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Innovation is age-related: fact or fable?
A study regarding the relationship between the manager’s age and their firm’s
innovativeness
Abstract: Evidence on the effect of manager’s age on the firm’s innovativeness have to be
interpreted with great caution. Drawing generalized conclusions about the age-dependence of innovativeness seems to be inappropriate. It is found that investigating the interplay between the manager’s age and the firm innovativeness at higher aggregation levels such as country or industry is a promising alternative which may be used to complement existing individual-level evidence on managers’ age and innovation. Cultural environments lacking innovative opportunities would benefit shareholders hiring a more selfish leader whose style is more autocratic, while a highly innovative industrial environment seems to be a young man’s game.
Han Miedema
Student nr.: 2213990, e-mail: j.r.miedema@student.rug.nl
January 2016
Supervisor: dr. A.A.J. van Hoorn Referent: drs. J. van Polen
Faculty: Economics and Business Administration Programme: International Business and Management
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1. Introduction
Over the last decades research on ‘innovation’ has continuously grown and spilled over to many fields of inquiry (Damanpour & Aravind, 2011). When environmental factors are taken into account innovation has proven to positively affect firms, provide a huge source of competitive advantage (Damanpour & Schneider, 2006), and being essential for survival (Hull & Rotherberg, 2008). Current research on innovation primarily focusses on identifying environmental conditions that facilitate or inhibit innovation. However, recent studies demonstrate the importance of how managerial leadership can positively influence change and innovation. While Littrell and Valentin (2005) showed that especially managerial leadership is crucial to successfully innovate when sudden changes in an external environment take place, Damanpour and Schneider (2009) additionally demonstrated that leaders are able to encourage innovation as a means to improve organizational effectiveness and are able to pioneer change.
Therefore, managerial characteristics could affect the degree of firm innovativeness. Especially age seems to determine the level of innovativeness (Damanpour & Schneider, 2006). Young managers are often criticized for focusing on short-term performance and taking no responsibility for the long-term development of an organization. However, young managers are not expected to focus on the development of an organization while they are not involved in the discussions about the long-term performance of the firm. Young generations should be represented in managerial functions because they are more willing to take risks and their technological knowledge is more recent (Damanpour & Schneider, 2006). The consultation of new, young managers has proven to be innovatively pioneering. Moreover, earlier research suggested that older managers may be less able to grasp new ideas and learn new behaviour (Hambrick & Mason, 1984). However, within organizations there are many talented and longer tenured managers who are able to innovate. One of the best known examples is Steve Jobs. He was founder of Apple at a young age and later revolutionized their industry by introducing the i-Pod, i-Phone and i-Pad devices. Older people have great experience, are full of passion regarding their profession and are interested in working with younger colleagues (Connors et al, 2007). Moreover, because of the changes in the economic environment longer careers are
imperative. Therefore, focusing on recruiting only younger employees and managers would appear to be short-sighted. Firms refusing to invest in older workers would be wasting talent and knowledge (Frosch, 2011).
U-2 shape would represent an inflection point where the innovative effectiveness of managers starts to decline at a certain age. Anticipating the point of inflection would imply firms are able to react prematurely to declining innovativeness of managers. It is possible that the managerial effectiveness of younger managers is higher due to more recent knowledge of innovation. This should suggest that it would be more beneficial to ‘refresh’ the managers whom have passed the inflection point by some years.
Additionally, according to Lewin’s equation, behaviour is a function of person and its environment. A single person's behaviour may be different in unique situations, because he or she is acting in response to different forces and factors (Samsone et al, 2003). National culture would considerably improve our understanding of whether, when, how and in what form innovation will evolve (Herbig, 1994; Della Piana et al, 2015). Perception of aging influences expectations and behaviour towards senior people with growing evidence that views of aging differ across cultures as well (Löckenhoff et al, 2009). Organizational decisions about senior workers may be affected by the negative stereotypes of senior people (Bertolino et al, 2013). Thus cultural influences can affect the range of most ideal age for best possible managerial effectiveness and impact the inflection point. Moreover, in order to be effective innovators, organizations need to scan the environment, analyse and understand the industry structure to be alert to new opportunities. Managerial perceptions of industry structure play a key role in the learning and innovation process (Weerawardena et al, 2006). Industries
characterized by a high level of innovativeness would also demand more innovativeness of their managers which might change the position of the inflection point. Thus, according to Lewin’s
3 inflection points and gain precision around understanding where and why they occur. Moreover, control variables will shed light on whether inflection points are delayed or even eliminated.
Most literature on determinants of innovations have been carried out in developed countries. As a result of socio-economic, cultural and institutional factors, innovation processes seem to be different in developing countries. Variation between developed and developing markets is likely to occur as a function of differences in norms, resources, and infrastructures (Hitt et al, 2000). These important differences in the underlying institutional infrastructures of developing and developed market affect managers’ strategic orientations (Hitt et al, 2000). Due to the increased importance of developing markets this study will look at the firm innovation determinants in a sample of developing countries. Thus, this study focusses on determining the inflection point of the U-shaped relationship from various national cultures and industries in developing countries. The possible variance in inflection points will explained by the environmental characteristics.
1. Theory & Hypotheses
1.1 Background: Defining Innovation
Defining innovation causes a lot of confusion in the literature. It is considered a vague concept and the lack of clarity on this might even be an obstacle to the progress of research (Adams, Bessant, & Phelps, 2006). Innovation is known to depend on R&D, because it enables product innovation and eases the adoption of technologies developed in other firms and countries (Daveri & Parisi, 2015). Innovation at organizational levels has been defined as the generation and/or adoption of new ideas or behaviours, which may pertain to a product, service, technology, system or practice (Damanpour & Schneider, 2009; Kessler, 2004). Baregheh et al (2009) state that the concept of innovation includes a wide array of different types of change, depending on the resources, capabilities and strategies of organizations and the requirements they must meet. In order to achieve a uniform and comprehensive definition, Baragheh and colleagues analysed 60 carefully selected definitions and subsequently discovered six main characteristics of innovation, which formed the basis for their comprehensive definition that captures the essence of innovation.
The subsequent characteristics influence innovation:
o The nature of innovation: something new or improved o The type of innovation: For example, a product or service
4 o The social context: social entities, systems or groups of people in the innovation process
involved or environmental factors that may affect it.
o The funds: the necessary resources (e.g. financial resources) o The goal: improving an organization’s focus on innovation
Based on the abovementioned characteristics Barageh et al. come to an overarching definition: ‘Innovation is the multi-stage process whereby organizations transform ideas into new/improved products, service or processes, in order to advance, compete and differentiate themselves
successfully in their marketplace’. (Baragheh et al, 2009: 1334)
2.2 Hypotheses
2.2.1. Effects Managerial Characteristics
Age and tenure
Researchers have been exchanging arguments about the effect of a manager’s age on innovation. Traditionally, managers were likely to be older and more experienced than most of the individuals they supervised. However, it is now increasingly common that older workers report to younger managers (Goldberg & Cleveland, 2002).
5 to novel problems (Mumford,2000) and therefore influences relationship between age and innovation. Learning a subset of the skills, theories, and facts developed by prior generations seems to be a necessary ingredient for innovative activity (Jones, 2010) . Management experience was positively correlated with accuracy in judging the information value (Taylor, 1975). Moreover, senior managers often intuitively take complex decisions because they have more experience. Furthermore, senior managers have more general knowledge and vocabulary (Kooij, 2010), whereas their work-related outcomes of cognitive ability may not be affected by aging (Sterns & Miklos, 1995). They are also seen as dependable, cooperative, conscientious and consistent (Sterns & Miklos, 1995). In addition, as a results of slower working brains their decisions are often less hasty or impulsive than those of younger people (Daniels, 2014).
If a manager hopes to maintain performance levels, he or she will need to compensate for decline in fluid intellectual ability by working harder and/or longer. Younger adults are more resilient in the face of relatively high level of continued effort in comparison to senior adults. However, senior adults may be less willing to commit to performance goals, engage in work behaviour or persist at tasks that they perceive to involve substantial levels of effort (Kanfer & Ackerman, 2004).
For senior workers, knowledge is typically substantial, whereas time and cognitive effort are often in shorter supply. For younger employees the opposite is true (Kanfer & Ackerman, 2004). Managers new to their position would be more willing to innovate because they bring a fresh perspective, but they may negatively influence innovation due to the lack of familiarity with their job and the organization. Therefore gaining experience and becoming familiar with critical issues are needed to learn and resolve them. However, the effect of age and experience will reverse when older managers are ingrained in the existing organizational routines and practices, which may mitigate their inclination to change the status quo and pioneer an innovation (Damanpour & Schneider, 2009). According to Cole (1979) age is curvilinear related to productivity. Productivity rates increase to about to age of 45 and then gradually decreases. The capacity to produce economically relevels, novel achievement, follow a curvilinear, inversely u-shaped functional form with age at the individual level. This suggests that at older ages creative performance gradually levels off after a certain age (Frosch, 2011). Thus,
H1: Managers’ age has an inverted U-shaped relationship with their firms’ innovativeness.
H2: An inflection point of the increase of managers’ age on the firms’ innovativeness declines exists. 2.2.2 Industry as control variable
6 characteristics and innovation. Industries differ in their effect of R&D and innovative efforts on productivity due to the existence of different scientific and technological opportunities, market demand and appropriability (Crespi & Pianta, 2009; Klenow 1996).
o Technological opportunities: Industries with more technological opportunities are assumed to encourage innovation because the accumulated knowledge reduces the cost of translating knowledge into new products and processes (Martinez-Ros, 1999). Moreover, the scientific environment provides richer ground for improvement in some industries than others, therefore the technical advance generated per unit of R&D differs per industry.
Technological opportunities differ across industries since the scientific environment provides more fertile ground for advances in some industries than others. As a result, the technical advance generated per unit of R&D is greater in some industries than others (Baldwin et al, 2000). Technological characteristics influence the direction and magnitude of learning processes and the knowledge accumulated by managers. The knowledge base can be generic or specific, codified or tacit, simple or complex, independent or embedded in a system, which varies across industries (Malerba, 2005). Moreover, over time firms cumulatively increase their absorptive capacities, knowledge competencies and organizational capabilities. These cumulativeness conditions actively vary among industries and therefore affect the innovativeness in each sector (Malerba, 2005).
7 other research institutes), the market (competitors and clients), the suppliers, or be exclusively based on internal sources, as in the case of large and established innovative firms (Malerba, 2005: 8)
o Appropriability: This refers to the capacity of the firm to retain the added value it creates for its own benefit1. The appropriability conditions are the possibilities of appropriating the innovative rents by protecting innovations from imitation through a variety of means, such as patents, process secrecy and know-how, design and R&D know-how, and other non-technical means (Malerba, 2005:10). Industries differ in the extent to which innovator can capture the social returns to their innovations. Industries characterized by lower appropriability are more likely to undertake too less R&D (Klenow, 1996). Firms’ strategies also differ regarding the composition and type of expenditures. They often tend to rely upon a variety of additional innovative expenditures such as new equipment, training, production preparation and design-related expenditures (Malerba, 2005). Moreover, the money required for a radical product innovation varies enormously. For example, compare 70 million dollars for a radical new drug with one billion for a new model car that only might have incremental improvements in its various components (Hage, 1999).
Several relevant factors may determine differences of innovativeness between industries. Technological opportunity, market demand and appropriability are the three primary factors representing inter-industry differences for innovation, which requires different knowledge of managers. Industries characterized by high technological opportunities affect the magnitude of learning processes and the knowledge accumulation by managers. According to Feeney (2002) senior people have more difficulty in activating their learning processes and thus their ability to learn declines, which would affect their firm’s innovativeness. Moreover, the need for anticipating quickly to the changing preferences of consumers ensures managers need to respond accordingly. However, senior people perform poorly when the anticipation period is short (Lewis & Bottomley, 1999). The differing industry characteristics ensure that the level of firm innovativeness varies. A high degree of innovation may be related to time pressure and information overload, which influences the manager’s performance (Andrews & Farris, 1972). For example, an older manager will be less likely to be innovative in an industry that is characterized by high demand variation than an industry with low variation. Therefore managers are likely affected by the industry in which they operate and adjust their innovative behaviour appropriately. Thus,
‘Hypothesis 3: Industry characteristics affect the degree of innovativeness of a firm’
8 ‘Hypothesis 4: Industry characteristics will affect the inflection point of the relationship between managers’ age and their firms’ innovativeness.’
2.2.3 National Culture as a Moderating Variable
Managerial creativity as a basis for initiating innovation greatly depends on the surrounding culture as a whole. Cultural influence is based on two opposing processes – tradition and innovation – which ensures the openness towards new experiences varies among cultures (Kaase & Vadi, 2008). In order to determine the influence of culture it is important to establish an encompassing definition:
‘Culture is an all-inclusive system of communications which incorporates the biological and technical behaviour of human beings with their verbal and nonverbal systems of expressive behaviour. Culture is the sum total of a way of life: it is patterns of values, traits, or behaviours shared by people within a region.’ (Herbig & Dunphy, 1998:13).
Existing cultural conditions determine whether, when, how and in what form a new innovation will be adopted. Culture may inhibit or foster innovation and therefore has a great influence on the innovative capacity of a society (Herbig & Dunphy, 1998). Cultural perceptions of aging are multidimensional in nature and have controversial characteristics, which could influence the relationship between the managers’ age and their firms’ innovativeness. The relationship between leaders and followers are based on mutual trust and respect for each other. Therefore the respect for seniority within a culture influences this relationship. Certain cultures are characterized by high respect for seniority, whereby the persuasiveness and effectiveness of senior managers may be higher. There are systematic age differences in physical abilities and cognitive performance due to biological changes which are related to healthy aging (Löckenhoff et al, 2009). Senior respect is interpreted and practiced in diverse cultural contexts and varies by culture (Sung & Kim, 2003). Moreover, age-related stereotypes are believed to reflect the cultural norms of social interaction and therefore create cross-cultural variation (Boduroglu et al, 2006) and negative stereotypes of senior people may indeed effect productivity (Blackburn & Lawrence, 1986). Organizational decisions about senior workers may be affected by whether they hold negative views of senior workers (Bertolino et al, 2013).
9 colleagues (2009) participants from cultures with greater uncertainty avoidance reported more negative societal views of aging, which would moderate the relationship between the manager’s age and their firms’ innovativeness. The negative stereotypes regarding senior employees could influence the effectivity of senior managers and thereby moderate the inflection point.
Moreover, the status symbols of power are crucial in order to indicate social position and communicate the respect that could be required. According to Hofstede (1980) the power distance measures how far inequality is accepted by a culture. Low power distance facilitates technological innovation because the organisations are decentralised, which transmits trust and helps to equalise participants by providing information about new product development. However, bureaucracy is a negative effect of low power distance and it facilitates employee passiveness and eliminates creative thinking (Kaasa & Vadi, 2008; Busse, 2014). Participants from high power distance cultures reported less favourable views of age-related changes in knowledge and wisdom. In these cultures individuals tend to value hierarchy, which implies they are more likely to show respect for superiors and expects them to take the lead (Ahmed et al, 2009) and therefore is associated with a more favourable societal view on aging. (Löckenhoff et al, 2009). Therefore, the degree of firm innovativeness would be higher in cultures characterized by low power distance. However, the relationship between a managers’ age and a firm’s innovativeness would be moderated due to the societal view on aging. High power distance cultures are characterized by a less favourable view on aging, whereby the effectiveness of managers may be lower. According to Hofstede (2011) an indulgent society allow relatively free gratification of basic and natural human desires related to enjoying life and having fun. The emphasize on enjoying might reduce the effectiveness of managers. However, a culture characterized by restraint controls gratification of needs and regulates it by means of strict social norms. The strict social norm might reduce the individual creativity of managers. Societies in which restraint dominates have more formal rules and restrictive norms (Busse, 2014). According to Jie & Ling (2015) senior managers have more tendencies towards restraint and fewer towards indulgence. Maintaining order is less emphasized in indulgent cultures, while this has a high priority within countries characterized by restraint. This influences the status symbols of power within a country and thus the societal view on aging. A more hierarchical structure of society implies citizens are more likely to show respect for superiors and therefore is associated with a more favorable view on aging (Ahmed et al, 2009). A company that is unable to meet the environmentally demanded innovation in indulgent countries would benefit from a more autocratic leader (Rotemberg & Saloner, 1993).
10 process (Van Everdingen & Waarts, 2003). According to Lynn & Gelb (1996) national innovativeness is positively related to national levels of individualism. The inflection point might be affected by the fact that collectivistic cultures are characterized by a high degree of respect and honour for seniors (Cai et al, 1998). This positive perception regarding aging in those cultures can affect degree effectiveness of managers. Furthermore, cultures that have a long-term orientation are more likely to adapt to new circumstances and thus more innovative. Firms are be receptive to changes than companies operating in a short-term orientation culture. Conversely, short-term oriented cultures tend to be less innovative because of the respect for tradition (Van Everdingen & Waarts, 2003). Enduring and emotional commitments are found in long-term orientated cultures (Lee & Daws, 2005). The effect on the U-shaped relationship is not straightforward, because senior managers could maintain their status quo due to enduring commitments but replacing them for younger managers might be a long-term investment.
According to Hofstede (2001) a masculine culture positively influences innovativeness due to the emphasis on rewards and recognition of performance, and training and improvement of individuals Managers in masculine cultures are expected to be decisive, assertive, aggressive and competitive (Van Everdingen & Waarts, 2003). While their polar opposite, feminine cultures, emphasizes the usage of intuition, dealing with feeling and trying to find a consensus. According to Imm and colleagues (2007) Hofstede’s masculinity and Schwartz’ (2006) mastery are compatible. Mastery encourages active self-assertion in order to master, direct, and change the natural and social environment to attain group or personal goals (Schwartz, 2006). This cultural value would foster innovation because it emphasizes daring and ambition. Those cultures would also contemplate genuine respect for elderly more important than cultures where harmony prevails. Moreover, Löckenhoff and colleagues (2009) also showed that perceived increases in respect were linked to higher cultural levels of mastery.
As a result of the abovementioned arguments the inflection point would vary among different cultures. Thus,
‘Hypothesis 5: National cultures affects the degree of firm innovativeness’.
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3 Method
Central to this research is the influence of age on the degree of innovativeness of managers when considering the contextual factors, such as culture and industry. In this chapter the chosen research method firstly will be discussed and subsequently the characteristics of the studied population. Finally the research model with the associated concepts and the operationalization of the corresponding variables will be scrutinized.
The hypotheses are tested by using the Business Environment and Enterprise Performance Survey (BEEPS) database, which has been conducted by the World Bank and ERBD since 1999. Most of the data gathered have come from surveys implemented in nearly all transition countries of Central and Eastern Europe and the former Soviet Union. In each country, based on the size of their economies, between 150 and 500 firms were interviewed. The database is publicly available on the World Bank Web site and contains 3,565 foreign- and locally owned firms in the above mentioned countries (after excluding public agencies, charities, non-governmental organizations, and farms). The focus of the interviews with firm managers is the business environment in which firms are operating, but it also includes key figures about the firm, including sales, percentage R&D spending of annual sales and growth. The BEEPS database collects direct measures of innovation. This research uses the 2002 survey data across 27 countries, because this includes information about the managers’ demographic characteristics. The second round of the BEEPS in 2002 covered 6,667 enterprises in 27 countries of Eastern Europe and Central Asia: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, FYR Macedonia, Georgia, Hungary, Kazakhstan, Kyrgyz Republic, Latvia, Lithuania, Moldova, Poland, Romania, Russia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine, Uzbekistan and Yugoslavia. Questions are usually answered by the top manager of the organization. The Word Bank guaranteed a high degree of confidentiality, whereby they ensured a high participation and better confidence in the quality of the responses collected. The main purpose of the survey is to identify whether or not the relationship between managerial characteristics and innovation are different among cultures and industries. BEEPS asks firms to answer to different types of innovativeness, whereby a comprehensive view on this variable is captured. In addition to these innovation indicators the BEEPS dataset also contains a rich set of other variables which give an indication of managers’ demographic characteristics. The BEEPS dataset also provides detail about the type of industry and country of origin, which may also influence the degree of innovation.
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3.1 Data
3.1.1 Dependent variable
The firm innovativeness is the dependent variable in the analysis. More recently the literature has started to shift focus to direct measures of innovation rather than indirect ones such as R&D spending. BEEPS asks firms to report different types of innovativeness. Hence, it is possible to define innovation broadly as the development and upgrading of new products or adoption of new technologies. Specifically, the binary variables used based on answers to the question about if the company has undertaken any of the following initiatives since 1998 are:
o Successful development a major new product line o Upgrade of an existing product line
o Introduced new technology that substantially changed the way that the main product is used This gives advantages over the more commonly used measures of R&D expenditures, which may be inappropriate. Firms may have different levels of efficiency when introducing new products and processes, which implies that higher levels of R&D input do not necessarily ensure higher levels of innovative output (Klomp, 2001). Moreover, R&D expenditure figures do not reveal whether the innovation process receives attention across firms and industries, which limits the comparison between countries (Klomp, 2001). Domestic firms in emerging markets are less likely to invest in R&D, because they are expected to engage more in imitation and adaptation of already created and tested technologies, rather than generating new inventions (Gorodnichenko & Schnitzer, 2013). The measures of innovation are in agreement with the recommendations of the Oslo Manual suggesting the use of survey measures of innovations which are ‘new to the firm’ (Gorodnichenko & Schnitzer, 2013).
To complement the analysis of innovation a dummy variable equal to one is used if a firm reports a positive R&D spending and zero otherwise. The measurement of innovation by volume of R&D spending is preferred because the distribution of R&D spending is highly skewed with a large mass of firms reporting zero R&D expenditures. Unfortunately, approximately 35% answered the question by which the amount of missing values would increase enormously. Therefore the alternative measure is only used as a robustness/validity check.
3.1.2 Independent variables
Managers’ age
13 1) 34 or younger 2) 35 to and including 49 3) 50 to and including 64 4) 65 or older Industry
The industry categorization used for the survey is based on eight different main areas of activity: 1) Mining and quarrying
2) Construction 3) Manufacturing
4) Transport storage and communication 5) Wholesale and retail trade
6) Real estate, renting and business services 7) Hotels and restaurants
8) Other services; motion pictures and video activity, radio and television activities, other entertainment activities, news agency activities, washing and dry cleaning, hairdressing, funeral and related activities, other service activities
The table 9 in the appendix provides information on the distribution of firms by industry for the sample used in this study.
Culture
14 By making use of Hofstede’s dimensions (2001) a large range of cultures will be covered. Hofstede’s work on culture is the most widely cited in existence and provides a highly valuable insight into the dynamics of cross-cultural relationships (Jones, 2007). Hofstede (2013) defined six value dimensions based on worldwide responses: power distance (i.e. acceptance of differences in status and power), uncertainty avoidance (i.e. extent society feels threatened by uncertainty), individualism (i.e. low group integration and high self-interest), masculinity (i.e. focus on being assertive and successful), long-term orientation (i.e. orientation towards future reward) and indulgence (i.e. free gratification of some desires and feelings). The scores used in the present study were drawn from Hofstede (2001). In order to benchmark the inflection point on a global scale, a complete list of the countries’ inflection points is provided in table 10 of the appendices.
3.2 Empirical Model and Estimation
The above stated hypotheses were tested using a multiple regression analysis. Based on the obtained information from the analysis will be determined if the assumed hypotheses are valid. The model will test the first and second hypothesis on whether or not an inverted U-relationship between the managers’ age and firm innovativeness exists. Thus, the innovativeness of a firm (f) in a certain country (c) depends on the managers’ age.
𝐼𝑐𝑓 = β0+ β1∗ Age + β2∗ Age2+ Ɛ
To obtain the inflection point of the curve, the derivative of the function with respect to age is calculated. The inflection point is where the derivative is equal to zero.
𝑑𝐼 𝑑𝐴𝑔𝑒= β 1+ 2 β2𝐴𝑔𝑒 = 0 𝐴𝑔𝑒 = β 1 −2β2
The effect of industrial and country characteristics will be measured by dummy variables. 𝐼𝑐𝑓 = β0+ β1∗ Age + β2∗ Age2+ β3∗ CONTROLS + Ɛ
15 impact. Thus the inflection point of firm f in country c is:
𝐼𝑃𝑓𝑓 = β0+ β1∗ 𝐶𝑉
4 Empirical Results
4.1 Validity and reliability
A factor analysis is used to check whether the questions of firm innovativeness sufficiently correlate with each other in order to reduce it to a single construct. The Barlett’s test was used to calculate the redundancy between the variables that can be summarized with one factor. The Bartlett’s test of sphericity tests the null hypothesis in which it assumes no single variable correlates. The significance level of the Bartlett’s test is smaller than 0.05 whereby it can be assumed that the chosen variables correlate. The Kaiser-Meyer-Olkin Measure checks whether the original variables can be combined into one factor. The value needs to be above 0.5 in order to be able to reduce the questions to one factor (Hair et al, 2006). The KMO value of innovativeness is 0.659 and thus meets the requirement, whereby the chosen variables correlate and can be merged. Additionally the internal consistency of the questions are tested by means of the Cronbach’s Alpha. A value lower than 0.6 proves there is little similarity between the variables to measure an underlying dimension (Hair et al, 2006). The value of the Cronbach’s Alpha in table 1 shows that the firm innovativeness factor complies with the requirement. The value of the test is an indication of the extent to which a number of questions in a test measures the same concept. Moreover, Ferketich (1991) recommended that corrected item-total correlations should range between .30 and .70 for a good scale. Items that correlate below .30 are not sufficiently related and therefore do not contribute to measurement of the core factor and that items that correlate over .70 are redundant. According to table 1 the chosen variables have met the sufficient criteria. The selected questions of the dependent variable have been combined to a specific concept by means of the calculation of the average.
Table 1: Factor Analysis Innovativeness Contructs
Construct Criterion Factor
loading
Cronbach’s alpha Firm innovativeness - Developed successfully a major new product
line
- Upgraded an existing product line - Introduced new technology that has
substantially changed the way that the main product is produced.
0.775 0.768 0.731
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4.2 Baseline Results
The results in table 2 show no significant curvilinear relationship between a manager’s age and the firm innovativeness. Moreover, the extremely low R2 indicates that the model explains none of the variability of the response data around its mean. Whereby hypothesis 1 and 2 are not confirmed. Table 2:The Effects on Firm Innovativeness
Dependent variable: innovativeness Age group -.014 (.034) -.042 (.032) .003 (.033) -.024 (.032) Age group2 .004 (.008) .007 (.007) -.001 (.007) .002 (.007)
Country dummy No No Yes Yes
Industry dummy No Yes No Yes
R2 .000 .083*** .046*** .132***
Notes: Standard errors are robust standard errors that are clustered at the level indicated in the table.*, ** and *** denotes statistical significance at the 10%, 5% and 1% level.
As seen in table 2, in none of the regressed models age has a significant curvilinear relationship with firm innovativeness. The model becomes significant when culture and industry are taken into consideration. However, the coefficients of age remain insignificant which again confirms the rejection of hypothesis 1 and 2. It seems that national culture and industry have a direct significant impact on the innovativeness of firms.
Hypothesis 3 states the industry impacts the degree of firm innovativeness. Table 2 shows that entering an industry dummy in the model results in a significant model (p<.01). The industry explains around 8.3% of the firm innovativeness, whereby hypothesis 3 is confirmed. Table 11 in the appendix shows the coefficients of the industry dummies. Moreover, as hypothesis 4 states the industrial characteristics might influence the inflection point of the inverted U-shaped relationship of the managers’ age and their firm’s innovativeness. In table 4 the coefficients of the curvilinear relationship per industry are estimated. None of the considered industries seems to have a curvilinear relationship or being significantly influenced by the manager’s age. Only construction and whole estate are proven to be significantly influenced by age (p<.10).
Table 3: Effect Innovativeness on Inflection Point Dependent variable: inflection point
Industry
Mean innovativeness -7.126** (2.905)
17 The estimated inflection points of the industries in the fourth row in table 4 are varying. This variation could be explained by the fact that some industries are characterized by a higher rate of innovativeness, which proves to have a significant impact on the inflection point (see table 3). Thus, hypothesis 4 is confirmed. For example, a 10% decrease of the industry innovativeness would decrease the inflection point with .713. The degree of innovation within an industry negatively influences the point of inflection. This implies the decline in managerial effectiveness is at an earlier stage of life if the industry is characterized by a high level of innovation. Figure 2 graphically shows this downward sloping trend.
Table 4: Industry Effects on Curvilinear Relationship
Notes: Standard errors are robust standard errors that are clustered at the level indicated in the table.*, ** and *** denotes statistical significance at the 10%, 5% and 1% level. The estimated inflection points in this table are rounded numbers from a precisely calculated number in excel.
Figure 2: Effect Mean Innovativeness Industry on Inflection Point
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 In fle ctio n p o in t Mean innovativeness Dependent: innovativeness Mining and quarrying
18 Furthermore, table 2 shows that the country dummy has a significant impact on the firm innovativeness. National culture explains around 4.6% of the firm innovativeness, which confirms hypothesis 5. National culture does affect the degree of firms innovativeness. Hypothesis 6 states that national culture affects the U-shaped relationship of the manager’s age and the firm’s innovativeness. Again, the curvilinear relationship of the complete sample remains insignificant. The estimated coefficients and main results of the selected countries can be found in table 10 in the appendix. Regarding Hofstede’s values regarding power distance, uncertainty avoidance, individualism and masculinity there are 14 different countries, of which 10 show a significant result of the curvilinear relationship. However, only for Croatia, Estonia and Slovakia both coefficients were significant. The fact that there does exist a curvilinear relationship in some countries partially confirms hypothesis 1 and 2. In some countries the manager’s age has an inverted U-shaped relationship with their firms’ innovativeness, whereby an inflection point of the increase of managers’ age on the firms’ innovativeness declines exists. This result poses a question for further research: why is the curvilinear effect of age on firm innovativeness in some countries significant while it is insignificant in others? The fact that the significance of the U-shaped relationship differs among countries may be a results of the cultural characteristics. Table 5 summarizes the effects the Hofstede’s cultural dimension on the inflection point. Only indulgence shows to significantly affect the inflection point (p<.10).
Table 5: The Effects of Hofstede's Dimensions on the Inflection Point
Dependent = Inflection point
Uncertainty avoidance
Individualism Masculinity Power distance Long-term orientation Indulgence S.E. -.125 (.109) .118 (.084) -.072 (.055) -.088 (.075) .047 (.071) -.158 (.088) R2 .099 .142 .123 .104 .021 .144*
Notes: Standard errors are robust standard errors that are clustered at the level indicated in the table.*, ** and *** denotes statistical significance at the 10%, 5% and 1% level.
19 Figure 3: Effect of Cultural Indulgence on Inflection Point
Notes: Meaning of the abbreviations can be found in table 10 of the appendices
4.3 Robustness and Extensions
As shown in table 6 R&D obviously generates innovations (p<.01), however the coefficients of age are still not significant and the extreme low R2 suggests the R&D expenditure is not an influential factor regarding this sample. Furthermore, the age coefficients remain insignificant when entering the R&D dummy.
Table 6: The Effect of R&D Dummy
Dependent variable: Innovativeness Age -.014 (.034) -.054 (.055) Age2 .004 (.008) .013 (.012) R&D Dummy - .004*** (.001) R2 .000 .009***
Notes: Standard errors are robust standard errors that are clustered at the level indicated in the table.*, ** and *** denotes statistical significance at the 10%, 5% and 1% level. R&D dummy is the dummy variable equal to one if the firm reports positive research and development spending and zero otherwise
The used variables for determining innovativeness might differ regarding improvements. Upgrading an existing product line refers towards a more incremental innovation, while developing a new product line or technology is more radical. The relation between the manager’s age and firm innovativeness might differ among the types of innovation. However, table 7 shows that the results remain insignificant. Whereby we cannot draw conclusions regarding this issue.
20 Table 7: Independent Measures of Innovation
Dependent variable New product New technology Upgraded product R&D Age -.014 (.044) .021 (.041) -.056 (.045) .652 (1.151) Age2 .001 (.010) -.001 (.009) .012 (.010) -.216 (.254) R2 .000 .001 .000 .001
There may be other drivers of the inflection point which may be age-related, and which therefore bias the estimated age–performance profiles if omitted. The median age within a country may determine the point of inflection. Median age is the age that divides a population into two numerically equal groups - that is, half the people are younger than this age and half are older. The countries’ corresponding mean age can be found in table 10 of the appendix and are retrieved from the World Factbook. As we see in table 8 and figure 4, the median age of the country significantly influences the inflection point (p<.10). The effect of manager’s age may be eliminated by accounting for the median age within a country, which would be interesting for further research. The higher the median age within a country, the higher the point of inflection. Moreover, the fact that the inflection point are varying could also be explained by the degree of innovativeness within a country. However, there is no significant pattern found. Figure 5 shows there exists no graphical pattern between the mean innovativeness of a country and the corresponding inflection point.
Table 8: Effect Omitted Variables on Inflection Point Country
Notes: Standard errors are robust standard errors that are clustered at the level indicated in the table.*, ** and *** denotes statistical significance at the 10%, 5% and 1% level.
21 Figure 4:Effect of Median Age on Inflection Point
22
5 Discussion and Conclusion
Firstly, the used research method and models in this study are examined. The potential strengths and weaknesses are noted and consequently followed by recommendation for future research. Following, the results of the study are discussed and are recommendation made for the management of organization.
5.2 Discussion and recommendations
23 The survey evidence produced by BEEPS is very insightful for cross-country studies, but their data is limited. Country coverage of the BEEPS survey is limited to Europe and Central Asia, whereby the generalizability towards countries outside the sample is restricted. Thus, the study is not representative for the rest of the world. However, the innovation processes seem to differ between developing and developed countries. These important differences in the underlying institutional infrastructures of developing and developed market affect managers’ strategic orientations.
Furthermore, this study is limited by making use of Hofstede’s cultural dimensions. Firstly, according to DiMaggio (1997) culture is fragmented across group and national lines, which assumes a domestic population is heterogeneous. Hofstede’s analysis is therefore constrained by the character of the individual being assessed; the outcomes have a possibility of arbitrariness (Jones, 2007). However, national identities are the only means we have of identifying and measuring cultural differences. Secondly, Hofstede’s research is based on an ethnocentric pattern, which also represent one timeframe. Finally, not all sample countries were measured by Hofstede, whereby observation are lost. In order to obtain a more comprehensive view of cultural characteristics GLOBE can be used to establish the relationship between culture and leadership behaviour.
To obtain a sufficient age variation this investigation did not focus on one industry or country, which would also benefit the generalizability. However, the definition of innovation depends on the industry allowing differing interpretations of the actual meaning of the concepts used to measure innovation (Patterson, 2002). In order to draw concise conclusions about specific industries it is recommended to allow future research within one certain environment, to ensure the differences between respondents are minimized. There also exists a personal limitation. As a result of the lack of time and resources it was impossible to conduct a proper in-depth research. Further scientific research about the influence of environmental characteristics on the relationship between the manager’s age and their firm’s innovativeness is certainly worthwhile. Perhaps the combination of different personal characteristics could be further examined. For example, educational influences can widen the range of this most ideal age for the best possible managerial effectiveness, whereby organizations can prevent wasting talent and experience.
5.3 Conclusion and Managerial Implications
24 lower the inflection point (see figure 2). This can be explained by the fact that the pressure on managers in highly innovative industries is more intense due to increased market demand, with increased chances of being replaced. A high degree of innovation may be related to time pressure and information overload, which influences the manager’s performance (Andrews & Farris, 1972). If a manager is unable to process the information, the performance of the manager will decline. It is known that younger people learn more easily, whereby they are able to react quicker to a new situation (Vlassaks, 2014). Moreover, according to Kanfer & Ackerman (2004) younger adults are more resilient in the face of relatively high level of continued effort in comparison to senior adults. The receptivity decreases when age increases and elderly should therefore be expected to be less active and less responsive. The need for anticipating quickly to the changing preferences of consumers ensures managers need to respond accordingly. Managers are indeed affect by the industry in which they operate. Thus, the replacement of a senior manager for a younger manager in a highly innovative environment would be advisable.
25 are more likely to show respect for superiors and therefore is associated with a more favorable view on aging (Ahmed et al, 2009). Therefore, the inflection point of indulgent countries would be lower. Furthermore, when the environment is lacking innovative capacity, shareholders benefit from hiring a more selfish (i.e., more profit maximizing) leader whose style is more autocratic (Rotemberg & Saloner, 1993). Thus, highly indulgent countries would benefit from more autocratic leaders.
26
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32
Appendices
Table 9: Distribution Industries
Industry Frequency Percentage
Mining and quarrying 78 1.2
Construction 808 12.1
Manufacturing 1685 25.3
Transport storage and communication
524 7.9
Wholesale, retail, repairs 2027 30.4
Real estate, renting and business services
675 10.1
Hotels and restaurants 457 6.9
Other 413 6.2
Table 10: Coefficients Countries
Country Age Age2 R2 Inflection
33 Notes: The estimated inflection points in this table are rounded numbers from a precisely calculated number in excel
34 Table 11: Coefficients Industry Dummies
Dependent variable: Innovativeness
B Std. Error (Constant) .340 .035 Age -.042 .032 Age2 .007 .007 Mining .115*** .041 Construction .080*** .015 Manufacturing .275*** .012 Transport .086*** .018 Realestate .052*** .016 Hotels .018 .019 Other .107*** .019
Table 12: Coefficients country dummies
Dependent variable: Innovativeness
