Relationship between Age of Senior Management and Corporate Performance - Research Paper Example

Relationship between Age of Senior Management and Corporate Performance Student Name: Student ID: Lecturer: Date: Executive Summary In the contemporary business environment, modern businesses are complicated. There is a variety of competing factors and organizations that can effectively use the available information and make good use of the cognitive abilities of their human resources can ensure their success in performance. This paper provides an analysis and evaluation of the current relationship between age of senior management and corporate performance.The method of analysis includes regression of age and performance. Performance is determined through the profit/asset ratio and age from the respective companies.The computational tool used in this study is the SPSS. All the analysis tables can be found in the appendix section. Results of data analysis show that there is a positive relationship between the age of senior management and corporate performance. This report finds that a higher age of the senior management would not have significant impact on performance as would be expected from the literature review.One of the study assumptions is that the final decision maker is the senior management. The recommendations discussed include: employing younger persons with who will easily embrace technological advancements and changes.The report also investigates the fact that the analysis conducted has limitations. One of the limitations include that the data submitted may not be very clearly true since some companies supply data to take care of their desired need. Table of Contents Executive Summary 2 Introduction 1 Background 1 Hypothesis 2 Literature Review 2 Upper Level Research and Executive Age 2 Decrement theory of aging and compensation 3 Age diversity and age discrimination climate 5 Methodology 5 Data collection and sampling criterion 5 Data analysis 6 Results and Analysis 6 Descriptive statistics 6 Linear regressionfor age and performance 6 Scatter graph 7 Conclusion 7 Discussion and Recommendations 8 Limitations 8 Assumptions 8 Recommendations 8 Appendix 9 References 10 Introduction Background In the contemporary business environment, modern businesses are complicated. There is a variety of competing factors and organizations that can effectively use the available information and make good use of the cognitive abilities of their human resources can ensure their success in performance. Amongst the factors include, but limited to innovativeness, creativity and critical thinking in services dispensation (Mollick, 2012, p. 1001-1015). One of the factors that affect the performance of any corporate business is age of senior management (Nielsen & Nielsen, 2013, p.373-382).The age of senior management positively affects the performance of a company because working experience helps them better manage a company. The aim of this study is to establish the link between the age of senior management and performance of a firm. Due to reduced number of younger workforce especially in Europe and Scandinavian countries, older generation continues to experience the demographic shift (Qian, Cao & Takeuchi, 2013, p.110-120). The workers are bound to stay in the workforce longer because losing them to retirement will leave a large knowledge gap in the firms (PANDE, 2015, p.88-93). Older senior management is rich in implicit knowledge, social networks and mentoring abilities. On the other hand, younger management teams are able to quickly adapt to new changes, acquire new knowledge and adapt to new environment (Son, Fuller, Muriithi, Walters & Kroll, 2015 p.9-27). With technological advancement in the last decade, younger managers have been crucial in implementation of relevant technology in companies. Most empirical research has focused on age of senior managementalongside/ a combined effect with other managerial characteristics. Research on age versus performance spreads across various disciplines. Economists study the effects of aging on old-age social security, wages or value of human capital (Wei & Chen, 2009, p.443-456). Psychology focuses on cognitive performance of older generations. Sociology lays emphasis on demographics of aging and the ability of social institutions to cope with a large population of older people. Previous research suggests that job intricacies moderate the relationship between age of senior management and corporate performance, in that the relationship is more positive for professionals in comparison with nonprofessionals (Wei & Chen, 2009, p.443-456). Williams (2016, p.346-373) Suggests a profession classification in accordance with how age moderates performance. These researches will find out that the age of senior management positively related to the company performance. Younger managers have less experience but more new ideas. Older people have more experience and established networks. Over time, their capabilities have become sharper. Therefore, when senior management is older the performance increases. With the conclusion around age being that it is a complex issue, this study seeks to test for age as stated in the hypothesis below. Hypothesis There are two hypotheses to be tested in this study: the first, Null hypothesis is to test whether there exists a relationship between age of senior management and corporate performance. The second hypothesis to test is whether the coefficient of age is statistically significant. Literature Review Upper Level Research and Executive Age A 1984 publication (Senior management teams, 1998 p. 37) suggested a model in which senior managers play a vital role in shaping major corporate performance. The assumption was that demographic characteristics of senior management surrogates cognitions values, beliefs and perceptions of top managers. This in turn influence the strategies made to the overall outcomes. Upper Echelons focused on the entire top management as opposed to the chief executive officers and individual managers. The study stated that a company’s’ performance is a reflection of its top management (Abatecola, Mandarelli&Poggesi, 2013 p. 1073-1100). This study had far-reaching implications going beyond management to reshaping perspective in psychology. Earlier research shows this perspective used in US, international organizations, business, and corporate strategy arenas. An executive age affects company out comes. Younger managers pursue riskier strategies. They also experience greater growth and variability in performance (Bévort&Poulfelt, 2015). Younger managers are also more ready to give out higher salaries to executives (Cass, 2015 p. 1). In summation, Upper Echelons research provides a theoretical background in linking the effect of age senior management to corporate performance. This section describes various factors that contribute to a curvilinear relationship between age of top management and performance. Decrement theory of aging and compensation Decrement theory of aging and compensation mechanism state that increased age causes deterioration in cognitive abilities but the cognitive deficit is compensated by gains in other abilities such as knowledge, strategy and networks(Birkinshaw&Ridderstråle, 2015 p. 44-57). Thus unless the gains in knowledge and experience in older management members surpasses the mental capabilities then the firm is likely to perform poorly. Aging also affects motivation. Aging workers go through a resignation stage where they take in what is available to them and reduce their expectations (Chang, 2015 p. 79-101). Increased age also causes decline in performance of complex tasks. Particularly in tasks that result in heavy demand on resources which have reduced capacity (Chang, 2015 p. 79-101). Decreasing flexibility, greater rigidity and resistance to change are among the disadvantageous characteristics associated with older age (Daspit, Ramachandran& D'Souza, 2014 p. 219-239). Older senior management are risk averse and exhibit a preference for career security compared to the younger managers. Older managers are also less willing to take to new ideologies and trends (Chang, 2015 p. 79-101). Continuity theory of aging suggests that age may have a double effect on managerial output. Older people demonstrate that their activities and relationships tend to be highly interdependent and take on highly established forms thus resulting in reduced willingness to taken on highly changing environments (Deng, H., Moshirian, Pham &Zein, 2013 p.1781-1811). Older executives have knowledge that is tacit and implicit and is embedded in their memory and the knowledge of the professional environment is found in the networks of contacts. In terms of substitution, the more cognitive ability one loses, the more one seeks to make it up by gaining the package of knowledge experience and wisdom (Weel, 2011). Younger managers rely more on their raw ability while older manager rely more on accumulated wealth of experience in decisionmaking. It is important, though, to note that in specific jobs, detrimental effects on aging of top management are not likely to experience the effects overtime during the same time (Gentry &Shen, 2013 p.121-130). The nature of competition in technology companies illuminates a different approach with regard to age of management and performance. Illustratively, organizations that adopt to use advanced technology, prefer to recruit experienced young managers because they are more up to date. These companies rely on constant innovation a premise of younger generation. Still, younger managers are recently out of school and their knowledge is more contemporary compared to older people. It is thus important to note that in these companies young age is positively related to high performance. Technology sector tends to rely more on innovation, equipment plant as opposed to social skills and strategy a premise of the older people. It is therefore believed that the curvilinear association must come out as short of context among the organizations that use technology than those whose managers are older. It is because of this that brings out an increase within organizations that do not adopt high technology. Younger executives have greater energy and more incentive to work for the would like to mark their place in society. Older directors prefer to retain the level of their organizations within the most appropriate financial position (). Previous studies also show that old age of senior management has a negative relationship with how organizations formulate internationalization strategies. Despite such a focus, we find that no one specific study that tries to focus its research into factors that influences organizations to conducts internationalization strategy in reference to age and performance (Grima, 2011, p.1312-1332). Younger managers are therefore attracted to international business environments that are more complex and challenging. Hutzschenreuter, & Horstkotte, (2013, p. 704-726) show industries that have the potential to expand to new environments attract younger managers who are risk takers. Local industries may attract older people as directors. Different aspects found in an industry or a market helps to offer the motivation for managers to adopt varying changes in their strategies. For instance, organizations that operate among a highly concentrated industry have a likelihood of recording increased market shares as well as increased returns than those that operate in low concentrated industries. A centralized industry setting with formal rules and bureaucracy is unattractive to younger innovative minds but certainly comfortable for older people. Thus, industry concentration will positively affect the performance of firms within for high concentration will attract older mangers while less concentration will attract younger managers. In conclusion, many industry factors play a role in determining company performance in relation to age of the top management. Depending on the context of the firm, it is likely to attract managers of different age groups. High- technology, informal and international companies associate young age with high performance. Centralized industries that are local and hierarchical tend to prefer older people as part of the management. Age diversity and age discrimination climate According to Kotha, Zheng & George (2011, p.1011-1024), age discrimination is broad and directed at both the older and younger managers. It is based on the organizational climate on fairness and unfairness and other behaviors, actions towards different age groups. Within the workplace age similarity leads to more liking and better communication within groups and departments within an organization. An organization with people of the same age is more likely to work better and communicate compared to an age diverse organization. This is a contribution of stereotypes associated with different ages. These affect positively and/or negatively the performance and productivity of the company. Methodology Data collection and sampling criterion The main data of focus for the companies was the performance data/index and the age of senior management for that particular period. The population sample included 100 large and stock listed companies. For reliability, the companies included those in the United Kingdom, United States of America and Germany as ranked by market capitalization at year 2014.The countries were so selected because they are known to have differential age of senior management. Companies falling within the European Union of small and medium sized companies were portfolio investors and were fully integrated subsidiaries of separately listed parent company were excluded. These criteria excluded companies that are not operative, have limited ability, and have very small actual business (Pande, 2015). The performance of the companies was obtained from all the stock markets where they traded. There several ways employed in obtaining the age of senior management. The Annual reports as at 2014, official company websites, third party archival databases, press releases and newspaper articles are some of the methods for secondary data collection that the study used (Yayavaram& Chen, 2015). Having exhausted secondary methodology, primary data was obtained by email to all the companies for comparison and data cross validation. Having identified all the information, any company whose age showed inconsistency was eliminated. One other inclusion and exclusion criterion for age sifting was the number of years senior management has been in place. Only those senior managers who have been in place for over 3 years were selected with the highest priority. Recent appointments were excluded from the study. This is because performance is time-lagged with managerial efficiency. Otherfactors that were considered in this respect were based on the fact that one manager taking over might be so good such that they may be good performers who are recovering a company from a bad status (Williams, 2016). This left about 70 companies from the population. This study considered having a sample size of only 30 companies. As a result, a sample of 30 companies were randomly selected was prepared for study. This random selection followed a systematic criterion of 10 companies from each of the three countries. Data analysis The main objective of the paper is to establish a relationship between age and performance. The most appropriate way to do this is to run a regression analysis. The R squared is also necessary in determining the amount of performance accounted for age.A graphical representation of the relationship using a fitted scatter diagram gives a better diagrammatic representation of the relationship. In this analysis, the dependent variable was performance and the independent age. Analyzing this size of data required a computing tool. The most appropriate tool that could give the desired results as outlined above was determined to be the statistical package for social sciences (SPSS)(Ats.ucla.edu, 2016). Results and Analysis Descriptive statistics The descriptive statistics are as shown in the appendix section Table-1. From the given data, the average age of managers is 52 years with an average performance of 7.59% returns on assets Linear regressionfor age and performance Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .016a .000 -.035 7.28100% a. Predictors: (Constant), Age of senior management 2014 Years The model summary indicates that using this data, there is no relationship between the age of senior management and corporate performance. However, the standardized form, which would apply on some other sample, shows a negative relationship between age and corporate performance. Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 8.219 7.454 1.103 .280 Age of senior management 2014 Years -.012 .141 -.016 -.085 .933 a. Dependent Variable: ROA 2014 There is no significant relationship between age of senior management and the corporate performance (p>0.05). Scatter graph Thescatter graph is in the appendix section af figure-1. It shows a near horizontal line around 52 years of age as average age for senior management of the sample study. This graph just confirms the results of the regression table. Conclusion The age of senior management has a significant influence on corporate performance. This study applies in a highly bureaucratic public organization. On a general principle, increased age would signify a better performance of a given corporation as would be expected from the reviewed literature. When the results of this sample are extended elsewhere, it would show a negative relationship. Discussion and Recommendations The study sample shows results that do not agree with the reviewed literature. In fact, by 2000, age would account for near 24% of corporate performance (Milana and Maldaona, 2015). However, between then and the current periods, the impact of age on performance has been reducing such that this study reveals that there is no relationship. A standardized result shows that generally, increasing age would reduce the corporate performance.The coefficient for age as a factor of performance is not significant. This implies that the null hypothesis for the coefficient of age as 0 is true.These results could possibly imply that in the near future, age of senior management will be negatively correlate with corporate performance. If to just mention, in the most recent times, the major managerial characteristic of senior management that favours performance is education of the management and the ability of management to embrace the technological dynamisms. This comes with technological and changing market trends (Chang, 2015).This results look more realistic compared to some of the recent ones based on the facts of age and technology acceptability as far as senior management is concerned. The younger managers are more ready to embrace and switch to new technology compared to the older ones. Technology has shown its peak of dynamism in the recent times and more especially in the said countries of study(Chang, 2015). Limitations 1. The study focused on countries which are highly affected by technology and therefore the impact of age may not come out sufficiently. Assumptions The main assumption is that the information provided by the corporations is very true Recommendations 1. Based on the results of this study, it is highly recommended to the corporations to avoid age discrimination on the basis of impact on performance since there’s no relationship between age and performance. At least not at the current situation. 2. Researchers are highly advised to consider researching on other managerial characteristics as affects performance. Appendix Table-1: Descriptive Statistics N Minimum Maximum Mean Std. Deviation ROA 2014 30 -8.40% 33.94% 7.5927% 7.15529% Age of senior management 2014 Years 30 27 77 52.10 9.604 Valid N (listwise) 30 Regression Results Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Age of senior management 2014 Yearsb . Enter a. Dependent Variable: ROA 2014 b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .016a .000 -.035 7.28100% a. Predictors: (Constant), Age of senior management 2014 Years ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression .387 1 .387 .007 .933b Residual 1484.361 28 53.013 Total 1484.748 29 a. Dependent Variable: ROA 2014 b. Predictors: (Constant), Age of senior management 2014 Years Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 8.219 7.454 1.103 .280 Age of senior management 2014 Years -.012 .141 -.016 -.085 .933 Figure-1:Scatter graph showing the relationship between age and corporate performance References Abatecola, G., Mandarelli, G., &Poggesi, S. (2013). The personality factor: how top management teams make decisions. A literature review.Journal Of Management & Governance, 17(4), 1073-1100. Bévort, F., &Poulfelt, F. (2015).Human Resource Management in Professional Services Firms: Too good to be true? Transcending conflicting institutional logics Birkinshaw, J., &Ridderstråle, J. (2015).Adhocracy for an agile age.Mckinsey Quarterly, (4), 44-57. Cass, M. (2015). Meet Your 19-Year-Old Portfolio Managers: AM CheatSheet. Money Management Letter, 1. Chang, Y. (2015). 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