Dairy Supply Chain Research Articles

Eliciting agents’ behaviour and model validation using role playing game in agent-based dairy supply chain model

Role playing games have been widely used to develop and validate an agent-based model by observing players’ behaviour. Our study focuses on proposing a novel approach to use role-playing games in the development and validation of an agent-based model. Our innovations include matching the game’s parameters and player composition to reality, incorporating the design of experiments into the data collection, and incorporating operational validation steps into the process. We demonstrate the benefits of our approach by a case study of a dairy supply chain. Our analysis illustrates that the data obtained from the role playing game are valuable for the validation of agent-based models at the micro-level (process and knowledge representation) and, subsequently, improve the validity of the model at the macro-level.

Isolation and phenotypic identification of Campylobacter in dairy supply chain

Isolation and phenotypic identification of Campylobacter in dairy supply chain

Optimal Design of Sustainable Biodiesel Supply Chain Using Dairy Waste Scum as a Feedstock Generated from Dairy Supply Chain

The rapid depletion of fossil fuels and the increased environmental impact of their combustion make it necessary to find cleaner and more sustainable energy resources. Over the last decades, biodiesel has been introduced as an alternative because of its advantages over fossil fuels. However, the high production cost of biodiesel is one of the main obstacles to achieving its commercial viability. One way to improve the efficiency and sustainability of this process is to use Dairy Waste Scum (DWS), which is a waste product from the dairy industry as a feedstock. Selection of the feedstock used is only a part of the strategy to increase the sustainability of this type of production. The most effective way to achieve this is by optimising the activities across the supply chains (SCs). In addition, the sustainability of the biodiesel production process using DWS may be influenced by design of optimal product portfolio of the considered dairy SC. This study proposes an approach for optimal design of a sustainable combined dairy and biodiesel/diesel SC using dairy waste scum as a feedstock, generated from dairy SC. It is based on defining mixed integer linear programming (MILP) model of the optimal design of the considered combined SC. The latter includes economic and environmental assessments. The first one is defined as an optimization criterion while the second one is defined as a constraint. The model takes into account key SC activities such as infrastructure compatibility; the production of the dairy products; milk, dairy products and DWS transportation between the regions, carbon taxes, related with all SC activities. The environmental and economic performance of the combined dairy and biodiesel/diesel SC is assessed by the annual operating costs for the combined SC design and greenhouse gas (GHG) emissions of pollutants associated with its operation. The developed approach was implemented on a real case study from Bulgaria. The analysis of the environmental results shown that the total GHG emissions generated by the operation of the SC for all time intervals are mainly due to the production of the products in dairies and utilization of unused DWS for production of biodiesel.

A MINLP Model to Optimal Design of ? Sustainable Dairy Supply Chain Taking into Account Preferences of the Network Actors

The increase of pollutants generated in the production of dairy products, the increase of the production costs and emerging social problems requires the development of approaches for resilience improvement of the considered product productions. An effective way to achieve this is by optimising all activities across the supply chain: from milk suppliers through the production itself to end-users meeting environmental, economic and social criteria. The other important aspect of solving this type of problems is taking into account the preferences of all actors in the network. The present study proposes a mixed-integer non-linear programming (MINLP) model for the optimal design of a sustainable dairy supply chain (SC) for the production of different dairy products satisfying the preferences of all actors of the network - milk suppliers, dairies and markets. The approach includes models for the production of dairy products along with the economic, environmental and social impact of the considered SC. Three optimization problems are defined and solved at different optimisation criteria representing the preferences of all actors in the SC. The first solution results in the supply of 162,022 kg of two types of milk for the production of 61,758 kg of low and high-fat content products. The latter exceeds the market demands. This is the solution with the largest economic and social costs and lowest production profit of 118,008 BGN. The second solution is related to the production of 60,023 kg of both products. This is the solution with the lowest economic costs and largest production profit of 143,809 BGN. In solution 3, full satisfaction of market requirements was achieved. It is related to the supply of 132,146 kg of both types of milk for the production of 60,057 kg of both products.

Empirical study on risk mitigation for dairy supply chain management of Aavin Co-operative Milk Producers’ Union Ltd.

Raw fresh-milk has a perishable characteristic, so it needs an appropriate handling from milking to processing, otherwise fresh milk will be contaminated by bacteria so that the shelf life becomes shorter and its losses the quality. Besides, from the perspective of quantity, the lower farmer’s production in the upstream will minimizes the product availability in the downstream. This condition may cause some potential risk during the supply chain. There is a need to map the risk along the supply chain, using samples in Tirunelveli Aavin Nellai milk plant. This paper aimed to analyze the pattern of the supply chain and its risk, to set the risk treatment and to mitigate the risk as well. Data sampling were selected by simple random sampling and then collected using in-depth interview to the risk owners. The results show there are 6 supply chain models and the total number of risks is 50 some of the risks are repeated and from that 10 prioritized risks are mitigated.

Strategic Actions for a Sustainable Internationalization of Agri-Food Supply Chains: The Case of the Dairy Industries from Brazil and Germany

While facing a growing domestic demand of milk and milk products, the Brazilian dairy industry is far behind in terms of competitiveness and sustainability when compared to other national agricultural sectors. Nonetheless, in Germany the leading dairy companies mainly pushed by a saturated domestic market, EU agriculture policy oriented to liberalization of markets, and increasing political and social demands are looking at markets beyond EU. In the context of the increasing globalization of agricultural supply chains, the issue of sustainability gains particular importance in companies’ internationalization strategies. By using expert interviews, this paper investigates strategies for integrating Brazilian and German dairy supply chains and how both sides can benefit from this situation also in terms of sustainability. The analyses show that problems of the industries in both countries basically complement each other at different levels and positive synergies for both sides exist when it comes to sustainable issues, positioning themselves competitively for the future and creating a good position for conquering market shares in a globally growing milk market. This paper proposes an approach for the challenges of such integration, as well as viable solutions to sustainability issues.

Inventory strategy development under supply disruption risk

This paper proposes a multi-period decision-making framework that enables procurement managers to develop an optimal supply inventory strategy under uncertain supply conditions. The framework draws on financial options valuation techniques by adopting the view of a procurement manager facing several uncertainties, while seeking to maximise its profit by exercising its flexibility to procure supplies and use inventories. Given the multitude of uncertain variables influencing inventory management decision in practice, the model is developed to remain robust to the inclusion of several underlying stochastic variables; it uses an American options valuation method and a least squares Monte Carlo simulation technique to solve the underlying dynamic programming problem. To demonstrate the application of the developed framework, a case study is presented based on data from a dairy supply chain. The case study explores the decision problem in several scenarios, showing how a decision-maker’s perception of product demand and supply price uncertainties, expectations over the timing of a supply disruption, discount rate, price shocks and disruption duration can be suitably incorporated into the decision-making framework.

Intention to Purchase Milk Packaged in Biodegradable Packaging: Evidence from Italian Consumers.

The dairy industry generates large volumes of liquid waste that can be used to produce biopolymers, potentially employable for the creation of milk biodegradable bottles. In that regard, this paper aims to explore the consumers’ intention to purchase sustainable packages, as well as to assess the willingness to pay for it considering renewable packages made using organic waste feedstocks from the dairy industry (e.g., whey) and plant-based material (e.g., corn, sugarcane, etc.). To reach the stated objectives, we collected individual-level information (e.g., age, gender, education, income) from a convenient sample of 260 Italian consumers and a modified version of the Theory of Planned Behavior estimated using a structural equation model. Findings show that attitudes and perceived behavioral control are the most important drivers of the consumers’ intention to purchase sustainable packages. Finally, statistics show that respondents slightly prefer to purchase products packaged using plant-based biodegradable material, as well as most of the respondents show a low willingness to pay for milk offered in biodegradable packaging, regardless of the raw material used. Then, policymakers and companies should invest in educational/informational campaigns pointing out the beneficial effects on the environment from the purchase of foods in sustainable packaging. This may potentially increase the consumers’ intention to purchase, as well as their willingness to pay for plant-based and dairy whey-based packages by increasing the sustainability of the dairy supply chain.

Probabilistic modelling of Escherichia coli concentration in raw milk under hot weather conditions

Climate change is one of the threats to the dairy supply chain as it may affect the microbiological quality of raw milk. In this context, a probabilistic model was developed to quantify the concentration of Escherichia coli in raw milk and explore what may happen to France under climate change conditions. It included four modules: initial contamination, packaging, retailing, and consumer refrigeration.The model was built in R using the 2nd order Monte Carlo mc2d package to propagate the uncertainty and analysed its impact independently of the variability. The initial microbial counts were obtained from a dairy farm located in Saudi Arabia to reflect the impact of hot weather conditions. This country was taken as representative of what might happen in Europe and therefore in France in the future due to climate change. A large dataset containing 622 data points was analysed. They were fitted by a Normal probability distribution using the fitdistrplus package. The microbial growth was determined across various scenarios of time and temperature storage reflecting the raw milk supply-chain in France. Existing growth rate data from literature and ComBase were analysed by the Ratkowsky secondary model. Results were interpreted using the nlstools package.The mean E. coli initial concentration in raw milk was estimated to be 1.31 [1.27; 1.35] log CFU/ mL and was found to increase at the end of the supply chain as a function of various time and temperature conditions. The estimations varied from 1.73 [1.42; 2.28] log CFU/mL after 12 h, 2.11 [1.46; 3.22] log CFU/mL after 36 h, and 2.41 [1.69;3.86] log CFU/mL after 60 h of consumer storage. The number of milk packages exceeding the 2-log French hygiene criterion for E. coli increased from 10% [8;12%] to 53% [27;77%] during consumer storage. In addition, the most significant factors contributing to the uncertainty of the model outputs were identified by running a sensitivity analysis. The results showed that the uncertainty around the Ratkowsky model parameters contributed the most to the uncertainty of E. coli concentration estimates.Overall, the model and its outputs provide an insight on the possible microbial raw milk quality in the future in France due to higher temperatures conditions driven by climate change.

Mediator margins in the dairy supply chain and factors influencing marketing preferences in Eastern Mediterranean region of Turkey

The purpose of this study is to identify the shares of the intermediaries in the Eastern Mediterranean region milk supply chain (I) and to estimate the factors influencing the raw milk marketing preferences of milk producers (II). The research was conducted in 2017 with 102 dairy farms and 36 dairy industry enterprises in Hatay, Kahramanmaraş, and Osmaniye provinces. As a result of the research, it was found that 85% of the milk produced by dairy farms was offered to the market, 65% of the milk entering the supply chain was transferred to the dairy industry and the average capacity utilization rate of the industry was 37%. It was found that the most rational chain for the milk producers and dairies among the 4 main marketing channels in the region is the third channel, which has two stages. Binary logistic regression was found to be significant (p < 0.01) as a whole. It was found that "scale" and "price" variables explained the variation in marketing preference by 70%. The cattle unit in the livestock enterprise has a positive effect on the transfer of milk to the industry, and the possibility of selling the milk directly at a higher price has a negative effect. For a more sustainable market organization and supply chain, business scales need to be increased and raw milk prices should be linked with production costs.

Safety Failure Factors Affecting Dairy Supply Chain: Insights from a Developing Economy

Safety issues in the dairy industry have attracted greater attention in recent years, and the public have showed an intensive concern regarding safety failure in the dairy supply chain. Since the dairy industry is closely associated with humans and fulfills basic necessities, it is necessary to explore safety failure factors (SFFs) affecting the supply chain of the dairy industry. This paper aims to explore the SFFs of the dairy supply chain using an interpretive structural modeling technique (ISM) and Matrice d’Impacts Croises Multiplication Appliques a un Classement (MICMAC) analysis in a Pakistani context. A total of twenty-five failure factors have been identified through literature reviews and the opinion of an expert team, including managerial and technical experts from the dairy industry, as well as academics. Interpretive structural modeling (ISM) is applied to analyze the mutual interaction among barriers and to develop a structural model. The MICMAC technique is used to identify the importance of SFFs based on their driving and dependence power. The results of this study will help decision-makers in the dairy industry to plan their supply chain activities more effectively and efficiently by managing the identified barriers.

Research on Profit Distribution Between Dairy Farmers and Manufacturing Enterprises in Dairy Supply Chain Based on Qualified Rate

As an indispensable industry for the health and prosperity of the Chinese nation, dairy industry is a symbolic industry of agricultural modernization and a strategic industry of coordinated development of primary, secondary and tertiary industries.With the rapid development of China's dairy industry, China’s dairy product quality and safety risks still exist.The imbalance of profit distribution is one of the important reasons for the confusion of dairy market and quality and safety problems.The essence of the normal operation of the dairy supply chain and the guarantee of the quality and safety of dairy products lies in the correct handling and coordination of the interest relationship between the enterprises in each node of the supply chain.Reasonable benefit coordination mechanism and fair benefit distribution mode are of great significance to ensure the quality and safety of dairy products, maintain the stable relationship of dairy supply chain, and promote the healthy and sustainable development of China’s dairy industry.This paper discusses the optimal quality and safety level and optimal revenue of two-stage dairy supply chain based on the pass rate of dairy farmers and dairy processing enterprises under decentralized and centralized decision-making.In order to improve the quality efforts of dairy farmers, the internal and external loss sharing contract is designed, that is, dairy farmers and dairy processing enterprises share consumer losses, whilemanufacturing enterprises provide certain quality cost subsidies for dairy farmers. Finally, through the example analysis, it is verified that the benefit sharing and risk sharing between dairy farmers and national processing enterprises can be realized through the contract.Through contract coordination, the profit distribution of dairy farmers and processing enterprises and the quality and safety level of supply chain were optimized, and the importance of quality control in raw milk production was further verified.

A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions

This study determines the potential barriers to achieving circularity in dairy supply chains; it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘economic’, ‘environmental’, ‘social and legal’, ‘technological’, ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning, optimization, data mining, cloud computing, artificial neural network, statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers, ‘economic’ was of the highest importance, followed by ‘technological’, ‘environmental’, ‘strategic’, ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers, ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’, ‘machine learning’, ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains.

An approach for a sustainable decision-making in product portfolio design of dairy supply chain in terms of environmental, economic and social criteria

The production of dairy products is related to water and energy costs and generation of large amounts of emissions of pollutants. Full sustainability of these systems can be achieved by optimizing all activities in the supply chain (SC) taking into account not only the environmental and economic aspects, but also the social ones. This study proposes a multi-objective modeling approach for optimal design of three-echelon SC for production of dairy products according to different recipes while satisfying environmental, economic and social criteria defined in terms of costs. The environmental costs are associated with the generated wastewater from dairy production and CO2 emissions due to energy consumed and transport of raw materials and products. The social ones are related to the employees hired for implementation of the SC activities. It was implemented on a real case study from Bulgaria. Four mix integer nonlinear programming optimization models were defined–one without and three with social impact consideration. They were solved at different values of the environmental and social constraints. The obtain results showed that stricter environmental constraints lead to higher economic costs and lower profit. Conversely, higher environmental constraints result in higher profit and lower economic costs. The greatest share in the environmental impact has the wastewater generated, followed by CO2 emissions related with energy consumed and CO2 emissions due to transport. The obtained solutions can be used in the decision-making process in terms of seeking a trade-off between profit, environmental and social impact.Graphic abstract

COVID-19 and the U.S. Dairy Supply Chain

COVID-19 and the U.S. Dairy Supply Chain

Leverage risks for supply chain robustness against corruption

PurposeThis paper examines the establishment of supply chain robustness against corruption by utilizing risk interactions.Design/methodology/approachBased on empirical results from the New Zealand dairy industry, a system dynamics model is established to explore the underlying relationships among variables.FindingsThe results show that although certain supply chain risks seem unrelated to corruption, their mitigation would help mitigate the impact of corruption due to risk interactions; and mitigation of some of the risks is more effective in mitigating the impact of corruption. Leverage risks have been defined and identified in this research, which expands the extant knowledge in reducing the impact of corruption on supply chains.Originality/valueThe research illustrates how the impact of corruption can be studied in an integrated way with dairy supply chain SD analysis. It is a pioneering study to mitigate the impact of corruption on supply chains from supply chain robustness.

Co-occurrence and toxicological relevance of secondary metabolites in dairy cow feed from Thailand

ABSTRACT The occurrence of secondary metabolites and co-contaminants in dairy cow feed samples (n = 115), concentrate, roughage, and mixed feed, collected from Ratchaburi and Kanjanaburi provinces, Thailand, between August 2018 and March 2019 were investigated using LC-MS/MS based multi-toxin method. A total of 113 metabolites were found in the samples. Fungal metabolites were the predominant compounds, followed by plant metabolites. Among major mycotoxins, zearalenone and fumonisins were most frequently detected in concentrate and mixed feed samples, while deoxynivalenol and aflatoxin B1 were found at the frequency lower than 50%. Other metabolites, produced by Aspergillus, Fusarium, Penicillium, and Alternaria species, occurred in the samples. Flavoglaucin, 3-nitropropionic acid, averufin, and sterigmatocystin were the most prevalent Aspergillus metabolites. Common Fusarium metabolites occurring in the samples included moniliformin, beauvericin, and enniatins. For Penicillium metabolites, mycophenolic acid, questiomycin A, quinolactacin A, oxaline, citrinin, and dihydrocitrinone were frequently detected. The toxic Alternaria metabolites, alternariol, and alternariol monomethyl ether showed the high incidence in the samples. Plant metabolites were commonly found, mainly cyanogenic compounds and isoflavones, from cassava and soybean meal used as feed ingredients. Overall, 96.6% of feed samples contained at least two metabolites, in a range from 2 to 69. According to co-contamination of mycotoxins found in feed samples, zearalenone were mostly found in combination with fumonisin B1, deoxynivalenol, and aflatoxin B1. Fumonisin B1 co-occurred with aflatoxin B1 and deoxynivalenol. The mixtures of deoxynivalenol and aflatoxin B1, and of zearalenone, fumonisin B1 and deoxynivalenol were also found. Due to known individual toxicity of fungal and plant metabolites and possible additive or synergistic toxic effects of multi-mycotoxins, the occurrence of these metabolites and co-contaminants should be monitored continuously to ensure food safety through the dairy supply chain.

How much can combinations of measures reduce methane and nitrous oxide emissions from European livestock husbandry and feed cultivation?

In the EU28, the meat and dairy supply chains emitted 360 Mt CO2-eq or 80% of all agricultural CH4 and N2O emissions in 2016, which must be reduced to reach net-zero greenhouse gas emissions by 2050. Our research explores how far these emissions can be reduced by combining field tested mitigation measures for beef cattle, dairy cattle, swine, sheep, and synthetic fertilizers. Many mitigation measures targeting enteric fermentation, manure management, and fertilizer application have been experimentally tested; however, the impact of combining measures is relatively unexplored. To address this knowledge gap, we use graph theory to create combinations of measures for which we calculate the overall mitigation potential. From previous review studies, we identified 44 measures and formulated rules on impossible and mandatory combinations of measures. Based on the resulting sets of feasible cliques in the graphs and a simplified technological baseline, we estimate that the combinations with the highest reductions reduce CH4 and N2O emissions from beef cattle by 57%, dairy cattle by 47%, swine by 70%, sheep by 48%, and synthetic fertilizers by 44%. Together, they can reduce CH4 and N2O emissions in the EU28 from meat and dairy production by 54%, and for agriculture overall by 42%. This indicates that implementing more measures in the meat and dairy sectors can create room for further reduction than in the existing modelled pathways for the EU28. However, technical measures are incapable of fully eliminating agricultural CH4 and N2O, so there remains a need for CO2 removal technologies.

Assessing dairy supply chain vulnerability during the Covid-19 pandemic

ABSTRACT Frequent occurrence of disruptions in the supply chain due to the Covid-19 pandemic has increased the supply chain vulnerability (SCU), which affects the performance and revenue generation of firms. If the commodity we are dealing with in a supply chain is of a perishable nature, then the situation becomes more complicated, as such products need restrictive storage and transportation facilities. The dairy supply chain is one such perishable product supply chain. This paper, thus, proposes a method to identify key drivers of SCU in a dairy SC followed by establishing a model using interpretive structural modeling (ISM) and a graph theory approach (GTA) to calculate the SCU Index. It is important to quantify the SCU for identifying major factors affecting it and then developing techniques to mitigate it. In order to quantify the SCU, first, the ISM model is used to identify the interrelation between drivers, and then an adjacency matrix is formed by using the interdependence, thereby adding inheritance of each driver. A variable permanent matrix is formed to calculate the SCU Index for the SC. This proposed approach will help managers in mitigating the adverse effects of COVID-19 on the dairy supply chain.

Are UK retailers well placed to deliver ‘less and better’ meat and dairy to consumers?

Retailers can play an important role in facilitating a transition to sustainable diets in the UK. They have been implementing strategies aimed at helping customers make healthier choices and are now considering how to broaden this to include sustainability, which is a live discussion in the UK retail sector. Focusing on ‘less and better’ meat and dairy as a core component of sustainable diets, this study investigates retailer perceptions of sustainable diets and their strategies and challenges to provide and promote customer purchasing of ‘less and better’ meat and dairy. Results from a series of semi-structured interviews with senior health and sustainability professionals within the UK retail sector indicate that retailers have a diverse understanding of sustainable diets that seldom includes ‘less and better’ meat and dairy. Retailers are adopting a range of different strategies linked to ‘less and better’ meat and dairy – from improving the sustainability of their meat and dairy supply chains to influencing customer purchasing through ‘nudge’ interventions. While strategies related to ‘better’ meat and dairy are being adopted, no retailer is implementing interventions focused on reducing purchasing of meat products. The promotion of sustainable diets is seen by some retailers as a way of positively engaging with customers and improving brand loyalty, but there are external barriers to reducing purchasing of meat and dairy products that are beyond the direct control of the retailer.