Study on factors influencing the performance of the farmer-producer organizations dealing with non-perishable products

Tamil Nadu had almost 900 FPOs at that time, with more than 50% of them dealing with non-perishable products in various forms. Each of them had the highest potential to grow, but only a few were performing well, while others were not. While observing them, there were some factors that differentiated the well-performing FPOs from the other FPOs that were yet to perform well. The study aimed to find the factors that influenced the performance of the Farmer's Producer Organizations. Many of the influencing factors were identified through brainstorming with different CEOs, boards of directors of the FPOs, and other experts in the field. Major factors such as operational factors, managerial factors, financial factors, and leadership factors were considered for the study. These factors were then converted into statements to determine the degree of influence on the performance of the FPOs. The sample was collected from 60 respondents (CEOs and BODs). Once the data were collected, the analysis was carried out using the Exploratory Factor Analysis method in the SPSS software. The factors were divided into three levels: highly influencing, moderately influencing, and low influencing factors. The study found that out of 68.7% of the identified factors influencing the performance, 53% of the performance was influenced by operational factors, 8.5% of the performance was influenced by marketing factors, and 7.146% of the performance was influenced by financial factors.

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Percentage: Less than 50 vs 50 – 70 vs 70 – 90 vs 90 – 130 vs Above 130Close ×

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Variance explained: Operational /... vs Marketing Factors vs Financial FactorsClose ×

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Introduction

The performance of Farmer Producer Organizations (FPOs) had been a subject of considerable research interest, with various studies exploring the factors that influenced their effectiveness and success. These investigations had provided valuable insights into the dynamics that shaped FPO performance and had offered a deeper understanding of the challenges and opportunities within this realm. For instance, Amitha et al. (2021) [1] had focused on FPOs in the Medak district of Karnataka, highlighting the significance of education, group leadership, communication, and participation as key factors influencing FPO performance. Sanjiv Kumar et al. (2023) had conducted an extensive study across multiple Indian states, revealing that FPOs engaging in diverse activities had tended to achieve higher turnover and net profit. Their findings had underscored the importance of factors like membership, Board of Directors size, operational years, and paid-up capital in shaping FPO success. Mahesh Babu et al. (2021) [4] had examined how member characteristics related to FPO performance, emphasizing the positive impact of education, income, training, market orientation, and social involvement. Neha Kumari (2023) had delved into the competencies crucial for effective FPO management, highlighting areas like planning, marketing, financial management, and leadership as pivotal for enhanced performance. Beyond the Indian context, studies by Agrawal (2022) [3] , Gagana (2023) [6] , had also explored various aspects of FPO performance, ranging from factors influencing farmer participation and technical efficiency to market performance and welfare. These studies had collectively shed light on the multifaceted nature of FPOs and their performance determinants.

By examining these diverse findings, we could gain a comprehensive understanding of the factors that drove the success of Farmer Producer Organizations, informing strategies to enhance their impact and effectiveness in agricultural contexts.

Materials and Methods

Materials and Methods

Study area

The data had been collected from the CEOs and Board of Directors of the FPOs dealing with non-perishable products randomly all over Tamil Nadu to rate the most influential factors for the performance of the FPO. A total of 60 responses were collected from various FPOs dealing with non-perishable products.

Tool for analysis

Exploratory factor analysis were used to analyze and to identify the most influential characteristics that determined the performance of the FPOs dealing with non-perishable products.

Result and Discussion

Result and Discussion

Socio-economic profile of the respondents

The socio-economic profile of the respondents were analysed and shown in the table. The survey had gathered responses from 60 participants regarding various aspects of Farmer Producer Organizations (FPOs). In terms of the FPOs' age, the majority of them had been in existence for 4 to 7 years (68.33%), followed by those in operation for 8 to 11 years (25%). A smaller percentage had represented FPOs of different age ranges. When it came to the number of members within these FPOs, the data indicated a diverse distribution. The majority of FPOs had fallen within the range of 900 to 1100 members (38.33%), followed closely by those with 1250 to 1500 members (26.66%). Some FPOs had had larger membership sizes, but they had formed a smaller proportion of the total. The survey participants had also identified the promoting agencies behind the FPOs. Notably, NABARD had played a significant role in promoting 35% of the FPOs, followed by TNSFAC at 45%. There had also been FPOs that had been self-promoted (13.33%) or promoted by other agencies, such as TNIAMP and Central SFAC. Regarding turnover, most FPOs (75%) had reported having a turnover of less than 50 lakhs Rupees. A smaller percentage had had turnover values in the ranges of 50-70 lakhs, 70-90 lakhs, 90-130 lakhs, and above 130 lakhs, each accounting for 10-5% of the FPOs. Gender distribution within the FPOs had been skewed, with the majority of members being male (96.66%), while only a small percentage had been female (3.33%).

In terms of education levels, the majority of FPO members had had undergraduate degrees (80%), followed by those with higher secondary education (10%) and postgraduate qualifications (6.66%). Secondary-level education had been represented by 3.33% of the members, while no members had had primary education. When it had come to experience, the distribution had been fairly balanced. A significant portion of FPO members had had 1 year or less of experience (28.33%), while others had had 2 years (35%), 3 years (15%), 4 years (10%), and 5 years or more (11.66%) of experience. In summary, the survey had shed light on various aspects of the surveyed Farmer Producer Organizations, including their age, membership sizes, promoting agencies, turnover, gender distribution, educational qualifications, and experience levels of their members. The results had indicated a diverse landscape of FPOs with varying characteristics and dynamics.

Factors influencing the performance of the FPOs

According to the study conducted by Amitha et al. (2021) [1] , the factors that contributed to the performance of the FPO in the Medak district of Karnataka, with three different promoting institutions, had been analyzed. The study had found that education, group leadership, group communication, and group participation were the most influencing factors. In this study, the factors that influenced the performance of the FPOs, dealing with non-perishable products were identified. .000

Based on the information provided in Table 3.0, it could be understood that the KMO (Kaiser-Meyer-Olkin) statistic value had been 0.845, which was greater than the recommended value of 0.5. This had suggested that the sample size used for the analysis had been sufficient and appropriate. Additionally, Bartlett's test had yielded an approximate chi-square statistic of 975.692 with 59 degrees of freedom, which had been significant at the 0.01 significance level. In simple terms, this had meant that using factor analysis had been a suitable and valid approach for further analyzing the data. The use of principal component analysis (PCA) had helped us understand how factors and variables were connected in the analysis. These connections were called factor loadings and had shown how variables related. However, while factor loadings had helped us understand relationships, they might not have perfectly grouped all variables under their respective factors. Looking at Table 4.0, it had been evident that three components had Eigenvalues greater than one. These three components had explained around 69.159% of the variance in the data. Table 5.0 showed that there were cases where variables were associated with more than one factor. To make sense of how variables should be grouped under specific factors, the components were rotated using a method called varimax rotation with Kaiser Normalization. We can understand from Table 6 that factor loadings were obtained after performing a varimax rotation. Factor loadings of 0.5 or higher are taken into account. The initial component had 6-factor loadings exceeding 0.5, the second component had 5, and the third component had 4, all with eigenvalues surpassing 0.5. These components are given appropriate names based on their factors. It could be inferred from the factor analysis that procuring products at a higher price than the market price, Leadership, aggregation of the product by the FPO, regular Procurement of products from the farmers, sharing the profit, percentage of contribution from value addition of the product were the most influential factors determining the performance of the FPOs dealing with nonperishable products.

—	Factors	C 1	C 2	C 3
1	Procuring products at a higher price than the farm gate price	0.735
2	The leadership of the CEO & Chairman	0.724
3	Aggregation of the product by the FPO	0.721
4	Regular Procurement of products from the farmers	0.707
5	Providing infrastructures	0.583
6	Providing inputs to the farmers	0.515
7	Percentage of contribution from value addition of the product		0.796
8	Branding		0.725
9	Potential to meet all supply with demand		0.677
10	No.of. marketing channels followed by the FPOs		0.581
11	No. of members selling through FPO		0.531
12	Turnover of the FPO			0.822
13	Access to credit			0.743
14	Transparency in Financial transactions			0.696
15	Grants received by the FPO			0.690

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Table 6Close ×

Rotated component matrix

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—	Factors	Component 1	Component 2	Component 3
1	Procuring products at a higher price than the farm gate price	0.826	-.234	-.226
2	The leadership of the CEO & Chairman	0.801	-.122	-.103
3	Aggregation of the product by the FPO	0.797	0.073	-.283
4	Regular Procurement of products from the farmers	0.783	-.382	-.039
5	Providing infrastructures	0.760	0.150	-.050
6	Providing inputs to the farmers	0.739	-.169	-.010
7	Percentage of contribution from value addition of the product	0.732	0.316	0.199
8	Use digital marketing for branding and sales	0.731	0.131	-.342
9	Potential to meet all supply with demand	0.725	0.512	0.155
10	No.of. marketing channels followed by the FPOs	0.722	-.028	-.356
11	No. of members selling through FPO	0.703	-.411	0.249
12	Turnover of the FPO	0.699	0.540	-.082
13	Access to credit	0.682	-.202	0.110
14	Transparency in Financial transactions	0.652	-.288	0.323
15	Grants received by the FPO	0.647	.157	0.641

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Component Matrix

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Component	Initial Eigenvalues	—	—	Extraction sums of squared loadings	—	—
	Total	% of Variance	Cumulative %	Total	% of variance	Cumulative %
1	8.060	53.733	53.733	8.060	53.733	53.733
2	1.263	8.422	62.155	1.263	8.422	62.155
3	1.051	7.004	69.159	1.051	7.004	69.159
4	.892	5.949	75.108
5	.703	4.684	79.791
6	.689	4.593	84.384
7	.515	3.436	87.820
8	.389	2.595	90.415
9	.334	2.230	92.644
10	.273	1.822	94.467
11	.234	1.557	96.024
12	.203	1.350	97.375
13	.181	1.205	98.579
14	.123	.819	99.398
15	.090	.602	100.000

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Total Variance Explained

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Kaiser-Meyer-Olkin Measure of Sampling Adequacy	—	.845
Bartlett's Test of Sphericity	Approx. Chi-Square	975.692
	DF	59
	Sig.	.000

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KMO and Bartlett’s Test

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Conclusion

From the study, it could be concluded that three components had been extracted and found to have an Eigenvalue greater than 1. The total variance explained by the study had been 69.159%. It had been concluded from the study operational /functional factors had been the highly influencing factors. Percentage of contribution from value addition of the product, branding, Potential to meet all supply with demand, No. of marketing channels followed by the FPOs, No. of members selling through FPO had been the moderately influencing factors. Turnover of the FPO, Access to credit, and Transparency in Financial transactions, and Grants received by the FPO had been the low influencing factors.

Figures and tables from the paper

S. No	Particulars	No. of respondents (n=60)	Percentage
1	Age of the FPO
	1 to 3 Years	2	3.33
	4 to 7 Years	41	68.33
	8 to 11 Years	15	25.00
	12 to 15 Years	1	1.67
	above 15 Years	1	1.67
2	Number of members in FPO
	650 - 900	12	20.00
	900 - 1100	23	38.33
	1100 - 1250	7	11.66
	1250 - 1500	16	26.66
	Above 1500	2	3.33
3	Promoting agency of the FPO
	NABARD	21	35.00
	SELF PROMOTED	8	13.33
	TNSFAC	27	45.00
	TNIAMP	3	5.00
	Central SFAC	1	1.67
4	Turnover (Rupees in lakhs)
	Less than 50	45	75
	50 – 70	6	10
	70 – 90	3	5
	90 – 130	3	5
	Above 130	3	5
5	Gender
	Male	58	96.66
	Female	2	3.33
6	Number of members in FPO
	Postgraduate	4	6.66
	Undergraduate	48	80
	Higher Secondary	6	10
	Secondary	2	3.33
	Primary	0	0
7	Experience (Years)
	1 & less than one	17	28.33
	2	21	35
	3	9	15
	4	6	10
	5 & above	7	11.66

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Socioeconomic profile

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S. No	Statement
1	Access to credit
2	Turnover of the FPO
3	Providing inputs to the farmers
4	The leadership of the CEO & Chairman
5	Regular Procurement of products from the farmers
6	Aggregation of the product by the FPO
7	Procuring products at a higher price than the farm gate price
8	Potential to meet all supply with demand
9	Use digital marketing for branding and sales
10	Grants received by the FPO
11	No.of. marketing channels followed by the FPOs
12	Transparency in Financial transactions
13	Percentage of contribution from value addition of the product (Demand analysis)
14	Providing infrastructures
15	No. of members selling through FPO

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List of Statements

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Components	Factor names	Variance explained	Factor loadings	Variables
1	Operational / Functional Factors	53.132	0.735	Procuring products at a higher price than the farm gate price
			0.724	The leadership of the CEO & Chairman
			0.721	Aggregation of the product by the FPO
			0.707	Regular Procurement of products from the farmers
			0.583	Providing infrastructures
			0.515	Providing inputs to the farmers
2	Marketing Factors	8.513	0.796	Percentage of contribution from value addition of the product
			0.725	Branding
			0.677	Potential to meet all supply with demand
			0.581	No. of. marketing channels followed by the FPOs
			0.531	No. of members selling through FPO
3	Financial Factors	7.146	0.822	Turnover of the FPO
			0.743	Access to credit
			0.696	Transparency in Financial transactions
			0.690	Grants received by the FPO

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Table 7Close ×

Components and Factor

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1. Amitha CD, Savitha B, Sudha Rani V, Laxminarayana P. Factors contributing to the performance of farmer producer organizations (FPOs)-a study in Medak district of Telangana state. International Journal of Bio-Resource and Stress Management. 2021;12(3):192-198.
2. Kumar S, Kumar R, Meena PC, Kumar A. Determinants of Performance and Constraints Faced by Farmer Producer Organizations (FPOs) in India. Indian Journal of Extension Education. 2023;59(2):1-5.
3. Kumari N, Bisht K. Identification of Core Competencies for Managing Farmer Producer Organizations Using Factor Analysis. Indian Journal of Extension Education. 2023;59(3):108-112.
4. Gagana D, Velmurugan P. Members' Intention to Participate in Farmer Producer Company Activities in the Cauvery Delta Region of Tamil Nadu. Current Agriculture Research Journal. 2023;11:1.