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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 purpose of this paper is to put forward a multi-period dynamic pricing strategy for perishable food considering consumers’ price fairness perception. The impacts of the multi-period retail price, food freshness and inventory shortage risk on consumers’ heterogeneous willingness to pay (WTP) and their strategic purchasing behaviours are studied.

The authors present a price optimization model for perishable food, and conduct a laboratory experiment to justify the theoretical model. The data collected are analysed by correlation analysis and nonparametric test.

The results obtained reveal, first, food freshness and inventory shortage risk have effect on consumers’ heterogeneous WTP. Second, different retail prices lead to consumers’ strategically purchasing behaviours. Finally, consumers’ intertemporal price fairness perception and the food retailer’s long-term utility maximization can be achieved by developing multi-period dynamic pricing strategy.

This study suggests the perishable food retailer to apply a step-by-step price markdown strategy. It aims at eliminating price unfairness perceptions caused by loss of freshness and high shortage risk of the perishable food in the subsequent selling periods within the shelf life. Some valuable managerial insights towards perishable pricing for food retailers are discussed.

This study serves as the first step to utilize a laboratory experiment to dig out consumers’ intertemporal WTP towards perishable food. It also presents a novel way for describing consumers’ intertemporal price fairness perception by equalizing consumers’ average utilities considering consumer surplus, food freshness and shortage risk at different selling periods. The line of research on dynamic pricing concerning consumers’ price fairness perception is quite new in academic research, and has arisen due to its importance for food retailers of maximizing their long-term revenues and also of constructing mutual benefit and lasting connections with the consumers.

The purpose of this paper is to contribute to the understanding of the relationship between information sharing and performance of perishable product supply chains (PPSC). Building on transaction cost economics (TCE), organisational information processing theory (OIPT), and contingency theory (CT), this study proposes a theoretical framework to guide future research into information sharing in perishable product supply chains (IS-PPSC).

Using the systematic literature review methodology, 48 peer-reviewed articles are carefully selected, mapped, and assessed. Template analysis is performed to unravel the relationship mechanisms between information sharing and PPSC performance.

The authors find that the relationship between information sharing and PPSC performance is currently unclear, and there is inconsistency in the positioning of information sharing among constructs and variables in the IS-PPSC literature. This implies a requirement to refine the relationship between information sharing and PPSC performance. The review also revealed that the role of perishable product characteristics has largely been ignored in existing research.

This study applies relevant multiple theoretical perspectives to overcome the ambiguity of the IS-PPSC literature and contributes nine propositions to guide future research. Accordingly, this study contributes to the refined roles of relationship uncertainty, environmental uncertainty, information sharing capabilities, and perishable product characteristics in shaping the relationship between information sharing and PPSC performance.

The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies. It is achieved by understanding the dynamics between various risks in perishable food supply chain and modeling them using interpretive structural modeling (ISM).

Four categories and 17 types of risk are established from literature and conducting brainstorming sessions with managers/engineers in Indian dairy firms. A methodology is proposed using ISM, risk priority number and risk mitigation number to prioritize risk mitigation strategy decisions for the dairy industry.

For a perishable food supply chain, risk positioned at lower levels (levels 1 or 2) in the hierarchy should be targeted first, while formulating mitigation strategies. To investigate further, risk- enabling factors which are identified for an Indian dairy firm for these levels 1 and 2 risks and mitigation strategy prioritization show that supplier side risks are more dominant followed by market risks and process risks.

This proposed methodology has not been statistically validated or empirically tested, and factors taken are in the Indian context, but the authors believe that the study is highly relevant to other markets as well because the ISM-based analysis is for generic perishable food supply chain environment.

This study provides a useful approach to managers/decision makers to identify, analyze and prioritize risk in the supply chain. It also provides insights into the mutual relationships of supply chain risks which would help them to focus on the effective risk mitigation strategies formulation. The study provides the insights to benchmark and risk management in the dairy industry environment with priority considerations.

This paper provides an integrated approach to identifying, quantify, analyze, evaluate and mitigate the risks of perishable food (in the dairy environment) in the Indian context.

Covid-19 is a serious threat to the dietary quality of vulnerable communities in developing countries with limited economic resources. This study explored the implications of COVID-19 on daily dietary behavior and food consumption patterns of perishable and nonperishable food commodities based on the gender of household headship in Pakistan.

The data was collected through an online survey using the snowball sampling technique. A mixed design ANOVA, an independent t-test and a multivariate probit model were used to look at the data from 417 female-headed households and 1,131 male-headed households that were surveyed in the study.

Female-headed households experienced a greater decrease in their daily intake of perishable and nonperishable food commodities compared to male-headed households during COVID-19. The decrease in consumption of perishable food commodities was greater than the decrease in nonperishable food commodities for both female-headed and male-headed households. Female-headed households witnessed the largest decrease in daily intake of animal-derived foods, while male-headed households observed the highest diminution in consumption of fruits. Female-headed households and male-headed households reduced their consumption of perishable food commodities by more than one-third and one-fifth, respectively. Households with lower socioeconomic status reported higher reductions in their daily intakes of food commodities compared to households with higher socioeconomic status.

The cross-sectional nature of the collected data does not allow the development of a causal relationship between COVID-19 implications and food consumption changes in daily dietary patterns.

Dietary and consumption patterns of populations are changing worldwide due to COVID-19. There is no study to assist policymakers in determining how COVID-19 is affecting the daily food consumption patterns of perishable and non-perishable food commodities of households based on gender in the developing world.

Managing perishable inventories is a trade‐off of shortages and lost sales against wastage. This paper aims to identify what drives good management of perishables within the supply chain using the example of blood inventory management in hospitals.

Seven case studies with hospital transfusion laboratories in the UK blood supply chain were carried out in order to explore how perishable inventories are managed. The case studies identify drivers for good performance in perishable inventories.

Six recommendations are developed for how managers can improve perishable inventory performance. These are based around simple management procedures implemented by experienced staff. The case studies develop three propositions that recommend how inventory theory should be embedded in practice.

This research demonstrates that managerial changes and training issues have a significant impact on waste reduction and inventory management performance in perishable supply chains. However, as the case studies focus on the blood supply chain, some caution needs to be applied in generalising these findings beyond the specific context studied.

A multi‐disciplinary approach, combining awareness of the importance of the dynamics of the whole supply chain with good skill and experience, leads to new thinking, which enables staff to make better inventory decisions resulting in better performance and reduced wastage. Managerial changes and training are critical for good inventory performance.

Literature suggests that sophisticated and complex inventory models will drive performance; however, in practice a combination of basic well‐grounded inventory theory with simple management procedures carried out by experienced staff leads to better performance.

The purpose of this study is to compare the impact of multi‐period pricing, as an example of more dynamic pricing and discounting strategy with that of a present less dynamic alternative on customer satisfaction and consumers' willingness to make trade‐offs between price and remaining shelf‐life.

The authors conducted interviews with three food retail managers in South Korea to gather practical information about the management of perishable foods, which informed the design of a survey in which consumers in South Korea were questioned about their perceptions of the two strategies, with respect to nine perishable food products in three categories. The data collected were analysed by one‐way ANOVA and the t‐test.

The findings of this research present an improved understanding of the impact of a multi‐period pricing strategy on consumer satisfaction and customer behaviour for perishable foods. The conclusions have the potential to significantly assist food retailers to understand the consumers' perspective on the benefits of a more dynamic pricing strategy.

The findings suggest that food retailers can enhance customer satisfaction by offering an earlier but lower discount, and increasing it as perishable food items approach their expiry date, rather than a higher discount when the expiry date is imminent.

The findings in this study are significant since they serve as the first step in measuring the value of dynamic pricing approaches that provide better trade‐off options between price and remaining shelf‐life from consumers' perspectives.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

The purpose of this paper is to examine the effects of price consciousness and sale proneness on purchase intentions regarding with expiration date-based priced perishable foods.

Data were collected from a convenience sample of consumers with structured questionnaires. Structural equation modeling was used in order to test the proposed hypotheses.

Results of a structural model reveal positive relationship between price consciousness and sale proneness. The findings also confirm the effect of price consciousness on purchase intentions toward expiration date-based priced perishable foods. On the other hand, the results have not support the positive effect of sale proneness on purchase intentions.

To the knowledge, this is the first study which has examined the relationships between price consciousness, sale proneness and purchase intentions in the context of expiration date-based pricing.