Search results

The purpose of this paper is to determine compatibility groups of different fruits and vegetables that can be stored and transported together based upon their requirements for temperature, relative humidity, odour and ethylene production. Pre-cooling which is necessary to prepare the commodity for subsequent shipping and safe storage is also discussed.

The methodology used in this journal is an attempt to form clusters/groups of storing together 43 identified fruits and vegetables based on four important parameters, namely, temperature, relative humidity, odour and ethylene production. An agglomerative hierarchical clustering algorithm is used to build a cluster hierarchy that is commonly displayed as a tree diagram called dendrogram. The same is further analyzed using K-means clustering to find clusters of comparable spatial extent. The results obtained from the analytics are compared with the available data of grouping fruits and vegetables.

This study investigates the usefulness and efficacy of the proposed clustering approach for storage and transportation of different fruits and vegetables that will eventually save huge investment made in terms of developing infrastructure components and energy consumption. This will enable the investors to adopt it for using the space more effectively and also reducing food wastage.

Due to limited research and development (R&D) data pertaining to storage parameters of different fruits and vegetables on the basis of temperature, relative humidity, ethylene production/sensitivity, odour and pre-cooling, information from different available sources have been utilized. India needs to develop its own crop specific R&D data, since the conditions for soil, water and environment vary when compared to other countries. Due to the limited availability of the research data, various multi-criteria approaches used in other areas have been applied to this paper. Future studies might be interested in considering other relevant variables depending upon R&D and data availability.

With the increase in population, the demand for food is also increasing. To meet such growing demand and provide quality and nutritional food, it is important to have a clear methodology in terms of compatibility grouping for utilizing the available storage space for multi-commodity produce and during transportation. The methodology used shall enable the practitioners to understand the importance of temperature, humidity, odour and ethylene sensitivity for storage and transportation of perishables.

This approach shall be useful for decision making by farmers, Farmer Producer Organization, cold-storage owners, practicing managers, policy makers and researchers in the areas of cold-chain management and will provide an opportunity to use the available space in the cold storage for storing different fruits and vegetables, thereby facilitating optimum use of infrastructure and resources. This will enable the investors to utilize the space more effectively and also reduce food wastage. It shall also facilitate organizations to manage their logistic activities to gain competitive advantage.

The proposed model would help decision makers to resolve the issues related to the selection of storing different perishable commodities together. From the secondary research, not much research papers have been found where such a multi-criteria clustering approach has been applied for the storage of fruits and vegetables incorporating four important parameters relevant for storage and transportation.

A poor performance of the cold supply chain (CSC) may increase the loss of quality and potency of perishables and temperature-sensitive products that deteriorate the financial and environmental aspects of the same. The purpose of the current research work is to identify the critical performance factors (criteria) and their co-factors (sub-criteria) that are responsible for the performance measurement of CSC and suggest the best possible solutions (alternatives) to improve the same.

To achieve the objective of the research, a hierarchical model has been developed and analyzed using Analytic Hierarchy Process (AHP)-Fuzzy TOPSIS as a hybrid approach to obtain the severity weights of the identified criteria and prioritization toward their relative importance for the best possible alternatives.

Analysis reveals that the criteria “energy consumption” comes out to be the most critical criteria, and alternative “application of passive cold devices” is the most effective solution for improving the performance of CSC. Higher energy consumption leads to a higher rate of greenhouse gas (GHG) emissions increasing the global warming phenomenon, high operational cost and degradation of natural energy resources. The Application of Passive Cold Devices (PCDs) utilizes solar energy to operate the refrigeration units reducing the energy consumption, environmental and operating cost of CSC.

The research work provides several insights into the critical issues related to the CSC and suggests significant findings that enable the management and decision-makers to adopt these practices for performance evaluation and improvement of the same. The key findings of the work, such as “application of passive cold devices” and “application of IoT in cold chain logistics”, facilitate an improved platform to improve the CSC performance and proposed several directions that will enhance the merit of future research.

The presented study consolidates the various perspectives associated with CSC performance, explores the most critical criteria and proposes the best suitable cold chain practices for organizational growth. The work also provides an analytical analysis with the essence of practicalities and sensitivity analysis to support the robustness of the results. By enriching the literature and quantitative analysis of the new proposed model, this paper forms vast managerial and research implications in the field of CSC.

The purpose of this study is to select the appropriate forecasting model at the retail stage for selected vegetables on the basis of performance analysis.

Various forecasting models such as the Box–Jenkins-based auto-regressive integrated moving average model and machine learning-based algorithms such as long short-term memory (LSTM) networks, support vector regression (SVR), random forest regression, gradient boosting regression (GBR) and extreme GBR (XGBoost/XGBR) were proposed and applied (i.e. modeling, training, testing and predicting) at the retail stage for selected vegetables to forecast demand. The performance analysis (i.e. forecasting error analysis) was carried out to select the appropriate forecasting model at the retail stage for selected vegetables.

From the obtained results for a case environment, it was observed that the machine learning algorithms, namely LSTM and SVR, produced the better results in comparison with other different demand forecasting models.

The results obtained from the case environment cannot be generalized. However, it may be used for forecasting of different agriculture produces at the retail stage, capturing their demand environment.

The implementation of LSTM and SVR for the case situation at the retail stage will reduce the forecast error, daily retail inventory and fresh produce wastage and will increase the daily revenue.

The demand forecasting model selection for agriculture produce at the retail stage on the basis of performance analysis is a unique study where both traditional and non-traditional models were analyzed and compared.

The purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.

In total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.

There are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.

Only peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.

Stress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.

The current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

The countryside population has always been depended on the revenues earned from agricultural yields. These yields often suffer losses in the absence of coordination guidelines in the post-yield supply chains (PYSC). This study aims to identify, address and mitigate the post-yield supply chain impediments (PYSCIs) that lead to enormous amounts of waste and revenue losses. These are the parameters that require government and stakeholders’ attention for alleviation from losses.

Structural equation modelling (SEM) was performed to categorise the identified PYSCIs as “standard measures”. The motive for SEM results is to attract the stakeholders’ attention toward PYSCIs for business sustainability. The PYSCIs were clustered into three “standard measures” (i.e. strategic, tactical and operational measures) for revenue generation and reduced fresh produce spoilage in the countryside.

The SEM results suggest that the focus should be on revising minimum support prices and government support for initiatives, subsidy schemes and incentives at the strategic level. Tactical initiatives focus on linking markets including exports, research and development, attitude towards certification, value addition process adoption and reduced number of stages in the supply chain. The operational initiatives are attitudes towards agriculture and entrepreneurship, transportation infrastructure, supply chain coordination, information visibility, scientific design for packaging and handling and storage space availability for both long and short term at the village level.

This study was performed in India; thus, the research outcomes of this study are restricted to adaption into the developing sub-continents with sub-tropical climates.

The existing level of losses in the PYSC demands introspection and policy changes at the farm level. In the era of cold chains, the Internet of Things, and other advanced mechanisms, a few elementary parameters must be worked upon to reduce PYSC losses. These parameters were identified as impediments to PYSC, requiring public, government and stakeholders’ attention. There is an urgent need for guidelines to be issued to mitigate losses. SEM was performed to attract the public, government and stakeholders’ attention toward impediments to fresh produce spoilage, opportunity generation and business sustainability.

This study uses a novel SEM approach where the PYSCIs were identified and empirically validated in an Indian context. The SEM approach will help in effective decision-making. Similar studies to manage the PYSCIs to reduce fresh produce spoilage with standard measures have not been reported in the literature.

The objective of the study is to develop a methodology to strategically rank store locations using criteria such as population, store site characteristics, economic considerations, competition and so on to select the most optimal retail convenience store location.

A case of National Capital Region, India, for a 24-h convenience store was considered for the study and the major criteria that affect the performance of a convenience store are identified, such as population characteristics, economic criteria, competition, consumer accessibility, store size, total cost, site attractiveness and security. Fuzzy AHP is utilized to find the weightage for each criteria and a combination of fuzzy TOPSIS and grey relational analysis (GRA) is applied to rank the alternative using these criteria weight. Further, results obtained are compared with results from fuzzy TOPSIS and fuzzy VIKOR methods. Sensitivity analysis is also performed for ensuring the robustness of the framework.

It is observed that outcomes do not change under various settling coefficient values, demonstrating that the methodology is very robust. The developed framework will be quite useful to diverse retailers looking to expand and generate substantial profits.

A large sample size of number of locations encourages generalization of results. Strategic ranking of the selected locations is carried out on a few selected criteria. The study was limited by the designated geographical area.

The study contributes to the few available articles on convenience store selection using combination of fuzzy AHP, fuzzy TOPSIS and GRA for a developing country.

Presented work gives comparative review of food supply chain (FSC) under various notions related to its conceptualisation, operationality and technological advancements in lieu with Industry 4.0 revolution. In Indian scenario, the impression of FSC seems in a scattered way that cannot be directly useful for an organisation, to overcome this scattering, a framework has been developed to consolidate the previous research works and exploration of new trends in food supply chain management (FSCM) in context to Indian scenario.

This article encapsulates the essence of various research articles and reports retrieved from databases of Emerald and Elsevier's Science direct, clustering the various notions related to FSC in Indian context. To visualise the one-sight view of related works, a pictorial representations have also been appended.

This article explains the general aspect of FSC and its linkage in context to Indian system. Presented work outlays both empirical and theoretical approaches trending from last 15 years. As research count in context to Indian FSC is lacking, so this work will be a road map for expedition in direction of FSCM, in era of research.

Findings and suggestion in this work can expanded in various industries related to food, helping to turn their fortune and enrichment of Indian FSC.

Food is binding word for all the commodities, and its effective supply chain management is a big boon for economy of country along with large employment generation for people directly/indirectly associated with this industry. This article covers a generalise approach from ground level framework to a level of advancement which fulfil technological aspects, future needs and upcoming trends in lieu to need of developing nation.

As limited research is done in Indian FSCM, this work to bridge this gap along with a well-defined framework which going to explore FSC. This work is going to be facilitation for researchers of this area as no major review for Indian context has not been published.

The cold supply chain industry is still emerging and digital transformation is in the nascent stage in this industry. This paper argues that there are various barriers to implementing blockchain technology in the cold supply chain and aims to develop and validate a model for overcoming key barriers to implementing blockchain technology in the cold supply chain.

The adoption of blockchain technology was proposed through interpretive structural modeling (ISM) and further it is validated using structural equation modeling (SEM).

In this study, ten key barriers to implementing blockchain technology in the cold supply chain were identified, modelled and analysed. Poor leadership style of top management was found to be the most important barriers to implementing blockchain technology in the cold supply chain. The results of SEM indicate that all the paths are supported. The findings showcase the barriers responsible for the lack of blockchain technology infrastructure that ultimately impacts the cold supply chains.

This study highlights the fact that the fate of blockchain technology infrastructure development depends on the leadership style of top management. Demonstrating good leadership style by top management can help overcome the barriers. A good leader pulls the entire team instead of pushing the team. A good leader can guide the entire team to improve IT governance, financial investment, digital footprint, digital readiness, skills and collaboration with service providers to implement blockchain technology. Not only that, a good leader provides mental strength to the team and helps overcome the fear of implementing blockchain in the cold supply chain. A good leader demonstrates good administrative skills and focus on security and privacy policies.

This is a novel contribution towards analysing the key barriers to implementing blockchain technology in the South African cold supply chain using the integrated ISM–MICMAC and SEM approach.

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.

Information and communication technology (ICT) implementation has demonstrated usefulness in supply chain coordination and efficiency optimization in various industries and sectors. This study investigates the extent of ICT deployment in fruits and vegetable supply chains (FVSC) from “farm-to-fork” to ensure food security.

This paper employs a systematic literature review (SLR) methodology and identified a total of 99 journal articles ranging from 2001 to April 2023 for analysis. The reviewed articles have been classified based on the framework proposed from the perspective of food security. Bibliometric and content analysis is carried out with the final list of articles to extract useful insights.

The findings reveal that ICT implementation in FVSC is a relatively new research area; researchers have started investigating several aspects of ICT in FVSC through varied research methodologies. Experimental research aimed at addressing food safety and condition monitoring of fruits and vegetables (FV) has started to gain traction while theory building is yet to gain traction in the literature reviewed. Findings indicate further research is required on technologies like blockchain (BCT), artificial intelligence (AI) and machine learning (ML), especially on key objectives such as food security, and the triple-bottom-line approach of sustainability. It also indicates that implementing relevant ICTs in FVSC can help delay, if not avert, the food crisis predicted by Malthusian theory.

This study used only well-established databases to ensure quality of the studies examined. There is a possibility of missing out on articles from other sources not considered. As a result, future SLR studies may employ additional databases, such as Springer Link, Taylor and Francis, Emerald Insight and Google Scholar. Other methodologies such as expert interviews and extra empirical methodologies may also be employed to give a more balanced picture and insights into ICTs implementation in FVSC.

This study offers a summative detail of the status of ICT implementation in FVSC and can serve as a reference guide for stakeholders in developing strategies for efficient FVSC management. This research work highlights the impact of ICT implementation in FVSC on the four pillars of food security which include improved availability, accessibility, utilization and stability.

This study focuses on ICT implementation for food security in FVSC. The SLR highlights the gaps and proffers potential solutions that enhance global efforts on food security through ICT-enabled reduction in food waste and food loss in FVSC.