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Original Article Managerial risk preference and its influencing factors: analysis of large state-owned enterprises management personnel in China Yingyu Zhanga,*, Hui Luana, Wei Shaoa and Yingjun Xub a School of Management, Qufu Normal University, No. 80 Yantai Road, Rizhao 276826, Shandong, China. E-mail: [email protected] b Research Center for Food Safety Governance Policy, Qufu Normal University, No. 80 Yantai Road, Rizhao 276826, Shandong, China. *Corresponding author. Abstract Using the managerial risk preference scale, the managerial risk preferences of 308 state-owned enterprises (SOEs) management personnel in China are investigated. The results show that older management personnel are more risk averse. Management personnel who have higher positions are more risk averse. The highest degree of risk pursuit across different industries is management personnel in the agriculture industry followed by manufacturing, energy, transportation, trade, and construction. No significant differences were observed in the managerial risk preference distribution of management personnel with respect to gender, and level of education. Risk Management (2016). doi:10.1057/s41283-016-0001-9 Keywords: managerial risk preference; managerial risk preference scale; influencing factors; China; state-owned enterprise management personnel Introduction S tate-owned enterprises (SOEs) are an important component of China’s economy. Reforms over the last 3 decades have divided China’s SOEs into two groups: those supervised by local governments, and those supervised by the central government (Li et al, 2015). In ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management www.palgrave.com/journals Vol. 18, 2–3, 135–158 Zhang et al. March 2003, the State-Owned Assets Supervision and Administration Commission (SASAC) was established as a shareholder representative of the central government in order to better manage central enterprises (Sam, 2013). Subsequently, local governments also set up asset supervision and administrative institutions to manage local SOEs. In general, SOEs supervised by local or central government are large entities in key industries such as national security and national economic lifelines. These industries are the basis of healthy development for the entire country. SOEs under the supervision of central government contribute approximately 10% of GDP. From 2003 until the end of 2013, the assets of central enterprises rose from RMB 7.13 trillion to RMB 35 trillion. Operating revenue rose from RMB 3.36 trillion to RMB 24.4 trillion. Profit increased from RMB 240.5 billion to RMB 1.3 trillion.1 SOEs usually play more important roles in developing countries than in developed countries (Andrew and Smith, 2001). However, in mainstream economics, empirical evidence shows that SOEs, rather than correcting market failures (Xu and Gui, 2016), generally yield negative results (Andrew and Smith, 2001). From 2001 to 2011, China’s economy had an average annual growth rate of 10.4%, while from 2012 to 2015, the growth rates were 7.7, 7.7, 7.3, and 6.9%, respectively.2 This is the ‘‘new normal,’’ and China’s economy no longer sees double-digit growth (Huang, 2014; Jin, 2015; Li, 2015; Wang, 2014). Under the ‘‘new normal’’ economic background, there are many difficulties and challenges for China’s SOEs. In 2014, the total profit of national state-owned and state holding enterprises (excluding financial enterprises) showed slowed growth, increasing only by 3.4%. The losses of large SOEs have become disastrous, and the deteriorating trend is increasingly disquieting (Wang, 2015). In 2015, the total revenue of national SOEs was RMB 45.47 trillion, down by 5.4%; total profit was RMB 2.3 trillion, down by 6.7%.3 Investigations showed that a large number of ‘‘zombie firms’’ comprise large SOEs, typified by discontinuation, semi-cut, continued loss, insolvency, and operations maintained by relying on government subsidies and bank credit (Yang, 2016). Managing risk is fundamental in today’s dynamic, uncertain environment (Gordon et al, 2009). Companies use enterprise risk management (ERM) to assess, control, and monitor risks to increase organizations’ short- and longterm values, and it is important for an effective corporate governance system (COSO, 2004). Since the 1990s, more and more companies are moving from traditional risk management, which managed different corporate risks individually, toward ERM, which takes an integrated view of corporate risks (Beasley et al, 2005; Hoyt and Liebenberg, 2010; Nocco and Stulz, 2006; Mikes, 2005, 2008). Effective risk management is viewed as a crucial competitive advantage that determines the success of an enterprise in an uncertain environment (Bartram, 2000; Beasley et al, 2005). In September 2004, the Committee of Sponsoring Organizations of the Treadway Commission (COSO) issued Enterprise Risk Management – Integrated 136 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Framework, to provide a model framework for ERM. In July 2006, SASAC issued Central Enterprise Risk Management Guidelines (hereinafter referred to as Guidelines), which served as the prelude to central enterprise risk management (ERM). The Guidelines were favorably received by central enterprises, and ERM gained the attention of SOEs (Zhang, 2009; Zhang and Li, 2009). Decision making constitutes the start of all human economic behavior (Liu, 2008). Any model attempting to explain the behavior of the decision maker has a basic element: risk preference, which has significant impact on outcomes in saving, migration, technology adoption, and risk-taking (Brown and Pol, 2015; Chuang and Schechter, 2015; Wang, 2005). Empirical evidence suggests that risk preference varies considerably among individuals (Barsky et al, 2010), and a number of studies have researched methods of predicting it. One approach to theoretical development is through understanding the consistency of risky decision making (Blais and Weber, 2006; Weber et al, 2002). Despite increased focus on the importance of risk in decision making, empirical studies on enterprise managerial risk preference – the attitude of enterprise management personnel toward risk management, risky decision making, and facing enterprise risks – remain limited (Slovic et al, 1982; Vlek and Stallen, 1980; Zhang, 2009). Until the 1980s, this problem was explored only in its theoretical aspects. A large number of studies found that the traits of management personnel, such as risk aversion, lack of patience, and optimism, were significantly related to business-associated decision making (Graham et al, 2013; Lv, 2014; Zhang et al, 2016). One of the basic premises of effective ERM is to establish an appropriate risk preference for individuals and firms. For firms, risk preference refers to the amount of risk generally accepted while pursuing value. Risk preference is the overall risk impact that firms will undertake to realize strategic goals. Thus, risk preference directly reflects the operations of an enterprise. Risk preference differs among enterprises as well as individuals. The 2008 global financial crisis was partially caused by failures and weaknesses of corporate governance, and in many cases, risk management systems, rather than traditional risk management techniques (Feng, 2010; Isaksson and Kirkpatrick, 2009). Managerial risk preference also differs among management personnel. The risk preference of management personnel directly influences the effect of various risk-based decisions, as well as the effectiveness and process of ERM. With the current economic development of China, determining the risk preference and contributing factors of management personnel in large SOEs has gained considerable attention from regulators, stakeholders, management personnel, and researchers. The management personnel of large SOEs in China have a dual identity. On one hand, they are enterprise staff members; on the other hand, they are ‘‘government officials.’’ This paper examines the risk preference of large SOE ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 137 Zhang et al. management personnel when they face enterprise risk-based decisions. Using the managerial risk preference scale, the managerial risk preferences of 308 large SOE management personnel in China are investigated. The paper focuses on two main issues: (1) will China SOE management personnel present features characteristic of enterprise staff, government officials, or both? For various reasons, the studies of domestic and foreign scholars will not be referenced regarding this question, so this work will initiate a new discussion. (2) what factors affect the managerial risk preference of China’s SOE management personnel, including personal characteristics and organizational characteristics. Literature Review and Hypotheses Gender and risk preference Gender is one of the factors that have gained the attention of researchers. A large number of psychology and behavioral science studies have shown that women were more cautious during uncertainty. Byrnes et al (1999) conducted a literature review on 150 studies on risk preference from 1967 to 1997. These studies involved more than 100,000 people, and the results showed, in general, that men pursued more risks than women. Based on an analysis of 50 studies, Arch (1993) also found that women were more risk averse than men. Eckel and Grossman (2008) pointed out that although women were more risk averse than men, the results of the laboratory experiment were ambiguous. According to Hambrick and Chen (1996), the gender composition of the senior management is one of the most important factors that influence organizational risk preference from the angle of gender difference in risk aversion. Zhu et al (2012) conducted an empirical study that considered investment level and long-term loan as indicators of risk aversion, and discovered that companies with a high proportion of female directors demonstrated a rapid decline in investment level during a crisis. These companies also tended to reduce long-term borrowing. Cheng and Zhao (2014) revealed that an increase in the number of female supervisors in Chinese listed financial institutions would not result in an improvement in organizational risk preference, whereas the increase in the number of female directors could improve the risk preference level of the organization. Therefore, the following hypothesis is proposed. Hypothesis 1: 138 Female management personnel are more risk averse than male management personnel (H1). ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Age and risk preference Lauriola and Levin (2001) used an experimental method to compare the riskbased decisions of three age groups (21–40, 41–60, 61–80 years old), and found that under the condition of income, the group with younger members was more willing to take risks than the other age groups; however, under the condition of loss, the adventurous feature of the younger group (21–40 years) was lower than that of the other two groups. Gardner and Steinberg (2005) conducted a questionnaire survey on the risk preference of people in three different age stages, namely, puberty (13–16 years), youth (18–22 years), and adult (24+ years). The results indicated that the younger the individual, the lesser the risk taking and risky decision making. The influence of the same age group on adolescent and young people in risky decision making was larger than on adults. Hambrick and Mason (1984), Bantel and Jackson (1989), Barker and Mueller (2002), Chen et al (2010) believed that the age of management personnel affected their attitudes toward risks because young management personnel possess more recent education and are better acquainted with modern and advanced technologies than older management personnel. Thus, young management personnel are more capable of learning and integrating all kinds of information. They are also more confident and tend to choose riskier strategies when called to exercise their decision making because their financial and career securities are not related to the recent situation of the enterprise, but to its longterm status. Therefore, the following hypothesis is proposed. Hypothesis 2: Older management personnel are more risk averse than younger management personnel (H2). Position and risk preference Regarding the influence of position on risk preference, scholars have concluded that, in general, management personnel with higher positions had more propensity toward risk taking than personnel holding lower positions (Fishburn and Kochenberger, 1979; Dan and Crum, 1980; MacCrimmon and Wehrung, 1986; Li and Xu, 1996). Graham et al (2013, 2015) also found that CEOs were more optimistic than general management personnel, and that companies with optimistic management personnel had higher leverage. Western management scholars widely believed that one of the most common psychological characteristics of entrepreneurs is high ambiguity (risk) tolerance because the physical capital of entrepreneurs usually account for only a small proportion, and they have more reasons to take more risks (Zhu and Li, 2000). March and Shapira (1987) found that middle management personnel tended to believe that the difference in risk preference would disappear when they are promoted to a higher position, whereas top management personnel ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 139 Zhang et al. stated the necessity of educating new office management personnel to help them understand the importance of taking risks. Therefore, the following hypothesis is proposed. Hypothesis 3: Lower position management personnel are more risk averse than higher position management personnel (H3). Education and risk preference The influence of professional experience and level of education of management personnel on their decision-making process have been discussed over the last 25 years (Barker and Mueller, 2002). The discussion focused on whether the preference of management personnel in decision making reflected their training. Different study fields have different purposes and methods that facilitate management personnel to adapt and strengthen their training to collect and interpret information. Many studies have also shown that management personnel make different decisions because of different levels of education, and better education resulted in better strategic decisions that would benefit the company. Thus, the company would enjoy profit and growth (Tihanyi et al, 2000; Bosma et al, 2004). Jianakoplos and Bernasek (1998) showed that level of education was closely related to risk preference, and that the lower the level of education, the higher the degree of risk aversion. By contrast, Blais and Weber (2006) investigated the risk preference of 359 British and French individuals, and found no significant difference in the distribution of risk preference among different education levels. Wang and Zhou (2013) used a sample of listed companies in Shanghai and Shenzhen stock exchanges from 2003 to 2012, and determined that the correlation between education level and risk preference of top decision makers was significant and negative. Corporations managed by more highly educated decision makers were found to have lower earnings volatility and asset-liability ratio as well as higher risk management and tolerance capacity. Therefore, the following hypothesis is proposed. Hypothesis 4: Lower education management personnel are more risk averse than higher education management personnel (H4). Industries and risk preference Different industries have different characteristics. For example, some industries are technology intensive, while some industries are capital intensive; some industries are mainly concentrated in the domestic market, while some industries are focused on foreign market. Scholars have relatively little research on risk preference in different industries. Dan and Crum (1980) found that industry has a significant effect on risk preference, and that the management 140 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors personnel of airline companies pursued the most risks, followed by personnel from the food chain, construction, and chemical industries, whereas a bank’s manager was the most risk averse. Levy (1994) found that the degree of risk aversion of management personnel in food, steel, and real-estate industries displayed an increasing trend. John et al (2004) study showed that the relationship between corporate risk-taking behaviors and industry growth rate was statistically significant. Therefore, the following hypothesis is proposed. Hypothesis 5: Management personnel of different industries will demonstrate different levels of risk preference (H5). Method Procedure and samples This part of study successively conducted two large-scale surveys with the help of SASAC. One is from June to August in 2010 in 231 large SOEs in 30 provinces, municipalities, and autonomous regions; the other one is in July 2010 in 37 Beijing SOEs. It is necessary to specially emphasize that a series of questionnaires used in this study are supported by SASAC and local SASAC, thus ensuring the credibility of the questionnaire. Table 1 provides the relative information of the respondents. For these two investigations, 500 questionnaires were issued, among which 359 were recycled and 308 were valid. The recovery rate was 71.80%, and the effective rate was 61.60%. Measures Management personnel will inevitably meet and deal with risks in the process of operation management. Obviously, their attitude toward risks will also differ. Previous studies have pointed out that the attitude of enterprise management personnel toward industrial risks differed from that of individual risks. Studies on enterprise managerial risk preference should not simply continue to use the traditional risk preference research method. Therefore, this research employed the concept of risk preference and used managerial risk preference to replace the traditional risk preference. Dan and Crum (1980), McKenna and Yong (1986), and Grambo (1978) referred to risk preference as managerial risk preference. Smith (2004) referred to it as corporate risk attitude, whereas David and Ruth (2008) referred to it as corporate risk attitude and organization risk attitude. The literature did not provide a clear and systematic definition of managerial risk preference. Using relevant theories and concepts, this paper defines managerial risk preference as the behavior of managerial personnel in the risk management process and the decisions they make toward the risks confronting their companies. ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 141 Zhang et al. Table 1: Managerial risk preference respondent situation Project Amout Percentage (%) Remarks Gender Male 205 75.93 38 valid questionnaires with item on gender not filled out Age Fmale Total 40 65 270 135 24.07 100.00 47.37 [40 Total Junior college and under Undergraduate Master or above Senior 150 285 25 52.63 100.00 8.31 161 115 89 75.93 38.20 30.07 121 37 49 296 72 40.88 12.50 16.55 100.00 24.41 110 38 45 37.29 12.88 15.25 30 10.17 295 100.00 Education Position Yearly operating Income of Enterprise Department head Office head General manager Total Under RMB 1 billion RMB 1–5 billion RMB 5–10 billion RMB 10–20 billion RMB 20 billion and above Total 23 valid questionnaires with item on age not filled out, Average age was 40.01 years old 7 valid questionnaires with item on gender not filled out 12 valid questionnaires with item on gender not filled out 12 valid questionnaires with item on gender not filled out From the traditional microeconomic theory perspective, the measurement and characterization of risk preference became controversial because the assumption of risk preference was too simple. Studies on managerial risk preference cannot utilize the same research method used to investigate risk preference in individual decision making. Therefore, we used the managerial risk preference scale of Zhang (2009) to investigate and measure the managerial risk preference. Empirical validation results showed that the scale had good content validity and structure validity. This scale has 5 dimensions and 16 items. Table 2 lists the items included in each dimension. Results In this paper, managerial risk preference is divided into two types: individual managerial risk preference, which refers to the preference level of management personnel toward certain risk; and overall risk preference, which refers to the overall response of management personnel toward the overall industrial risks. 142 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Table 2: Item and information on managerial risk preference scale Dimension Indicator Entry information Strategic risk Merger risk Risk of personnel placement, non-performing assets, and cultural conflict because of merger andacquisition Going out to face the risk of politics, economics, and society of the host country Risk of negative effects of changes in national industries and fiscal policy on companies Risk of external environment, technical level, and tight money. Risk of enterprise assets safety because of associated business, guaranty, and entrusted financing Risk of failure to fulfill the payment obligation or promise to pay because of the financial gap Risk of fluctuating corporate profitability ‘‘Go out’’ national risk National policy risk Financial risk Major projects investment risk Asset security risk Liquidity risk Market risk Operational risk Legal risk Yield fluctuation risk Account receivable risk Customer demand risk Remit interest rate risk Supplier product quality risk Information system risk Major natural disaster risk Environmental risk Contract law risk Financial report compliance risk Risk of companies cannot recycle all kinds of accounts in time Risk of company products that cannot satisfy the market need, which is increasingly personalized and customized Risk of turmoil in international financial structure, market interest rate, and exchange rate fluctuation Risk of quality problems of company product because of the quality of supplier products Risk of inaccurate and leaked information as well as attacks from hackers and viruses Risk due to major natural disasters (such as typhoons, earthquakes, and floods) Risk from various environment problems arising from the enterprise production process Risk of business contract legal disputes in enterprise production and operation process Risk of financial report without compliance Reliability test In practice, the most commonly used method to test the reliability is Cronbach’s coefficient technique. In general, Cronbach’s coefficient above 0.7 can be considered the scale with higher reliability. The scale score in each item converts to scoring matrix, obtaining the total score variance of all items, and the sum of the correlations between each item then calculates the Cronbach’s coefficient of each item (results shown in Table 3). The Cronbach’s coefficients of all items range between 0.85 and 0.92, which indicates managerial risk reference scale with a satisfactory reliability. ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 143 Zhang et al. Table 3: Cronbach’s coefficient Item Cronbach’s Merger risk ‘‘Go out’’ national risk National policy risk Major projects investment risk Asset security risk Liquidity risk Yield fluctuation risk Account receivable risk Customer demand risk Remit interest rate risk Supplier product quality risk Information system risk Major natural disaster risk Environmental risk Contract law risk Financial report compliance risk 0.8740 0.8713 0.8674 0.8833 0.9139 0.8770 0.8849 0.8904 0.8974 0.8862 0.8890 0.9148 0.9066 0.9024 0.9209 0.9089 Validity test Scholars have proposed a variety of methods to test the validity of scale. In this paper, the content validity and construct validity were tested. Content validity refers to whether or not the design items represent the content or subject matter to be measured. Content validity tests are often used in the methods of logical analysis and statistical analysis. In general, logical analysis is used by the developer to judge whether the entry ‘‘looks’’ consistent with the purpose and requirements of measurement. Statistical analysis is mainly used for the relationship analysis between single item and all items to obtain the test results. First, the data were normalized; then, using SPSS, the Spearson coefficients between single item and all items were calculated (results in Table 4). Statistical analysis shows that, in 16 items, there are significant correlations between the score of each item and the total score at 0.01 level, which indicates that the scale possesses a satisfactory content validity. The managerial risk preference scale has five dimensions: the dimension of strategic risk preference, the dimension of financial risk preference, the dimension of market risk preference, the dimension of operational risk preference, and the dimension of legal risk preference , which are characterized by 16 items. According to this idea, the scale can be visually presented as structural equation modeling (SEM). By SEM operation, free parameter estimates and model evaluation index values can be obtained, which can test the rationality of the hypothetical model. Maximum likelihood estimation method is used to estimate the free parameters. The results are shown in Table 5 and Figure 1. Taken together, the findings indicate the scale with a satisfactory construct validity. 144 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Table 4: Spearson coefficient Item Spearson coefficient Merger risk ‘‘Go out’’ national risk National policy risk Major projects investment risk Asset security risk Liquidity risk Yield fluctuation risk Account receivable risk Customer demand risk Remit interest rate risk Supplier product quality risk Information system risk Major natural disaster risk Environmental risk Contract law risk Financial report compliance risk 0.240* 0.363** 0.367** 0.478** 0.306** 0.482** 0.530** 0.309** 0.395** 0.363** 0.463** 0.459** 0.160* 0.405** 0.365** 0.450** * P \ 0.05. ** P \ 0.01. Table 5: Fit indices of the managerial risk reference scale v2 v2/df NFI CFI IFI GFI AGFI RMSEA 437.30 4.70 0.74 0.92 0.94 0.96 0.94 0.026 Gender, education, and managerial risk preference No obvious differences were observed in the Mann-Whitney U test, distribution of all individual risk preferences, all kinds of managerial risk preferences, and overall managerial risk preference of different genders (specific data omitted), implying that gender was not an influencing factor of managerial risk preference. In this study, level of education was divided into three categories, namely, college degree and under, undergraduate, and graduate and above. No obvious difference was found in the results of the KruskalWallis test on individual risk preference, all kinds of managerial risk preferences, and overall managerial risk preference of management personnel with different educational levels except for contract law risk preference, which had 0.01 significant differences (specific data omitted). Therefore, no obvious difference was found in the distribution of the managerial risk preference of management personnel with different levels of education. In taking all the results together, H1 and H4 are not supported. ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 145 Zhang et al. Figure 1: Free parameter estimation. Age and managerial risk preference The age of respondents was divided into two age groups ( 40, [40 years). The result of Kruskal-Wallis test revealed an obvious difference of 0.01 in the distribution of the merger risk preference, significant investment risk preference, customer demand change risk preference, supplier product quality risk preference, and financial reporting compliance risk preference; an obvious difference of 0.05 was found between the distribution of the yield fluctuation risk and asset security risk preferences (see Table 6), whereas no obvious difference was found in the other individual managerial risk preference distribution (specific data omitted). Further study revealed that one of the characteristics of the different items, management risk aversion, showed an increasing trend as age increased. The result of the Kruskal-Wallis test on the distribution of the overall managerial risk preference of management personnel at different age groups showed an obvious difference. Figure 2 provides the average of the overall managerial risk preference of management personnel of different age groups. Management personnel who belong to 40-year-old age group tend to manifest more risk pursuit than[40-year-old 146 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Table 6: Individual managerial risk preference related to age Item Merger and acquisition risk preference Customer demand change risk preference Supplier product quality risk preference Financial reporting compliance risk preference Major investment risk preference Yield fluctuation risk preference Asset security risk preferences B40 [40 Asymp. Sig. 2.7968 2.1578 2.5397 1.4363 2.3783 2.2513 1.8062 2.4921 1.9434 2.1593 1.2807 2.0773 2.0566 1.6819 0.007** 0.001** 0.000** 0.001** 0.006** 0.040** 0.044** * P \ 0.05. ** P \ 0.01. 60 56.15 50 45.55 Score 40 30 20 10 0 ≤40 >40 Years Figure 2: The overall management of risk preference of different age groups. group risks. The overall risk pursuit of management personnel was on a declining curve as age increased, and older people were more risk averse than younger ones. In taking all the results together, H2 is supported. Position and managerial risk preference The positions of the respondents in this study were divided into four types: general manager, head of the office, department head, and senior executives. The results of the Kruskal-Wallis test on the distribution of investment risk preference of management personnel of different positions revealed an obvious difference at 0.01 significance in all single managerial risk preference distributions, whereas asset-safety risk preference, information-system risk preference, and environmental risk preference had an obvious difference at 0.05 significance (as shown in Table 7), implying that the position of management personnel in the company was a factor that would influence some individual managerial risk preferences. ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 147 Zhang et al. Table 7: Individual managerial risk preference related to position Item Asset security risk preferences Information system risk preference Environmental risk preference Investment risk preference Senior executive Office Department General Asymp. Sig. 1.6629 1.2921 1.7025 1.4545 1.8378 1.4865 1.8980 1.4082 0.032* 0.044* 1.7303 2.0337 1.7521 2.3140 1.9730 2.2432 1.8776 2.4490 0.045* 0.005** * P \ 0.05. ** P \ 0.01. The result of Kruskal-Wallis test on the distribution of the overall management of risk preference of management personnel with different positions revealed an obvious difference at 0.05 significance. Figure 3 compares the average overall management of risk preference of management personnel with different positions. General management personnel pursued the most risks, followed by office and department heads. Senior management personnel were the most risk averse, indicating that overall level of risk pursuit tended to decrease as the position became higher, and thus management personnel in higher positions were more risk averse than those in lower positions. In taking all the results together, H3 is not supported. Industries and managerial risk preference We selected six industries including construction, transportation, energy, agriculture, trade, and manufacturing, which had more samples. The result of the Kruskal-Wallis test on the distribution of remitted interest rate risk of management personnel from different industries revealed an obvious difference at 0.01 significance among all distributions of individual managerial risk preference. The venturing-out national risk preference had an obvious difference at 0.05 significance, although no obvious relations were found among customer demand change risk preference, contract law risk preference, yield fluctuation risk preference, and supplier managerial risk preference. The value was also generally small, indicating that individual risk preference of management from different industries had some differences (see Table 8). The results indicated that industry is a factor that influences some individual managerial risk preferences. The result of the Kruskal-Wallis test on the distribution of the overall management of risk preference of management personnel from different industries revealed an obvious difference at 0.05. Figure 4 compares the average of overall management risks of different industries. Agriculture had the highest level of risk pursuit, followed by manufacturing, energy, transportation, trade, and construction. In taking all the results together, H5 is supported. 148 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Figure 3: The overall managerial risk preference of different positions. Discussion and conclusions In studies of risk preference in decision making, gender difference has always been an important factor. A considerable number of studies on gender differences in risk preference have been conducted (Byrnes et al, 1999; Arch, 1993; Eckel and Grossman, 2008). One general conclusion is that men tended to display greater tendency toward risk pursuit compared with their women counterparts. No obvious differences in managerial risk preference of management personnel between genders was observed because both men and women industrial management personnel were adventurous in operation decision making (Li and Xu, 1996). However, gender could also, to some extent, predict the risk propensity of an individual (Xie, 2003). The results of the analysis show that the understanding of management personnel toward enterprise risk problem depends on their external environment and their own practical experience. A high level of education may give rise to differences in the understanding of management personnel on some issues (such as contract law risk preference). Overall, education level would not have a significant effect on managerial risk preference. Our statistical analysis results were consistent with the conclusion of Gardner and Steinberg (2005) who stated that risk-taking behavior would decrease along with age. The differences in the risk preference of the various age groups could be attributed to the varying mental abilities of the age groups (Steinberg and Cauffman, 2010). Young people would take more risks because they can be easily influenced by similar risk propensities of their peers (Zimring, 1998). In addition to the above explanations, we also believe that the cognitive level toward various industrial risks of management personnel from different age groups varied because of the differences in social and management experiences. The difference in risk cognitive level would cause ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 149 150 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management ** P \ 0.01. * P \ 0.05. Customer demand change risk Risk of ‘‘venturing out’’ Remitted interest rate risk Contract law risk Yield fluctuation risk Supplier product quality risk Customer demand change risk Individual managerial risk preference 2.0000 2.0000 1.9375 1.6875 1.8125 2.2500 2.0000 Construction 2.1667 2.6111 1.4444 1.7222 2.1111 2.0556 2.1667 Transportation 2.2273 2.2727 1.4545 1.8182 2.0000 2.4091 2.2273 Energy Table 8: Individual managerial risk preference related to industries and Asymp. Sig 2.4375 2.5625 2.0000 1.8750 2.4375 2.6875 2.4375 Husbandry 1.8636 2.4091 1.5909 1.8636 1.9545 2.2727 1.8636 Trade 2.1667 2.6667 1.7778 2.1111 2.2778 2.5556 2.1667 Manufacturing 0.058 0.020* 0.009** 0.084 0.091 0.083 0.058 Asymp. Sig. Zhang et al. Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors Figure 4: The overall managerial risk preference of different industries. management personnel from different age groups to form diverse judgments regarding the risk level in the same risks. Moreover, this kind of difference may be attributed to personality traits. Personality is associated with different risk-based decisions, and young people are more extroverts in nature and more liberal than older people, and thus, they are more prone to taking more risks. Previous results of studies on the risk preference of management personnel with different positions indicated that management personnel with higher positions had higher risk pursuit levels (Li and Xu, 1996; Xie, 2000). The explanation of this result in Xie (2000) is that when the power is in the range of prescribed, decision-making risk is relatively small; while the power is beyond the prescribed scope, the decision-making risk is relatively large. In order to avoid excessive risk, the managers of lower position take decisions in their relatively small power range, with relatively strong risk aversion. We believe that this explanation has its rationality, but cannot be used for the interpretation of our results. The ‘‘abnormal’’ phenomenon of managerial risk preference of management personnel of China’s large SOEs can be explained from two aspects. Chinese traditional thought is based on the ‘‘Official Standard.’’ Enterprise management officials and entrepreneurs of Chinese state-owned businesses differ significantly. Although both types of management personnel engage in management work under the framework of principal-agent, entrepreneurs allocate resources and provide innovative combination, whereas management officials of SOEs are the owners of the enterprise or main management cadres appointed by the ruling party. At present, senior management in state-owned business in most provinces and cities manage the business according to standards set by the administrative level. Chinese traditional thought on Official Standard, on the one hand, has enabled industrial officials of all levels ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 151 Zhang et al. to maintain a low-key style and sound approach to decision making, particularly in making decisions at various levels of risks. On the other hand, officials with lower positions would attempt various methods to earn promotions. Although all kinds of risky decision-making problems would bring considerable risks, these problems also offer opportunities. Thus, officials in lower positions would take more risks in decision making. Results of the risk income differences. In the compensation system series of current SOEs, the compensation for senior management is based on the performance assessment of the state-owned assets regulatory institution at the corresponding level, and deputies take a free rider on the principal that is multiplied by a fixed coefficient based on the total salary of principals. The salary of industrial officials can be described as cap-on-top and guarantee-atthe-bottom, whereas the salary of other management personnel is decided internally based on performance level (Zhang, 2013). Therefore, the risk motivation of the enterprise in general and middle management personnel to some extent would be higher than senior executives. In their view, the undertaking of some risks would bring more benefits, including a rise in position and fame, as well as an improvement in their internal status, among others. We draw the following conclusions based on the risk preference scale and our investigation on the managerial risk preferences of management personnel of large state-owned enterprise in China. A difference exists among the distribution of the managerial risk preference of management personnel of different age, positions, and industries. The results of our statistical analysis indicated that age, position, and industry are the factors that influence managerial risk preference. As management personnel of large SOEs grew older, their level of risk pursuit decreased, and older management personnel became more risk averse than their younger counterparts. As the position of management personnel became higher, their level of risk pursuit decreased. Management personnel with higher positions were more risk averse than their younger counterparts. In the six industries analyzed in this study, the overall management of risk preference in the agriculture, manufacturing, energy, transportation, commerce, and construction industries tended to exhibit an increasing trend toward risk aversion. The managerial risk preferences of management personnel of different genders, education level, and firm scale had no significant differences. Gender and level of education do not influence managerial risk preference. However, firm scale should be analyzed further because only large-scale firms were included in this study. In 1957, the Mean-Variance Model was proposed by Markowitz. Since then, a number of mathematical finance experts from developed economies has sought to measure and manage risk using quantitative statistical techniques, excessive superstition, and exaggerated features of mathematical 152 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors models, and, ultimately, risk management has been led astray. Blind trust and overreliance on these models contributed to Wall Street’s confused means and goals, leading to a loss of rationality in the process of pursuing rationality (Liu, 2009). In the 2008 global financial crisis, with many well-known international financial institutions being pushed to a state of distress or even bankruptcy, the fundamental lesson was that risk preference had undergone significant ‘‘deviation.’’ In the face of immediate interests and market temptation, risk preference had become radical (Zhang, 2009). Although risk management failed in the global financial crisis, the importance of risk management remains. The basic principle of Samuelson’s Revealed Preference Theory is that consumer purchase behavior under certain price conditions exposes his/her inherent preferences. Thus, purchasing behavior can be used to derive consumers’ preference, which is not logical thinking based on ‘‘preference (utility function)-select,’’ but the opposite, namely, ‘‘select-preference.’’ Managerial risk preference is based on logical ‘‘select preference’’ thinking combined with risk management or risky decision-making behavior, under certain conditions, to derive managerial risk preference. Therefore, managerial risk preference is a revealed preference. In expected utility theory, the body of risk preference is ‘‘economic man,’’ whose rationality is the basic assumption, and whose individual risk preferences are determined through utility function. The body of managerial risk preference is based on ‘‘administrative man,’’ whose basic assumption is bounded rationality, and whose managerial risk preference is determined through exhibited behavior in the process of management and risky decision making. The meaning of ‘‘economic man’’ and ‘‘administrative man’’ are fundamentally different: ‘‘economic man’’ considers man to be completely rational, makes choice that maximize his/her own interests; ‘‘administrative man,’’ due to scarcity of resources, does not meet rational requirements, and chooses the principle of satisfaction to replace the principle of optimal self-utility. Based on expected utility theory, the research objective of risk preference is to determine risky behavior in the individual decision-making process using lottery method; while the research objective of managerial risk preference is risky behavior in a company’s decision-making process. Individual decision making can be regarded as a single objective whose purpose is to satisfy a single requirement: personal utility maximization. Company decision making is a multiobjective or multiattribute decision-making problem, which determines that managers consider not only personal gain, but other targets, such as national interests, social interests, corporate interests, and so on, when making business decisions. Managers are not isolated individuals, and their behavior is influenced by internal and external factors. Managerial decision making needs to adapt risk management objectives, making a greater contribution to the survival and development of the enterprise, and deriving greater benefit from ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 153 Zhang et al. it. Enterprise risk management objectives are adjusted according to changes in the environment, which is a dynamic process. Similarly, the managerial risk preference is adjusted, with adaptive features. A basic premise of effective risk management is to establish an appropriate risk preference, including individuals and organizations. Risk preference affects the risk management process at every stage (David and Ruth, 2008), including start-up, risk identification, risk assessment, risk analysis, and risk response. For example, in the risk identification stage, risk-averse managers express more pessimism than risk-seeking managers facing the same risk. Risk-averse managers identify many risks, including risks otherwise considered small, unworthy of attention, or uncertain fuzzy events, ignoring opportunities; while risk-seeking managers usually do not focus on threats, even treating them as ‘‘normal business activity,’’ with a tendency to downplay risk. At present, ERM is used in China’s large SOEs. The study of managerial risk preference and its influencing factors has positive implications. Through horizontal or vertical comparison of the managerial risk preferences among members of enterprises, decision makers can ‘‘intervene’’ in the managerial risk preference of individuals and groups according to the enterprises risk management objectives, and optimize managerial risk preference through micro-regulation and scientific management, therefore guaranteeing the achievement of ERM objectives. In addition, managerial risk preference plays an important role in human resource management (HRM) activities. In recruitment and selection, candidates with appropriate managerial risk preference may be selected. For example, when a company is in the start-up period, a moderate risk-seeking candidate should be considered for general manager. In contrast, risk-averse managers may be more appropriate for financial management positions. Limitations of this study Several methodological limitations of the present study should be acknowledged. One limitation of the research is that the method is too simple. Lottery method is a common method to research the individual risk preference. Individual risk preference can be viewed as the degree of risk aversion in the face of personal decision problem. Managerial risk preference can be viewed as the degree of risk aversion in the face of enterprise decision problem. Obviously, in the processing of personal decision and enterprise decision, management personnel will show different degrees of risk aversion. The method of individual risk preference can not be directly applied to the study of the managerial risk preference. But so far, we have not found one good tool for measuring managerial risk preference. The Managerial Risk Preference Scale (Zhang and Li, 2009) is relatively a too simple tool. In addition, the reliability and validity of the scale also need large-scale test. 154 ª 2016 Macmillan Publishers Ltd. 1460-3799 Risk Management Vol. 18, 2–3, 135–158 Managerial risk preference and its influencing factors The research results highlighted the existence of an obvious difference among the managerial risk preferences of management personnel from different industries. As for individual managerial risk preference, a large manufacturing firm generally encounters international problems, and thus pursues a higher level of national risk of ‘‘venturing out.’’ However, we cannot provide a convincing explanation for the difference in the overall management of risk preference. This question can be investigated in future studies. Acknowledgments This work was supported by Major project of the National Social Science Foundation of China (Project ID: 14ZDA069), National Natural Science Foundation of China (Project ID: 11426143, 11501320, 71203122), Humanities and Social Sciences in Colleges and Universities of Anhui provincial key projects (Project ID: SK2013A040), and Natural Science Foundation of Shandong Province, China (Project ID: ZR2013GL002, ZR2014AP008). We sincerely thank anonymous reviewers who help in improving this paper. Notes 1 http://www.sasac.gov.cn/n86302/index.html. 2 http://www.stats.gov.cn/tjsj/ndsj/2015/indexch.htm. 3 http://www.money.163.com/16/0126/08/BE8978KP00253B0H.html. References Andrew, D. and Smith, C. (2001) State-owned enterprises in less developed countries: Privatization and alterbative reform strategies. European Journal of law and Economics, 12: 217–252. Arch, E. (1993). Risk taking: A motivational basis for sex differences. Psychological Reports, 73(3): 6–11. 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