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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.

This study aims to explore farmers’ perceptions of environmental impacts of dairying and their practices towards implementing environmental management accounting (EMA) techniques.

Semi-structured interviews were held with five dairy farmers in the South Island of New Zealand (NZ).

Dairy farmers perceive environmental sustainability in dairying as being able to feed people while protecting the environment so that future generations can also enjoy the natural world. Recognising the need to alter their practices to reduce environmental damage they have produced, dairy farmers use some EMA techniques, but the primary motivation is compliance with government regulations. Other motivations for using EMA techniques are high economic returns, maintaining their reputation and self-satisfaction. Barriers to implementing EMA techniques are primarily due to lack of clarity and feasibility of regulations, coercion and inadequate communication by regulators and high compliance costs.

The findings contribute to the current EMA literature by providing a better understanding of EMA practices of dairy farmers in NZ, barriers to implementing EMA and how those barriers could be reduced. It may also help NZ central and local government in developing environmental strategies and policies. Furthermore, this research is expected to help people in the dairy industry to find ways to educate farmers about how the measures that are required can help them to reduce both the environmental impacts and the costs of dairying, thus contributing to sustainable development globally.

The purpose of this paper is to analyse the association between farm/farmer characteristics and unsubsidized farm insurance premium expenditure in Ireland. The distribution of farm insurance expenditures is wide, and it is important to understand the extent to which individual factors influence demand for different levels of insurance premium.

The quantile regression approach and farm accountancy data from the Teagasc National Farm Survey are used to model the association between farm/farmer characteristics and farm insurance demand in Ireland.

Asset values (livestock, buildings and machinery) are positively associated with total insurance expenditure. Both forestry area and crop area are significantly associated with farm insurance expenditure with a stronger influence on the middle and upper part of the distribution. The interaction between farm income and farmer age is positively associated with insurance expenditure pointing to the importance of farm income protection.

The research is mainly concerned with insuring against substantive risks, which are capable of threatening the asset base and continuation of the farm business. Future research can integrate questions in relation to farm safety and farmer health with research on the economic survival of the farm business.

Farmers in Ireland adopt unsubsidized farm insurance as a risk management tool. This situation is relevant to other EU member states including Belgium, Denmark, Germany and Sweden. The findings can be used to inform stakeholders and policymakers about the relative impact of different factors on insurance expenditure.

Previous research has typically focused on the linear relationship between farm/farmer characteristics and insurance demand without accounting for variability across the size distribution. This research is based on the quantile regression approach where the association between farm/farmer characteristics and farm insurance expenditure can be assessed at different points of the distribution.

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 study acclaims the social entrepreneurship based on cow rearing experiential tourism in Himachal Pradesh. This study aims to illustrate the role of indigenous cows in the Indian society, especially in the Northern Mountain regions by taking Kangra district of Himachal Pradesh as an exemplar. This study highlights the relevance of experiential tourism that elucidates on the basis of cow tourism pertaining to health, mental and spiritual rejuvenation. Lastly, the paper is an attempt to integrate social entrepreneurship and cow tourism highlighting the relevance of experiential economy in empowering the local community.

The case study elucidates on the whence of Swadeshi Kamdhenu Gaushala (SKG), an initiative of Mr Rishi Dogra and Mr Rajesh Dogra, their immaculate micro-management and its benefits to the local community. It highlights how SKG is uplifting the socio-economic standards of the local villagers and providing a distinctive learning experience of indigenous knowledge to visitors. This study is qualitative in nature that uses narrative analysis of secondary data to recognise the importance of indigenous Indian cows, and case study analysis of interviews of SKG proprietors to understand the micro-management, production of organic products and community engagement in their social entrepreneurship.

The SKG is not only helping the local community in their livelihood but also creating value and positioning to the place on the tourist map. This study sheds some light on the importance of cow products in sectors such as agriculture, green energy and for human health and nutrition. The study also crystallizes the challenges faced by the cow rearers, at last the paper sorted out the benefits of cow tourism and how it can result in community empowerment and development.

The case study on SKG helps us in understanding the importance of social entrepreneurs in community empowerment and also the intervention of tourism in the sector that can bring new and different vertical to the tourism industry with experiential learning of the tourist, which results in knowledge sharing about the benefits of Indian cows and helps in creating and placing such destinations on tourist maps. This study attempts towards contributing to the existing knowledge, highlighting the benefits of social entrepreneurship and cow tourism for the society in general and local community in particular.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The purpose is to analyse the nutritional adequacy and carbon footprint of intermediated meals provided to preschool children and primary-level students in a Portuguese municipality.

An observational cross-sectional study was conducted with a convenience sampling consisting of school snacks from a Portuguese municipality. The nutritional assessment used food labels and a Portuguese food composition table. The literature review for carbon footprint assessment was conducted by searching for the products under analysis or similar ones.

The results showed that 80% of snacks have a higher energy value than recommended. The majority of options are below recommendations for protein and fat and above recommendations for carbohydrates. The intermediated meals with more dairy products in composition have the highest carbon footprint. The carbon footprint included the packaging of the products, and it wasn't possible to determine the influence of non-food products.

This study has limitations in the fact that we do not know the carbon footprint of Portuguese products and we had to compare them with others, from different countries, with possibly different types of production.

Intermediate meals are inadequate, and the carbon footprint is higher when the intermediated meals include products of animal origin – the reason why the composition of intermediated meals should be redesigned considering the achievement of these targets.

The promotion of intermediated meals that promote the Mediterranean eating pattern contributes to health and well-being and is a vehicle for nutrition education and healthy food consumption in schools.

Many studies have been conducted to analyse the carbon footprint and environmental impact of school meals, but commonly lunch is the meal evaluated and the assessment of intermediated meals' impact is an open field.

Micro-, small-, and medium-sized enterprise (MSME) sectors have a strong influence on the Egyptian economy. Yet, effective formulation of integrated cluster along the value chain can lead MSMEs to become international actors in export-oriented activities. An Agro-Industrial Park is an integrated cluster taking into consideration synergetic agglomeration of agribusiness MSMEs assisting in decreasing deprivation of rural territories. This research aims to present the needs of agriculture MSMEs in Egypt, to describe challenges faced by this specific sector, and to set guidelines for a business model integrating small farmers and producers into an integrated agribusiness cluster. The researcher followed purposive/nonprobability sampling technique of 100 MSMEs research participants. A combination of questionnaires and open-ended interviews were the research instruments of choice along with secondary data. This research focused on agribusiness only and specifically MSMEs in Egypt. There is no agribusiness-integrated cluster in Egypt, even though the agricultural land increased significantly in the past 5 years, leading us to believe that it is imperative to develop agribusiness-integrated clusters in the coming few years.

Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.

This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.

The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.

Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.

This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.

This study examined the effects of adopting dairy feed technology bundles on the milk production of smallholder dairy farmers.

The study was based on Multinomial Endogenous Switching Regression (MESR) to estimate the effects of the adoption of three feed technology bundles on milk production using data collected from 518 dairy farm households in West Java, Indonesia.

The findings indicated that adopting technology bundles had positive and robust effects on milk production, with gradual positive effects between non-adoption and the adoption of different bundles of technologies.

This study focused on the association between the adoption of feed technology bundles and milk production. However, further analysis of the causal links between the adoption of feed technologies and milk production as well as the inclusion of other outcomes in the analysis, such as production costs and risk mitigation, are required.

Most of the literature on agricultural technology adoption focuses on the adoption of individual technologies, crop farming and conservation practices. Therefore, this study examined the effects of the adoption of dairy feed technology bundles.