INFORMS 2017 Presentation

1. www.cranfield.ac.uk/som
Policies to minimise food
waste in retail environment
Emel Aktas, Akunna Oledinma, Hafize Sahin, Zahir Irani,
Amir Sharif, Samsul Huda, Zeynep Topaloglu, Mehran
Kamrava
Contact: emel.aktas@cranfield.ac.uk
22 October 2017
This presentation was made possible by NPRP grant # [NPRP 7-1103-5-156] from the Qatar National Research Fund (a
member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

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• Background
• Research Problem
• Literature
• Methodology
• Results
• Future work
Outline

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oPerishable products deteriorate and lose value in a short period of time
oMost common causes of food waste at a retailer
§ overstocking,
§ consumer behaviour,
§ inappropriate quality control and product handling
oInventory management strategies considering the consumer behaviour
are needed.
Research Problem
http://www.davinfoods.co.uk

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www.cranfield.ac.uk/som
Literature

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Converting retail food waste into by-product (Lee
& Tongarlak, 2017)

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Discounting and dynamic shelf life to reduce
fresh food waste at retailers (Buisman et al., 2017)

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• Dynamic price strategies to reduce food and other perishable product
spoilage
• A deterministic mathematical model to study the influence of
§ price elasticity of demand (alpha)
§ age-sensitivity of demand and (beta)
§ age profile of initial inventory (gamma)
Effects of dynamic pricing of perishable products
on revenue and waste (Adenso-Diaz et al., 2017)
Revenue loss (w.r.t. no-discount benchmark) versus
total waste reduction (α = 2, β = 2).

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• Reduce costs of shortages and lost sales
• Reduce costs of inventory
• Reduce wastage
• Improve customer service and loyalty
Multiple objectives in perishable inventory
management
Work
Reduce
waste
Decrease shortage/
backorder
Reduce average
stock costs
Increase
profit
Improve service
level / others
Duan and Liao, (2013) √ √
Sharda and Akiya, (2012) √ √
Haijema, (2014) √ √ √
Broekmeulen & Donselaar, (2009) √ √
Tekin, Gürler and Berk, (2001) √ √
Gómez et al. (2004) √ √
Ferguson and Ketzenberg, (2006) √ √
√
Minner and Transchel, (2010) √
√
Gunpinar and Centeno, (2015) √ √
√

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Modelling Store Inventory
Chuang & Oliva (2016)

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Methodology

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1. Interviews with stakeholders on causes of food waste in Qatar
2. Identification of factors
3. A panel of experts rates the importance factors
4. A list of factors with the highest relevance to food waste
5. Preliminary cause – effect diagram based on interviews
6. Final cause – effect diagram with experts’ input over Webinars
7. Subset of retail food waste cause-effect diagram
8. System dynamics simulation of retail food waste [in progress]
Methodology

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Results

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Analysis of Interviews
https://blogs.commons.georgetown.edu/safeq/factors-relevant-to-food-waste/

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• 17 experts in supply chain / operations
• 22 experts in demand / consumer behaviour
• 14 calibration questions
Expert Ratings
Supply example
Demand example

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Rating of Importance: Supply Factors
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4
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3.527 4.190 4.854 5.518 6.181 6.845 7.509
Histogram of the Factor Weights for Supply
Perspective

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Rating of Importance: Demand Factors
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2
4
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10
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3.366 4.094 4.823 5.551 6.279 7.007 7.736
Histogram of the Factor Weights for Demand
Perspective

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Final Set of Factors
6.000 6.500 7.000 7.500 8.000 8.500
Break in the Cold Chain
Shelf Life
Portion Size
Expiry Date
Demand Planning
Food Product Type
Buying Behaviour
Open Buffet
Storage / Refrigeration Conditions
Left-overs
Factors Selected for Cause-Effect Relationships

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Preliminary Cause – Effect Map

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Synthesized Cause-Effect Map

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A Cause-Effect Diagram of the Retail Food Waste
B1: Sales
B2: Out-of-stock
B3: Waste

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• Food waste in retail environment is a complex problem
• Inventory policies should consider changing consumer behaviour and
gaming effects
• Discounts based on expiry date / time depends on demand elasticity
• Costs of implementing discounts to be considered in design of inventory
policy
• Dynamic price policy should be adopted to shelf life features and product
deterioration rates
Future work
• Collecting data on food imports and local produce
• Estimating the parameters in system dynamics model
• Running scenarios
Conclusions and Future Research

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Thank you
Questions / Comments?
Emel.Aktas@cranfield.ac.uk
@emelaktas
http://uk.linkedin.com/in/emelaktas/
https://blogs.commons.georgetown.edu/safeq/

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Food Product Grand Total (QAR)
SEMI MILLED OR WHOLLY MILLED RICE, WHETHER OR NOT
POLISHED OR GLAZED 5,289,170,010
POULTRY, NOT CUT IN PIECES, FROZEN 2,835,247,638
CAMELS AND OTHER CAMELIDS (CAMELIDAE) 2,411,567,047
LIVE SHEEP OTHER BREED 2,223,144,702
CONCENTRATED, MILK 2,215,200,174
POULTRY, CUTS AND OFFAL, FROZEN 1,528,819,711
VEGETABLE FATS AND OILS AND THEIR FRACTIONS, PARTLY OR
WHOLLY HYDROGENATED, INTER ESTERIFIED, RE ESTERIFIED OR
ELAIDINISED, WHETHER OR NOT REFINED, BUT NOT FURTHER
PREPARED 1,455,613,930
YOGURT, WHETHER OR NOT CONCENTRATED OR CONTAINING
ADDED SUGAR OR OTHER FLAVORING OR CONTAINING ADDED
FRUIT OR COCOA 1,285,491,116
LIVE SHEEP 1,238,862,890
PARSLEY, CHERVIL, CRESS, CORIANDER AND OTHER EDIBLE
VEGETABLES (N.E.S.) FRESH OR CHILLED OKRA 1,175,439,767
Food Imports to Qatar