Top management team diversity and high performance: An integrative approach based on upper echelons and complexity theory

Depósito de Investigación de la Universidad de Sevilla https://idus.us.es/ This is an Accepted Manuscript of an article published by Elsevier in European Management Journal, Vol. 38, issue 1 on February 2020, available at: https://doi.org/10.1016/j.emj.2019.06.006 Copyright 2020 Elsevier. En idUS Licencia Creative Commons CC BY-NC-ND 1 Top Management Team diversity and high performance: an integrative approach based on Upper Echelons and Complexity Theory Abstract This paper analyses Top Management Team (TMT) composition diversity as an antecedent of firm performance in accordance with a recent paradigm based on Complexity Theory. Research into TMT diversity is commonly seen as a double-edged sword because inconclusive results have been achieved in prior studies. This controversy has reinforced the call to employ a more appropriate methodology by moving beyond the reliance on multiple regression analysis and towards the use of fuzzy-set qualitative comparative analysis. The study provides various TMT diversity configurations that lead to high performance. The study therefore contributes towards the TMT diversity literature by utilising asymmetric testing to advance in the understanding of the diversity of TMT attributes as an antecedent of high firm outcome. The paradigm currently facing TMT internal complexity is doubly relevant for managers, to ascertain the best TMT diversity compositions to achieve the best strategic goal and thereby the highest firm outcome, and for new research avenues in the demographic literature, to obtain richer insights from TMT data, which might provide additional information on the complex relations established within these TMTs. Keywords: TMT composition diversity, High firm performance, Complexity Theory, Fuzzy-set qualitative comparative analysis, Asymmetric testing. 1. Introduction The highly complex knowledge held by members of Top Management Teams (TMTs) is essential for a firm’s success (Chen, Kang & Butler, 2019; Drucker, 1974; Hambrick, 2007; Roh, Chun, Ryou & Son, 2019). However, this knowledge requires an in-depth and valued understanding of the features of the TMT and the way they interact, to achieve the planned goals involved in a managerial process (Díaz-Fernández, González-Rodríguez & Simonetti, 2015 a, b; Hutzschenreuter & Horstkotte, 2013; Lampaki & Papadakis, 2018). The relevance of the managerial role played by TMT members has been recognised as the beginning of the century, and abundant literature has been produced concerning Upper Echelons (Certo, Lester, Dalton & Dalton, 2006; Lin & Kuo, 2007; Crossland & Hambrick, 2011; Wiersema & Bird, 1996). This theory, introduced and developed by Hambrick and Mason (1984), claims that organisations are a reflection of their top managers as the traits of the TMTs are determinants of a firm’s strategic choices and thereby of its organisational performance (Crossland, Zyung, Hiller & Hambrick, 2014; Georgakakis, Greve & Ruigrok, 2017; Yohannes & Ayako, 2016). In addition to the recognition of the major role that the diversity of TMTs plays in firm performance (Akewushola, Elegunde & Saka, 2018; Bach & Lee, 2018; Oduor and Kilika, 2018), a considerable debate and controversy has also emerged around this school of thought, which is widely known as the ‘Black box’ of the literature on demography (Hope, Eisenhardt & Xin, 1999; Lawrence, 1997; Simons, Pelled & Smith, 1999). In this debate, the mechanism underlying the relationship between demographic and managerial traits and organisational outcomes acquires special relevance (Boone, Lokshin, Guenter and Belderbos, 2019; Buyl, Boone, Hendriks & Matthyssens, 2011; Mohr & Batsakis, 2018; Nielsen & Nielsen, 2013). Despite efforts made by researchers of organisational demography to analyse the influence of TMT diversity attributes on firm performance (Allen, Dawson, Wheatly, & White, 2008; Auden, Shackman, & Onken, 2006; Díaz- 2 Fernández, González-Rodríguez, & Simonetti, 2015c; Erhardt & Werbel, 2003), the results achieved appear to be contradictory when focusing on different environmental and methodological issues (Pelled, Eisenhardt, & Xin, 1999; Smith, Smith, Sims, O’Bannon, Scully, & Olian, 1994; Tihanyi, Ellstrand, Daily & Dalton, 2000). The controversy, which remains largely unresolved (Bantel & Jackson, 1989; Díaz-Fernández, González- Rodríguez, & Pawlak, 2014; Roh et al., 2018), might have been caused by any of several reasons: The widespread use of an inappropriate methodology (Dainty, 2008; Murray, 1989; Wiersema and Bowen, 2009); the fact that the Upper Echelons conceptualisation remains insufficiently mature to provide practitioners with a comprehensive knowledge of its main purpose (Abatecola & Cristofaro, 2018; Buchanan and Bryman, 2007; Cassell & Johnson, 2006); and the influence of the complex and competitive environment in which the managers of the companies operate (Haleblian & Finkesltein, 1993; Vachon & Klassen, 2008; Yamak et al. 2014). On the other hand, it is widely recognised that ‘Upper Echelons research is increasingly multidisciplinary in nature’ (Nielsen, 2010, p. 1). Because of its historically evolving and self-propagating basis, research into Upper Echelons has entered diverse research fields both inside and outside the academic discipline of management (Wren & Bedeian, 2017), which has led to consistent streams of research and theories (Abatecola & Cristofaro, 2018; Carpenter, Geletkanycz & Sanders, 2004; Hambrick, 2007; Dhaouadi, 2018). Furthermore, as Whetten (1989) points out, the most innovative contributions in Upper Echelons research are those regarding demographic literature when combined with other theories from different scientific disciplines. Moreover, the complexity of diversity within TMTs needs to be acknowledged and operationalised accordingly, and the relevance of adopting a multilevel research approach should be stressed (Cannella & Holcomb, 2015), in addition to that of devoting attention to sociobehavioural and cognitive influences (Bromiley & Rau, 2016) within TMTs. In accordance with the aforementioned arguments, a new approach emerges whereby the Complexity Theory (CT) on the Upper Echelons framework delves more deeply into the complexity of the relationships between TMT composition diversity and high firm performance. In the traditional academic literature, the influence of TMT diversity on firm outcomes has been widely recognised by scholars (Buyl, Boone & Hendriks, 2014; Cannella, Park & Lee, 2008; Nielsen & Nielsen, 2013; van Dijk, van Engen, & van Knippenberg, 2012). However, the results achieved by using multiple regression analysis (MRA) and structural equation modelling (SEM), which assume symmetric relations among the variables, appear to be inconclusive. Although several papers show evidence of positive relationships between certain TMT diversity attributes and performance (Nielsen, 2010), others report negative relationships (O’Relly, Snyder, Boothe, 1993; Simons et al., 1999) and even no relationship at all (Farrell & Hersch, 2005; Nüesch, 2009). These results give rise to the consideration of asymmetric complex relationships between the composition diversity of TMTs and firm outcomes. Based on the CT, Woodside (2013 a, b; 2014; 2015) advocates a new paradigm in research, by moving from symmetric testing to asymmetric testing of the relationships between variables through fuzzy-set qualitative comparative analysis (fsQCA). Despite fsQCA being originally developed by researchers pertaining to the field of sociology (Ragin, 2008), it has recently gained attention in other scientific and academic areas, such as management (Crilly, Zollo & Hansen, 2012; Misangyi, Greckhamer, Furnari, Fiss, Crilly & Aguilera, 2017; Greckhamer, Misangyi, Elms & Lacey, 2008; Misangyi, Greckhamer, Furnari, Fiss, Crilly & Aguilera, 2017), innovation (Ordanini & Maglio, 2009; Ordanini et al., 2014), organisation science (Fiss, 2007; Fiss, 2011; Meier & Donzé, 2012) and marketing (Chung & Woodside, 2011; Schuchmacher et al., 2013; Woodside 3 & Zhang, 2012), to delve deeper into the knowledge and understanding of the complex configuration of antecedent conditions that explain an outcome. The present study contributes towards Upper Echelons by highlighting the asymmetric complex relationship observed between the diversity of TMT attributes and high firm performance, which enhances the understanding of these complex relationships in a company. The study, which bridges Upper Echelons and CT, offers richer insights into how the configurations underlying different TMT internal compositions allow the company to reach high firm performance. Our study strives to shed light on the internal complexity within a TMT, and thereby on its inherent consequence on the company outcome. Hence, this research constitutes the first attempt to integrate Configural Analysis into the demographic literature to explore the diverse configurations in terms of the diversity of TMT attributes leading to a high firm performance. To address the topic, the paper is structured as follows. In Section 2, a literature review on Upper Echelons and its relation with the CT is presented. In Section 3, the main methodological issues are explained, and the findings are described in Section 4. A discussion of the main implications from the results is offered in Section 5. Suggestions for future research avenues to overcome the limitations of the study are presented in Section 6. Section 7 ends with the general conclusions drawn from the research. 2. Literature Review Traditionally, papers in the demographic and strategy literature have supported the relationship between TMT diversity and organisational decisions (Barsade et al., 2000; Cannella et al., 2008; Humphrey et al., 2009; Li & Tan, 2013). According to this theory, the managerial decisions are strongly influenced by values, beliefs, perceptions and judgements of top managers (Chi, Huang & Lin, 2009; Horwitz & Horwitz, 2007; Humphrey et al., 2009; Srivastava & Lee, 2008). Hambrick and Mason (1984) considered the use of TMT characteristics as a good proxy for cognition due to the difficulties of access and measurement of the cognitive variables. In this respect, TMT background diversity has been assumed to be a good indicator of cognitive diversity (Bromiley & Rau, 2016; Lin & Kuo, 2007). Managerial decisions, made under conditions of complex, uncertain and ambiguous information, are affected by individual experiences and psychological traits of top managers (Finkelstein & Hambrick, 1990; Schmid & Dauth, 2014). These individual characteristics, which influence organisational outcomes, render top managers as an important part of strategic management (Finkelstein et al., 2009). Understanding the mechanism through which the combined effect of the TMT composition diversity influences the decision-making process constitutes a difficult task that holds great relevance for the success of the firm (Harrison, Price, Gavin, & Florey, 2002). Most of the studies on TMT diversity and firm performance have used Upper Echelons as the main theoretical perspective, although in combination with other theories, such as Behavioural Theory, Psychological Theory and Organisational Theory (Cyert & March, 1963; Nielsen, 2010). From these frameworks, papers have dealt with the complexity behind the interactions among TMT diversity attributes with the specification of the interaction terms in the linear regression models (Canella, Park, & Lee, 2008; Jackson & Joshi, 2004). Nevertheless, on the one hand, linear regression models adopt very restrictive assumptions, such as linear and symmetric relationships between TMT diversity attributes and firm performance; and on the other hand, the interaction terms in these models fail to include all possible combinations of diversity of TMT attributes for a desired firm outcome due to collinearity issues. Furthermore, inconclusive findings with regard to the influence of TMT diversity composition on a firm’s performance have been 4 observed from those studies (Ferrier, 2001; Finkelstein & Hambrick, 1996; Williams & O’Reilly, 1998). This theoretical controversy, well-known as the demography ‘black box’, and the inconclusive results achieved in the literature are mostly attributed to the methodological weakness of these studies (Nielsen, 2010). In fact, this research deficiency has already been pointed out by Hambrick and Mason (1984) in their early work, whereby they argue that complexity of the relationships established between individuals and organisations in competitive environments requires multidisciplinary research and sufficiently strong methodologies to capture those complex relations. The vast majority of research in the demographic literature employs MRA and focuses on the main effect of TMT diversity features and on the moderator effect of the environmental variables on the relationship between TMT diversity and firm performance (Bakar & Sheer, 2013; Carpenter & Fredrickson, 2001; Carpenter, 2002). In another context different from that of Upper Echelons, Woodside (2013 a, b) states that the focus of net effects of main and interaction terms in the linear regression model is misleading because, in real life, not all cases in the data support positive or negative relationships between the independent and dependent variables. Rather, in reality, one or more combinations of antecedent conditions give rise to high values in the outcome conditions. It is precisely the presence or absence of attributes that characterises the configuration for an outcome to occur, and hence, the term interaction in linear models cannot be understood as configurations in the way that they are defined in the configural approach (Ragin, 2006; Woodside, 2013 a, b). Dick and Casell (2002) also noted that the underlying reason for the inconclusive results obtained in the demographic literature is due to the fact that Upper Echelons research tends to obfuscate on certain theoretical and methodological issues that are widely used in this field. Hence, a need emerges to apply alternative theories in combination with the Upper Echelons perspectives to find the answer to the fundamental research question (RQ) of whether TMT composition diversity contributes towards the accuracy of a firm's strategic actions and therefore towards a high level of firm performance. Since the 20th century, the concept of complexity has been integrated into practically all fields encouraging discussions concerning complex reality, the theory of complex systems and the paradigm of complexity (Balandier, 1989). Simon (1965) conceives a complex system as a nested hierarchy of subsystems such as the hierarchy observed from the relation of the entities, industry, firms and TMTs, that interact in a non-simple way. Accordingly, Urry (2005) asserts that CT examines how components of an emergent, dynamic and self-organising system, such as TMTs in a firm, ‘spontaneously’ develop collective properties and patterns through their interactions. This theory declares that any system formed by interacting entities produces non-linear and positive feedback (Walby, 2007). Regarding CT, Ragin (2008) also admits that, in real life, the symmetric assumption is rather simplistic and hence, asymmetric relationships are often present. Symmetric relationships imply that high (low) values of a vector X of explanatory variables (antecedent conditions, such as diversity of TMT traits) are both necessary and sufficient to obtain high (low) values of Y (outcome condition, such as firm performance). Asymmetric relationships indicate that high values of X (high diversity in TMT traits) are sufficient but not a necessary condition for high values of Y (high performance) to occur. This insight is consistent with the CT proposed by Byrne (2005), who claims that high or low scores of X might lead to high values of Y depending on the configurations along with other antecedent conditions of Y. The same outcome, let’s say, high firm performance, might therefore be achieved by a combination of different antecedents (diversity of TMT traits). 5 Summarising, from the CT, the diversity of certain TMT traits cannot be considered in an isolated way when the influence of the diversity of TMT composition on organisational performance is analysed. Furthermore, the diversity of TMT characteristics interacts in opposite directions with regard to firm decisions. On the one hand, greater diversity encourages teams to share different perspectives and ideas, which positively affects the decision-making process. On the other hand, greater diversity implies the appearance of more conflicts within the team which can be time-consuming and therefore costly for the company in terms of decision quality and, hence, of results. The complexity of the mechanism through which diversity influences company decisions makes it difficult for researchers and practitioners to determine the best combination of demographic characteristics that would lead to the best decision-making outcome for the company and would make it necessary to adopt the CT. The CT is justified by considering Upper Echelons from the perspective of the theory of complex systems, which can lead to a better understanding of the relationships of TMT composition diversity and high firm performance. The CT and qualitative comparative analysis (QCA) posit several tenets (Woodside, 2013 a, b; Wu et al., 2014) of special relevance to address the inconclusive results derived from methodological weaknesses in the demographic literature. The first tenet states that causal factors rarely lead to an outcome in isolation: Outcomes of interest (such as high firm performance) result from a combination of antecedents and not from a single antecedent. Thus, by focusing on Upper Echelons, the CT does not emphasise the net or marginal effect of each simple condition (age, education, functional, industry and experience diversity) on the outcome (high firm performance) in a configurational model but rather describes and predicts the outcome by complex (two or more) antecedent conditions. The second premise of CT posits that the same antecedent (such as a low score of a single antecedent) might be associated to different outcomes (low or high outcome scores) depending on the other antecedents that form a causal combination of conditions. Such principles imply the concept of ‘equifinality’, meaning that the same outcome can be achieved through various configurations of causal factors (Ragin, 2000). The CT in Upper Echelons recognises that alternative combinations of antecedents (age, education, functional, industry and experience diversity) will lead to a high score in the outcome (high firm performance). There is more than one combination of the diversity of TMT attributes that explains the outcome condition. Considering that fsQCA is an exploratory method, the following RQ is proposed from these statements: RQ1: Diverse configurations of complex TMT compositions are equifinal in leading to the achievement of high firm performance. Because a firm is a hierarchical structure with complex interconnected substructures, both firm and TMT size may influence firm performance. In particular, large companies are often characterised by a greater number of members integrated into their management teams, and therefore, it could be assumed that they are more inclined to have more heterogeneous TMTs in terms of attribute diversity. Likewise, it could be assumed that high TMT diversity appears more frequently in those TMTs with a high number of members and that this combination influences firm performance. The following RQ is adopted: RQ2. Firm and TMT size influence the configurations of the diversity of the TMT attributes on high firm performance. 6 The conceptual framework of this paper (Figure 1) puts forward that while high firm performance (outcome) depends on TMT demographic and managerial trait diversity, only the meaningful configurations of these attributes really lead to this outcome. The research model employs Venn diagrams to describe the configurational nature of the antecedent conditions that lead to high firm performance. [Insert Figure 1] 3. Method 3.1. Data Source Data were collected from subsidiary companies of multinational high-technology companies pertaining to 8 countries in the G20 group (USA, China, France, Germany, Canada, Italy, the United Kingdom and Spain) with their headquarters in Spain. This selection was chosen due to several factors: 1) Market demands and competitor situations in different geographical markets varied dramatically, due to their presently unbalanced economies (Zhang et al., 2015); 2) The G20 group includes the most powerful countries which drive the most relevant decision-making processes and, hence, attain the most relevant goals and results in business; and 3) Despite the companies being considered as strategically independent units, the current economic situation (globalisation, crisis, proliferation of new technologies, etc.) together with new customer demands has led companies competing in the same market to implement new managerial actions to survive. Consequently, a major vision of this managerial framework needs to be focused on the diverse types of strategic entrepreneurial units. Regarding these strategic managerial units, their TMTs play a fundamental role in the decision-making process, and hence in the goal pursued and the results achieved (Hambrick & Mason, 1984). In accordance with the TMT notion that a ‘TMT is defined as the hierarchy and composition of the staff (Pegels et al., 2000) and includes all those executives at the highest level of management of an organisation (president, vicepresident, senior vice-president, vice-chairman and CEO)’, all of these TMT members have been considered in this paper even though other papers have focused on only CEOs or board composition (Crossland et al., 2014; Farrell & Hersch, 2005; Finkelstein, Hambrick & Cannella, 2009). Collecting demographical variables of TMT members is always a difficult task. Primary demographical data collection from true TMTs is unusual as access to demographic and managerial traits is always difficult (Clark and Maggitti, 2012). Basic information concerning the attributes of top managers was obtained from various sources. Although much research on TMTs uses secondary databases to collect demographical variables (Cohen & Bailey, 1997), this study collected the data by using both secondary information and primary information. The secondary sources were related to company websites, yearbooks, the specialist entrepreneurial journal ‘Nueva Empresa’ (New Firm) and other similar database sources (including Who’s Who in the World, and Who’s Who in Finance and Industry, available for various years and countries). In a first stage, the secondary sources allowed us to obtain initial information on TMT members and company variables, which were then updated and completed from primary information, generally from telephone and email interviews, between January 2013 and December 2015. Data on firm performance were also obtained from two relevant databases, SABI and CNMV, and the annual financial reports of the companies for the years 2013-2015. Data on top managers’ demographic and managerial variables were taken from the year 2013. 7 The sample size resulted in 179 multinational high-technology TMTs. The final size of the sample is justified by the requirement to attain all the demographic and managerial traits selected for all the TMT members, the economic and financial information of the companies, their location, environment, business knowledge and cultural criteria. The aforementioned difficulties encountered in the data collection limited the sample size, as did the restrictions imposed by certain multinational companies on giving information about the company. Observations with missing data at company or industry level were omitted from the data. However, the final sample size can be considered appropriate for an acceptable comprehension of the aim of the paper to be achieved (Jehn, Northcraft, & Neale, 2000; Wiersema & Bowen, 2005). In addition, the choice of the high-technology sector is justified by the following reasons: 1) It is the sector from which the greatest volume of highly representative information was collected; 2) Many researchers and entrepreneurs have recognised the great relevance of this sector, which is well-known as the fourth economic sector, and is responsible for changes at strategic level, and hence for the results achieved in the companies (Aydalot & Keeble, 2018; Thornhill, 2006; van Stel, Carree, & Thurik, 2005). The results derived from this study could therefore be considered both attractive and relevant in the academic and business world. 3.2. Measures The diversity of top managers’ demographic characteristics (educational background, education level and age) and managerial experience diversity (functional, industrial and international experience) were selected as explanatory variables for the analysis. Their measurement was attained following the criteria established in Upper Echelons. The variable on background education was classified into eight categories in accordance with the literature: sciences, engineering, maths, business, economics, law, arts and others (Carpenter & Fredrickson, 2001). The educational level was measured as a categorical variable that indicated the level of education (Wiersema & Bantel, 1992). The education classification has been widely used in the demographic literature (Díaz-Fernández et al., 2015 a, b; Díaz-Fernández et al., 2016; Helfat & Peteraf, 2015). Functional experience was categorised as a dummy variable, whereby the value one is taken if the TMT member has carried out numerous functions within the company, and zero otherwise. Industrial experience was categorised as a dummy variable based mainly on Wiersema and Bantel (1992), depending on whether or not the manager has performed various functions outside the company. International experience was also a dummy variable, whereby the value one is taken if a top manager shows knowledge and expertise in foreign markets and culture. The majority of research into Upper Echelons uses the term diversity to encompass variations of the commonly broad definition of diversity: the distribution of personal attributes among interdependent members of a work unit (Jackson, Joshi & Erhardt, 2003). Harrison and Klein (2007) stressed that diversity can be defined in three ways: diversity as ‘separation’, ‘variety’ and ‘disparity’. Diversity as separation is related to differences in opinion or position among team members. This demographic fault-line approach, rather than focusing on a disparity of single attributes, splits the team into homogenous subgroups of knowledge and expertise (Crawford & Lepine, 2013). Diversity as variety refers to differences between group members in attributes, mainly in knowledge or experience. Accordingly, diversity as variety is regarded as a synonym for heterogeneity across different demographic characteristics (Finkelstein & Hambrick, 1996). The two terms are therefore commonly used interchangeably. Diversity as disparity is related to the concentration of valued social assets or resources, such as pay and power, among unit members. Our paper uses the concept of diversity as variety as 8 does the majority of research in the field of Upper Echelons (Finkelstein et al., 2008; Li & Tan, 2013; Srivastava & Lee, 2008; Wei and Wu, 2013). To aggregate data at team level for the analysis of TMT composition diversity, the following criteria were applied. Simple ratios were calculated for categorical variables, such as functional, industrial and international experience diversity (dummy variables) as well as for education level and background education diversity. Blau’s Index (1977) was applied to measure the diversity for all these categorical variables. Blau’s index (1977) is a frequently used diversity measure for categorical variables (Bantel & Jackson, 1989; Keck, 1997; Pegels et al., 2000) with the following expression (=1-∑ (Pi)2), whereby Pi is the percentage of individuals in the i-th category of each of the categorical variables, which take values from 0 to 1, where high values indicate a greater diversity in a particular variable. Allison´s Coefficient of Variation (1978) (=σ/µ) was used for the age diversity. In the literature, firm performance has been measured by using a variety of ratios: the sales variation rate (Boeker & Goodstein, 1993; Salancik & Meindl, 1984), the average return on assets (ROA) and return on sales (ROS) (Certo et al., 2006; Denis & Denis, 1995). These indicators differ from those standard indicators identified in the literature, such as return on equity (ROE) (Venkatraman & Ramanujam, 1984). The lower volatility of ROA in relation to ROE provides a reason for the final decision to opt for ROA. The ROA provides an appropriate proxy of firm performance, as it measures the firm’s operative efficiency in all sectors, and was chosen following the majority of previous studies (Chaddad & Mondelli, 2013; Garcia-Fuentes et al., 2013; Lopez-Valeiras et al., 2016; Nehring, Gillespie, Sandretto, & Hallahan, 2009). The ROA was calculated as net income divided by total assets (Fiss, 2011; Gschwandtner, 2005; Lee, 2009) and was averaged over three years (2013-2015). The size of the TMT, measured as the number of TMT members, was also included, as was the firm size measured in terms of the number of employees. 3.3 Data analysis Longest and Vaisey (2008) highlighted that, in contrast to MRA, fsQCA is a settheoretical method that explains cases by identifying configurations of causal conditions, based on the assumption that several solutions can be equally effective in achieving the final effect (Fiss, 2007; Ragin, 2008). By using Boolean algebra, FsQCA performs a systematic cross-case analysis that models relationships between variables in terms of set membership. To this end, the application of QCA involves the following sequential stages: 1) definition of the property space; 2) calibration of causal conditions and outcome; and 3) construction and refinement of the truth table, consistency and logical deduction (Fiss, 2011; Ragin, 2008). The definition of the property space consists of specifying all causal conditions underlying an outcome, by identifying the attributes of cases exhibiting that outcome. The selection of causal conditions should be guided by the theory and the researchers’ knowledge on the topic of interest (Fiss, 2011). Our study employs the drivers identified by the demographic literature to achieve high firm performance. Accordingly, the property space consists of the presence or absence of the diversity of TMT attributes. Calibration constitutes a fundamental stage of fsQCA and refers to the transformation of construct measures, or variables, into fuzzy-set membership scores. In management studies, fuzzy-set calibration makes use of external information based on theoretical and extant empirical knowledge. This knowledge specifies three thresholds in fuzzy-set calibration: full membership (value 1.00), full non-membership (value 0.00) and the 15 ROA is used here as a proxy for firm performance as it is widely employed in the strategic management literature (Blažková, & Dvouletý, 2017; Garcia-Fuentes, Ferreira, & Kennedy, 2013; López-Valeiras, González-Sánchez, & Gómez-Conde, 2016). However, alternative dimensions of firm performance might have been considered, such as ROE, ROS, and sales growth (Díaz-Fernández, 2015 a,b). In future research avenues, the performance could be measured through a latent variable which would include its various dimensions. The scores of the construct obtained by using an SEM approach could therefore be used as the performance measures. Our study focuses on various configurations of the diversity of TMT attributes in addition to TMT size and firm size. However, we are aware that other internal and external environmental factors may take part in these configurations that lead to high firm performance. This limitation digresses from the main purpose of this paper and might be considered in future research. Additionally, it must be borne in mind that the application of calibration thresholds in fsQCA in social science is still in its infancy (Ragin, 2008). As a consequence, ROA calibration has focused on only management research, and therefore, verification of robustness of the outcomes across different thresholds has been necessary for the calibration of firm performance. Furthermore, although QCA has been primarily used for cross-sectional analyses, methods have recently been developed for their application in longitudinal studies (Schneider & Wagemann, 2012; Thygeson, Peikes, & Zutshi, 2013). To the best of our knowledge, no temporal QCA has yet been applied in longitudinal studies, and this constitutes an excellent opportunity to investigate the relationship of TMT composition diversity and high firm performance through the use of longitudinal data. 7. Conclusions The increasing complexity and uncertainty in the competitive environment in which companies operate make it necessary for companies to comprehend the internal mechanisms where the TMT members’ attributes are combined to bring about company success, in terms of performance and competitiveness. The main assumption of this study is that the diversity of TMT attributes should be conceived as interconnected elements, and consequently, given this complexity, multiple paths to high organisational outcome may exist. The new approach used in the present study of TMT composition diversity has combined the CT and that of Upper Echelons. The CT enables TMTs to be recognised as complex structures, where the diverse attributes of TMT members are combined in various ways to achieve optimum decision-making. As a complex structure, the demographic attributes of TMT members interact and adapt to certain mechanisms to reveal that even contrarian cases might lead to a successful company outcome. Tenets of CT have been applied in the TMT diversity literature by formulating two RQs based on the assumptions of the possible set of TMT composition diversity antecedents that lead to high firm performance. The findings achieved by conducting fsQCA support the assumption of complex causality and reveal six configurational paths that lead to high firm performance, which, in turn, describe TMT typologies. The results show that no single TMT composition diversity leads to high firm outcomes, but instead that various solutions in terms of TMT diversity antecedents are achieved. Furthermore, while paths 1 and 5 represent homogeneous TMTs with low variability in the diversity of the TMT attributes, configurations 2 and 6 highlight TMTs of a more diverse nature in terms of demographic characteristics leading to high performance (heterogeneous TMTs). The remaining configurations describe those TMTs with different combinations of attributes 16 as being either those present or those absent (Mixed TMTs). The antecedent conditions obtained for TMT diversity appear to be more reliable and valuable for organisations regarding the best composition of TMT members. The findings of this paper point out that CT and fsQCA are useful tools for the comprehension of how different combinations of attributes relate to high firm performance. Summarising, to advance in the understanding of TMT diversity composition, a study of the interdependencies is required between the diversity of TMT demographic characteristics and of how these combinations may affect strategy adoption and, hence, high firm performance. The use of fsQCA and configurational logic captures the complexities underlying TMT internal composition to adopt strategies, and identifies the ways in which TMT characteristics should be aligned to design the best TMT internal composition. These findings also help to explain why, to date, knowledge regarding the role of TMT internal composition has been not only inconsistent and unreliable but also insufficient and inconclusive. Acknowledgements This paper has been funded by the V Research Programme’s Grant of the University of Seville (Reference: PP2013-1331). References Abatecola, G., & Cristofaro, M. (2018). Hambrick and Mason’s “Upper Echelons Theory”: Evolution and open avenues. Journal of Management History. https://doi.org/10.1108/ JMH-02-2018-0016. Akewushola, R. O., Elegunde, A. F., & Saka, R. O. (2018). Effects of Top Management Team Diversity on Organizational Performance in the Banking Industry. Global Journal of Applied, Management and Social Sciences,15, 214 – 226 Auden, W.C, Shackman, J.D, & Onken, M. H. (2006). Top management team, international risk management factor and firm performance. Team Performance Measurement, 12(7/8), 209-224. Aydalot, P, & Keeble, D. (2018). High technology industry and innovative environments: the European experience. Routledge. Bach, S., & Lee, J. J. (2018). Is the Upper Echelons Perspective Relevant Outside the US? An Empirical Study of Executives’ Impact on Firm Performance in the Global Context. Journal of Behavioral and Applied Management, 18(1), 3752. Balandier, G. (1989). El desorden. La teoría del caos y las ciencias sociales. Elogio de la fecundidad del movimiento. Barcelona: Gedisa, 115. Bantel, K. A, & Jackson, S.E. (1989). Top management and innovation in banking: Does the composition of the top team make a difference?. Strategic Management Journal, 10, 107-124. Barsade, S.G.,Ward, A.J., Turner, J.D.F., & Sonnenfeld, J.A. (2000). To your heart´s content: a model of affective diversity in top management teams. Administrative Science Quarterly, 45, 802-836. Berg-Schlosser, D., De Meur, G., Rihoux, B., & Ragin, C. C. (2009). Qualitative comparative analysis (QCA) as an approach. Configurational comparative methods: 17 qualitative comparative analysis (QCA) and related techniques, Sage Publications Inc. Blau, P. (1977). Inequality and Heterogeneity: A Primitive Theory of Social Structure. Free Press: New York. Blažková, I., & Dvouletý, O. (2017). Drivers of ROE and ROA in the Czech Food Processing Industry in the Context of Market Concentration. AGRIS on-line Papers in Economics and Informatics, 9(3), 3-14. Boeker, W. B., & Goodstein, J. (1993). Performance and successor choice: the moderating effects of governance and ownership. Academy of Management Journal, 36(1), 172-186. Boone, C., Lokshin, B., Guenter, H., & Belderbos, R. (2019). Top management team nationality diversity, corporate entrepreneurship, and innovation in multinational firms. Strategic Management Journal, 40(2), 277-302. Bromiley, P., & Rau, D. (2016). Social, Behavioural, and Cognitive Influences on Upper Echelons During Strategy Process: A Literature Review. Journal of Management, 42(1), 174-202. Buchanan, D. A., & Bryman, A. (2007). Contextualizing methods choice in organizational research. Organizational Research Methods, 10(3), 483-501. Buyl, T., Boone, C., & Hendriks, W. (2014). Top Management Team Members’ Decision Influence and Cooperative Behaviour: An Empirical Study in the Information Technology Industry. British Journal of Management, 25, 285–304. Buyl, T., Boone, C., Hendriks, W., & Matthyssens, P. (2011). Top management team functional diversity and firm performance: The moderating role of CEO characteristics. Journal of Management Studies, 48(1), 151-177. Byrne, D. (2005). Complexity, configurations and cases. Theory, Culture & Society, 22(5), 95-111. Cannella, A.A. Jr., Park, J., & Lee, H. (2008). Top management team functional background diversity and firm performance: examining the roles of team member collocation and environmental uncertainty. Academy of Management Journal, 51(4), 768–784. Cannella, A. A., Jr., & Holcomb, T. R. (2005). A multilevel analysis of the upperechelons model. In A. Dansereau, & F. J. Yammarino (Eds.), Research in Multi-Level Issues (pp. 197-237). Oxford, UK: Elsevier Ltd. Carmeli, A. (2008). Top management team behavioural integration and the performance of service organizations, Group & Organization Management, 33(6), 712-735. Carpenter, M. A. (2002). The implications of strategy and social context for the relationship between top management team heterogeneity and firm performance. Strategic Management Journal, 23, 275-284. Carpenter, M. A., & Fredrickson, J. W. (2001). Top management teams, global strategic posture, and the moderating role of uncertainty. Academy of Management Journal, 44(3), 533-545. Carpenter, M.A., Geletkanycz, M., & Sanders, W.G. (2004). The upper echelons revisited: the antecedents, elements, and consequences of TMT composition. Journal of Management, 30, 749–778. 18 Cassell, C., & Johnson, P. (2006). Action research: Explaining the diversity. Human relations, 59(6), 783-814. Certo, S.T., Lester, R.H., Dalton C.M., & Dalton D.R.. (2006). Top management teams, strategy and financial performance: a meta-analytic examination. Journal of Management Studies, 43 (4), 813–839. Chaddad, F. R., & Mondelli, M. P. (2013). Sources of firm performance differences in the US food economy. Journal of Agricultural Economics, 64(2), 382-404 Chen, W. H., Kang, M. P., & Butler, B. (2019). How does top management team composition matter for continual growth? Reinvestigating Penrose’s growth theory through the lens of upper echelons theory. Management Decision, 57(1), 41-70. Chi, N.W., Huang, Y. M., & Lin, S.C. (2009). A Double-Edged Sword? Exploring the Curvilinear Relationship Between Organizational Tenure Diversity and Team Innovation: The Moderating Role of Team-Oriented HR Practices. Group & Organization Management, 34, 698-726. Chung, M., & Woodside, A.G. (2011). Causal recipes sufficient for identifying market gurus versus mavens. Fuzzy methods for customer relationship management and marketing: Applications and classification, Andreas Meier and Laurent Donzé (Eds.), IGI Global, Hershey, PA, USA, 312-331. Clark, K. D., & Maggitti, P. G. (2012). TMT Potency and Strategic Decision-Making in High Technology Firms. Journal of Management Studies, 49(7), 1168-1193. Clegg, S. R., Hardy, C., & Nord, W. R. (2003). Handbook of organization studies. SAGE Publications Ltd. Cohen, S., & Bailey, E. (1997). What makes groups work: Group effectiveness research from the shop floor to the executive suite. Journal of Management, 23, 239-290. Crawford, E., & LePine, J. (2013). A configural theory of team processes. Accounting for the structure of task-work and team-work. Academy of Management Review, 38, 32–48. Crilly, D., Zollo, M., & Hansen, M. T. (2012). Faking it or muddling through? Understanding decoupling in response to stakeholder pressures. Academy of Management Journal, 55(6), 1429-1448. Crossland, C., & Hambrick, D.C. (2011). Differences in managerial discretion across countries: how nation-level institutions affect degree to which CEOs matter. Strategic Management Journal, 32 (8), 797–819. Crossland, C., Zyung, J., Hiller, N.J., & Hambrick, D. (2014). CEO career variety: effects on firm-level strategic and social novelty. Academy of Management Journal, 57(3), 652-674. Cyert, R., & March, J. (1963). A behavioral theory of the firm. EC: Prentice-Hall. Dainty, A. (2008). Methodological pluralism in construction management research. Advanced Research Methods in the Built Environment, 1, 1-13. Denis, D.J., & Denis, D.K. (1995). Performance Changes Following Top Management Dismissals. The Journal of Finance, 1(4), 1029-1057. Dhaouadi, K. (2018). Corporate Board and Upper Echelons: The Case of the American Most Admired Firms. International Journal of Business and Management, 13(4), 245. 19 Di Benedetto, C. A. (1999). Identifying the key success factors in new product launch. Journal of Product Innovation Management, 16 (6), 530–545. Díaz-Fernández, M. C., González-Rodríguez, M. R., & Pawlak, M. (2014). Top Management Demographic Characteristics and Company Performance. Industrial Management & Data Systems, 114 (3), 365-368. Díaz-Fernández, M. C., González-Rodríguez, M. R., & Simonetti, B. (2015ª). Top management team’s intellectual capital and firm performance. European Management Journal, 33(5), 322-331. Díaz-Fernández, M. C., González-Rodríguez, M. R, & Simonetti, B. (2015b). Top management teams´ demographic characteristics and their influence on strategic change. Quality & Quantity, 49 (3), 1305-1322. Díaz-Fernández, M. C., González-Rodríguez, M. R., & Paddison, B. (2015c). Exploring the antecedents of firm performance in a Latino-American and European diversity industrial context. Academia Revista Latinoamericana de Administración (ARLA), 28 (4), 502-522. Díaz-Fernández, M. C., González-Rodríguez, M. R., & Simonetti, B. (2016). The role played by job and non-job-related TMT diversity traits on firm performance and strategic change. Management Decision, 54 (5), 1110 – 1139. Dick, P. & Cassell, C. (2002). Barriers to managing diversity in a UK constabulary: the role of discourse. Journal of Management Studies, 39, 953- 976. Drucker, P. (1974). Management: tasks, responsibilities, practices. Harper and Row, New York. Erhardt, N. L., Werbel, J. D., & Shrader, C. B. (2003). Board of director diversity and firm financial performance. Corporate Governance: An International Review, 11(2), 102-111. Farrell, K.A., & Hersch, P. L. (2005). Additions to corporate boards: the effect of gender. Journal of Corporate Finance, 11, 85-106. Ferrier, W. J. (2001). Navigating the competitive landscape: The drivers and consequences of competitive aggressiveness. Academy of Management Journal, 44(4), 858-877. Finkelstein, S., & Hambrick, D. C. (1990). Top management team tenure and organizational outcomes: the moderating role of managerial discretion. Administrative Science Quarterly, 35, 484-504 Finkelstein, S., & Hambrick, D. C. (1996). Strategic leadership: top executives and their effects on organizations. St. Paul: West. Finkelstein, S., Harvey, C. and Lawton, T. (2008). Vision by design: a reflexive approach to enterprise regeneration. Journal of Business Strategy, 29(2), 4-13. Finkelstein, S., Hambrick, D., & Cannella, A. (2009). Strategic leadership: Theory and research on executives, top management teams and boards. NY: Oxford University Press. Fiss, P.C. (2007). A set-theoretic approach to organizational configurations. The Academy of Management Review, 32 (2), 1180-1198. 20 Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organizational research. Academy of Management Journal, 54 (2), 393–420. Garcia-Fuentes, P. A., Ferreira, G. F., & Kennedy, P. L. (2013). Economic performance of US multinational agribusinesses: foreign direct investment and firm strategy. Agribusiness, 29(2), 242-255. Greckhamer, T., Misangyi, V.F., Elms, H.,& Lacey, R. (2008). Using QCA in Strategic Management Research: An Examination of Combinations of Industry, Corporate, and Business Unit Effects. Organizational Research Methods, 11 (4), 695–726 Georgakakis, D., Greve, P., & Ruigrok, W. (2017). Top management team faultlines and firm performance: Examining the CEO-TMT interface. The Leadership Quarterly, 28, 741–758 Greckhamer, T., Misangyi, V.F., Elms, H.,& Lacey, R. (2008). Using QCA in Strategic Management Research: An Examination of Combinations of Industry, Corporate, and Business Unit Effects. Organizational Research Methods, 11 (4), 695–726 Gschwandtner, A. (2005). Profit persistence in the ‘very’long run: evidence from survivors and exiters. Applied Economics, 37(7), 793-806. Haleblian, J., & Finkesltein, S. (1993). Top management team size, CEO dominance, and firm performance: the moderating roles of environmental turbulence and discretion. Academy of Management Journal, 36, 844-863. Hambrick, D. C., & Mason, P. A. (1984). Upper Echelons: The organization as a reflection of its top managers. Academy of Management Review, 9 (2), 193-206. Hambrick, D. C. (2007). Upper echelons theory: an update. Academy of Management Review 32(2), 334–343. Harrison, D., Price, K., Gavin, J., & Florey, A. (2002). Time, teams and task performance: changing effects of diversity on group functioning. Academy of Management Journal, 45, 1029-1045. Harrison, D. A., & Klein, K. J. (2007). What's the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review, 32(4), 1199-1228. Hope, L.,Eisenhardt K. M, & Xin, K. R. (1999). Exploring the black box: an analysis of work group diversity, conflict, and performance. Administrative Science Quarterly, 44 (1), 1-29. Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity on team outcomes: a meta-analytic review of team demography. Journal of Management, 33 (6), 987- 1015. Humphrey, S. E., Morgerson, F. P., & Mannor, M. J. (2009). Developing a theory of the strategic core of teams: a role composition model of team performance. Journal of Applied Psychology, 94(1), 48-61. Hutzschenreuter, T., & Horstkotte, J. (2013). Performance effects of international expansion processes: The moderating role of top management team experiences. International Business Review, 22, 259-277. Jackson, S.E. & Joshi, A. (2004). Diversity in social context: a multi-attribute, multilevelanalysis of team diversity and sales performance. Journal of Organizational Behavior, 25 (6), 675-702. 21 Jackson, S.E., Joshi, A. & Erhardt, N.L. (2003). Recent research on team and organizationaldiversity: SWOT analysis and implications. Journal of Management, 29(6), 801-830. Jehn, K., Northcraft, G. B., & Neale, M. A. (2000). Why differences make a difference: A field study of diversity, conflict and performance in workgroups. Administrative Science Quarterly, 44, 741-763. Keck, S.L. (1997). Top Management team structure: differential effects by environmental context. Organization Science, 8, 143-56. Lawrence, B. S. (1997). The black box of organizational demography. Organization Science, 8(1), 1-22. Lampaki, A., & Papadakis, V. (2019). The impact of organisational politics and trust in the top management team on strategic decision implementation success: A middlemanager's perspective. European Management Journal, 36(5), 627-637. Lee, J. (2009). Does size matter in firm performance? Evidence from US public firms. International Journal of the Economics of Business, 16(2), 189-203. Li, Y., & Tan, C. H. (2013). Matching business strategy and CEO characteristics: The impact on organizational performance. Journal of Business Research, 66, 248-259. Lin, W. T., & Cheng, K. Y. 2013a. The effect of upper echelons’ compensation on firm Internationalization”, Asia Pacific Journal Management, 30: 73–90. Lin, W. T., & Cheng, K. Y. (2013b). Upper echelon compensation, performance, and the rhythm of firm internationalization. Management Decision, 51(7), 1380-1401. Lin, C. Y., & Kuo, T. H. (2007). The mediate effect of learning and knowledge on organizational performance. Industrial Management & Data Systems, 107(7), 1066- 1083. Longest, K., Vaisey, S. (2008). Fuzzy: A Program for Performing Qualitative Comparative Analyses (QCA) in STATA. The STATA Journal, 8 (1), 79–104. Lopez-Valeiras, E., Gonzalez-Sanchez, M. B., & Gomez-Conde, J. (2016). The effects of the interactive use of management control systems on process and organizational innovation. Review of Managerial Science, 10(3), 487-510. Meier, A., & Donzé, L. (Eds.) (2012). Fuzzy methods for customer relationship management and marketing: Applications and classification, IGI Global, Hershey, PA, USA. Misangyi, V. F., Greckhamer, T., Furnari, S., Fiss, P. C., Crilly, D., & Aguilera, R. (2017). Embracing causal complexity: The emergence of a neo-configurational perspective. Journal of Management, 43(1), 255-282. Mohr, A., & Batsakis, G. (2018). Firm resources, cultural distance and simultaneous international expansion in the retail sector. International Business Review, 27(1), 113- 124 Murray, A. (1989). Top management group heterogeneity and firm performance, Strategic of Management Journal, 10, 125-141. Nehring, R., Gillespie, J., Sandretto, C., & Hallahan, C. (2009). Small US dairy farms: can they compete? Agricultural Economics, 40 (s1), 817-825. 22 Newbold, P., Carlson, W., & Thorne, B. M. (2012). Statistics for business and economics, Pearson. Nielsen, S. (2010). Top Management Team Internationalization and Firm Performance: The Mediating Role of Foreign Market Entry. Management International Review, 50(2), 185-206. Nielsen, B. B. & Nielsen, S. (2013). Top Management Team Nationality Diversity and Firm Performance: A Multilevel Study. Strategic Management Journal, 34 (3), 373- 382. Nüesch, S. (2009). Are demographic diversity effects spurious? Economic Analysis and Policy, 39(3), 379-388. O’Reilly, C. A., Snyder, R. C., Boothe, J. N. (1993). Executive team demography and organizational change. In Huber, G.P., Glick, W.H. (2003), Organizational change and redesign: Ideas and insights for improving performance, New York: Oxford University Press. Oduor, B. A., & Kilika, J. M. (2018). TMT Diversity, Decision Quality and Service Sector Firm Performance: A Research Agenda. Journal of Management and Strategy, 9(2), 34-45. Ordanini, A., Maglio, P. P. (2009). Market Orientation, Internal Process, and External Network: A Qualitative Comparative Analysis of Decisional Alternatives in New Service Development. Decision Science, 40 (3), 601–625. Ordanini, A., Parasuraman, A. & Rubera, G. (2014). When the recipe is more important than the ingredients: A qualitative comparative analysis (QCA) of service innovation configurations. Journal of Service Research, 17, 134–149. Pegels, C. C., Song, Y. I. & Yang, B. (2000). Management heterogeneity, competitive interaction groups, and firm performance. Strategic Management Journal, 21(9), 911- 24. Pelled, L. H.; Eisenhardt, K. M. & Xin, K. R. (1999). Exploring the black box: an analysis of work group diversity, conflict and performance. Administrative Science Quarterly, 44, 1-28. Ragin, C. (2000). Fuzzy Set Social Science. Chicago: Chicago University Press. Ragin, C. (2006). Turning the tables: How case-orientated research challenges variableorientated research. Comparative Social Research, 16, 27-42. Ragin, C. (2008). Redesigning social inquiry: Fuzzy sets and beyond. Chicago: Chicago University Press. Roh, H., Chun, K., Ryou, Y., & Son, J. (2019). Opening the Black Box: A Meta-Analytic Examination of the Effects of Top Management Team Diversity on Emergent Team Processes and Multilevel Contextual Influence. Group & Organization Management, 44 (1), 112-164. Salancik, G., & Meindl, J. (1984). Corporate attributions as strategic illusions of management control. Administrative Science Quarterly, 30, 46-60. Schmid, S., & Dauth, T. (2014). Does internationalization make a difference? Stock market reaction to announcements of international top executive appointments. Journal of World Business, 49(1), 63-77. 23 Schneider, C. Q. & Wagemann, C. (2012). Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis. New York: Cambridge University Press Schuhmacher, M.C., von Janda, S., & Woodside, A.G. (2013). Configural theory of why people shop for clothes: Personal-attribute explanations of four stalwart segments. Journal of Global Fashion Marketing, 4, 1-25. Simon, H. A. (1965). The architecture of complexity. General systems, 10, 63-76. Simons, T., Pelled, L. P., & Smith, K. A. (1999). Making use of difference: diversity, debate, and decision comprehensiveness in top management teams. Academy of Management Journal, 42(6), 662-73. Smith, K. G., Smith, K. A., Sims, H. P. Jr, O’Bannon, D. P., Scully, J. A., & Olian, J. D. (1994). Top management team demography and process: the role of social integration and communication. Administrative Science Quarterly, 39(3), 412-38 Srivastava, A., & Lee, H. (2008). Firm performance and top management team age, tenure, and education: a research synthesis. International Journal of Business Research, 8(2), 1-8. Thornhill, S. (2006). Knowledge, innovation and firm performance in high-and lowtechnology regimes. Journal of Business Venturing, 21(5), 687-703. Thygeson, N. M., Peikes, D., & Zutshi, A. (2013). Mixed methods: Fuzzy set qualitative comparative analysis and configurational comparative methods: Powerful tools to study and refine patient-centered medical home models. Rockville, MD: Agency for Healthcare Research and Quality Tihanyi, L., Ellstrand, A., Daily, C., & Dalton, D. (2000). Composition of the top management team and firm international diversification. Journal of Management, 26 (6), 1157-1177. Urry, J. (2005). The complexities of the global. Theory Culture & Society, 22 (5), 235- 254. Vachon, S., & Klassen, R. D. (2008). Environmental management and manufacturing performance: The role of collaboration in the supply chain. International Journal of Production Economics, 111(2), 299-315. Van Dijk, H., van Engen, M. L., & van Knippenberg, D. (2012). Defying conventional wisdom: A meta-analytical examination of the differences between demographic and job-related diversity relationships with performance. Organizational Behavior and Human Decision Processes, 119, 38–53. Van Stel, A., Carree, M., & Thurik, R. (2005). The effect of entrepreneurial activity on national economic growth. Small Business Economics, 24(3), 311-321. Venkatraman, N., & Ramanunjam, V. (1986). Measurement of business performance in strategy research: a comparison of approaches. Academy of Management Review, 11(4), 801-804 Wei, L. Q., & Wu, L. (2013). What a diverse top management team means: Testing an integrated model. Journal of Management Studies, 50(3), 389-412. Whetten, D. A. (1989). What constitutes a theoretical contribution? Academy of Management Rreview, 14(4), 490-495. 24 Wally, S., & Becerra, M. (2001). Top management team characteristics and strategic changes in international diversification- The case of US multinationals in the European community. Group & Organization Management, 26(2), 165-188. Wiersema, M. F., & Bantel, K. A. (1992). Top management team demography and corporate strategic change. Academy of Management Journal, 35 (1), 91-121. Wiersema, M. & Bird, A. (1996). Universalizing Upper Echelon Theory: contrasting US theory with Japanese firm performance. Journal of Asian Business, 12 (12), 1-30. Wiersema, M., & Bowen, H. (2005). Foreign-Based Competition and Corporate Diversification Strategy. Strategic Management Journal, 26, 1153-1171. Wiersema, M. F., & Bowen, H. P. 2009. The use of limited dependent variable techniques in strategy research: Issues and methods. Strategic Management Journal, 30(6), 679- 692. Williams, K.Y. & O’Reilly, C.A. (1998). Demography and diversity in organizations: a review of 40 years of research, in Staw, B.M. and Cummings, L.L, (Eds), Research in Organizational Behaviour, JAI Press, Greenwich, pp. 77-140. Woodside, A. G. (2011). Responding to severe limitations of cross-sectional surveys: Commenting on Rong and Wilkinson’s perspectives. Australian Marketing Journal, 19, 153-156. Woodside, A. G. & Zhang, M. (2012). Identifying X-consumers using causal recipes: ‘whales’ and ‘jumbo shrimps’ casino gamblers. Journal of Gambling Studies, 28, 13– 26. Woodside, A. G. (2013a). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66, 463-472. Woodside, A. G. (2013b). Proposing a new logic for data analysis in marketing and consumer behavior: case study research of large-N survey data for estimating algorithms that accurately profile X (extremely high-use) consumers. Journal of Global Scholars of Marketing Science, 22 (4), 277–289. Woodside, A. G. (2014). Embrace perform model: Complexity theory, contrarian case analysis, and multiple realities. Journal of Business Research, 67, 2495-2503. Woodside, A. G. (2015). The general theory of behavioral pricing: Applying complexity theory to explicate heterogeneity and achieve high-predictive validity. Industrial Marketing Management, 47, 39-52. Wren, D.A. & Bedeian, A.G. (2017). The Evolution of Management Thought, 7th ed.,Wiley, US. Wu, P-L., Yeh, S-S., Huan, T-C., & Woodside, A. G. (2014). Applying complexity theory to deepen service dominant logic: Configural analysis of customer experience-and- outcome assessments of professional services for personal transformations. Journal of Business Research, 67, 1647–1670. Yamak, S., Nielsen, S., & Escribá-Esteve, A. (2014). The role of external environment in upper echelons theory: A review of existing literature and future research directions. Group & Organization Management, 39(1), 69-109.