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\title{Factors Affecting the Successful Growth and Survival of Small and Micro Enterprises (SMEs) in Zimmerman Ward, Nairobi County -Kenya}
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             \author[1]{Daniel Njoya  Ndungu}

             \affil[1]{  Kenyatta University}

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\date{\small \em Received: 13 December 2016 Accepted: 4 January 2017 Published: 15 January 2017}

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\begin{abstract}
        


Small and micro- enterprises play an important role in developing a country even though they are not given adequate attention and have been biased towards larger and listed enterprises. This study investigates the factors affecting the successful growth and survival of small and micro- enterprises in Zimmerman ward, Nairobi County. The survey utilized a descriptive research design whereby descriptive statistics based on frequency tables and graphs provided information on demographic variables. Data was collected through questionnaire instrument. Convenience sampling technique was used because of the rationale that respondents were easily accessible. Statistical Package for Social Sciences 20.0 was used to analyze and present results. Techniques used included percentage analysis, samples and mean analysis. Inferential statistics (Pearson Product-Moment Correlation Coefficient) and multiple regressions were then applied to determine prediction level of the variables.

\end{abstract}


\keywords{criterion variable, contingency theory, motivation, performance, competence.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction a) Background to the Study}]{Introduction a) Background to the Study}\par
here is an increasing demand for Small and Micro Enterprises (SMEs) in most nations. Kenya notwithstanding is not immune to this norm. SMEs play an important role in developing a country even though they are not given adequate attention and have been biased towards larger and listed enterprises. Available data show that in 2003 SMEs in Kenya employed 3.2 million people and accounted for 18 percent of the national GDP. Currently, a number of issues are emerging posing serious challenges to the SMEs in Kenya. Understanding the problems and challenges are fundamental solutions to expand and strategize SMEs to future economic objectives of the country. 
\section[{b) Statement of the Problem}]{b) Statement of the Problem}\par
Small and Micro enterprises operate in the same environment as their larger counterparts, but without the associated benefits like adequate capital and extended human resources of the larger organizations, \hyperref[b15]{Smit and Watkins (2012)}. This paper attempts therefore to look into the factors affecting the Author: Kenyatta University. e-mail: danielnjoya@gmail.com c) General Objective\par
The study investigated the factors affecting the successful growth and survival of Small and Micro enterprises (SMEs) in Zimmerman Ward, Nairobi County-Kenya in a human resource perspective.\par
i. Specific Objectives In order to fulfill objectives, this research intended: i. To determine whether appropriate human resource management affects the successful growth survival of small and micro enterprises (SMEs). ii. To investigate whether Effective entrepreneurship affects the successful growth survival of small and micro enterprises (SMEs). iii. To determine whether application of information technology affects the successful growth survival of small and micro enterprises (SMEs). 
\section[{d) Hypotheses}]{d) Hypotheses}\par
To examine how each of the criterion variables influences the response variable, the following null hypotheses were tested: H 1 : There is a negative relationship between inappropriate human resource management (HRM) and performance. H 2 : There is a positive relationship between effective entrepreneurship and performance of SMEs. H 3 : There is a positive relationship between application of information technology (IT) and performance. 
\section[{e) Significance of Study}]{e) Significance of Study}\par
According to \hyperref[b10]{Mead and Liedholm (1998)}, there are more SMEs closures than expansions, with approximately only 1\% of micro enterprises growing from five or less employees to ten or more. Therefore upgrading the roles of SMEs sector would improve economic growth through increasing competitiveness, generating employment and redistributing income. 
\section[{f) Scope of the Study}]{f) Scope of the Study}\par
The study covers various factors affecting successful operations of SMEs in Kenya. The aim of this research is to investigate factors affecting successful growth and survival of small and micro enterprises in Zimmerman ward, Nairobi County -Kenya. The contingency theory coined and developed \hyperref[b4]{Fiedler (1964)} was used as the theoretical framework. The conceptual framework covered in empirical review tests whether the most appropriate structure for a business or organization is the one that best fits a given operating contingency, e.g. technology. 
\section[{g) Limitation of study}]{g) Limitation of study}\par
The study had several limitations. This research was primarily limited by its small sample size. The sample could have been expanded by including the rest of the wards in Nairobi County in data collection and analysis. An earlier start in data collection would have increased the time needed to survey more participants. There was also suspicion from employees to provide information in case of victimization. However, the study strived to fully explain the intention of the study and assured confidentiality. 
\section[{h) Organization of the study}]{h) Organization of the study}\par
The first chapter projects importance of the research and provides aspects like basic back ground information, statement of the problem, significance of the study , research objectives and hypothesis, scope and limitations of the study among others. Chapter two is the Literature review which provides the contingency theory used and how it helps construct the conceptual framework in the empirical review. Chapter three is the methodology and provides target population, sample size, research design, data collection and analysis methods. Finally chapter four is research findings which provide descriptive statistics and inferential statistics. 
\section[{Chapter Two}]{Chapter Two}\par
II. 
\section[{Literature Review a) Introduction}]{Literature Review a) Introduction}\par
This chapter will review literature related to the research. This will include analysis of contingency theory by \hyperref[b4]{Fiedler (1964)} who postulates that the most appropriate structure for an organization is the one that best fits a given contingency or environment. This section also presents the conceptual framework and summary of literature and research gap. 
\section[{b) Theoretical Review}]{b) Theoretical Review}\par
Numerous studies have been conducted to investigate the process of harmonization of organizational structures and environmental conditions versus modifying the relationship between organizational sizes and structure. Notwithstanding, the contingency perspective emphasizes the fit between business strategy and HRM policies and strategies and hence create the process of business strategies being followed by HRM policies in determining business performance. 
\section[{i. Contingency Theory}]{i. Contingency Theory}\par
Most significantly, \hyperref[b2]{Donaldson (2001)} posits that the key element of structural contingency theory is that organizational performance results from a fit between characteristics of structural organization and environment i.e. contingency factors. \hyperref[b4]{Fiedler (1964)} similarly argued that there is no "best way" for organizational structure. It is common to distinguish between an organization's general environment and the task environment. He additionally describes the task environment as everything that bears on the immediate achievement of the organizational goals e.g. state -ofthe -art technology, leadership, market structures, human resource management, sales networks and source of finance. \hyperref[b16]{Sorge (2002)} reiterates that to investigate the whole environment would be time consuming and expensive since it is too broad and complex. He urges that well -argued selections should hence be made about which criteria to focus on. 
\section[{c) Empirical Review}]{c) Empirical Review}\par
According   {\ref (1995)} propose that small firms make extensive use of job-tryouts, which are inexpensive and very well suited to evaluate the actual fit of a person with the (implicit) demands of the job. The personal atmosphere of small firms is reflected in the high use of informal procedures like job posting and bidding. In the same way, Huiban and Bouhsina (1998) suggest that HRM aims at attracting, developing and retaining human resources and for many small firms, human resources are the core of their competitive advantage. From the review of literature, the following hypotheses emerge;H 1:\par
There is a negative relationship between inappropriate human resource management (HRM) and performance. 
\section[{ii. Effective Entrepreneurship}]{ii. Effective Entrepreneurship}\par
Adams and Neeley (2002) argue that many SMEs owners or managers lack managerial training and experience. They develop their own approach through the process of trial and error. The authors therefore claim that the management style is likely to be more intuitive than analytical. The managers or owners are consequently more concerned with the day to day -to -day operations than long term issues. The approach is hence more opportunistic than strategic in its concept. From the review of literature, the following hypotheses emerge; H 2: There is a positive relationship between effective entrepreneurship and performance of SMEs. 
\section[{iii. Application of Information technology}]{iii. Application of Information technology}\par
Introduction to information systems (IS) provide opportunities to SMEs for obtaining added value through exploitation of information resource. \hyperref[b9]{Levy and Powell (2001)} state that SMEs align there IS strategy to the strategic context defined by the level of customer dominance, to capture both cost advantages and values added benefits. Likewise, it also adds strategic competitive advantage. From the Literature, the following hypothesis is tested; H 3: There is a positive relationship between application of information technology (IT) and performance. 
\section[{d) Growth of SMEs}]{d) Growth of SMEs}\par
Huselid and Becker (1996) suggested that the examination of alternative dependent variables should provide important confirmatory information on the association between HR practices and firm performance. It is very likely that various HR practices affect different measures of performance differently. In this research, we use development of HRM strategy as an indicator of growth of SMEs. The theoretical literature implies that HRM practices increases productivity by increasing employees' skills and motivation. Consequently, HRM practices contribute to business objectives through strategic innovation and also in technical competence. HRM strategy consists of training or development of employees' decision making involvement, support of personal initiative and goal communication.\par
Owner's and employees' human capital serve as the moderator of the relationship between HRM and success brought about by reasons; HRM serves as a tool to increase the firm specific skills that are not available in the labor market. On the other hand, better educated and qualified employees should be able to increase the firm's specific skills and knowledge faster than less educated and qualified employees.\par
Human capital theory proposes that employees make rational choices regarding investments in their own human capital. The theory postulates that individuals make rational choices whether or not they want to invest more of their time, effort and money in education, training and experience. 
\section[{e) Summary of Literature and Research Gap}]{e) Summary of Literature and Research Gap}\par
The contingency perspective argues that the relationship between the independent and the dependent variables differs when the contingency variable is added, and most studies are concerned with the meaning of internal and external fit and with how to achieve them, such as fitness of HR practices and various organizational and environmental factors, \hyperref[b4]{Fiedler (1964)}. This study will be conducted at individual level rather than organizational level in view of SMEs in Zimmerman ward in Nairobi County. As with many developing countries, there is limited research and scholarly studies about the SMEs sector in Kenya. The major practitioner knowledge gap will address the factors that influence performance of SMEs and relationships between the variables. 
\section[{f) Conceptual framework}]{f) Conceptual framework}\par
Figure  {\ref 2}.1 shows relationships between the various key independent variables and the criterion variable and the outcome as discussed in the literature review. 
\section[{Independent Variables Dependent Variable}]{Independent Variables Dependent Variable}
\begin{quote}
Figure 2\end{quote}
 
\section[{.1: Conceptual Framework}]{.1: Conceptual Framework}\par
The conceptual framework of the study was constructed from reviewed literature and relevant research hypotheses. The frame work shows that a relationship exists between the independent variables (Appropriate HRM, Effective Entrepreneurship and Information Technology) and dependent variable (Growth of SMEs) which is instigated by HRM strategy and moderated by owner's and employees' human capital.\par
Chapter Three III. 
\section[{Research Methodology a) Introduction}]{Research Methodology a) Introduction}\par
This chapter describes the research design explored, the research methodology and sampling design of the study. Specifically, it details sample selection and the procedure followed when gathering data. The chapter concludes with instrumentation, data collection and analysis. 
\section[{b) Research Design}]{b) Research Design}\par
A descriptive research design was used for this study. A survey was administered to a selected sample from a specific population.  {\ref Robson (1993)} suggests that the term 'survey' is commonly applied to a research methodology designed to collect data from a specific population, or a sample from that population, and typically utilizes a questionnaire or an interview as the survey instrument. The researcher chose a descriptive research methodology and designed a questionnaire survey instrument to assess the factors affecting the successful growth and survival of small and micro enterprises in Zimmerman ward, Nairobi County-Kenya. 
\section[{c) Target Population of the Study}]{c) Target Population of the Study}\par
Target population is the group or the individuals to whom the survey applies. The target population should be represented as a finite list of all its members, Kitchenham and Pfleeger  {\ref (2002)}. In research methodology, 'population' does not refer to the population of a country, but rather to the objects, subjects, phenomena, cases, events or activities specified for the purpose of sampling;  {\ref Robson (1993)}.\par
The study targeted managers/owners of small and micro service enterprises (SMEs). The study used a large sample (N= 33) so that the sampling distribution of mean approximate to a normal distribution. This spanned across such SMEs as Cyber Cafes, Hair Salon and hair Cut, Vending shops, clothing shops, car wash, butcheries, Mpesa shops, Video and CD lending/selling shops, Electric shops, Tire repair shops, hard wares, cobblers and shoe shiners, among others.  
\section[{d) Sampling Technique}]{d) Sampling Technique}\par
For the survey, a non probability sampling design in the form of convenience sampling technique was used to record responses. This was considered appropriate to gather data because of the rationale that respondents were easily accessible, their availability as well as being less time consuming and inexpensive to gather research information. Welman and Kruger (2001) argue that the advantage of non-probability samples is that they are less complicated and more economical than probability samples. The authors reiterate that convenience sampling involves collecting information of members of the population that are near and readily available for research purposes and is usually done for pilot survey. Besides that, it is not representative of the population and therefore the results are not generalized to other entities and consequently, the external validity of the study was compromised. 
\section[{e) Data Collection Methods and Research Procedures}]{e) Data Collection Methods and Research Procedures}\par
For the survey, a cross-sectional survey design using a quantitative method was conducted to determine the relationship between independent variable (performance of SMEs). The data collection methods involved included: primary data which was basically from the questionnaire in the form of interviews and the secondary data was from journals, annual reports, conferences, internet, books, magazines, etc. Respondents were the business owners or those involved in the start-up and day to day running of these enterprises. 
\section[{f) Data Analysis Methods}]{f) Data Analysis Methods}\par
The data was gathered, analyzed and presented using descriptive statistics. Descriptive statistics based on frequency tables and graphs were used to provide information on demographic variables. Statistical Package for Social Sciences (SPSS) version 20.0 was used for the purpose of analyzing and presenting of results. Techniques used included percentage analysis, samples and mean analysis. Inferential statistics (Pearson Product-Moment Correlation Coefficient) and multiple regressions were then applied to determine prediction level of the variables. 
\section[{Chapter Four}]{Chapter Four}\par
IV. 
\section[{Research Findings a) Introduction}]{Research Findings a) Introduction}\par
This chapter describes the empirical analysis of the data collected. The analysis among other things details the demographic characteristics of the respondents, descriptive statistics, and Inferential Statistics (Pearson Product Moment Correlation). Standardized multiple regressions were then employed to the analyzed data to determine whether the group of factors proposed together predict the factors affecting successful growth and survival of SMEs in Zimmerman ward, Nairobi County. 
\section[{b) Analysis of the Response Rate and Descriptive statistics}]{b) Analysis of the Response Rate and Descriptive statistics}\par
A total of 33 questionnaires were returned out of the 40 questionnaires distributed to respondents which made the response rate 82.5\%, an acceptable figure to make the study rigorous and generalizable. Demographic data was collected from seven questions relating to the managers characteristics and his or her role in the business. This is presented in table 4.1.The results indicate that majority of the sample (n=17) or 51.5\% were males while the remaining (n=16) or 48.5\% were females. This shows roughly that there is an equal distribution of business owners/managers for both genders in Zimmerman ward, Nairobi County.\par
The major portion of the respondents 14(42.4\%) was in the range of 21-30 years, 12(36.4\%) of the respondents were in the range of 31-40 years, while 4(12.1\%) in the range 41-50 years. 2(6.1\%) were in the range 51 years and above whilst the lowest frequency was 20 years and below with 1(3\%). Considering that the major portion of the respondents falls in the range of 21-30 years, it can be deduced that most owners/managers of SMEs are young and inexperienced with businesses startups based on trial and error. The SMEs tends to lose managers/owners at the age of 51 years or above. This can be adduced from the competitive nature of SMEs which needs vibrant, young and energetic managers who can easily change with hostile business environment. From the results, it can be empirically observed that the majority of the respondents had the highest level of education as O' Level with 12(36.4\%) closely followed by Certificate holders with 9(27.3\%). Diploma holders tied with "other" (which represented primary school leavers) at the bottom with 6(18.2\%). This shows that most SMEs are owned or managed by O' level and Certificate graduates in Zimmerman ward, Nairobi County.\par
As for the kind of business, majority of the respondents operated in trade sector with 16(48.5\%) followed by the service industry with 14(42.4\%). Textile industry had the least number of respondents; 14(42.2\%). Trading activities seem from analysis to be the favored form of SMEs maybe because of the ease of starting and the need of simple management skills to take off.\par
Considering the Length of time business has been in operation, it can be inferred that the majority of SMEs businesses were between 1 year -5 years with 17(51.5\%). This is followed by businesses in the age bracket 6 years-10 years old with 10 (30.3\%). In the same way, less than 1 year old businesses follow with 3(9.1\%) while 11 years -15 years old business come second to last with 2(6.1\%). At the bottom, businesses with 21 years or longer in age hold 1(3\%). Interestingly, not a single business was 16 years -20 years old. This can be due to change of business or quitting the business altogether.\par
As for managerial or job experience, 25(75.8\%) had previous employment and the rest; 8(24.2\%) had no previous experience. It can therefore be inferred that the majority of the managers or owners of these SMEs have experience which play a major part of running and survival of these enterprises.\par
Sole proprietorship played the bulk of business ownership of the SMEs with 25(75.8\%) with joint ownership and family business enterprises tying at the bottom with 4(12.1\%). It can therefore be inferred that majority of the owner/managers in the survey were driven to set-up their business by financial motives, the desire to be independent and job satisfied.\par
Descriptive statistics were used in determining the central tendency of the data and trend of variables involved in Contingency theory. Descriptive statistics inform of standard deviation and arithmetic mean for independent variables were computed which showed that the means for the use of; appropriate HRM, effective entrepreneurship and Information Technology (IT) ranged from a low of 17.5152 to a high of 27.1515. It can therefore be inferred from the data that use of effective entrepreneurship is the basic line of defense for the survival of SMEs with a mean of 27.1515. This is mainly because of previous experience from a different or family business.\par
There is average use of HRM practices portrayed by a mean of 19.5455 due to the low number of employees in these businesses (Mostly less than 10). Information Technology has not yet penetrated on this sector and seems as irrelevant at this point since most respondents seemed oblivious of the need of items such as computers which held no immediate bearing to the business and its profitability. These businesses are small and skirt on simple management skills. Use of IT had the lowest mean of 17.5152. 
\section[{c) Inferential Statistics}]{c) Inferential Statistics}\par
In this subsection, results of inferential statistical techniques used in the research are presented. Pearson Product Correlation Coefficient was computed to obtain relationships.\par
Consequently, standard multiple regressions was used to determine whether the independent variables predicted the factors posed as challenges to successful growth of SMEs in Zimmerman ward, Nairobi County.\par
i. Correlation Pearson product Moment Correlation Coefficient was computed for determining the direction of the relationship between the independent variables; appropriate use of HRM practices, use of effective entrepreneurship and Information Technology (IT). The above data illustrates that there is a small and negative correlation between Use of appropriate HRM and the development of HRM strategy with an r= -0.422. Squaring the "r" indicates 17.80 per cent shared variance between the two variables. Use of effective entrepreneurship helps to explain nearly 22.2784 percent of the variance in respondents' challenges in the development of HR strategy in the SMEs.\par
The data also shows that there is a strong correlation between the use of information technology and use of appropriate HRM with an r=0.337 and thereby explaining 11.3569\% of shared variance. In addition, the table also shows a strong positive correlation between Use of IT and use of appropriate HRM with an r=0.365 explaining 13.3225\% of shared variance between the two variables. 
\section[{ii. Standard Multiple Regressions}]{ii. Standard Multiple Regressions}\par
In this regression, all the independent (or predictor) variables are entered into the equation simultaneously. Each independent variable is evaluated in terms of its predictive power, over and above that offered by all the other independent variables. This approach also told us how much unique variance in the dependent variable each of the independent variables explained.\par
Using Tubachnick and Fidell's (2001) table, one can determine how long independent variables will be included in the multiple regression analysis. In our study, since we have three independent variables, the critical value then becomes 16.27. Looking at the model summary box, (in SPSS Output) and checking for R square i.e. 0.6474 which is expressed as a percentage to be 41.9126\% meaning that 41.9126\% of the variance in Human resource strategy is explained by the model. This means that the model has a moderately good fit.\par
Looking at data under standardized coefficients, IT application has the largest beta coefficient of 0.575. This means that this variable makes the strongest unique contribution to explaining the dependent variable. HRM practices have a lower value which indicates less contribution to the model. Entrepreneurship makes the lowest contribution to the model with 0.404. This is statistically significant contribution as indicated by sig. F change value for this line (.000). The ANOVA table that the model as a whole; including all blocks of variables is significant F (4,419), p<.0005. The beta values obtained in this analysis can also be used for other more practical purposes than the theoretical model testing. The standardized beta values indicate the number of standard deviations that scores in the dependent variable would change if there was one standard deviation unit change in the predictor. The beta values represented the unique contribution of each variable when the overlapping effects of all other variables are statistically removed. 
\section[{Chapter Five}]{Chapter Five}\par
V. 
\section[{Summary, Conclusion and Recommendation a) Introduction}]{Summary, Conclusion and Recommendation a) Introduction}\par
This chapter will discuss the results obtained in chapter four in greater detail and also the Summary of the study. The section will conclude with recommendations. 
\section[{b) Summary}]{b) Summary}\par
This research study had one major objective, to investigate the factors affecting the successful growth and survival of small and micro enterprises (SMEs) in Zimmerman ward, Nairobi County-Kenya, in a human resource perspective. The researcher chose a descriptive research methodology and designed a questionnaire survey instrument to assess factors affecting the successful growth and survival of SMEs. The study targeted managers/ owners of small and micro service enterprises, and used a large sample (N = 33) so that the sampling distribution of mean approximates to a normal distribution.\par
A non probability sampling design in the form of convenience sampling technique was used to record responses. This was considered appropriate to gather data because of the rationale that respondents were easily accessible. A cross-sectional survey design using a quantitative method was conducted to determine the relationship between independent indicators. Descriptive statistics, inferential statistics (Pearson Product Moment Correlation) and standard multiple regressions were then employed to the analyzed data. The data collected was coded, cleaned and themes were then developed. This was analyzed using Statistical Package for Social sciences (SPSS) version 20.0. Three major approaches of data analysis were then employed descriptive statistics, Person's Product Moment Correlation Coefficient and standardized multiple regressions. 
\section[{c) Conclusions}]{c) Conclusions}\par
The study indicated that males participated more than females and the major portion of respondents were aged 21-30 years. It also pointed out that most managers/owners of SMEs are young and inexperienced with business startups based on trial and error. Majority of the respondents in the research had "O" level as the highest level of education attained. Majority of the respondents also operated in trade sector just more than the service sector. Majority of the businesses, when considering length of time in operation were between one year and five years. Sole proprietorship played the bulk of business ownership of the SMEs and also the managers/owners have experience which plays a major part of running and survival of the enterprise. From comparisons of means, it can be inferred from the data that the use of effective entrepreneurship was the strongest defense for survival of SMEs. There is an average use of HRM practices due to low number of employees of these businesses.\par
From correlation, use of effective entrepreneurship helps to explain nearly twenty-two percent of the variance in respondents' challenges in developing a HR strategy and hence firm's growth. The regression model had an R of 0.6474 which meant 41.9126\% of the variance in HR strategy is explained by the model. IT had the highest beta coefficient and made the strongest unique contribution to explaining the dependent variable. 
\section[{d) Recommendations}]{d) Recommendations}\par
Use of effective entrepreneurship is the most important factor in SMEs growth. If taken an advantage of, it can create a synergetic effect with other factors to lead to sustainable growth of the said SMEs. Use of IT applications should also boost the success of these firms if well executed. 
\section[{Bibliography}]{Bibliography}\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}110}\end{figure}
  \begin{figure}[htbp]
\noindent\textbf{31} \par 
\begin{longtable}{P{0.11819526627218933\textwidth}P{0.5884615384615385\textwidth}P{0.14334319526627218\textwidth}}
.Sub -Sector\tabcellsep SMEs\tabcellsep SMEs Sample Size (N)\\
Textile\tabcellsep Clothing Shops\tabcellsep 1\\
\tabcellsep Vending shops\tabcellsep 5\\
\tabcellsep Video and CD lending/selling shops\tabcellsep 1\\
\tabcellsep Hard wares\tabcellsep 2\\
Trade\tabcellsep Butcheries\tabcellsep 3\\
\tabcellsep Chicken shops\tabcellsep 1\\
\tabcellsep Chemists\tabcellsep 2\\
\tabcellsep Vegetable and ready food stalls\tabcellsep 3\\
Technical\tabcellsep Electric shops\tabcellsep 3\\
\tabcellsep Cyber cafes\tabcellsep 2\\
\tabcellsep Hair Salons and Hair cut shops\tabcellsep 2\\
Services\tabcellsep Car wash\tabcellsep 1\\
\tabcellsep Tire Repair\tabcellsep 2\\
\tabcellsep Cobbler and shoe shiner\tabcellsep 2\\
Totals\tabcellsep \tabcellsep 30\\
\tabcellsep \tabcellsep Source: Survey (2014)\end{longtable} \par
 
\caption{\label{tab_1}Table 3 . 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{41} \par 
\begin{longtable}{P{0.17539682539682538\textwidth}P{0.34404761904761905\textwidth}P{0.09444444444444444\textwidth}P{0.2361111111111111\textwidth}}
Measures\tabcellsep Items\tabcellsep Frequency\tabcellsep \%\\
\tabcellsep Male\tabcellsep 17\tabcellsep 51.5\%\\
Gender\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Female\tabcellsep 16\tabcellsep 48.5\%\\
Total\tabcellsep \tabcellsep 33\tabcellsep 100.0\%\\
\tabcellsep < 20 years\tabcellsep 1\tabcellsep 3\%\\
\tabcellsep 21-30 years\tabcellsep 14\tabcellsep 42.4\%\\
Age\tabcellsep 31-40 years\tabcellsep 12\tabcellsep 36.4\%\\
\tabcellsep 41-50 years\tabcellsep 4\tabcellsep 12.1\%\\
\tabcellsep 51 years and above\tabcellsep 2\tabcellsep 6.1\%\\
Total\tabcellsep \tabcellsep 33\tabcellsep 100.0\\
Highest Level of\tabcellsep O' Level\tabcellsep 12\tabcellsep 36.4\%\\
Education\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Certificate\tabcellsep 9\tabcellsep 27.3\%\\
\tabcellsep Diploma\tabcellsep 6\tabcellsep 18.2\%\end{longtable} \par
 
\caption{\label{tab_2}Table 4 . 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{42} \par 
\begin{longtable}{P{0.3247191011235955\textwidth}P{0.13848314606741574\textwidth}P{0.11938202247191011\textwidth}P{0.26741573033707866\textwidth}}
\tabcellsep Descriptive Statistics\tabcellsep \tabcellsep \\
\tabcellsep N\tabcellsep Mean\tabcellsep Std. Deviation\\
Appropriate HRM\tabcellsep 33\tabcellsep 19.5455\tabcellsep 8.77173\\
Effective Entrepreneurship\tabcellsep 33\tabcellsep 27.1515\tabcellsep 5.32166\\
Information Technology (IT)\tabcellsep 33\tabcellsep 17.5152\tabcellsep 8.87455\\
\tabcellsep \tabcellsep \tabcellsep Source: Survey (2014)\end{longtable} \par
 
\caption{\label{tab_3}Table 4 . 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{43} \par 
\begin{longtable}{P{0.6749999999999999\textwidth}P{0.08214285714285714\textwidth}P{0.05357142857142857\textwidth}P{0.03214285714285714\textwidth}P{0.007142857142857143\textwidth}}
\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\\
HRM strategy\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Use of Appropriate HRM\tabcellsep -0.422**\tabcellsep \tabcellsep \tabcellsep \\
Use of Effective Entrepreneurship\tabcellsep 0.472**\tabcellsep 0.337**\tabcellsep \tabcellsep \\
Use of Information Technology (IT)\tabcellsep 0.562**\tabcellsep 0.365**\tabcellsep -0.147**\tabcellsep 1\\
\multicolumn{2}{l}{** Correlation is significant at the 0.01 level (2-tailed).}\tabcellsep \tabcellsep \tabcellsep \\
Source of data: Survey (2014)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}Table 4 . 3 :}\end{figure}
 			\footnote{T © 2017 Global Journals Inc. (US)} 			\footnote{© 2017 Global Journals Inc. (US) 1Factors Affecting the Successful Growth and Survival of Small and Micro Enterprises (SMEs) in Zimmerman Ward, Nairobi County -Kenya} 			\footnote{Factors Affecting the Successful Growth and Survival of Small and Micro Enterprises (SMEs) in Zimmerman Ward, Nairobi County -Kenya} 			\footnote{© 2017 Global Journals Inc. (US) 1} 			\footnote{© 2017 Global Journals Inc. (US)} 			\footnote{Factors Affecting the Successful Growth and Survival of Small and Micro Enterprises (SMEs) in Zimmerman Ward, Nairobi County -KenyaThis page is intentionally left blank} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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