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As with most industries who provide a regular and efficient service, the Dairy Industry is taken very much for granted. The appearance early every morning of fresh, clean milk on doorsteps throughout the country is accepted by everyone as part of daily life. Also the great variety of dairy products which have become available in recent years have been enthusiastically welcomed.

It is noted that a number of presently developing countries, in an attempt to offset the unfavourable internal terms of trade facing their agricultural sector, have recently increased subsidies to this sector. A useful aid to the measurement of subsidies is the Producer Subsidy Equivalent (PSE); this conceptually simple “tool” possesses the merit of being easily computed and easily comprehended by policy‐makers. In this article the results of a study of PSEs for the dairy industry in Peninsular Malaysia are presented and analysed. Overall, it is observed that the dairy industry is heavily subsidised, with the parastatal ranch sector more so than the smallholder sector. Doubt is also expressed as to whether the infant‐industry argument is a valid one in Malaysian conditions.

Operations and Logistics.

Senior undergraduate students and postgraduate students specialising in agricultural economics/agribusiness/supply chain management and can also be used for executive training for supply chain managers and corporate social responsibility (CSR) managers of food companies.

This case presents an industry leading company – Nestlé’s sustainable initiative in its dairy supply chain in China. The case begins with the background of China’s dairy industry, followed by an introduction of the case company. The case then moves on to the comparison of Nestlé’s fresh milk supply chain operation before and after 2008 and different approaches to help the dairy suppliers’ transformation. The focus is on Nestlé’s innovative industry collaboration platform, the Dairy Farming Institute.

This case allows students to explore the following theoretical frameworks: sustainable supply chain management; supply chain leadership, supply chain learning and supply chain structure. By analysing this case, students should be able to gain an understanding of how multinational corporations (MNCs) play a supply chain leadership role in supply chain learning of sustainable supply chain initiatives.

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CSS 9: Operations and Logistics.

The purpose of this paper is to present theoretical explanations for the failure of the largest dairy processing firm in Former Yugoslav Republic of Macedonia (FYROM) after only about one year of operation.

The paper contains a case study on the establishment and failure of a new firm is presented. Data were collected through mass media reports and interviews with knowledgeable individuals in the dairy industry. The data were analyzed using neo-institutional theories, primarily agency theory.

The core of the explanation is that the various categories of institutions were not aligned. For example, poor contract enforcement created insurmountable agency costs for all parties involved.

As this paper is based on a case study it is uncertain to which extent the finding can be generalized.

Most case studies describe successes. This paper presents a case where the odds for success were poor, but the project was still initiated.

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.

As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.

Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.

This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

This paper aims to explore the formal (i.e. contracts, standards, processes, and structure) and informal (i.e. social structure, norms, information sharing, and value system and culture) governance instruments used in supply networks and their influence on quality.

This research is qualitative-exploratory in nature, involving semi-structured interviews with 20 managers from three essential layers in the dairy industry's supply chain: companies that supply essential inputs to milk producers; milk producers; and milk cooperatives.

Analysis of the generated data show that formal governance instruments have a strong and/or weak influence on products' and operations' quality in the dairy industry context; informal instruments have a strong and/or weak influence on quality, as a counterpart to formal instruments; and the integration of verified governance instruments positively influences the quality of products and operations.

This paper offers several managerial and practical implications. The first is to encourage suppliers of primary inputs and milk producers to invest in the formal structure, primarily in formal contracts with each other. The second implication suggests the relevance of creating different training and qualification courses with members from all organizational levels. Third, there is a need for cooperatives, encompassing all industries, to consider several informal instruments, complementary to contracts and standards currently used for processes.

Governance instruments can lead to desired supply chain outcomes, including those related to quality. Although previous supply chain studies have investigated the relationship between governance instruments and the supply chain, and quality management and the supply chain, studies on governance instruments' influence on supply chain quality are limited.

The Greek dairy industry, with more than 1,000 companies, is extremely dynamic and developing, and it is presumably attractive to some investors, usually big foreign companies. The question of great interest is which cluster of the industry should they compete with, and what changes will that potential entrance cause to the industry. Uses the strategic group theory to cluster firms in this industry into groups, as a first approach to investigate this industry. That provides a better approach of understanding and evaluating the industry’s potential as well as useful information of the current situation and the future changes.

The chapter will document the Canadian reaction, as reflected in the demand of New Zealand, that Canada fundamentally alters its dairy supply management system in order to participate in the Trans-Pacific Partnership negotiations. The Canadian government has resolutely refused to do so, supported wholeheartedly by dairy farmers throughout the country. This is in part because of the effect such an action would have on rural spaces and the debilitating result it would have on Canadian dairy production. As well, the chapter will address the issue of the cost of dairy products in New Zealand as compared with Canada. Part of this analysis will focus on the role of supermarkets in determining the price structure of milk in both Canada and New Zealand. Finally, the chapter will offer an examination of the New Zealand system as represented by Fonterra and the Canadian system as epitomized by dairy supply management.

The global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology.

This study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power.

This research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption.

This research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM.

This paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges.

In Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India.

To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

The purpose of this paper is to present an econometric model to empirically analyze the influence of production patterns and transaction style on raw milk quality. More specifically, the paper examines the effects of these institutions on both nutrition and safety aspects of raw milk quality.

Using data collected from 396 households in Inner Mongolia, this paper adopts a multiple linear regression model (OLS/FGLS) and a zero-inflated Poisson regression model to test two hypotheses proposed according to theory and descriptive analysis.

The empirical results indicate that both production pattern and transaction style significantly affect raw milk quality. Production pattern has a more significant effect on raw milk nutrition, while transaction style has a more significant effect on raw milk safety.

Current government policies focus on reducing household production and regulating private milk collection stations. From a comprehensive quality perspective, these policies are not effective in that they cannot guarantee raw milk safety and have little effect on improving raw milk nutrition. Alternatively, promoting dairy farmers' specialized cooperatives may be a more effective policy measure.

In contrast to other studies, this paper adopts a comprehensive quality perspective that examines both nutritional and safety characteristics rather than focusing on any single quality indicator, separately analyzing the factors influencing raw milk nutrition and raw milk safety. Therefore, the conclusion of this paper provides a new perspective in addressing the current raw milk quality problems facing China's dairy industry.