain constant over time. Parts, a heterogeneous perspective, can also imply a focus on “change,” such as person (e.g., leader) charac- teristics that shift over time (see Dansereau et al., 1984, 1999; Yammarino & Dansereau, 2009a).

3.3. Adjacent levels: multiple levels and multi-level effects

Beyond single levels of analysis viewed separately, another key issue is that of multiple levels of analysis. In all the sciences, assuming only one level of analysis or choosing only one level without consideration of other levels can either mask effects or indicate effects when none exist (e.g., Gould, 2002; Lerner, 1963; Markham, 2010; Miller, 1978; Yammarino & Dansereau, 2009a; Yammarino et al., 2005). Given the embeddedness of levels, multiple levels should be considered in combination and multi-level effects should be identified.

3.3.1. ET and multiple levels Gould (2002) offers “the grand analogy” of various evolutionary theory ideas, processes, and concepts between microevolution

at the organism level and macroevolution at the species level. Moreover, in evolutionary theory, selection at one level of analysis may enhance (positively—synergistic), counteract (negatively—in opposition), or be orthogonal (independent) to selection at another (higher or lower) level of analysis (Gould, 2002). These alternatives are plausible because each level differs from all other levels in a variety of substantial ways, including the style and frequency of patterns of change as well as the causes of these changes over time.

Although Darwin asserted a single-level “reductionist” theory with organisms as the locus of selection, multi-level selection theory (MLST) (Gould, 2002; Wilson, 1980, 2002) espouses the possibility that natural selection can operate at more than one biological level of analysis. Darwin's (1859) three components of selection (phenotypic variation, heritability, and fitness consequences) can occur at both the individual organism level and higher (e.g., species or group) levels of analysis. Darwin eventually endorsed the notion of species-level selection, rejecting reductionism to the organism level, the lowest level known in his time (see Gould, 2002; Wilson, 2002). Likewise, many modern scholars have rejected a similar reductionist position to the gene level, the lowest level known at the present time (see Gould, 2002). Natural selection at the group or higher level (e.g., demes, species, or clades) is far more complex than selection at the individual (i.e., organism or gene) level and does not necessarily result in outcomes that would be viewed as “adaptive” when considered from an outside perspective (Wilson, 2002).

Humans, like other organisms, are biological entities driven by self-interest to promote survival. These self-preservation and self-enhancement instincts serve us well (i.e., “selfish gene,” Dawkins, 1976). But, like the great apes, our closest biological rela- tives, and other organisms (e.g., insects), humans are also social entities. As such, group living is also a likely key element in our survival (e.g., Gould, 2002; Van Vugt et al., 2008; Yammarino & Dansereau 2009a). Of course, harmonious group relations have not solely characterized human history or the history of other entities. Lethal intergroup competition is also highly evident. As such, evolutionary adaptation has promoted both within-group solidarity and between-group hostility (e.g., Pierce & White, 1999; Van Vugt et al., 2008).

Wilson (1980, 2002) uses the term “trait-group” to emphasize the intimate connections between traits and groups in MLST. He notes that groups must be defined separately for every trait, behavior, or activity—a notion consistent with the definition of groups in OSL and other fields. Moreover, selection at the level of the group may be just as important as lower-level selection. In some cases, the groups are so highly integrated (i.e., wholes) that they can be called “organisms” themselves, suggesting the “organismic concept of human groups” (Wilson, 2002). Groups as a unit of selection and the interconnectedness among individuals in a group raises the possibility of “group cognitions” (e.g., shared mental models, consensus decision making; also see Klein & Kozlowski, 2000; Yammarino & Dansereau 2009a) and “collective leadership” (e.g., shared leadership, team leadership; also see DeChurch et al., 2010; Yammarino & Dansereau, 2009a).

For Wilson (2002), “Natural selection is a multi-level process that operates among groups in addition to among individuals within groups” (p. 43). In this regard, Wilson (2002) details multiple meanings of reductionism and holism. A homology thesis posits a basic consistency across multiple levels of selection (analysis) (Gould, 2002; Wilson, 2002). A strong version of this notion would view effects across all (many) levels, while a weaker version would assert effects across at least two levels. Such cross-level effects are also called continuities. In contrast, discontinuities specify differing effects at multiple levels. In particular, emergents or emergent properties are not found at lower levels or are characteristics that “drop out” in the evolution of higher levels (e.g., Gould, 2002; Miller, 1978). As noted by Gould (2002), “when selection works upon emergent features, then causal reduction to individual genes and their independent summations becomes logically impossible” (p. 627).

Likewise, in evolutionary psychology, there is no need to take a reductionist position. As noted by Nicholson (1997), to under- stand the functioning of human beings as organisms requires examination from many levels of analysis, not just the genetic or neurological levels. Moreover, the environment (situation or higher level) within which human behavior occurs also requires examination. Thus lower- and not higher-level possibilities (reduction), higher- and not lower-level possibilities (emergent), and

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cross-level possibilities (homology) exist in the realm of evolutionary psychology (e.g., de Waal, 2002; Nicholson, 1997; Pierce & White, 1999).

3.3.2. OSL and multiple levels In organization science and leadership, micro versus macro theories, processes, and concepts can be either contrasted or

viewed as analogous, depending on various levels-of-analysis formulations. Adjacent levels can interact in alignment, misalign- ment, or opposition to one another, creating various types of multi-level effects. The focus here for “linking” (multiple) levels of analysis is on three general types of multiple-level formulations—level-specific, emergent, and cross-level formulations— from both wholes and parts perspectives, resulting in six cases relevant for work in OSL. For each of these formulations, we offer a description and some examples.

In particular, relationships among constructs may be hypothesized to hold at a lower level (e.g., person) but not at a higher level (e.g., group). This possibility may be discussed as a discontinuity thesis (Miller, 1978), as level-specific formulations (Dansereau et al., 1984; Miller, 1978), or empirically as disaggregated, individual, or level-specific effects (Pedhazur, 1982; Robinson, 1950). In these cases, the higher level of analysis is not relevant for understanding the theoretical constructs.

Wholes at a lower level may not aggregate or manifest themselves at a higher level (independent). This level-specific wholes formulation means that members are homogeneous with respect to the constructs of interest in all lower-level entities (e.g., groups), and higher-level entities (e.g., collectives) are not relevant. Examples of level-specific wholes formulations include the notions of psychological climate (James, Joyce, & Slocum 1988), commitment approaches, and various personality approaches at the individual level (Yammarino & Dansereau, 2009a); many team-based and shared leadership approaches at the group level (Klein & Kozlowski 2000; Yammarino & Dansereau, 2009a; Yammarino et al., 2005); and organizational climate (Glick, 1985) and organizational missions and visions and strategic leadership at the organization level.

Parts at a lower level may not aggregate or manifest themselves at a higher level (independent). This level-specific parts formulation means that members are heterogeneous with respect to the constructs of interest in all lower-level entities (e.g., groups), and higher-level entities (e.g., collectives) are not relevant. Examples of level-specific parts formulations include newer approaches that consider personality changes across time (see Yammarino & Dansereau, 2009a) and vertical dyad linkage (VDL) and leader–member exchange (LMX in- and out-group) leadership approaches at the group level (Dansereau et al., 1995a, 1995b; Yammarino et al., 2005).

In contrast, relationships among constructs may not be asserted at a lower level but are hypothesized to manifest themselves at a higher level of analysis. This possibility may also be discussed as a type of discontinuity thesis (Miller, 1978), as emergent formulations that hold at a higher level (e.g., group) after not being asserted or found to hold at a lower level (e.g., person) (Dansereau et al., 1984; Miller, 1978), empirically as higher-level effects that do not disaggregate, or as emergent effects (Miller, 1978; Robinson, 1950). In these cases, the lower level of analysis is not relevant for understanding the theoretical constructs.

For an emergent wholes formulation, constructs are expected to hold at a higher (e.g., group) level where members are homo- geneous with respect to the constructs after not having been expected or observed at a lower level (independent). Examples of emergent wholes formulations include concepts such as group cohesion, shared mental models, and shared and team leadership at the team level (DeChurch et al., 2010; Klein & Kozlowski, 2000; Yammarino et al., 2005) and several of the GLOBE cultural values dimensions at the society level (House, Hanges, Javidan, Dorfman, & Gupta 2004).

For an emergent parts formulation, constructs are expected to hold at a higher (e.g., group) level where members are hetero- geneous with respect to the constructs after not having been expected or observed at a lower level (independent). Examples of emergent parts formulations include concepts such as vertical dyad linkage and perhaps leader–member exchange (see Dansereau et al., 1995a, 1995b) and intra-group conflict and compatible mental models at the team level (Klein & Kozlowski, 2000) and aspects of organizational subcultures at the organization level (Katz & Kahn, 1978).

Relationships among constructs also may be hypothesized to hold at higher (e.g., collective) and lower (e.g., group) levels of analysis. This possibility is discussed as a homology thesis (Miller, 1978), empirically as aggregated or ecological effects (Pedhazur, 1982; Robinson, 1950), and as cross-level explanations (Behling, 1978; Dansereau et al., 1984; Miller, 1978). Cross-level formula- tions (theories, propositions, and hypotheses) are statements about relationships among variables that are likely to hold equally well at a number of levels of analysis (e.g., X and Y are positively related for individuals and for groups), and they specify patterns of relationships replicated across levels of analysis. Models of this type are uniquely powerful and parsimonious because the same effect is manifested at more than one level of analysis (e.g., E=mc2, which holds at multiple levels of analysis, is a cross-level formulation).

Wholes at a lower level can aggregate or manifest themselves as wholes at a higher level. This cross-level wholes formulation means that members are homogeneous with respect to the constructs of interest in all entities (e.g., groups and collectives) at both levels of analysis, but the entities (e.g., groups and collectives) differ from one another. Examples of cross-level wholes formulations include various GLOBE cultural dimensions from the individual to organization to society levels (House et al., 2004) and professional and functional titles and associated expectations about them from the individual to dyad to group to organization levels (see Yammarino & Dansereau, 2009a).

Wholes at a lower level can aggregate or manifest themselves as parts at a higher level. This cross-level parts formulation means that members are homogeneous with respect to the constructs of interest in all the lower-level entities (e.g., groups), and these differ from one another; in all higher-level entities (e.g., collectives), however, there is heterogeneity because members within the entities differ from one another. Examples of cross-level parts formulations include functional area task differences and subsystem subcultures from the individual to organization and group to organization levels (Katz & Kahn, 1978).

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3.4. Levels over time

Another important multi-level issue for both ET and OSL is the theoretical specification and empirical test of potentially changing variables and phenomena (e.g., traits, properties) and shifting levels of analysis (entities) over time (see Dansereau et al., 1999; Gould, 2002). By definition, ET is longitudinal in nature, and the time frame is generally long. Likewise, although with a relatively shorter time frame, OSL must be viewed from a longitudinal perspective to fully understand relevant phenomena that are stable or shifting, changing, and developing over time.

3.4.1. ET, time, and levels The essence of evolutionary theory is changes within and across various levels of organization or selection (analysis) over time.

The production and the elimination of “individuals” at the organism level are termed birth and death, respectively; at the species level, these events are called speciation and extinction, respectively (Gould, 2002). Moreover, mutation at the organism level and various other mechanisms at the species level are sources of variation in new “individuals” over time. In particular, three major styles of changes in entities over time can be distinguished: first, selection, as discussed above, is differential proliferation due to traits or properties of “interactors,” such as natural (organism) selection and species selection. Second, drift is random differential proliferation that entails random “sorting” at the organism level; genetic drift occurs within the deme or species, and founder drift results in founding new demes or species; at the species level, drift occurs within the clade, and founder drift results in founding new clades (Gould, 2002).

Third, drives, opposite or at least orthogonal to selection, are directional variation within and between “individuals,” which direc- tionally change species and clades, for example, by changing organisms and species, respectively, from within. Drives include several mechanisms such as the following (for details, see Gould, 2002): Lamarckism, a type of drive at the organism level, espouses the “soft” inheritance of acquired characteristics. For example, in cultural evolution, based on gene (biology)-culture co-evolution, culture reinforces patterns of social behavior that reflect adaptive traits and properties in humans (Wilson, 1978). Anagenesis is a type of drive at the species level; it occurs when the population of an entire species changes on a genetic level without a split or branching. In contrast, cladogenesis is when a branching occurs or a species splits into two genetically distinct populations that adapt to different environments, ecosystems, or other factors. Punctuated equilibrium asserts that evolution occurs not in degrees of gradualism, but rather in rapid bursts separated by long periods of stasis or relatively little change. Catastrophic mass extinction is an abrupt end to one or many species in a short period of time—for example, due to a major external or environmental event (asteroid strike, flood, or volcanic eruption in a geographic region). Mass extinctions may also be caused by a sharp drop in the rate of speciation. Mutation pressure, a reproductive drive at the organism level, is a biased production of new organisms. The frequency of occurrence is very low if the mutation is harmful to the organism, because selection at the organism level effectively suppresses changes at the lower (gene or cell) level. Analogously, directional speciation, a reproductive drive at the species level, is a biased production of new species. The frequency of occurrence here is potentially quite common because species do not strongly suppress organism and deme selection, and new species originate because of change that emanates from the parent.

3.4.2. OSL, time, and levels In organization science and leadership, while much has been written about changing variables or constructs over time and

strategies for analyzing these changes (e.g., Chan, 1998; Gottman, 1995; Yammarino et al., 2005), relatively little has been written about changing entities (levels of analysis) over time (for exceptions, see Dansereau et al., 1984, 1999; Yammarino & Dansereau, 2009a). Based on the varient paradigm, Dansereau et al. (1999) consider the plausible units of analysis (wholes, parts, indepen- dence, and null) at two points in time to account for entity changes over time. A 16-cell matrix results for understanding changes or stability in levels of analysis over time.

In particular, for various levels of analysis, Dansereau et al. (1999) define, describe, and illustrate the following components: four types of stable conditions (in terms of wholes, parts, lower-level independent units, and null over time); three types of changes that move the focus up from a lower to a higher level (transformation up from parts to wholes, level change up from independent units to wholes, and level change up from independent units to parts); three types of changes that move the focus down from a higher to a lower level (transformation down from wholes to parts, level change down from wholes to independent units, and level change down from parts to independent units); and six types of changes that indicate the beginning or end of a level (three “emergents” from null or nothing to wholes, parts, or independent units, and three “ends” from wholes, parts, or independent units to null or nothing).

As an example, a portion of the work of Klein and Kozlowski (2000) can be cast in terms of the Dansereau et al. (1999) frame- work. Klein and Kozlowski (2000) offer two forms for the emergence or change of entities over time—composition and compila- tion. Composition, based on isomorphism, suggests that lower-level entities (e.g., individuals), based on shared mental models and similar information and expertise, combine in a linear or pooled fashion with stable or uniform interactions over time, resulting in higher-level entities (e.g., teams) viewed from a homogeneous perspective. In this case, lower-level wholes shift to higher level wholes over time. Compilation, based on discontinuity, suggests that lower-level entities (e.g., individuals), based on compatible mental models and diverse information and expertise, combine in a non-linear or adaptive fashion with irregular or non-uniform in- teractions over time, resulting in higher-level entities (e.g., teams) viewed from a heterogeneous perspective. In this case, lower-level wholes shift to higher-level parts over time.

The Dansereau et al. (1999) framework for understanding change and stability in entities over time can be extended to more than two levels, to more than two time periods, and to various intervals of time (e.g., hours, days, months, years, decades, and

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generations). The incorporation and use of this framework offers a way to conceptualize and then test longitudinal and dynamic views on levels of analysis for a more complete approach to theory building and testing in OSL.

3.5. Fallacies

For evolutionary theory and organization science and leadership, it is critical to avoid committing a “fallacy of the wrong level” (Dansereau & Yammarino, 2006; Dansereau et al., 2006; Gould, 2002). In the inference-drawing process, traits, properties, rela- tionships, and even theories cannot be attributed to, or expected to operate or hold at, one level of analysis given empirical results (or lack thereof) regarding entities at another level of analysis. An ecological fallacy occurs when lower levels of analysis are pre- sumed to be mere disaggregations of higher-level entities. In contrast, an individual fallacy occurs when higher levels of analysis are presumed to be mere aggregations of lower-level entities. Work by Robinson (1950) and others (e.g., Dansereau et al., 1984, 2006; Rousseau, 1985) in the social sciences and by numerous scholars in the physical sciences (e.g., Lerner, 1963; Miller, 1978; Wolfram 2002) highlights the problems and issues associated with such fallacies.

3.5.1. ET and fallacies In evolutionary theory, while Gould (2002) notes “the grand analogy” between microevolution features at the organism level

and macroevolution features at the species level, he also discusses that these features are not identical. Organisms cannot be viewed as just disaggregated species, and species cannot be seen as just aggregated organisms—processes, properties, traits, and other aspects of these entities can vary by level of analysis or biological organization, such that some can emerge or hold at one level but not at other levels.

Nicholson (1997) states that evolutionary psychology avoids both the individualistic fallacy (e.g., societies are just individual characteristics manifested at or aggregated to a larger scale) and the ecological fallacy (e.g., individuals characteristics are just manifestations or disaggregations of societies on a lower scale). Moreover, evolutionary psychology does not take solely a reductionist position, instead allowing for both emergents and homology.

3.5.2. OSL and fallacies In organization science and leadership, while Dansereau et al. (1984) and Yammarino and Dansereau (2009a) note that

similarities may be apparent between micro elements at lower levels and macro elements at higher levels, they also make clear that these elements are not identical. Persons cannot be viewed as just disaggregated groups or organizations, and groups or organizations cannot be seen as just aggregated persons—processes, constructs, relationships, theories, and other aspects of these entities can vary by level of analysis, such that some can emerge or hold at one level and not at other levels.

Dansereau and Yammarino and colleagues (Dansereau & Yammarino, 2006; Dansereau et al., 1984, 2006; Markham, 2010; Yammarino & Dansereau, 2009a; Yammarino et al., 2005) elaborate on various aspects of fallacies of the wrong level for organi- zation science in general and for leadership research in particular. They also offer a variety of potential solutions to, and ways to avoid, such ecological and individual fallacies in theory and hypothesis formulation, measurement, data analysis, and inference- drawing procedures.

3.6. False dichotomies

Various Aristotelian “either-or” controversies, that have existed for several millennia, can be expressed as, and often degrade to, false dichotomies and inappropriate dualisms. In terms of multi-level issues in evolutionary theory and organization science and leadership, these dichotomies typically relate to some version of “the individual versus the environment.” In ET, this trans- lates into the “nature–nurture” and “free will–determinism” debates; in OSL, it is the “person–situation” and “genes–learning/ development” debates. In both ET and OSL, the goal is to resolve Aristotelian “either-or” controversies with a “Galilean approach” characterized by integration of the components of each duality.

3.6.1. ET and dichotomies Relevant to evolutionary theory, Wolfram (2002) states that “even though a system may follow definite underlying laws, its

overall behavior can still have aspects that fundamentally cannot be described by reasonable laws” (p. 750). According to him, this idea explains the phenomenon of “free will;” i.e., organisms (e.g., humans) still show variation in behavior that is not accounted for by theories (rules) per se. In short, systems or entities have free will.

Further, de Waal (2002) notes that “ancient dualisms”—such as mind–body, human–animal, and nature–culture—prevent psychology from fully adopting, endorsing, and employing ET in its theories and conceptualizations of human behavior (also see Nicholson & White, 2006). But, just as neuroscience is breaking down the mind–body dualism, so too will ET and evolutionary psychology undermine the human–animal and nature–culture dualisms (de Waal, 2002).

Nicholson (1997) argues that the nature–nurture dichotomy is false because the institutions that socialize and nurture humans are ones that have come from our natures. He notes that these patterns of socialization have persistent and replicated themes across cultures and are not arbitrary or accidental, yet their manifestations differ greatly to deal with local environments (for a related discussion, see Van Vugt et al., 2008).

Pierce and White (1999) note that humans are not preprogrammed and that we have a large and flexible set of behaviors that permit considerable latitude and the exercise of free will. Given that these behaviors are flexible and not completely biologically

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predetermined, some may be learned. The “nature versus nurture” debate then centers on how much of human behavior is learned versus how much is biologically determined. Nature predisposes humans to act in particular ways in specific circumstances, but learning and cognitions can then alter our actions and behaviors. Rather than thinking of “nature–nurture” and “free will– determinism” as “either-or” controversies, it is useful to think about both notions operating in each case—nature and nurture as well as free will and determinism affect human behaviors, actions, and interactions (see Pierce & White, 1999).

3.6.2. OSL and dichotomies In organization science and leadership, there is a long history related to the “person–situation” debate (e.g., Dansereau et al.,

1995a, 1995b, 1999; Epstein & O'Brien, 1985; Johns, 2006; Schneider, 1983; Yammarino & Dansereau, 2009a). This discussion can also be framed in terms of an “individual–environment” debate, or the micro–macro distinction, where an integration can occur to resolve the debate by viewing higher levels of analysis as the context (situation or environment) for or boundaries on lower levels of analysis (Dansereau et al., 1984, 1999; Johns 2006; Yammarino & Dansereau, 2009a).

Schneider (1983), rather than assuming person (lower-level) or situation (higher-level) explanations of effects, offers a person-by-situation or interactional psychology explanation for behavior. Likewise, Epstein and O'Brien (1985) conclude that it is the person within situation (context) that matters for explanation of phenomena; again, there is an appeal to integrate these notions in terms of lower and higher levels of analysis.

Johns (2006) extends these notions to further develop the idea and importance of “context” as a higher level of analysis within which behavior occurs and without which behavior often becomes uninterpretable. For example, individual behavior occurs within a group context, individual and group behaviors occur with an organizational context, and so on. In this way, lower and higher levels of analysis together, in integration, explain the phenomena of interest.

Similarly, in human behavioral genetics research, Arvey and Bouchard (1994), Arvey, Rotundo, Johnson, Zhang and McGue (2006), and Ilies, Arvey and Bouchard (2006) identify and explicate both genetic (lower-level) and environmental (higher- level) factors that influence individual differences in a variety of topic areas (e.g., personality, leadership). They partition the between-person behavioral (phenotypic) variance into its genetic and environmental components, recognizing that heredity and environment both play key roles and are intimately connected in human development and behavior. Avoiding the “either- or” controversy in favor of an integration, Arvey and colleagues suggest that genes likely establish general predispositions and natural inclinations (e.g., a baseline) that are then altered or shaped by the environment (e.g., learning and development) to increase or decrease an individual's likelihood of displaying particular traits and behaviors.

3.7. Analytical tools

Given the diverse and multi-level nature of the issues and concepts addressed here for evolutionary theory and organization science and leadership, a variety of multi-level methods and analytic tools are required for assessing and testing these notions empirically.

3.7.1. ET and tools In evolutionary theory, because past causes cannot be observed directly, research and methodology attempt to draw conclu-

sions from the preserved results (historical, geological, and fossil records) of these past causes. According to Gould (2002, p. 59), Darwin developed four general procedures for this purpose: extrapolation to longer times and effects of actual historical changes observed; explication and ordering of several phenomena as sequential stages from a single historical process; inference of history as an explanation for a large set of seemingly disparate observations; and inference of history from single objects based on oddities and imperfections that must denote paths of prior change.

In ET, beyond these procedures and methods, researchers often attempt to assess variation and differences within and be- tween species, organisms, and other entities. A variety of analytic tools are used for these purposes. “Relative frequencies” are used to assess many evolutionary ideas and approaches, and “dominant relative frequencies” are employed for the assessment of punctuated equilibrium notions (Gould, 2002). Heritability (h2), which is a correlation between parents and offspring caused by any mechanism, including but not limited to genes (e.g., Gould, 2002; Wilson, 1980, 2002), is also used. The behavioral genetic study of human traits has been a key component of evolutionary research since the time of Darwin and Galton, and along with observational studies and molecular genetic studies, can provide a more complete research approach for evolutionary psychology. Another approach is the use of dynamic computational modeling and simulation (e.g., Wolfram, 2002), which focuses on complex nonlinear interactions among various biological elements, levels of biological organization, and environmental elements. Using such modeling, Wolfram (2002) showed for various aspects of evolutionary theory and natural selection that simple rules (ideas, notions, theories) can lead to and explain both simple and complex evolutionary phenomena.

3.7.2. OSL and tools In organization science and leadership, Arvey and Bouchard (1994), Arvey et al. (2006), and Ilies et al. (2006) identified the

relative contributions of genotypic and environmental differences to variation in heritable constructs across individuals. The h2

coefficient estimates the proportion of phenotypic variance (between individuals) accounted for by genetic differences. For several constructs (e.g., intelligence, 60% to 80%; personality, 35% to 50%; attitudes, about 30%; work values, about 35%; leadership, about 30%), approximately one third of the variation may be due to genetic differences, while two thirds of the variation can be attributed to nongenetic (e.g., environmental) differences.

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Another tool is dynamic computational modeling and simulation (e.g., Dionne & Dionne 2008; Hulin & Ilgen 2000) of complex nonlinear relations among various traits, behaviors, properties, levels of analysis, and environmental characteristics for organiza- tion science and leadership phenomena. Dionne and Dionne (2008), for example, developed a computational model for a levels- based comparison of four types of leadership that represent three different levels—individual, dyad, and group—across a dynamic group decision-making optimization scenario.

Random coefficient models (RCM), including hierarchical linear modeling (HLM), multi-level structural equation models (MLSEM), and within and between analysis (WABA), based on the varient approach, are among the other approaches for analyzing multi-level notions (for details and organization science and leadership examples, see Bliese, Chan, & Ployhart, 2007; Dansereau et al., 1984, 2006; Dansereau & Yammarino, 2000, 2006; Drasgow & Schmitt, 2002; Gooty & Yammarino, 2011; Klein & Kozlowski, 2000; Yammarino, 1998; Yammarino & Markham, 1992). All these analytic tools for assessing multiple levels of analysis have procedures for testing multi-level meditation, moderation, and longitudinal (processual, developmental) notions.

4. Implications and conclusions

4.1. Theory building and theory testing in OSL

Theory or theory building, and data or theory testing, require an interplay that recognizes the importance of both notions (see Van Maanen, Sorensen, & Mitchell 2007); and considering multi-level issues can foster a balance between and an integration of these inductive and deductive processes (Dansereau et al., 1984; Yammarino & Dansereau, 2009a). Addressing multi-level issues in theory building will help overcome “what theory is not” (Sutton & Staw, 1995; Weick, 1995) and facilitate internal consistency, logic, clarity, novelty, and contribution—all key dimensions of “good” theory (Klein & Zedeck, 2004; Whetton, 1989). Likewise, incorporation of multi-level issues into theory testing will help address “poor” methods and data (Dansereau & Yammarino, 2006; Dansereau et al., 1984; Yammarino & Dansereau, 2009a; Yammarino et al., 2005) and enhance internal logics, sampling, data collection, statistical analyses, and drawing of inferences—all key dimensions of “good” methods (see Van Maanen et al., 2007).

The multi-level issues presented and illustrated above for ET and OSL can facilitate and enhance understanding of all these aspects of organizational and leadership research. Theory and theory building without levels of analysis is incomplete; data and theory testing without levels of analysis is incomprehensible. These “realities” hold for both ET and OSL, as aligned and juxtaposed above; and OSL scholars can learn lessons regarding the importance of multi-level issues from scholars' work in the more-established ET realm.

For example, evolutionary theory scholars often discuss competition at the organism level and cooperation at the species level that can occur simultaneously; and they assess, measure, and analyze these ideas at multiple levels to draw conclusions about them in terms of MLST (multi-level selection theory) (e.g., Gould, 2002; Sober & Wilson, 1998; Wilson, 1980). The former idea, competition, is an example of a wholes (homogeneity) perspective at the organism level; the latter idea, cooperation, is an instance of a wholes perspective at the species level; and the simultaneity means the formulation is a cross-level one in nature. So, we have a clear example of a cross-level wholes formulation from the organism to the species level that then can be assessed and tested to determine its merit and validity for ET.

An analogous case for OSL scholars might be the study of competition and cooperation in terms of individual performance and decision making differences together with team performance and decision making differences of those same individuals (e.g., Dionne & Dionne, 2008; Yammarino & Dansereau, 2009a). In this instance, there is a wholes perspective endorsed at the individual level (individual differences), a wholes perspective employed at the team level, and a cross-level formulation that is of interest. Similarly, Van Vugt et al. (2008) discuss the evolution of leading and following as a solution to a social coordination problem involving, among other elements, intra-group peacekeeping and inter-group competition. In this case, there is a wholes perspective employed at both the leader (individual level) and the group level, and thus a cross-level (wholes) formulation of focus. The constructs in these formulations can then be measured and analyzed at multiple levels to assess their merit and validity for individual, team, and cross-level behaviors in organizations and for leadership, decision making, and performance. As such, we have the parallel examples in OSL (to that from ET) of cross-level wholes formulations and effects from the individual to the team levels. Thus, the example from the more mature and established field of ET provides scholars with some potential insights to the study of the newer instances in OSL, and levels knowledge is transferred or translated across disciplines to enhance this latter field of study.

ET, as a well established interdisciplinary approach, also endorses the position that simple notions can explain complex phenomena (e.g., Gould, 2002; Wilson, 2002; Wolfram, 2002). For example, Gould's (2002) comprehensive review of evolu- tionary theory, using a levels-of-analysis perspective, recounts the history of evolution from simple to complex explanations and then back to simple explanations of evolution and its various aspects and applications at multiple levels. Wolfram (2002), also cognizant of levels of analysis, similarly shows how simple computational dynamic models (simulations) at a focal level, can explain a variety of simple and complex evolutionary ideas which may occur at higher or lower levels. Likewise, Stix (2008) contrasted the current competing evolutionary theories of human origins and migrations—the more complex multi-regional (higher-level) theory that posits modern characteristics evolved from archaic hominid populations in Africa, Asia, and Europe that inter-bred so they remained a single species; and the simpler (lower-level) out-of-Africa theory that asserts humans with modern traits left Africa and settled the world. He demonstrated that the most recent data from DNA analysis and tracking favor the latter, simpler view.

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In all these cases, as in science in general, simple explanations are preferred to complex ones, especially when they account for phenomena equally well; and levels of analysis offer one way to help clarify and simplify such explanations. So, for OSL, learning from the mature established ET field, simple notions or theories can hold great promise for explaining a variety of both simple as well as complex behaviors in organizations at various levels of analysis. Complexity, and explaining complex behaviors, does not require complex underlying rule structures (i.e., complex theories or ideas); and levels of analysis issues provide a way to frame such explanations (see Wolfram, 2002; Yammarino & Dansereau, 2009a).

As noted by Yammarino and Dansereau (2009a), however, organizational and leadership research is currently in a “complex” phase, after having been in a much “simpler” phase earlier in its history. To help jump-start a return of the field to simpler explanatory times, they develop and illustrate four simple OSL theories using a levels-of-analysis perspective to account for complex phenomena. And importantly, in terms of the etiology of these theories, all four have their foundations in evolutionary theory ideas which serve as the ultimate explanation of why the behaviors in the theories exist (see Scott-Phillips, Dickins, & West, 2011).

Theory 1 asserts that option cutting and commitment are positively related based on between-persons differences (inter- individual differences or whole persons); a level-specific theory at the person level of analysis. From an evolutionary theory per- spective, Yammarino and Dansereau (2009a) note that this effect may matter because without it or something similar, it would likely be impossible for individuals to make decisions and stay with or attach to them (also see Scott-Phillips et al., 2011). The assertion means that an individual can commit to a course of action and pursue it. Without this capability, or something similar to it, when faced with a threat, there would be too many (virtually unlimited) options to pursue, and the individual would likely experience analysis paralysis. In such a situation, if a predator was starting to attack, this paralysis would have resulted in extinc- tion. Thus this effect, or something like it, may be quite important for the survival of humans. Those individuals with capabilities to cut options and become committed may have been likely to pass that characteristic on in an evolutionary sense.

Theory 2 asserts that investments and returns are positively related based on between-dyads differences (whole dyads); a level-specific theory that emerges at the dyad level of analysis. From an evolutionary theory perspective, Yammarino and Dansereau (2009a) note that this effect may matter because without it or something similar, it seems unlikely that individuals would have seen benefits from interacting with others (making investments), even if only for a very short time (also see Scott-Phillips et al., 2011). For example, those individuals who are likely to see returns (for example, of a sexual nature) from interacting with others are those who are more likely to have children. Thus the capability implicit in the assertion would be passed on in an evolutionary sense. Moreover, without this effect, it would be difficult for a child to survive because a child cannot fend for himself or herself. Thus, if providing for the child did not provide some benefit to the parent or other caregiver, the child would be unable to survive.

Theory 3 asserts that interdependence and cohesion are positively related based on between-groups differences (whole groups); a level-specific theory that emerges at the group level of analysis. From an evolutionary theory perspective, Yammarino and Dansereau (2009a) note that this effect may matter because without it or something similar, it seems unlikely that people would have cooperated with or bonded to one another (also see Scott-Phillips et al., 2011). Specifically, when faced with the need to hunt or protect themselves, individuals are almost by definition interdependent with each other because they would likely be unable to eat or survive without one another. As a result, cooperation and cohesion serve as ways for human beings to compete successfully relative to other species; and in a somewhat interesting way, cooperation provides a way to compete with other species. Because those individuals who cooperate will likely survive, it is their capability for group-level cooperation and cohesion in response to interdependence that would be passed on in an evolutionary sense.

Theory 4 asserts that titles and expectations are positively related based on between-collectives differences (whole collec- tives); a cross-level theory from person to dyad to group to collective levels of analysis. From an evolutionary theory perspective, Yammarino and Dansereau (2009a) note that this effect may matter because without it or something similar, it seems unlikely that language would have developed (also see Scott-Phillips et al., 2011). Language provides a way to learn from the knowledge of the past about how things occur. Thus the ability to title an event and use this title in the future provides an advantage in the competition of a species for survival. Obviously, without language, each event and approach to it would have to be rediscovered by each generation. With the learning of words (titles) and their meaning (expectations), it becomes possible to use the successes of the past to cope with the present. As such, this capability increases the likelihood of human survival and so would be passed on in an evolutionary sense.

Likewise, relying on the combination of “simpler” ideas and levels of analysis and evolutionary theory perspectives, Lawrence (2010) attempts to explain and understand leadership as a function of four independent and at times conflicting basic human drives that have evolutionary and biological bases. These are the drives (1) to acquire what is needed to survive and for the conception and survival of offspring; (2) to defend oneself and offspring; (3) to bond, or form long-term mutually caring and trusting relationships with others; and (4) to comprehend, or learn, create, innovate, and understand oneself and the environ- ment. To accomplish this purpose, Lawrence (2010) relies on both of Darwin's books (1859, 1871). In the latter book, The Descent of Man, Darwin notes the most important difference between humans and other species is our innate moral sense or conscience. As such, while the first two drives are common across species, the third and fourth are unique to humans.

Lawrence (2010) builds the case that our brain has evolved for, and has specific structures involved in, leadership and decision making which integrate and resolve conflicts among the four drives. He asserts that when all four primary drives are fulfilled and balanced long-term by leaders who also help and influence their followers and stakeholders to do likewise, then an optimal state of leadership, good (moral) leadership, will be achieved. For Lawrence (2010), misguided (amoral) leadership is when leaders as well as followers and stakeholders whom they influence fulfill one or some drives but ignore or suppress other drives; bad (immoral) leadership is when leaders lack the drive to bond and have influence over others

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and only fulfill their own drives to acquire, defend, and comprehend; and evil (immoral) leadership, a subset of bad leadership, is the actual killing of others.

So, for Lawrence (2010), anyone with a conscience or a moral sense has the potential to be a good leader and can be involved in leadership per se. He also uses his approach to describe and categorize a number of historical and contemporary leaders in the political, economic–corporate, and religion–art–science arenas. Thus, Lawrence (2010) presents an evolutionary-based approach to leadership that includes multiple levels of analysis—the first and second drives (to acquire and defend) are individual-level phenomena; the third drive (to bond) is fulfilled at the dyad, group/team, and higher levels; and the fourth drive (to comprehend) can be viewed as multi-level and cross-level in nature.

As these “simple” theories of Yammarino and Dansereau (2009a) and Lawrence (2010) employ both evolutionary theory and levels-of-analysis perspectives as foundations, they can serve as exemplars of the transfer or translation of learning across fields from ET to OSL. In essence, as developed and illustrated by these scholars, multi-level OSL theory and research must become the norm, not the exception, for the advancement of our field, and can be informed by the alignment of the analogous multi-level issues from ET.

4.2. Multi-level issues in OSL

Individual differences notions, one-to-one dyadic (interpersonal) relationships, group and team dynamics, theories and models within different types of organizations and industries, strategic-level ideas, and cross-cultural approaches are all levels- of-analysis conceptualizations and formulations that OSL scholars should address more fully. In these cases, as in ET, higher levels of analysis also can serve as moderators, mediators, and contexts (environments) in various multi-level approaches that should be considered in future theory and research. As in ET, constructs and variables must be defined explicitly to include single or multiple levels of analyses, and relationships must be specified explicitly to incorporate levels of analyses, whether single- level, multiple levels, or multi-level in nature.

Measures and assessments, in turn, as those in ET, must be developed with the level(s) of analysis of the concepts, constructs, and theory in mind. Measurement and assessments must be conducted at the appropriate level(s) of analysis; and, at a minimum, justification and tests for aggregation are necessary when concepts are measured and assessed at a lower level than their theo- retical specification. Next, like in ET, the choice of a data-analytic technique should be driven by theory and include the appropri- ate multi-level tools and analyses. Because many OSL formulations are process-oriented or developmental, as in ET, designs and data collection must be longitudinal in nature, requiring the use of appropriate longitudinal multi-level data analytic techniques. Finally, in terms of drawing inferences, analogous to procedures in ET, alignment of theory (with explicit multiple levels-of- analysis specifications) and data (with explicit incorporation of multiple levels of analysis in measurement and analysis) must have a multi-level focus. When these concerns are addressed, OSL research will better emulate and align with more established work like in ET and understanding in our field will advance to the cutting edge.

As noted by Nicholson and White (2006) and Van Vugt et al. (2008), there is a growing interest in ET ideas and an increasing application of them to a variety of areas “in and around” organizations and leadership (e.g., cognitions, decision making, emo- tions, motivation, negotiation, interpersonal relations, group dynamics, ethical behaviors, gender issues, social structure, and culture). The use of analogous multi-level concepts and issues in ET and OSL provide one way to begin to address these ideas in future work. For example, from a more micro perspective, using behavioral genetics notions, Ilies et al. (2006) point out developments that occur in genetic studies of between-individual differences variables, genetic influences on organizational out- comes, genetic–environment interactions on behavioral constructs, and person–situation interactions on attitudes and perfor- mance. From a more macro perspective, using ET and Darwinian ideas, Pierce and White (1999, 2006) assert and demonstrate that the resources context (a higher level of analysis) affects emergent social structure and behaviors in groups and collectives (lower levels of analysis). From a more multi-level perspective, Yammarino and Dansereau (2009a) use ET ideas and explanations to understand the etiology of the effects for four theories that constitute a new kind of OSL. In all these cases, a multi-level perspec- tive on ET and OSL in combination is employed, and multi-level issues in ET offer an opportunity to expand our knowledge of multi- level theory building and theory testing in OSL.

There are many ways to pursue OSL topics using the multi-level approach described here. Focusing on leadership, we provide some additional examples from previous research that have begun to pursue new directions and lines of work that can be further enhanced based on this multi-level approach. The examples are organized in terms of first, theory development from inductive and deductive perspectives; second, literature reviews; third, validity; and fourth, empirical testing. Modeling these leadership exemplars in future research would result in theories that are anchored in a specific level or multiple levels of analysis, theoretically and empirically, parsimonious or unique from each other, and repeatedly predictive and observable. Without movement in this multi-level direction, we will have theories that are limited as they refer to nothing that can be observed and, therefore, are not testable, are redundant, are not parsimonious, and ultimately are not predictive.

First, in terms of theory development in leadership, multi-level concepts are particularly important because there is a focus on leaders as persons (e.g., leader traits, perceptions of leaders, implicit leadership theories) and others who are followers connected with leaders in dyads or groups/teams, typically within multiple collectives (e.g., departments and organizations). Scholars can then ask, for example, what leadership variables might explain the evolution of independent individuals to a dyad, group, or team composed of interdependent individuals?

A study by Zhou and Schriesheim (2009) illustrates a somewhat qualitative and inductive way to gain insights to this evolu- tionary process. Zhou and Schriesheim (2009) focused on both leaders and followers simultaneously and developed hypotheses

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about how leaders and followers may perceive each other and when they may be in agreement with one another. Although focused on LMX, this approach can be employed to build theories about the development of leader–follower relationships based on other leadership views. In another qualitative and somewhat inductive study, Wallis, Yammarino, and Feyerherm (2011) used observational and interview techniques in a non-structured way to develop an understanding of the relationship between leaders and followers. Although their results supported the notion of individualized leadership (Dansereau, Yammarino, et al., 1995b), this approach can be used to clarify how leaders move (or evolve) from independent individuals to individuals who are interdependent with their followers one-to-one in dyads. This evolutionary process seems to be poorly understood; but inductive research similar to that of Zhou and Schriesheim (2009) and Wallis et al. (2011) would appear to help to clarify it.

Taking a more deductive perspective, current theories of leadership may be enhanced by further development from a multi- level perspective. In this case, a key issue is whether a particular theory can apply in different ways at multiple levels of analysis. Yammarino, Dionne, Schriesheim, and Dansereau (2008), for example, develop and extend authentic leadership theory and the concepts of authentic leadership per se and positive organizational behavior to include several levels of analysis and multi- level notions. Such evolutions of existing theoretical approaches that focus on multiple levels do not preclude theories that focus on solely one level and not other levels, but do offer another venue for future research to pursue.

Second, in terms of literature reviews, there are numerous contemporary approaches to leadership, each with their own concepts and relationships. There are, however, very few reviews that focus on the meaning of key concepts and relationships along with the level(s) of analysis that are hypothesized in the theories and with a careful examination of what level(s) of analysis are actually tested in the studies reviewed. As an exception, Schriesheim, Castro, and Cogliser (1999) provide a compre- hensive review of the evolution of the LMX literature and raise very specific questions about levels issues for LMX. Similar levels- based questions and issues can arise for other leadership views but have been largely ignored in literature reviews of these other leadership approaches. An exception, for this case, is the comprehensive levels-based literature review of 17 leadership theories by Yammarino et al. (2005). Their review of the literature suggests that many of the levels of analysis problems described by Schriesheim et al. (1999) about LMX may be fairly widespread throughout the leadership theories in the extant literature. Clearly, much more work of this type is needed in future literature reviews of leadership, especially for those theories not covered by Schriesheim et al. (1999) and Yammarino et al. (2005).

Third, in terms of validity, a key question that arises is, what are the significant differences among the various approaches to leadership both theoretically and empirically? In terms of parsimony, this question can be phrased as, are there basic (simpler) processes underlying leadership that justify all, or a number of, the different approaches? Data showing convergence and discrim- ination validity seems needed across studies and approaches to address these issues, and levels of analysis are part of the solution toward parsimony and simplicity in leadership work. For example, in examining LMX, Schriesheim and Cogliser (2009) provided a way to examine such issues via levels and raised questions about the meaning of LMX relative to other more basic variables. Moreover, Yammarino and Dansereau (2009a) offered two parsimonious levels-based leadership theories, and empirical evidence for their validity, as a way to integrate and simplify several leadership approaches. Such levels-of-analysis-related validity studies seem necessary to understand the commonality across leadership work, but they could also provide validation of the differences among multiple theories of leadership.

Fourth, in terms of empirical testing, the notion of levels of analysis and multi-level issues creates tremendous challenges and opportunities for theory testing in OSL. In an organizational setting, the difficulty arises from the nesting and potential dependen- cies of individuals in dyads, groups/teams, and collectives such as departments and organizations. As pointed out by Schriesheim, Castro, Zhou, and Yammarino (2001), the setting creates the possibility of theorizing “A” but testing “B.” In their review and illus- tration, Schriesheim et al. (2001) indicate that without appropriate levels-based tests, researchers have no real idea about the level(s) potentially associated with observed effects in data collected in the setting. The dominant solution in the literature is to assume that (1) a particular level (levels) is (are) relevant, (2) that effects will not occur if the level is incorrect, and (3) that effects will occur if the level is accurately specified. Because of the nesting in the setting, however, that is not necessarily the case and these assumptions may not hold. Effects may occur at only one level, or be a manifestation of higher- and lower-level effects simultaneously, or effects may not occur at one level because the effects hold at a lower level. There are a number of illus- trations of how to deal with these various types of multi-level effects and the multi-level analytic techniques to rule out (test) the effects of levels of analysis that seem less plausible based on the data (e.g., Dansereau & Yammarino, 2006; Dansereau et al., 1984, 2006; Klein & Kozlowski, 2000; Schriesheim et al., 2001; Yammarino, 1998). Moreover, as multi-level issues are considered more comprehensively, then various methods such as RCM/HLM, MLSEM, and WABA can be compared and used simultaneously rather than separately (see, for example, Gooty & Yammarino, 2011; Klein & Kozlowski, 2000).

In addition, longitudinal studies are clearly necessary to address evolutionary-type questions in OSL. To focus solely on con- cepts and relationships over time without regard for levels of analysis and multi-level issues over time will greatly hamper theory building and theory testing. Methods are available to assess the degree of interdependence among individuals and other entities over time and changes in entities over time that allow for interdependencies that do not involve just aggregation (see, for exam- ple, Dansereau et al., 1999). Addressing such issues may provide a window into the role that leaders play in the evolution or emergence of groups and teams (e.g., Yammarino & Dansereau, 2009a). Interestingly, a focus on multi-level effects over time does not preclude concurrent investigations of less changeable characteristics of entities. Longitudinal studies allow for an assess- ment of stability and change in, on the one hand, concepts and relationships, and on the other hand, entities and levels of analysis. Such work allows scholars to tease out those factors in a study that are less changeable than others. The interaction of more stable (e.g., whole person) variables and effects with less stable (e.g., person parts) variables, as well as assessments of the stability and change or evolution of higher-level entities and variables, would provide richer, more comprehensive, and likely more successful

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theories in leadership. Such a multi-level approach to longitudinal theory building and testing in leadership and all organization science can be based on the successes of the analogous multi-level approaches in ET and other sciences.

5. Conclusion

Overall then, there are three primary transfers or translations of learning, lessons learned so to speak, for OSL scholars to gain from the exploration of ET and multi-level issues here. First, as shown for ET, levels of analysis and multi-level issues are critical for the development of a field to become a mature and established discipline. Therefore, it is important to include a consideration of multi-level issues in the formulation and testing of OSL notions for our field to develop further and faster. Second, as discussed for ET, the formulation of simple ideas that are well tested are a hallmark of an established discipline, and levels of analysis and multi- level issues provide a way to facilitate that scientific research process. OSL scholars might strive to use levels of analysis and multi- level issues to formulate and test simple notions in a rigorous way. Third, again as shown for ET, levels of analysis and multi-level concerns are not solely methods issues, but are also theoretical issues. So, for OSL to advance as a field and mature into a more established discipline, multi-level issues and levels of analysis should be addressed in both theory building (conceptualization) and theory testing (methodology). While employing insights from the multi-level notions in evolutionary theory is by no means easy, doing so will inform organization science and leadership scholars and bring the goal of better understanding in the field a bit closer to realization.

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  • Multi-level issues in evolutionary theory, organization science, and leadership
    • 1. Introduction
    • 2. Evolutionary theory
      • 2.1. Fundamental notions
      • 2.2. Evolutionary psychology
    • 3. Multi-level issues and concepts
      • 3.1. Levels of analysis
        • 3.1.1. ET and levels
        • 3.1.2. OSL and levels
      • 3.2. Units of analysis
        • 3.2.1. ET and units
        • 3.2.2. OSL and units
      • 3.3. Adjacent levels: multiple levels and multi-level effects
        • 3.3.1. ET and multiple levels
        • 3.3.2. OSL and multiple levels
      • 3.4. Levels over time
        • 3.4.1. ET, time, and levels
        • 3.4.2. OSL, time, and levels
      • 3.5. Fallacies
        • 3.5.1. ET and fallacies
        • 3.5.2. OSL and fallacies
      • 3.6. False dichotomies
        • 3.6.1. ET and dichotomies
        • 3.6.2. OSL and dichotomies
      • 3.7. Analytical tools
        • 3.7.1. ET and tools
        • 3.7.2. OSL and tools
    • 4. Implications and conclusions
      • 4.1. Theory building and theory testing in OSL
      • 4.2. Multi-level issues in OSL
    • 5. Conclusion
    • References