Search results

This study aims to formulate a conceptual sustainable framework for developing a trusted, reliable, scalable, transparent, traceable and sustainable agri-food supply chain in a developing country so that it minimizes wastage and increases the efficiency levels of agri-produce and its usage.

This study uses a rigorous review of extant literature, case studies and the interview method for theory building, using blockchain technology (BT) as a subject. Further, the study builds a framework to relate blockchain solutions to the challenges faced by the agri-supply chain. Notably, the use of BT in the agri-food supply chain is a relatively new area of study.

Limitations of using BT 3.0 in a diverse supply chain like the food sector, especially in a developing country such as India, may be overcome by adopting BT 4.0 and could change the country’s face by controlling inefficiencies and ensuring transparency, helping in good governance, improving the humanitarian supply chain and integrating the bottom of the pyramid to the main economy. Based on the findings, this study proposes BT 4.0 for the agri-supply chain in India to deal with the current issues of demand-supply gap, wastages of agri-produce, unequal distribution of profit among agriproduct producers and logistics suppliers and ensuring sustainability.

Results in this study have been derived from a specific demographic condition in India. Future research with other demographic conditions may be replicated. BT is a new technology product, and its effectiveness is yet to be established.

The outcome of this study provides the application of BT 4.0 in the area of the agri-food supply chain. The BT 4.0 framework has been developed on studying a few cases that either implemented BT or were in the testing phase. The benefits of the agri-food supply chain vis-à-vis its overall social well-being may be achieved on the successful implementation of the framework, despite existing complexities in the food supply chain. Further research on this subject may help the other dimensions of the complexity of adopting BT 4.0. Both practitioners and policymakers from developing countries can, therefore, use the findings of this study to analyze BT 4.0 and address the concerns of the agri-food supply chain.

This research paper has proposed a conceptual framework of BT 4.0, which is a completely new technology. It is fairly transparent, and therefore sustainable supply chain practices may be achieved easily.

Due to unceasing declination in environment, sustainable agro-food supply chains have become a topic of concern to business, government organizations and customers. The purpose of this study is to examine a problem associated with sustainable network design in context of Indian agro-food grain supply chain.

A mixed integer nonlinear programming (MINLP) model is suggested to apprehend the major complications related with two-echelon food grain supply chain along with sustainability aspects (carbon emissions). Genetic algorithm (GA) and quantum-based genetic algorithm (Q-GA), two meta-heuristic algorithms and LINGO 18 (traditional approach) are employed to establish the vehicle allocation and selection of orders set.

The model minimizes the total transportation cost and carbon emission tax in gathering food grains from farmers to the hubs and later to the selected demand points (warehouses). The simulated data are adopted to test and validate the suggested model. The computational experiments concede that the performance of LINGO is superior than meta-heuristic algorithms (GA and Q-GA) in terms of solution obtained, but there is trade-off with respect to computational time.

In literature, inadequate study has been perceived on defining environmental sustainable issues connected with agro-food supply chain from farmer to final distribution centers. A MINLP model has been formulated as practical scenario for central part of India that captures all the major complexities to make the system more efficient. This study is regulated to agro-food Indian industries.

The suggested network design problem is an innovative approach to design distribution systems from farmers to the hubs and later to the selected warehouses. This study considerably assists the organizations to design their distribution network more efficiently.

The aim of this paper is to develop a model for the prioritization of collusive behaviours within Indian food grain supply chain (FGSC) to enable government authorities, entrusted with the task of public distribution, to address those frauds based on their priority for making an existing supply chain more sustainable.

An interval 2-tuple linguistic Technique for Order Preference by Similarity to Ideal Solution (ITL-TOPSIS) method has been used to deal with the problem of prioritization of frauds under incomplete and uncertain information. Unlike traditional methods, this methodology offers an ability to make informed decisions, without loss of information, while factoring in various ambiguities.

The outcome indicates that the most severe fraud is adulteration, which adversely impacts the health of a person. Bogus Ration Card comes next, as it results into the distribution of grains to non-poor, ineligible population rather than the deserving beneficiaries. Next is diversion, where diverted food grains end up being sold at much higher rates than specified subsidized rates. Theft is least severe, as this would not affect FGSC much until done on large scale.

More decision-makers can be consulted to entertain more uncertainty and ambiguity. Also, a comparative study can be performed using different methodologies.

The proposed modelling could empower various governmental and non-governmental regulatory bodies in formulation of food policies to effectively tackle the problem of inappropriate delivery of food to the unintended population and to take necessary informed decisions for ensuring food security and safety to the society at large.

There is a dearth of studies related to the prioritization of frauds within FGSC. This research bridges the gap in literature by providing a decision-making framework for prioritizing collusive behaviour under ambiguous and uncertain information.

The main purpose of this paper is to conduct a review of the literature published on food supply chain management (FSCM) in last one and half decade to find out the ongoing research in the field, identify gaps and develop relevant research questions (RQs) from the perspectives of academicians, researchers, policymakers and corporate for the future research.

In all 281 research articles published on FSCM between the years 2005 and 2020 used for searching online databases such as Emerald, Science Direct (Elsevier), Springer and Wiley online. The methodology of structured review and classification involves various dimensions such as journal, publishing house, country, research design and methods, data analysis tool and multi-criteria decision-making methods.

It is found that the research in the field of FSCM has gained momentum in the last one and half decades. Majority of published articles are related to food supply chain management and food cold chain. Fewer authors have addressed issues and challenges related to food chain in developing country like India and still fewer studies are found on comparison of present food chain management practices adopted by developing countries like India vis-à-vis developed countries. Also it is observed that limited research is reported in food chain logistics system and intelligent tracking system.

This paper is limited to reviewing only those articles which are related to food chain management.

The main objective of this comprehensive review of literature is to present the various perspectives of food chain management and its numerous challenges. This paper attempts to draw the attention of researchers for further research in the FSCM disciplines. The findings provide future research directions, need of sound policymaking and regulatory mechanism to ensure food security to world's second largest populous country.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

This article sheds light on the missing links concerning the study of using integrated enabling technologies toward sustainable and circular agriculture supply chains by examining the available literature and proposing future research possibilities.

The relevant literature was researched through online databases such as Scopus, Web of Science, Academic Search Premier, Emerald, IEEE Xplore, Science Direct, World Scientific Net and Springer-Link Journals, covering a period from 1999 to 2020. A systematic literature review based on 75 papers analyzed the integration of the concepts of enabling technologies, sustainability, circular economy and supply chain performance in agriculture supply chains.

It was identified that enabling technologies and agriculture supply chains alone have been explored further than integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains. Enabling technologies and agriculture supply chains' main findings are: enabling technologies have been studied to improve food safety, food quality and traceability in agriculture supply chains. The main results regarding integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains are: Internet of Things and information communication technology play an important role in addressing food security, traceability and food quality, which help achieve sustainable development goals.

This review study provides 13 research questions to underpin future trends regarding integrated technologies' application in agriculture supply chains for circular and sustainable growth.

Many commodity supply chains suffer from an unfair value distribution across the supply chain like “Coffee Paradox.” This study explores the coffee supply chain to determine how the country of origin–geographical indicator can be used as a method of fair distribution of value and provenance across the supply chain effectuated by the blockchain technology. By looking at an exemplar case study for India, this study provides insights into diverse research streams and practice.

Based on the case method, analyzing the implementation of blockchain in the coffee industry by a leading Indian software implementation of the logic, dynamics and forces for a provenance model has been devised. It further adopts a stakeholder cum institutional theory framework to understand the logical implementation of a blockchain project embedded in a territorial logic for a commodity supply chain.

This study specifically looks at coffee which is representative of a commodity supply chain. It also explores how the malaise of unfair value distribution gets addressed by bringing farmers and the consumers on a common platform facilitated by blockchain technology. This study contributes to the literature on blockchain, territory, commodity and supply chain. Using stakeholder cum institutional theory, this study helps to explore how the implementation is successful by different actors in the supply chain through collaboration.

This study provides a new stream of multi-disciplinary study at the interface of supply chain, technology, international trade and geography.

Blockchains are embedded in the supply chain, and supply chains are embedded in territories. This linkage is paramount and the ability to make these blockchain projects successful requires the deep study of the interaction of territory, technology and actors from the provenance angle. De-commodification of coffee can be actualized through blockchain.

The coffee paradox and skewed value distribution is also a social problem wherein the farmers do not get the right price of their produce and are exploited. This case also highlights how this social malaise can be addressed and rightful and equitable distribution of value happens across the value chain.

This linkage between territory, blockchain, commodity supply chain and institutions has not been discussed in the literature. Adopting the territorial design approach, this study is an attempt to stimulate inter-disciplinary conversations and thereby create a provenance framework for commodity and research questions for scholars from different disciplines and divergent disciplinary perspectives.

The purpose of this paper is to investigate and evaluate the new performance measurement model for the Thai frozen shrimp chain.

The performance measurement model was developed by the combination method between a structural equation modeling and an analytical hierarchy process, which the method confirmed and proved the construction of the framework and identified the important key performance indicators of the chain from different supply chain members’ point of views.

The results showed that the model is reliable and valid as well as being theoretically acceptable on the basis of performance measurement foundations. Furthermore, the financial and the customer perspectives are demonstrated as the first to be prioritized in order to evaluate the performance.

Two limitations should be considered. First, small sample size of this study is a limitation. Hence, further study should consider on enough sample size. A next limitation, different points of view from participants has effect on factor loading which represented minus value on the research model. Therefore, the future research should apply several techniques, such as the fuzzy set and data envelopment analysis.

The contribution of this study is the new performance measurement model which based on the integrated conceptual ideas and the synthesizing methods for evaluating the Thai frozen shrimp chain.

Food insecurity is a major concern for developing economies. Operational inadequacies get introduced with unorganized interactions among stakeholders in the food supply chain, affecting social, economic, environmental and operational (SEEO) aspects of a nation. This study analyzes India's largest food safety net program, Public Distribution System (PDS) and develops a perception-based model, mapping the root causes (of food insecurity) with possible solutions. The novelty lies in leveraging blockchain in the implementation of food traceability system.

Soft system methodology (SSM) is used to identify and analyze problems in PDS, leveraging the learning and inquiry process. It relies on system thinking and action research to create a defendable and rational model, which helps in proposing recommendations for addressing the problem.

Blockchain-enabled food traceability system increases transparency, thus enabling the fulfillment of basic food necessities for beneficiaries.

The proposed model enables policymakers to build a profound understanding of existing operational issues and provides insightful recommendations for making informed decisions to deal with the grave issue of food insecurity.

Unlike previous studies, this research attempts to understand operational inefficiencies during interactions among stakeholders. It proposes a perception-based conceptual model for the final implementation at the ground level. It also reveals significance of three systems: a delivery system, an enabling system empowering delivery system and a criteria system to control and monitor processes. This study thus bridges an important gap in the literature by proposing a blockchain-driven traceability system, under the control of criteria system, through the integration of system-thinking and action-research approach.

The purpose of this paper is to explore and identify the indicators of institutional barriers hindering the technology transfer training (TTT) process behind the technology adoption lag affecting the agricultural output in India through development of a scale.

Quantitative technique has been followed for data collection through a close-ended questionnaire scored on the seven-point Likert scale. The sample size was considered as 161; target respondents were farmers and farmer-centric individuals. Data were analyzed using an exploratory factor analysis technique.

Factor analysis revealed that there are three significant factors related to TTT process, namely, comprehension, customization and generalization, which are liable for institutional barriers in technology adoption by farmers.

The main limitation is biasness from both respondents’ end and interviewer’s end might exist during survey due to differences in perception.

The key beneficiaries from this research are the small and marginal farming community in India. They can enhance their productivity through an appropriate training process. Corporates will show interest in investment through the mechanism of corporate social responsibility.

Under this study, the factors of the institutional barriers from the farmers’ perspective are being introduced as a new research contribution, especially for the resource crunch area of Jangalmahal and other similar places in India.