Evaluating Agripreneurs’ Satisfaction: Exploring the Effect of Demographics and Emporographics

This paper attempts to gauge the satisfaction of agripreneurs and seeks to explore the effect of demographics and emporographics on the agripreneurs’ satisfaction. This study proposes a seven-dimension survey instrument, called AprenSAT, for measuring agripreneurs’ satisfaction. Responses from 784 agripreneurs are analyzed by applying exploratory and conrmatory factor analysis and multiple linear regression. The extraction of seven factors conrms that agripreneurs’ satisfaction is inuenced by material availability, government support, farm growth, farm income, market performance, cultivation & production and perceived farm image. The linear regression result delineates that demographic factors such as age, education level and farming experience signicantly inuence the agripreneurs’ satisfaction. Similarly, variables of emporographics such as farm age, farm size, annual income, land ownership, sources of funds, and intercropping have a substantial inuence on agripreneurs’ satisfaction. We recommend information dissemination, hands-on training, the creation of adequate infrastructure and technology adoption to enhance agripreneurs’ satisfaction and rural development.


Introduction
Entrepreneurship is widely recognized as one of the key drivers of economic growth and development of emerging economies in the globe (Spring 2009). It is best described as the pursuit of economic a uence through the individual's innovative ideas while functioning in an uncertain environment with limited resources (Austin et al. 2006). Entrepreneurs launch new business ventures to lift their wealth and elevate the prosperity of their country through faster economic growth (Smit 2004). In emerging economies, a plethora of research works primarily focused on entrepreneurship and entrepreneurial behaviour among small business units (Adom et al. 2018; Obeng et al. 2014). Although mainstream entrepreneurship research had previously ignored agriculture and its allied sectors, this scenario has changed in recent years with new studies on diverse phenomena in many sectors across the world (Afreh et al. 2019;Boer 2013). Still, those studies are inadequate to address the burning issues of entrepreneurs in agriculture and allied sectors. We observe a marked difference among urban and rural populations in which poverty incidence is higher among rural poor in developing nations, especially in India. Obviously, there is an expectation that entrepreneurship development in the agricultural sector would play a critical role in the mitigation of poverty and wealth generation (Smit 2004).
At the time of independence, the economy of India was predominantly an agrarian economy. During 1950-51, the contribution of agriculture, in terms of real gross value added, to the real total gross value addition was 53.7 per cent. Since then, the contribution of agriculture to the GDP has been slowly drifting lower every year and in terms of percentage, the values stand at 33 per cent and 19.9 per cent for the year 1990-91 and 2020-21, respectively (GOI 2021). At the same time, captivatingly, the number of people employed in agriculture and allied sectors declined only moderately from 70 per cent during the 1950s to around 58 per cent during 2020 (IBEF 2021). This paradoxical phenomenon provides the answer to two pertinent questions. One answer is that agriculture is slowly losing out to other sectors such as industry and services in their contribution to GDP. Another point of explanation that worth attention is that, still, more people completely rely on agriculture for their livelihood. This translates into more people sharing lesser income from agriculture which ultimately resulted in disguised unemployment, a lower standard of living and, poverty for those dependent on agriculture. India being the second most populated nation having 17.5 per cent of the world population has only 2.4 per cent of world land to feed its people (World Bank 2016).
Even though agriculture is seen as a low-tech industry, it is also considered as a critical sector contributing hugely to the industry and service sector in the form of raw material and other inputs (Lans et al. 2013;Bairwa et al. 2014). The changing political, economic, social and natural environmental factors necessitate the need to revisit the agriculture sector with new vigour for the sustainable development of other sectors and the survival of humankind. At this juncture, it is highly desired that the farmers are donned with entrepreneurial skill sets. Originally, during the 18th century, the term entrepreneurship was associated with agriculture by French physiocrats, but apparently, it is used the least to relate an agricultural activity (Singh and Krishna 1994;Hazarika and Goswami 2018;Singh 2013). Agricultural entrepreneurship refers to the establishment of an innovative economic enterprise for the purpose of growth or gains under situations of risk and uncertainty in agriculture (Pindado and Sánchez 2017). The term agricultural entrepreneur is synonymously used with many evolving terms like agropreneur, agripreneur, owerpreneur, farmerpreneur, horti-preneurs, apipreneur, shpreneurs, and aquapreneurs. We propose to de ne Agripreneurs as entrepreneurial people in agriculture and allied sector who either create or run either formal or informal agriventures.
Farmers and those who perform agri-related activities are entrepreneurs in that they run businesses (McElwee 2008). There is a general trend suggesting farmers need to become entrepreneurs (Frans et al. 2011). The ever-changing environmental factors invite the farmer entrepreneurs to acquire new sets of relevant entrepreneurial skills that need not be the same as industrial and service sector entrepreneurs (Pyysiäinen et al. 2006;Subagyo et al. 2020). The globalization and economic reforms around the globe have compelled agripreneurs to take up higher responsibility to run their farm-oriented businesses (Alex 2011). Agripreneurs have to nd ways and means of carrying out their farm businesses innovatively yet, pro tably. As agriculture in India is the largest employer, innovation and creativity in the agriculture sector by agripreneurs will provide new impetus to the decaying farming sector and, consequently, create more high-income jobs (Ashoka et al. 2017; Kerstin and Martin 2017). There is a slow but steady trend of enterprising agripreneurs going all out for technology adoption in their farming and related activities. Application of arti cial intelligence and smart technologies in cultivation, crop management, harvesting to post-harvest management, usage of agribots, precision farming, greenhouse farming and organic farming are some of the emerging themes preferred by modern tech-savvy agripreneurs (Abdolazim et al. 2012; Federica and Eugenio 2019).
As ingenious agripreneurs in India start to look beyond their domestic market to market their produce, technology adoption and innovation are the means through which they can ensure world-class quality while increasing both farm productivity and pro tability. Highly educated youth will be inclined to agripreneurship as a career option once; it becomes socially acceptable and highly pro table. Carefully crafted agripreneurship programmes will mend youth's ways in favour of either agripreneurship or managerial workforce to serve the agricultural sector across the globe (Bairwa et al. 2014). Based on these assessments, this study seeks to gauge the satisfaction of agripreneurs and explore the effect of demographic and emporographics on agripreneurs' satisfaction by taking farmer entrepreneurs in India as the respondent unit.

Literature Review
Agripreneurs' Satisfaction Assessing the satisfaction of agripreneurs who are in the business of cultivation and marketing agricultural products is essential for developing suitable policy initiatives that will address the needs and demands of agripreneurs (Kassem et al. 2021). Many factors that determine the overall satisfaction of farming entrepreneurs include agricultural credit usage (Erdogan et al. 2016), the supports provided by the government for maintaining the nancial structure and livestock (Demirtas 2021) and cognitive and emotional factors (Higuchi et al. 2020). Sharma (2014) revealed that satisfaction was greatly in uenced by information sources and services among the farmer entrepreneurs as reliable sources of information were relatively inaccessible to them. Agripreneurs expect the availability of timely information since most of their produce is perishable in nature. Ao et al. (2017) found that the rural infrastructure, including access roads and uninterrupted electricity supply, plays an undiminished role in the agripreneurs' satisfaction. Relationship marketing, logistics (Acar 2020), and communication technology play a vital role in enhancing farmers' satisfaction (Elias et al. 2021).

Demographic Characteristics and Agripreneurs' Satisfaction
Demographic factors describe the characteristics of study participants. It is essential to determine whether the sample respondents in a study are a representative sample of the target population for the generalization of results. Generally, they are considered as independent variables because they cannot be changed. Demographic factors include age, gender, education, marital status, family type, professional experience, etc. They play a considerable role in the satisfaction of agripreneurs (Ali et al. 2018). Lauwere (2005) found that personal characteristics had negatively affected agripreneurs.
Age is a vital demographic variable. Bradley and Roberts (2004) and Gazioglu and Tansel (2006) identi ed a U-shaped connection between age and satisfaction. Indeed, young entrepreneurs have a high level of con dence than older (Forbes 2005). Age has a substantial in uence on the agripreneurs' satisfaction (Dias et  Previous studies have yielded mixed results on con rming the relationship between gender and satisfaction with rm performance. Selvendran (2017) and Wayne et al. (2014) noted that gender was correlated with agripreneurs' satisfaction. Women entrepreneurs were more satis ed with business than men (Cooper and Artz 1995). But, the result of studies conducted by Madhumitha and Karthikeyan (2020), Kuada (2009) and Sinyolo et al. (2017) identi ed that gender was not related to the satisfaction of agripreneurs.
Education is a vital component that provides the required knowledge, skills, ability, self-con dence and motivation (Cooper et al. 1994 The knowledge and skills needed to run an agri-business can be gained by observing how family members perform their tasks on their farms. The children of the agricultural family can easily understand business nuances (Kim et al. 2006). Madhumitha and Karthikeyan (2020) claimed that family support was considered as the key factor in motivating women to become successful agripreneur as young women in many societies rely on family members' opinions on their business and personal Like education, experience in agribusiness is also one of the crucial factors which support acquiring business skills. An experienced entrepreneur can realize their limitations than young entrepreneurs (Wright et al. 1997). According to Hayward et al. (2006), experienced entrepreneurs may be overcon dent when the nature of an enterprise varies from core areas. Fraser and Greene (2006) noted that experienced entrepreneurs were apparently more satis ed. Similarly, Dias et al. (2019b), Ovharhe et al. (2020) and Selvendran (2017) showed a positive correlation between farming experience and satisfaction of agripreneurs. But, Bradley and Roberts (2004) found that entrepreneurial experience did not affect entrepreneurs' satisfaction.

Emporographics and Agripreneurs' Satisfaction
Emporographics are known as farm characteristics which play a vibrant role in the segmentation of the agricultural business. Several prior research works disclose the satisfaction of agripreneurs in uenced by the set of essential emporographics variables viz., farm age, farm size, annual income, land ownership, sources of funds and intercropping.
Age of the farm notably connected with the gaining professional experience of the agripreneurs. Seasoned farmers perhaps, could learn more entrepreneurial skills from their routine business operations. The longevity of business operations ultimately determines the business growth and performance (Sleuwaegen and Goedhuys 2002). Richard et al. (2021) revealed that farm age has positively in uenced the satisfaction of agripreneurs. Additionally, many studies identi ed that farms' age is considerably related to the satisfaction of agripreneurs (Antoncic 2009; Sagire Lucas 2017).
A farm size denotes an area of land devoted to agricultural processes to produce food and other crops that determine the capacity of production and volume of business operations of the agripreneurs. It is an indication of the farm's potential for pro t-making. Thus, it serves as a surrogate for the entrepreneur's prestige, success and eliciting satisfaction (Weaver 1977 (2015) found that agripreneurs derived additional income from intercrops, generate more employment and also, increase soil fertility.
Even though our review of the literature is not extensive, it clearly highlights the gaps in existing research. Based on the analysis of available literature, we seek to explore the role of demographics and emporographics on agripreneurs' satisfaction. In this regard, the following two hypotheses are framed and tested. Based on prior studies, we hypothesize that demographic characteristics such as age (H1a), gender (H1b), education level (H1c), marital status (H1d), type of family (H1e) and farming experience (H1f) signi cantly in uence the agripreneurs' satisfaction. Likewise, emporographics factors such as farm age, (H2a) farm size (H2b), annual income (H2c), land ownership (H2d), sources of funds (H2e) and intercropping (H2f) signi cantly in uence the agripreneurs' satisfaction. Figure 1 depicting the hypothesized relationship between the dependent (agripreneurs' satisfaction) and independent variables (demographics and emporographics).

Materials And Methods
The current study aims at gauging the satisfaction of agripreneurs and seeks to explore the effect of demographics and emporographics on agripreneurs' satisfaction. The agripreneurs who had been involved in the cultivation and marketing of agricultural products in the rural area were the target population. The Salem district was purposively selected for the study since relatively a great number of people have rigorously engaged in agripreneurial activities than their counterparts in other districts of Tamilnadu. A eld survey was conducted to gather data from the agripreneurs. In all, 800 questionnaires were distributed, 16 of the questionnaires were incomplete. Thus, 784 questionnaires were used for analysis.
In this study, carefully crafted a questionnaire was used to amass responses from the agripreneurs. Using a questionnaire for data collection is considered an appropriate method to obtain correct responses (Chisnall 2001).
After the extensive literature survey, we amassed scales and items related to agripreneurs satisfaction from earlier studies. These were reworded to suit agricultural entreprenerus. Moreover, we found that there is no comprehensive standardized instrument for measuring agripreneurs' satisfaction. So, we propose a new survey instrument developed by us that effectively measures the agripreneurs' satisfaction. We would prefer to call this instrument AprenSAT. This instrument covers seven dimensions, namely, material availability, government support, farm growth, farm income, market performance, cultivation and production and perceived farm image. The pilot study, frequent discussions made with agripreneurs and in-depth interactions with subject experts provided the necessary input and direction in de ning, crafting, and re ning the AprenSAT Questionnaire.
Further, the content validity was checked by a panel of experts consisting of two representations from each category, namely, subject expert, doctoral scholar and agripreneur. To check the comprehensibility of the AprenSAT instrument, a pilot study was conducted with the original pre-nal version of the drafted questionnaire that comprised 34 attributes for measuring the agriprenerus' satisfaction. After the pilot study, we observed that only 29 attributes are consistent with the seven dimensions of AprenSAT. Eventually, the nal version of the questionnaire has seven dimensions of AprenSAT covering only 29 attributes out of the original 34 attributes (Table 1). This novel AprenSAT Questionnaire could effectively be used not only in India but across the globe to measure the satisfaction of agripreneurs.  The data collected from the agripreneurs were analyzed using the SPSS and SPSS-AMOS. The construct validity was measured through the Exploratory Factor Analysis (EFA) and Con rmatory Factor Analysis (CFA). The discriminant validity was assessed using Construct Reliability (CR) and Average Variance Extracted (AVE). Further, multiple linear regression was employed to identify the effect of demographic and emporographics on agripreneurs' satisfaction.

Results
This section presents the demography of agripreneurs, emporographics of agri-ventures, agripreneurs' satisfaction, and the effect of demographic and emporographics on agripreneurs' satisfaction. The demography of the agripreneurs as exhibited in Table 2 reveals that out of 784 agripreneurs, 44.6 per cent were in the age group of below 35 years. It indicates that young farmers as agriculture entrepreneurs constitute the major chunk of the study population while the middle-aged and old-aged farmers groups constitute the remaining study population in the study area.

Demographics and Emporographics of Agripreneurs
Another interesting inference that can be made from this descriptive analysis is that the majority (73.  The emporographics as presented in Table 3

Results of Exploratory Factor Analysis for Satisfaction of Agripreneurs
The result of EFA presented in Table 4. As the value of KMO stood at 0.644, the application of factor analysis was highly appropriate for the variables included in this study (Hair et al., 2010). Bartlett's χ 2 value was 23721.048, and it was signi cant (p=<0.05) at a 5 per cent level. It is noted that a high level of inter-relationship was found among the scale variables. So, these variables were adequate for the PCA. The factor analysis by PCA with varimax rotation identi ed seven Eigenvalues, which were greater than 1. These seven extracted factors explained 78.77 per cent of the total variation depicting the presence of seven factors that have predominantly in uence the satisfaction of agripreneurs. In a nutshell, the material availability, government support, farm growth, farm income, market performance, cultivation and production and perceived farm image were highly in uenced in the agripreneurs' satisfaction ( Figure 2).  CFI=0.912; TLI=0.901; 2 /df =3.16). The value of the RMSEA was 0.049, which denotes that the model t was good as RMSEA value less than 0.08 is the gold standard for a strong t of the model (Browne and Cudeck 1993). This goodness of t index for the seven-factor model shows the con rmation of construct distinctiveness for materials availability, government support, farm growth, farm income, market performance, cultivation and production and perceived farm image.

Results of Con rmatory Factor Analysis (CFA) and Discriminant Validity
Moreover, we checked for discriminant validity by comparing the variance-extracted estimates of the measures with the squared correlation between constructs, as described by Fornell and Larcker (1981) and Netemeyer et al. (1990). The average variance-extracted (AVE) for all variables in this investigation was more than the suggested value of 0.50 (Malhotra and Dash, 2011). Since the value of variance extracted was more than the squared correlation, the measures have discriminant validity.
In this study, the estimates of variance extracted for cultivation and production and perceived farm image were 0.563 and 0.546, respectively, and both variables were more than the squared correlation between them. Likewise, the squared correlation between government support and farm growth was more than the variance extracted. Based on these statistics along with the CFA results, the study establishes discriminant validity between these seven variables.  Table 6 reports mean (x̅ ), standard deviation (σ) and correlation. The mean values indicate that agripreneurs were highly satis ed with the market performance followed by farm growth, perceived farm image, farm income, materials availability, government support and cultivation and production. The study observed a strong positive correlation (0.594) between farm growth and government support, a moderate positive correlation (0.473) between materials availability and cultivation and production and a weak positive correlation (0.385) between materials availability and perceived farm image. Furthermore, government support was signi cantly related to farm growth, farm income, market performance, cultivation and production and perceived farm image.

Effect of Demographic and Emporographics on Agripreneurs' Satisfaction
Multiple regression was employed to nd out the effect of independent variables namely, demographic factors and emporographics on the dependent variable namely, satisfaction of agripreneurs. The effect of demographics and emporographics on the agripreneurs' satisfaction as presented in Table 7 reveals that the satisfaction of agripreneurs was substantially in uenced by the demographic characteristics included in the model since Adj.R 2 value stood at 0.427. It denotes that 42.7per cent of the difference in the agripreneurs' satisfaction was in uenced by the set of demographic variables, which con rms that the proposed model was a strong predictor. There was a strong association between agripreneurs' satisfaction and demographic characteristics since the 'R' value was 0.687. The F statistic (18.692) was signi cant at a 5 per cent level (p≤.05) points out that the overall model t was signi cant.
The regression coe cient shows that the demographic characteristics of agripreneurs such as age (β=-.328; t=.-1.702, p ≤ 0.05), education level (β=.160; t=1.163, p ≤ 0.05) and farming experience (β=.371; t=4.447; p ≤ 0.05) substantially in uence the agripreneurs' satisfaction. It could be ascertained that that age has a substantial negative in uence on agripreneurs' satisfaction. Further, gender, marital status and type of family did not signi cantly (p > 0.05) in uence the agripreneurs' satisfaction. Therefore, the study hypotheses H1 a , H1 c, and H1 f are proven correct, whereas the study failed to prove the remaining hypothesis such as H1 b , H1 d, and H1 e.  (Figure 3).

Discussion
This study observes that agripreneurs' satisfaction was highly in uenced by factors such as market performance, farm growth, perceived farm image, farm income, materials availability, government support and cultivation and production. There was a marked linkage between cultivation and production and farm image. There exists a moderate positive correlation between materials availability and cultivation and production. Moreover, government support was signi cantly related to farm growth, farm income, market performance, cultivation and production and perceived farm image. In addition, the study identi es that age has a negative in uence on the agripreneurs' satisfaction. It denotes that as In the study area, the farmers follow intercropping practices, which facilitate getting a higher return from the same piece of land. Thus, the intercropping pattern has a positive in uence on the satisfaction level of the agripreneurs in the study area. This result conforms with the ndings of prior research works done by Xiaoqing et al. (2017) and Jaganathan and Nagaraja (2015).

Recommendations
Among agripreneurial operations, cash crop cultivation is considered to be the most pro table income-generating business in the Indian economy. The agripreneurs will be highly motivated when the government comes out with supportive policies and implement suitable and actionable marketing strategies. Adequate information about the market, marketing strategies and export opportunities must be communicated to the agripreneurs through proper channels and facilitated by the fast-growing digital economy. Besides, capitalizing on IoT during the production phase will also help in data mining and open doors to new economic activities in the blockchain industry. The fourth industrial revolution is not just for the heavy or technological-based industries but also agriculture and, in this case, the cultivation, production, promotion and marketing, distribution and sales of the agricultural products and agro-based value-added products. Cultivation and production of agricultural products are seasonal. Hence the agripreneurs need to engage in other income-generating activities to supplement their livelihood. Scheduling the production and harvesting times, the agripreneurs and farm managers may plan with the cultivation of intercrops or be engaged in other sectors to generate additional cash ow. This will ensure that they have continuous income for daily and monthly expenses. The agripreneurs may also be assisted with nancial support during the seasonal demand to compensate for the unexpected loss encountered. On the other hand, the government can take necessary steps to provide an incentive for research and development (R&D) to diversify the use of agricultural products.
Training programmes can be conducted for the agripreneurs so that they can learn new techniques and technologies in cultivation, which in turn takes them to the next level in cultivation. Capacity-building initiatives are crucial for the empowerment of the farmers' community, facilitating the creation of an effective value chain for agricultural products and value-added products. This will increase the demand for agricultural and agro-based value-added products domestically and internationally, which will boost the growth of the economy in the long run.
The cost of production or the yield per acre is signi cantly high. The farmers can meet the expenses only when the product reaches the markets on time. Besides having a good access road, transportation facilities and adequate storage facilities must be provided. The entrepreneurs who see this as a business opportunity may be provided nancial and technical support for the creation of transportation and storage facilities. These facilities in turn will create more jobs. Most importantly, these measures will ensure that the agricultural products reach the clients in various markets be it domestic or international in pristine conditions and on time; otherwise, most of the agricultural produce would lose its value and may only be sold below the market value or just be disposed of due to its perishable nature. The barriers and obstacles related to the communication process between wholesalers, retailers and commission agents must be recti ed. An integrated system that allows arti cial intelligence to record the trend of production will help the buyers and clients be updated on the availability of the agricultural products based on the origin of locality, the quantity and the quality of the produce. This will also help the clients be prepared for the arrival times for collection on various occasions, celebrations, and events. In a nutshell, only a coordinated set of activities that include government support, training, institutional support, and technology modernization in every stage of production to supply chain can positively enhance the livelihood and satisfaction of agripreneurs. Moreover, agripreneurship activities signi cantly support the economic growth and development of India.

Conclusion
The current study investigates satisfaction of agripreneurs and seeks to explore the effect of demographics and emporographics on agripreneurs' satisfaction. We propose a new survey instrument, called AprenSAT, for effective measurement agripreneurs' satisfaction cutting across regions. The extraction of seven factors con rms the presence of seven dimensions of agripreneurs' satisfaction. The heptagon model of AprenSAT reveals the seven factors as market performance, farm growth, perceived farm image, farm income, materials availability, government support and cultivation and production. The regression result proves that demographic factors such as age, education level and farming experience have a signi cant in uence on the agripreneurs' satisfaction. Also, emporographics such as farm age, farm size, annual income, land ownership, sources of funds, and intercropping have a substantial in uence on agripreneurs' satisfaction. The results derived from the current study are relevant and valuable in numerous ways. First, this study helps to understand the level of agripreneurs' satisfaction towards their agri-business. Secondly, the proposed survey instrument, the AprenSAT is a valid, reliable and effective tool for measuring the agripreneurs' satisfaction. Thirdly, the proposed seven-dimension heptagon model of AprenSAT has remarkable utility to all stakeholders starting from researchers, academicians, etc., to policymakers. Fourthly, this study makes an immense contribution to the existing body of knowledge. Fifthly, since we recommend to policymakers the coordinated set of activities including training, institutional support and technology modernization in every stage of production to supply chain to enhance the livelihood and satisfaction of agripreneurs, our recommendation will have a ripple effect on the well-being of not only agripreneurs but also, on the rural, industry and service sector. Regression Model for Effect of Demographics and Emporographics on Agripreneurs' Satisfaction