# Entrepreneurship Behavior of Indigenous Fish Farmers in Eastern Chitwan, Nepal

Authors: Samyog Paudel; Reja Regmi; Milan Subedi; Tilak Karki
Journal: Discrete Dynamics in Nature and Society
 (2022)

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## Abstract

Aquaculture has great potential in the Terai region of Nepal due to the suitability of pond resources and government attempts to improve the fisheries sector. The majority of fish farmers in Chitwan belong to indigenous nationalities. Entrepreneurship skills help in uplifting local rural communities but due to the lack of attractiveness and economic production of fish in Chitwan, there is a higher chance of fish enterprise failure. Hence, an immediate need of assessing entrepreneurial behavior was felt and the study was carried out among indigenous fish farmers of Eastern Chitwan. For data collection, a questionnaire survey was conducted among eighty random respondents and a key informant interview was performed with expert farmers and fish scientists using the convergent parallel mixed method. Collected data were analyzed using SPSS version 22 and MS Excel. The entrepreneurial behavioral index (EBI) was calculated for each respondent, and it was assessed with various sociological and production factors. Average EBI was found among respondents. Most of the surveyed entrepreneurs have a low level of innovativeness, farming knowledge, and leadership while a medium level of motivation and decision-making ability. From thet-test, it was found that factors like AKC (Agriculture Knowledge Centre) visit, farming type, and organizational membership are significant but farmers’ gender, extension consultation, training, information source, education, and experience are nonsignificant with respondents’ entrepreneurship. Farmers who do commercial farming, visit AKC, and are members of social organizations have relatively more entrepreneurial behavioral indexes than other farmers. For the improvement of fish enterprises in the study area, training related to fisheries innovativeness, fish farming knowledge, and leadership is recommended through the collaboration of AKC and social organizations.


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## Body

## 1. Introduction

Modern fish farming was initiated in Nepal with the introduction of exotic carps in the early 1950s [1]. Aquaculture is one of the potential enterprises in the plane terai region of Nepal as it is the source of food and money for many people and plays a great role in food security, livelihood, and social development in developing countries [2]. Chitwan district has a great scope in fish farming due to its land suitability and water availability. It has the highest productivity among all districts of the country [3]. The majority of fish farmers in Chitwan belong to indigenous (adivasi and janjati) nationalities [4].The government has identified fish farming as one of the major subsectors for poverty reduction and targeted to make Nepal a self-sufficient country in fish production [5] by implementing various attempts to increase fish production and productivity [4, 6]. According to an evaluation study on income generation and consumption pattern of fish in Chitwan, farmers consumed a greater number of fish than they sold [7], which indicates that aquaculture is criticized as an uneconomic, unattractive, and less-innovative business by farmers.To implement aquaculture successfully as an attractive, economic, and innovative enterprise, fish farmers must behave and act as a change agent [8] by adopting entrepreneurial behavior. Entrepreneurial behavior is the combination of various components, namely, innovativeness, decision-making ability, achievement motivation, information-seeking ability, risk-taking ability, coordinating ability, leadership ability, and market orientation skill [9, 10]. Entrepreneurial behavior is not only doing new things but also doing things in a new way with new results [11]. It is also perceived as the changes in knowledge, skill, and attitude of farmers [12]. Entrepreneurial talent affects the development of small-scale enterprises [13]. Entrepreneurship contributes to the multidimensional development of fish farming in various ways, namely, generating seeds, fish breeding, improving production techniques from locally available materials to reduce cost and increase production, creating a market, incorporating other agricultural activities in the farm, and coordinating and managing other fish growers.An entrepreneur is a person who initiates, organizes, manages, and controls business activities by combining factors of production to supply goods and services [8]. Entrepreneurs are a key population in promoting economic growth and technological changes. Fish entrepreneurs play an important role in economic development, employment creation, and resource utilization in the Terai region of the country. Assessment and development of entrepreneurship among fish farmers is a prerequisite to establishing an economic, attractive, and sustained fish farming system for the socioeconomic development of the society. Despite these potential and values of fish farming, there is a trend of dropping fish farming. It is necessary to nurture the quality of entrepreneurship among fish farmers to avoid this kind of enterprise failure [14]. Previous research studies related to the topics are unable to explain the behavioral status of indigenous entrepreneurs and factors affecting entrepreneurship in the study area. Hence, this study was conducted to access and examine the entrepreneurship behavior of indigenous fish farmers in Eastern Chitwan, Nepal.


## 2. Materials and Methods

This study was conducted in the eastern part of Chitwan district which is in the southwest of Bagmati Province, Nepal. Eastern Chitwan consists of four municipalities of Chitwan district, namely, Ratnanagar, Kalika, Khairahani, and Rapti. This region is selected purposively because the Chitwan district has the highest productivity among other districts [3] and countries' deepest river flows in the district. Also, the fisheries development center under the government of Nepal was in the eastern part of the district.Convergent parallel mixed design [15] was used in the study, where both qualitative and quantitative methods were used simultaneously. The sampling frame of 170 indigenous ethnic caste farmers of the study area was prepared from the fish farmers’ profile of the Chitwan district [16], and a total of 80 respondents were selected as a sample from the sampling frame through a simple random sampling method (without replacement) by using Microsoft Excel. The questionnaire was developed through the m-Water portal and pretested in 10 households of Bharatpur to check its reliability and effectiveness, and with the help of the review, the final questionnaire was developed. Data were collected from the m-Water surveyor through face-to-face interviews, observations, and key informant interviews.Entrepreneurship behavior of fish farmers was calculated as the aggregated outcome of entrepreneurial components, namely, innovativeness, decision-making ability, motivation, fish farming knowledge, and leadership [8–10, 12] by using the entrepreneurship behavior index (EBI) equation adopted from the index recommended by Guilford in 1954 [8]. (1) is the equation given by Guilford, and (2) is the equation adopted for this study. In the equation, five components were used to calculate EBI (which are given as follows: n1, n2, n3, n4, and n5).(1)EBI=∑n=15Tn/Mn∑n=15Rcn∗100.That is,(2)EBI=Tn1/Mn1∗Rc1+Tn2/Mn2∗Rc2+Tn3/Mn3∗Rc3+Tn4/Mn4∗Rc4+Tn5/Mn5∗Rc5Rc1+Rc2+Rc3+Rc4+Rc5∗100,where Tn = individual obtained score of the “n” component (attributes), Mn = maximum obtainable score of the component “n”, Rcn = scale value of component “n”, n = number of components (5 in this context), n1 = innovativeness, n2 = decision-making ability, n3 = motivation, n4 = fish farming knowledge, and n5 = leadership ability; i.e., Tn1, Tn2, Tn3, Tn4, and Tn5 are scores of entrepreneurs on n1, n2, n3, n4, and n5 components, respectively; Mn1, Mn2, Mn3, Mn4, and Mn5 are the maximum obtainable scores on n1, n2, n3, n4, and n5 components, respectively; and Rc1, Rc2, Rc3, Rc4, and Rc5 are the scale values or rating of n1, n2, n3, n4, and n5 components, respectively.Collected data were entered and analyzed using the Microsoft Excel, 2007, and SPSS version 22. Descriptive statistics were used to find out the mean, frequency, percentage, and standard deviation of sociological factors, EBI, and other attributes, while inferential statistics were used for indexing to calculate EBI and fort-tests to compare mean EBI on various attributes of respondents. EBI was categorized to five ranges with a difference of 0.2 (i.e., 0.00–0.20, 0.21–0.40, 0.41–0.60, 0.61–0.80, and 0.81–1.00) to assess EBI range of the majority of respondents. Analyzed data and results were interpreted as tables and paragraphs.


## 3. Results and Discussion

Eastern Chitwan is located at the eastern part of the Chitwan district of Bagmati Province of Nepal. Chitwan district lies in the southern mid-part of the country. Four municipalities named Ratnanagar, Kalika, Khairahani, and Rapti of Chitwan district are considered as Eastern Chitwan. The majority of fish growers in the study area belong to indigenous nationalities that are native to the place from the beginning of residence in the area. They are considered a marginal group of the Hindu community in Nepal. Indigenous communities have less opportunity and chance for a worthy life as compared to high-class people in Nepal.This section includes results about the socioeconomic status of indigenous fish farmers, their entrepreneurial behavior, and factors affecting entrepreneurship among these indigenous fish growers in Eastern Chitwan, Nepal.


### 3.1. Sociodemographic Status of Indigenous Fish Farmers in Eastern Chitwan

The socioeconomic situation of respondents was assessed by studying demographic attributes like age, education, and experience and farm economic attributes like pond area, training, farming experience, and annual income. Six attributes, namely, age (refers to age after birth in years), education (refers to the year of schooling), pond area (area of fish pond in hectare), annual income (average income from fish farming by farmers in a year), experience (years of fish farming), and training (refers to an average amount of training in fish farming taken by a farmer), were assessed during the study (Table1).Table 1
Socioeconomic and demographic status of respondents.
AttributesMeanSDAge (years)47.9211.59Education (year)6.114.90Pond area (hectare)0.630.56Annual income (000′ Rs)359.375401.671Experience (farming year)9.237.68Training (number)0.751.95Source: field survey, 2019.The mean age of indigenous fish growers in the Eastern Chitwan area was found to be 47.92 years with a minimum of 25 years and a maximum of 71 years, which is in line with the result of the Nepal Fishery Survey 2072 [17] and socioeconomic study of pond farmers in other developing countries [18–20].From the examination of the educational status of respondents, it was determined that 28.75% of them were illiterate and 81.25% were literate. Also, a mean schooling year of 6.11 years was found among fish farmers ranging from 0 years of schooling to 16 years of schooling (bachelor’s degree). A study of fish farmers’ assessment in other rural areas also reported a similar mean schooling year [21, 22], while it is less than the agricultural entrepreneurship behavioral study of African developing nations [20].According to the national sample census of agriculture in Nepal, most fish farmers of Chitwan have a pond area of 0.33 hectares to 1.014 hectares [23]. A similar result of an average of 0.63 hectares of the pond area was found among respondent fish farmers with a minimum of 0.033 hectares and a maximum of 2.7 hectares of the pond area.From the survey result, the average annual income of Rs. 3,59,375 (2896 USD) with a standard deviation of Rs. 8,38,230.6 (6756 USD) was observed among fish farmers of the study area, ranging from Rs. 50,000 (403 USD) to Rs. 25,00,000 (20150 USD). This mean income is more than the result of Olowa and Olowa’s (2015) study of factors affecting entrepreneurship development in agribusiness enterprises in Nigeria [20]. The average annual household income of fish farmers in the study area is higher than the average household income of the overall population of the central development region [24]. This suggests that the aquaculture business is a profitable farming enterprise in Eastern Chitwan.Also from the study, an average of 9.23 years of farming experience with a minimum of 1 year to a maximum of 38 years was found among indigenous fish growers of Eastern Chitwan. The mean experience of fish farmers in the study area is lower than other developing South Asian countries [21, 25] and higher than African developing nations [26].From the result in Table1, it was observed that the farmer has taken an average of 0.72 times training and the number of training has a greater standard deviation than the mean due to a training range of 0 to 12 times. Among 80 surveyed respondents, 22 farmers got training on fish farming practices, which is very low as compared to the fishery census of Chitwan [17] and research on fisheries extension in other South Asian developing countries [21, 27].


### 3.2. Entrepreneurial Behavioral Index (EBI) of Respondents

The entrepreneurial behavior of respondents was assessed by asking multiple questions related to five attributes, namely, innovativeness, decision-making ability, motivation, farming knowledge, and leadership. Farmers using mechanized equipment, using commercial farming technique, doing self-breeding of fish, farming polyculture of fish, and using oral delivery of vaccine are referred as innovative; farmers deciding on fish species to grow, feed to use, increasing pond area, and appropriate treatment and vaccination to fish were considered to have more decision-making power; farmers who were satisfied from fish farming, engaged in group and organization, and learned and taught others about fish farming were considered as motivated farmers; farmers having feeding knowledge, i.e., knowledge on growth promoting hormones, amount of crude protein in feed, and feeding rate; pond management knowledge, i.e., knowledge on the requirement of lime, compost, and organic manure and fertilizer in the pond; market knowledge, i.e., knowledge of fish price and market margin; and disease management knowledge, i.e., knowledge on symptoms, prevention, and treatment of fish disease were considered to have farming knowledge; farmers with board membership in groups, with past experience of leading any program, who engaged in multiple organizations, and who were followed by other farmers on farming practice and knowledge were considered as having leadership (Table2).Table 2
Entrepreneurial behavior of indigenous fish farmers in Eastern Chitwan, Nepal.
AttributesCategoriesFrequencyPercentageInnovativenessLow (<4)5265Medium (=4)1417.5High (>4)1417.5Decision-making abilityLow (<3)2227.5Medium (=3)3847.5High (>3)2025MotivationLow (<2)2227.5Medium (=2)2936.25High (>2)2936.25Farming knowledgeLow (<6)4455Medium (=6)1417.5High (>6)2227.5LeadershipLow (<2)7087.5Medium (=2)56.25High (>2)56.25Source: field survey, 2019.An average of 0.39 EBI ranging from 0.19 to 0.66 was found among respondents (Table3). This is less compared to the result of other entrepreneurship studies [8, 28]. Also, it is found that the majority of respondents have EBI ranging between 0.21 and 0.40. The entrepreneurial behavioral index (EBI) of indigenous fish farmers of Eastern Chitwan was calculated from the score of five entrepreneurial skills, namely, innovativeness, decision-making ability, motivation, farming knowledge, and leadership.Table 3
Overall entrepreneurial behavioral index (EBI) of respondents.
EBI (range)FrequencyPercentage0.00–0.2022.50.21–0.404252.50.41–0.603442.50.61–0.8022.5Maximum EBI = 0.66Minimum EBI = 0.19Mean EBI = 0.39Mean of best ten = 0.57Mean of worst ten = 0.22Source: field survey, 2019.


#### 3.2.1. Innovativeness

The result shows that most of the respondents have low innovativeness, which is in line with the study by Anthony et al. (2014) but contradicts the result of Chandra (2005), Rathod et al. (2012), and Patil and Singh (2019) [8, 29–31]. Low innovativeness was obtained among respondents due to traditional and old farming practices.


#### 3.2.2. Decision-Making Ability

The majority of respondents have a medium level of decision-making on their fish farm due to their low farm ownership decisions and medium risk-taking behavior. This result is in line with that of Ravikumar et al. (2006), Rathod et al. (2012), and Patil and Singh (2019) [30–32].


#### 3.2.3. Motivation

An equal number of respondents have a high and medium level of motivation followed by a low level, which is in line with the study of Vijay Kumar (2001), Suresh (2004), Rathod et al. (2012), and Patil and Singh (2019) [10, 30, 31, 33]. This is due to their engagement in the fish farmers association and satisfaction from the farm.


#### 3.2.4. Farming Knowledge

Most of the respondents have a low level of farming knowledge followed by high and medium. This result is in line with that of Adesoji and Kerere (2013), which contradicts the result of Anthony et al. (2014) [8, 34].


#### 3.2.5. Leadership

Almost 90% of respondents have a low level of leadership, and this contradicts the result of Anthony et al. (2014) [8]. Most of the farmers have not ever represented fish farming in any field, and the reputed post of fish farming organizations was also governed by limited farmers in Eastern Chitwan, which may be the reason for a low level of leadership among respondents.


### 3.3. Factors Affecting Entrepreneurial Behavioral Index (EBI)

Nine attributes were studied during the study, namely, AKC visits (farmers visit to government extension office), farming type (attributed according to the size of farm and categorized as commercial and subsistence), gender (categorized as men and women), training taken (farmers taking training related to fish farming), consultation with extension agents (farmers taking suggestions from extension agents like fishery experts, government officials, and agro-vet owners), membership in farmers organization (farmers having membership of farmers group and farmers organizations), major source of farming information (categorized as formal source, i.e., extension centers and organizations, and informal source, i.e., friends and media), education (farmers taking formal schooling are referred as literate and not taking formal schooling are referred as illiterate), and experience (farmers having more than 10 years of experience in fish farming are categorized as more than a decade, and farmers having less than 10 years of experience are categorized as less than a decade). The above attributes were tested with EBI to find out what are the factors affecting the entrepreneurship of respondents Table4.Table 4
Mean EBI comparison among various attributes of respondents.
AttributesCategoriesFrequency (%)Mean EBIt-valueAKC visitsYes36 (45)42.8472.84∗∗No44 (55)36.193Farming typeCommercial26 (32.5)46.5704.75∗∗Subsistence54 (67.5)35.632GenderMen63 (78.75)40.2911.77Women17 (21.25)35.098Training takenYes22 (27.5)42.7651.84No58 (72.5)37.830Consult with an extension agentYes5 (6.25)46.1661.49No75 (93.75)38.722Membership in farmer's organizationYes61 (76.25)40.6962.28∗No19 (23.75)34.342Major source of farming informationExtension/Organization43 (53.75)40.4651.13Friends and media37 (46.25)37.702EducationLiterate57 (71.25)40.1461.24Illiterate23 (28.75)36.811ExperienceFor more than a decade32 (40)37.5521.10Less than a decade48 (60)40.277The symbols∗ and ∗∗ indicate statistically significant at p ≤ 0.01 and p ≤ 0.05, respectively. Source: field survey, 2019.Nearly half of the respondents visit the government extension service or Agriculture Knowledge Centre (AKC) [21, 26, 35], and farmers visiting AKC have significantly more knowledge index. An agricultural extension center visit is an avenue for fisheries development as it provides information, knowledge, consulting, support, and technical guidance to farmers [34], which increases motivation, innovativeness, coordination, and leadership skills that eventually improve the entrepreneurial behavior of farmer [34, 36].About one-third of respondents do commercial fish farming in the study area, and they have statistically more knowledge index than subsistence farmers. Commercial fish farmers are farmers with larger pond areas and more investment and returns that generate higher purchasing power for inputs which increases their innovativeness, leadership, and entrepreneurship [22]. Also, the size of enterprises affects agricultural entrepreneurship [37].Among surveyed indigenous fish farmers, only 21% are female farmers. This indicates that male is the dominant group of gender involved in fish farming [18, 19, 22, 35]. According to the t-test, it was found that gender is statistically nonsignificant to entrepreneurship.A few number of respondents (27%) were trained farmers, which is in line with the study of Khatun and Ahmed [21, 27]. The resulted t-test statistics suggested that the mean difference between trained and untrained farmers was not statistically significant.Only a few pond farmers consult with extension agents [19], which is due to poor access to extension services and extension agents in rural areas [38]. From the t-test, it was observed that there is no significant association between consulting with an extension agent and entrepreneurship.The majority of respondents were engaged in social organizations, which is in line with the entrepreneurship assessment of Olowa and Olowa [20], but contradictory to the finding of the fishery extension assessment by Agbebi in Nigeria [26]. From the t-test, it was found that farmers engaging in organizations have significantly more entrepreneurial behavioral indexes than others. Farmers engaging in organizations have a more entrepreneurial index because organizational involvement enables social participation and interaction [39], which helps in developing entrepreneurship.From the study, it was observed that farmers get more information about farm enterprise practices from extensions and organizations than from friends and media. The result of thet-test confirms that there is no significant association between information source and entrepreneurship behavior index at a 95% confidence level.About 70% of respondents were literate, and they have more EBI because education has been known to enable farmers access new information and practices [40] and help in decision-making [42]. But, the t-test results suggest that this mean difference is statistically nonsignificant [20].Only 28% of farmers have experience of more than 10 years, but their experience was not found to be significantly affecting the mean entrepreneurship behavior index.From the mean comparison by thet-test, it was observed that government extension center visit (p ≤ 0.01), farming type (p ≤ 0.01), and membership in an organization (p ≤ 0.05) were found to be significantly associated factors affecting entrepreneurial behavior of indigenous fish farmers in Eastern Chitwan, while gender, training, extension consult, information source, education, and experience were not statistically associated with indigenous fish farmers entrepreneurship. This obtained result is in line with that of Olowa and Olowa (2015) but contradicts the result of Balhara et al. (2013), Khan (2014), Obeng and Weber (2014), and Seyed et al. (2011) [13, 20, 41–43].In brief, the study resulted in the majority of respondents being middle-aged, male farmers, with an average education. About one-fourth of respondents are trained farmers, very few respondents consult with extension agents, and nearly two-thirds of respondents are subsistence farmers. On average, respondents are more experienced than African developing nations but less experienced than other developing countries in South Asia. Indigenous fish growers have very low innovativeness, knowledge, and leadership but have medium motivation and decision-making ability. Also, the majorities have a low level of innovativeness, farming knowledge, and leadership, while a medium level of motivation and decision-making ability. Factors like AKC visit, farming type, and organizational membership significantly affect the entrepreneurial behavior of indigenous fish farmers, but farmers’ gender, consultation with extension agents, training, information source, education, and experience have a nonsignificant association with entrepreneurship. Farmers who do commercial farming, visit AKC, and are members of social organizations have a relatively more entrepreneurial behavioral index than other farmers. Hence, the study suggests that to sustain and improve fish farming among indigenous groups by accelerating their entrepreneurship, it is essential to improve innovativeness, fish farming knowledge, and leadership among farmers through their frequent visits and consultation with extension agents, engagement in group or organization, and shifting their subsistence farm to commercial farms.


## 3.1. Sociodemographic Status of Indigenous Fish Farmers in Eastern Chitwan

The socioeconomic situation of respondents was assessed by studying demographic attributes like age, education, and experience and farm economic attributes like pond area, training, farming experience, and annual income. Six attributes, namely, age (refers to age after birth in years), education (refers to the year of schooling), pond area (area of fish pond in hectare), annual income (average income from fish farming by farmers in a year), experience (years of fish farming), and training (refers to an average amount of training in fish farming taken by a farmer), were assessed during the study (Table1).Table 1
Socioeconomic and demographic status of respondents.
AttributesMeanSDAge (years)47.9211.59Education (year)6.114.90Pond area (hectare)0.630.56Annual income (000′ Rs)359.375401.671Experience (farming year)9.237.68Training (number)0.751.95Source: field survey, 2019.The mean age of indigenous fish growers in the Eastern Chitwan area was found to be 47.92 years with a minimum of 25 years and a maximum of 71 years, which is in line with the result of the Nepal Fishery Survey 2072 [17] and socioeconomic study of pond farmers in other developing countries [18–20].From the examination of the educational status of respondents, it was determined that 28.75% of them were illiterate and 81.25% were literate. Also, a mean schooling year of 6.11 years was found among fish farmers ranging from 0 years of schooling to 16 years of schooling (bachelor’s degree). A study of fish farmers’ assessment in other rural areas also reported a similar mean schooling year [21, 22], while it is less than the agricultural entrepreneurship behavioral study of African developing nations [20].According to the national sample census of agriculture in Nepal, most fish farmers of Chitwan have a pond area of 0.33 hectares to 1.014 hectares [23]. A similar result of an average of 0.63 hectares of the pond area was found among respondent fish farmers with a minimum of 0.033 hectares and a maximum of 2.7 hectares of the pond area.From the survey result, the average annual income of Rs. 3,59,375 (2896 USD) with a standard deviation of Rs. 8,38,230.6 (6756 USD) was observed among fish farmers of the study area, ranging from Rs. 50,000 (403 USD) to Rs. 25,00,000 (20150 USD). This mean income is more than the result of Olowa and Olowa’s (2015) study of factors affecting entrepreneurship development in agribusiness enterprises in Nigeria [20]. The average annual household income of fish farmers in the study area is higher than the average household income of the overall population of the central development region [24]. This suggests that the aquaculture business is a profitable farming enterprise in Eastern Chitwan.Also from the study, an average of 9.23 years of farming experience with a minimum of 1 year to a maximum of 38 years was found among indigenous fish growers of Eastern Chitwan. The mean experience of fish farmers in the study area is lower than other developing South Asian countries [21, 25] and higher than African developing nations [26].From the result in Table1, it was observed that the farmer has taken an average of 0.72 times training and the number of training has a greater standard deviation than the mean due to a training range of 0 to 12 times. Among 80 surveyed respondents, 22 farmers got training on fish farming practices, which is very low as compared to the fishery census of Chitwan [17] and research on fisheries extension in other South Asian developing countries [21, 27].


## 3.2. Entrepreneurial Behavioral Index (EBI) of Respondents

The entrepreneurial behavior of respondents was assessed by asking multiple questions related to five attributes, namely, innovativeness, decision-making ability, motivation, farming knowledge, and leadership. Farmers using mechanized equipment, using commercial farming technique, doing self-breeding of fish, farming polyculture of fish, and using oral delivery of vaccine are referred as innovative; farmers deciding on fish species to grow, feed to use, increasing pond area, and appropriate treatment and vaccination to fish were considered to have more decision-making power; farmers who were satisfied from fish farming, engaged in group and organization, and learned and taught others about fish farming were considered as motivated farmers; farmers having feeding knowledge, i.e., knowledge on growth promoting hormones, amount of crude protein in feed, and feeding rate; pond management knowledge, i.e., knowledge on the requirement of lime, compost, and organic manure and fertilizer in the pond; market knowledge, i.e., knowledge of fish price and market margin; and disease management knowledge, i.e., knowledge on symptoms, prevention, and treatment of fish disease were considered to have farming knowledge; farmers with board membership in groups, with past experience of leading any program, who engaged in multiple organizations, and who were followed by other farmers on farming practice and knowledge were considered as having leadership (Table2).Table 2
Entrepreneurial behavior of indigenous fish farmers in Eastern Chitwan, Nepal.
AttributesCategoriesFrequencyPercentageInnovativenessLow (<4)5265Medium (=4)1417.5High (>4)1417.5Decision-making abilityLow (<3)2227.5Medium (=3)3847.5High (>3)2025MotivationLow (<2)2227.5Medium (=2)2936.25High (>2)2936.25Farming knowledgeLow (<6)4455Medium (=6)1417.5High (>6)2227.5LeadershipLow (<2)7087.5Medium (=2)56.25High (>2)56.25Source: field survey, 2019.An average of 0.39 EBI ranging from 0.19 to 0.66 was found among respondents (Table3). This is less compared to the result of other entrepreneurship studies [8, 28]. Also, it is found that the majority of respondents have EBI ranging between 0.21 and 0.40. The entrepreneurial behavioral index (EBI) of indigenous fish farmers of Eastern Chitwan was calculated from the score of five entrepreneurial skills, namely, innovativeness, decision-making ability, motivation, farming knowledge, and leadership.Table 3
Overall entrepreneurial behavioral index (EBI) of respondents.
EBI (range)FrequencyPercentage0.00–0.2022.50.21–0.404252.50.41–0.603442.50.61–0.8022.5Maximum EBI = 0.66Minimum EBI = 0.19Mean EBI = 0.39Mean of best ten = 0.57Mean of worst ten = 0.22Source: field survey, 2019.


### 3.2.1. Innovativeness

The result shows that most of the respondents have low innovativeness, which is in line with the study by Anthony et al. (2014) but contradicts the result of Chandra (2005), Rathod et al. (2012), and Patil and Singh (2019) [8, 29–31]. Low innovativeness was obtained among respondents due to traditional and old farming practices.


### 3.2.2. Decision-Making Ability

The majority of respondents have a medium level of decision-making on their fish farm due to their low farm ownership decisions and medium risk-taking behavior. This result is in line with that of Ravikumar et al. (2006), Rathod et al. (2012), and Patil and Singh (2019) [30–32].


### 3.2.3. Motivation

An equal number of respondents have a high and medium level of motivation followed by a low level, which is in line with the study of Vijay Kumar (2001), Suresh (2004), Rathod et al. (2012), and Patil and Singh (2019) [10, 30, 31, 33]. This is due to their engagement in the fish farmers association and satisfaction from the farm.


### 3.2.4. Farming Knowledge

Most of the respondents have a low level of farming knowledge followed by high and medium. This result is in line with that of Adesoji and Kerere (2013), which contradicts the result of Anthony et al. (2014) [8, 34].


### 3.2.5. Leadership

Almost 90% of respondents have a low level of leadership, and this contradicts the result of Anthony et al. (2014) [8]. Most of the farmers have not ever represented fish farming in any field, and the reputed post of fish farming organizations was also governed by limited farmers in Eastern Chitwan, which may be the reason for a low level of leadership among respondents.


## 3.2.1. Innovativeness

The result shows that most of the respondents have low innovativeness, which is in line with the study by Anthony et al. (2014) but contradicts the result of Chandra (2005), Rathod et al. (2012), and Patil and Singh (2019) [8, 29–31]. Low innovativeness was obtained among respondents due to traditional and old farming practices.


## 3.2.2. Decision-Making Ability

The majority of respondents have a medium level of decision-making on their fish farm due to their low farm ownership decisions and medium risk-taking behavior. This result is in line with that of Ravikumar et al. (2006), Rathod et al. (2012), and Patil and Singh (2019) [30–32].


## 3.2.3. Motivation

An equal number of respondents have a high and medium level of motivation followed by a low level, which is in line with the study of Vijay Kumar (2001), Suresh (2004), Rathod et al. (2012), and Patil and Singh (2019) [10, 30, 31, 33]. This is due to their engagement in the fish farmers association and satisfaction from the farm.


## 3.2.4. Farming Knowledge

Most of the respondents have a low level of farming knowledge followed by high and medium. This result is in line with that of Adesoji and Kerere (2013), which contradicts the result of Anthony et al. (2014) [8, 34].


## 3.2.5. Leadership

Almost 90% of respondents have a low level of leadership, and this contradicts the result of Anthony et al. (2014) [8]. Most of the farmers have not ever represented fish farming in any field, and the reputed post of fish farming organizations was also governed by limited farmers in Eastern Chitwan, which may be the reason for a low level of leadership among respondents.


## 3.3. Factors Affecting Entrepreneurial Behavioral Index (EBI)

Nine attributes were studied during the study, namely, AKC visits (farmers visit to government extension office), farming type (attributed according to the size of farm and categorized as commercial and subsistence), gender (categorized as men and women), training taken (farmers taking training related to fish farming), consultation with extension agents (farmers taking suggestions from extension agents like fishery experts, government officials, and agro-vet owners), membership in farmers organization (farmers having membership of farmers group and farmers organizations), major source of farming information (categorized as formal source, i.e., extension centers and organizations, and informal source, i.e., friends and media), education (farmers taking formal schooling are referred as literate and not taking formal schooling are referred as illiterate), and experience (farmers having more than 10 years of experience in fish farming are categorized as more than a decade, and farmers having less than 10 years of experience are categorized as less than a decade). The above attributes were tested with EBI to find out what are the factors affecting the entrepreneurship of respondents Table4.Table 4
Mean EBI comparison among various attributes of respondents.
AttributesCategoriesFrequency (%)Mean EBIt-valueAKC visitsYes36 (45)42.8472.84∗∗No44 (55)36.193Farming typeCommercial26 (32.5)46.5704.75∗∗Subsistence54 (67.5)35.632GenderMen63 (78.75)40.2911.77Women17 (21.25)35.098Training takenYes22 (27.5)42.7651.84No58 (72.5)37.830Consult with an extension agentYes5 (6.25)46.1661.49No75 (93.75)38.722Membership in farmer's organizationYes61 (76.25)40.6962.28∗No19 (23.75)34.342Major source of farming informationExtension/Organization43 (53.75)40.4651.13Friends and media37 (46.25)37.702EducationLiterate57 (71.25)40.1461.24Illiterate23 (28.75)36.811ExperienceFor more than a decade32 (40)37.5521.10Less than a decade48 (60)40.277The symbols∗ and ∗∗ indicate statistically significant at p ≤ 0.01 and p ≤ 0.05, respectively. Source: field survey, 2019.Nearly half of the respondents visit the government extension service or Agriculture Knowledge Centre (AKC) [21, 26, 35], and farmers visiting AKC have significantly more knowledge index. An agricultural extension center visit is an avenue for fisheries development as it provides information, knowledge, consulting, support, and technical guidance to farmers [34], which increases motivation, innovativeness, coordination, and leadership skills that eventually improve the entrepreneurial behavior of farmer [34, 36].About one-third of respondents do commercial fish farming in the study area, and they have statistically more knowledge index than subsistence farmers. Commercial fish farmers are farmers with larger pond areas and more investment and returns that generate higher purchasing power for inputs which increases their innovativeness, leadership, and entrepreneurship [22]. Also, the size of enterprises affects agricultural entrepreneurship [37].Among surveyed indigenous fish farmers, only 21% are female farmers. This indicates that male is the dominant group of gender involved in fish farming [18, 19, 22, 35]. According to the t-test, it was found that gender is statistically nonsignificant to entrepreneurship.A few number of respondents (27%) were trained farmers, which is in line with the study of Khatun and Ahmed [21, 27]. The resulted t-test statistics suggested that the mean difference between trained and untrained farmers was not statistically significant.Only a few pond farmers consult with extension agents [19], which is due to poor access to extension services and extension agents in rural areas [38]. From the t-test, it was observed that there is no significant association between consulting with an extension agent and entrepreneurship.The majority of respondents were engaged in social organizations, which is in line with the entrepreneurship assessment of Olowa and Olowa [20], but contradictory to the finding of the fishery extension assessment by Agbebi in Nigeria [26]. From the t-test, it was found that farmers engaging in organizations have significantly more entrepreneurial behavioral indexes than others. Farmers engaging in organizations have a more entrepreneurial index because organizational involvement enables social participation and interaction [39], which helps in developing entrepreneurship.From the study, it was observed that farmers get more information about farm enterprise practices from extensions and organizations than from friends and media. The result of thet-test confirms that there is no significant association between information source and entrepreneurship behavior index at a 95% confidence level.About 70% of respondents were literate, and they have more EBI because education has been known to enable farmers access new information and practices [40] and help in decision-making [42]. But, the t-test results suggest that this mean difference is statistically nonsignificant [20].Only 28% of farmers have experience of more than 10 years, but their experience was not found to be significantly affecting the mean entrepreneurship behavior index.From the mean comparison by thet-test, it was observed that government extension center visit (p ≤ 0.01), farming type (p ≤ 0.01), and membership in an organization (p ≤ 0.05) were found to be significantly associated factors affecting entrepreneurial behavior of indigenous fish farmers in Eastern Chitwan, while gender, training, extension consult, information source, education, and experience were not statistically associated with indigenous fish farmers entrepreneurship. This obtained result is in line with that of Olowa and Olowa (2015) but contradicts the result of Balhara et al. (2013), Khan (2014), Obeng and Weber (2014), and Seyed et al. (2011) [13, 20, 41–43].In brief, the study resulted in the majority of respondents being middle-aged, male farmers, with an average education. About one-fourth of respondents are trained farmers, very few respondents consult with extension agents, and nearly two-thirds of respondents are subsistence farmers. On average, respondents are more experienced than African developing nations but less experienced than other developing countries in South Asia. Indigenous fish growers have very low innovativeness, knowledge, and leadership but have medium motivation and decision-making ability. Also, the majorities have a low level of innovativeness, farming knowledge, and leadership, while a medium level of motivation and decision-making ability. Factors like AKC visit, farming type, and organizational membership significantly affect the entrepreneurial behavior of indigenous fish farmers, but farmers’ gender, consultation with extension agents, training, information source, education, and experience have a nonsignificant association with entrepreneurship. Farmers who do commercial farming, visit AKC, and are members of social organizations have a relatively more entrepreneurial behavioral index than other farmers. Hence, the study suggests that to sustain and improve fish farming among indigenous groups by accelerating their entrepreneurship, it is essential to improve innovativeness, fish farming knowledge, and leadership among farmers through their frequent visits and consultation with extension agents, engagement in group or organization, and shifting their subsistence farm to commercial farms.


## 4. Conclusions

Indigenous fish growers in the study area are dominated by middle-aged males with average education, no training on fish farming practice, less consultation with extension agents, and subsistence farming. They have about forty percent of an entrepreneurial behavioral index with very low innovativeness, knowledge, and leadership but have medium motivation and decision-making ability. Entrepreneurial behaviors of respondents are affected by a visit to a government extension office, type of farming, and membership in an organization. Farmers visiting government extension office, doing commercial farming, and engaging in groups or organizations has more EBI values as compared to others; hence, farmers should be engaged in the group, motivated to visit extension personnel and experts, and encouraged to do commercial farming for improving their entrepreneurship.



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*Source: 3154821-2022-07-21.xml*