A mathematical model formulation to design a traditional Indian agri-fresh food supply chain: a case study problem

Patidar, Rakesh; Agrawal, Sunil

doi:10.1108/bij-01-2020-0013

Cited by 27 publications

(17 citation statements)

References 36 publications

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“…Through the adoption of real-time data collection and sharing, Radio Frequency Identification (RFID) scans, Time and Temperature Indicators (TTI), and Internet of Things (IoT) sensors, better flow management decisions can be made to achieve real-time visibility (Villalobos et al, 2019) and to reduce uncertainty. Patidar and Agrawal (2020) state that agricultural productivity is the key driver during all agricultural activities to achieve profitability. Currently, real-time monitoring of the goods flow is possible from early stages in the supply chain, such as farms, when sensors are placed in the pallets to provide constant data about the location, temperature, humidity and light exposure, which can be used to calculate the predicted shelf life of the produce (G€ oransson et al, 2018).…”

Section: Problem Statementmentioning

confidence: 99%

“…Patidar and Agrawal (2020) state that agricultural productivity is the key driver during all agricultural activities to achieve profitability. Currently, real-time monitoring of the goods flow is possible from early stages in the supply chain, such as farms, when sensors are placed in the pallets to provide constant data about the location, temperature, humidity and light exposure, which can be used to calculate the predicted shelf life of the produce (Göransson et al.…”

Section: Problem Statementmentioning

confidence: 99%

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In-transit interventions using real-time data in Australian berry supply chains

Rendon-Benavides

Perez-Franco

Elphick-Darling

et al. 2022

TQM

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PurposeThe objective of this paper is to contribute to Australian berry supply chains with a relevant identification regarding the possible data driven interventions that stakeholders can take while the berries are in transit.Design/methodology/approachAn exploratory series of semi-structured interviews was conducted through six Australian experts in the industry with more than 20 years of experience in Australian berry supply chains and the Australian perishable food industry, to identify key possible in-transit interventions that could be implemented in the Australian berry industry.FindingsThe analysis of the interviews revealed a total of 18 possible in-transit interventions. An important finding is that in-transit interventions are made possible by the use of real-time data gathered through IoT devices such as Active Radio Frequency Identification, Time and Temperature Indicators interacting with Wireless Sensor Networks. Another key finding is that Australian berry growers and retailers do possess the technologies and the resources necessary to make in-transit interventions possible, however they have yet applied these technologies to operational decision-making and interventions based on the product, rather focussing on supply chain transactions and events.Research limitations/implicationsSince the research focusses on an Australian context, its findings may or may not be applicable to other countries. The research is exploratory in nature, and its findings should be verified by future research, in particular to test whether the in-transit interventions proposed here can be implemented in a cost-efficient way.Originality/valueTo the authors' knowledge, this publication is the first known academic article to provide a clear understanding of the Australian berry industry from a supply chain and logistics perspective, and the first to explore possible data driven in-transit interventions in perishable food supply chains.

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Section: Problem Statementmentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

In-transit interventions using real-time data in Australian berry supply chains

Rendon-Benavides

Perez-Franco

Elphick-Darling

et al. 2022

TQM

View full text Add to dashboard Cite

show abstract

“…The perishable nature and bulkiness of products, seasonal and scattered production, variability in quantity and quality (i.e. the product does not have standard dimensions), and specific logistics requirements should be considered (Patidar and Agrawal, 2020). These and similar reasons drive costs and reduce if not completely negate farmer profitability (Priya and Vivek, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry

Ramos

Coles

Chavez

et al. 2021

BIJ

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PurposeAgri-food firms face many challenges when assessing and managing their performance. The purpose of this research is to determine important factors for an integrated agri-food supply chain performance measurement system.Design/methodology/approachThis research uses the Peruvian kiwicha supply chain as a meaningful context to examine critical factors affecting agri-food supply chain performance. The research uses interpretative structural modelling (ISM) with fuzzy MICMAC methods to suggest a hierarchical performance measurement model.FindingsThe resulting kiwicha supply chain performance management model provides insights for managers and academic theory regarding managing competing priorities within the agri-food supply chain.Originality/valueThe model developed in this research has been validated by cooperative kiwicha associations based in Puno, Peru, and further refined by experts. Moreover, the results obtained through ISM and fuzzy MICMAC methods could help decision-makers from any agri-food supply chain focus on achieving high operational performance by integrating key performance measurement factors.

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“…Perishability modeling Allen and Schuster (2004), Merrill (2007), Lodree and Uzochukwu (2008), Bohle et al (2010), Ahumada and Villalobos (2011), Cai and Zhou (2014), Nahmias (1982), Goyal and Giri (2001) The authors implemented dual sourcing as an effective strategy to reduce the risk of supply-demand mismatch. A recent study by Patidar and Agrawal (2020) developed an MILP model to present a three-echelon, multiproduct, multiperiod production-distribution problem to minimize the total distribution cost. However, the study did not consider the impact of demand variability in the model.…”

Section: IIImentioning

confidence: 99%

“…The authors implemented dual sourcing as an effective strategy to reduce the risk of supply–demand mismatch. A recent study by Patidar and Agrawal (2020) developed an MILP model to present a three-echelon, multiproduct, multiperiod production–distribution problem to minimize the total distribution cost. However, the study did not consider the impact of demand variability in the model.…”

Section: Literature Reviewmentioning

confidence: 99%

Distribution planning problem of a supply chain of perishable products under disruptions and demand stochasticity

Suryawanshi

Dutta

2021

IJPPM

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PurposeThe emergence of risk in today's business environment is affecting every managerial decision, majorly due to globalization, disruptions, poor infrastructure, forecasting errors and different uncertainties. The impact of such disruptive events is significantly high for perishable items due to their susceptibility toward economic loss. This paper aims to design and address an operational planning problem of a perishable food supply chain (SC).Design/methodology/approachThe proposed model considers the simultaneous effect of disruption, random demand and deterioration of food items on business objectives under constrained conditions. The study describes this situation using a mixed-integer nonlinear program with a piecewise approximation algorithm. The proposed algorithm is easy to implement and competitive to handle stationary as well as nonstationary random variables in place of scenario techniques. The mathematical model includes a real-life case study from a kiwi fruit distribution industry.FindingsThe study quantifies the performance of SC in terms of SC cost and fill rate. Additionally, it investigates the effects of disruption due to suppliers, transport losses, product perishability and demand stochasticity. The model incorporates an incentive-based strategy to provide cost-cutting in the existing business plan considering the effect of deterioration. The study performs sensitivity analysis to show various “what-if” situations and derives implications for managerial insights.Originality/valueThe study contributes to the scant literature of quantitative modeling of food SC. The research work is original as it integrates a stochastic (uncertain) nature of SC simultaneously coupled with the effect of disruption, transport losses and product perishability. It incorporates proactive planning strategies to minimize the disruption impact and the concept of incremental quantity discounts on lot sizes at a destination node.

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A mathematical model formulation to design a traditional Indian agri-fresh food supply chain: a case study problem

Cited by 27 publications

References 36 publications

In-transit interventions using real-time data in Australian berry supply chains

In-transit interventions using real-time data in Australian berry supply chains

Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry

Distribution planning problem of a supply chain of perishable products under disruptions and demand stochasticity

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