Browsing by Author "Gopika Somanath"

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    Effectiveness of e-marketing of cardamom in Kerala-an exploratory analysis
    (Department of Agricultural Extension, College of Agriculture,Vellayani, 2022) Jeena Paul; Gopika Somanath
    The study entitled 'Effectiveness of e-marketing of cardamom in Kerala— an exploratory analysis' was conducted in Idukki district of Kerala during the year 2019-21 among the cardamom farmers undertaking conventional marketing as well as e-marketing of cardamom. The objective of the research was comparative assessment of the effectivencss of e-marketing and conventional marketing of cardamom as well as delineation of farmers' perception on benefits and constraints of e-marketing. Six farmers undertaking conventional marketing and six farmers undertaking e-marketing of cardamom each were randomly selected from ten panchayats, totaling the sample size to 120. The independent variables in the study selected through judges rating were age, education, area under cardamom cultivation, experience in cardamom cultivation, production of cardamom, price received, extension contact, attitude towards e-marketing, awareness on digital tools and adoption of digital tools, and dependent variable marketing effectiveness was measured using the index developed for the study. On analysis it was found that majority of the farmers undertaking conventional marketing (51.7%) and e-marketing (40%) belonged to middle age category. Majority (43.3%) of the farmers undertaking conventional marketing had high school level education and 58.4 per cent of the farmers undertaking e-marketing had degree and above level of education. Majority of the farmers undertaking conventional marketing were marginal farmers (31.7%) and farmers undertaking e-marketing had medium area (4-10 ha) under cardamom cultivation (35%). Majority of the fanners undertaking conventional marketing (55%) and e-marketing (45%) had medium level of experience (6-20 years) in cardamom cultivation. Majority of the farmers undertaking conventional marketing (43.3%) had low production of cardamom and fanners undertaking e-marketing (4803%) had medium production of cardamom. Majority of the farmers undertaking conventional marketing (73.3%) and e-marketing (36.7%) received a price between per kilogram of.cardamom. More than half of the farmers undertaking conventional (5166%) and e-marketing (51.6%) had medium level of extension contact. More than half of the fanners undertaking conventional marketing (55%) had negative attitude towards emarketing and more than half of the farmers undertaking e-marketing (61.7%) had neutral attitude towards e-marketing. More than half of the farmers undertaking conventional (66.7%) and e-marketing (75%) had medium awareness on digital tools. Majority of the farmers undertaking conventional marketing (45%) and e-marketing (56.7%) had medium level of adoption of digital tools. Marketing effectiveness has been measured under seven components, four quantitative variables, viz., marketing channel, marketing cost, price spread and producer's share in consumer's rupee and three qualitative variables, viz., market information utilization, timeliness of marketing and ease of marketing. Based on factor analysis, the components were grouped into two factors contributing to a cumulative variance of 91.68 per cent. The factor loadings ofvariables showed that producer's share in consumer's rupee (96.4%) and price spread (94.2%) explained more than 90 per cent variance. Majority of the fanners undertaking conventional marketing had medium (46.7%) followed by low (41.7%) marketing effectiveness and fanners undertaking e-marketing had medium (53.4%) followed by high (38.4%) marketing effectiveness. The comparison between the marketing effectiveness of conventional marketing and e-marketing using z-test showed that there exists significant mean difference between the six components of marketing effectiveness for the two categories of respondents and their marketing effectiveness index scores. The results ofKarl Pearson correlation analysis revealed that out of 10 independent variables selected for the study, six variables were significantly related to the dependent variable marketing effectiveness. The variables, viz., price received, extension contact, attitude towards e-marketing and adoption of digital tools were significant at 0.1 % level of significance and education and awareness on digital tools were significant at 1 % level of significance. Majority of the farmers undertaking conventional marketing adopted marketing channel with five (41.7%) and six parties (41.7%) and farmers undertaking e-marketing adopted marketing channel with five parties (63.4%). Farmers undertaking e-marketing recei ved higher price g 1265.75) for their produce as compared to the fanners undertaking conventional marketing (?1083.75). Majority (71.7%) of the farmers undertaking emarketing store their produce and sells only at remunerative prices, whereas only 28.3 per cent of the fanners undertaking conventional marketing store their produce and wait for better price. Marketing effectiveness index scores of fanners undertaking e-marketing (67.6) was found to be higher than that ofthe fanners undertaking conventional marketing (53.9). Among the e-marketing platforms, social media (89.4) and websites (72.4) showed higher marketing effectiveness index score than e-auction (61). The major benefits of e-marketing as perceived by farmers were availability of proper transaction details and bills (83.3%) and assurance of timely delivery and prompt payment (80%). The major constraints of e-marketing as perceived by farmers were delay in payment up to 20-30 days after e-auction (66.7%) and disfress procurement of credit by the farmers from the auctioning agency to compensate for the delayed payment (60%). Mechanisms to ensure timely and prompt payment for the produce, separate eauctions for farmers and traders, ensuring remunerative base prices for cardamom, regulation and monitoring ofthe e-auction system by the Spices Board to reduce unhealthy practices, approval of registration of the cardamom lands by the Government, minimization of the formalities in credit disbursal by the banks, extending support to the fanner producer organizations (FPOs) to undertake value addition in cardamom and expansion of extension services in the realm of e-marketing are the key strategies to overcome the constraints in e-marketing. It could be concluded that the e-auction mechanism was introduced by the Spices Board for the benefit of both the farmers and traders by promoting healthy competition among bidders and monitoring the auction price elecfronically. But presently fanners are not completely satisfied with the system due to lack of remunerative prices and delayed payment. The scope of the other e-marketing platforms such as social media and websites need to be more popularized among the cardamom farmers.
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    Entrepreneurial effectiveness of agripreneurs in Kerala
    (Department of Agricultural Extension, College of Agriculture, Vellayani, 2009) Gopika Somanath; Seema, B
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    Supply chain management in mango: A critical analysis
    (Department of Agricultural Extension, College of Agriculture ,Vellayani, 2023) Prathiksha, I.; Gopika Somanath
    The study entitled ‘Supply Chain Management in Mango: A Critical Analysis’ was conducted in Palakkad district of Kerala and Krishnagiri district of Tamil Nadu during the year 2021-2022 among the actors identified in the supply chain. The objectives of the research were identification of the existing supply chains and the supply chain management activities related to mango in Kerala and Tamil Nadu; comparative assessment of the performance effectiveness of supply chains in the selected districts and formulation of extension strategies based on the constraints identified, to strengthen the performance of the supply chains. Five respondents of each mango supply chain actor namely input suppliers, farmers, wholesalers, processors, retailers, logistic partners and consumers and officials who work on the mango supply chain from each of the four panchayats were randomly selected, totalling the sample size 160. The independent variables in the study selected through judges rating were age, education, annual income, market perception, perception about supply chain, information seeking behaviour, alertness, problem solving skill and risk orientation and dependent variable performance effectiveness of the mango supply chain was measured using the scale developed for the study. On performing Mann-Whitney U test on independent variables among all the actors it was found that there exists a significant difference between age of the farmers in Kerala (52.4) and Tamil Nadu (63.5), education status of the farmers in Kerala (5.4) and Tamil Nadu (2.9), annual income of the wholesalers in Kerala (685000) and Tamil Nadu (285000), market perception of the wholesalers in Kerala (6.1) and Tamil Nadu (7.2) and the retailers in Kerala (5.4) and Tamil Nadu (7.5), perception about supply chain of the wholesalers in Kerala (14.0) and Tamil Nadu (14.8), alertness of the retailers in Kerala (13.2) and Tamil Nadu (12.5), problem-solving skill of the wholesalers in Kerala (8.1) and Tamil Nadu (8.9), retailers in Kerala (8.7) and Tamil Nadu (8.0) and logistics partners in Kerala (8.1) and Tamil Nadu (7.4) and risk orientation of the farmers in Kerala (17.5) and Tamil Nadu (19.1) with the P-value less than 0.05 at 0.05% level of significance, whereas other actors are relatively significant with the P-value 123 greater than 0.05 at 0.05% level of significance for all the independent variables. From the analysis of Mann-Whitney U test on the performance effectiveness of the mango supply chains in Kerala and Tamil Nadu it was found that there exist no significant differences in the performance effectiveness scores of the respondents in Kerala and Tamil Nadu with a P-value of 0.571 which is not significant at 0.05% level of significance. It was also observed that the P-values for the input suppliers (1) and processors (1) were equal, which may be attributed to the fact that the input suppliers and processors operating across the border in Tamil Nadu is depended upon by the mango supply chains operating in both the states. It was pertinent to observe that there were no input suppliers and processors for mango in Kollengode block in Kerala. On performing Principal Component Analysis for the influence of the subdimensions on the performance effectiveness scores of the supply chains it was found that the first principal component accounts to the largest percentage variance (73.25%) in the performance effectiveness scores of the respondents in Kerala and the first three principal components accounts for a cumulative variance of more than 97 percent. It was also revealed that it is the product quality ensured by the supply chains and the efficiency of the supply chains which largely influence the performance effectiveness of the mango supply chains in Kerala whereas in Tamil Nadu it was found that the first principal component accounts to the largest percentage variance (70.55%) in the performance effectiveness scores of the respondents and the first three principal components accounts for a cumulative variance of more than 97 percent. It was also revealed that it is the efficiency of the performance of the supply chains and the responsiveness of the supply chains which largely influence the performance effectiveness of the mango supply chains in Tamil Nadu. Comparative analysis of the PCA-biplots revealed that majority of the mango supply chains in Kerala (60%) were having higher flexibility, efficiency, product quality and responsiveness compared to 40% of mango supply chains in Tamil Nadu giving similar results. From the analysis of multiple regression for the influence of actors on the performance effectiveness of the mango supply chains in Kerala and Tamil Nadu it was found that the performance effectiveness scores of the seven actors viz., 124 input suppliers (0.026), farmers (0.000), wholesalers (0.044), processors (0.012), retailers (0.050), logistics partners (0.003) and consumers (0.003) were significant in influencing the performance effectiveness of the mango supply chains. It was further observed that the performance effectiveness of the farmers was found to be highly significant in influencing the performance effectiveness scores of the mango supply chains. Since the respondents of input suppliers and processors from Kerala and Tamil Nadu are same, major constraints faced by the supply chain actors in Kerala and Tamil Nadu were unavailability of good quality saplings, delay in payments, post-harvest management losses, lack of awareness about production, lack of financial support from Government, competitive pricing of the products, inadequate storage facilities, lack of communication among the actors upstream and downstream the chain and miscommunication of feedback to upstream actors in the supply chain. Suggestions to strengthen the performance effectiveness of the mango supply chains in Kerala and Tamil Nadu are assisting the farmers in choosing reliable suppliers for availing good quality inputs during peak seasons and providing useful training programme for better production. Assisting the farmers with subsidies to provide purchasers with quick payment options. Imparting knowledge to farmers and wholesalers on proper grading, standardizing, processing and careful handling of the products which can help in reducing postharvest and handling losses. The real-time data sharing of information across the actors in the supply chain can be improved with the help of social media, newspapers, APMC markets, market information sharing platforms, etc., Improvements can be brought in scientific transportation facilities like cold storage vans and providing infrastructure facilities for setting up of warehouse, processing units, cold storage units in rural areas. Pricing of products should be set after considering the market conditions that actually exist and limit pricing competitions among the retailers. Improving the large scale organised direct retailing by farmers in Agriculture Produce Market Committee markets. Increasing the supply chain visibility by ensuring technology assisted traceability of the supply chains for better communication across the actors. 125 The major extension strategies suggested are providing training on the use of mobile applications and software of the improved agricultural technologies for input suppliers. Sensitising the farmers on direct marketing of their produce through APMC markets which reduces the intervention of middlemen thereby increasing the profit. Conducting workshops to familiarize the wholesalers with the real-time data sharing tools to ensure better co-ordination in the supply chain. Awareness on the importance of cold storage facilities, capacity building programmes for the managers of the processing units and demonstrations on the improved technologies in value addition in mango. Empowering the retailers on the use of ICT based applications and platforms for improved communication within the supply chain. Capacity building programmes to facilitate computerised documentation for the logistics partners. Awareness regarding consumer rights, quality produce, pricing of products. Sensitization on their role in providing feedback on the supply of the produce by the consumers and creating awareness on traceability of the products.
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    Transforming innovations into enterprises through agri- business incubators: a process analysis
    (Department of Agricultural Extension Education, College of Agriculture,Vellayani., 2024-01-20) Sarathi, R.; Gopika Somanath
    The present study titled “Transforming innovations into enterprises through agri business incubators – A process analysis” was conducted in two states – Kerala and Tamil Nadu. The selected agri-business incubators in these two states are attached to the State Agricultural Universities and Research Institutes under ICAR. Two Agribusiness incubators each from Kerala and Tamil Nadu has been selected purposively for this study. From Kerala, Agri-Business Incubator (ABI) of Kerala Agricultural University (KAU) at Thrissur and Technology Incubation Centre (TIC) of Central Tuber Crop Research Institute (CTCRI) at Thiruvananthapuram under ICAR has been selected. From Tamil Nadu, the Madurai Agri Business Incubation Forum (MABIF) of National Bank for Agriculture and Rural Development (NABARD) at Madurai under TNAU and Agribusiness Incubator (ABI) of ICAR Sugarcane Breeding Institute (SBI) at Coimbatore under ICAR has been selected for the study. Thus a total of four ABIs one each under the SAU and ICAR has been selected for the study from each state. The objectives of the research were comparison of the nature and extent of innovation based agri-business incubation undertaken by the Agri-business Incubators (ABIs) in Kerala and Tamil Nadu; analysis of the entrepreneurial effectiveness of ABI incubatee and non- incubatee agripreneurs; delineation of the factors contributing to the capacity building of the ABI incubatee agripreneurs and formulation of extension strategies based on the constraints identified, to improve the performance of ABIs. From each of the selected incubators, fifteen ABI incubatee entrepreneurs and five officials was selected. Fifteen non-incubatee agripreneurs each were selected randomly from the respective districts where the incubators were located. Thus, a total of 120 agripreneurs and 20 officials adding up to a total of 140 respondents from the two states constituted the sample for the study. The independent variables in the study selected through judges rating were age, education, agripreneurial income, reason for starting the enterprise, type of ownership, source of capital, market information seeking behaviour, opportunism, pro-activeness, networking, marketing strategies and innovativeness. The dependent variable entrepreneurial effectiveness of the agripreneurs was measured using the scale developed by Somanath (2009), with suitable modifications. The number of enterprises established after incubation and their survival rate was collected from the ABIs and it was found that in Kerala, the agro-enterprises has a survival percentage of 94.12, whereas in Tamil Nadu, the agro-enterprises has a survival percentage of 90.52. The nature of innovations undertaken by the agripreneurs were classified under the broad areas as production, processing/value addition, packaging, marketing and distribution, agricultural consultancy, agricultural services and combination of any. Majority of the 256 incubatees in Kerala (80.60) and Tamil Nadu (41.25) were found to undertake innovative agri business enterprises related to processing/value addition. From the analysis of of the entrepreneurial effectiveness of agripreneurs in Kerala and Tamil Nadu using Z-test, it was found that there exists no significant difference in the entrepreneurial effectiveness scores of incubatees and non-incubatees of Kerala but there exists significant difference between the entrepreneurial effectiveness scores of incubatees and non incubatees of Tamil Nadu (0.05% level of significance). It was observed that in state-wise and category-wise comparison, there is no significant difference in the entrepreneurial effectiveness scores of the agripreneurs of Kerala and Tamil Nadu. From the analysis of Pearson’s coefficient of correlation ‘r’ for the relationship between the socio-personal variables and entrepreneurial effectiveness of the agripreneurs, it was found that among the incubatees of Kerala, age and agripreneurial income had no significant correlation with the entrepreneurial effectiveness whereas education of the agripreneurs had highly significant correlation with the entrepreneurial effectiveness at 0.001% level of significance. It was further observed that among the non-incubatees of Kerala, age exhibited no correlation with the entrepreneurial effectiveness whereas education and agripreneurial income were significantly correlated with the entrepreneurial effectiveness at 0.05% level of significance. In case of incubatees of Tamil Nadu, age showed no correlation with the entrepreneurial effectiveness whereas education and agripreneurial income had a significant bearing on the entrepreneurial effectiveness, at 0.01% level of significance. It was found that for the non-incubatees of Tamil Nadu, age and agripreneurial income had significant correlation with the entrepreneurial effectiveness at 0.01% and the relationship with education was significant at 0.05% level of significance. On performing the Chi-square test for the relationship between the qualitative socio personal variables and entrepreneurial effectiveness of the agripreneurs, it was found that among the incubatees of Kerala, all the variables i.e., reason for starting the enterprise, type of ownership and source of capital did not show correlation with the entrepreneurial effectiveness with p-values 0.690, 0.586, 0.801 respectively. It was further observed that for the non incubatees of Kerala also, all the variables i.e., reason for starting the enterprise, type of ownership and source of capital were not significantly correlated with the entrepreneurial effectiveness with p-values 0.896, 0.564, 0.862 respectively. It was found that among the incubatees of Tamil Nadu, reason for starting the enterprise was significantly correlated with entrepreneurial effectiveness at 0.05% level of significance with p-value 0.433, whereas type of ownership and source of capital were not correlated with the entrepreneurial effectiveness with p-values 0.762 and 0.839 respectively. In case of non-incubatees of Tamil Nadu, reason for starting the enterprise and source of capital were significant at 0.05% level of significance 257 with p-values 0.308 and 0.455 respectively and type of ownership was not significantly correlated with entrepreneurial effectiveness with p-value 0.621. From the analysis of Pearson’s coefficient of correlation ‘r’ for the relationship between the entrepreneurial variables and entrepreneurial effectiveness of the agripreneurs, it was found that among the incubatees of Kerala, all the six variables were significant at 0.001% level of significance. While for the non-incubatees of Kerala, networking and market information seeking behaviour were significant at 0.01% level of significance and the other four variables were significant at 0.001% level of significance. It was observed that for the incubatees of Tamil Nadu, networking and innovativeness were significant at 0.01% level of significance and the other four variables were significant at 0.001% level of significance. In case of non incubatees of Tamil Nadu, only networking was significant at 0.01% level of significance and the other five variables were significant at 0.001% level of significance. On performing the Principal Component Analysis for the influence of the sub dimensions on the entrepreneurial effectiveness scores of the agripreneurs, it was found that the first principal component accounts to the largest percentage variance (69.98%) in the entrepreneurial effectiveness scores of the agripreneurs in Kerala and the first five principal components accounts for a cumulative variance of 97 per cent. It was also revealed that it is the risk management effectiveness and production management effectiveness were largely influencing the entrepreneurial effectiveness of the agripreneurs in Kerala. Whereas in Tamil Nadu, it was found that the first principal component accounts to the largest percentage variance (69.63%) and the first five principal components accounts for a cumulative variance of more than 97 per cent. It was also revealed that it is the risk management effectiveness and time management effectiveness were largely influencing the entrepreneurial effectiveness of the agripreneurs in Tamil Nadu.Comparative analysis of the PCA-biplots revealed that majority of the agripreneurs in Kerala (50%) were having a little higher effectiveness compared to 49% of agripreneurs in Tamil Nadu giving similar results. The results revealed that 71.67 per cent of incubatees belong to middle age category, 86.67 per cent of non-incubatees possessed graduate level of education, 55 per cent of incubatees received income between Rs.100001 to Rs. 500000, 33.33 percent of non incubatees had securing self-employment as their reason for starting the enterprise, 60 per cent of non-incubatees possessed individual proprietorship type of ownership, 98.33 per cent pf incubatees possessed personal capital as their source of capital, 61.67 per cent of non incubatees exhibited medium level of market information seeking behaviour, 63.33 per cent of incubatees possessed medium level of opportunism, 60 per cent of non-incubatees exhibited medium level of pro-activeness, 68.33 per cent of incubatees possessed medium level of networking, 73.33 per cent of incubatees having medium level of marketing strategies and 73.33 per cent of incubatees possessed medium level of innovativeness. 258 Results of the t-test for the process analysis indicated that product development, capacity building and market linkage were found to be significant with p-values 0.003. 0.015, 0.0004 respectively, whereas networking, mentoring, technology utilization, finance facilitation and follow-up were found to be non-significant with p-values 0.159, 0.477, 0.552, 0.459, 0.334 respectively. The Strengths, Weaknesses, Opportunities and Challenges (SWOC) of KAU-ABI include product development and refinement, less publicity among public about incubation facilities, food analysis and quality control laboratory inside the incubator and shortage of separate fund for Research and Development (R&D). While the SWOC of TIC-CTCRI include tuber crops are more focused for increasing the value, enrolment of incubatees is less, scope for tuber crops exploitation and product diversification and lack of infrastructure. The SWOC of NABARD-MABIF include various schemes including Intellectual Property Facilitation Centre (IPFC), Cluster Based Business Organizations (CBBOs), Catalytic Capital Fund (CCF), huge cost of modern technologies, in-house production centre, breakdown cost is more. The SWOC of SBI-ABI include sugarcane based novel and commercialized products, non availability of dedicated labs and facilities, incubation and technology promotion, low manpower. The major suggestions for improving the performance of ABIs in Kerala include increasing incubation office facility with increased manpower and provision for seed funds to the incubatees. While the suggestions for ABIs in Tamil Nadu include providing national and international networking and collaboration for increasing export opportunities and conducting meet-ups between sector-specific incubator and incubatee meet-ups through 'networks of incubators' for sharing resources best practices and for generating new ideas. The major entrepreneurial constraint perceived by the incubatees of Kerala and Tamil Nadu was lack of skilled labour availability (90%) and raw material price hike (90%) respectively. Whereas for the non-incubatees of Kerala and Tamil Nadu, the major constraint was raw material availability (86.67%) and uneven price hike of raw material (80%) respectively. The major suggestion for improving the effectiveness of agripreneurs of Kerala include the establishment of facilities such as the labour banks at the Panchayat level which would serve to ensure the timely availability of labour for the various agricultural activities. In case of the agripreneurs of Tamil Nadu, the Government support is called for to regularize the cost of inputs and ensure the quality of inputs supplied by the dealers. The general suggestions for the agripreneurs in both the states include diversification in their agri-business activities to buffer the losses they may incur in case of the seasonal fluctuations in the demand for the regular produce which in turn results in the fluctuation in their market prices