105 Entrepreneurship processes and small Farms Achievements: Empirical Analysis of Linkage Temidayo Gabriel Apata* Abstract Entrepreneurship process has been argued as opportunity-driven, creative, and resource-efficient, that could influence income generation of small farmers that adopted entrepreneurial skills and innovation into their farming operations. This study examines entrepreneurship process strategies employed to income increase by small farmers, evidence from southwest of Nigeria. The sampling procedures entail three stages of samples selection of 240 farmers but only 200 data was useful. Descriptive statistical and inferential statistics were used to analyze and describe the data. Respondents’ age ranges from 16 to 65 years old, mean age was 36.16 years. The study found out that 5 % of the samples had modest communication skills that aid adoption of effective entrepreneurial processes and about 83% have a strong belief in one’s self to succeed. Successful farmers had multiple sources of related income generation business ventures. Targeting the entrepreneurs for support could make them even more effective. Keywords: agricultural entrepreneurship, entrepreneurial skills, effective management, small farms, entrepreneurial learning identity. Introduction Entrepreneurship has been argued as a multifaceted notion, which has been defined in different ways by various investigators. It is a complex and holistic ‘‘fit and balance’’ of several factors (Timmons, 1999). Various investigators have given prominence to different blend of factors, but most would concur with Timmons (1999) and Kodithuwakku and Rosa (2002) that at its fundament, the entrepreneurial process is opportunity-driven, creative and resource-efficient. Scott et al. (1997) argued that entrepreneurship is a “creative process of extracting social and economic value from the environment”. The * Temidayo Gabriel Apata, Department of Agricultural Economics and Extension, Federal University, Oye-Ekiti, Nigeria. Tel.: +2348060222394. E-mail: [email protected]. 106 / Entrepreneurship Processes and Small Farms Achievements: Empirical Analysis of Linkage entrepreneurship route to success is not just creative, but also opportunity- driven (Pieter et al, 2013; Fry, 1993). In his words Bryant (1989) argues that “entrepreneurs are characteristically people who go beyond the limits of resources over which they have direct control’. Moreover, Bygrave (1994) reasoned that entrepreneurs looked for route of regulatory decisive resources without owning them. Alsos et al, 2011 maintained that the key quality of entrepreneurs is their capability to be innovative with limited resources. Allan et al. (2012) and Stevenson, (1997) argued that ownership of resources is not a mandatory requirement for entrepreneur to make use of and it is not necessary to provoke its movement or change of application but a process by which individuals pursue opportunities without regard to the resources they currently control. In the light of the above concepts and arguments, the study deduced that anentrepreneur is an individual who is inventive in finding ways that add value to his own wealth, produces influence, and reputation and who is not afraid to take a risk that could advance his belief. It is said that “entrepreneurial process provides an alternative way to efficiently manage resources than just following conventional or standard good management practice” (Pieter et al, 2013 and Allan et al. 2012). Thus, an entrepreneur is an individual who is more resourceful in making use of what is available to create opportunities to advance growth. Agriculture is at the heart of the majority of rural households in developing countries like Nigeria. Past studies have indicated that a great mass of people in rural areas earn their livelihood from the land and see it as a way of life, operating mainly on small scale due to limited resources (Oyebola and Ajiboshin, 2013; Raimi and Towobola, 2011; Chu et al., 2010; Onipede, 2003; Akin and Peter, 2002). It is also argued that these categories of people are efficient in the allocation of resources at their disposal (Fans et al, 2003; Babatunde and Qaim, 2010). A small farm is defined as “operated units in which most labour and enterprise come from farm family, which puts much of its working time into the farm” (Gries and Nande, 2011; Wiggins, 2009; Nick, 2008; Cormia, 1985); The World Bank’s Rural Strategy defines smallholders as those with a low asset base, operating less than 2 hectares of cropland (UNECA, 2009). Also, small farms have been ascribed as “limited resource endowments, relative to other productive activities” (Bozzoli and Bruck, 2009; Cormia, 1985). Review of similar studies showed that a small farm is a subsistence farming operation where the family provides the majority of labour and the farm provides the principal source of income” (Pingali 2010, Nagayets, 2005; Hazell and Haggblade, 1993). From these lines of arguments it can be deduced that small farmers are already entrepreneurs in the sense that they seek out money- making prospects, manage costs of production and marketing, and aspire to Entrepreneurship: Intentions, Institutions and Processes, Anna Ujwary-Gil, Krzysztof Klincewicz (Eds.) Temidayo Gabriel Apata / 107 grow their business. Evidence from Africa and Asia revealed that small farms still dominate the country gross domestic product. Thus, the secret of their recorded successes are embedded in the entrepreneurial process adopted at various levels of production (Vik and McElwee, 2011; Discuo, et al, 2010). Literature has shown that there is a positive linkage between small farmers that adopted entrepreneurial skills and innovation into their farming operations and increase income (Tilman et al, 2013; David, 2012; Chen and Ravallion, 2010). Evidence abounds in a substantial body of literature linking the value of entrepreneurial approaches and strategies by individual entrepreneurs to business growth (Rijkers and Costa, 2010; Bardassi and Sabarwal, 2009; Parker, 2009; Carter and Ram, 2003). Hypothetically, it can be seen that entrepreneur business growth stems from effective resource management through conventional management practice and fortunate access to resources (Jervell, 2011; Bruck et al, 2011; Bennet, 2010; Parker, 2008). There is, however, a dearth of studies demonstrating the empirical vibrant operations of the entrepreneurial processes to business growth among small farmers. Therefore, this study empirically examined entrepreneurial processes and exploitation of small farms by exploring the subtleties of the entrepreneurial process in an all-inclusive socioeconomic background using both qualitative and quantitative methods of data analysis. This research was driven by the basic issue of why some rural entrepreneurs in Nigeria were much more successful than their fellow rural farmers who do not adopt such strategies. Also, giving the same level of opportunity and resources to rural household, what would be the factor (s) that will define economic success or entrepreneurial success, is it through their socio-economic characteristics and what are the factors that influence this? This study answers this question by looking at adoption of entrepreneurship processes and exploitation of small farms in Nigeria using empirical evidence from rural farming households in Southwest Nigeria. Methodology area of study The area of study is South West Nigeria. There are six major zones in Nigeria of which South West is one of them and it comprises of six states. The states are Lagos, Ogun, Osun, Oyo, Ondo and Ekiti States respectively. Osun and Ondo States were purposively selected for the study because of wide range of entrepreneurs that are springing up every day. In addition, there are visible government support and international organization presence to develop and Journal of Entrepreneurship Management and Innovation (JEMI), Volume 11, Issue 2, 2015: 105-127 108 / Entrepreneurship Processes and Small Farms Achievements: Empirical Analysis of Linkage encourage entrepreneurship in the two states selected. Ondo State is the only oil-producing state in the zone and enjoys attention from the Federal Government. This state receives on average N450 million monthly (i.e. about 3.6 million US dollars) in addition to monthly subvention. This state is also regarded as the food basket of the zone. Osun State was selected based on the information of United Nation Human Development Reports (UNECA, 2009) as the poorest state in the South West Nigeria and currently enjoys attention both from local, national and international agencies to support growth of small and medium scale businesses. Sampling procedure and data collection The study adopted sampling procedure in three stages in which both purposive (non-probability sampling) and simple random sampling techniques (probability sampling) were used to pick the villages/towns that have been economically active for the past five years (NBS, 2013). The first stage of sampling selection entails the choice of Idoani and Ilara towns in Ondo State. Idoani town was strategically picked based on literature reviewed that this town enjoys support from Leventis Foundation, state government micro- agencies and International Fund for Agricultural Development (IFAD). While Ilara town also enjoys State government support couple with IFAD funding. Similarly, in Osun State, Owena and Okuku towns were also strategically picked because these towns are economically active, enjoy support from local, state and federal government. In addition, these towns enjoy Federal Government of Nigeria (FGN) special programme on poverty alleviation; Youth Empowerment Scheme (O-YES), SURE-P (a special intervention by FGN that encourage entrepreneurship development among the youth). Osun state selected towns also enjoy support of funding from United States Agencies for International Development (USAID). To identify the sampling frame for the study, in the second stage, list of households’ heads having access to these supports were extracted from extension section of the Ministry of Agriculture and Rural Development (MARD) of the selected states. Help was also sourced from Agricultural Development Programme (ADP) offices to verify and augment some of the data collected from MARD. While a list of farmers (cassava growers) compiled from these agencies were 2500 from Ondo State and 2350 identified farmers (cassava growers) were also sourced from Osun State. In the final stage of selection, 60 respondents were sampled randomly from each town to get a total of 240 farmers (cassava growers), but only 200 data (80% response rate) were useful for subsequent analysis (Table 1). Entrepreneurship: Intentions, Institutions and Processes, Anna Ujwary-Gil, Krzysztof Klincewicz (Eds.) Temidayo Gabriel Apata / 109 table 1. Distribution of sampled respondents in the study area Cassava Farmer Final selection sampling Frame Sampling Distribution Villages / towns of sample (n) Idoani 1350 60 52 Ilara 1150 60 48 Owena 1025 60 46 Okuku 1325 60 54 Total 4850 240 200 Source: Field Survey (2013). The data collection for this research were quantitative and qualitative data. Data collection was done through various mechanisms which include interviews schedule, Focus Group Discussions (FGD) and observations. The quantitative data were personal characteristics, socio-economic factors, and situational factors. While qualitative data were based on key informants, extension officials, village leaders, Libraries/librarians, NGO workers and, groups of farmers. Observations on the choice of the study area revealed equal opportunity of access to productive resources and services (extension and government support) to all cassava growers. Methods of data analysis The study used descriptive statistics such as means, percentages, frequencies, and standard deviations to analyze the quantitative data, while the qualitative data were used to validate responses gathered from quantitative data. In addition, qualitative data were partly analyzed on spot during data collection to avoid omission and to be able to fill the gaps in the quantitative data collection. The use of Multiple Linear Regression (MLR) analysis was used to examine factors influencing entrepreneurial success/failure among the cassava growers. This was captured by their level of income/asset of the identified respondents. The use of this specialized MLR was adopted by the study of Hair et al, 1998 who argued that independent variables are known to predict the single dependent value. According to Browen and Starr (1983), the regression equation takes the form of Y = a + b X + b X + b X + ... + b X + u (1) 1 1 2 2 3 3 . 16 16 1 Where: Y= Dependent variable X - = Independent variables 1 16 Journal of Entrepreneurship Management and Innovation (JEMI), Volume 11, Issue 2, 2015: 105-127 110 / Entrepreneurship Processes and Small Farms Achievements: Empirical Analysis of Linkage a = intercept b = the slope of the line a and b are parameters to be estimated. u = error term (unexplained variables) 1 Estimation procedure Due to the nature of the data, Ordinary Least Square (OLS) method was adopted for estimation technique. Other techniques used to reduce measurement errors are in the use of Dublin Watson test to assess multi-co linearity among the explanatory variables to avoid co linearity problem and the use of Best Linear Unbiased Estimation (BLUE) method. Data were coded into SPSS version 17 for analysis. Variables and their definitions Dependent variable The dependent variable used for this study is the entrepreneurial success/ failure of the respondent’s outputs in terms of knowledge and it is captured by their assets/income or losses accrued. This is to serve as function of knowledge of farmers on daily good farm management practices and their level of utilization of resources at their disposal. To capture farmers’ level of knowledge about effective farming practices the use of ‘teacher - made type’ test was developed. This method was developed and used in consultation with the concerned ADPs Office, key informants representative and officials of the Ministry of Agriculture. Appropriate questions were developed to collect appropriate responses from the farmers about the selected salient features of their entrepreneur ability. The various items were developed for the knowledge test in respect of operative farming practices and these were given weights as per their prominence. Independent variables For this study, 16 independent variables (see Table 2) were identified and hypothesized to influence the dependent variable. From these 16 variables 10 were continuous and 6 were discrete. The independent variables include the personal characteristics, socio-economic factors, situational factors and psychological factors of farmers that may influence the dependent variables. Selection of these independent variables used in the study was logically taken from the review of past research and published literature related to the scope of the study (Renwick, 2010, and Aina, 2004). Entrepreneurship: Intentions, Institutions and Processes, Anna Ujwary-Gil, Krzysztof Klincewicz (Eds.) Temidayo Gabriel Apata / 111 table 2. List of independent variables and measurements s/n Variables Measurements Expected signs 1. Age (X) Measured in terms of number of years of age. negative relationship 1 2. Marital Status (X) This indicates whether respondents are married, positive relationship 2 unmarried, single, or widowed. This data was ope- among married rationalized through scoring system labelled from respondents questionnaire 3. Educational Level Education refers to the level of formal and non-formal Educational level (X) education and this was scored in terms of ability to positively affects use 3 read and write and enrolment in primary, secondary of information. schools or post-secondary. 4. Communication Communication skills are referred to as the ability to Communication skill Skills (X) express ideas effectively in written or spoken form, was anticipated to 4 and the ability to listen attentively. This variable was have positive rela- measured using list of items selected through syste- tionship matic procedure. 5 Positiveness (X) Defined as a person’s quality that is characterized by The variable was 5 displaying certainty, acceptance, or affirmation. It was assumed to have measured by respondents’ willingness to discuss agri- positive relationship cultural matters with other farmers. Also, despite the harsh environment, their belief in one’s self to succe- ed. It was operationalized as low, medium and high. 6 Income (X) Operationally defined as the value of the products of The income level was 6 the household after home consumption and income anticipated to have a obtained from off-farm and non-farm activities that positive relationship are expressed in Naira per year. 7 Size of land holding This refers to the area of cultivated land owned by the Therefore, it was hy- (X) respondents or their families. It was assumed that the pothesized that land 7 larger the farm size, the better access the farmer has to size has a positive use combination of technological packages on the land. relationship 8 Family size (X) The size of the family of the respondent measured in family size was assu- 8 terms of total number of members in the family inclu- med to have positive ding the elderly and children. relation 9. Radio Ownership The farmers who own the radio and listen to program- Information network (X) mes or news have the opportunity of getting more has positive relation. 9 agricultural information. Radio ownership by respon- dents was 1 for Yes and 0 otherwise 10 Social participation This refers to the involvement in social activities and Social participation (X ) membership of the respondent in various formal and was expected to have 10 informal organizations, either as member or as an positive relationship office bearer. It was measured in terms of member- with the dependent ship or official status in any formal or informal organi- variable zations, along with the frequency of participation and type of organization of which the farmer is a member using the scale developed by Trivedi (1963) with slight modifications. 11 Information Seeking This was defined as the degree to which the respon- Information seeking behaviour (X ) dent was eager to get information from various sour- behaviour was assu- 11 ces on different roles he performs. This was measured med to have positive in terms of how much information was sought, how relationship frequently and from where the information was so- ught. Journal of Entrepreneurship Management and Innovation (JEMI), Volume 11, Issue 2, 2015: 105-127 112 / Entrepreneurship Processes and Small Farms Achievements: Empirical Analysis of Linkage s/n Variables Measurements Expected signs 12 Cosmopoliteness This is the degree of orientation of the respondent Expected to have (X ) towards outside of the social system to which he be- positive relationship 12 longs. It is measured in terms of frequency of visits to outside his village and the purpose of such visits. 13 Attitude towards Defined as the degree of positive or negative attitude anticipated to have a development agent of farmers towards Development Agent. This variable positive relationship (X ) was measured using the Likert scale model. 13 14 Sharing of available Defined as the extent to which the respondent shared anticipated to have a information (X ) the information with others, including family mem- positive relationship 14 bers, friends or neighbours, extension agent, etc. 15 Access to credit (X ) Access to credit has impact on the level of utilization variable was assu- 15 of recommended technological packages and this in med to have a positi- turn will expose respondents to divergent information. ve relationship 16 Extension participa- It was measured using a weighted index. variable was assu- tion (X ) med to have a positi- 16 ve relationship Source: Field Survey (2013). Results and discussions Descriptive statistics The study examined individual features of respondents as they influenced their entrepreneur ability and these are educational attainment, communication ability, marital status, age, household size, attitude to change, and positiveness among others. Table 3 describes individual features of the sample respondents. table 3. Distribution of sample respondents based on their personal charac- teristics (N = 200) Personal characteristics Features Frequency percent Age of Respondents 15-29 (Younger) 45 22.5 30-49 (Middle) 122 61.0 50-65 (Older) 33 16.5 Total 200 100.0 Marital Status Single 57 28.5 Married 103 51.5 Widowed/Separated 40 20.0 Total 200 100.0 Level of Education Illiterate 32 16.0 Can read and write 43 21.5 Primary School 41 20.5 Secondary School 62 31.0 Post-secondary School 22 11.0 Total 200 100.0 Communication Skills Low 17 8.5 Entrepreneurship: Intentions, Institutions and Processes, Anna Ujwary-Gil, Krzysztof Klincewicz (Eds.) Temidayo Gabriel Apata / 113 Personal characteristics Features Frequency percent Medium 93 46.5 High 90 45.0 Total 200 100.0 Family Size 1-3 47 18.8 4-6 141 56.4 7-9 39 15.6 Above 9 23 9.2 Total 200 100.0 Radio Ownership No 77 38.5 Yes 123 61.5 Total 200 100.0 Size of land holding in 0.1-1.99 59 29.5 Acres 2.0-3.5 115 57.5 Above 3.5 26 13.0 Total 200 100.0 Positiveness Low esteem in one’s self to positiveness 34 17.0 Medium esteem in one’s self to 129 64.5 positiveness High esteem in one’s self to 37 18.5 positiveness Total 200 100.0 Source: Field Survey, 2013 Respondent’s age The study revealed that respondents’ ages ranges from 16 to 65 years old. The mean age was 36.16 years with the standard deviation of 13.04 years. Analysis of the arrays showed that respondents in the age bracket 30-49 years were the majority (61.0%), age bracket 15-29 years (22.5%) and age cluster 50-65 years (16.5%). Analysis of the age distribution reflected the active age bracket of the respondents to be in the mean distribution. Thus indicating that innovation or adoption of technology could easily be embraced and could also be hostile to disagreeable innovation or technology adoption. Respondent’s marital status The results of the analysis of marital status of the respondents revealed that majority (51.5%) of the respondents were married and living together with their spouses. Those not married or engaged were 28.5% of the sampled population, while the widowed and separated respondents were the minority. Implication of this finding could signify that stable income generation and decent living among respondents could be useful in their togetherness as husband and wife, as the study showed that high proportion existed between stable families than others. In other words, joint deliberations and evaluation Journal of Entrepreneurship Management and Innovation (JEMI), Volume 11, Issue 2, 2015: 105-127 114 / Entrepreneurship Processes and Small Farms Achievements: Empirical Analysis of Linkage on issues and information can be jointly considered and best decisions could be adopted. Respondent’s educational attainment It has been argued that an important factor which can influence the ability of a farmer/person to understand innovation is education. Also, underdevelopment occurring in most developing countries like Nigeria is the low level of education and high illiteracy rate among the people. Aina (2006) argued that poor education among Nigerian farmers has deprived them of the ability to make good use of agricultural innovation available to them. Consequently, this study deduced that education plays a great role in the entrepreneurial ability of the respondents and thus examined. As indicated in Table 3, the description of the respondents showed that 16.0% were uneducated, while 11.3% were able to read, and write and 41.5% had post-primary school education. This indicates that for innovation to be appreciated and useful it must come in a language people will be able to understand, digest and use. Respondent’s communication skills This study deduced communication skills to be the ability of a person to be able to express ideas effectively in written or spoken form, and also understand the language directed at his person. The study outlined three types of communication skills levels as low, medium and high communication skills. Table 3 showed that about 91.5 % of the respondents had medium and high level of communication skills, respectively. This finding foretells that active information can be easily diffused and exchanged with another. Respondent’s positiveness The study inferred positiveness as the disposition of a person towards acceptability, belief and certainty about an idea or innovation that will bring a positive change. Positiveness was captured in the study among respondents as readiness to discuss agricultural innovations they believe in with other farmers and seek necessary information and help with its adoption. Also, despite the harsh environment there is the belief in one’s self to succeed. Adopting and use of agricultural innovations in the study was operationalized as low, medium and high. The study revealed that respondents who indicated low esteem in one’s self to succeed are about 17.0%, while about 83% have a strong believe in one’s self to succeed. The implication of this finding is that agricultural innovation success among adopters is tied to their esteem on the innovations. Thus scientists, agricultural extensions need to raise esteem Entrepreneurship: Intentions, Institutions and Processes, Anna Ujwary-Gil, Krzysztof Klincewicz (Eds.)