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Author: Adolfo Javier Cegarra Acosta

Universidad Nacional Experimental de los Llanos Occidentales Ezequiel Zamora, UNELLEZ

quantum.analitica2@gmail.com

Barinas, Venezuela

 

External Environment and Financial Performance in the Private Health Sector

 

Abstract

The purpose of this study is to analyze the relationship between the external environment and financial performance, in the context of the private healthcare sector in Barinas (Venezuela). A review of the literature and a focus group identified 15 environmental factors that influence this business sector. Subsequently, the presidents of the 25 companies in Barinas were surveyed to measure their perceptions about these environmental factors, in terms of their Dynamism and Munificence dimensions. The results obtained in the survey and the profitability of each company in its last financial year were analyzed with Optimal Scaling procedures. The findings demonstrated the existence of a strong relationship between 12 environmental factors and profitability, in which the external environment is characterized by a great complexity, with low dynamism (low variability / high predictability), in a munificent task environment and an unfavorable general environment.

 

Keywords: strategic planning; profits; medical centres; private enterprises.

 

 

 

Ambiente Externo y Desempeño Financiero en el Sector Privado de la Salud

 

Resumen

El propósito de este estudio es analizar la relación entre el ambiente externo y el desempeño financiero, en el contexto del sector privado de la salud en la ciudad de Barinas (Venezuela). Mediante la revisión de la literatura y un focus group se identificaron 15 factores ambientales que influyen sobre este sector empresarial. Posteriormente, se encuestó a los presidentes de las 25 empresas existentes en Barinas, para medir sus percepciones sobre estos factores ambientales, en cuanto a sus dimensiones de Dinamismo y Munificencia. Los resultados obtenidos en la encuesta y la rentabilidad de cada empresa en su último ejercicio económico, se analizaron con procedimientos de Escalamiento Óptimo. Los hallazgos demostraron la existencia de una fuerte relación entre 12 factores ambientales y la rentabilidad, en el cual el ambiente externo se caracteriza por tener bajo dinamismo (baja variabilidad / alta predictibilidad), en un Entorno de Trabajo munificente y un Entorno General desfavorable.

 

Palabras clave: planificación estratégica; ganancia; centro médico; empresa privada.

 

 

 

1.    Introduction

In Venezuela, the political, economic and social factors of the external environment seem to exert a significant influence on the financial performance of companies in the private health sector, which was evidenced by a negative financial result in some important companies in the state of Barinas. In general, it seems that there is a perception that environmental factors such as the political confrontation between the government and the opposition, the shortage of medicines, equipment and spare parts, high inflation, the increase in personnel costs through presidential decrees, among others, have a very negative effect on the financial indicators of these companies. This perception has its foundation, since political interference and variations in the economic situation have been related to poor organizational performance, even with a perfectly formulated strategy (Njoroge, Ongeti, Kinuu and Kasomi, 2016a). This leads to study the external environment-financial performance relationship, on which there is already a rich theoretical perspective developed since the beginning of the 1980, with abundant empirical demonstrations in developed countries. Despite this, there is a lack of literature in developing countries and, moreover, that provides evidence on how environmental factors that manifest themselves in Venezuela in the financial viability of companies.

 

The influence of the external environment on the performance of companies has been approached theoretically from two perspectives: the first considers that the external environment is a variable that moderates the relationship between the company's strategy and its organizational performance. This approach suggests that, in order to defend their market position and business performance, companies deliberately select strategies in response to their external environments (Balas, Gokus and Colakoglu, 2014).

 

The second perspective treats organizational performance as a dependent variable, and the external environment as one of its independent constructs (Murgor, 2014). This research will be carried out under this perspective, since all the organizations of the private sector of health lack a formal strategy, on the one hand, and on the other, it is necessary to elucidate the true role that environmental factors play in the performance of companies in the sector, and more specifically in financial performance.

 

This study aims to identify the objective environmental factors that influence private health organizations in the context of the city of Barinas (Venezuela), as well as describe the perceptions that exist about these factors among the presidents of these companies for, finally, to correlate these results with the profitability reached by these organizations in their last fiscal year.

 

2. Literature Review

2.1. The External Environment

In the literature there is a broad consensus on the definition of external environment. Academics agree in defining it as a certain combination of factors, outside the limits of the organization that influence the performance of their activities (Krivstov, 2014a). All organizations are open systems (Njoroge et al., 2016b), which are in constant exchange with their environments. The external environment provides companies with inputs that they transform into products through internal processes and then the products are returned to the environment. Organizations can not have control over environmental factors. The environment is a source of restrictions, contingencies, problems and opportunities that affect the terms in which organizations do business.

 

Conversely, there is an extensive disagreement about how the external environment should be evaluated and measured. Some theorists treat the external environment as objective facts independent of the companies while other researchers consider that the external environment is determined by the perceptions of their actors. However, Bourgeois, (cited by Njoroge et al., 2016c), concluded that the question was not whether the measures should be objective or perceptive; rather, he suggested that both objective measures and perceptual measures are real and relevant to an organization's strategy. Moreover, he argues that the difference in conceptual vision between objective measures and perceptual measures does not seem to be distinctive. In this context, many studies found a strong correlation between perceptual and objective assessments of the environment. Taking these points of view into account, it operationalized the external environment in two dimensions: the Objective Environment, formed by external environmental factors; and the Perceived Environment, constituted by the internal perceptions of these environmental factors. In turn, the Target Environment is formed by the General Environment and the Work Environment.

 

For Krivstov (2014b), the General Environment is made up of the common conditions for the functioning of all organizations and, as a general rule, has no peculiar features in relation to any particular company, however, the level of its influence in the different Companies can be different. The General Environment is made up of political, legal, economic, technological, social and environmental factors.

 

On the other hand, the study of the Work Environment of a company has as objective to evaluate those environmental factors that are in a more direct interaction with each organization. This is based on the study of the business environment, which includes suppliers, buyers, subcontractors, customers, investors, creditors, competitors and other interested parties, whether at the corporate level, at the corporate level or at the level of the business sector, depending on the case (Krivstov, 2014c, p.31).

 

The external environment consists of three dimensions or underlying patterns identified to evaluate and understand the concept of external environment in a systematic way, called Munificence, Dynamism and Complexity (Njoroge, et al., 2016d, p.2). Munificence refers to the scarcity or abundance of resources available in an environment, and demanded by one or more companies that operate in the same environment (Gathungu, Aiko and Machuki, 2014). The dynamism refers to the ever changing nature of the external environment, which can transform the purpose of the company and the environment in which it operates (Machuki and Aosa, cited by Njoroge et al., 2016e, p.42) and consists of numerous variables such as the speed at which the environment is changing (stable-turbulent) and predictability (predictable-unpredictable). And complexity is assessed through the number of issues that organizations must address in various environmental aspects and whether those issues are similar or different from each other (Njoroge et al., 2016f, p.42).

 

2.2. Financial Performance

Financial Performance can be interpreted as a measure of how well the company achieves its financial objectives. Many researchers insist that financial measures are the most reasonable measures to measure the performance of a company (Affes, 2016a, p.1).

 

Income and profits are important variables to measure the financial performance of a company. When the utility is compared with the income, assets and assets of the company, the profitability measures are obtained. The traditional measures of profitability to compare the financial performance between companies have been the Return on Investment (ROI), the Return on Sales (ROS) and the Return on Equity (ROE) (Affes, 2016b, p.2). The Return on Investment, also called Economic Return, evaluates the benefit obtained by investing in assets. The Return on Sales or Profit Margin, measures the profit derived from commercialization of the services. And the Return on Equity, called Shareholder Profitability, computes the return on shareholders' capital contributions.

 

3. Methods

3.1. Design of the investigation

This study is an empirical generalization that tests a set of hypotheses to identify significant relationships between environmental factors and the profitability of companies, through the dimensions of the external environment.

 

A transectional design was used because the information that was gathered about the topics happens in a single point in time. For the purposes of this study, all 25 private health companies that exist in the city of Barinas were selected, so a census was conducted.

 

3.2. Measurement of key constructs

3.2.1.  The External Environment. The external environment was operationalized along two main categorizations. The first is the composition of the external environment, which refers to the objective environmental factors that make up the focal environment of the organization. And, secondly, the environmental dimensions, which refer to the perception of the attributes of the sector's environment. To evaluate the nature of the external environment, both categorizations were used, while both objective and perceptual measures were obtained. The 15 most important objective environmental factors for the sector were identified, on political, economic, supplier and client aspects, and two dimensions (Munificence and Dynamism) were used to describe the perceptions on each of the factors. The dimension of Dynamism was measured by the variability and predictability of each environmental factor. On the other hand, the Munificence was measured by the favorability of the environmental factors on the organizations, that is, how favorable or unfavorable each factor is for each company in particular. In this way, respondents were asked about their perception of the variability, predictability and favorability of each of the fifteen objective environmental factors identified above.

 

3.2.2.  Financial performance. To measure this construct, the approach based on the Profitability measures was adopted, of which the ROI was preferred to establish the effect of the external environment on the use of the assets; and the ROE, in order to specify the profitability of the shareholders' contribution. To calculate these measures, the survey investigated the amounts of the Net Profits, the Accounting Capital and the Total Asset in the financial statements of the companies at the close of the 2016 fiscal year. With these data, the profitability measures were calculated, ROI and ROE, as the ratio of Net Income to Total Assets and Stockholders' Equity, respectively.

 

3.3. Research hypothesis

Four hypotheses were raised. The first three tests the associations between environmental factors and the dimensions of the external environment, Dynamism and Munificence. The fourth hypothesis tries to prove the relationship between these dimensions and financial performance. The hypotheses to be examined are the following:

H1: The environmental factors are related to the Variability of the External Environment. It seeks to identify the environmental factors that influence the stability or turbulence of the external environment.

 

H2: The environmental factors are related to the Predictibility of the External Environment. Investigate the environmental factors associated with the predictable or unpredictable external environment.

 

H3: The environmental factors are related to the Favorability of the External Environment. It examines the environmental factors that intervene favorably or unfavorably in the external environment.

 

H4: The Variability, Predictability and Favorability of the External Environment are related to Profitability. Scrutinize the relationship between the dimensions of the external environment and financial performance.

 

3.4. Data collection

The data was collected from primary and secondary sources. The environmental factors were identified from the review of the profile issued by The Economist Intelligence Unit (EIU) on Venezuela in February 2017, which was codified and linked with the qualitative data analysis software Atlas.ti v.7.5.4. In this way an inventory of 75 objective factors of the General Environment (political and economic) was collected, which were submitted to the consideration of a focus group made up of 6 experts from the private health sector, who ranked them according to the degree of influence they perceive about the sector, and eleven factors that accumulated 80% of the votes were selected. Additionally, the members of the focus group incorporated 4 factors that belong to the Work Environment of the sector. As a result, the 15 factors identified were: political transition (refers to the possibility of a political transition in the national government); concentration of powers (includes the accumulation of special powers in the national executive branch); rate of inflation; deterioration of infrastructure (dealing with the deterioration of public health facilities) public hospital; tax regime; black market currency; labor irremovability; shortage (denotes the lack of supplies, equipment and spare parts, price regulation, exchange control, overvaluation of the currency, purchasing conditions (describes the negotiation of purchase conditions with suppliers), purchasing power (alludes to the purchasing power of those customers that are not covered by insurance policies), coverage of the policies (refers to the amounts covered by insurance policies and health funds), and insurance debt (these are the accounts receivable from insurance companies and other customers who pay on credit the services provided by companies in the sector).

 

Respondents were asked about the perceived degree of variability, predictability and favorability of each environmental factor, on a Likert scale of 5 categories. The degree of variability and predictability measured the dynamism, and the degree of favorability assessed the munificence. The reliability was 0.818, obtained with the Cronbach alpha coefficient.

 

3.5. Analysis Techniques

Statistical techniques of Optimal Scaling were used to analyze the data and test the research hypotheses.

 

The first 3 hypotheses were evaluated through the Principal Component Analysis Categorical (CATPCA) with varimax rotation. In this way, the Variability of the 15 environmental factors was reduced to 2 components ("Variab1" and "Variab2"), whose loads in rotated components (which correspond to the Pearson correlations) reveal the contribution of environmental factors in each component. On the other hand, the quantification of the 5 categories (of the Likert scale) of each environmental factor elucidated the degree of perception prevailing in each one of them. In the same way we proceeded with the other 2 indicators of the dimensions of the external environment (Predictability and Favorability), and 2 components were obtained for each of them, called "Predict1", "Predict2", "Favorab1" and "Favorab2" respectively.

 

The ROI and ROE were reduced by a "Factor Analysis" to a single component called "Rentab".

 

To demonstrate the significant associations between the dimensions of the external environment and financial performance, the Nonlinear Canonical Correlation Analysis (OVERALS) was used. With the 7 components previously obtained in the CATPCA and factorial procedures, 4 sets of data called "Variability", "Predictability", "Munificence" and "Profitability" were constructed and analyzed with OVERALS, with which the saturations were obtained, that allowed to determine which components are associated with profitability. All this allowed us to map the relationship between environmental factors and financial performance, as well as the degree of perception of each factor that influences this relationship.

 

4. Results

H1: Environmental factors are related to the Variability of the External Environment.

The CATPCA procedure of the perceptions of the variability of environmental factors yielded a solution of 2 components, called "Variab1" and "Variab2", which together explained 75.9% of the variance of the data. The rotated component loads revealed that "Variab1" is associated with 10 environmental factors, while "Variab2" correlates with the 5 other environmental factors.

 

CATPCA also assigned an optimal quantification to the categories of perception of variability of each environmental factor, whose higher absolute value represents the category that differs most clearly and, therefore, the one that has a greater contribution in the obtained solution. Table 1 identifies the loads of rotated components of the environmental factors in each component, and the quantification of the predominant category in the solution obtained:

Table 1. Variability of environmental factors.

Source: The Author (2017).

 

 

H2: The environmental factors are related to the Predictability of the External Environment.

Also through the CATPCA procedure, the predictability of the 15 environmental factors was reduced to 2 components, which were called "Predict1" and "Predict2", which explained 76.1% of the variance of the data. Based on the rotated component loads, "Predict1" is associated with 10 environmental factors while "Predict2" is associated with the other 5 environmental factors. Table 2 shows the results of the rotated component loads and the quantification of the predictability perception categories of each environmental factor prevailing in the obtained solution:

Table 2. Predictability of environmental factors.

Source: The Author (2017).

 

H3: The environmental factors are related to the Favorability of the External Environment.

The CATPCA procedure reduced the perceptions of favorability of the 15 environmental factors to 2 components designated as "Favorab1" and "Favorab2", which explained 70.4% of the variance of the data. The rotated component loads showed the "Favorab1" ratio with 9 environmental factors. On the other hand, "Favorab2" is related to the other 6 environmental factors. In Table 3 shown below, the results of the rotated component loads and the quantification of the prevailing favorability perception categories in each environmental factor are presented.

Table 3. Favorability of environmental factors.

Environmental Factor	Rotary component loads		Quantification of the preponderant category in each environmental factor
	Favorab1	Favorab2	Value and Category Label	Quantification
Political Transition	,-653		2 = Unfavorable	-1,782
Concentration of powers		,902	5 = Very favorable	1,774
Rate of inflation	,745		3 = Neutral	3,559
Impairment of infrastructure	,726		3 = Neutral	2,256
Tax regime		,768	1 = Very unfavorable	1,357
Black Currency Market	,773		2 = Unfavorable	1,414
Labor immobility	,719		3 = Neutral	1,464
Shortage		-,604	1 = Very unfavorable	-1,265
Price regulation	,856		4 = Favorable	1,509
Change control	,869		3 = Neutral	2,968
Overvaluation currency	,860		3 = Neutral	1,494
Purchase conditions		,809	4 = Favorable	1,705
Purchasing power		,875	5 = Very favorable	2,579
Policy coverages		,827	5 = Favorable	2,060
Debt insurance	,915		3 = Neutral	2,901

Source: The Author (2017).

 

          H4: The Variability, Predictability and Favorability of the External Environment are related to Profitability.

With the OVERALS technique, a 2-dimensional solution was obtained that explained 70.7% of the variance of the data.

 

The Component Saturation analysis shown in Table 4 provides an indication of the contribution that each component of the external environment contributes to the dimensions of the solution obtained. In this way, high saturations were found between the components "Variab1", "Predict2", "Favorab2" and "Rentab" in Dimension 1; and between "Variab2", Predict1 "and" Favorab1 "in Dimension 2. Therefore, in Dimension 1 the relationship between profitability and the environmental factors associated with the components" Variab1 "," Predict2 "," Favorab2 "was evidenced".

Table 4. OVERALS: Components Saturations.

Source: The Author (2017).

 

The robustness of the obtained solution was evaluated from the mean loss and eigenvalue of dimension 1, which are also shown in Table 4. The average loss allowed to calculate the multiple correlation coefficient of said dimension, with a result of 0.903 ; and the proportion of the real adjustment explained in this dimension was calculated from the eigenvalue, and was 57.7%. Both values show that there is a high degree of relationship between the components.

 

5. Discussion of results.

The findings demonstrated the existence of a strong relationship between the external environment and financial performance and at the same time provides support to the theoretical perspective that considers organizational performance as a dependent variable, and the external environment as one of its independent constructs. Certainly, it was concluded that the external environment is strongly related to the financial performance of the private sector of health in the context studied, since very high correlations were found between most of the environmental factors, the dimensions of the external environment and the profitability of the companies in the sector that suggest the existence of this strong relationship. The hypothesis H4 was verified by the OVERALS procedure, which showed a high saturation in the components "Variab1", "Predict2", "Favorab2" and "Rentab" in dimension 1, which suggests that there is a strong relationship between them, therefore, the environmental factors associated with these components are those that influence financial performance. The identification of these factors was achieved by testing the other hypotheses of the investigation.

 

The CATPCA procedure of the Variability perceptions tested H1 hypothesis, and the analysis of rotated component loads found that 10 environmental factors have a manifest contribution in the "Variab1" component. These factors were: concentration of powers; inflation; tax regime; black market currency; shortage; price regulation; change control; purchasing power; coverage of the policies; and insurance debt. In all these factors, the predominant quantification was that corresponding to category 1 "Very Little Changeable".

 

In the same way, the application of CATPCA to the perceptions of Predictibility was used to test hypothesis H2 and showed that 5 environmental factors have a high rotated load in the "Predict2" component, which distinguishes them as the factors that they have a fundamental contribution in this component, which are: political transition; concentration of powers; inflation; purchasing conditions; and purchasing power. In these factors, the quantification that prevailed was that corresponding to category 5 "Very Predictable".

 

The evidence also suggests that the actors in the sector perceive that the external environment is characterized by low dynamism. Indeed, the quantification of environmental variability and predictability indicators indicated that the preponderant categories in the solution were "Very little changeable" and "Very predictable" respectively, which indicates that the perception that the external environment is stable and predictable predominated, or what is the same, not very dynamic. This condition is convenient for companies in the sector because it gives them a greater capacity to react to changes that may occur in the environment.

 

Finally, the use of CATPCA in Favorability perceptions tested hypothesis H3 and showed that 6 environmental factors have the greatest contribution in the "Favorab2" component, however, the quantification of the preponderant categories in these factors yielded divergent results. On the one hand, concentration of powers, purchasing conditions, purchasing power, and the coverage of the policies were expressed as "Favorable / Very Favorable"; while tax regime and shortage revealed "Very Unfavorable". These results suggest that the actors of the sector perceive that in the Work Environment there are munificent conditions to operate successfully, while shortages and taxes are factors of the General Environment that constitute serious threats that affect companies. The relationships obtained were represented in figure 1, which is shown below.

 

Figure 1: Relations between environmental factors, dimensions of the external environment and financial performance.

SEE IN THE ORIGINAL VERSION

Source: The Author (2017).

 

6. Conclusion

The private health sector is immersed in an external environment that is not very dynamic, with an unfavorable general environment and a munificent work environment that exerts a strong influence on its financial performance. For companies in the sector, this means that today more than ever, the influences of the external environment must be taken into account in order to preserve financial viability, to anticipate changes in the environment and to make more appropriate strategic decisions.

 

7. References

Affes, H. (2016a,b). Cognitive role of engineers and its implications on financial performance: An empirical analysis on the french market. Journal of Internet Banking and Commerce, 21(2), 1.

 

Balas, A. N., Gokus, O., & Colakoglu, S. N. (2014). Exploring the role of external environment on determining strategic focus, market orientation, and firm performance of service firms. Academy of Marketing Studies Journal, 18(1), 19.

 

EIU (2017). Country Analysis: Venezuela. The Economist Intelligence Unit. Recuperado de: http://country.eiu.com/Venezuela

 

Gathungu J., Aiko D. & Machuki V. (2014). Entrepreneurial Orientation, Networking, External Environment, and Firm Performance: A Critical Literature Review. European Scientific Journal, march vol. 10(7).

 

Krivstov, A. (2014a,b,c,d). Strategic Analysis of External Environment as a Basis for Risks Assessment. Actual Problems of Economics #10(160).

 

Murgor, P. (2014). External environment, firm capabilities, strategic responses and performance of large scale manufacturing firms in Kenya. University of Nairobi, Unpublished Ph.D. Thesis.

 

Njoroge J., Ongeti W., Kinuu D., & Kasomi, F., (2016a,b,c,d,e,f). Does External Environment Influence Organizational Performance? The Case of Kenyan State Corporations. Management and Organizational Studies, 3(3).

 

 

Adolfo Javier Cegarra Acosta

e-mail: quantum.analitica2@gmail.com

 

Born in Barinas, Venezuela, on 06/14/1963. Agroindustrial Engineer, MSc. in Industrial Engineering and Specialist in Business Management. PhD Candidate in Business Administration at the Universidad Politécnica de Madrid (UPM).

Ten years in the national food industry (HALACA, PROTINAL, REMAVENCA). Seventeen years leading companies in the private health sector. University professor at the IUP "Santiago Mariño" and the Universidad Santa María.

 

The content of this manuscript is disseminated under a Creative Commons License Attribution-NonCommercial-ShareAlike 4.0 International

 

- Original Version in Spanish -

DOI: https://doi.org/10.29394/Scientific.issn.2542-2987.2018.3.7.1.17-36