Top management team’s intellectual capital and firm performance

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European Management Journal j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / e m j

Top management team’s intellectual capital and firm performance M. Carmen Díaz-Fernández a, M. Rosario González-Rodríguez a,*, Biagio Simonetti b a b

University of Seville, Spain University of Sannio, Benevento, Italy

A R T I C L E

I N F O

Article history: Received 28 November 2014 Accepted 18 March 2015 Available online Associate editor: Sabina Siebert Keywords: TMT Upper Echelon Theory Intellectual capital Corporate strategy Moderator effects

A B S T R A C T

Intellectual capital (IC), which is frequently associated with firm performance, is an organisational intangible asset, and is commonly categorised into three core components: human, structural, and relational capital (Abdullah & Sofian). By integrating the Upper Echelon Theory and the Resource-Based View of the firm, this paper aims to study not only the net effect of TMT diversity in human capital on performance but also the moderator effect of corporate strategy (Product and International diversification) on performance. The research focuses on a longitudinal study for a sample of multinational enterprises from diverse industries (trading, service, finance, and technology) whose headquarters are in Spain. The study contributes towards the comprehension of the complexity embodied in the Check relation strategy firm decision, TMT’s IC and firm performance. This paper answers the call to explore new causal relations that influence firm performance that can therefore help managers to adopt the best decision-making strategies, and to shed light on the inconsistent and inconclusive results derived from the literature. © 2015 Elsevier Ltd. All rights reserved.

Introduction Intellectual Capital (IC) is considered an appropriate source of sustainable competitive advantage as well as the way through which technological development and economic growth are run (Hayton, 2005; Rehman, Rehman, Rehman, & Zahid, 2011). Hence, IC is currently identified as an essential intangible asset in business, especially in those sectors of industry characterised by their highly intensive knowledge capital and advanced technology. Moreover, IC can be used to enhance an organisation’s success (Brooking, 1997), and to encourage organisational benefits, such as innovativeness, creativity, competitive edge and value creation (Bontis, Chua, & Richardson, 2000; Hong, Plowman, & Hancock, 2007; Marr, 2008; Perk, 2005). Indeed, as noted by Brooking (1997), IC at an appropriate level could potentially improve corporate performance. In support of IC firm advantages, Hayton (2005) showed that, by controlling IC, it is possible to change the perceived risks and rewards associated with managerial actions in order to provide firms with better possibilities to penetrate new markets, create better products, and to earn first movement advantages, particularly in high-technology stock. A considerable part of organisational knowledge is embodied in the organisational IC (Edvinsson & Malone, 1997) that plays a relevant role in the Top Management Team’s decision-making. Along the same lines, Sullivan (1999) highlights the “brain power” yield in the TMT’s IC. Previously, Drucker (1974) defended the vital role

* Corresponding author. Faculty of Tourism and Finance. Avda San Franscisco Javier s/n Sevilla, 41018 (Spain). Tel.: +34954557488; fax: +34954551612. E-mail address: [email protected] (M.R. González-Rodríguez).

played by managers in firms, and Hambrick and Mason (1984) argued that organisations are a reflection of their top managers, and highlighted the great power of the dominant coalition in the formulation and adoption of the best organisational strategy in order to accomplish a high level of corporate performance. In accordance with the above authors, Raja Adzrin, Abu Thahir, and Maisarah (2009) suggested that enterprises could gain and retain a competitive advantage when they have great human talents, major capabilities, and boundless innovation and creativity. Indeed, the argument based on the influences that IC has on entrepreneurial performance is consistent with the Resource-Based View theory, which advocates that an organisation should identify and manage their resources (tangible and intangible) effectively to attain higher performance (Kristandl & Bontis, 2007; Lewicka, 2011). In accordance with previous arguments, the present paper considers that the IC of a firm’s TMT should be properly managed and applied in order to instil innovativeness, thereby promoting value creation and enhancing competitive advantages. These criteria are critical for companies to improve performance, sustain profitability, and keep pace with the competition, particularly in unpredictable economies (Abdullah & Sofian, 2012). Organisation competitiveness requires the skills, knowledge and capabilities of top managers. However, measurement of the influence of the TMT’s IC on firm performance is not an easy task since many studies in the Upper Echelon Literature have achieved inconsistent and inconclusive results. Those contradictory results can be explained by the fact that the majority of studies to date have taken into consideration only the main effects of TMT attributes on firm performance, and have avoided the organisational internal complexity and the environmental external complexity. This paper

http://dx.doi.org/10.1016/j.emj.2015.03.004 0263-2373/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article in press as: M. Carmen Díaz-Fernández, M. Rosario González-Rodríguez, Biagio Simonetti, Top management team’s intellectual capital and firm performance, European Management Journal (2015), doi: 10.1016/j.emj.2015.03.004

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strives to ascertain not only the marginal effect of TMT diversity on performance but also the moderator effect of TMT diversity on the relationship between corporate strategy and performance. To this end, TMT demographical traits are used as proxies of the human capital dimension of IC, while Product and International diversification are used as proxies of corporate strategy. TMT diversity is associated to the skills and capabilities of decision makers (Carpenter, 2002). However, diversity in a TMT appears as a countervailing force. On the one hand, greater diversity might lead to more internal conflict, which implies less effective decisionmaking and lower firm outcomes. On the other hand, diversity enables top managers to identify the environmental opportunities and threats in order to formulate the most accurate strategies thereby boosting firm performance (Allen, Dawson, Wheatly, & White, 2008). The research questions of this paper are: Does the intellectual capital diversity of a TMT influence firm performance?; Does corporate strategy (product and international diversification) always lead to a greater outcome for the firm?; In the presence of high complexity in the strategy of decision-making for product diversification, does the intellectual capital diversity of a TMT improve the influence of the strategy on performance?; and, In the presence of high complexity in the strategy of decision-making for international diversification, does the intellectual capital diversity of a TMT influence the binominal relationship between strategy and performance? The paper advances the literature by integrating the Upper Echelon Theory with the Resource-Based View of a firm and presents the following innovative aspects: (1) the paper is the first study to analyse the moderator effect of TMT diversity as a proxy of IC when firms follow complex strategies towards product and international diversification. (2) It is one of the first studies to use a Spanish industrial context: this scarcity of papers based in the Spanish context is probably due to the legal restrictions imposed by the Spanish Law LORTAD which leads to difficulties in gathering information on all members of the Top Management Teams. (3) A longitudinal study has been applied in order to capture the influence of TMT diversity on performance over time, as required from the recent literature trends. The paper is structured as follows. The first section includes a review of prior research on the main topics: TMT diversity, international and product diversification, firm performance, conceptual links between these issues; and the research model supported by the literature review. The second section presents the research design and methodology on which the study relies. The third section discusses the results accomplished. Finally, in the fourth section, a general conclusion is drawn, certain limitations are recognised and managerial implications and future research avenues are proposed. Theory and hypotheses TMT diversity and intellectual capital The literature contains numerous definitions of IC (see Brooking, 1997; Edvinsson & Malone, 1997; Roos, Roos, Edvinsson, & Dragonetti, 1998; Stewart, 1997; Youndt, 1998) due to the categorisation of the assets that comprise this issue (human capital, intellectual property, relationships with external stakeholders, organisational structure, information systems, etc.) (Hayton, 2005). Furthermore, IC has traditionally been categorised into three components: human, structural, and relational capital (Marr, 2008; Roos, Pike, & Fernström, 2005; Sullivan, 1999; Tayles, Pike, & Sofian, 2007; Wall, Kirk, & Martin, 2004). These categories include: Human capital, which includes knowledge, professional skills and experience, expertise, educational level, and creativity of employees; Structural capital, which includes innovation capital, databases, software systems, distribution networks, organisational charts,

corporate culture, strategies, and policies; and Relational capital, which includes marketing channels, customer relationships, relationships with suppliers, customer loyalty, governmental and industrial networking, intermediaries, and partners (Abdullah & Sofian, 2012; Bransing, Leenders, & Wijnberg, 2012). The IC notion applied in this research is based on that of Roos et al. (1998): “all non-monetary and non-physical resources that are fully or partly controlled by the organisation and that contribute to the organisation’s value creation”, which supports the results attained in traditional IC taxonomy. This paper is focused on the first dimension of the three components of IC: human capital. Further to establishing conceptual clarity between the notion of IC and its dimensions, it is necessary that the distinction of IC components as stocks of knowledge and dynamic capabilities are recognised by organisations in order to create value, and to exploit this resource (Hayton, 2005). These arguments are consistent with approaches in the literature such as the hierarchical view of resources and capabilities (Nelson & Winter, 1982), the notion of potential versus realised capabilities (Zahra & George, 2002), the theoretical model of intangible resources (Hall, 1992, 1993) and Upper Echelon Theory (Hambrick & Mason, 1984). As mentioned above, this paper focuses on Human capital, which refers to knowledge, skills, and abilities of employees. Human capital as the first dimension of IC is expected to be positively associated with entrepreneurial behaviour, which has a significant influence upon this organisational behaviour and is considered to be the most organisational resource of a firm (Hayton, 2005). Due to the above arguments, the research model is supported by the Upper Echelon Theory created by Hambrick and Mason (1984). These researchers state that TMT cognitive resources and values exert significant influence on their strategic decision-making through observable TMT characteristics, such as their age, education, and managerial experience. In addition, many researchers have suggested that these TMT characteristics are associated with firm success (Chandler & Hanks, 1994; Cooper, Gimeno-Gascon, & Woo, 1994; Honig, 1998; MacMillan, Zemann, & Subbanarasimha, 1987; Stuart & Abetti, 1990) due to the influence of human capital upon decision-making processes. Greater cognitive resources not only aid problem identification, formulation, and problem solving in the best way (Bantel & Jackson, 1989) but also increase the range of alternative problem solutions, the combination of information, and hence, TMT creativity. In this way, it is possible to find in the literature empirical support for the relationship between TMT demographical traits, such as education, intelligence, cognitive style, and creativity (Amabile, 1983; Oldham & Cummings, 1996; Woodman & Schoenfeldt, 1989), and innovation, corporate strategy, and firm performance (Bantel & Jackson, 1989; Kimberly & Evanisko, 1981; Rogers & Schoemaker, 1971; Wiersema & Bantel, 1992). In short, the influence of TMT demographical characteristics upon the organisational behaviour and therefore upon firm performance will be significant, as noted by Cyert and March (1963), mainly due to their position as key decisionmakers and members of the ‘dominant coalition’, the essential organisational brain. In addition to considering the additive effects of the individual human capital of TMTs, scholars in the strategy and demographic literature have highlighted the significant contribution and role played by the aggregate human capital characteristics of TMTs. A relevant aggregate demographical characteristic of TMTs, namely, TMT diversity, is expected to be significant in obtaining vital managerial implications and goals both for the firm and for society (Guzzo & Shea, 1992). In accordance with the TMT composition diversity has traditionally been considered as an antecedent or moderator of vital entrepreneurial variables, such as strategic decision-making in relation to firm performance (Bantel & Jackson, 1989; Simons, Pelled, & Smith, 1999; Smith et al., 1994; Wiersema & Bantel, 1992). According to Weick (1995), TMT human capital is likely to have a positive

Please cite this article in press as: M. Carmen Díaz-Fernández, M. Rosario González-Rodríguez, Biagio Simonetti, Top management team’s intellectual capital and firm performance, European Management Journal (2015), doi: 10.1016/j.emj.2015.03.004

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association with innovation, strategic decision-making processes and performance since these aggregate demographical diversity traits lead to the best knowledge and organisational learning processes. Hence, TMT human capital can be considered as a broad source of knowledge to adopt the best strategic decision-making in order to determine the best way to bridge the identified gaps in performance. The discussion above suggests that TMT demographic characteristics and managerial experience diversity will enhance the innovation, flexibility and creativity in TMT strategic decision-making processes by triggering learning and facilitating knowledge acquisition and transformation, thereby improving firm performance (Hayton, 2005). Thus, the following hypotheses are tested: Hypothesis 1. TMT human capital diversity will be positively related to firm performance in terms of demographical attributes (age, education) (H1a) and in terms of managerial experience diversity (functional, industry and international diversity) (H1b). Corporate strategy (product and international diversification) and TMT diversity International diversification offers several competitive advantages to firms (Greve, Nielsen, & Ruigrok, 2009; Rehman et al., 2011; Tihanyi, Ellstrand, Daily, & Dalton, 2000). Buhner (1987) argues that international diversification of a firm offers prospective market opportunities; Kogut (1985) reports several internal benefits, such as economies of scale, scope, and learning; and Porter (1985, 1990) highlighted the exploitation of relationships between business segments, geographic areas and the differences in firm capabilities and core competences across business units. The arguments above related to the benefits from firm internationalisation are largely based on the Resource-Based View of a firm (Barney, 1991). As noted by Fladmoe-Lindquist and Tallman (1994), the international diversification characteristics derive primarily from this theoretical perspective that generates which allows organisations to increase their efficiency and to reach strong core competences in international markets (Bartlett & Ghoshal, 1989). In addition, Tallman and Li (1996) suggest that internal tasks render the use of internal capabilities more effective, which leads to greater firm performance, which in turn reveals the moderator character of the TMT’s IC. Despite the previous theoretical arguments defending a positive relationship between international diversification and firm performance, empirical research appears less compelling since it yields contradictory and hence non-conclusive results (Ramaswamy, 1995; Tallman & Li, 1996). Therefore while researchers such as Haar (1989), Kim, Hwang, and Burgers (1993) and Daniels and Bracker (1989) found a positive relationship between international diversification and firm performance, others, such as Geringer, Beamish, and daCosta (1989) and Morck and Yeung (1991), have found a nonlinear relationship between these magnitudes. Many researchers justify the inconsistent results by arguing that International diversification is a complex and difficult to manage topic (Roth, 1992; Sundaram & Black, 1992). Although there may be good reasons to believe that moderate levels of international diversification provide multiple benefits to an organisation, there are also certain significant costs associated with the international diversification of a firm that frequently exceed the benefit provided by the economies of scale and by the managerial capabilities which influence firm performance (Hitt, Hoskisson, & Kim, 1997). Hitt et al. (1997) hypothesised a non-linear relationship between international diversification and performance, and noticed that “it would help explain the conflicting findings of past research” (p. 773). In line with the previous arguments, we suggest the following hypothesis: Hypothesis 2. There is an inverted U-shaped relationship between international diversification and firm performance.

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Product diversification has been a popular strategy (Rumelt, 1974). However, there is no unanimity in the literature regarding the effects of this strategic variable on firm performance (Hoskisson & Hitt, 1990; Ramanujam & Varadarajan, 1989). This lack of agreement had been attributed by Hoskisson and Hitt (1990) to the fact that the relationship between product diversification and performance is far more complex than that portrayed in previous research. Thus, Hitt et al. (1997) added the influence of international diversification to the relationship between product diversification and performance. Geringer et al. (1989) and Rumelt (1974) stated that firms would be higher performers if they were able to capture the potential synergies between their businesses. Thus, an integration of product and international diversification helps firms to exploit interdependencies across their businesses to achieve potential synergies. Firms capable of capturing the synergies and economies of scale from product and international diversification strategies can better implement integrated business-level strategies (Hitt, Keats, & DeMarie, 1995) and are positively related to improvements in firm performance (Hitt et al., 1997). In support of these arguments, Kim, Hwang, and Burgers (1989) establish that an unrelated integrated product and international diversification strategy helps to achieve profit growth, and reduces the risk across product markets as well as the probability of losses, and, as consequence, increases both the probability of achieving a positive return and thereby the probability of the firm’s performance level being raised by a TMT. More recently, Harrison, Hitt, Hoskisson, and Ireland (1991) found that differences in resource allocation patterns across firms’ business units produced higher performance than did similarities, due to the difficulty in imitating encountered by competitors. Therefore, Hitt et al. (1997), on taking a resource-based perspective, expected product diversification to moderate the relationship between international diversification and firm performance in such a way that internationally diversified firms that were also product diversified would achieve higher performance than that of internationally diversified firms that were not product diversified. This expectation suggests that, due to efficient structure, better governance, and enhanced managerial capabilities (learned from experience with diversity), the apex of the curvilinear relationship between international diversification and performance shifts upward and to the right. We therefore propose the following hypotheses: Hypothesis 3. Product diversification positively influences firm performance (H3a) and positively moderates the curvilinear relationship between international diversification and firm performance (H3b). The skills, knowledge and capabilities of a TMT are crucial to anticipating and responding to external opportunities and pressures in order to adopt the best strategy that results in the high performance of the firm. Organisations with Top Management Teams that are more knowledgeable and have greater expertise accurately manage the complexity inherent to a higher level of Product and International diversification, reducing the cost derived from strategic complexity. Diversity in demographic attributes (education, age) and managerial backgrounds provides the firm with the intellectual capital in terms of knowledge, expertise, skills and social networks necessary to successfully address competitiveness within complex organisations (Nielsen, 2009). Thus, TMT can be considered as a bridge between corporate strategy (product and international diversification) and performance (Cannella & Holcomb, 2005). However, the moderator role of TMT diversity in intellectual capital has hardly been noticed by the academic world. While most studies have focused on the moderator effect of the Industry on the relationship between TMT diversity and firm performance, very few studies have recognised the influence of TMT attributes, such as top managers’ experience on the relationship between corporate strategy and firm performance (Singh, Gaur, & Schmid, 2010). Throughout

Please cite this article in press as: M. Carmen Díaz-Fernández, M. Rosario González-Rodríguez, Biagio Simonetti, Top management team’s intellectual capital and firm performance, European Management Journal (2015), doi: 10.1016/j.emj.2015.03.004

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Performance H1

H3a H4a, b

Product Diversification

Corporate Strategy

TMT´s IC diversity

H3b H2

H5a, b

International Diversification

Demographical attributes Managerial experiences

Fig. 1. Research model: trinomial relation corporate strategy-TMT’s IC diversity-performance.

these arguments, we expect that a higher diversity in the human capital of a TMT moderates the relationship between product diversification and performance and between International diversification and performance: Hypothesis 4. TMT diversity positively moderates the relationship between Product diversification strategy and firm performance in terms of demographic experience (age, education) (4a), and in terms of managerial experience (functionality, Industry, International) (4b). Hypothesis 5. TMT diversity positively moderates the relationship between International diversification strategy and firm performance in terms of demographic experience (age, education) (5a), and in terms of managerial experience (functionality, Industry, International) (5b). As a result, and taking Upper Echelon Theory as a reference, the research model in Fig. 1 attempts to test the influence of the TMT diversity in the human capital on the performance. The research model integrating the Upper Echelon Theory with the Resource-Based View is displayed in Fig. 1. Method Data source Within the context of this research, TMT is defined as the hierarchy and the staff composition and includes all those executives around and above the president level, as well as any other officers who serve as directors of the company (i.e. vice-president, senior vice-president, vice-chairman, and CEO) (Pegels, Song, & Yang, 2000). Data on the composition of the TMT sample was obtained from the Business Journal, namely, “New Firms”, during the observed period (2004–2010). In addition, it was necessary to obtain the demographical traits of TMT top managers. While much of the research on TMTs has used secondary databases such as Duns (Cohen & Bailey, 1997), this study has used primary and secondary information sources. Secondary data include company websites, yearbooks and other similar sources (Quien es Quien en España, 2000; Quien es Quien en Europa: CEE, 1991; Who’s Who in the world, 2001; Who’s Who in Finance and Industry, 2000; Who’s Who in Spain, 2003,…), newspapers (Expansión, Cinco Días, El País, ABC,…), and specialist magazines (Nueva Empresa, Actualidad Económica, Dirigentes, El Empresario, Ranking, IPMark, Fomento de la Producción, Fortune, Agenda de la Empresa, Mk Marketing+Ventas, Emprendedores,…), (Pegels et al., 2000; Westphal & Milton, 2000). Primary data have been obtained from personal interviews with the top managers involved in the reference sample. The final sample size resulted in 147 multicultural TMTs from large companies across 18 industries with headquarters in Spain. Data were collected between January 2004 and December 2010.

Observations with missing data at company or industry level were omitted from the data. The restrictions imposed by the Spanish law, LORTAD,1 limited the sample size. However, the sample size can be considered appropriate to achieve an acceptable comprehension of the aim of the paper (Jehn, Northcraft, & Neale, 2000; Wiersema & Bowen, 2005). Data on the performance of companies and their industrial sector were also obtained from two relevant databases, SABI2 and CNMV.3 Measures Performance Three accounting-based measures were initially considered as firm performance indicators to address the objective of the article: the Variation Sales rate (Boeker & Goodstein, 1993; Salancik & Meindl, 1984), the average return on assets (ROA), and the return on sales (ROS) (Certo, Lester, Dalton, & Dalton, 2006; Denis & Denis, 1995). These indicators are different from the standard indicators identified in the literature (Venkatraman & Ramanunjam, 1986), where predominant financial measures, such as return on equity (ROE) are used (Díaz-Fernández, 2004). The lower volatility of the former firm measurement in relation to the latter, as recognised by previous performance researchers, guided the final choice of ROA and ROS. All three measurements, ROS, ROA, and Sales, are very sensitive to the industrial sector. To correct this bias and to achieve an adequate estimation, this study has used relative performance instead of absolute performance, which is supported by Wagner, Pfeffer, and O’Reilly (1984) and Denis and Denis (1995). ROA was calculated as net income divided by total assets and ROS was obtained by dividing the profit between the sales. While ROA measures the firm’s operative efficiency, ROS determines the gross benefit obtained by each monetary unit sold. Once the econometric models were estimated, the indicators ROA and ROS provide similar findings, with even better findings for ROA for the purpose of our study. The results achieved together with the high correlation between ROA and ROS (r = 0.78) motivated our preference to choose ROA rather than ROS as the dependent variable. Furthermore, since ROS and the control variable firm size are functions of sales, the regression analysis with ROS as the dependent

1 LORTAD, Organic Spanish Law, specifically, Ley Orgánica 5/1992, October 29th, on the treatment of the personal data. 2 SABI, Sistema de Análisis de Balances Ibéricos. SABI is a database created by the company Informa that has collected annual accounts from the main Spanish and Portuguese companies since 1990. It is an interesting tool that helps with business analysis, comparisons between companies or company groups, rankings, concentration and segmentation analysis, and sectorial studies. 3 CNMV, Comisión Nacional del Mercado de Valores. CNMV is the Spanish government agency responsible for the financial regulation of these securities markets in Spain. It is an independent agency that is under the direction of the Ministry of Economy and Finance of Spain.

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variable might display “mathematical artefact as well as true relations” (Hitt et al., 1997). Hence, the use of ROA as the dependent variable is then reinforced for the analysis.

Similarly, International diversification was measured by ID = Σ[Pix ln(1/Pi)], where Pi is the sales attributed to the global market region and ln (1/Pi) is the weight given to each global market region.

Predictor variables Top managers’ background characteristics (educational background, educational level, and age), Top manager’s managerial experiences (functional experience, industrial experience and international experience), and corporate strategies (Product diversification and International diversification) were included in the model as predictor variables. TMT attributes were measured following the criteria established in the Upper Echelon Theory. Age was codified according to the biological age of top managers (Pegels et al., 2000; Wiersema & Bantel, 1992). The variable education background was categorised into eight categories according to the literature, including sciences, engineering, maths, business, economics, law, arts, and others (Carpenter & Fredrickson, 2001), whereas the educational level was measured as a categorical variable and the level of education was indicated as recognised by the Spanish Education Administration. Functional background has been categorised as a dummy variable based mainly on that of Wiersema and Bantel (1992), whereby the value one is taken if the TMT member carries out numerous functions within the company, and zero otherwise. Industrial experience was measured as a dummy variable with value one if the top manager has previous experience in an industry different to the industry in which the top manager is performing his/her current professional activity. International experience is also a dummy variable with value one if the top manager manifests knowledge and expertise on foreign markets and culture. Two different measures have been applied to aggregate the data at team level following the criteria established in the Upper Echelon Theory. The average age of the TMT was used as the proxy for agelevel diversity. Blau’s (1977) was used to measure TMT diversity. Blau’s (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), with Pi being the percentage of individuals in the ith category, taking values from 0 to 1, with high values indicating a greater diversity on a particular variable. The average was used to measure the age level, and the Allison’s Coefficient of Variation (1978) (=σ/μ) was applied for the age diversity. An entropy indicator is employed to measure Product diversification and International diversification strategy. Product diversification has been measured using the formula PDT = Σ[Pix ln(1/Pi)], where Pi is the percentage of sales attributed to segment i, and ln (1/Pi) is the weight given to each segment (Hitt et al., 1997).

Control variables TMT size was included as the control variable due to its influence on the group decision-making process and therefore on firm performance (Bantel & Jackson, 1989). Firm size, age of the firm and industry are standard control variables. Firm size measured by the natural logarithm of total sales to control for economies of scale at firm level (Hitt et al., 1997). The age of the firm is taken as the year of the annual report minus the year of establishment. The industry has been codified as three dummies (He & Huang, 2011): Industry 1 takes the value one if the firm is in the agriculture, mining, construction or manufacturing industry and zero otherwise (SIC codes 01–39); Industry 2 with value one for those firms in transportation, communications, electric, gas wholesale or retail trade industry, and zero otherwise (SIC codes 40–59); Industry 3 as dummy variable with value one indicating that the firm is in the finance, insurance, services or public administration industry and with value zero otherwise (SIC codes 60–99). Modelling The hypotheses formulated were tested using panel data where the cross-sectional observations are the TMTs of 147 Spanish firms. A random-effect model was used to analyse the panel data since the fixed-effect model approach is costly in terms of loss of freedom (Gujarati & Porter, 2009). The random-effect model assumes that the error term varies over a cross-section (unit of analysis) as well as over time. Since the error term is not required to correlate with any of the explanatory variables included in the model, then the Hausman test must be applied. The Hausman test (χ2 = 12.23, p = 0.093) indicates that the estimation results of the dummy variable and the random effects are consistent and that the error terms are not correlated with the explanatory variables in the model. The Breush and Pagan Lagrange Multiplier Test implemented in STATA reinforce the Hausman test (Gujarati & Porter, 2009). Thus, the method to estimate the random-effect model has been chosen as the generalised least-squares estimation technique (GLS) using STATA software. Results Table 1 presents the means and standard deviations of the core variables and their bivariate correlations. Functional diversity ranges from 0 (no diversity at all) to 1 (highest diversity). Background

Table 1 Means, standard deviations, and correlations. Variable

Mean

Std deviation

1

2

3

4

5

6

7

8

9

10

11

12

13

1. Edubackdiv 2. Edulevdiv 3. Funtiondiv 4. Industdiv 5. Averageage 6. Agecomp 7. Internatexpdiv 8. Productdiversif 9. Interndiversif 10. SizeTMT 11. Firm size 12. Firm age 13. ROA

0.38 0.47 0.40 0.39 48.38 0.13 0.27 0.5 0.38 5.76 5.85 5.65 0.066

0.24 0.16 0.32 0.28 7.88 0.059 0.23 0.55 0.43 2.44 1.25 0.97 0.17

1.00 0.26*** 0.0024 0.14* 0.09 0.05 0.15** 0.21** 0.14* 0.12** 0.17** −0.12** 0.43***

1.00 0.0042 0.23** 0.011 0.13** 0.001 0.12* 0.08 0.29*** 0.15** 0.08 −0.06

1.00 −0.30** 0.037 0.12** 0.14* 0.45*** 0.18* 0.16** 0.11* −0.27** −0.13*

1.00 −0.031 −0.021 0.014 0.36** 0.21* 0.19** 0.12** 0.10 0.14**

1.00 −0.13** 0.0017 −0.011 0.042 0.008 0.18** −0.15** −0.086*

1.00 0.0021 0.08 0.11* 0.18** −0.033 −0.32** 0.014

1.00 0.10 0.42*** 0.13* 0.38** 0.21** 0.11*

1.00 0.58*** 0.21** 0.24** 0.32** 0.11*

1.00 0.25** 0.35** 0.45*** 0.15*

1.00 0.44** 0.008 0.013

1.00 0.001 0.017

1.00 0.008

1

Note. Pearson correlation, Sig (2-tailed) *p < 0.1, **p < 0.05,***p < 0.001. Variables: Edubackdiv, Educational background diversity; Edulevdiv, Education level diversity; Functiondiv, Funcionality diversity; Industdiv, Industry diversity; agecom, Age diversity; Internaexpdiv, International experience diversity; Productdiversif, Product diversification; Interndiversif, International diversification.

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Table 2 Regression models (ROA). Model 1

TMT diversity

Corporate strategy

Product diversif

Internat diversif

Variable Intercept Control SizeTMT Firm age Firm size Industrydummy2 Industrydummy3 Main effects Averageage Agediv Education level div Educationbackgrounddiv Functionalitydiv Industrydiv Internatexpdiv Productdiversif Internationaldiversif Internationadiversifquared Interaction effects Educationbackgrounddiv × productdiversif Funcionalitydiv × productdiversif Industrydiv × productdiversif productdiv × internationaldiversif Productdiv × internationaldivsquared Intexp × internationaldiversif Intexp × internationadiversifquared Educback × internationaldiversif Educback × internationadiversifquared R-sq ΔR_sq Chi2 Prob > chi2

Model 2

Coefficient 0.14

Std. err 0.34

0.24*

Std. err 0.14

−0.007 −0.072* −0.003* 0.58** −0.45**

0.0043 0.041 0.011 0.282 0.193

−0.007* −0.087* −0.003* 0.48** −0.31**

0.0038 0.043 0.001 0.244 0.153

−0.061* 0.074 0.053 0.48** −0.109 0.078* 0.18** 0.02* 0.16** −0.30***

0.031 0.09 0.182 0.134 0.07 0.041 0.072 0.009 0.081 0.017

−0.055* 0.074 0.071 0.35** −0.110* 0.083* 0.12** 0.01* 0.16** −0.31***

0.028 0.06 0.131 0.134 0.059 0.043 0.043 0.005 0.079 0.011

0.143* 0.451** 0.33** 0.740** −1.02** 0.42** −0.21* 0.32* −0.17* 0.39 0.26 39.68 0.0419

0.075 0.138 0.116 0.368 0.402 0.171 0.107 0.136 0.089

0.13 28.63 0.0381

Note. P-value *p < 0.1, **p < 0.05, ***p < 0.001.

education diversity ranges from 0 to 0.75, education level diversity ranges from 0 to 0.77, and age diversity ranges from 0 to 0.23. Education background (SK = −0.504), education level diversity (SK = −1.078) and age level (SK = −1.39) present left-skewed distributions, which indicates that most of the companies do not have a high diversity in their TMT. However, age diversity (SK = 0.20), functional diversity (0.27), industry diversity (SK = 0.39), and International experience diversity (SK = 0.18) highlight a moderate right-skewed distribution. The modest correlations between the independent variables appear to suggest no evidence of multi-collinearity in the model. An ordinary least-squares regression was also applied to obtain the VIFs to test for any presence of multi-collinearity. The highest VIF was 1.27 indicating non-perfect correlation between the variables included in the model (Greene, 2000). Table 2 displays estimates for Model 1 where control variables and the main effects are included and Model 2 (Full Model) where control variables, main effects and interaction effects are included. Only the significant interaction effects are displayed in Model 2 for easier interpretation. The chi-square statistic indicates the overall significance of each model. The model with ROA as the dependent variable appears to be significant at 5%. The control variables TMT size, firm size and firm age have a negative influence on firm performance (b = −0.007, p < 0.01, b = −0.003, p < 0.01; p = −0.087, p < 0.05), which indicates that small teams, and small, new companies present better corporate performance than older and larger companies with larger TMTs during the period 2004–2010. The industry dummy variables appear to exert significant influence on firm performance. Firms in retail trade, gas and electricity industries, transportation, and communications perform better than firms in agriculture, mining, construction, and manufacturing industries (b = 0.48, p < 0.05). Firms in finance, services and public administration industries achieve lower performance than firms

in retail trade, gas and electricity industries, transportation, and communications (b = −0.31, p < 0.05). Regression analysis shows the TMT’s average age result in a negative and significant influence on firm performance as measured by ROA (b = −0.055; p < 0.05). The result is consistent with the Upper Echelon Theory literature which states that younger managers are more receptive towards risk taking, towards pursuing more innovative growth strategies, and towards generating high levels of firm performance (Grimm & Smith, 1991; Hambrick & Mason, 1984). Therefore the findings support H1a for the predictor variable average age. However, the diversity of the age composition of the TMT is insignificant (b = 0.074; p > 0.1), which reveals that more homogeneity in terms of age composition promotes better performance. Hence, hypothesis H1a does not receive support when considering age composition diversity as a predictor, thereby revealing the weaknesses in Murray’s (1989) methodological argument. Education level diversity appears insignificant (b = 0.071, p > 0.1) and Educational background diversity is positive and significant (b = 0.35, p < 0.05) when using ROA as the performance proxy. Hence, Hypothesis H1a for education diversity is partially supported. Functional experience resulted in a negative and significant effect on performance (b = −0.110, p < 0.10). Industry diversity and International experience appear to influence ROA positively (b = 0.083, p < 0.10; b = 0.12, p < 0.05). Hence, Hypothesis 1b is supported. The positive significant coefficient for International diversification (b = 0.16, p < 0.05) and the negative significant coefficient for International diversification squared (b = −0.31, p < 0.01) suggest a curvilinear (inverted U-shaped) relationship between ROA and International diversification. There is a statistically significant and positive relationship between Product diversification and firm performance (b = 0.01, p < 0.10). The results achieved support hypotheses H2 and H3a.

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0.7

0.5

0.4

Low Productdiversif

0.3

High Productdiversif

Performance

Performance

0.6

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Low Functiondiv High Functiondiv

Low Productdiversif

0.2

0.1 Low Internationaldiversif

7

High Productdiversif

Fig. 4. Moderating effect of functional diversity on product diversification-perfomance. High Internationaldiversif

Fig. 2. Moderating effect of product diversification on international diversification-performance.

1 0.9

In Table 2, the interaction effect of Product diversification and International diversification squared on ROA provides support for hypothesis H3b. The moderator effect of Product diversification on the relationship between International diversification and ROA has been examined by plotting that relationship for low and high product-diversified firms. As observed from Fig. 2, for non-extreme values of International diversification, those firms that are more product-diversified positively intensified the relationship between International diversification and ROA in comparison to those firms with low Product diversification. The significant moderator effects of TMT diversity on the relationship between Product diversification and ROA are depicted in Figs. 3–5. As observed in Fig. 3, Product diversification moderates the relationship between educational background diversity and ROA. The positive sign of the interaction effect (b = 0.143, p < 0.10) suggests that the influence of Product diversification on performance is more positive for greater diversity of TMT educational background. From Fig. 4, functional diversity positively moderates the relationship between Product diversification and performance (b = 0.451, p < 0.01). The correlation between Product diversification and ROA is negative for firms with low functionality diversity in their TMTs, while the correlation turns positive for those firms with TMTs with high functionality diversity. International experience diversity also positively moderates the relationship between Product diversification and corporate performance (b = 0.42, p < 0.05) and reveals s a higher positive correlation between Product diversification and ROA in TMTs

performance

0.8 0.7 0.6 Low Industdiv

0.5 0.4

High Industdiv

0.3 0.2 0.1 0 Low Productdiversif

High Productdiversif

Fig. 5. Moderating effect of industry diversity on product diversification-perfomance.

with high diversity international experience (Fig. 5). Hypothesis 4 is supported in terms of the IC, educational background diversity and managerial background diversity of the TMT. Finally, International experience diversity and educational background diversity positively moderate the relationship between International diversification and firm performance as observed in Figs. 6 and 7. An upward shift of the inverted U-shaped relationship is observed. The influence of international diversification on performance is more positive in those firms with top managers with 3 different experiences and knowledge in foreign markets. The evidence supports Hypothesis 5 for International experience and background education diversity.

0.7

1 0.6

performance

0.8 0.7 0.6 Low Educbackdiv

0.5 0.4

High Educbackdiv

0.3 0.2

Performance

0.9

0.5

0.4

Low edubackground

0.3

High edubackground

0.2

0.1 0 Low Productdiversif

High Productdiversif

Fig. 3. Moderating effect of educational background diversity on product diversification-perfomance.

0.1 Low Internationaldiversif

High Internationaldiversif

Fig. 6. Moderating effect of educational background diversity on international diversification-perfomance.

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8

0.7

Performance

0.6

0.5

0.4

Low Internatexpdiv

0.3

High Internatexpdiv

0.2

0.1 Low Internationaldiversif

High Internationaldiversif

Fig. 7. Moderating effect of international experience diversity on international diversification-perfomance.

Discussion and conclusion Organisational competitiveness requires Intellectual capital so that it can respond to internal and external opportunities and so that threats can be faced properly by the firm. Diversity in TMT attributes is commonly seen as a double-edged sword. On the one hand, diversity allows top managers to identify those environmental opportunities and threats and to formulate company strategies of greater precision that are easily adapted to complex environments. Hence, TMT diversity is associated to the skills and capability (IC) of decision-makers. On the other hand, greater heterogeneity in TMT characteristics could lead to more internal conflict which might be translated into less effective decision-making and therefore lower firm outcomes. The opposing forces on performance due to TMT diversity have led to inconclusive results on the relationship between TMT diversity and firm outcome. However, the real influence of heterogeneity in TMT characteristics on performance cannot be found by analysing only the main effects of TMT diversity on firm outcome. The decision-making process is much more complex than that and requires the effect of TMT diversity on firm outcome to be conditioned on its effects at firm level (corporate strategies), at industry level (environmental), and TMT level (Carpenter, 2002; Finkelstein, Hambrick, & Cannella, 2008). To this end, longitudinal studies are also required in order to determine the effect of TMT diversity on performance. In line with these arguments, this study offers several contributions to the literature. First, while there has been a growing interest in the literature in analysing the moderator effects of environmental circumstances on the relationship between TMT diversity and firm performance, very few studies have paid attention to the three-component relation: strategy complexity versus TMT diversity versus Performance. In fact, complex organisations characterised by product diversification and international diversification strategies need higher heterogeneity in demographic characteristics (age, education) and managerial experience (functional, industrial and international) which bring to the firm accurate human capital (knowledge, skill, expertise) and relational capital (network contacts) which in turn exert a positive influence on corporate performance. Our study contributes to the literature by analysing the moderator effect of TMT background diversity as a proxy of Intellectual Capital on the relationship between corporate strategy (product and international diversification) and firm outcome. Thus, our study brings together the Upper Echelon Theory, the ResourceBased View and the diversification literature. Top Management Teams of greater diversity are expected to have a greater impact on the

relationship between corporate strategy and firm outcome since heterogeneity in experience and background renders the team more capable of managing complex strategies (Cannella, Park, & Lee, 2008; Carpenter, 2002). Our findings suggest that diversity in TMTs is more appropriate in firms with higher complexity, and therefore for the bionomic corporate strategy-performance. The significant positive moderating effects on TMT diversity on the relationship between strategy and performance reveal that TMT knowledge, skills and capabilities are vital for the successful implementation of corporate strategies that lead to a higher firm outcome. The curvilinear relationship between International diversification and performance guides managers not to overdiversify their corporate strategy, which might otherwise result in a downward trend for performance. The positive interaction effect between Product diversification and International diversification means that the experience, knowledge skills, and capabilities acquired by top managers in Product diversification can be applied in order to adopt an accurate strategy on International diversification. In fact, the moderator effect of product diversification reduces the negative effect on performance of a high level of International diversification. Second, very few studies on TMT diversity have been carried out in European countries, and even fewer in Spain. The legal restrictions imposed by the Spanish Law LORTAD curb any study into TMTs. By using primary and secondary sources of information, our study has collected information on the most relevant demographic and managerial experiences. Not many papers use as many top managers’ attributes as this paper. Furthermore, our study has collected demographic and managerial attributes for all top managers, and not only for CEOs as is common in most demographic studies. Third, the present study analyses the influence of TMT diversity on performance (main effects) and on the binomial corporate strategy-performance (moderator effects) by using panel data to understand how changes in diversity traits affect performance (main effects) and how they affect the relationship between corporate strategy and performance (moderator effects) over time. Our study is an attempt to address the call, emerging from the recent academic literature, to comprehend the inconsistent and inconclusive results obtained when studying the relationship between TMT diversity and performance. This paper provides an extension to the Upper Echelon Theory by exploring the moderator effects of TMT diversity as a proxy of TMT intellectual capital diversity in the binomial relationship between corporate strategy and performance. To this end, an integrated approach has been applied by combining the Upper Echelon Theory, the Resource-Based View and literature on corporate strategy. Limitations and future research The empirical results largely support the research model but certain limitations need to be considered, which might provide opportunities for future research avenues. Even though the sample size used in the study is commonly considered appropriate for the scope of the analysis, a larger sample size, a wider period of time and a cross-cultural comparative analysis is recommended in order to generalise the inferential results achieved. While the research model includes magnitudes at TMT level (IC) and firm level (corporate strategy), no variables have been included at environmental level (Industry). Future research might simultaneously analyse the moderator effect of industry variables (dynamism, munificence, concentration) on the relationship between TMT and performance with the moderator effects already included in this study. The research paper strives to shed light on the controversy surrounding the inconsistent and inconclusive results found in empirical analysis. In line with this argument, the study explores the moderator effects of TMTs on the binomial relationship between corporate strategy and performance. In addition, other relations need to be

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Please cite this article in press as: M. Carmen Díaz-Fernández, M. Rosario González-Rodríguez, Biagio Simonetti, Top management team’s intellectual capital and firm performance, European Management Journal (2015), doi: 10.1016/j.emj.2015.03.004