Keywords

Entrepreneurship scholars have paid significant attention to the role of theory in their research. Indeed, publishing in most top entrepreneurship and management journals requires a paper to contribute to theory (Hambrick, 2007; Shepherd, 2010). Although some scholars question this dominant role of theory (Hambrick, 2007; Pfeffer, 2014), few disagree about the salience of theory building for furthering knowledge (Suddaby, 2014a). For instance, business scholars have called for new theories of entrepreneurship (Shepherd, 2015), management (Barkema et al., 2015), compassion (Rynes et al., 2012), and so on. Despite this deep recognition of the salience of theory building, actually developing theory is a decidedly difficult task. Accordingly, scholars have become increasingly interested in the process of theorizing—namely, how to build theories. This emerging literature stream provides many tools and approaches to theorizing, including engaged scholarship (Van de Ven & Johnson, 2006), metaphor (Cornelissen, 2005), and finding the balance between novelty and continuity (Locke & Golden-Biddle, 1997). This work has made significant contributions by offering varying insights into specific parts of the theorizing process—namely, different methods to initiate the creation of a new theory, different approaches to forming new explanations of entrepreneurial phenomena, and different ideas of what a theoretical contribution entails, respectively.

However, where does this current literature leave nascent entrepreneurship theorists? It appears to leave them with a wide range of potential “theorizing tools” without providing a coherent picture of how these many tools fit together. Namely, there is scant direction regarding when to use a specific theorizing tool vis-à-vis another (i.e., substitutes) and which combinations of tools (i.e., complements) can be harnessed in the theorizing process to further the entrepreneurship field. Therefore, although the different approaches in the literature address distinct and often isolated questions about how to build specific parts of theory, they fall short of explaining how and when to utilize the various tools to facilitate entrepreneurial theorizing. As such, in this chapter, we integrate the numerous threads of theory building in entrepreneurship and then extend this integration to a particular theorizing approach—pragmatic empirical theorizing.

Through our literature review on theory building in entrepreneurship, we integrate the many individual components of theory building to gain a more holistic picture.Footnote 1 This budding literature stream shows the increasing importance of narratives and storytelling in theorizing (Pollock & Bono, 2013), demonstrating that compelling theories are, in essence, compelling stories. A compelling story centers on the main character (or characters) who grapples with a formidable entity (narrative conflict) within a narrative setting. The story is woven together by a specific sequence of events and is made comprehendible by its plot. By the end of the story’s narrative arc, there is a resolution to the story’s problem and/or the problem faced by the main character(s). As such, we center our review of theory building on the five key elements characterizing every compelling story: conflict, character, setting, sequence, and plot/arc.

We hope to make three main contributions to the entrepreneurship scholar community by reviewing and organizing the literature on theory building. First, by organizing the theory-building literature, we integrate “like tools” to better understand how they enable specific parts of the theorizing process. Second, this organizing allows us to connect different parts of the theorizing process. In turn, the resulting deeper understanding within and across theorizing parts provides a clearer “big picture” of the process of building interesting theories to further the field of entrepreneurship. Finally, we offer pragmatic empirical theorizing—a theorizing tool we believe has significant promise to advance entrepreneurship theories. At its core, pragmatic empirical theorizing harnesses quantitative empirical findings to motivate theorizing as part of an abductive inquiry process.

Theorizing Trigger—The Narrative Conflict

Arguably the most difficult part of theorizing is identifying an anomaly or tension to initiate and guide the theorizing process. This task involves a creative process requiring both extensive imagination (Mills, 1959) and keen observational powers—skills that March (1970) claims can best be obtained by learning about the observational habits of exceptional storytellers.

In storytelling, narrative conflict reflects the struggle between two powerful entities, for example, human versus human, human versus nature, or human versus god. In theory building, narrative conflict represents the struggle between two realms of knowing: namely, the empirical world of phenomena and the scholarly world of theoretical literature that aims to explain the empirical world. Conflict arises not only from within these worlds but also—perhaps more typically—from gaps between them. We examine both types of conflict to establish the different techniques entrepreneurship scholars use to “trigger” the theorization process.

Conflict in the Literature

Becoming immersed in the literature can unveil numerous paradoxes, problems, challenges, and puzzles. A paradox entails “contradictory yet interrelated elements that exist simultaneously and persist over time” (Smith & Lewis, 2011: 382). For example, a paradox can arise in the form of an underlying tension between two sets of relationships that seem to make sense when considered individually but appear contradictory when considered simultaneously. This scenario can trigger theorizing as an attempt to reconcile the paradox. Paradoxes stem from changes in systems, differences in individual and collective identities, competing organizing modes/designs, and different stakeholder goals (Smith & Lewis, 2011). They also arise across categories of learning, belonging, organizing, and performing and reflect (or generate) a tension that can motivate more extensive theorizing as an attempt to resolve the focal paradox (Poole & Van de Ven, 1989). For instance, in their paper on the effect of negative feedback on new ventures’ organizational identity (OI), Domurath et al. (2020: 2) explain,

On the one hand, negative feedback indicates that the achievement of future venture goals is threatened, which can raise doubt among organizational members about who they are as an organization (Corley and Gioia, 2004), thus weakening OI (Gioia et al., 2000). On the other hand, organizational members can use negative feedback as a legitimization of their distinctiveness, thus maintaining or even enhancing OI strength (Clark et al., 2010; Gioia et al., 2000). To date, we do not have a theoretical explanation of when a venture’s OI is more or less weakened upon negative feedback events.

Another approach to engaging the literature to trigger theorizing is problematization. Problematization refers to “challeng[ing] the value of a theory and explor[ing] its weaknesses and problems about the phenomena it is supposed to explicate” (Alvesson & Karreman, 2007: 1265–1266). This approach highlights the need to rethink existing theory and perhaps the need to change direction. Problematizing requires researchers to both gain an understanding of the literature and keep an open mind regarding that literature. By approaching the literature with an open mind, entrepreneurship scholars can allow the literature (as data, in line with a grounded theory approach) to “speak to them” to uncover (in a bottom-up way) problems within or across literature streams (see Chapter 6). Moreover, problematizing entails significant rhetorical ability in creating the “gap” between the literature and the real world or in explaining a logical flaw in previous theory (Locke & Golden-Biddle, 1997) because this task likely (hopefully) involves more than simply incremental gap-spotting. Instead it involves the construction of a considerable gap that contests critical assumptions (Sandberg & Alevesson, 2011). For example, problematization was used in a recent study (Patzelt et al., 2021: 2) on employees’ emotions resulting from entrepreneurial project failure to identify a major gap in previous research:

However, although existing work provides insights into the individual and organizational factors that can help employees manage their negative emotions after the failure of entrepreneurial projects, neither the corporate entrepreneurship nor the leadership literature acknowledges the potential role of supervising managers in the aftermath of entrepreneurial project failure. Ignoring supervisor-employee dyads in this context is a critical omission not only because supervisors “are formally responsible for monitoring and regulating the performance of others” (Sheridan and Ambrose, 2020: 2) but also because it is well known that supervisors shape their subordinate employees’ attitudes toward their organizations (Bear et al., 2010; Wayne et al., 2002) and their behaviors at work (Judge et al., 2006; Settoon et al., 1996). Indeed, the success of entrepreneurial projects depends, in part, on managers leading employees such that they yield high individual performance. (Reid et al., 2018; Simsek et al., 2015)

Scholars can ask contrastive questions to help problematize a situation or explanation by referring to various elements of an event (i.e., an allomorph) or by emphasizing a focal fact and contrasting it with one or more alternative(s) (i.e., fact and foil) (Tsang & Ellsaesser, 2011). Contrastive questions are so useful because by asking better questions, entrepreneurship scholars can begin to provide better explanations of different phenomena. Accordingly, Abbot (2004) suggests that problematization can be spurred by reversing a well-known proposition, switching figure and ground, using emotional language, and—as we discuss below—putting things in motion (Abbot, 2004).

Conflict Revealed Through Entrepreneurial Phenomena and Entrepreneurs’ Practices

As discussed above, the data that triggers theorizing can come from the literature; however, it can also come from the phenomenon of interest—namely, through knowledge discovery beginning with “observation by the senses” (Locke, 2007: 888). Like with conflict in the literature, in the case of this observation, entrepreneurship scholars need to approach the focal phenomenon and data with an open mind, or else they run the risk of forcing the data and/or its interpretation to fit previous theories. Keeping an open mind (i.e., withholding prior expectations as much as possible) facilitates the discovery of interesting research problems during data collection and analysis; that is, it enables “the high potential for an empirical response and a novel insight that adds significantly to—or against—previous understandings” (Alvesson & Karreman, 2007: 1268). Further, in the case of grounded theory, keeping an open mind can “elicit fresh understandings about patterned relationships” and social interactions (Shah & Corley, 2006; see also Glaser & Strauss, 1967; Turner, 1983). For instance, by observing social entrepreneurs, McMullen and Bergman (2017: 244) found that these entrepreneurs sometimes continue their venturing efforts even after solving their original target problems. This observation challenged the dominant view that social ventures are temporary organizations that are terminated once they solve their social problems:

SE [social entrepreneurship] is often conceived of as an institutional patch that arguably succeeds by rendering itself no longer necessary, implying that it is temporary (e.g., Mair & Martí, 2009; McMullen, 2011; Santos, 2012). But if this is true, then how do we reconcile it with Negroponte’s reaction to Intel’s and Microsoft’s foray into the LDC market for inexpensive laptops? If the focus of social entrepreneurship is truly on value creation, not value capture, and SE is indeed an institutional patch, then would it not be reasonable to expect Negroponte to jump for joy and declare his mission accomplished upon any announcement that multinational corporations (MNCs) like Intel or Microsoft have taken up his cross to bear?

A significant data source for motivating theorizing on entrepreneurial phenomena can come from a practice orientation—namely, how entrepreneurs establish and enact entrepreneurial activities. Entrepreneurial theorizing that is triggered in such a way helps uncover paradoxes and problems of practical value to entrepreneurs. To undertake such theorizing, scholars may need to either zoom in on specific activities in context or zoom out to observe relationships and patterns across practices to more deeply understand the connections between and potential of activities, tools, and interactions (Sandberg & Tsoukas, 2011). Indeed, when undertaking an entrepreneurial activity, founders and/or employees often become one with the task (Dreyfus, 1995). However, if the effectiveness of an activity temporarily breaks down—namely, if an individual experiences a momentary disconnection from others and/or things—that individual separates from the task and engages in deliberate reflection (Sandberg & Tsoukas, 2011). In the entrepreneurial context, such temporary breakdowns unveil problems for entrepreneurs and thus opportunities to theorize to gain a more comprehensive and practically useful understanding of such situations and/or tasks. This type of theorizing helps “explore new terrain and develop novel ideas, thus potentially overcoming the inherent conservatism in well-established frameworks” (Alvesson & Karreman, 2007: 1267).

Indeed, according to Weick (1974), theorists should focus on everyday events, ordinary places, common questions, micro-organizations, and absurd organizations. When scholars seek, observe, and/or question everyday events in ordinary places, theorizing can itself become more commonplace instead of being bound solely to Fortune 500 companies or the “armchair.” Such theorizing begins with observing a pattern and then formulating robust explanations for the pattern underlying the focal task (and organizing tasks more generally). Likewise, focusing on micro-organizations helps deemphasize the centrality of the thing (i.e., the organization) and instead highlights the process (i.e., the organizing). Finally, studying absurd organizations—almost by definition (of absurd)—challenges theorists’ core assumptions, which is a fundamental step toward theorizing to expose new research terrain (Weick, 1974) and contribute to knowledge.

Engaged scholarship can also trigger new theorizing. Engaged scholarship refers to “a collaborative form of inquiry in which academics and practitioners leverage their different perspectives and competencies to co-produce knowledge about a complex problem or phenomenon under conditions found in the world” (Van de Ven & Johnson, 2006: 803). This form of scholarship is likely most beneficial when projects are designed to explore complex real-world problems, be collaborative learning endeavors, endure for a prolonged period, and harness multiple frames of reference (Van de Ven & Johnson, 2006). Such problem-driven research requires scholars to at least minimally engage with entrepreneurs (or related stakeholders, such as venture capitalists) as they perform their activities, to be open to new experiences (compared to existing theories), and to self-reflect on their engaged scholarship role (see Van de Ven & Johnson, 2006). With this approach, scholars are taking a step toward addressing what is generally referred to as the large gap between theory and practice (Rynes et al., 2001). Indeed, collaborating with entrepreneurs throughout the research process enables theorists to formulate problems that are grounded in the experiences of those actually engaged in the various entrepreneurial tasks under exploration—namely, they can investigate real-world problems faced by entrepreneurs whose solutions contribute to the knowledge of both academics and practicing entrepreneurs.

Conflict Between the Entrepreneurship Literature and Entrepreneurial Phenomena

Scholars have devoted considerable effort to debating the relative importance of phenomenal gaps versus gaps in the literature. Those who advocate for the former tend to emphasize empirical facts (Hambrick, 2007; Pfeffer, 2014) and are backed by intellectual giants in social theory, including Durkheim (1895/1964: 15), who claims that researchers should move from “things to ideas,” not from ideas to things. However, according to the pragmatic consensus—as backed by a long succession of scholars beginning with Peirce (1934), extending to Merton (1967), and advancing today with Weick (2014)—effective theorizing is a process whereby a researcher moves iteratively between gaps observed in the phenomenal world and those observed in the existing literature. Indeed, such gaps create a tension that often triggers the need for a new theory.

After triggering the theorizing process by revealing or creating a conflict in entrepreneurship—a paradox, problem, or challenge—the focal entrepreneurship scholar then needs to conceive of a research idea. This idea may start as a simple construct or guess that the scholar then constructs into a theory to explain an entrepreneurial phenomenon.

Conceiving and Constructing Entrepreneurship Theories—Building Stories

We organize the research on conceiving and building entrepreneurship theories using a narrative framework because this framework reinforces the idea that effective theorizing entails adeptly interweaving prior knowledge (i.e., existing literature) and emerging knowledge (i.e., new empirical observations) of entrepreneurship.

Identifying the Core Constructs of an Entrepreneurship Theory: The Main Characters

Compelling stories center on main characters (Pentland, 1999)—namely, actors whose behavior best portrays the focal narrative. In storytelling, an actor is a person, animal, or entity whose experience is the story’s central point. Similar to stories being built around main actors, theories are built around core constructs (Pentland, 1999). Accordingly, a critically important step early in the theorizing process is formally naming core constructs even if the theoretical narrative remains unclear. At this point, constructs also tend to be somewhat fuzzy, but the act of formally naming a phenomenon of interest is a critical step in conceptually separating a specific phenomenon from the collective “noise” of routine empirical experience and/or separating specific core constructs from the collective “noise” of previous entrepreneurship research.

Theorists have implemented numerous strategies to name constructs. Arguably, the most common strategy is to simply use a commonplace term that captures the phenomenon of interest most closely. For example, the rather general word performance has been used to refer to the array of activities by which entrepreneurial organizations are evaluated. Prominent sociologist Max Weber (2001: 63) recommended this approach, encouraging scholars to use “the nearest and most descriptive words” from everyday language to name constructs. However, there are clear downsides to using commonplace terms to name constructs. In particular, scholars run the risk that adopting words from everyday language will weigh down constructs with too much “surplus meaning” (Cronbach & Meehl, 1955). Indeed, using the term performance invites scholars to infer—consciously or not—a range of meanings for performance based on individuals, machines, sports teams, and a variety of other entities and activities, thus markedly reducing the analytic precision of the construct. For example, strategic management performance can refer to an organization’s sustainable competitive advantage whereas entrepreneurial performance can refer to an organization’s growth.

Another similar strategy for naming constructs is to borrow an established construct from a related field. In organizational theory, for example, population ecologists have borrowed words like niche and species from the neighboring field of evolutionary biology (Freeman & Hannan, 1989; Hannan & Freeman, 1977). Borrowing a term from a related field partly resolves the lack of definitional precision stemming from using everyday language, but this approach does not fully solve the surplus-meaning issue. Returning to the previous example, population ecology has been criticized for using terms like species, a word that has a much more precise meaning when referring to living organisms (i.e., capable of interbreeding and producing viable offspring) than organizations. Indeed, according to Whetten et al. (2009), borrowing terms from other fields frequently creates more confusion (e.g., in levels of analysis, boundary conditions, etc.) than clarity in understanding phenomena.

A final strategy for naming constructs is to coin a new term to describe a phenomenon of interest. In management theory, Weick’s use of the term sensemaking is an apt example. This new word is a portmanteau of common preexisting terms that have acquired a unique and specific meaning due to Weick’s theorizing.

No matter what strategy is used, identifying and naming constructs are critical for theorizing because constructs are a source of agency or causality. In other words, when constructs and their relationships to phenomena of interest are described in greater clarity, the motivations and causal relationships in the associated theoretical arguments also become clearer (Suddaby, 2010; for other rigor-related aspects of theory building, see Donaldson et al., 2013). In theory, such clearly defined constructs necessitate precise definitions and specific boundary conditions/contexts in which they do and do not apply and thus help readers understand the focal theoretical arguments more fully. Indeed, when constructs are captured accurately, readers can quickly grasp their history, the motivation for their use, and the implications of their roles in the causal relationships being presented. It is worth mentioning, however, that construct clarity has limits. As Kaplan (1964) notes, enhancing definitional clarity ultimately leads to increasingly finer-grained distinctions that eventually fall outside understanding: the “more discriminations we make, the more opportunities we create for classification errors between borderlines” (Kaplan, 1964: 65).

Choosing a Perspective for Theorizing: Determining the Narrative Setting

In addition to having main characters, all stories occur in a narrative setting—that is, a specific time and place in which the main events occur. In a way, a story’s setting is as critical in explaining causality as the overarching conflict that defines the story and the main character’s motivations. Adept storytellers appreciate that context goes beyond a story’s backdrop and can play a decisive role in an argument—it is critical both to a theoretical argument’s credibility and to readers’ understanding of a theory’s causal logic—and by altering the context, a theorist can expose new conceptual terrain. In this section, we discuss a variety of strategies entrepreneurship scholars use to introduce new perspectives by modifying the philosophical settings within which theory is presented: namely, shifting ontology, moving up or down the ladder of theory complexity, moving back and forth between data and theory, and shifting the level of analysis.

First, scholars can introduce a new perspective by shifting the ontology of their research. Scholars typically use a specific theoretical lens to explore a phenomenon such that one philosophical perspective tends to dominate a particular research topic. Alternatively, research topics can be bifurcated by research streams that advance in parallel based on different philosophical underpinnings (e.g., research anchored in either a structural realist or a social constructivist perspective; Hassard, 1993). However, instead of sticking with just one philosophical approach, theorists can harness an ontological shift to produce creative insights that can be used to develop mid-range theories. An ontological shift comprises “changes in the ontological emphasis that maintain epistemic-ontological alignment” (Thompson, 2011: 755). Here, ontology refers to the nature of phenomena, and epistemology refers to the nature of knowledge about the phenomena (Gioia & Pitre, 1990). When shifting ontology, scholars must be sure to change the epistemology, or else they can compromise their constructs, which leads to ontological drift (Thompson, 2011).

One way to shift ontology for theorizing is to move from an entity-based ontology to a process-based ontology (or vice versa). Indeed, entrepreneurship theories tend to focus more on entities (e.g., organizations, entrepreneurs, and institutions) than processes (e.g., organizing, emergence, co-constructing). However, as an example, the notions of entrepreneur and institution (i.e., entities) can be considered as processes, such as venturing and institutionalizing. This theorizing approach does not eliminate or replace the entity construct but complexifies it, which can lead to different research logics of action that reflect different assumptions and orientations and can be used to address different research questions (see Morgan, 1980).

Second, scholars can also move up and/or down the ladder of theory complexity to conceive and build theory. According to Ofori-Dankwa and Julian (2001), two dimensions are vital in establishing the level of theory complexity: (1) relative endurance, which refers to the degree to which the core concepts of a (proposed) theory are represented as relatively stable (high endurance) or unstable (low endurance), and (2) relative exclusivity, which refers to the degree to which a single core concept (high exclusivity) or several core concepts (low exclusivity) form a model. Thus, as a 2 × 2 setup, there are four levels of theoretical complexity: Level 1 (simple complexity) involves high endurance and high exclusivity to offer theories of contingency, Level 2 (medium complexity) involves low endurance and high exclusivity to offer theories of cycles, Level 3 (high complexity) involves high endurance and low exclusivity to offer theories of competing value, and Level 4 (very high complexity) involves low endurance and low exclusivity to offer theories of chaos (Shepherd & Suddaby, 2017).

Abstracting one’s theorizing—that is, moving up the ladder of theory complexity—can provide the foundation for a meta-paradigm perspective, allowing scholars to consider diverse approaches to theory building together as a way to bridge paradigm boundaries (Gioia & Pitre, 1990; for an epistemological approach [evolutionary naturalist] to combine disparate perspectives, see Azevedo, 2002). Indeed, according to Kaplan (1964), many theorists move from observable indicators of a phenomenon (i.e., the “individual”) to higher levels of abstraction that entail unobservable categories or concepts (i.e., “social classes” or “society”). Similarly, Stinchcombe (1968) notes that the theorizing process requires skillful abstraction, or carefully moving up or down the ladder of abstraction, to develop propositions (generated at higher levels of abstraction) or operationalize hypotheses (generated at observable levels of abstraction). For instance, Dencker et al. (2021) attempt to clarify the concept and manifestation of necessity entrepreneurship, acknowledging that different basic needs may spur necessity entrepreneurship and that necessity entrepreneurs may vary in their level of human capital. Based on these premises, the authors formulate propositions regarding the different entrepreneurial processes entrepreneurs engage in under distinct contextual conditions.

Abstraction is required for theorists to broaden their view (from one based on assumptions from one paradigm) to juxtapose, and perhaps connect, formerly distinct views to provide a broader perspective of the focal phenomena (Lewis & Grimes, 1999). While theorizing across paradigms might seem challenging due to each paradigm’s different assumptions, the boundaries between paradigms tend to be blurry and can be usefully thought of as “transition zones” that can be bridged (Gioia & Pitre, 1990). Specifically, through abstraction, scholars can generate second-order concepts, which describe scientific understanding, instead of first-order concepts, which describe how people experience phenomena. As abstractions of first-order concepts, second-order concepts enable scholars to recognize related or comparable concepts as the foundation for a bridge across the transition zones of two or more paradigms (Gioia & Pitre, 1990; Lewis & Grimes, 1999). This type of meta-paradigm perspective goes beyond the “agree to disagree” approach to disparate paradigms to provide a deeper understanding of why disagreement exists and to theorize on the similarities and interrelationships underlying entrepreneurship phenomena, in turn broadening the “conception of theory and the theory-building process itself” (Gioia & Pitre, 1990: 600). For instance, Pfeffer and Fong (2005) promote theorizing that reveals and connects foundational core constructs to build a broad understanding that explains a range of behaviors. In the entrepreneurship context, a firm’s entrepreneurial orientation can be considered such a core construct as it encompasses the degree to which a firm generates innovative ideas, shows aggressiveness compared to competitors, fosters autonomous thinking in employees, takes risks, and behaves proactively in the marketplace (Lumpkin & Dess, 1996). While these firm characteristics may vary independently, by considering them as part of the broader entrepreneurial orientation construct, scholars can theorize on how characteristics of a firm’s environment and structure moderate the relationship between entrepreneurial orientation and firm performance (Lumpkin & Dess, 1996). Thus, both abstraction and complexification can lead to new theories of entrepreneurship.

Third, moving back and forth between data and theory helps provide new perspectives to construct a theoretical story. Eisenhardt (1989) proposes that the best way to build a theoretical narrative is by comparing multiple case studies. In this approach, a theorist enters the field with a clear-cut research question (perhaps one taken from the literature or one centering on clarifying specific constructs), thoughtfully chooses cases that create tension or contrast around the research question (“theoretical sampling”), and identifies illustrative patterns that match data with theory to build “bridges from rich qualitative evidence to mainstream deductive research” (Eisenhardt & Graebner, 2007: 25). For example, in their work, Williams and Shepherd (2016) explore the emergence of six ventures created to alleviate suffering after the 2010 Haiti earthquake. Based on their analysis, the authors identify two divergent groups of ventures that differed in how they recognized opportunities to help, accessed important resources, and acted to alleviate victims’ suffering. Similarly, Preller et al. (2020) investigate eight founding teams to shed light on how individual team members’ entrepreneurial dreams impact future venture performance. Another approach to moving between data and theory, proposed by Dyer and Wilkins (1991), emphasizes the narrative elements of a single case study. With this approach, a theorist builds theory by shifting between the thick description of data and the existing literature. For instance, Waldron et al. (2015) offer a comprehensive exploration of the Rainforest Action Network to examine how institutional entrepreneurs harness institutional change to enhance their influence within organizational fields. In the case of both approaches, however, a theoretical narrative surfaces from abductive iteration between theory and the literature to fulfill an “unmet expectation.” According to Van Maanen et al. (2007: 1149), an unmet expectation is “like the dog that did not bark in the fictional world of Sherlock Holmes”—namely, a mystery or a clue that triggers theorizing by pushing a theorist to build a hearty explanatory narrative that gives “primacy to the empirical world, but in the service of theorizing.”

Finally, changing assumptions by shifting the level of analysis can facilitate theory building. Klein et al. (1994) outline three critical assumptions underlying multilevel theorizing that scholars should make clear—(1) homogeneity, which refers to “group members are sufficiently similar with respect to the construct in question that they may be characterized as a whole” (Klein et al., 1994: 199); (2) independence, which refers to group members being independent of the group’s influence and others in the group concerning the construct of interest (between individual variance); and (3) heterogeneity, which refers to individuals being nested within the group such that the “group context is not only informative but necessary to interpret an individual’s placement or standing in the group” (Klein et al., 1994: 202). For instance, Laspita et al. (2012) explore the extent to which entrepreneurial intentions are transmitted from parents to children across different cultures (individualist vs. collectivist). Indeed, theorizing across levels of analysis provides a more in-depth understanding of mechanisms that shift the level of analysis, thereby distinguishing mechanisms used in initial theories or topics to explain the “why” of existing relationships (and theories) (see also Shepherd & Sutcliffe, 2015).

In particular, Morgeson and Hofmann (1999: 251) emphasize the multilevel nature of constructs in collective contexts, with collective referring to “any interdependent and goal directed combination of individuals, groups, departments, organizations, or institutions.” In such collective contexts, constructs can exist at both the individual and group levels and can be investigated in terms of their function (i.e., the causal output of the focal system [or part of the system]) and/or their structure (i.e., the system of interaction among members of the collective). For example, Shepherd et al. (2010) establish a theory for how organizational members’ entrepreneurial mindset can trigger the formation of an entrepreneurial culture in organizations and vice versa, resulting in a spiraling relationship between constructs at the individual and organizational levels. By exploring the function and structure of collective constructs, scholars can build theory on the emergence of, stability of, and changes in collective entrepreneurial constructs. Notably, these features—emergence, stability, and change—all entail notions of time, to which we now turn.

Set Time to Establish the Boundary Conditions of an Entrepreneurship Theory: The Story’s Sequence of Events

A story’s sequence of events is the order in which events occur, which brings together the different parts of the story. While time is directly or indirectly a boundary condition for most theories, theorizing sometimes entails shifting the time perspective to alter the ontological nature of constructs and the relationships between them (George & Jones, 2000; Zaheer et al., 1999). Indeed, in Whetten’s (1989; see also Dubin, 1978) explanation of the criteria of theory—namely, “what,” “how,” “why,” “who,” “where,” and “when”—the “when” directly reflects the salience of time for theory. Further, George and Jones (2000) outline how time can be applied in theorizing by considering the following: (1) how the past and future influence the present and how time can be experienced differently (i.e., subjective time) within and across individuals; (2) how time is grouped into chunks, such as with defined episodes (for different time scales, see Zaheer et al., 1999); (3) how the duration of different periods can be classified as periods of stability and change; (4) how the nature of change can be considered in terms of its rate (over time), its magnitude (e.g., incremental or discontinuous), and its pattern (e.g., frequency, rhythm, and cycles); and (5) how the interplay between constructs over time can be reflected in mutual causation (e.g., positive or negative spirals) and change intensity (Dansereau et al., 1999; Mitchell & James, 2001). For example, Breugst et al. (2020) theorize how a new venture team member’s perception of their teammates’ efforts at a specific point in time (one week) impacts this member’s efforts at a later point in time (the following week), thus explaining the dynamic process of effort contagion in new venture teams. Moreover, Corley and Gioia (2011) propose that scholars should direct their attention to the future to foresee problems and thus inform future thought and action, generate vibrancy, and ensure value in quickly changing external environments. This type of theorizing—known as prescient theorizing—is informed by either projective futurism or prospection. Projective futurism refers to a sound theoretical foundation for arguing and predicting, whereas prospection is the use of informed projections into the future to predict issues, act as if those issues have arisen, and then infer domains that need attention or innovation (Corley & Gioia, 2011: 25).

For scholars who explicitly consider time to build process theories (as opposed to theories of variance; Mohr, 1982), Langley (1999) provides several different strategies to construct theories: (1) developing a comprehensive story through time (narrative strategy); (2) coding qualitative events into predetermined categories for statistical analysis (quantification strategy); (3) proposing and evaluating alternative theoretical templates of the same events with different theoretical premises (alternate templates strategy); (4) repeatedly comparing datasets to progressively develop a system of categories that can be connected to explicate a process (grounded theory strategy); (5) graphically or visually presenting multiple depictions of “precedence, parallel processes, and the passage of time” (Langley, 1999: 700) (visual mapping strategy); (6) bracketing and labeling periods of a single event and highlighting the continuities within that period as well as the discontinuities at or outside the period’s borders (temporal bracketing strategy); and (7) constructing global measures of a process as a whole to compare and contrast with other processes (synthetic strategy). Indeed, McMullen and Dimov (2013) contend that while entrepreneurship is frequently described as a process, scholars have failed to fully consider its processual nature in entrepreneurial theorizing. Likewise, Rauch and Hulsink (2021) propose that studying the temporal sequences of events comprising the entrepreneurial process would benefit entrepreneurial theorizing. Lévesque and Stephan (2020) also suggest that applying a time-based lens could significantly advance the entrepreneurship field.

Entrepreneurship Scholars’ Disciplined Imagination: Plot and Theme

The plot is what binds a story together (Jameson, 2001), makes it intelligible (Garud & Giuliani, 2013), and—with the main character(s)—provides coherence (Ibarra & Barbulescu, 2010). In other words, the plot provides the discipline for the imaginative parts of a story. Similarly, theorizing to generate something new—a new explanation, new insights, or a new story—necessitates discipline and imagination. Theorizing in the form of disciplined imagination can entail thought experiments—abstract hypothetical scenarios (Folger & Turilo, 1999) or simulations that are part of an artificial selection process (Weick, 1989)—“a method for using computer software to model the operation of real-world processes, systems, or events” (Davis et al., 2007: 481). Indeed, Weick (1989) suggests that when theorists construct theory through such thought experiments, their endeavors resemble an evolutionary model of variation, (artificial) selection, and retention.

The disciplined imagination process starts with devising a research question in the form of a problem statement. A problem statement is formulated and posed by a theorist to indicate a specific need that requires a solution. Specifically, the theorist identifies a problem that needs to be solved (explained), outlines assumptions that can be disconfirmed, provides a set of concepts that can be linked in different ways, suggests a plot that may be improbable, and asks a question that has not been asked yet (Weick, 1989). After constructing a problem statement, the theorist can then undertake thought trials, testing (competing) conjectures of a solution to the problem statement (see also Kaplan, 1964; Stinchcombe, 1968). Conducting a higher number of and more diverse thought trials enhances theorizing by helping the theorist refine conjectures about the potential solutions as heterogeneous thought trials provide more information to inform the theorizing process. Finally, the theorist must choose and apply selection criteria for the thought trials to determine the plausibility of the emerging story. Namely, theorizing becomes more promising when the selection process consistently applies a set of criteria (Weick, 1989), when it provides access to tacit knowledge through embodied or vicarious participation (Folger & Turilo, 1999), and when it invokes the related properties of a system’s interrelated links (Folger & Turilo, 1999; Shepherd & Suddaby, 2017). While scholars can conduct thought trials in their minds (or through simulation software), the production of knowledge usually involves a social component such that theorists typically need to test conjectures by communicating them to others (i.e., via stories) and receiving feedback (Jacques, 1992; Weick et al., 2005).

The discipline of theorizing can come from numerous sources, including metaphors (e.g., the specific case of anthropomorphizing [see Chapter 3]), other forms of blending, at-hand knowledge resources (i.e., bricolage), and patterns in the form of typologies, to which we now turn.

To theorize using an interaction metaphor (Cornelissen, 2005, 2006), a theorist must begin by creating a generic structure that links a source and a target domain. The theorist can then start to map the similarities between the two domains and transfer “instance-specific” information about concepts between them. This approach allows the theorist to expand upon the emerging story by combining the source and target concepts, thereby gaining new insights into both the target and source domains (Cornelissen, 2005, 2006) (more on blending in the following sections). Specifically, metaphors aid the theorizing process in several ways: they (1) provide a vocabulary to “express, map, and understand” the complexity of different phenomena, thus enabling a stronger foundation for understanding (and communicating about) underlying constructs (Cornelissen, 2005: 753; Lakoff & Johnson, 1980; Tsoukas, 1991); (2) foster an open-minded approach with “multiple ways of seeing, conceptualizing, and understanding” phenomena of interest (Cornelissen, 2005: 753); and (3) enable new insights that may have been implausible beforehand (Morgan, 1980, 1983, 1996; Oswick et al., 2002). For instance, Lundmark et al. (2019) analyze highly cited entrepreneurship articles to propose eight root metaphors (e.g., entrepreneurship as parenthood, mutagen, conduit of knowledge, method, mindset, networking, exploration, and politics) capturing core assumptions and thought patterns in the mainstream entrepreneurship literature. The authors suggest that future research to extend these metaphors could advance the field by questioning and defying these assumptions and investigating entrepreneurial topics from different angles.

Anthropomorphizing is another way to theorize through metaphor. Anthropomorphizing refers to “imbuing the imagined or real behavior of nonhuman agents with humanlike characteristics, motivations, intentions and/or emotions” (Epley et al., 2007: 864). Chapter 3 highlights how anthropomorphizing has been critical to creating and developing many important management theories, including organizational knowledge and entrepreneurial orientation (see also Shepherd & Sutcliffe, 2011). This theorizing tool can be especially beneficial when theorists use their rich understanding of themselves and others to (1) take a chance to guess the explanation of an anomaly, (2) shed light on the mechanisms underlying the “how” and “why” of important relationships and provide insights into organizing, and (3) aid sensemaking as well as tap into audiences’ knowledge of themselves and people in general as a sensegiving communication strategy to tell compelling stories. Indeed, anthropomorphizing enables theorists to conceptualize, construct, and communicate creative theories of organizations, organizing other non−human entities, and other processes (and perhaps even theories of themselves). Moreover, this tool instills confidence in junior scholars so they are able to theorize more easily.

In the interaction model of metaphor, metaphor entails blending; however, not all blending for theorizing entails metaphor. For example, Oswick and colleagues (2011) highlight four types of blending that do not involve metaphor: (1) orthodox domestic theory (i.e., narrow focus in terms of theoretical contributions and primarily involves the domain of production) enables incremental extensions to a specific sub-area of management; (2) innovative domestic theory (i.e., broad focus in terms of theoretical contributions and mainly involves the domains of production) “challenges existing knowledge and ways of thinking but does so from an insider’s perspective” (p. 323); (3) novel traveling theory (i.e., narrow focus in terms of theoretical contributions and involves numerous domains) provides “quirky insights into non-management disciplines yet largely reinforces, builds upon, or resonates with prior knowledge” (p. 324); and (4) radical traveling theory (i.e., broad focus in terms of theoretical contributions and involves numerous domains) reflects a “significant challenge to and departure from the contemporary and conventional pre-existing insights in a particular discipline” (p. 322) but calls for significant “repackaging, refining, and repositioning” (p. 323) for it to be adopted by management scholars. When using blending, it is essential for scholars to theorize about how the insights generated influence the source domain (over and above the influence on the target domain), possibly including how prior source theories need to be adjusted and boundary conditions need to be reassessed (see also Zahra & Newey, 2009).Footnote 2 In their study on how affect impacts entrepreneurial effort, for example, Foo and colleagues (2009) not only advance theory on affect’s role in entrepreneurship but also extend affect-as-information theory (a major psychological theory) by revealing how positive affect can increase (rather than decrease) effort through a future temporal focus. Similarly, Haynie and Shepherd (2011) explore how an entrepreneurial career can enable traumatized veterans to build a future for themselves; in doing so, they offer major insights into theories of career transitions in addition to contributing to entrepreneurship theory.

Whereas blending offers a foundation to transform constructs and relationships in both the target and source literatures (i.e., bidirectional information flow), bricolage combines sub-elements from a source domain that can be applied in entrepreneurship to generate a unique combination (i.e., unidirectional information flow). Knowledge production can be conceptualized as evolution, differentiation, and bricolage. While evolution (i.e., the accumulation of knowledge via “trial and error toward an increasingly robust view of the world”) and differentiation (i.e., efforts to “generate knowledge that is discontinuous with existing knowledge”) prevail in scholarship (Boxenbaum & Rouleau, 2011: 279–280), bricolage holds significant promise as a source of novel theories and is thus an important theorizing tool. For theorizing, bricolage signifies “the assembly of different knowledge elements that are readily available to the researcher” to form fluid knowledge constructs (Boxenbaum & Rouleau, 2011: 281). This strategy necessitates theorists to be “flexible and responsive... to deploy whatever research strategies, methods, or empirical materials, at hand, to get the job done” (Denzin & Lincoln, 1994: 2). Accordingly, bricolage’s role in theorizing may actually be stronger than it appears because although scholars may apply bricolage in their theorizing, they often communicate the outcomes of the process in terms of an evolution or differentiation approach.

According to Boxenbaum and Rouleau (2011), theorists undertake bricolage by (1) concentrating on combining different elements (e.g., ideas, concepts, experiences) they have at hand instead of endlessly examining the literature or generating a theory from “scratch”; (2) selecting elements that are nearby (to the theorist) and adequately diverse such that combining them can lead to novel (and hopefully useful) insights; (3) using common sense when choosing and combining elements so additional theorizing can produce logical, broad, and valuable explanations of phenomena; (4) staying flexible and alert to new combinations by considering the elements (to be combined) as fluid concepts and their combination as potentially transformative (in terms of new insights); and (5) reflecting on their use of bricolage to theorize. For instance, Cardon et al. (2009) apply bricolage to theorize about various types of entrepreneurial passion and how they influence entrepreneurial action. In particular, the authors evoke Gartner et al.’s (1999) taxonomy of entrepreneurial activities to propose that entrepreneurs may be passionate about inventing new products, founding new ventures, or developing their ventures.

Finally, using typologies is another useful way to combine constructs. Typologies aid in theorizing by representing complicated explanations of causal relationships entailing contextual, structural, and strategic factors to explain an outcome (Doty & Glick, 1994; Fiss, 2011). Importantly, these explanations are not classification schemes—“systems that categorize phenomena into mutually exclusive and exhaustive sets with a series of discrete decision rules” (Doty & Glick, 1994: 232) for describing phenomena—but are instead complex theories in themselves (Doty & Glick, 1994). To use typologies to theorize, theorists need to make their grand theoretical claims explicit (Doty & Glick, 1994: 235), specify each ideal type, describe each ideal type with the same set of dimensions and elucidate the assumptions underlying how the dimensions (e.g., core and peripheral elements; Fiss, 2011) that describe the ideal types (Doty & Glick, 1994) are weighted. Typologies can reveal vital insights to further knowledge because they help theorists go beyond the linear to investigate numerous patterns (Miles et al., 1978), highlight the significance of how multiple aspects fit together to provide a more complete story (Fry & Smith, 1987; McKelvey, 1982), allow for equifinality (i.e., organizations can achieve the same outcome [e.g., high performance] via different routes; Katz & Kahn, 1978; Payne, 2006; Van de Ven & Drazin, 1985), and provide a “form of social scientific shorthand” (Ragin, 1987: 149) to explain multiple causal relationships (Fiss, 2011). As an example, Zahra and colleagues (2009) develop a typology of social entrepreneurs based on their motives and search processes. Douglas et al. (2020) also suggest that using qualitative comparative analysis can help theorists generate novel theories by classifying entrepreneurial behavior based on the antecedent attributes of individuals within groups.

Evaluating a Theory: The Narrative Arc

Narrative arcs generally end by providing a resolution to the focal story’s problem and/or the problem faced by the story’s main actor. Although constructing theories and making theoretical contributions are important, the resolution in stories (i.e., what constitutes a theory) varies widely, as do interpretations of what constitutes a good story (i.e., a theoretical contribution). As Suddaby (2014b) argues, the range of beliefs of what represents theory reflects the extensive variety of beliefs about what theory should be used for. Some (perhaps most) view theory as a way to accumulate knowledge. Others view theory as a means to legitimate some forms of knowledge over others. Still, others see a powerful normative value in theory—namely, they believe that summarizing existing knowledge is less important than guiding the attention of a research community to investigate salient issues for the future. However, for each group, some theories appear to be favored over others due to their narrative attributes (Van Maanen, 1995). Accordingly, in this section, our goal is to review the rhetorical attributes of successful theories and, in particular, identify the narrative elements constituting a contribution to theory.

A theory can be thought of as a statement of concepts and their relationships that indicate how and/or why a phenomenon occurs within boundary conditions as well as who is involved (Bacharach, 1989; Gioia & Pitre, 1990). The overall purpose of a theory is to organize (parsimoniously) and communicate (clearly) (Bacharach, 1989), which it does by providing a logical explanation of a phenomenon, making assumptions, and building on those assumptions to coherently generate predictions and offering conjectures that can be tested, confirmed, refuted, and/or falsified (Shapira, 2011).

While these attributes of the conceptualization of theory are helpful, it is not always entirely clear whether the outcome of a specific scholarly work is a theory. Indeed, Sutton and Staw (1995) note the challenge in establishing an outcome as a theory, instead they approach the matter by describing what theory is not. According to these authors, theory is not references to previous work, data reflecting a phenomenon, a list of variables or constructs, a diagram with boxes and arrows, or a set of hypotheses. Similarly, Bacharach (1989) explains what theory is not by describing how theory is not an explanation, or the what, of a relationship without the how, why, and when.

Weick (1995) mainly concurs with Sutton and Staw (1995), and thus Bacharach (1989), about what theory is not. However, he also acknowledges that offering a fully developed theory is rare and that scholars should instead hope to contribute to knowledge by presenting their work as an interim struggle (Runkel & Runkel, 1984), the outcome of which can be assessed in terms of a continuum rather than a dichotomy (i.e., a theory or not). This notion of theory as a continuum is comforting because it establishes more realistic expectations about what is (or should be thought of) a theoretical contribution. Thus, while Sutton and Staw’s (1995) list of what theory is not is apt when theory is considered a dichotomy, theorizing outcomes can be an important part of an emerging story and/or an input to further theorizing. When theorizing as an interim struggle contributes to subsequent work, it can be valuable and is perhaps a contribution worth publishing (despite not yet achieving the status of a fully developed theory).

Thus, the next question is what characterizes a theoretical contribution. A theorizing outcome can be deemed a contribution when it bridges a gap between two theories as a foundation to explain something between two domains (Bacharach, 1989) and when it produces useful new insights (Whetten, 1989) that lead to a reassessment of existing theories (Bacharach, 1989). Accordingly, a theorizing outcome must be original and useful to constitute a contribution. To be original, a theorizing outcome needs to uncover something previously unknown (Corley & Gioia, 2011), surprise scholars by pushing them to reexamine something they thought they knew (Rynes, 2002), and be adequately novel and/or counterintuitive (Davis, 1971). To be useful, a theorizing outcome needs to provide scientific utility or practical utility. Scientific utility facilitates improvements in conceptual rigor and specificity and/or aids in operationalization and testing, while practical utility applies directly to the problems entrepreneurs face (i.e., problems that matter; Pfeffer, 1993). Thus, although a theory must be distinct enough from established wisdom to justify a reexamination, it also needs to be similar enough to this wisdom to be intelligible (McKinley et al., 1999). By connecting a theory with established knowledge, a theorist infuses novelty with meaning, thereby setting up a dynamic tension and interplay between novelty and continuity (McKinley et al., 1999: 638). For example, Patzelt and Shepherd (2011) draw on the well-established idea that knowledge and motivation are major drivers of opportunity recognition (McMullen & Shepherd, 2006) to theorize on the antecedents of recognizing opportunities for sustainable development. However, they also acknowledge that sustainable development outcomes differ from purely economic outcomes and are thus able to theorize on the roles non-economic knowledge and motivation play in opportunity recognition in the sustainable development context.

The value of a theory (or another type of theorizing outcome) may also arise from its ability to spur further theorizing. For instance, theorists can be reflexive—namely, they can reflect on the research process by acknowledging the situated nature of the knowledge and knowledge creation behind their theorizing outcomes. Alvesson et al. (2008) propose several different practices to stimulate reflexivity: (1) taking different perspectives to develop a different frame of reference from that applied in the original theorizing to see the focal phenomenon differently and thus recognize that these different perspectives represent new knowledge sources, (2) using a different voice than the one used in the original theorizing to appreciate how voice impacts perspective (see also Pentland, 1999), (3) employing different positionings to understand how time and context affect the choice of perspective (see also Pentland, 1999), and (4) destabilizing a perspective by examining the conditions and consequences of theory building and thus problematizing the process and outcome of the original theorizing. When used to stimulate new theorizing, reflexivity may also depend on how researchers exit their fieldwork. For instance, Michailova and colleagues (2014) suggest that researchers can achieve paradoxical thinking and revelatory theoretical outcomes from a fieldwork exit in which the relationship between the researcher and their subjects (or informants) is terminated and not easily restarted. Specifically, they contend that such a relationship disruption enables researchers to disengage (physically, mentally, and emotionally) from the field, thereby facilitating the abstraction required for theorizing; provides the aggravation needed for abductive research; and takes researchers out of their comfort zone as the foundation for an “aha” moment. Indeed, when engaging in inductive research, the challenge for entrepreneurship scholars is stepping back from the data (i.e., the trees) to obtain a more abstract perspective (i.e., see the forest) for theory building.

Pragmatic Empirical Theorizing

In the discussion above, we reviewed existing methods for successfully identifying an anomaly and then generating, building, and assessing an entrepreneurship theory as expressed by leading theorists. A recurrent issue in this literature, however, is the ongoing tension between how much emphasis should be given to prior versus emerging knowledge, or how much emphasis should be given to the existing theoretical literature versus empirical observation. There is a growing concern—detailed most adeptly by Hambrick (2007)—that the management field’s obsession with theory often hinders the publication of research exploring new but undertheorized phenomena, which many also believe is true for the entrepreneurship field. Hambrick (2007: 1346) contends that,

A theory fetish prevents the reporting of rich detail about an interesting phenomenon for which no theory yet exists. And it bans the reporting of facts—no matter how important or how competently generated—that lack explanation, but that once reported, might stimulate the search for explanation.

Similarly, Harris et al. (2013: 451) propose that “many of the interesting gaps to be filled by empirical research may be in phenomenological understanding rather than in questions about theoretical axioms.”

Many renowned scholars join Hambrick in arguing that theory is progressively becoming a limiting instead of a generative tool for building new knowledge in management. For instance, Miller et al. (2009) characterize top-tier management journals’ approach as narrowing the idea of what a contribution to theory is (i.e., applying a straightjacket) to topics that fit neatly within popular contemporary theories and that enable the development and modification of those theories. Sutton and Staw (1995: 381) support Miller’s notion of theory as a straightjacket, noting that “the problem with theory building may also be structural” in that scholars can only interpret data through the lens of existing theory. Consequently, “the craft of manuscript writing becomes the art of fitting concepts and arguments around what has been reassured and discovered.”

As Suddaby (2014a, 2014b) observes, Hambrick’s concerns reflect the deep-rooted frustration and tension between rationalism and empiricism. Rationalists contend that knowledge is most valuable when it is abstracted into general principles and relationships—namely, theory. Rationalists deride the notion that a new phenomenon can be understood without theory, instead arguing that what makes a phenomenon new can only be determined by explaining the existing literature. Rationalists build new knowledge mainly via deduction from past knowledge. However, many scholars view this conforming effect of prior theory as a constraining straightjacket that necessitates a contribution to theory.

Empiricism is the alternative to rationalism. It centers on direct empirical observation without the constraining influence of theory. In empiricism, knowledge is accumulated via induction (i.e., building observation on observation, fact on fact), with purist empiricists arguing that prior theory obscures observation and hinders the development of knowledge through brute facts. This perspective—as evidenced in Hambrick’s (2007) and others’ (e.g., Pfeffer, 2014) fervent appeals for less theory—is perhaps best captured in Kerr’s (1998, in Bern, 1987: 173) reflection:

There are two possible articles you can write: (1) the articles you planned to write when you designed your study, or (2) the article that makes the most sense now that you have seen the results. They are rarely the same and the correct answer is (2). . . . The best journal articles are informed by the actual empirical finding from the opening sentence.

How can scholars make sense of these two contradictory views of theory? We provide a middle ground between these two extremes that we term pragmatic empirical theorizing. This view primarily draws on the well-known founder of American Pragmatism, Charles Saunders Peirce (1958). Pragmatic theorizing focuses on abductive reasoning as a practical compromise between induction and deduction that more accurately captures the authentic process driving theorizing.

With pragmatic empirical theorizing, entrepreneurship scholars can uncover and engage interesting findings as a transparent step in the hypothetico-deductive process (not as the conclusion of all steps in the process). Interesting and novel facts, such as anomalies that current theories do not readily explain, are critical because they trigger an investigation. Indeed, such anomalies spur abduction, which is fundamental to the logic of discovery (at least in the pragmatic tradition; Hanson, 1958). Accordingly, theorizing can be triggered by interesting facts about entrepreneurial phenomena. Instead of merely outlining the interesting facts upon which other scholars can theorize, the entrepreneurship scholars who uncover these interesting facts can make more significant contributions by making initial attempts at providing explanations for them. In other words, they have the opportunity to offer a story to explain the “why” of the relationships they discover.

Unlike presenting post hoc hypotheses as a priori (PPHA; also known as hypothesizing after results are known [HARKing]), the pragmatic theorizing approach to exploring entrepreneurial phenomena presents post hoc propositions as post hoc—namely, it entails transparently theorizing from results. This approach overcomes many concerns related to PPHA because many of these concerns are attributable to a lack of transparency (or deception) about the process. That is, many of the problems related to PPHA stem from misleading audiences that the theorizing preceeded the findings. With pragmatic empirical theorizing, however, scholars can fulfill both the possibility of discovering anomalies and the need for building theory by unmasking the process. We do not naïvely believe that this approach will not require a shift in the research mindset of authors, reviewers, and editors. Nevertheless, the need for new discoveries, the emphasis on theory, and the potentially prevalent practice of PPHA indicate that the scholarly entrepreneurship community may be open to pragmatic empirical theorizing—an approach that harnesses empirical insights from interesting findings on entrepreneurial phenomena to spur and inform a preliminary conjecture and adjustments to that conjecture while also documenting and reporting crucial steps in this process.

In this approach, facts can play a critical role in triggering (i.e., spurring and informing) theorizing to provide a tentative (and potentially highly speculative) explanation for the focal data. This theorizing can then be combined with the facts to form a theoretical contribution to the entrepreneurship literature. In other words, theorizing does not need to be omitted from a paper and reserved for future research. Instead, we suggest that the entrepreneurship scholar—as the discoverer or creator of the anomaly at hand—has the opportunity to present the first explanation. Indeed, identifying a problem and taking the initial step toward its resolution provide a sturdier foundation for contributing to understanding than solely recognizing a problem. Of course, offering a potential explanation does make one susceptible to being challenged and having one’s efforts replaced by a superior explanation. However, if this occurs, we should consider ourselves lucky. As a theorizing story evolves across ensuing papers, so does its original contribution—or at least it should.

Although scarce, some recent examples of empirical theorizing on entrepreneurial phenomena have emerged. Specifically, entrepreneurship scholars have used qualitative comparative analysis (QCA) and similar techniques to investigate how configurations of antecedents are connected to entrepreneurial outcomes and then offered theoretical explanations for the resulting findings. Muñoz and Dimov (2015), for instance, apply fuzzy-set QCA (fsQCA) to explore how entrepreneurs’ previous sustainability-related knowledge, sustainability orientation, entrepreneurial intentions, desired value creation, and perceived social and business support influence how they articulate sustainability-related venture ideas, actions, and relationships. Using the fsQCA technique, the authors reveal two distinct paths (conformist/insurgent) that sustainable entrepreneurs take to establish their ventures. They then draw on these findings to theorize the role distinct antecedent configurations play in entrepreneurs’ choices. In a similar vein, Douglas and colleagues (2021) use fsQCA to investigate the influence of different individual-level factors on the formation of entrepreneurial intentions, finding complementary, substitutive, and suppressive conditions. Based on these empirical findings, the authors advance propositions on the formation of entrepreneurial intentions. Finally, Debrulle et al.’s (2021) recent work explore how different configurations of founders’ resources, venture strategies, and environmental conditions impact venture performance. Due to the complexity involved in theorizing configurational relationships, the authors begin with an empirical investigation to uncover distinct configurations associated with high venture performance and then go on to develop theoretical explanations for their findings and divergence from prior theory.

Ultimately, we concur with Hambrick’s (2007) notion that facts can trigger theorizing. We hope entrepreneurship scholars (as well as reviewers and editors) begin to realize that interesting findings can lead to theorizing within a single paper instead of having to be investigated across multiple papers. Stated differently, data does not have to follow theory. Indeed, when data highlights an unfulfilled expectation (i.e., an explanation for an empirical phenomenon), it can trigger an abductive process that “works backward to invent a... theory that would make the surprise meaningful.... [Abduction] assigns primacy to the empirical world, but in the service of theorizing” (Van Maanen et al., 2007: 1149; see also Swedberg, 2014). Although informative descriptions can spark interesting questions, theorizing is necessary to provide novel insights. Thus far, the notion of what constitutes a contribution has largely been based on the insight provided by a paper (an insight that is original and useful; Corley & Gioia, 2011). However, future contributions are likely to emerge from entrepreneurship scholars transparently presenting interesting findings and subsequently theorizing on potential explanations (instead of offering these findings as theory testing or providing only interesting findings).

Conclusion

In this chapter, our goal was to review and integrate the rapidly expanding literature on theorizing. By focusing on what prominent theorists have to say about the theorizing process, we aimed to accrue knowledge on the tools used to generate exceptional theory that explains entrepreneurial phenomena. Further, we hoped to reinforce the idea that creative theory building is not exclusively reserved for elite or experienced scholars; rather, it is a technical skill that all scholars can learn and apply. In particular, we identified and expounded upon several activities that can generate influential theories. The first activity we presented—the theorizing trigger—requires aspirant theorists to identify a tension that will drive the remainder of the theorizing process. Indeed, theories are often triggered by tensions between what scholars know and what they observe. Accordingly, we outlined a variety of tensions that have previously led to solid theory. Next, we discussed the activities of developing the main character(s) (or construct[s]) for a theory, constructing the context or setting, and actively engaging the audience’s imagination by introducing plots and themes. Finally, we detailed how entrepreneurship scholars need to choose story elements to construct the narrative arc of a theory—namely, to justify and evaluate the theory.

Furthermore, after reviewing the literature on theorizing, we proposed a theorizing approach that we believe has significant promise to produce new entrepreneurship theories—pragmatic empirical theorizing. This approach builds on the idea that interesting findings can be an important source of new theories, and it overcomes the lack of transparency resulting from PPHA (i.e., presenting post hoc hypotheses as a priori). We are interested in what others think about pragmatic empirical theorizing and hope to see this approach adopted and eventually accepted as a legitimate tool for entrepreneurial theorizing.

Each of the tools we described necessitates a high level of skill and insight and likely involves a degree of detail going far beyond the scope and space of this chapter. Here, we hope to start the conversation required to make theorizing a point of continual reflection in the scholarly entrepreneurship community. We offer merely an initial step in the form of a common language and a causal process that necessitate further clarification and elaboration by a group of like-minded scholars. Like all research endeavors, advancing entrepreneurial theorizing is a collective effort. We hope this concise account provides the basis for an ongoing and engaging conversation.