Entrepreneurial Orientation and Performance of Small and Medium Scale Enterprises (Smes) in Ikeja, Lagos State, Nigeria




Akinwande Ademosu1, Akinola Morakinyo2



Abstract: The study investigates the relationship between EO and SMEs’ performance using 96 SMEs in Ikeja, Lagos State, Nigeria. The three domains of EO namely innovation, pro-activeness and risk-taking are the focus of the study. Structured questionnaire is used to elicit responses from the SMEs’ entrepreneurs. The responses are subjected to both descriptive and inferential analysis under quantitative technique. The result from the analysis shows that strong synergy exists between risk-taking and pro-activeness. Findings further indicate that for EO to have significant impact on SMEs’ performance, the orientation of the entrepreneurs must be the one that brings about a strong connection between their drives for risk- taking and pro-activeness. This means that SMEs’ entrepreneurs should not only take risk or innovate but must be proactive with the two to achieve sustainable outstanding performances in their businesses.

Keywords: Entrepreneurial Orientation; Risk-Taking; Pro-activeness; Innovation; SMEs’ performance

JEL Classification: L26



1. Introduction

Over the years, SMEs have been one of the major drivers of Nigerian economy contributing between 50 to 60 percent to the Gross Domestic Product GDP of Nigeria within the last two decades on the average (CBN, 2019). The performance of small and medium enterprises (SMEs) as a sector does not only act as a significant part linked to the strengthening and enhancement of the development of the nations but, also a major component part of their economies. The sector is an engine which encourages the creation of wealth in the country’s economic system. Its performance is a major driver for the level of industrialization; modernization; urbanization, gainful and meaningful employment for all those who are able and willing to work (Aremu & Bamiduro, 2012).

Despite all the advantages inherent in SMEs both to the society and the economy of the country as a whole, the SMEs sector has been bedeviled by a wide range of challenges which has limited its performance in recent years. The SMEs sector’s contribution to the GDP of Nigeria fell from 45.7% in 2016 to 34.6% in 2017, there was a slight increase in 2018 to 35.9% but unfortunately it fell to 31.% in 2019 (SMEDAN, 2020). These unstable performances have been the characteristics of the SMEs sector in Nigeria over the years.

The orientation of the entrepreneurs who are the major stakeholders in SMEs in Nigeria has been identified as a major factor affecting the performance of the sector. According to (Ibrahim & Abu, 2020), the skills and entrepreneurial knowledge of business owners are directly dependent on their orientation and this has been identified has a key component that determines their ability to strategically manage their establishments to engender good performance (Shu, De Clercq, Zhou, & Liu, 2019). However, there is a contrary opinion to this, (Gupta, Niranjan, & Markin, 2019) stated that entrepreneurial orientation (EO) does not have anything significant to do with performance. They buttress their position from their empirical study where it was revealed that many entrepreneurs with little or no prior training or orientation about business management appeared to be more successful in their businesses than some with some levels of orientation.

Another contentious issue is the measurement of entrepreneurial orientation. Some efforts have been made to develop a construct for this by past authors such as (Hernández-Perlines, Moreno-García, & Yáñez-Araque, 2019; Yoo & Kim, 2019). All these used firm level construct without taking into consideration individual entrepreneurial differences. In other words, these authors see entrepreneurial orientation (EO) as a firm-level construct or strategy-making process which a firm uses to enact its organizational purpose, sustain its vision and create competitive advantage. According to them, EO of a firm is defined as a firm that involves itself in technological innovation, undertakes risky ventures and pursue opportunities proactively (Bolton & Lane, 2012; Covin & Wales, 2012). However, studies have shown that entrepreneurial orientation is more of individual business owner skill than the firm level thing. These authors identified Innovativeness, pro-activeness and risk-taking as the most prominent dimensions or domains of EO. All these will be used in this study as against firm level construct.

Therefore the main objective of this study is to examine the effect of EO on the SMEs’ performance using Ikeja local government of Lagos State Nigeria as the case study. The rest of the paper is divided into literature review, methodology, results and discussion, conclusions.



2. Literature Review

This aspect of the paper primarily focuses on the review of the theoretical and empirical literatures that are relevant to the study.

Theoretical Literatures

The major theory that is chosen for this paper is the Knowledge based theory KBT which emphasizes knowledge of an entrepreneur as the main resources needed fro good performance

The Knowledge based Theory (KBT)

The knowledge based theory of the firm considers knowledge as the most strategically significant resource of a firm. Its proponents argue that since knowledge based resources are usually difficult to imitate and socially complex, heterogeneous knowledge bases and capabilities among firms are the major determinants of sustained competitive advantage and superior corporate performance. Knowledge is entrenched and carried through multiple entities, including organisational cultures and identity, policies, routines, documents, systems and employees. This perspective builds and extends the resource based view of the firm (RBV), initially promoted by Penrose (1959) and later expanded by (Barney, 1991; Conner, 1991; Wernefelt, 1984). The knowledge based theory owes its origin to the view of the classical scholars in persons of Socrates, Plato and Aristotle. The classical scholars provided Knowledge Management scholars the theoretical foundations upon which the KBT later developed. For example, two strands of knowledge were observed by classical knowledge theorists. The innatists (building on the Plato’s idea of innate knowledge) referred to as a priori knowledge to explain knowledge that can be acquired independent of sensory experience. On the other hand, the empirists influenced by Aristotle’s views, defined knowledge acquired through experience as posteri knowledge. The reference being made by modern KM scholars to both tacit and explicit knowledge is well rooted in the a priori and posteri knowledge paradigm(Mbhalati, 2017).



Empirical Literature

There have been studies in and outside Nigeria on issues relating to EO and SMEs performance. Some of these relevant studies are reviewed under this section.

Ibrahim and Mahmood (2016) investigated the relationship between entrepreneurial orientation, competitive advantage and SMEs’ performance in Kano State, Nigeria. The study administered structured questionnaire on 256 SMEs’ in the area, Both the Pearson correlation and structural equation modeling were applied and the results showed that EO has a significant link with competitive advantage which brings about its significant impact on the performance of SMEs in the area sampled.

Uchenna, Sanjo & Joseph (2019) examined the effect of entrepreneurial orientation (EO) on micro, small and medium enterprises’ (MSMEs) performance in Abia State, Nigeria. The study applied survey research design through the administration of structured questionnaire to the chief executives of some selected MSMEs in Abia State, Nigeria. The findings from the descriptive analysis revealed that innovativeness, risk-taking and pro-activeness, are the critical dimensions of EO driving MSMEs performance in Abia State, Nigeria while competitive aggressiveness does not significantly affect MSMEs’ performance. It can therefore, be concluded that EO positively and significantly affects MSMEs’ performance in Abia State, Nigeria.

Hoque (2018) explored the role of organizational culture (OC) in the relationship between entrepreneurial orientation (EO) and Bangladeshi small and medium enterprises (SMEs) performance. A quantitative survey technique was exercised and the data were collected from the randomly-selected 384 owners of SMEs in Dhaka–Bangladesh. The data were analyzed by using SEM-AMOS. Based on the statistical results, EO and OC were significantly related to SME performance and OC was found to mediate the relationship between EO and SME performance.

Isichei, Agbaeze & Odiba (2020) addressed the mediating effect of structural infrastructure capability on the relationship between entrepreneurial orientation (EO) and SMEs performance in emerging economies, focusing on Nigeria. The study adopted a survey design, utilizing a sample of 377 SMEs covering the six geopolitical zones in Nigeria. A questionnaire was used for data collection, and data analysis was conducted using partial least squares structural equation modeling (PLS-SEM) with the aid of SmartPLSv3.The study found that innovativeness and pro-activeness, as dimensions of EO, have a significant effect on SMEs’ performance. Risking-taking, however, showed no significant effect on performance. The study found that structural infrastructure capability significantly mediates the EO–performance relationship.

Kiyabo & Isaga (2020) analyzed the influence of entrepreneurial orientation on SMEs’ performance under the mediation of competitive advantage using firm growth and personal wealth measures. Entrepreneurial orientation was adopted as an intangible resource in form of processes. A survey method with cross-sectional design was used to collect data from 300 owners-manager of welding industry SMEs located in Dar es Salaam, Mbeya, and Morogoro urban centers in Tanzania. By the aid of AMOS software, data analysis comprised of developing measurement and structural models using structural equation modeling technique. Sample data were then bootstrapped using 200 samples to determine the indirect effect of entrepreneurial orientation on SMEs’ performance through competitive advantage. Findings from this study inform that competitive advantage mediates the relationship between entrepreneurial orientation and SMEs’ performance for both firm growth and personal wealth performance measures.

It is obvious from the studies reviewed that they were all much more interested in the mediating effect of a certain variable or the other in the relationship between EO and SMEs’ performance. The only study that examined the effect EO directly on SMEs performance only made use of descriptive statistics which might not be reliable as the usage of both inferential and descriptive which is used in this study.



3. Methodlogy

This aspect of the research paper discusses the methodology adopted to achieve the objectives of the study.

Research Design

This study is an exploratory one that uses survey method to collect information from the target respondents via structured questionnaires and quantitative method of analysis is adopted. The research philosophy or paradigm for this study revolves around both positivism and epistemology. Positivism is a research philosophy that believes that research operates with objectivity in the execution of their research work. In other words there are no predetermined outcomes expected by the researcher. Epistemology is a research paradigm that studies the nature of knowledge and the process through which knowledge is acquired and validated (Cazeaux, 2017). Consequently, this study has no predetermined idea of how EO impacts SMEs performance. This objective will only be achieved when the research is conducted (Rahi, 2017).

Population of the Study

The population of the study includes all the SMEs registered with the SMEDAN in Ikeja, Lagos State. From the list, there are 125 registered SMEs in Ikeja. This figure forms the population for the study.

Sample and Sampling Technique

A simple random sampling technique is embraced by the study using the Taro Yamane method to select the sample size for the numbers of SMEs the study covers in the survey. The calculation is as follows;

(1)

Where n is the sample size, N is the population, e is the error margin usually 0.05 is used.

In getting the sample for the numbers of SMEs to be included in the survey, N is 125 which is the total population of the SMEs in Ikeja. Lagos State of Nigeria. Using the formula (2)

(3)

(4)

Therefore, the minimum SMEs that are covered in the survey is approximately 96.

Instrumentation and scoring

The questionnaire is divided into four sections. Section A contains questions on socio- demographic characteristics about the respondents and the SMEs. These include gender, age, years of operation, number of employees and highest qualification. Section B contains questions on innovativeness, pro-activeness and risk-taking which are the dimensions/domains of entrepreneurial orientation. Lastly, section C contains questions on SMEs performance. Apart from Section A, other sections have close-ended questions on variable by variable using a five- point Likert rating scale ranging from Strongly Agree (5), Agree (4), Neutral (3), Disagree (2) to Strongly Disagree (1). Each respondent is asked to indicate his or her level of agreement with the statements relating to the variables.

Validity and Reliability Tests

Bryman and Bell (2011) defined validity as the fact that “a measure of a concept really measures concept”. Validity attests to whether an instrument measures what it is supposed to and justified by the evidence. Essentially, it entails the extent to which an instrument actually measures the aspects that it was intended to measure. Validity test of Kaiser-Meyer Olkin (KMO) value of 70 percent and Bartlet test of Sphericity with p-value less than 0.05 are applied. Reliability is the consistency of a measure of a concept (Bryman & Bell, 2011). It is linked to the stability of the data. Asika (1991) explains that reliability of research instrument concerns the extent to which the instrument yields the same results on repeated trials. The Chronbarch alpha test is applied and any question with less than 0.7 reliability index will have to be reconstructed or replaced. The results are presented in table 1

Table1. Validity and Reliability Test

Variable

Number of Questions

Reliability test Cronbach value

Validity test

KMO value

EO: Innovation

6

0.78

0.702

Pro-activeness

8

0.71

0.73

Risk-Taking

6

0.83

0.77

SMEs Performance

6

0.79

0.72

Source: Output of Author’s Data Analysis (2020)

Table 1 shows that all the instruments yielded Cronbach alpha values that is above 0.7. The implication of this is that they all passed the reliability test. In the same vein, the KMO test produced values that are all beyond 0.7 for all the instruments. This implies that all of them as well passed the validity test. The general implication is that all the instruments used are suitable for the survey.

Method of Data Analysis

This aspect of the paper discusses the techniques of analysis adopted in the study. However, the model to be estimated is first discussed

Model Specifications

From the literature and the theoretical framework, especially the Knwoledge based theory of Penrose (1959), it is clear that Entrepreneurial orientation is the independent variable while SMEs performance is the dependent variable. Based on the foregoing, the model that exp[resses the relationship between the two is specified as follows:

(5)

Where SMEP is SMEs performance and EO is entrepreneurial orientation. More explicitly the model can be expressed thus;

(6)

Where, INNO is innovation, PROACT is Pro-activeness and RISK is rRisk-taking. These are three domains of EO captured in the study. is the stochastic variable or the error term.

Estimating Techniques and Data Analysis

Data analysis tools for this study are broadly divided into two categories namely descriptive and inferential statistics.

Descriptive Statistics

The descriptive statistics include the usage of the frequency distribution tables and charts to present data harvested from the survey. Percentages and ratio tables are also used where relevant during the analysis.

Inferential Statistics

Inferential statistics such as; multiple linear regression, Pearson Product-moment correlation analysis and Analysis of Variance ANOVA are applied with the aid of statistical package for social science (SPSS) version 24.0. The use of Pearson Product-moment correlation analysis is necessitated because it helps to determine the degree or level of relationship or association that exists between variables. Also, it allowed the researcher to examine and explain the association between the independent and dependent variables (Johnson, 2010). Multiple linear regression is also used because it provides useful link between variables for further investigation and there is no provision for manipulation of behaviour. Also, the ANOVA is used because, it helps to examine and know which variable accounts for the most significant change in the dependent variable (Molliegeorgious, 2015).



4. Results and Discussions

This section presents, interprets and discusses the empirical results obtained after the application of the methods of analysis explained under the methodology.

Response Rate

As clearly spelt out in the methodology purposive random sampling is utilized as the sample selection technique based on the fact that specific sets of staff in the organisation are qualified to answer the questions. Table 4.1 describes the response rates.

Table 2. Description of the Response Rates

Operational

Questionnaires administered

Questionnaires collected

response percentage

SMEs owners

96

96

100%

Source: Output of Author’s Data Analysis (2020)

From the methodology, the sample selected for the study is 96 SMEs. It will be recalled that this was calculated from the total population of 125 SMEs registered in Ikeja wuth SMEDAN. The implication is that all the distributed questionnaire were successfully colleceted from the respondents

Demographic Features Analysis

The demographic features describe the characteristics of each respondent included in the survey since the study focuses on the owners of the SMEs hence the demographic characteristics of the owners are important.

Table 3. Gender Distribution of the Respondents

Gender



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

65

65.0

67.7

67.7

Female

31

31.0

32.3

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

The result from the analysis on table 4 is an indication that more men are included in the survey than women. Men are about 67.7% while women are about 32.3% of the total population covered in the survey. This might not be unconnected with the population composing in the SMEs.

Table 4. Age Distribution of the Respondents

Age



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

26-35years

21

21.0

21.9

21.9

36-45years

56

56.0

58.3

80.2

46-55years

12

12.0

12.5

92.7

56 -65years

7

7.0

7.3

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

The age distribution of the entrepreneurs is described in table 4. The result shows that most of the SMEs owners interviewed are youths. For instance, the largest percentage is about 58.3% which belongs to age group 36 to 45 years, .very few of the entrepreneurs are adults. Just 7.3% of them are between 56 and 65 years. It further underscores the importance of the youth in SMEs development in society.

Table 5. Marital Status

Marital Status



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Married

76

76.0

79.2

79.2

Single

20

20.0

20.8

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

It is obvious from table 5 that most of the SMEs entrepreneurs included in the survey are responsible youn adults. About 79.2% are married while 20.8% are single. This distribution imposes some validity on the responses exected from the entrepreneurs.



Table 6. Years of Operation

Years of Operation



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0-5 years

14

14.0

14.6

14.6

6-10 years

27

27.0

28.1

42.7

11 years and above

55

55.0

57.3

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

Few of the SMEs are relatively young according to the data presented in table 7. The result further shows that most of the SMEs used in the srvey have been existing for more than 11 years and above. Precisely about 57% of them are in this category while just a few of about 14.6% are still existing for between 0 and 5years.

Table 7. Numbers of Employee

Numbers of Employees



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0- 5

53

53.0

68.8

68.8

6-10

6

6.0

7.8

76.6

11-above

18

18.0

23.4

100.0

Total

77

77.0

100.0


Source: Output of Author’s Data Analysis (2020)

The information shown on table 7 is an indication that majority of the SMEs covered are small business with staff strength of a maximum of 5 people. At least 68.8% of them are small. Notwithstanding, about 23.4% of them have staff strength above 11 but less than 50 the general implication is that with the definition by SMEDAN all the establishments covered in the survey fall in the category of SMEs.

Table 8. Nature of Work

Nature of Work



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Service Provider

37

37.0

38.5

38.5

Manufacturing/Production

28

28.0

29.2

67.7

Both

31

31.0

32.3

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

The analysis on table 8 shows that majority of the SMEs included in the survey are service providers. At least 38.5% of the sampled SMEs are into services. Notwithstanding, about 32% of them too combine production or manufacturing with services. 29.2% are predominantly into production or manufacturing.

Table 9. Business Ownership

Business Ownership



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

One Man Business

37

37.0

38.5

38.5

Partnership

34

34.0

35.4

74.0

Limited Liability Company

25

25.0

26.0

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

The information on table 9 shows that 38.5% of the SMEs are sole proprietorship or what is known as one man business. 35.4% are partnership while 26% are limited liability companies. This shows how entrepreneurship orientation is very important for the SMEs since many of them are one man business.

Table 10. Highest Qualification

Highest Education Qualification



Frequency

Percent

Valid Percent

Cumulative Percent

Valid

OND/HND/BSC/DIP

51

51.0

53.1

53.1

MSc/MBA/PGD

45

45.0

46.9

100.0

Total

96

96.0

100.0


Source: Output of Author’s Data Analysis (2020)

The pool of respondents included in the survey comprised of well-educated personnel in the SMEs. This is evident in result presented on table 11 which indicates that about 53.1% of the respondents have OND, HND or BSC. In addition, 46.9% hold Masters degree and above. The analysis shows that many of the SMEs entrepreneurs are educationally suitable to understand the questionnaires and provide the required answers to the questions.

Analysis of Entrepreneurial Orientation Impacts on SMEs Performance

This is the main objective of this paper and after the initial factors analysis to confirm both the validity and reliability of the research instruments, the correlation and regression analysis were conducted and the result of the correlation is presented in table 11.



Table 11. Correlation Analysis

Correlations



Innovation

Pro-activeness

Risk-Taking

SMEs Performance

Innovation

Pearson Correlation

1

.107

.150

.000

Sig. (2-tailed)


.300

.143

1.000

N

96

96

96

96

Pro-activeness

Pearson Correlation

.107

1

.456**

-.277**

Sig. (2-tailed)

.300


.000

.006

N

96

96

96

96

Risk-Taking

Pearson Correlation

.150

.456**

1

.335**

Sig. (2-tailed)

.143

.000


.001

N

96

96

96

96

SMEs Performance

Pearson Correlation

.000

-.277**

.335**

1

Sig. (2-tailed)

1.000

.006

.001


N

96

96

96

96

**. Correlation is significant at the 0.01 level (2-tailed).



The result of the correlation shows the level of relationships existing among the core variables in the analysis especially between the three domains of EO and SMEs performance. Innovation exhibit does not exhibit significant relationship with either pro-activeness or risk-taking which are the two other EO domains. On the contrary, there appears to be more synergy between pro-activeness and risk-taking. The correlation coefficient between the two is 0.456 and the value is statistically significant at 1%. This is an indication that significant correlation exist between risk-taking and pro-activeness domains of EO. In addition, both risk-taking and pro-activeness domains have significant correlation with SMEs performance but innovation does not have. This further attests to the synergy between the two domains of EO



Table 12. Regression Results

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

3.956

.604


6.547

.000

Innovation

-.173

.099

-.177

-1.742

.085

Risk-Taking

.577

.127

.465

4.545

.000

Pro-activeness

.337

.094

.328

3.583

.001

  1. Dependent Variable: Rise in sales,

  2. R Square: .742




Source: Output of Author’s Data Analysis (2020)

The results on table 12 have shown that out of the three domains of EO risk-taking and pro-activeness have the most significant impacts on SMEs performance. The coefficients of the two are 0.577 and 0.337 respectively and the two are statistically significant at 15 and 5% respectively. The implication of the results is that EO in terms of risk-taking and pro-activeness are very germane to the SMEs’ performance. Notwithstanding, innovation is part of the EO domain but it is not as important to SMEs performance as risk-taking and pro-activeness. Considering the R-square of the model, this is shown in table 12 as 0.742. The implication is that EO explains about 74% variation in SMEs performance. This underscores the importance of EO in promoting the performance of the SMEs. The ANOVA is an avenue to test the overall significance of the model. The result shows that the model estimated is statistically significant and it further confirms the importance of the role of EO in the success of any SMEs. The ANOVA result is presented in table 13

Table 13. Analysis of Variance ANOVA

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

8.228

3

2.743

10.051

.000a

Residual

25.105

92

.273



Total

33.333

95




a. Predictors: (Constant), Pro-activeness, Innovation, Risk-Taking


b. Dependent Variable: SMEs performance




Source: Output of Author’s Data Analysis (2020)

Table 13 shows F statistics of 10.051 and this value is significant at 1%. This result shows that there is a significant relationship between SMEs performance and EO. It indicates that the orientation of the SMEs owners sampled in the survey is very important to the survival of their businesses.



5. Conclusion

The results from the study have shown that EO is measured by three domains which have strong correlation with one another. However, the result further indicates that the correlation between risk-taking and pro-activeness is the most significant thus showing that an SME entrepreneur with good orientation in terms of risk-taking is also going to be proactive. The implication is that an entrepreneur who is going to be taking risk to explore new ideas in moving his or her business forward must also be proactive in taking any risk. The result conforms to the position of (Uchenna, Sanjo, & Joseph, 2019) who concluded from their study that managers from organizations will need to be very smart (proactive) in order to minimize and maximize the gains from any adventurous project that is, risk they embark on during the course of their operations. Consequently, it can be concluded from this study that there is a strong linkage between risk-taking and pro-activeness domains of EO. In other words, an SMEs owner with good drive for risk- taking will also likely to be very proactive as well.

Innovation is part of the EO domains but it fails to have significant correlation with either risk-taking and pro-activeness as shown in the analysis. The implication is that being been a good innovator does not mean you are proactive or like risk-taking. The finding is similar to that of (Kiyabo & Isaga 2020) who posited after their studies that many inventors of ideas fail to benefit from their innovations because they are not proactive in the execution of their innovative ideas. They further pointed out that people that steal their ideas might end up gaining from such ideas more than them.

Furthermore, the result from the study shows that both pro-activeness and risk-taking show positive and significant correlation with SMEs performance but innovation does not. This conclusion might not be unconnected with the strong correlation established between risk-taking and pro-activeness

Again, the result from the regression analysis that examined the impacts of EO on SMEs performance show that EO has significant impact on SMEs performance but pro-activeness and risk taking have individual significant impact on SMEs performance. Innovation is the only domain of EO that failed to show individual significant impact on SMEs’ performance. The result further underscore the importance of the conclusions made earlier about the strong synergy between risk-taking and pro-activeness.

Following these findings it can be concluded from the study that for EO to have significant impact on SMEs’ performance there must be a strong synergy between their levels of orientation in risk taking and pro-activeness. It is obvious from the study that having innovative ideas alone is not an enough orientation on the part of an entrepreneur to achieve outstanding performance in his or business. Notwithstanding, the results show that jointly, the three domains will influence the performance of the SMEs positively and significantly as well.

It is recommended that SMEs should not rely on innovative ideas alone but must be ready to take risk and be proactive with both risk-taking and innovation. With this, their orientation will significantly influence the performance of their businesses positively.



References

Aremu, M. A., & Bamiduro, J. A. (2012). Marketing mix practice as a determinant of entrepreneurial business performance. International Journal of Business and management, 7(1), p. 205.

Bolton, D. L. & Lane, M. D. (2012). Individual entrepreneurial orientation: Development of a measurement instrument. Education Training.

Covin, J. G. & Wales, W. J. (2012). The measurement of entrepreneurial orientation. Entrepreneurship theory and practice, 36(4), pp. 677-702.

Gupta, V. K.; Niranjan, S. & Markin, E. (2019). Entrepreneurial orientation and firm performance: the mediating role of generative and acquisitive learning through customer relationships. Review of Managerial Science, pp. 1-25.

Hernández-Perlines, F.; Moreno-García, J. & Yáñez-Araque, B. (2019). The influence of socioemotional wealth in the entrepreneurial orientation of family businesses. International Entrepreneurship and Management Journal, 15(2), pp. 523-544.

Hoque, A. (2018). The effect of entrepreneurial orientation on Bangladeshi SME performance: Role of organizational culture. International Journal of Data and Network Science, 2(1), pp. 1-14.

Ibrahim, A. U. & Abu, M. M. (2020). Influence of Entrepreneurial Orientation on Firms Performance: Evidence from Small and Medium Enterprises in Nigeria. International Journal of Economics and Financial Issues, 10(2), pp. 99-106.

Ibrahim, N. M. N. & Mahmood, R. (2016). Mediating role of competitive advantage on the relationship between entrepreneurial orientation and the performance of small and medium enterprises. International business management, 10(12), pp. 2444-2452.

Isichei, E. E.; Agbaeze, K. E. & Odiba, M. O. (2020). Entrepreneurial orientation and performance in SMEs. International Journal of Emerging Markets.



Kiyabo, K. & Isaga, N. (2020). Entrepreneurial orientation, competitive advantage, and SMEs’ performance: application of firm growth and personal wealth measures. Journal of Innovation and Entrepreneurship, 9(1), pp. 1-15.

Uchenna, E. B.; Sanjo, O. M. & Joseph, F. (2019). Entrepreneurial orientation and micro, small and medium enterprises (MSMEs) performance in Abia State, Nigeria. Covenant Journal of Entrepreneurship (Special Edition), 3(1).

Shu, C.; De Clercq, D.; Zhou, Y. & Liu, C. (2019). Government institutional support, entrepreneurial orientation, strategic renewal, and firm performance in transitional China. International Journal of Entrepreneurial Behavior & Research.

Yoo, J. & Kim, J. (2019). The effects of entrepreneurial orientation and environmental uncertainty on Korean technology firms’ R&D investment. Journal of Open Innovation: Technology, Market, and Complexity, 5(2), p. 29.




1J. Mark Robinson College of Business, Georgia State University, United States of America, Address: Atlanta, GA 30302, Georgia, United States of America, Corresponding author: akin@ademosu.org.

2Department of Economics, Pan Atlantic University, Lagos, Nigeria, Address: Lekki - Epe Expy, Lagos, Nigeria, E-mail: akinmorakinyo@yahoo.com.

AUDOE Vol 17, No, 2/2020, pp. 37-52