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The purpose of this paper is to verify if, in the dairy business ecosystem (dairy farmers, dairy cooperatives, government, research agencies, consultants and financial institutions) perspective, the dairy production barriers presented by Bonamigo et al. (2016b) can be mitigated through the dairy production key factors indicated in the literature.

To achieve the proposed goal of this study, the methodology used for the study comprises three stages: exploratory search in the literature to identify barriers and drivers of dairy production, data collection and statistical model. For the first stage, the authors conducted exploratory research in the literature, to better understand the dairy production ecosystem and to find arguments that characterize the barriers and drivers of this activity. In the second stage, a structured questionnaire with 13 closed-ended questions in a single block, with ordinal responses, following the suggestion of Likert (1932), was developed and applied to the dairy production ecosystem players of Santa Catarina, Brazil. A total of 305 responses suitable for analysis based, that were analyzed through an exploratory factorial analysis and modeling of structural equations via partial least squares, resulting in the Statistical model.

Based on the analyses results, the authors verified that there is an inverse association between the characteristics of the barriers and the dairy production key factors. In this sense, the authors can confirm that the increase of the loads in the dairy production key factors, reduce loads of the milk production barriers. Based on the results of this test, new theoretical and practical insights can be identified to develop new studies with the aim of boosting the dairy sector development as well as providing support in the decision making of the dairy system players.

This study may not have enabled a complete coverage of all existing peer-reviewed articles in the field of dairy production. It seems reasonable to assume that the review process covered a significant proportion of studies available.

It is the first study that compares identifies barriers and key factors of dairy production in Santa Catarina using as an analytical lens the business ecosystem.

Food supply chain (FSC) in Greece is dominated by small and medium-sized enterprises (SMEs), who face several challenges in adopting green practices. The purpose of this paper is to identify the key drivers and barriers influencing the environmental performance of SMEs within the Greek dairy supply chain (SC).

Descriptive research methodology attempts to prioritize the drivers and barriers for improving the environmental sustainability performance. Analytical hierarchy process and sensitivity analysis are used to understand the complex nature of the influencing factors.

The analysis identifies five barriers and six drivers for the implementation of green practices within the dairy SC. While external drivers significantly influence the market structure and logistics network, government, competitors and customers are the driving factors for improving environmental performance.

The study contributes to filling the literature gap on key factors influencing the implementation of green practices within the FSC. The identified influential factors will contribute toward building a framework for improving sustainability performance within the Greek dairy SC.

The study is expected to benefit the Greek and European SMEs by driving their environmental practices within the perishable SC network.

The paper provides directions for researchers, practitioners and policy makers in understanding the challenges for implementing green practices in the dairy SC. The holistic approach followed in this paper is a building block for a conceptual framework on implementing environmental sustainability within the FSC. Apart from contributing to the current literature by extending the research horizon to SMEs’ green adoption capability, this study also provides better understanding of the pivotal role of internal and external key factors in influencing sustainability performance.

The purpose of this paper is to examine the rise in crossbred cow numbers in the US dairy herd. Methods used look at well managed herds to see if crossbreeding provides a management tool that producers are using to maintain profitability.

The authors estimate a Translog stochastic production frontier (SPF) for US dairy farms to examine the competitiveness of crossbred and non-crossbred dairy herds by system and region.

The bottom-line conclusion is that WM or highly efficient crossbred herds solidly compete on a financial basis with larger WM Western Holstein herds, the most technically efficient managed group, based on the SPF results in the authors’ study. The study finds that net return on assets for crossbred herds are not different from Western Holstein herds and that there is no significant difference in amount of milk per cow produced annually.

Because of a need to unmask the advantages of crossbreeding as a technology it was necessary to separate WM herds from poorly managed herds. That was done by frontier estimates that robustly ranked operation and corrected for endogeneity, tested for selectivity bias, and incorporated the NASS survey design.

For the first time, the 2010 Dairy Cost and Returns questionnaire version of the Agricultural Resource Management Survey (Dairy CAR) design allows researchers to expand survey observations to represent the vast majority of the US dairy farm population and to sort dairy farms into crossbred/non-crossbred herds.

The purpose of this article is to identify the drivers for, and barriers to, the adoption of assurance systems in a range of agri‐food value chains that will allow the design of better, more appropriate‐for‐the‐task assurance systems that are more likely to be fully utilised by value chain members.

Semi‐structured interviews were used to collect a snapshot of the knowledge, attitudes, skills and aspirations (KASA) of value‐chain members with regard to assurance systems in fruit (cherries), seafood (mussels) and red meat (lamb). Responses were grouped by KASA characteristic for qualitative analysis. The nature of the dairy industry necessitated the use of a desktop review of the food‐safety assurance system.

The actual drivers for, and barriers to, adoption varied with the industry studied but included the requirements of domestic and export market customers, realistic appreciation of risk, mandatory schemes, the influence of other value chain members, financial incentives and external influences. The major barrier to the adoption of assurance systems was the perception that the costs of such an assurance system outweigh its benefits.

This study was purely qualitative and covered only one value chain within each of three industries with a desktop review in a fourth industry.

A suite of drivers that includes financial incentives results in more effective adoption of assurance systems than a single driver such as market access.

The observations could lead to a series of design principles for the development and deployment of agri‐food assurance systems.

The purpose of this paper is to empirically test the dairy production barriers: lack of cooperation between the chain actors, milk quality deficiencies, rural exodus and, productivity limitations in southern Brazil, based on Santa Catarina’s dairy production ecosystem players perceptions.

From inquiry result analysis with 305 dairy sector experts, the authors performed statistical tests using the technique of factorial analysis and confirmatory factorial analysis to confirm and/or refute the dairy production barriers presented by Bonamigo et al. (2016b).

The results confirmed the presence of the barriers presented by Bonamigo et al. (2016b). The barrier lack of cooperation between the chain actors is presented as the biggest obstacle in the sector, according to the interviewees. The authors also found that rural exodus is the barrier with the smallest impact on the dairy sector development in relation to other barriers presented by Bonamigo et al. (2016b). The confirmation of these barriers in practice allows developing new studies to eliminate and/or mitigate these barriers of the dairy sector. Furthermore, the study might shed some light on dairy production activities and help improve management skills.

This study does not cover all the players that make up the dairy production ecosystem. It is limited only to the main players that are inserted in this sector. The authors observed the lack of data characterizing the dairy production system in Santa Catarina.

This study presents theoretical and practical contribution. By the confirmation that these barriers are present in the field, it is possible to direct new studies that seek to mitigate them and results in dairy production improvements. As for the practical contribution, the confirmation of those barriers can serve as a basis for the dairy sector decision-making actors, such as government, research institutions, and extension, producers, cooperatives, among others, and assist them in developing strategic actions that concern a cooperative way to develop the whole sector.

In every industry there are resources. Some are moving, others more fixed; some are technical, others social. People working with the resources, for example, as buyers or sellers, or users or producers, may not make much notice of them. A product sells. A facility functions. The business relationship in which we make our money has “always” been there. However, some times this picture of order is disturbed. A user having purchased a product for decades may “suddenly” say to the producer that s/he does not appreciate the product. And a producer having received an order of a product that s/he thought was well known, may find it impossible to sell it. Such disturbances may be ignored. Or they can be used as a platform for development. In this study we investigate the latter option, theoretically and through real world data. Concerning theory we draw on the industrial network approach. We see industrial actors as part of (industrial) networks. In their activities actors use and produce resources. Moreover, the actors interact − bilaterally and multilaterally. This leads to development of resources and networks. Through “thick” descriptions of two cases we illustrate and try to understand the interactive character of resource development and how actors do business on features of resources. The cases are about a certain type of resource, a product − goat milk. The main message to industrial actors is that they should pay attention to that products can be co-created. Successful co-creation of products, moreover, may require development also of business relationships and their connections (“networking”).

The purpose of this paper is to explore the key performance indicators (PIs) that serve as a decision support tool in case of dairy supply chain practices and to analyze their interactions in the context of Indian dairy industry sector. A total of 11 PIs have been identified through the literature review and the opinions of an expert team consisting of managerial and technical experts from dairy industry and academics.

A solution methodology based on the interpretive structure modeling (ISM) technique is used to analyze the interactions among PIs and to propose a structural model. The developed model not only helps in understanding the contextual relationship among the PIs, but also in determining their interdependence to assess the supply chain performance in dairy industry. Further, the importance of PIs has been determined based on their driving and dependence power by using MICMAC analysis.

The ISM-based model suggests four PIs at first level, three PIs at second level, one PI at third level as well as one PI at fourth level and two PIs at fifth level. Model allocates to the effective information technology, brand management, responsiveness in shipment and accuracy and a control over wastages as the key PIs in the dairy industry sector. The effective traceability systems, cold chain infrastructure, quality management and the support for technological innovations are the next major PIs. There exists no autonomous PI in MICMAC analysis which proves the importance of identified PIs in the case study.

The proposed model is an attempt to capture the dynamics of milk processing sector and to incorporate all relevant constraints related to internal and external environments that would significantly improve the supply chain performance in the dairy industry.

The model developed in this study has been tested in the cooperative milk processing units based in India and also discussed with the experts from academics. This work may help practitioners, regulators and dairy industry professionals to focus their efforts toward achieving high performance by the effective implementation of the identified PIs.

In this study, 11 PIs are considered. Interactions among PIs are evaluated with the help of the ISM matrix. Out of the 11 PIs, six demonstrate both strong driving and dependence power as explained in the MICMAC analysis.

The purpose of this paper is to compare technical efficiency and metatechnology ratios (MTR) in three production systems confronted with different technological and resource endowments in Bangladesh to identify the suitable production systems for increasing productivity.

The primary data collected by authors from 180 dairy farmers were sampled and modeled in a stochastic metafrontier framework due to its ability to estimate and compare the efficiency of firms among various groups with possibly different group-specific technologies and heterogeneous production environments.

The empirical results show that farms from intensive system were closer to their production frontier than extensive and traditional system. Regarding productivity differences among systems, the MTR is by far highest for intensive, indicating the technological advantage of this system over others two systems. The estimation of farm-specific inefficiency model revealed that farmers’ access to extension and credit services are assumed to be significant determinants in reducing inefficiency.

This study concludes that the ability of the farmers to increase productivity vary depending on the production systems due to variation in resource endowments and access to various inputs and support services. Thus, improving productivity depends on effective policy design on harmonizing access to resources and delivery of extension and credit services.

The empirical analysis of data representing different production endowments by stochastic metafrontier make it possible to identify the efficiency level as well as technology gap, thus, ways to identify the possible policy options reducing those gaps and improving productivity.

This paper aims to examine the competitiveness trends and rankings of the Irish dairy sector at the farm and trade levels, relative to selected European Union (EU) Member States, in the context of the removal of the EU milk quota in 2015.

Competitiveness indicators including partial productivity measures and accountancy-based indicators were used for farm competitiveness, and net export market share and normalised revealed comparative advantage (NRCA) were used for export competitiveness.

Amongst the countries examined, Ireland had the highest growth in partial productivity indicators and was ranked first with the lowest total costs and cash costs per kg of milk solids post-quota. However, the total economic cost sub-components showed that Irish dairy farmers had high opportunity costs for owned land and labour. While Irish dairy products such as butter and powders have demonstrated growth potential in competitiveness post-quota with Irish butter and whey ranked in top three relative to other countries, other products, i.e. cheese and liquid milk have declined in competitiveness according to key export competitiveness indicators used.

The challenge for Irish dairy farmers is how to mitigate relatively high land and labour costs, which can limit farm competitiveness in the long run. The key players in the Irish dairy industry can now better position themselves in the global dairy market, recognizing the competitiveness dynamics of the different dairy products and their competitors. Policy implications and further areas of research have been identified to help improve the overall competitiveness position. It is surprising that Irish butter is a leader in the EU, yet not much research has been done to understand the market dynamics of this sector.

To the best of the authors’ knowledge, this study is the first of its kind to use both farm and export competitiveness measures to analyse the Irish dairy industry relative to other countries in the context of quota abolition. Unlike previous studies on dairy export competitiveness, this study has disaggregated the processed dairy products, which allowed for the ranking of countries and comparability across countries using NRCA.

This study aims to analyse the components of sustainable business models (SBMs) in the dairy industry, in relation to firm-relevant organisational features (size, ownership structure and production process) and through the lenses of the business model framework and the sustainable value exchange matrix (SVEM). This contribution proposes a taxonomy of emerging SBMs and sustainable value creation in the dairy industry.

This research makes use of a multiple case study approach, with cases selected in collaboration with industry experts. The selected firms are highly committed to sustainability transition. Results are drawn from qualitative data obtained from in-depth interviews and secondary sources. The interpretation phases, initially based on open coding, have been enriched by applying the components of business models (BMs) frameworks and the SVEM, and the analyses have been enhanced through an additional interpretative workshop with experts.

The authors related the BMs characteristics of some typical dairy firms transitioning to sustainability, using SBM components and taxonomies emerging in the literature, based on the formalisation of sustainability practices, the scope of operations, and the degree of integration of the three dimensions of sustainable value. These findings led to the discovery of three types of SBM in this dairy industry, referred to as “Milky Ways”.

This paper contributes to the scant literature on sustainability in dairy firms, highlighting the different paths followed by small and medium-sized enterprises (SMEs), cooperatives and large companies in remoulding their business models towards sustainability and thus achieving sustainable value creation.