Production and retailing of self help group products

Thyagarajan, Siddhartha; Nambirajan, T.; Ganeshkumar, C.

doi:10.1504/gber.2019.102590

Cited by 13 publications

(4 citation statements)

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“…(1995) explored machine-learning strategies to solve agricultural issues using three steps, namely data extraction, gaining insight from the problem domain and generating rules using machine-learning tools. They found that Waikato Environment for Knowledge Analysis (WEKA) helped transfer machine-learning techniques from laboratories to professionals in different disciplines (Siddhartha et al. , 2019).…”

Section: Literature Review On Agricultural Value Chain Actorsmentioning

confidence: 99%

“…McQueen et al (1995) explored machine-learning strategies to solve agricultural issues using three steps, namely data extraction, gaining insight from the problem domain and generating rules using machine-learning tools. They found that Waikato Environment for Knowledge Analysis (WEKA) helped transfer machinelearning techniques from laboratories to professionals in different disciplines (Siddhartha et al, 2019). Panigrahi and Ting (2012) classified and summarized different topics of AI in biology and agriculture by critically reviewing 13 research articles, and they suggested AI for solving different problems in biological and agricultural disciplines issues.…”

Section: Literature Review On Agricultural Value Chain Actorsmentioning

confidence: 99%

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Artificial intelligence in agricultural value chain: review and future directions

Ganeshkumar

Jena

Sivakumar

et al. 2021

JADEE

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PurposeThis paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.Design/methodology/approachThe authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.FindingsFifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.Research limitations/implicationsThe authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.Originality/valueEarlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

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Section: Literature Review On Agricultural Value Chain Actorsmentioning

confidence: 99%

Section: Literature Review On Agricultural Value Chain Actorsmentioning

confidence: 99%

Artificial intelligence in agricultural value chain: review and future directions

Ganeshkumar

Jena

Sivakumar

et al. 2021

JADEE

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“…The author notes that the relationship between urban nutrition and agriculture should be studied even further. Finally, the author notes that feeding the family is an important responsibility of the women and how they are doing it should be the subject of further research (Siddhartha et al, 2019).…”

Section: Self-help Groups Financingmentioning

confidence: 99%

Self-help group (SHG) production methods: insights from the union territory of Puducherry community

Thyagarajan

Nambirajan

Ganeshkumar

2021

JEC

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Purpose The purpose of this paper is to study the production methods and potential of self-help groups (SHGs) for linking to micro, small and medium enterprises (MSME) in the Union Territory of Puducherry region. Design/methodology/approach The variables for the research work were identified through a literature review relating to SHGs production methods and 251 primary data were collected through the random sample using the survey method. The statistical software of IBM-SPSS was used to analyze the data using the statistical methods of descriptive statistics like frequency analysis simple mean and inferential statistics such as chi-square, correspondence analysis, correlation and ANOVA test. Findings The majority of SHGs consisting of 49.8% are willing to pay an amount up to Rs. 5,000 if training is provided through MSME organizations, a higher number of SHGs have indicated that they are very much interested in ancillary production activities, 35.5% of SHGs are using no machines and ANOVA test result shows that there is a significant difference between numbers of years of functioning with respect to production activity. Research limitations/implications The authors have selected the Union Territory of Puducherry was taken as the sample region of the study due to its high rural poverty levels of 16.9%. Practical implications The research study endeavors to study the various production methods and preferences of SHGs and it will be of immense utility to the government, banks, microfinance organizations and other policymakers. Originality/value Existing literature reviews are conducted on various problems in service and manufacturing sectors, it is essential to conduct empirical research on an inclusive sector like SHG production activities and preferences in emerging economies like India.

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“…This paper answers the questions of the feasibility of BCT at the present trend, and its adaptation in the field of food supply chain management (Moe, 1998;Ochoa et al, 2001). Considering these attributes of BCT, in terms of integrity, trustworthiness, authenticity, cost reduction, favouring transactions, digital ledgers are the aim of this research (Siddhartha et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Blockchain Technology in the Food Supply Chain

David

Kumar

Paul

2021

International Journal of Information Systems and Supply Chain Management

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This paper explains about the feasibility of Blockchain Technology in food organization. The technology of BCT helps the organizations to achieve integrity among peer-to-peer nodes, such as maintaining proof of work, reducing intermediaries, traceability, etc. It can be applied in the BCT at different levels of Supply Chain Management processes. This empirical study was conducted with the help of the primary data. The data was collected from food industry managers who have knowledge about the BCT in the process of supply chain management. The questionnaire was prepared based on the different supply chain activities like procurement, pre-processing, logistics, warehousing, inventory management, distribution, retailing, processing, and marketing activities. Based on the literature and data analysis, the BCT had the greatest advantages are cost reduction, traceability, time-saving, immutability, authentication and proof of work. The major weaknesses that are associated with present employees having a lack of knowledge, limited scalability, complexity in usage, and high initial cost.

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Production and retailing of self help group products

Cited by 13 publications

References 0 publications

Artificial intelligence in agricultural value chain: review and future directions

Artificial intelligence in agricultural value chain: review and future directions

Self-help group (SHG) production methods: insights from the union territory of Puducherry community

Blockchain Technology in the Food Supply Chain

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