Entrepreneurial alertness and entrepreneurial orientation: Contributions to opportunity identification

Abstract

The literature presents entrepreneurial alertness (EA)—a cognitive resource—as an antecedent of entrepreneurial opportunity identification, although empirical evidence is lacking. The aim of this study is to test this relationship and explore the influence of entrepreneurial orientation (EO), which provides a mobilizing vision for leveraging firm's resources, as a mediating mechanism for this relationship. Using data collected from 152 French entrepreneurs, our results empirically confirm the relationship between EA and entrepreneurial opportunity identification. Furthermore, we find a positive relationship between EA and each of the three dimensions of EO (i.e. innovativeness, proactiveness, and risk-taking propensity). However, only one dimension of EO—proactiveness—has a significant relationship with entrepreneurial opportunity identification. Our results highlight the mediating role of proactiveness in the relationship between EA and the identification of entrepreneurial opportunities and also confirm the interest in further research on this critical dimension of EO.

Keywords

entrepreneurial alertness entrepreneurial opportunity identification entrepreneurial orientation

Introduction

“Without an opportunity, there is no entrepreneurship. A potential entrepreneur can be immensely creative and hardworking, but without an opportunity to target with these characteristics, entrepreneurial activities cannot take place” (Short et al., 2010: 40). Recent research argues that entrepreneurship requires action (McMullen et al., 2006), but this action is only possible if there are entrepreneurial opportunities. The identification of opportunities thus remains a prerequisite to any form of entrepreneurial action. For this reason, identifying entrepreneurial opportunities has become a major topic in entrepreneurship research over the last three decades (George et al., 2016). Investigating the identification of opportunities provides valuable insight into how innovation emerges in organizations, which is a major challenge for entrepreneurship research (Kromidha et al., 2022). Prior research has focused on examining the factors that enable some individuals to identify opportunities while others cannot (Ardichvili et al., 2003; Baron, 2006; George et al., 2016; Shane, 2000; Short et al., 2010). Several characteristics of individuals have been found to influence the process of identifying entrepreneurial opportunities: prior knowledge (Shane and Venkataraman, 2000), personality traits such as creativity, self-efficacy, optimism, locus of control and openness to experience (Shane et al., 2010; Tang, 2009; Tang et al., 2021), social capital (Ardichvili et al., 2003; Baron, 2006; Tang, 2010), entrepreneurial experience (Ucbasaran et al., 2009), and entrepreneurial alertness (EA) (Ardichvili et al., 2003).

EA is “a distinctive set of perceptual and cognitive processing skills that direct the opportunity identification process” (Gaglio and Katz, 2001: 96). As a result, this concept is becoming increasingly popular and gaining significant traction in the research on entrepreneurial opportunities (Araujo et al., 2023; Lanivich et al., 2022). However, despite its potential to enhance our understanding of how individuals identify entrepreneurial opportunities, previous research has focused primarily on the conceptual domain of the construct (Adomako et al., 2018). Empirical research on the relationship between EA and the identification of entrepreneurial opportunities remains scarce due to major problems with the measurement of EA (Levasseur et al., 2022). In this article, we propose to address this gap by investigating the relationship between EA and entrepreneurial opportunity identification through the recognized instrument developed by Tang et al. (2012).

In addition, previous studies have essentially considered individual-related factors to explain why some individuals recognize entrepreneurial opportunities while others do not (George et al., 2016). The rationale for this is that research on entrepreneurial opportunities has been conducted primarily in the context of new venture creation (Roundy et al., 2018). However, established companies also need to focus on identifying entrepreneurial opportunities to enable the development and introduction of new products that promote sustainable regeneration (Covin and Miles, 1999). In such a context, the identification of opportunities cannot be considered as depending only on the characteristics of the entrepreneur, the organizational context in which the opportunity identification process takes place is also important (Hansen et al., 2016; Short et al., 2010). Yet, little research has been conducted on the influence of the organizational context in the process of identifying entrepreneurial opportunities: “Previous work has drawn from a variety of theoretical perspectives focusing primarily on opportunity processes at the individual level of analysis. Future efforts could build on this work by examining team processes, as well as organizational characteristics, that serve as effective antecedents in creating, discovering, and/or recognizing opportunities” (Short et al., 2010: 56).

In this article, we propose to address this other limitation by simultaneously examining the influence of EA and organizational context, as captured by the company's entrepreneurial orientation (EO) (Covin and Slevin, 1989; Miller, 1983), on the identification of entrepreneurial opportunities. Specifically, drawing on the resource-based theory and the resource orchestration view (Barney, 1991; Morrow et al., 2007; Sirmon et al., 2007, 2011), we argue that EA is a cognitive resource (Adomako et al., 2018) which must be mobilized and leveraged at the organizational level to enhance opportunity identification. EO, which captures entrepreneurial methods, practices, and decision-making styles (Wiklund and Shepherd, 2005), provides the organization with a mobilizing vision to direct the use of resources toward entrepreneurial activities leading to opportunity identification (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003). Consequently, we assume that the relationship between EA—a cognitive resource—and entrepreneurial opportunity identification is mediated by EO, which provides a mobilizing vision in the resource orchestration process.

Data collected from 152 French entrepreneurs partially support our assumption. Our results empirically confirm the positive relationship between EA and the identification of entrepreneurial opportunities. They also reveal a positive association between EA and each of the three dimensions of EO: innovativeness, proactiveness, and risk-taking propensity. However, only one dimension of EO—proactiveness—has a significant relationship with entrepreneurial opportunity identification. Our results, therefore, highlight the mediating role of proactiveness in the relationship between EA and the identification of entrepreneurial opportunities.

This research makes five theoretical contributions to the literature. Our first contribution is to confirm empirically the long-assumed relationship between EA and entrepreneurial opportunity identification (Ardichvili et al., 2003; Baron, 2006; Gaglio and Katz, 2001; Kirzner, 1979; Lanivich et al., 2022; Roundy et al., 2018; Urban, 2020). Our second contribution is to expand knowledge about the genesis of EO (Rosenbusch et al., 2011; Turnalar-Çetinkaya, 2022; Wales et al., 2013), by identifying EA as an antecedent of EO. Our third contribution is to complement prior research considering EO as a mobilizing vision that enables resource orchestration (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003), by considering not the influence of the resource orchestration process on firm performance but rather its influence on entrepreneurial opportunity identification. Our study is among the first to explicitly apply the resource orchestration view to explain the organizational process enabling firms to recognize entrepreneurial opportunities. Our fourth contribution is to provide a more nuanced view of the positive relationship between EO and entrepreneurial opportunity identification (Song et al., 2017), as our findings indicate that neither innovativeness nor risk-taking propensity have any influence on the identification of entrepreneurial opportunities. The fifth contribution of this study is to address recent calls for a more complex research model examining EA and its relationship to entrepreneurial opportunity identification (George et al., 2016; Lanivich et al., 2022), by investigating EO as a mediator of this relationship. Our research also reveals that only proactiveness partially mediates the influence of EA on the identification of entrepreneurial opportunities, thus confirming the major importance of this less explored dimension of EO (Lumpkin and Dess, 2001; Tang et al., 2014).

Literature review

Entrepreneurial opportunities

Many studies examine the nature of entrepreneurial opportunities, opposing opportunities that result from objective events, specific to market imperfections, with opportunities created or co-created by the entrepreneur and stakeholders. This debate between discovery (Grégoire and Shepherd, 2012; Shane, 2012; Tumasjan and Braun, 2012) and opportunity creation (Alvarez et al., 2014; Sarasvathy, 2001; Sarasvathy and Venkataraman, 2011) produced rich scholarly contributions (see George et al., 2016; Hansen et al., 2016; Short et al., 2010 for a complete summary). While Short et al. (2010) suggest an intermediate position in which entrepreneurial opportunities can be discovered as well as constructed, other studies challenge the entrepreneurial opportunity concept by launching an “opportunity war” (Wood and McKinley, 2020). Highlighting the difficulties of developing a common definition, few scholars propose to abandon the concept of entrepreneurial opportunity (Davidsson, 2015; Klein, 2008) and look at alternative concepts such as new venture ideas, external enablers, and opportunity confidence (Davidsson, 2015). Far from being a weakness, these debates around the definition of entrepreneurial opportunity are instead a strength of the concept (Nair et al., 2022; Wood, 2017; Wood and McKinley, 2020).

Practitioners and researchers use the concept of entrepreneurial opportunity as an all-inclusive concept that represents the complexity and multidimensionality of the entrepreneurial mindset (Wood and McKinley, 2020). As such, Wood (2017: 21) defines entrepreneurial opportunity as “an umbrella construct that encompasses a range of dynamics that lead up to and include new venture formation.” He further states that this construct has superior representative value because it is flexible enough to embrace the range of cognitive and behavioral dynamics that are playing when individuals engage in entrepreneurship. In this article, we adopt this definition and more precisely the division made by Nair et al. (2022) considering entrepreneurial opportunities along three perspectives: the creation of the new venture, the viability of the company, and the temporal perspective. Since our study focuses on established firms, we define entrepreneurial opportunities from the second perspective as a market imperfection that emerges along with the actions of entrepreneurs (Alvarez and Barney, 2005, 2007; Nair et al., 2022). Consequently, the concept of entrepreneurial opportunity is essential to explain phenomena such as firm growth (Wood and McKinley, 2020).

Entrepreneurial alertness

EA has been widely studied in the literature since the seminal work of Kirzner (see Lanivich et al., 2022 for a complete summary). However, the various and evolving uses of the term “alertness” make it difficult to conceptualize. Developing a better conceptualization of EA remains essential to understanding of how entrepreneurial opportunities are initiated and developed by entrepreneurs (Shepherd et al., 2019). To do so, we can rely on the seminal work of Kirzner (1979) who characterizes EA as a market equilibrium mechanism focused on economic equilibrium. According to his work, alertness is defined as (1) the individual's ability to identify without searching those opportunities that others have not recognized, (2) a natural tendency to build an image of the future, (3) a receptive attitude about available but overlooked opportunities, and (4) an intuitive ability to notice what others have missed. This seminal work has led to the development of research on the cognitive and psychological aspects of EA (Adomako et al., 2018; Lanivich et al., 2022; Urban, 2020).

Kaish and Gilad (1991) are among the first to have considered information as a fundamental resource for EA. Their work particularly emphasizes the influence of active and passive searching for information. The combination of passive alertness and systematic research can be seen as two complementary forces, like yin and yang, whose dynamic interaction can enhance entrepreneurial opportunity identification (Tang and Khan, 2007). Busenitz (1996) is also interested in the interpretation of information and has paved the way for new research focusing on the link between cognition and EA. In this regard, prior research finds that individuals must be able to associate and interpret items of information to recognize opportunities (Gaglio and Katz, 2001). Other scholars describe EA as a mental process through which entrepreneurial skills are built (Puhakka, 2011; Urban, 2020). Notably, these skills are strengthened by an individual's experience, education, and prior knowledge, all of which contribute to developing mental patterns for recognizing additional value creation (Valliere, 2013). EA is therefore an entrepreneurial capacity that can be acquired through experience and learning.

Building on McMullen and Shepherd's (2006) idea that alertness involves judgment and an orientation towards action, Tang et al. (2012) conceptualize EA as consisting of three unique and complementary components. The first, “information scanning and searching,” refers to the act of constantly scanning the environment for information and changes ignored by others. The second, “information association and connection,” refers to the ability to link the information one already possesses with newly collected information to develop innovative proposals in response to market needs. Finally, “evaluation and judgment” is the process during which the individual reflects on the relevance of the collected and associated information and decides whether or not an entrepreneurial opportunity exists.

More recently, Adomako et al. (2018: 456) rely on the resource-based view (RBV) to “conceptualise entrepreneurial alertness as a cognitive resource that affords the entrepreneur a cognitive capacity to identify opportunities ahead of others.” As such, EA is considered part of the resource portfolio of the firm that can be mobilized to gain a competitive advantage by identifying entrepreneurial opportunities before competitors. In this article, we adopt this conceptualization of EA from the RBV and view it as a cognitive resource that can be leveraged to provide the company with valuable information and insights regarding emerging entrepreneurial opportunities.

Entrepreneurial orientation

EO refers to the strategic orientation of a firm towards entrepreneurship (Covin and Slevin, 1989). Miller (1983: 771) describes an organization with EO as one that “engages in product-market innovation, undertakes somewhat risky ventures, and is first to come up with ‘proactive’ innovations, beating competitors to the punch.” The literature views EO as a firm-level concept consisting of three dimensions: innovativeness, proactiveness, and risk-taking (Covin and Slevin, 1989; Miller, 1983). Innovativeness represents a company's ability to support new ideas, creativity, and experimentation to facilitate the development of new products. Proactiveness refers to a forward-looking tendency of the firm to anticipate market changes, new trends, and future wants and needs. Such behavior enables firms to capitalize on emerging opportunities and gain a first-mover advantage (Lumpkin and Dess, 1996). Risk-taking characterizes a company's willingness to make bold decisions by committing significant resources to develop projects with a high potential for returns but also a high cost of failure. In this article, we adopt Miller's (1983) and Covin and Slevin's (1989) dominant conceptualization of EO to ensure increased comparability with prior research (McMullen et al., 2021; Wales et al., 2019).

Furthermore, prior research uses the concept of EO within the theoretical framework of the RBV to explain how strategic organizational mechanisms help firms develop a competitive advantage (Wales et al., 2021). The RBV argues that firms need valuable, rare, inimitable, and non-substitutable resources to gain such an advantage and achieve superior performance (Barney, 1991). However, simply possessing such resources is insufficient, and firms must also develop appropriate organizational structures to leverage their resources. This idea is at the core of the resource orchestration view, which posits that managers must orchestrate the firm's resources to outperform competitors (Morrow et al., 2007; Sirmon et al., 2007, 2011). More precisely, managers need to structure, bundle, and leverage resources through mobilization and coordination mechanisms. Mobilization offers a vision of how firms can use their resources and capabilities to build a competitive advantage (Sirmon et al., 2011). Since EO “refers to a firm's strategic orientation, capturing specific entrepreneurial aspects of decision-making styles, methods, and practices” (Wiklund and Shepherd, 2005: 74), previous research views it as a way to direct the use of firm's resources towards entrepreneurship (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003). In this article, we adopt this view and consider EO as a mobilizing vision that companies can use to leverage their unique resources (Chirico et al., 2011). According to Wales et al. (2021), drawing on the resourced-based theory represents an important avenue for advancing EO research.

Hypothesis development

EA and entrepreneurial opportunity identification

Although Kirzner (1979) did not provide a precise definition of EA, his proposals clearly suggest that EA plays a central role in entrepreneurial opportunity identification. Additional research identifies EA as an important driver of entrepreneurial opportunity identification (Baron, 2006; Gaglio and Katz, 2001; Lanivich et al., 2022; Roundy et al., 2018). The ability to identify entrepreneurial opportunities before competitors is critical for a firm's success (Adomako et al., 2018; Ardichvili et al., 2003; Gaglio and Katz, 2001), as it enables one to gain a competitive advantage. Roundy et al. (2018) argue that established companies can benefit from EA to recognize and develop entrepreneurial opportunities and thus support competitive advantage and firm performance. According to Urban (2020), EA also promotes entrepreneurial opportunity identification and entrepreneurial intentions in the context of social entrepreneurship.

To detect entrepreneurial opportunities before others, alert entrepreneurs can rely on their uniquely preparedness and readiness (Kaish and Gilad, 1991). They can be “distinguished from others because they have chronically engaged schemata that constantly direct attention toward changes in the environment, and allow them to notice and evaluate such changes earlier and more flexibly process the information they receive or acquire” (Roundy et al., 2018: 200). Through the schemata and cognitive structures they develop, alert entrepreneurs are able to see the connections between various events and information, which guides them towards recognizing new entrepreneurial opportunities (Baron, 2006; Valliere, 2013). EA acts as a mechanism that organizes information (Busenitz, 1996) scanned in the environment and analyzed by entrepreneurs (Tang et al., 2012), so that they can shift from an envisioned reality to the one they plan to build (Lanivich et al., 2022). This cognitive processing system places entrepreneurs in a receptive attitude towards available and previously overlooked opportunities (Urban, 2020). Consistent with Lanivich et al. (2022) and Valliere (2013), we believe that EA acts as an intermediary between changes occurring within the environment and the identification of entrepreneurial opportunities. Thus, individuals with high EA are better able to identify entrepreneurial opportunities than others due to their event interpretation style (Song et al., 2017). Based on these arguments, we propose the following:

Hypothesis 1: EA is positively associated with OI.

EO as a mediator of the EA–OI relationship

The resourced-based theory asserts that firms gain a competitive advantage through their resources when they are valuable, rare, inimitable, and non-substitutable (Barney, 1991). This competitive advantage can notably arise from the ability to use such resources for identifying and exploiting entrepreneurial opportunities ahead of competitors (Adomako et al., 2018). As we argued previously, EA is a cognitive resource that favors entrepreneurial opportunity recognition (Baron, 2006; Gaglio and Katz, 2001; Lanivich et al., 2022; Roundy et al., 2018). However, consistent with the resource orchestration view, possessing valuable, rare, inimitable, and non-substitutable resources is not sufficient to guarantee competitive advantage (Morrow et al., 2007; Sirmon et al., 2007, 2011). These resources must be orchestrated and leveraged at the firm level. We, therefore, argue for an indirect effect of EA on entrepreneurial opportunity identification, as suggested by Lanivich et al. (2022: 1173): “indirect and interaction effects of constructs to be found nomologically intermediating alertness and opportunity need exploration.” Firms need resources to develop a strategic orientation, which positions resources as a starting point for building strategy (Kenneth, 1971). Drawing on the RBV and the resource orchestration view, we assume that EA constitutes a foundational resource that managers can mobilize to shape the strategic orientation of their company.

EA is a cognitive resource that produces valuable information about the company's environment and market dynamics, helping to anticipate their future evolution (Baron, 2006; Busenitz, 1996; Gaglio and Katz, 2001; Kaish and Gilad, 1991; Lanivich et al., 2022; Roundy et al., 2018; Urban, 2020; Valliere, 2013). But without the implementation of an organization that promotes the use of this resource and the information produced, it is likely that these elements will remain underutilized and that the company will not be able to fully leverage them to identify new entrepreneurial opportunities (Wiklund and Shepherd, 2003). Since EO captures entrepreneurial methods, practices, and decision-making styles (Wiklund and Shepherd, 2005), it can provide a mobilizing vision capable of directing the use of company's resources towards entrepreneurial activities consisting of innovative, proactive, and risk-taking behaviors (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003). Consequently, EA represents a crucial cognitive resource that can be leveraged to support the EO of an organization. Cognitive resources enable the production of valuable information and knowledge that fuel the company's entrepreneurial abilities (Wiklund and Shepherd, 2003). Alert entrepreneurs constantly seek out and integrate new information that supports the creation of innovative ideas and drives the company's efforts toward innovation (Srivastava et al., 2021). They also help create a proactive set of norms and values within the organization, such as an “entrepreneurially alert information system” (Simsek et al., 2009). These entrepreneurs are likely the key informants in the system, prompting others to collectively reflect on the market changes and social trends that can actively contribute to the development of firm proactiveness (Lumpkin and Dess, 2001). By leveraging a solid information base from EA, the company can also reduce the level of uncertainty as it develops a clearer vision of the path forward, and thus increase its risk-taking propensity.

EA, therefore, supports the company's EO, which in turn promotes the identification of entrepreneurial opportunities (Song et al., 2017). Prior research argues that high EO firms have a strong propensity to constantly search for new entrepreneurial opportunities (Covin and Miles, 1999; Keh et al., 2007). These firms have a natural tendency to constantly scrutinize their operating environment with the aim of identifying novel opportunities and enhancing their competitive advantage. EO represents the way a company is organized to develop activities leading to new entry (Lumpkin and Dess, 1996). Empirical results from Wiklund and Shepherd's (2003: 1310) study confirm that “EO represents how a firm is organized in order to discover and exploit opportunities.” High EO firms prioritize the identification and exploitation of unexplored opportunities as a fundamental guiding principle of their organization (Ince et al., 2023; Martin and Javalgi, 2016; Miao et al., 2017). Consequently, enhancing the ability to recognize new entry opportunities represents the primary benefit of developing the company's EO (Wales et al., 2013). Wales et al. (2020: 640) argue that “EO-as-new entry initiatives captures externally directed conduct in the pursuit of opportunities for new value creation in the market.” The benefits of EO are detailed in many contexts: startups (Alikhani and Shahriari, 2022), social and institutional contexts (Urban, 2020), and rural contexts (Veidal and Flaten, 2014). According to Kang et al. (2016), EO helps shape the organizational climates and enables the development of an innovation climate, a proactive climate, and a risk-taking climate within the company. These climates foster the engagement of individuals in activities that enable the identification of new entrepreneurial opportunities: “when organizations are willing to support and reward innovative efforts, employees’ emotional reactions to searching for new business opportunities and creating new products or services may be enhanced” (Kang et al., 2016: 631). Based on these rationales, and consistent with the RBV and the orchestration view, we assume that the relationship between EA and entrepreneurial opportunity identification is mediated by the three dimensions of EO:

Hypothesis 2: The relationship between EA and entrepreneurial opportunity identification is mediated by innovativeness.

Hypothesis 3: The relationship between EA and entrepreneurial opportunity identification is mediated by proactiveness.

Hypothesis 4: The relationship between EA and entrepreneurial opportunity identification is mediated by risk-taking propensity.

Methodology

Sampling frame

To test our hypotheses, we used survey data from French small and medium-sized enterprises (SMEs). Consistent with the European Commission's definition, we defined SMEs as firms with fewer than 250 employees. We focused on SMEs because they are a key component of the economy and account for more than 99% of all companies in Europe. In addition, there are fewer hierarchies and bureaucracies in this type of organization, which gives entrepreneurs a fundamental role both strategically and operationally. As key operators in the collection and dissemination of information within the organization, entrepreneurs exert a significant influence on the development of a firm strategic orientation. Moreover, we chose to survey innovative companies as their founders are better informed about the current state of the market and the company's technological knowledge.

To constitute our sample, we approached the directors of innovation clusters. The objective was to present the subject of the research and request their help in accessing SME contacts. We partnered with 29 French innovation clusters and distributed an online questionnaire to 2401 entrepreneurs located within these clusters from May to September 2014. After three rounds of reminders, 269 questionnaires were received, for an 11.2% response rate. Of these 269 returned questionnaires, 46 were incomplete (most respondents stopped at the first measurement scale), 35 were not completed by the right person (the respondent was not the entrepreneur), and 36 were completed by companies with more than 250 employees. After purification, our final sample consists of 152 complete responses. The characteristics of the sample are presented in Table 1.

Table 1.

Descriptive characteristics of the sample.

	N	Percentage
Gender
Male	122	80.3
Female	30	19.7
Entrepreneur's age
Under 30	2	1.3
31–40	27	17.8
41–50	61	40.1
Over 50	62	40.8
Entrepreneur's education level
High school diploma	4	2.6
Bachelor's degree	15	9.9
Master's degree	87	57.2
Doctoral degree	46	30.3
Firm age
Under 5 years	33	21.7
5–9 years	47	30.9
10–19 years	38	25.0
Over 20 years	34	22.4
Firm size
Under 10 employees	84	55.3
10–49 employees	43	28.3
More than 50 employees	25	16.4
Strategic domain of activities
Agriculture	11	7.2
Chemistry	31	20.4
Consulting	12	7.9
Defense	4	2.6
Energy	12	7.9
Environment	13	8.6
Health	48	31.6
Information and communication technologies	46	30.3
Transport	10	6.6

Assessment of nonresponse bias

Following Armstrong and Overton (1977), we examined the probability of nonresponse bias. We compared early responders to late responders to verify that there was no significant difference between these two groups. The mean responses on each key variable for the two groups showed no significant differences, so nonresponse bias was not a potential threat.

Control for common method bias

Common method bias can also be a problem in research samples (Podsakoff et al., 2003). We used Harman's single factor as the first step in assessing this bias. An exploratory factor analysis was performed with all items loaded on a single factor in order to verify that the variance explained by all the items on the single factor does not exceed the threshold of 50%. In our case, when the items were loaded on a single factor, the explained variance was 28.05%, suggesting the absence of a common method bias.

We then submitted the measurement model to the common latent factor (CLF) test to capture the common variance between the model variables. The difference in chi-square between the unconstrained model (χ ² = 69.671 for 40 df) and the constrained model (χ ² = 41.231 for 29 df) was significant, meaning that variance was shared with the CLF. For each item, we checked that the difference between the standardized regression coefficients of the basic model and those of the model incorporating the CLF did not exceed 0.200. All the items were significantly related to their constructs in the basic CFA model. Therefore, the results of this second test confirmed those of Harman's single factor test, indicating that the research design was not influenced by common method bias.

Measures

All constructs were measured using scales well established in the literature. These measures were based on 7-point Likert scales, apart from the measure of entrepreneurial opportunity identification. We conducted exploratory factor analysis (EFA) with SPSS 26.0 and confirmatory factor analysis (CFA) with AMOS 26.0 to evaluate the convergent and discriminant validity of the scales.

Entrepreneurial alertness

We adopted the 13-item scale developed and validated by Tang et al. (2012) to measure EA. Two items from the original scale were removed due to poor factor loadings and another item was removed because it was not factored in its right dimension.

Entrepreneurial orientation

We used Covin and Slevin's (1989) scale to measure the three dimensions of EO. Consistent with Lumpkin and Dess (1996) and in agreement with recent studies (Kollmann et al., 2021), we rejected one item that measured competitive aggressiveness more than proactiveness.

Opportunity identification

To assess the ability of firms to identify entrepreneurial opportunities, we employed the measure developed by Ucbasaran et al. (2009). Respondents were asked to report the number of opportunities identified over the past five years, and eight responses were recorded (0, 1, 2, 3, 4, 5, 6–10, and > 10).

Control variables

Four variables were controlled. Entrepreneurs’ education was controlled because prior research indicates that the more educated entrepreneurs are, the more likely they absorb new ideas and seek out new products (Barker and Mueller, 2002). We used a five-point scale to assess the level of education (1: self-taught, 2: high school diploma, 3: bachelor's degree, 4: master's degree, and 5: doctoral degree). Entrepreneurs’ age (ranging from 28 to 72 years) was controlled because it can influence motivation to start a new venture and entrepreneurial behavior (Araujo et al., 2023). Firm size (the number of employees) was controlled because small firms tend to encounter greater difficulties in accessing resources to develop new strategies (Tang et al., 2008). Finally, firm age (the number of years since the creation of the company) was controlled because younger firms have been found to be more favorable to the adoption of entrepreneurial initiatives and to be better able to discover entrepreneurial opportunities in line with market needs (Rosenbusch et al., 2011).

Results

Table 2 summarizes the means, standard deviations, and correlations for all variables. We tested our hypotheses using structural equation modeling (SEM) with AMOS. Following Gerbing and Anderson (1988), we employed a two-step modeling approach: confirmatory factor analyses were first conducted to confirm the validity and reliability of the measurement instruments, then hypotheses were tested with SEM. The measurement model showed good model fit indices: χ²/df = 69.671/40, Δχ²/Δdf = 1.742, RMSEA = .070, CFI = .917, and SRMR = .082. We then tested the internal consistency and convergent validity of the measurement scales. Results indicated significant standardized loadings of all items on their respective constructs and each construct AVE (average variance extracted) was near or above the threshold of 0.50 (between 0.47 and 0.54). Internal consistency was demonstrated by composite reliability (CR) values that were all near or above the threshold of 0.7 (between 0.67 and 0.76). Discriminant validity was also established since the square root of the AVE (presented on the diagonal in Table 2) for each construct exceeded its paired correlation with any other latent variables (Fornell and Larcker, 1981). Finally, multicollinearity was not an issue since all estimated correlations between the variables were below the cutoff of 0.70 (Hair et al., 2009).

Table 2.

Summary statistics and correlation matrix.

		Mean	SD	α	CR	AVE	Correlations
		Mean	SD	α	CR	AVE	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
(1)	Entrepreneurial alertness	3.579	0.450	0.77	0.72	0.47	(0.685)
(2)	Innovativeness	1.904	0.537	0.72	0.75	0.51	.444***	(0.715)
(3)	Proactiveness	5.125	0.919	0.61	0.67	0.53	.396***	.153	(0.725)
(4)	Risk-taking propensity	3.532	0.862	0.66	0.77	0.54	.544***	.221***	.222***	(0.733)
(5)	Entrepreneurial opportunity identification	6.539	3.255	–	–		.317***	.208**	.232***	.083	–
(6)	Firm size	26.375	37.268	–	–		−.105	.008	−.106	.029	.050	-
(7)	Firm age	16.526	25.560	–	–		−.142	−.012	−.209***	−.074	.039	.231***	–
(8)	Entrepreneurs’ age	48.493	8.677	–	–		.136	.086	.111	.179**	−.142	.149	.081	–
(9)	Entrepreneurs’ education	6.046	1.006	–	–		.128	.096	−.049	.138	.039	−.229***	−.158	−.078	–

***p < 0.01; **p < 0.05; *p < 0.10.

Diagonal values depict the square root of the AVE for the main constructs.

To test our hypotheses, three hierarchical models were estimated: a non-mediated model, a partially mediated model, and a fully mediated model. Chi-square tests were then performed to observe the variations in the model fit. Table 3 presents the results. The partially mediated model provided a better model fit than either the non-mediated or fully mediated models (χ²/df = 25.599/17, Δχ²/Δdf = 1.506, RMSEA = .058, CFI = .945, and SRMR = .080.) We also examined the difference in chi-square values between partially mediated and non-mediated models (Δχ² = 4.700, p < 0.05 for Δdf = 1) and between partially mediated and fully mediated models (Δχ² = 10.130, p < 0.001 for Δdf = 1). The partially mediated model was significantly different from the other two models, confirming that the models were nested. Therefore, the partially mediated model was retained for examining our hypotheses.

Table 3.

Results of structural equation modeling analyses.

	Model
	Non-mediated	Partially mediated	Fully mediated
	Entrepreneurial opportunity identification (OI)
Firm Size → OI	.107	0.119**	.093
Firm Age → OI	.081	0.109	.098
Entrepreneur's age → OI	−.200**	−0.211**	−.204**
Entrepreneur's education → OI	.018	0.042	.052
EA → OI	.386***	0.319**	–
EA → Innovativeness	.444***	0.444***	.444***
EA → Proactiveness	.396***	0.396***	.396***
EA → Risk-taking propensity	.544***	0.544***	.544***
Innovativeness → OI	.072	0.073	.174**
Proactiveness → OI	–	0.175**	.253**
Risk-taking propensity → OI	−.108	−0.111	.021
(Indirect) EA → Proactiveness → OI		0.069**	0.069**
R ²	0.195	0.233	0.167
χ² (df)	30.299 (18)	25.599 (17)	35.729 (18)
CMIN/df	1.683	1.506	1.985
RMSEA (PCLOSE)	0.067 (0.227)	0.058 (0.353)	0.081 (0.094)
SRMR	0.080	0.080	0.080
TLI	0.843	0.884	0.773
CFI	0.921	0.945	0.887
AIC	84.299	81.599	89.729

RMSEA: root mean square error of approximation; SRMR: standardized root mean square residual; CFI: comparative fit index; AIC: Akaike information criterion;

Coefficients are standardized. ***p < 0.01; **p < 0.05; *p < 0.10.

The partially mediated model accounted for 23.3% of the entrepreneurial opportunity identification variance. Hypothesis 1 predicts that EA is positively associated with entrepreneurial opportunity identification. The results of SEM in Table 3 show a significant direct relationship between EA and entrepreneurial opportunity identification (β = 0.319, p = 0.002), supporting Hypothesis 1. Hypotheses 2, 3, and 4 assume that the relationship between EA and entrepreneurial opportunity identification is mediated by innovativeness (Hypothesis 2), proactiveness (Hypothesis 3), and risk-taking propensity (Hypothesis 4). To test the mediation effects, we followed the approach recommended by Baron and Kenny (1986). First, a significant relationship must exist between the independent variable (EA) and the dependent variable (entrepreneurial opportunity identification), and between the independent variable (EA) and the mediators (innovativeness, proactiveness, and risk-taking propensity). Second, a significant relationship must exist between the mediators and the dependent variable. Third, the significance of the indirect effect between independent and dependent variables through the mediators must be assessed.

As indicated in Table 3, EA was significantly associated with all three dimensions of EO (β = 0.444, p = 0.001 for innovativeness; β = 0.396, p = 0.001 for proactiveness; and β = 0.544, p = 0.001 for risk-taking propensity). However, only proactiveness was significantly associated with entrepreneurial opportunity identification (β = 0.175, p = 0.032). Therefore, no mediation effects were found for innovativeness or risk-taking, providing no support for Hypotheses 2 and 4. Then, we used the bootstrapping method to further examine the indirect effect between EA and entrepreneurial opportunity identification through proactiveness. Results show that the relationship between EA and entrepreneurial opportunity identification was partially mediated by proactiveness (standardized indirect effect = 0.069, 95% bias-corrected CI [0.144, 1.058]), thus supporting Hypothesis 3.

Discussion and conclusion

The aim of this article was to provide a better understanding of how established firms identify new entrepreneurial opportunities. The literature has focused primarily on identifying individual-related factors to explain entrepreneurial opportunity identification in the context of new venture creation (George et al., 2016; Roundy et al., 2018). However, there is a gap in the entrepreneurship literature regarding how established firms mobilize and leverage resources through their organizational context to identify new entrepreneurial opportunities (Hansen et al., 2016; Short et al., 2010) and promote sustainable regeneration (Covin and Miles, 1999). Drawing on the RBV and the resource orchestration view (Barney, 1991; Morrow et al., 2007; Sirmon et al., 2007, 2011), this article addresses this limitation in the literature. We conceptualize EA as a cognitive resource (Adomako et al., 2018) that must be directed within the organization, through the mobilizing vision provided by EO (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003), to stimulate entrepreneurial activities and lead to improved entrepreneurial opportunity identification. Based on data collected from 152 French entrepreneurs, our results partially support our assumption.

Implications for theory and practice

This research makes five theoretical contributions to literature. Our first contribution is to confirm empirically that EA is positively associated with improved identification of entrepreneurial opportunities. We, therefore, contribute to the literature by providing empirical evidence of the long-assumed relationship between EA and entrepreneurial opportunity identification (Ardichvili et al., 2003; Baron, 2006; Gaglio and Katz, 2001; Kirzner, 1979; Lanivich et al., 2022; Roundy et al., 2018; Tang, 2008; Urban, 2020). Using Tang et al.'s (2012) scale, which has strong psychometric qualities, our study confirms that EA is a cognitive resource (Adomako et al., 2018) acting as an antecedent to identifying entrepreneurial opportunities.

Our second contribution concerns the literature on EO. Previous research has focused primarily on studying the relationship between EO and firm performance, as well as the moderators and mediators of this relationship (Wales et al., 2013). Few studies have examined the antecedents of EO, which is a major limitation of EO research that needs to expand knowledge about the genesis of this strategic orientation (Rosenbusch et al., 2013; Turnalar-Çetinkaya, 2022; Wales, 2016). Further, previous research has focused on firm-level antecedents of EO (Cowden et al., 2022). This article contributes to filling this gap by revealing that EA is an antecedent of EO. Our results show a significant relationship between EA and each dimension of EO: innovativeness, proactiveness, and risk-taking propensity. Our results highlight that EA is a crucial individual, cognitive resource that helps the entrepreneur capitalize on valuable information to drive entrepreneurial activities within the firm (Keh et al., 2007). In doing so, our study confirms that EO can serve as a mobilizing vision to orchestrate and direct individual-level resource use toward entrepreneurship (Chirico et al., 2011).

Relatedly, our third contribution concerns the stream of research investigating the role played by EO in the orchestration resource process allowing the company to leverage resources to gain a competitive advantage and obtain superior performance (Chirico et al., 2011; Miao et al., 2017; Wales et al., 2013; Wiklund and Shepherd, 2003). We advance this line of research by considering not the influence of the resource orchestration process on firm performance, but rather its influence on entrepreneurial opportunity identification. Our study is among the first to explicitly apply the resource orchestration view to explain the organizational process allowing established firms to recognize entrepreneurial opportunities. Identifying new entrepreneurial opportunities is critical to enable a sustainable regeneration of the company through new product development and introduction (Covin and Miles, 1999). Specifically, our research extends the understanding of the resource orchestration process by addressing the role played by EO to direct and leverage EA—an individual, cognitive resource—to improve the identification of entrepreneurial opportunities.

Our fourth contribution is to provide a more nuanced view of the positive relationship between EO and entrepreneurial opportunity identification evidenced by Song et al. (2017). Previous research has emphasized that high EO firms tend to constantly search for entrepreneurial opportunities (Covin and Miles, 1999; Keh et al., 2007) that enable new entry (Lumpkin and Dess, 1996). EO is therefore recognized as critical to supporting the identification and exploitation of entrepreneurial opportunities (Ince et al., 2023; Martin and Javalgi, 2016; Miao et al., 2017; Wiklund and Shepherd, 2003). Yet, our study reveals that neither innovativeness nor risk-taking propensity have any influence on the identification of entrepreneurial opportunities, and that only proactiveness is positively associated with entrepreneurial opportunity identification. Consequently, only proactiveness partially mediates the relationship between EA and entrepreneurial opportunity identification. This result could be explained, at least partially, by previous research suggesting that the dimensions of EO operate differently in the organization (McKenny et al., 2018). We suspect that innovativeness and risk-taking might be more related to the exploitation stages of the entrepreneurial process, whereas proactiveness is more related to the opportunity identification stage of the entrepreneurial process (Shane and Venkataraman, 2000). Indeed, these results are aligned with the previous literature indicating that EO is related to both opportunity identification and exploitation. The results relevant to the significant role of proactiveness in opportunity identification also respond to calls from previous research on investigating proactiveness as a less explored yet crucial component of EO (Lumpkin and Dess, 2001; Tang et al., 2014).

The fifth contribution of this study is to advance our understanding of the relationship between EA and entrepreneurial opportunity identification. As suggested by Lanivich et al. (2022), the literature has yet to explore the constructs that moderate and mediate this relationship. Our study responds to this recent call by providing evidence that one dimension of EO—proactiveness—partially mediates the influence of EA on the identification of entrepreneurial opportunities. By developing and empirically examining a mediation model explaining the process of entrepreneurial opportunity identification in established firms, we also respond to George et al.'s (2016: 342) call to “place added emphasis on the empirical examination of more complex research models that examine the role of antecedents and influencing factors’ effects in the opportunity recognition process.”

This research has also three important practical implications. EA is a cognitive resource that provides valuable information for identifying new entrepreneurial opportunities. First, since EA can be learned and developed (Adomako et al., 2018; Roundy et al., 2018; Tang et al., 2012), our findings suggest that entrepreneurs should develop their alertness to enhance the discovery of new entrepreneurial opportunities. Policymakers can assist them in this endeavor by developing education and training programs. These programs could help entrepreneurs develop strategies for schema modification by exposing them to analogies and inductive reasoning (Valliere, 2013). Second, entrepreneurs should emphasize the development of an EO within their organization as it provides a mobilizing vision for leveraging their company's resources and gaining a competitive advantage. Specifically, they should encourage proactiveness in their companies to improve the ability to identify new entrepreneurial opportunities. Third, entrepreneurs should be particularly attentive to sharing the valuable information they gain from their EA with members of their organization. In doing so, entrepreneurs can act as providers of information stimulating firm proactiveness, which in turn improves the identification of entrepreneurial opportunities. Entrepreneurs should therefore rely on their EA to create a proactive organizational climate (Kang et al., 2016), as such a climate can foster employee engagement in exploratory activities that increase the likelihood of discovering something new and positioning the firm as a market leader with significant competitive advantage (Lumpkin and Dess, 2001).

Limitations and future research directions

This research is not without its limitations, which also suggests avenues for future research. First, the sample used in this research focuses on innovative firms supported by innovation clusters. Firms with community support are more likely to discover opportunities through their networks (Donbesuur et al., 2020). Future research could compare firms with and without community support to assess whether innovation cluster support influences entrepreneurial opportunity identification. Second, our study is conducted in a developed economy, as our sample consists of French SMEs. Future studies could examine the relationship between EA, EO, and entrepreneurial opportunity identification in developing economies, which provide a different context that may lead to different findings (Adomako et al., 2018). Third, our results provide no evidence of the influence of innovativeness or risk-taking propensity on entrepreneurial opportunity identification, suggesting that these dimensions of EO might instead be related to entrepreneurial opportunity exploitation. Further research is needed to explore this assumption. Fourth, this study has focused on the number of opportunities recognized through EA and EO. However, EA and EO may also influence the type of opportunities identified (Tang et al., 2012). Future studies could, for example, consider the economic potential of the opportunities discovered. Finally, this research has examined how an important cognitive resource—EA—can be mobilized within the firm to improve the identification of entrepreneurial opportunities. A promising avenue for future research could be to explore whether other types of resources may be leveraged through the mobilizing vision of EO to increase the number of opportunities identified.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jintong Tang

References

Adomako

Danso

Boso

, et al. (2018) Entrepreneurial alertness and new venture performance: facilitating roles of networking capability. International Small Business Journal: Researching Entrepreneurship 36(5): 453–472.

Alikhani

Shahriari

(2022) The effect of servant leadership on competitiveness of startups: the mediating role of entrepreneurial orientation and self-efficacy. The International Journal of Entrepreneurship and Innovation 146575032211345.

Alvarez

Barney

(2005) How do entrepreneurs organize firms under conditions of uncertainty? Journal of Management 31(5): 776–793.

Alvarez

Barney

(2007) Discovery and creation: alternative theories of entrepreneurial action. Strategic Entrepreneurship Journal 1(1–2): 11–26.

Alvarez

Barney

McBride

, et al. (2014) Realism in the study of entrepreneurship. Academy of Management Review 39(2): 227–233.

Araujo

Karami

Tang

, et al. (2023) Entrepreneurial alertness: a meta-analysis and empirical review. Journal of Business Venturing Insights: e00394.

Ardichvili

Cardozo

Ray

(2003) A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing 18(1): 105–123.

Armstrong

Overton

(1977) Estimating nonresponse bias in mail surveys. Journal of Marketing Research 14: 396–402.

Barker

Mueller

(2002) CEO Characteristics and Firm R&D Spending. Management Science 48(6): 782–801.

10.

Barney

(1991) Firm resources and sustained competitive advantage. Journal of Management 17(1): 99–120.

11.

Baron

(2006) Opportunity recognition as pattern recognition: how entrepreneurs ‘connect the dots’ to identify new business opportunities. Academy of Management Perspectives 20(1): 104–119.

12.

Baron

Kenny

(1986) The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51(6): 1173–1182.

13.

Busenitz

(1996) Research on entrepreneurial alertness. Journal of Small Business Management 34(4): 35–44.

14.

Chirico

Sirmon

Sciascia

, et al. (2011) Resource orchestration in family firms: investigating how entrepreneurial orientation, generational involvement, and participative strategy affect performance: resource orchestration in family firms. Strategic Entrepreneurship Journal 5(4): 307–326.

15.

Covin

Miles

(1999) Corporate entrepreneurship and the pursuit of competitive advantage. Entrepreneurship Theory and Practice 23(3): 47–63.

16.

Covin

Slevin

(1989) Strategic management of small firms in hostile and benign environments. Strategic Management Journal 10(1): 75.

17.

Cowden

Karami

Tang

, et al. (2022) The spectrum of perceived uncertainty and entrepreneurial orientation: impacts on effectuation. Journal of Small Business Management. https://doi.org/10.1080/00472778.2022.2051179.

18.

Davidsson

(2015) Entrepreneurial opportunities and the entrepreneurship nexus: a re-conceptualization. Journal of Business Venturing 30(5): 674–695.

19.

Donbesuur

Boso

Hultman

(2020) The effect of entrepreneurial orientation on new venture performance: contingency roles of entrepreneurial actions. Journal of Business Research 118: 150–161.

20.

Fornell

Larcker

(1981) Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research 18(3): 382–388.

21.

Gaglio

Katz

(2001) The psychological basis of opportunity identification: entrepreneurial alertness. Small Business Economics 16(2): 95–111.

22.

George

Parida

Lahti

, et al. (2016) A systematic literature review of entrepreneurial opportunity recognition: insights on influencing factors. International Entrepreneurship and Management Journal 12(2): 309–350. DOI: 10.1007/s11365-014-0347-y.

23.

Gerbing

Anderson

(1988) An updated paradigm for scale development incorporating uni. JMR, Journal of Marketing Research 25(2): 186.

24.

Grégoire

Shepherd

(2012) Technology-market combinations and the identification of entrepreneurial opportunities: an investigation of the opportunity-individual nexus. Academy of Management Journal 55(4): 753–785.

25.

Hair

Black

Babin

, et al. (2009) Multivariate Data Analysis: A Global Perspective. Seventh Edition. Prentice Hall.

26.

Hansen

Monllor

Shrader

(2016) Identifying the elements of entrepreneurial opportunity constructs: recognizing what scholars are really examining. The International Journal of Entrepreneurship and Innovation 17(4): 240–255.

27.

Ince

Imamoglu

Karakose

(2023) Entrepreneurial orientation, social capital, and firm performance: the mediating role of innovation performance. The International Journal of Entrepreneurship and Innovation 24(1): 32–43.

28.

Kaish

Gilad

(1991) Characteristics of opportunities search of entrepreneurs versus executives: sources, interests, general alertness. Journal of Business Venturing 6(1): 45–61.

29.

Kang

Matusik

Kim

T-Y

, et al. (2016) Interactive effects of multiple organizational climates on employee innovative behavior in entrepreneurial firms: a cross-level investigation. Journal of Business Venturing 31(6): 628–642.

30.

Keh

Nguyen

TTM

(2007) The effects of entrepreneurial orientation and marketing information on the performance of SMEs. Journal of Business Venturing 22(4): 592–611.

31.

Kenneth

(1971) The concept of corporate strategy. Homewood, Illinois: Dow Jones Irwin Inc., pp.26–27

32.

Kirzner

(1979) Perception Opportunity and Profit. Chicago IL: Université of Chicago Press.

33.

Klein

(2008) Opportunity discovery, entrepreneurial action, and economic organization. Strategic Entrepreneurship Journal 2(3): 175–190.

34.

Kollmann

Stöckmann

Niemand

, et al. (2021) A configurational approach to entrepreneurial orientation and cooperation explaining product/service innovation in digital vs. non-digital startups. Journal of Business Research 125: 508–519.

35.

Kromidha

Refai

Pattinson

, et al. (2022) International journal of entrepreneurship and innovation editors’ series: innovation opportunities and future direction in entrepreneurship research. The International Journal of Entrepreneurship and Innovation 23(1): 3–4.

36.

Lanivich

Smith

Levasseur

, et al. (2022) Advancing entrepreneurial alertness: review, synthesis, and future research directions. Journal of Business Research 139: 1165–1176.

37.

Levasseur

Tang

Karami

, et al. (2022) Increasing alertness to new opportunities: the influence of positive affect and implications for innovation. Asia Pacific Journal of Management 39(1): 27–49.

38.

Lumpkin

Dess

(1996) Clarifying the entrepreneurial orientation construct and linking it to performance. The Academy of Management Review 21(1): 135.

39.

Lumpkin

Dess

(2001) Linking two dimensions of entrepreneurial orientation to firm performance. Journal of Business Venturing 16(5): 429–451.

40.

Martin

Javalgi

(2016) Entrepreneurial orientation, marketing capabilities and performance: the moderating role of competitive intensity on Latin American international new ventures. Journal of Business Research 69(6): 2040–2051.

41.

McKenny

Short

Ketchen

, et al. (2018) Strategic entrepreneurial orientation: configurations, performance, and the effects of industry and time. Strategic Entrepreneurship Journal 12(4): 504–521.

42.

McMullen

Brownell

Adams

(2021) What makes an entrepreneurship study entrepreneurial? Toward a unified theory of entrepreneurial agency. Entrepreneurship Theory and Practice 45(5): 1197–1238.

43.

McMullen

Plummer

Acs

(2006) What is an entrepreneurial opportunity? Small Business Economics 28(4): 273–283. DOI: 10.1007/s11187-006-9040-z.

44.

McMullen

Shepherd

(2006) Entrepreneurial action and the role of uncertainty in the theory of the entrepreneur. Academy of Management Review 31(1): 132–152.

45.

Miao

Coombs

Qian

, et al. (2017) The mediating role of entrepreneurial orientation: a meta-analysis of resource orchestration and cultural contingencies. Journal of Business Research 77: 68–80.

46.

Miller

(1983) The correlates of entrepreneurship in three types of firms. Management Science 29(7): 770.

47.

Morrow

Sirmon

Hitt

, et al. (2007) Creating value in the face of declining performance: firm strategies and organizational recovery. Strategic Management Journal 28(3): 271–283.

48.

Nair

Gaim

Dimov

(2022) Toward the emergence of entrepreneurial opportunities: organizing early-phase new venture creation support systems. Academy of Management Review 47(1): 162–183.

49.

Podsakoff

MacKenzie

Lee

J-Y

, et al. (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 88(5): 879–903.

50.

Puhakka

(2011) Developing a creative-cognitive model of entrepreneurial alertness to business opportunities. Journal of Management and Strategy 2(4): 85–94. DOI: 10.5430/jms.v2n4p85.

51.

Rosenbusch

Brinckmann

Bausch

(2011) Is innovation always beneficial? A meta-analysis of the relationship between innovation and performance in SMEs. Journal of Business Venturing 26(4): 441–457.

52.

Rosenbusch

Rauch

Bausch

(2013) The mediating role of entrepreneurial orientation in the task environment–performance relationship: a meta-analysis. Journal of Management 39(3): 633–659.

53.

Roundy

Harrison

Khavul

, et al. (2018) Entrepreneurial alertness as a pathway to strategic decisions and organizational performance. Strategic Organization 16(2): 192–226.

54.

Sarasvathy

(2001) Causation and effectuation: toward a theoretical shift from economic inevitability to entrepreneurial contingency. The Academy of Management Review 26(2): 243–263.

55.

Sarasvathy

Venkataraman

(2011) Entrepreneurship as method: open questions for an entrepreneurial future. Entrepreneurship: Theory & Practice 35(1): 113–135.

56.

Shane

(2000) Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science 11(4): 448–469.

57.

Shane

(2012) Reflections on the 2010 AMR decade award: delivering on the promise of entrepreneurship as a field of research. Academy of Management Review 37(1): 10–20.

58.

Shane

Nicolaou

Cherkas

, et al. (2010) Do openness to experience and recognizing opportunities have the same genetic source? Human Resource Management 49(2): 291–303.

59.

Shane

Venkataraman

(2000) The promise of entrepreneurship as a field of research. Academy of Management Review 25(1): 217–226.

60.

Shepherd

Wennberg

Suddaby

, et al. (2019) What are we explaining? A review and agenda on initiating, engaging, performing, and contextualizing entrepreneurship. Journal of Management 45(1): 159–196.

61.

Short

Ketchen

Shook

, et al. (2010) The concept of ‘opportunity’ in entrepreneurship research: past accomplishments and future challenges. Journal of Management 36(1): 40–65.

62.

Simsek

Lubatkin

Veiga

, et al. (2009) The role of an entrepreneurially alert information system in promoting corporate entrepreneurship. Journal of Business Research 62(8): 810–817.

63.

Sirmon

Hitt

Ireland

(2007) Managing firm resources in dynamic environments to create value: looking inside the black box. Academy of Management Review 32(1): 273–292.

64.

Sirmon

Hitt

Ireland

, et al. (2011) Resource orchestration to create competitive advantage: breadth, depth, and life cycle effects. Journal of Management 37(5): 1390–1412.

65.

Song

Min

Lee

, et al. (2017) The effects of network reliance on opportunity recognition: a moderated mediation model of knowledge acquisition and entrepreneurial orientation. Technological Forecasting and Social Change 117: 98–107.

66.

Srivastava

Sahaym

Allison

(2021) Alert and awake: role of alertness and attention on rate of new product introductions. Journal of Business Venturing 36(4): 106023.

67.

Tang

(2008) Environmental munificence for entrepreneurs: entrepreneurial alertness and commitment. International Journal of Entrepreneurial Behaviour & Research 14(3): 128–151.

68.

Tang

(2009) Exploring the constitution of entrepreneurial alertness: the regulatory focus view. Journal of Small Business and Entrepreneurship 22(3): 221–238.

69.

Tang

(2010) How entrepreneurs discover opportunities in China: an institutional view. Asia Pacific Journal of Management 27(3): 461–479.

70.

Tang

Baron

(2021) Entrepreneurial alertness: exploring its psychological antecedents and effects on firm outcomes. Journal of Small Business Management. DOI: 10.1080/00472778.2021.1945071.

71.

Tang

Kacmar

KMM

Busenitz

(2012) Entrepreneurial alertness in the pursuit of new opportunities. Journal of Business Venturing 27(1): 77–94.

72.

Tang

Khan

(2007) Dynamic interactions between alertness and systematic search: a yin and yang perspective on opportunity recognition and innovation. The International Journal of Entrepreneurship and Innovation 8(3): 175–187.

73.

Tang

Katz

(2014) Proactiveness, Stakeholder-firm power difference, and product safety and quality of Chinese SMEs. Entrepreneurship Theory and Practice 38(5): 1129–1157. DOI: 10.1111/etap.12029.

74.

Tang

Marino

, et al. (2008) Exploring an inverted U-Shape relationship between entrepreneurial orientation and performance in Chinese ventures. Entrepreneurship Theory and Practice 32(1): 219–239.

75.

Tumasjan

Braun

(2012) In the eye of the beholder: how regulatory focus and self-efficacy interact in influencing opportunity recognition. Journal of Business Venturing 27(6): 622–636.

76.

Turnalar-Çetinkaya

(2022) How managing errors facilitates entrepreneurial orientation: the mediating role of ambidextrous leadership. The International Journal of Entrepreneurship and Innovation: 1–13.

77.

Ucbasaran

Westhead

Wright

(2009) The extent and nature of opportunity identification by experienced entrepreneurs. Journal of Business Venturing 24(2): 99–115.

78.

Urban

(2020) Entrepreneurial alertness, self-efficacy and social entrepreneurship intentions. Journal of Small Business and Enterprise Development 27(3): 489–507.

79.

Valliere

(2013) Towards a schematic theory of entrepreneurial alertness. Journal of Business Venturing 28(3): 430–442.

80.

Veidal

Flaten

(2014) Entrepreneurial orientation and farm business performance: the moderating role of on-farm diversification and location. The International Journal of Entrepreneurship and Innovation 15(2): 101–112.

81.

Wales

(2016) Entrepreneurial orientation: a review and synthesis of promising research directions. International Small Business Journal: Researching Entrepreneurship 34(1): 3–15.

82.

Wales

Covin

Monsen

(2020) Entrepreneurial orientation: the necessity of a multilevel conceptualization. Strategic Entrepreneurship Journal 14: 639–660.

83.

Wales

Gupta

Marino

, et al. (2019) Entrepreneurial orientation: international, global and cross-cultural research. International Small Business Journal: Researching Entrepreneurship 37(2): 95–104.

84.

Wales

Kraus

Filser

, et al. (2021) The status quo of research on entrepreneurial orientation: conversational landmarks and theoretical scaffolding. Journal of Business Research 128: 564–577.

85.

Wales

Patel

Parida

, et al. (2013) Nonlinear effects of entrepreneurial orientation on small firm performance: the moderating role of resource orchestration capabilities: nonlinear effects of EO on small firm performance. Strategic Entrepreneurship Journal 7(2): 93–121.

86.

Wiklund

Shepherd

(2003) Knowledge-based resources, entrepreneurial orientation, and the performance of small and medium-sized businesses. Strategic Management Journal 24(13): 1307–1314.

87.

Wiklund

Shepherd

(2005) Entrepreneurial orientation and small business performance: a configurational approach. Journal of Business Venturing 20(1): 71–91.

88.

Wood

(2017) Misgivings about dismantling the opportunity construct. Journal of Business Venturing Insights 7: 21–25.

89.

Wood

McKinley

(2020) The entrepreneurial opportunity construct: dislodge or leverage? Academy of Management Perspectives 34(3): 352–365.