enterprise risk management and firm performance

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Combining resource-based theory (RBT) of the firm and Donabedian theory, a conceptual framework is developed. The model and hypotheses were assessed ...
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МАТЕМАТИЧНІ МЕТОДИ, МОДЕЛІ ТА ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ В ЕКОНОМІЦІ

Omar Masood1, Bora Aktan2, Kiran Javaria3

ENTERPRISE RISK MANAGEMENT AND FIRM PERFORMANCE: EVIDENCE FROM MALAYSIAN LISTED FIRMS This study examines the mediating roles of enterprise risk management on firm resources – firm performance relationship. Relationships among firm resources, enterprise risk management (ERM) and firm performance are yet to be comprehensively explored, particularly for the corporate sector of Malaysia. The main goal of this study is to fill this gap. Combining resource-based theory (RBT) of the firm and Donabedian theory, a conceptual framework is developed. The model and hypotheses were assessed using the partial least squares technique. The findings indicate that intangible resources are positively and significantly related to firm performance through ERM as the mediator. On the contrary, ERM do not mediate the relationship among tangible resources, capabilities and firm performance. It indicates that efficient allocation of intangible resources is crucial for better performance. Keywords: enterprise risk management; tangible and intangible resources; Bursa Malaysia. Peer-reviewed, approved and placed: 15.01.2017.

Омар Масуд, Бора Актан, Кіран Джаварія

СИСТЕМА УПРАВЛІННЯ РИЗИКАМИ ПІДПРИЄМСТВА ТА ЕФЕКТИВНІСТЬ ЙОГО РОБОТИ: ЗА ДАНИМИ КОМПАНІЙ, ЩО КОТУЮТЬСЯ НА ФОНДОВІЙ БІРЖІ МАЛАЙЗІЇ У статті описано посередницьку роль управління ризиками підприємства в системі «ресурси підприємства – ефективність роботи». На прикладі корпоративного сектору Малайзії описано, яким чином співвідносяться ресурси підприємства, його система управління ризиками та ефективність роботи. Для цього використано ресурсну теорію фірми в комбінації з теорією Донабедіана. Модель та гіпотези протестовано за допомогою методу найменших квадратів. Доведено, що нематеріальні активи суттєво впливають на ефективність роботи, при цьому система управління ризиками є фактором посередницького впливу. Однак, при цьому ця система не чинить жодного впливу на матеріальні активи. Таким чином доведено, що ефективне використання саме нематеріальних активів є життєво важливими для ефективності роботи компанії. Ключові слова: система управління ризиками підприємства; матеріальні та нематеріальні ресурси; фондова біржа Малайзії. Рис. 1. Табл. 4. Літ. 28.

Омар Масуд, Бора Актан, Киран Джавария

СИСТЕМА УПРАВЛЕНИЯ РИСКАМИ ПРЕДПРИЯТИЯ И ЭФФЕКТИВНОСТЬ ЕГО РАБОТЫ: ПО ДАННЫМ КОМПАНИЙ, КОТИРУЮЩИХСЯ НА ФОНДОВОЙ БИРЖЕ МАЛАЙЗИИ В статье описана посредническая роль управления рисками предприятия в системе «ресурсы предприятия – эффективность работы». На примере корпоративного сектора Малайзии описано, каким образом соотносятся ресурсы предприятия, его система управления рисками и эффективность работы. Для этого использована ресурсная теория фирмы в комбинации с теорией Донабедиана. Модель и гипотезы протестированы при помощи метода наименьших квадратов. Доказано, что нематериальные активы существенно влияют на эффективность работы, при этом система управления рисками 1 Quaid-i-Azam School of Management Sciences, Quaid-i-Azam University, Islamabad, Pakistan. 2 3

Corresponding author; College of Business Administration, University of Bahrain, Kingdom of Bahrain; Future University in Egypt, New Cairo, Egypt. Quaid-i-Azam School of Management Sciences, Quaid-i-Azam University, Islamabad, Pakistan.

© Omar Masood, Bora Aktan, Kiran Javaria, 2017

МАТЕМАТИЧНІ МЕТОДИ, МОДЕЛІ ТА ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ В ЕКОНОМІЦІ

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является фактором посреднического влияния. Однако, при этом данная система не оказывает никакого влияния на материальные активы. Таким образом доказано, что эффективное использование именно нематериальных активов является жизненно важным для эффективности работы компании. Ключевые слова: система управления рисками предприятия; материальные и нематериальные ресурсы; фондовая биржа Малайзии.

Introduction. Risk and Insurance Management Society (2008) emphasized that recognizing potential dangers at an early stage and introducing effective measures in good time require systematic capabilities within organizations as the economic environment is regularly confronted with financial crises such as the currency crises of Europe in 1992–1993, Mexico in 1994–1995, Russia and Asia in 1997–1998, Argentina in 2001–2002 and the most recent global financial crisis of 2008–2009. Nurturing of a strong risk-resistant culture within an organization is crucial to ensure that the corporate sector is not repeatedly facing vulnerability to contagion risks and spill-over effects. As such, priorities and vigilance are necessary to ensure all potential risks are taken into consideration and comprehensive risk management measures are adopted (Aziz, 2011). Any mistake in identifying risks could have a rigorous fiscal impact on organizations like what happened during the financial crisis of 1997 where Tenaga National Berhad (TNB) and Malaysian Airline System (MAS) suffered major losses mainly due to their failure to manage various risks linked (Yazid, 2001). Many researchers (e.g., Beasley et al., 2005, 2006) widely recognized the critical role of enterprise risk management (ERM) as a new paradigm for managing the portfolio of risks. As ERM practices are on the rise, not all organizations are adopting it, especially in Malaysia (Daud and Yazid, 2009). The Institute of Risk Management (IRM) (2002) defined risk as the combination of probability of an event and its consequences, with risk management being concerned with both positive and negative aspects. Numerous types of risks such as hazard risks, financial risks, strategic risks and many more exists and emerge from time to time within firms posing significant threat to reputation, profitability and also firm effectiveness (Committee of Sponsoring Organization of Tread way Commission, 2004). J. Lam (2000) on the other hand, emphasized that risk may exist from daily business operations, therefore, firms need to integrate all possible risks in a systematic manner, hence, ERM helps firms manage them better. Motivation behind this research is that the effects of firm resources on firm performance have been widely studied. However, research investigating combinations of firm resources and ERM towards firm performance is limited and still only on the surface (Rahman et al., 2013). The review of literature indicates the majorities of past studies on ERM were conducted mostly in developed countries such as the US and the UK, while they are still lacking for developing countries like Malaysia. Hence, this study intends to explore the impact of resources on the ERM process as a mediator for firm performance and focuses on the impact of ERM practice on firm performance based on the relationship partially adopted from Donabedian (Structure Process Outcome) model and resource-based view theory (RBV) thus contributing to the rather limited literature available (Daud and Yazid, 2009). The paper is divided into four sections. Section 2 reviews the literature presenting theoretical background together with the relationship between different tangible ACTUAL PROBLEMS OF ECONOMICS #7(193), 2017

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and intangible resources with firm performance. Additionally, risk management strategies are analyzed for organizations. Section 3 demonstrates the method whereas Section 4 provides analysis and findings. Section 5 concludes with short recommendations and practical implications. Literature review. 1. Theoretical background. This study develops the concept established by RBV theory and Donabedian model (DM) with the expressed purpose of attempting to unite the current body of cross-discipline studies between risk and strategic management into a more comprehensive model. A. Donabedian (1988) emphasized that assessment of an outcome can be understood by closely scrutinizing the structure of the setting in which care is provided by measuring the actual process stated various criteria under each variable concerning structure, process and outcome in quality assessment. He employed only tangible setting and facilities as dimension under its structure construct but our study uses a widely, multidimensional construct of firm resources under RBV. Measuring directly and empirically assessing the state of resources within the sampled firms, this study attempts to show how firm resources in combination with ERM construct may be able to create an improved outcome of firm performance despite various crises that might occur in the near future. The RBV identifies firm as an exclusive package of bundle of distinctive resources and capabilities where the crucial purpose is to manage fully utilized deployment of resources and capabilities in order to maximize value, while developing firm's stronger basis of resources deployment for the future. 2. Influence of firm resources on performance. According to many resource-based studies, performance is ultimately dependent on the unique assets owned and controlled by the firm whereby the line of reasoning is that there are differences in firm profitability stemming from acquisition and deployment of valuable firm resources (Caloghirou et al., 2004). A. Mcgahan and M. Porter (1997) argued that RBV supports that firm performance most influence unique organizational processes such as ERM. A central premise in the resource-based perspective holds that firm resources and capabilities can form the basis for competitive advantage through organizational processes and leads to positive performance (Barney, 1991; Peteraf, 1993). Firms are heterogeneous with respect to their resources and capabilities because they are endowed with unique and idiosyncratic abilities to accumulate, develop, and deploy those assets to formulate and implement value creating strategies (Amit and Schoemaker, 1993; Barney, 1991; Peteraf, 1993). J. Fahy (2002) also tested the impact of resources on low-performing vs. highperforming firms using discriminant analysis. Top-performing firms ascribe significantly higher levels of importance to firm-specific capabilities (intangible resources) than low-performing firms. His study, while generally confirming the theoretical predictions of RBV, also suggested that resources other than intangible ones may be important contributors to firm success. J. Galbreath (2005) studied the importance of intellectual property assets, organizational assets, reputational assets, and capabilities to firm success, relative to tangible assets. Therefore, the current study proposed that firm resources have significant impact on firm performance. H1: Tangible resources have significant relationship with firm performance. H2: Intangible resources have significant relationship with firm performance. АКТУАЛЬНІ ПРОБЛЕМИ ЕКОНОМІКИ №7(193), 2017

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H3: Capabilities have significant relationship with firm performance. 3. Influence of firm resources on ERP (mediator). There are various studies on firm-specific resources and firm-specific risks. It might sound that two different terms being put together within the firm but resources and risks are two items directly and indirectly linked together and have to be aligned to ensure the deployment of resources within a firm to formulate the best of strategies which will lead to superior performance through ERM effectiveness. L.L. Colquitt et al. (1999) provided some evidence that firm-specific characteristics such as industry, size, and background of individual skills and know-how were responsible for risk management affected the utilization of ERM techniques leading to perceived effectiveness. Despite a number of previous studies supporting the relationship between firmspecific and ERM practice, there is also a number of previous literatures that did not come to the same conclusion. For instance, D. Pagach and R. Warr (2010) pointed out that the relation between financial leverage of firm did not have a clear relationship with ERM. On the other hand, their findings concluded that opacity of a firm’s assets especially intangible ones have a positive relationship with ERM. This empirical evidence also supported by M. Woods (2009). L. Paape and R.F. Spekle (2011) similarly emphasized that internal factor of the firm indeed influence the perceived effectiveness of ERM practice which is consistent with (Woods, 2009). Therefore, the current study proposes that firm resources have significant impact on ERM. H4: Tangible resources have significant impact on the perceived effectiveness of ERM. H5: Intangible resources have significant impact on the perceived effectiveness of ERM. H6: Capabilities have significant impact on the perceived effectiveness of ERM. 4. Influence of ERM on firm performance. L.A. Gordon et al. (2009) found that ERM-firm performance relation is indeed contingent on the proper match between ERM and the following 5 variables: environmental uncertainty, industry competition, firm size, firm complexity, and monitoring by the board of directors. L. Pagach and R.F. Warr (2010) showed that the announcement made by a firm on hiring of Chief Risk Officer (CRO) had impact on earnings volatility but indicated negative relationship between ERM and firm performance that might be due mainly to low power test. R.E. Hoyt et al. (2008) further emphasized that the use of ERM has a positive impact on firm value up to 17%. They also found that ERM practice is also positively related to firm size, institutional ownership and internal diversification. S.G. Ashby and S.R. Diacon (1998) stressed that risk appetite embedded within ERM framework also indirectly enhanced organizational performance via improved returns, profits and growth. Therefore, the current study proposes that ERM has significant impact on firm performance. H7: The perceived effectiveness of ERM has a significant relationship with firm performance. H8: The relationship between tangible resources and firm performance will be mediated by the perceived effectiveness of ERM. H9: The relationship between intangible resources and firm performance will be mediated by the perceived effectiveness of ERM. ACTUAL PROBLEMS OF ECONOMICS #7(193), 2017

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H10: The relationship between capabilities and firm performance will be mediated by the perceived effectiveness of ERM. On the bases of the existing literature, models and theories, the following framework is developed (Figure 1) showing the firm resources as independent variables are tangible and Intangible assets together with capabilities. Firm performance is a dependent variable and ERM mediates this relationship. Firm resources Tangible resources Intangible resources Capabilities Independent variables

H4

H8, H9, H10

H5 H6

Enterprise risk management

H7

Firm performance Dependent variable

H1, H2, H3

Figure 1. Hypothesized research model, authors’

Methodology. 1. Statistical tools. Structural equation modeling (SEM) is a statistical technique that simultaneously tests and estimates causal relationships between independent and dependent constructs (Fornell and Wernerfelt, 1987). The basic function of the outer model is to assess the goodness of the measures used in this study through reliability and validity of the constructs. Partial least square (PLS) method was used to examine the hypotheses of this research as it is capable to tackle a set of interrelated questions with one comprehensive method. Two SEM measurement models were used in this study, i.e., reflective and formative measurement. These measurement models are assessed against the following aspects: indicator reliability, internal consistency reliability, convergent validity, and discriminant validity. Reliability analysis shows that all the items were consistent and reliable in nature. All Cronbach’s alpha values was greater than 0.6 thus showing that all the items were reliable. All variables’ skewness and kurtosis values lie between -3 to +3 and -10 to +10 respectively, thus showing that data is normally distributed. All constructs are loaded in their particular construct components, thus, confirming the data validity. There is no common method bias here. 2. Data. This strategy permits large amount of quantitative data to be collected from population, which then can be analyzed using descriptive and inferential statistics (Saunders et al., 2009). Statistical studies were used in the research to verify if firm performance is dependent on such factors as firm resources and ERM relationship. The study used both primary and secondary data. Primary data were collected from the questionnaire survey which was send through emails or personally administered and secondary data were gathered through literature review on the relationship between firm resources and performance. Firms are publicly traded ones listed on Malaysia Bourse. There were 930 firms at the main market whereas 130 in the ACE (standing for Access-Certainty-Efficiency which is the new name for the formerly known Malaysian Exchange of Securities Dealing and Automated Quotation market). 250 firms were selected for the study, and 234 responses were deemed usable for further analysis. Our study employs the use of judgment sampling. Given the selected sample has met the specific criteria, permission was obtained for the survey from the risk management departments of the entities. Two enumerators were appointed to distribute АКТУАЛЬНІ ПРОБЛЕМИ ЕКОНОМІКИ №7(193), 2017

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the questionnaire by hand, via mail and online. Appointed enumerators have got experience of more than 10 years in risk management and are also part of the vicinity of risk management practitioners within the corporate sector. Table 1. Demographic analysis, authors’ Demographics Frequency

Age: Under 30 31–40 41–45 46–50 Over 50 Total Gender : Male Female Total Working experience: Less than 5 years 6–10 years More than 10 years Total Education level: Doctoral Masters’s Bachelor’s Degree/Advanced Diploma Diploma Total Education background: Engineering/Production Finance/Accounting Marketing/Sales Economics/Business Human Resource Management Architecture Science/Technology Others Total

%

34 95 60 39 6 234

14.52 40.59 25.64 16.66 2.56 100

122 112 234

52.1 47.8 100

37 35 162 234

15.81 14.95 69.23 100

16 71 100 47 234

6.83 30.34 42.73 20.08 100

56 38 26 55 8 3 28 20 234

23.93 16.23 11.11 23.50 3.41 1.28 11.96 8.54 100

In the sample, 52% of the respondents were male and 48% female. Most of the respondents belong to the age group of 31–40 years, while their education background was mainly engineering, with 43% having Bachelor’s Degree/Advanced diploma. 69% of the respondents had more than 10 years of work experience. Empirical analysis. Assessment of the significance and relevance of the structural model relationships. Table 2 presents the VIF values and tolerance levels of all the exogenous constructs in the structural model. The results indicate that VIF values are below the recommended threshold value of 3.3 and the tolerance levels are greater than 0.20 indicating there are no significant levels of collinearity among the exogenous constructs (Hair et al. 2014). ACTUAL PROBLEMS OF ECONOMICS #7(193), 2017

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Table 2. Collinearity values among exogenous construct, authors’ Exogenous constructs Endogenous constructs VIF Tolerance TR 1.219 .820 ERM IR 1.145 .874 CAP 1.344 .744 TR 1.226 .815 PERF IR 1.236 .809 CAP 1.353 .739 ERM 1.111 .900

The path coefficient between TR, IR and CAP and ERM is comprised of mixed results, with TR and ERM having b = 0.052 and not significant, with t-value = 0.341. Similarly, the path coefficient between CAP and ERM is not strong, with b = (-0.042) and t-value = 0.437. As a result, H1 and H3 are not supported. However, the path coefficient between IR and ERM is strong with b = 0.358 and t-value = 3.993. As a result, H2 is supported. The path coefficient between TR and PERF is also not significant with has b = (-0.130) and t-value of 1.730. Same apples to path coefficient of CAP and PERF which has b = 0.018 and t-value = 0.251. As a result, H1 and H3 are not supported. However, the path coefficient between IR and PERF is moderate with b = 0.122 and t-value = 1.749. Thus, H2 is supported. Meanwhile, path coefficient of ERM and PERF is influenced directly by the strong value with b = 0.653, t = 15.029, p < 0.01. As a result, H7 is supported. Table 3. Path coefficients, observed t-statistics, and significance level for all hypothesized paths, authors’ Path Standard HYPOTHESIS T-value Results coefficient error CAPABILITIES -> ENTERPRISE Not -0.042 0.097 0.429 RISK MANAGEMENT supported CAPABILITIES -> PERFORMANCE Not 0.018 0.071 0.252 supported ENTERPRISE RISK MANAGEMENT 0.653 0.043 15.029** Supported -> PERFORMANCE INTANGIBLE RESOURCES -> 0.358 0.090 4.001** Supported ENTERPRISE RISK MANAGEMENT INTANGIBLE RESOURCES -> Supported 0.122 0.066 1.864* PERFORMANCE Not TANGIBLE RESOURCES -> 0.052 0.155 0.333 supported ENTERPRISE RISK MANAGEMENT TANGIBLE RESOURCES -> Not -0.130 0.075 1.730 PERFORMANCE supported t-values > 1.645 (p < 0.05); t-values > 2.33 (p < 0.01) (one-tailed test).

Within the structural model, each path connecting two latent variables represents a hypothesis. The analysis conducted on the structural model allows us confirm or disconfirm each hypothesis as well as understand the strength of the relationship between dependent and independent variables. Using the SmartPLS algorithm output, the relationships between independent and dependent variables were examined. However, in SmartPLS in order to test the significant level, t-statistics for all paths are АКТУАЛЬНІ ПРОБЛЕМИ ЕКОНОМІКИ №7(193), 2017

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generated using the SmartPLS bootstrapping function. Based on the t-statistics output, the significant level of each relationship is determined. Table 3 lists down the path coefficients, observed t-statistics, and significance levels for all the hypothesized paths. Using the results of path assessment, the acceptance or rejection of the proposed hypotheses is determined. To validate the proposed hypotheses and the structural model, the path coefficient between two latent variables is assessed. Based on the previous studies, the path coefficient value needs to be at least 0.1 to account for a certain impact within the model (Hair et al., 2011). Assessment of the path coefficient (Table 3) shows that all the proposed hypotheses are supported, except for H1, H3, H4, H6, H8 and H10. From the analysis, the supported hypotheses are significant at least at the level of 0.05, have expected sign directions (i.e., positive) and consist of a path coefficient value (b) ranging from 0.122 to 0.653. The coefficient of determination (R2) value is defined as the "amount of variance in the construct in question that is explained by the model" (Chin, 2010: 674). For this study, the bootstrapping generated 5000 samples from 234 cases. The result of the structural model is presented in Table 4: tangible resources (TR), intangible resources (IR), capabilities (CAP) and ERM are able to explain 47% of the variance in performance (PERF). Meanwhile, TR, IR, and CAP explain 13.4% of the variance in ERM. The f 2 value of 0.097 indicates IR has a small effect in producing R2 for ERM. In contrast, the 0.697 value indicates that ERM has a very large effect in producing R2 for PERF. On the other hand, other exogenous variables like TR and CAP have a very small (almost no) effect in producing R2 for ERM. CAP also has a very small effect in producing R2 for PERF. Similarly, TR and IR also have small scale effects on the R2 of PERF. Table 4. R2 of endogenous latent variable, authors’ Endogenous LV R2 ERM 0.134 PERFORMANCE 0.470

The final assessment addresses the calculation of the q2 effect sizes. 0.058 is the q2 effect size for the predictive relevance of IR on ERM. This 0.058 indicates that IR has a small effect in producing Q2 (predictive relevance) for ERM. 0.001 and 0.002 are the q2 effect size for the predictive relevance of TR and CAP on ERM. 0.001 and 0.002 indicate that TR and CAP have a very small effect in producing the Q2 for ERM. Conclusion. The relationships among firm resources, ERM and firm performance are yet to be comprehensively explored, particularly for the corporate sector of Malaysia. This study has examined what factors in firm’s performance help to perform better by considering the mediating roles of ERM. Drawing upon the combination of resource-based theory (RBT) of the firm and Donabedian theory, a conceptual framework was developed and a quantitative approach is employed to fill the existing gap in literature and to achieve the objectives. Structural equation modelling

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was used in the assessment. The analysis of the relationship among the variables showed that not all the factors had a significant effect on firm performance but intangible resources. The findings indicate that intangible resources are positively and significantly related to firm performance through ERM as the mediator. On the contrary, ERM do not mediate the relationship among tangible resources, capabilities and firm performance. The results prove that ERM does not act as a mediator in tangible resources – firm performance relationship as well as in capabilities – firm performance relationship. Thus, H8 and H10 that ERM acted as mediator in tangible resources – firm performance relationship and capabilities – firm performance relationship is not supported. However, H9 is supported that ERP acts as a mediator in intangible resources – firm performance relationship. It indicates that efficient allocation of intangible resources is crucial for good performance. References: Amlt, R., Schoemaker, P.J.H. (1993). Strategic assets and organizational rent. Strategic Management Journal, 14(1): 33–46 = http://doi.org/10.2307/2486548. Ashby, S.G., Diacon, S.R. (1998). The Corporate Demand for Insurance: A Strategic Perspective. Geneva Papers on Risk and Insurance, 23: 34–51. Aziz, Z.A. (2011). Better Supervision and Better Banking in a Post Crisis Era. BNM Quarterly Bulletin. Barney, J. (1991). The Resource-Based Model of the Firm: Origins, Implications, and Prospects. Journal of Management, 17(1): 97–98 = http://doi.org/0803973233. Beasley, M., Clune, R., Hermanson, D. (2006). The impact of enterprise risk management on the internal audit function (Vol. 8113) // erm.ncsu.edu. Beasley, M.S., Clune, R., Hermanson, D.R. (2005). Enterprise risk management: An empirical analysis of factors associated with the extent of implementation. Journal of Accounting and Public Policy, 24(6): 521–531 = http://doi.org/10.1016/j.jaccpubpol.2005.10.001. Caloghirou, Y., Protogerou, A., Spanos, Y., Papagiannakis, L. (2004). Industry-Versus Firm-specific Effects on Performance. European Management Journal, 22(2): 231–243 = http://doi.org/10.1016/ j.emj.2004.01.017. Chin, W. (2010). How to write up and report PLS analyses. In: Handbook of Partial Least Squares: Concepts, Methods and Application (pp. 645–689). Springer. Colquitt, L.L., Hoyt, R.E., Lee, R.B. (1999). Integrated Risk Management and the Role of the Risk Manager. Risk Management and Insurance Review, 2(3): 43–61 = http://doi.org/10.1111/j.15406296.1999.tb00003.x. Committee of Sponsoring Organization of Treadway Commission (2004). Enterprise risk management-integrated framework. Daud, W., Yazid, A. (2009). A Conceptual Framework for the Adoption of Enterprise Risk Management in Government-Linked Companies. International Review of Business Research, 5(5): 229–238. Donabedian, A. (1988). The quality of care: How can it be assessed? JAMA // jama.jamanetwork.com. Fahy, J. (2002). A resource-based analysis of sustainable competitive advantage in a global environment. International Business Review, 11(1): 57–77 = http://doi.org/10.1016/S0969-5931(01)00047-6. Fornell, C., Wernerfelt, B. (1987). Defensive Marketing Strategy by Customer Complaint Management: A Theoretical Analysis. Journal of Marketing Research, 24(4): 337–346. Galbreath, J. (2005). The intangible economy and firm superior performance: Evidence from Australia. Journal of Management and Organization, 11: 28–40 = http://doi.org/10.5172/ jmo.2005.11.1.28. Gordon, L.A., Loeb, M.P., Tseng, C.Y. (2009). Enterprise risk management and firm performance: A contingency perspective. Journal of Accounting and Public Policy, 28(4): 301–327 = http://doi.org/10.1016/j.jaccpubpol.2009.06.006. Hair jr, J., Sarstedt, M., Hopkins, L., Kuppelwieser, V.G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2): 106–121 = http://doi.org/10.1108/EBR10-2013-0128.

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ACTUAL PROBLEMS OF ECONOMICS #7(193), 2017