This study explores and examines the influence of Entrepreneurial Alertness (EA) on Small to Medium Enterprises (SME) performance within the Central Business District (CBD) of Lusaka. The study participants included 152 entrepreneurs who own SMEs represented by 44.7% females and 55.3% males. The purpose of the study was to investigate the influence that the EA construct has on SME performance, the association between the first order latent constructs, and to determine which roles of EA in venture performance were appropriate to the participants.
A cross-sectional survey was created using Qualtrics online survey software and sent through email and what’s app to SME’s whose contact details were provided by the Zambia Development Agency. The construct of EA was examined using a 13-point scale. Descriptive statistics were conducted in Statistical Package for the Social Sciences (SPSS) software. Confirmatory Factor Analysis (CFA) was performed in Amos SPSS to verify the factor structure of the observed variables and to ascertain the validity, and reliability of the measuring instrument. The influence of EA on SME performance and association between the first-order latent variables with performance were tested using multivariate Structural Equation Modeling (SEM).
The study found that the construct of EA has a positive and significant influence on SME performance. As regards the association between the first-order latent constructs (i.e., dimensions) and performance, this study demonstrated that only the evaluation and judgment latent construct (dimension) had a significant and positive association. Finally, the study determined that EA appears to be important when a company considers entering a foreign market as a strategy for market development, and EA has a direct impact on strategic change decisions and organizational performance. The study has implications for education, commerce, and industrial policymakers. Policy initiatives could influence training curriculum and capacity-building programs that promote EA to increase entrepreneurial opportunity identifications for increased national performance and contribution.
Table of Contents
Abstract
Acknowledgements or Preface of Acknowledgements
List of Tables
List of Abbreviations and Acronyms
Table of Contents
CHAPTER ONE: INTRODUCTION
1.0 Introduction
1.1 Background to the Research
1.2 The Research Problem
1.3 Objectives of the research
1.4 Research Questions
1.5 Significance of the Study
1.6 Scope and location of research
CHAPTER TWO: LITERATURE REVIEW
2.0 Introduction
2.1 Entrepreneurial Alertness
2.2 The Role of Entrepreneurial Alertness in Entrepreneurial Ventures
2.3 Business Performance
2.4 Theoretical Framework
2.5 Confirmatory Factor Analysis
2.6 Structural Equation Modeling
2.7 Hypothesis Testing
CHAPTER THREE: METHODOLOGY
3.0 Introduction
3.1 Hypothesized Model
3.2 Variable Measurement
3.2.1 Independent Variables
3.2.2 Dependent Variables
3.2.3 Latent Variables
3.2.4 Business performance
3.3 Research Design Matrix
3.3.1 Sampling Technique & Sample Size
3.3.2 Data Collection
3.3.3 Data Cleaning and Treatment of Missing Data
3.3.4 Data Analysis
3.3.5 Data Analysis Techniques – Confirmatory Factor Analysis
3.3.6 Data Analysis Technique Structural Equation Modeling
CHAPTER FOUR: DATA PRESENTATION AND DISCUSSION
4.0 Introduction
4.1 Data Presentation
4.1.1 Data Screening
4.1.1.1 Extreme Value Analysis
4.1.2 Sample Characterization
4.1.3 Normality Test
4.2 Confirmatory Factor Analysis
4.2.1 Unidimensionality
4.2.2 Composite Reliability
4.2.3 Construct Validity
4.2.3.1 Convergent Validity
4.2.3.2 Discriminant Validity
4.3 Structural Equation Modeling - Hypothesis Testing
4.3.1 Null Hypothesis (Ho)
4.3.2 Hypothesis (H1-1)
4.3.3 Hypothesis (H1-2)
4.3.4 Hypothesis (H1-3)
4.4 Discussion
4.4.1 Key Findings and Contributions
4.4.2 Limitations and strengths
4.4.3 Implication for Future Research
4.5 Conclusion
4.6 Recommendations
REFERENCES
APPENDICES
Abstract
This study explored and examined the influence of Entrepreneurial Alertness (EA) on Small to Medium Enterprises (SME) performance within the Central Business District (CBD) of Lusaka. The study participants included 152 entrepreneurs who own SMEs represented by 44.7% females and 55.3% males.
The purpose of the study was to investigate the influence that the EA construct has on SME performance, the association between the first order latent constructs, and to determine which roles of EA in venture performance were appropriate to the participants.
A cross-sectional survey was created using Qualtrics online survey software and sent through email and what’s app to SME’s whose contact details were provided by the Zambia Development Agency. The construct of EA was examined using a 13-point scale (Tang, Kacmar, & Busenitz, 2012). Descriptive statistics were conducted in Statistical Package for the Social Sciences (SPSS) software. Confirmatory Factor Analysis (CFA) was performed in Amos SPSS to verify the factor structure of the observed variables, and to ascertain the validity, and reliability of the measuring instrument. The influence of EA on SME performance, and association between the first order latent variables with performance were tested using multivariate Structural Equation Modeling (SEM).
The study found that the construct of EA has a positive and significant influence on SME performance. As regards the association between the first order latent constructs (i.e., dimensions) and performance, this study demonstrated that only the evaluation and judgment latent construct (dimension) had a significant and positive association. Finally, the study determined that EA appears to be important when a company considers entering a foreign market as a strategy for market development, and EA has a direct impact on strategic change decisions and organizational performance.
The study has implications for education, commerce, and industrial policymakers. Policy initiatives could influence training curriculum and capacity building programs that promote EA to increase entrepreneurial opportunity identifications for increased national performance and contribution.
Future studies could focus on specific industries, such as agriculture, and enhance the sample size.
Key Words: Entrepreneurial alertness, Business Performance, SMEs, Opportunities
Acknowledgements or Preface of Acknowledgements
Words cannot express my gratitude to my research supervisor, Dr. Muwe Mungule for his invaluable patience and feedback. Dr. Mungule generously provided knowledge and expertise throughout the study. The knowledge and skills gained throughout this research will forever be a reminder to me of how much I am indebted to my supervisor. Additionally, this endeavor would not have been possible without the generous support from the Staff and Management of the Graduate School of Business at the University of Zambia.
I am also grateful to the management of the Zambia Development Agency for the support provided in using their database for data gathering.
I am also grateful to my classmates and cohort members, for their editing help, and moral support. A special thanks goes to Mr. Felix Chanda for introducing me to the very basics of Research and simplifying the concept to me. It is an honor to know that this study influenced the creation of his business which I have no doubt with sore to greater heights.
Thank you for your support, family and friends. God bless my dad, Mr. Andrew Raphael Chilota Chirwa, for the foundation laid in my early childhood. My late mother would have been thrilled to see her encouragement pay off.
Lastly, I wish to make a special thanks to my lover, friend, critic and strength for the sleepless nights, the pushing to not give up and soldier on. To my husband, this is dedicated to you. I could not have reached this far had it not been for your belief in my passion and abilities. Financing the whole program from the beginning to the end and above all for giving up yourself in order to see me reach where I am today. You will forever be my source of strength. The Lord bless you and keep you, The Lord lift up the light of his countenance upon you and give you peace. I love you.
List of Tables
Table 1: Latent and Observable Variables
Table 2: Research Design Matrix
Table 3: Minimal Sample Sizes for SEM
Table 4: Sample Extreme Value Analysis
Table 5: Sample Description
Table 6: Tests of Normality
Table 10: Model Fit Indices
Table 11: Regression Weights
Table 12: Unidimensionality Results
Table 13: Composite Reliability
Table 14: Average Variance Extracted
Table 15: Standardized regression values
Table 16: Average Variance Extracted
Table 17: Model Fit Parameters
Table 18: Null Hypothesis Significance Summary
Table 19: Model Fit Parameters
Table 20: H1-2 Significance Summary
Table 21: Model Fit Parameters
Table 22: H1-2 Significance Summary
Table 23: Model Fit Parameters
Table 24: H1-3 Significance Summary
Table 25: Model Fit Parameters
List of Figures, Maps and Illustrations
Figure 1: Confirmatory Factor Analysis Model
Figure 2: Hypothesized Model
Figure 3: Confirmatory Factor Analysis
Figure 4: Null Hypothesis Model I
Figure 5: Hypothesis 1-1 Model II
Figure 6: Hypothesis 1-2 Model III
Figure 7: Hypothesis Model IV
List of Abbreviations and Acronyms
Abbildung in dieser Leseprobe nicht enthalten
CHAPTER ONE: INTRODUCTION
1.0 Introduction
According to the latest report published by the International Trade Centre (ITC) in collaboration with the Zambia Development Agency ZDA on promoting SME competitiveness in Zambia (ITC, 2019), Small to medium enterprises in Zambia represent about 97% of all businesses in the country, contribute 70% of the gross domestic product and represent 88% in employment. This report shows the key role that SMEs play in contributing to production, income and employment levels in the economy.
The government of the republic of Zambia attaches great importance to the growth of SMEs and their contribution to the economy at large. This is the more reason that through ZDA and its partners, the government in its quest to enable Zambia become “a prosperous middle – income nation by 2030” (Government of Zambia, 2006), has put in place various interventions to facilitate the growth of the SME sector. The mandate given to ZDA provides a means through which these interventions can be made such as providing capacity building to SME enterprises by helping them develop entrepreneurship skills and business culture, as well as provide access to financing and markets.
The government's role in promoting SME entrepreneurial engagement is critical to the sector's growth and development. Various entrepreneurial studies have identified some of the elements that have contributed to the SME sector's lack of growth. These include a lack of SMEs-specific policy, finance, and market access, as well as high production costs and regulatory burdens.
The government has made some strides in ensuring that the business environment is conducive to citizens taking advantage of the opportunities available. These efforts have paid off, with Forbes magazine ranking Zambia as the 10th best business climate in Sub-Saharan Africa (ITC., 2019).
Whether the citizenry see these opportunities or not is the basis on which this study is premised.
Entrepreneurship is defined as the scholarly examination of how, by whom, and with what influences opportunities to create future goods and services are discovered, evaluated, and exploited (Scott & Venkataraman, 2000). From this definition, the entrepreneur plays a critical role in identifying the opportunities that eventually impact the performance of the business. Opportunity identification has been an area of study that a number of researchers have explored with interesting outcomes. Entrepreneurs do not cause change (as claimed by the Schumpeterian or Austrian school) but exploit the opportunities that happen in technology and consumer preferences amongst many factors. Entrepreneurs search for change, respond to change and exploit it as an opportunity. Sustained sales growth which in turn improves overall business performance is achieved through balancing of a number of entrepreneurial activities among which balancing of exploration and exploitation of opportunities is important (AbdelShafy, Romme, & Walrave, 2015).
1.1 Background to the Research
While enterprise growth is viewed as a dynamic phenomenon (AbdelShafy et al., (2015), it is globally acknowledged that the growth of SME`s contributes significantly to economic growth and sustainable development (MCTI, Ministry of Commerce, & GRZ, 2008). Because many scholars have discovered that entrepreneurship promotes capital formation, large-scale employment, reduces economic power concentration, generates wealth and wealth redistribution, promotes balanced regional development, increases gross national product and per capita income, improves living standards, and helps promote country export trade, acknowledging the importance of SME contribution to economic and sustainable development is critical.
Sharma, (2019) in coming up with a conceptual framework defined entrepreneurship as the scholarly examination of how, by whom, and with what influences opportunities to create future goods and services are discovered, evaluated, and exploited. Opportunity identification and exploitation are central to the study of entrepreneurship (Zhao, Yang, Hughes, & Li, 2021). Research on cognitive behaviors that influence the identification and exploitation of these opportunities is burgeoning, with recent studies not only focusing on opportunities but on sustainable opportunities (Choongo, Van Burg, Paas, & Masurel, 2016). Whilst a plenitude of research has been focused on opportunity discovery and identification, questions raised by various scholars as to why some individuals are more ‘alert’ to these opportunities are increasingly being addressed through studies on cognitive behavioral phenomenon known as alertness or entrepreneurial alertness (Kirzner, 2009).
Although the number of studies on entrepreneurial awareness has increased, these studies have generally focused their efforts in the western world. There has not been much research conducted in underdeveloped African countries, notably here in Zambia. Furthermore, there are few studies that empirically assess the relationship between EA and firm performance.
As a result, the goal of this study will be to determine the influence of EA on SME performance in Lusaka, Zambia, with an emphasis on SME enterprises in the Central Business District (CBD). In doing so, the researcher aims to make a three-fold contribution to the current body of knowledge. Firstly, exploring the concept of EA and its perceived influence on performance of SMEs with specific applications to the Zambian SME entities. By so doing, the researcher aims to contribute to driving the change Process that is much needed in the wake of government policies shifting towards a well-diversified economy and the achievement of the UN sustainable development goals number 8 and 10 of reducing social exclusion and enhancing productive capacities (Jones & Coleman, 2019).
Secondly, drawing from existing knowledge and research conducted by various researchers like Tang et al. (2012) who concluded that entrepreneurial alertness has three dimensions namely scanning the environment, searching information and making evaluations and judgments about the opportunity or idea. The researcher will use the scale developed from this study as a theoretically justified measure of Alertness (Tang et al., 2012). Thirdly, the study will have implications for the building up of entrepreneurial knowledge for institutions that offer entrepreneurship courses and other institution that offer capacity building and skills training for the SME sector since other studies have proved that this cognitive behavior can be improved through structured training. This study could also have implications for policy makers in the development of policies that will enhance the SME sector.
1.2 The Research Problem
In Zambia, the performance of SMEs is intrinsically linked to the country's GDP. Small and medium-sized firms, for example, are claimed to account for 97 percent of all businesses in the country, contributing roughly 70 and 88 percent to GDP and employment respectively (ITC., 2019). Because this sector accounts for the majority of the business environment, it is usually assumed that improving it will have a significant impact on the country's economic growth and development. The government has made steps in adopting adjustments to numerous policies in an effort to offer tools to promote the SME sector, through the Ministry of Commerce Trade and Industry (MCTI) and the creation of the SME Ministry. Amendments to the ZDA Act, policy, strategy, and regulation improvements, and the establishment of a credit guarantee mechanism guaranteed to offer low-interest loans to the sector (MCTI et al., 2008) are just a few of the achievements.
Despite the important role that SMEs play in Zambia's economy, their failure rate is considerable, with the majority of them failing after only five years of operation (Cooper, 2016). With the surge of foreign competition as a result of open market policies that most countries are implementing, the participation of SMEs in the country may become even more exacerbated. Zambia's economy has relied on copper output for many years. However, economic indications imply that diversification is required if the economy is to improve, especially with copper prices fluctuating and being out of government control. This can be observed in data on total trade, which fell 19.3 percent in the first quarter of 2019 compared to the same period in 2020, owing mostly to reduced copper export revenues and fewer copper Ore imports (Bank of Zambia, 2019). The trajectory remains positive as it is anticipated that Copper prices are expected to average US$9,244.1 per ton in 2021 and rise to US$9,418.4 in 2022 (Bank of Zambia, 2019).
The government's enabling environment, when paired with other factors, opens up the SME sector to potential opportunities that can be exploited through entrepreneurship once discovered. According to Ardichvili, Cardozo, and Ray (2003), success in identifying opportunities leads to the formation of a successful firm. To recognize opportunities in a given environment, one must be 'alert' to them when they arise or are created. The cognitive trait that distinguishes the successful SME from the rest, resulting in a catalytic reaction, is entrepreneurial awareness.
Aim of the Study
The aim of the study was to determine the influence of EA on SME business performance in Lusaka
1.3 Objectives of the research
In order to meet the objectives of this research, the researcher sought to:
i. Evaluate the relationship between EA and performance.
ii. Compare the level of association between the scale items and performance
iii. Establish the role of EA in SME business performance.
1.4 Research Questions
In conducting this research, the following where the research questions were addressed:
i. What is the relationship between business performance and EA?
ii. How does EA influence performance?
iii. What is the role of EA in SMEs as entrepreneurial ventures?
1.5 Significance of the Study
The significance of this study is to:
i. Contribute to the existing body of knowledge on EA as a cognitive behavior which can promote the growth of SMEs.
ii. Help SMEs adopt sustainable entrepreneurial practices.
iii. Contribute to the change process in enhancing entrepreneurship for diversification.
1.6 Scope and location of research
The research was conducted in Lusaka’s CBD, with a focus on SMEs that are registered with the ZDA.
CHAPTER TWO: LITERATURE REVIEW
2.0 Introduction
This chapter introduces the key subjects that formed the basis of this study; these being EA, business performance, the selection of the measurement method for EA, Confirmatory factor analysis (CFA), Structural Equation Modeling (SEM) to investigate the casual relationship between the EA and performance, and finally, hypothesis testing.
2.1 Entrepreneurial Alertness
The concept of EA has its origins in the writings of the famous economist Israel Kirzner who defined it loosely as an “ability to notice, without search, opportunities that have hitherto been overlooked” by others (Kirzner, 1999) or as “a motivated propensity of man to formulate an image of the future” (1985, p. 56). Other researchers followed on with an expansion of the definition of EA as provided by Kirzner that alertness is the ability to notice opportunities without search by contributing to theory via a schema explaining how opportunities may be discovered or enacted (Gaglio & Katz, 2001). Since then, a number of scholars have gone on to expand further on this concept having realized the ambiguity that resulted from the various conceptions about what EA is, its link to opportunity identification, and business performance. For example, Ardichvilli suggested that the process of opportunity identification and the eventual formation of a business begins when the levels of entrepreneurial alertness are heightened by several factors such as personality traits, social networks and prior knowledge (Ardichvili et al., 2003). On the contrary (Blackburn, Hart, & Wainwright, 2011) found in their research that the size and age of the enterprise performance dominated more than the strategy and personality traits of the owners.
EA is of critical importance as a concept of opportunity seeking (Valliere, 2013) although not much attention has been given to this concept worldwide. Opportunity seeking is critical to every entrepreneur as it is through this process that the activities of the entrepreneur are extended eventually resulting in growth. It must be noted however that opportunities within the business environment will not just present themselves. It is the cognitive ability of entrepreneurial alertness which will cause the identification of these opportunities in order to turn them into business activities (Pulka, Ramli, Bin, & Bakar, 2018).
In order to better understand the concept of EA, attempts have been made by researchers to develop measures to use to study EA. One such study provided a theoretically justified, and validated measure of EA positing that it consists of three distinctive elements; scanning and searching for information, connecting previously disparate information, and making evaluations regarding the existence of potential business opportunities (Tang et al., 2012). Various scholars who have studied the concept of EA, seem to agree that there are elements that play a key role in developing EA. Sharma, (2019) identified six elements among which is cognitive ability. Amato, Baron, Barbieri, Jocelyn, and Pierro, (2016) concluded that these elements; locomotion, assessment, scanning, association and evaluation had a direct influence on entrepreneurial ability (Alertness). Valliere, (2013) attributed the use of unique schemata in making sense of the business environment. In so doing they recognized three antecedents which form the basis on which EA is developed.
Despite having many studies undertaken to understand the concept of EA, a number of gaps have been identified from the various literature reviewed. Firstly, much of the studies done on EA and its influence on SMEs, have been conducted in developed economies save for a few which have been done in developing countries (Isaga, 2018), (Fatoki & Oni, 2015) with some studies indirectly referring to the concept (Kamuri, 2019). Studying the concept from the perspective of the developing nations will broaden the knowledge base regarding the concept of entrepreneurial alertness (Adomako, Danso, Boso, & Narteh, 2018). Further, most of the studies have concentrated on establishing the relationship between opportunity identification and exploitation with not much consideration given to the influences of EA on business performance and specifically that of SMEs. Prior research has shown that successful entrepreneurs utilize cognitive abilities of entrepreneurial alertness to discover opportunities within the business environment (Urban, 2019).
2.2 The Role of Entrepreneurial Alertness in Entrepreneurial Ventures.
At the helm of any entrepreneurial journey is the goal of growth and profitability. As such, entrepreneurs create ventures as a response to the opportunities created within the environment. The pursuit of opportunities and new or relevant practices culminates into entrepreneurial ventures with the ultimate goal of growth and profit. Various scholars have studied the construct of EA. Through these studies, several conclusions have been drawn regarding the role that EA plays in entrepreneurial ventures.
Content analysis was utilized to analyze literature in order to better understand the role of EA on SME performance. The goal of content analysis is to develop and improve an understanding of the role that EA plays on SME performance in research by looking at the key research journals available. To conduct the content analysis, keyword analysis was conducted using the terms Entrepreneurial awareness, SME performance, and Performance, as well as the number of citations found in the text. The researcher downloaded all publications and reviewed them to identify keywords, main themes explored, and main results and conclusions.
Entrepreneurial alertness is regarded as a subjective factor that influences individuals' decision to become entrepreneurs (Arenius & Minniti, 2014) linked to entrepreneurial behavior and eventual performance of the business. Perceptual factors were substantially connected with new business development across all nations and genders in the study of Arenius and Minniti (2014), which used a large sample of individuals from 20 countries.
Other research investigated the function of entrepreneurial intelligence in encouraging entrepreneurial behavior. On the one hand, Tang (2008) found that entrepreneurial alertness is linked to self-efficacy in completing new venture formation responsibilities and duties. Similarly, entrepreneurial creativity is driven by alertness and other essential characteristics, which is becoming increasingly significant due to its link to entrepreneurial behavior (Ko & Butler, 2007). Furthermore, entrepreneurial alertness appears to be important when a company considers entering a foreign market (Kontinen & Ojala, 2011).
Several research looked at EA as a talent that can be cultivated through entrepreneurship education. Solesvik (2013), for example, found that students in entrepreneurship education who have entrepreneurial alertness assets have a more entrepreneurial mindset. Similarly, entrepreneurship education increases people's awareness of the process of identifying opportunities (Ghasemi & Rowshan, 2016); (Hu & Ye, 2017); Li et al., 2015). Furthermore, Westhead and Solesvik, (2015) found that female students who had received entrepreneurship training and displayed entrepreneurial alertness had a higher entrepreneurial ambition.
Finally, there exists a collection of publications in which EA is viewed as an organizational component that affects a firm's performance and provides a competitive advantage. Entrepreneurial alertness has a direct impact on strategic change decisions and organizational performance, according to Roundy, Harrison, Khavul, Pérez-nordtvedt, and Mcgee (2018). Other studies (Adomako et al., 2018); (Rezvani, Lashgari, & Journal, n.d.); (Cohen, 1992b); (Urban, 2019); (Zanella, Castro Solano, Hallam, & Guda, 2019) found similar results.
Based on the above review of literature, the role that EA plays in Entrepreneurial ventures can be summarized as follows:
i. EA is a factor or construct that influences individuals' decision to become entrepreneurs linked to entrepreneurial behavior and eventual performance of the business.
ii. EA is linked to self-efficacy in completing new venture formation responsibilities.
iii. EA appears to be important when a company considers entering a foreign market as a strategy for market development
iv. EA as a construct boosts people's awareness of the process of recognizing opportunities if it is included in the higher education curriculum or entrepreneurial education.
v. EA has a direct impact on strategic change decisions and organizational performance.
2.3 Business Performance
Demand for improved competitiveness as a result of increased globalization, makes the need to improve business performance as an area of interest for entrepreneurs. Simply put, improvement in business performance indicates an achievement of the strategic goals set by an entity in its quest to obtain competitive advantage. The importance of defining what business performance is, was discussed in a study conducted by Venkatraman and Ramanujam, (1986) in which it was emphasized that defining business performance proved to be a test for strategy, this being the direction which guides how the business or entity performs. Unfortunately, there seems to be no clear definition of what business performance is as evidenced by the various research conducted in which business performance is defined more by its characteristics rather than what it is.
Business performance measurement is important for entrepreneurs to turn their ideas into strategic results that are used for the purposes of monitoring progress, communicating expectations etc. Various scholars agree that the measurement of SME performance is multi-dimensional. That is to say, that measurement of business performance can be categorized into two types namely: objective and subjective measurement. Many scholars have studied these two types of business performance measurements (Vij & Bedi, 2016), (Zulkiffli, Atikah, & Perera, 2012), (Dawes, 1999), Singh, Darwish, & Potočnik, 2016). Despite the many different studies conducted on these, there is no common consensus when it comes to measurement of business performance.
Subjective measurement of performance comprises employee turnover, customer satisfaction, employee satisfaction, process innovation, product quality, sales or revenue growth and increase in market share (Vij & Bedi, 2016). On the other hand, objective measurement consists of return on asset, return on sales, earnings per share, return on net worth, asset growth etc (Zulkiffli et al., 2012). This stands out clearly as seen from the various ways in which SMEs are categorized from country to country. In Zambia, the Micro, Small and Medium Enterprise Development Policy (MSME), categorizes enterprises based on the total investment, annual turnover and the number of persons employed by an entity (MCTI et al., 2008). Different countries define these enterprises based on the level of turnover and the number of people employed by firms in this sector with some adding the level of investment as a measure. By categorizing SMEs in such a manner, it implicitly entails that an entity can be considered as having grown from one level to another by virtue of any of these variables increasing. This is one school of thought amongst the many that have been suggested by different scholars. Selvam, Gayathri, Vasanth, Lingaraja, and Marxiaoli, (2016) developed a subjective model with nine determinants of performance namely profitability performance, growth performance, market value performance of the firm, customer satisfaction, employee satisfaction, environmental audit performance, corporate governance performance and social performance (Venkatraman & Ramanujam, 1986). Cicea, Popa, Marinescu, and Ștefan, (2019) created a macroeconomic model for SME performance which identifies nine variables classified in economic, social, political and demographic types of environments to determine influence over SME performance.
The choice of measures such as employment growth, turnover and profitability seem to be easily accepted because of the ease with which this information can be compared across various SMEs (Blackburn et al., 2011). Despite the differences in measurement of firm performance, SMEs must be alert to the many opportunities that exist or are created in the environment that they operate in, more so because of the dynamism that is created with changes in technology and other factors (Teh et al., 2018).
To be able to exploit opportunities within the business environment, certain cognitive abilities are highlighted as key to achieving performance. The link between SME performance and alertness to opportunities in the business environment, has remained a subject of different studies. Isaga (2018) combined personality and cognitive characteristics to understand the relationship between the entrepreneur’s characteristics and the performance of an SME whose outcome was that these characteristics have an influence on the performance of an SME.
For the purposes of this study, the level of turnover will be used as measure of performance.
2.4 Theoretical Framework
The study was founded on Kirzner’s theoretical concept on EA. According to Montiel-Campos, (2021), Kirzner indicated that entrepreneurial alertness is concerned with abilities to identify various entrepreneurial opportunities that other individuals keep on overlooking. A study by Tang et al. (2012) indicated that the entrepreneurial alertness process constitutes of three stages, namely search and scanning, information analysis and judgement and valuation. In all these stages, the goal of the individual is to improve the original business idea through making appropriate adjustments and changes.
For instance, when a piece of new information emerges in the analysis stage, then the initial business opportunity may be changed to accommodate the new information as a way of making it better in the long run. The entire process helps to determine the commercial viability of a certain business idea before an entrepreneur can invest any fund in it.
One of the ways an organization's performance can be positively influenced is through innovation. Montiel-Campos, (2021) revealed that entrepreneurial alertness facilitates networking capabilities in an organization, which are critical in the identification of new business information, thorough scanning of the external and internal organization's business environment. Adomako et al. (2018) indicated that increased utilization of business and social networking capabilities enhances the ability of entrepreneurial alertness acting as a form of the driver of organizational success. Using EA, SMEs can identify business opportunities that can be innovated and transformed into profit-making ventures in the long run.
Interesting to note, Adomako et al. (2018) indicated Kirzner revealed that entrepreneurial alertness has the capacity of influencing the form of transactions that a business will enter in the future. This means that business transactions among SMEs, to a greater extent, can be determined by alertness and influencing the long-term organizational productivity and profitability. Valliere (2013) indicated that alertness involves a person's cognitive abilities to process prior experiences and knowledge, recognizing patterns within an environment, processing of information, plus engagement in various social interactions. SMEs owners have to have high cognitive capabilities to be alert to emerging opportunities.
The Kirzner theoretical framework aided in understanding how EA shapes different aspects of SMEs performance
2.5 Confirmatory Factor Analysis
Confirmatory factor analysis (CFA) is a sort of structural equation modeling (SEM) that focuses on the links between observable measurements and latent variables, or factors (Byrne, 2020). The number of underlying dimensions of the instrument (factors), and the structure of item–factor correlations are verified using CFA (factor loadings) as verified by (Suhr, 2014). CFA is used as the principal analytic approach to answer research questions (e.g., construct validation). CFA is employed as a prelude to SEM (Timothy, 2020).
A CFA model is depicted in Figure 1. Scanning & Searching, Association & Connection, and Evaluation & Judgment are the latent variables. The thirteen variables observed are responses to propositions on five Likert measurement scale. The number "1" indicates that the regression coefficient has been set to 1. This is done to keep the number of parameters estimated in the model to a minimum. The graphic representation represents the proposed model, which will be tested to see how well it fits the data.
Abbildung in dieser Leseprobe nicht enthalten
Figure 1 : Confirmatory Factor Analysis Model
As shown in the table below, each latent variable is measured using observable variables:
Table 1 : Latent and Observable Variables
Abbildung in dieser Leseprobe nicht enthalten
2.6 Structural Equation Modeling
Structural equation modeling (SEM) is a statistical methodology that takes a confirmatory (i.e., hypothesis-testing) approach to the analysis of a structural theory bearing on some phenomenon (Byrne, 2020). SEM sets out to understand the patterns of correlation/covariance among a set of variables and to explain as much of their variance as possible with the model specified (Suhr, 2006).
A structural equation model has two major components: (1) the measurement model (i.e., a CFA model), which specifies the number of factors, how the various indicators are related to the factors, and the relationships among indicator errors; and (2) the structural model (i.e., a CFA model), which specifies how the various factors are related to one another (e.g., direct or indirect effects, no relationship, spurious relationship), (Schreiber, Stage, King, Nora, & Barlow, 2010).
Structural equation modeling was selected as the best multivariate analysis method largely because of the reasons outlined in the book by Suhr, (2006) in which is described that SEM assumes multivariate normality, is flexible and comprehensive, requires formation of a model to be estimated and tested, incorporates both observed and unobserved variables, explicitly specifies errors and uses multiple tests to examine model fitness. The formation of a model in SEM entails that the model must be tested for fitness.
Current thinking and research on fit indices for SEM suggests fit indices that are regarded as most informative indices available to researchers (Hooper, Coughlan, & Mullen, 2008). These include chi squared test, RMSEA, GFI, AGFI, the RMI and SRMR (Hu & Bentler, 1999).
For the purposes of this study, fit indices were obtained for Chi square, GFI and RMSEA.
Whilst SEM is seen to be a better method than the traditional forms of regression analysis, it is not without issues. Hoe (2008) highlighted issues with SEM such as suggesting a sample size of 200 for SEM, standard fit indices values, standardized paths, Unidimensionality test and other various approaches.
In studying the influence of EA on SME performance, the researcher being a novice relied on the already determined table according to the study done by Cohen (1992b) in determining the best sample size to perform structural equation modeling.
2.7 Hypothesis Testing
For the purposes of this study, the measurement scale developed by Tang et al. (2012) was used to measure the construct of EA.
Given the above review of literature, the following hypotheses were proposed:
Null Hypothesis:
H0: Entrepreneurial alertness does not have a significant influence on SME performance
Alternative Hypothesis:
H1: Entrepreneurial alertness has a significant positive influence on SME performance
Further Hypothesis:
H1-1: Items of the Scanning and Searching latent construct have a significant positive influence on Performance
H1-2: Items of the Association & Connection latent construct have a significant positive influence on Performance
H1-3: Items of the Evaluation and Judgment latent construct have a significant positive influence on Performance
CHAPTER THREE: METHODOLOGY
3.0 Introduction
This chapter focuses on the research design and the methodology used in conducting the study. The chapter discusses the independent and dependent variables, hypothesis testing, research design, measurement instrument, sampling and sample size, data collection techniques and data analysis addressing the three objectives:
i. To evaluate the relationship between entrepreneurial alertness and performance.
ii. To compare the level of association between the 13 scale items (Independent Variables) and performance (Dependent Variable)
iii. To establish the role of entrepreneurial alertness in SME business performance.
And the research questions:
i. What is the relationship between business performance and entrepreneurial alertness? (In reference to the correlation results)
ii. How does entrepreneurial alertness influence performance?
iii. What is the role of entrepreneurial alertness in SMEs as entrepreneurial ventures?
The chapter further discusses the hypothesized model, independent and dependent variables, hypothesis tested, research design matrix, measurement instrument, sampling and sample size, data collection techniques and data analysis.
3.1 Hypothesized Model
The hypothesized model for the study is shown in Figure 1 below. It is based on the EA measurement scale developed by Tang et al., (2012).
Abbildung in dieser Leseprobe nicht enthalten
Figure 2 : Hypothesized Model
The model is designed as a prediction of the influence that EA is purported to have on SME business performance. The model depicts the thirteen factors that infer EA as an unobservable variable and the observable variable performance. The thirteen variables are categorized into three constructs of alertness namely: Scanning and Searching, Association and Connection, as well as Evaluation and Judgment. The independent and dependent variables are discussed further in the next section.
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- Citar trabajo
- Jessie Chirwa (Autor), 2023, The Influence of Entrepreneurial Alertness on Small to Medium Enterprise Performances, Múnich, GRIN Verlag, https://www.grin.com/document/1336097
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