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Automated body condition scoring (BCS) through extraction of information from digital images has been demonstrated to be feasible; and commercial technologies are being developed. The primary objective of this research was to identify the factors that influence the potential profitability of investing in an automated BCS system.

An expert opinion survey was conducted to provide estimates for potential improvements associated with technology adoption. A stochastic simulation model of a dairy system, designed to assist dairy producers with investment decisions for precision dairy farming technologies was utilized to perform a net present value (NPV) analysis. Benefits of technology adoption were estimated through assessment of the impact of BCS on the incidence of ketosis, milk fever, and metritis, conception rate at first service, and energy efficiency.

Improvements in reproductive performance had the largest influence on revenues followed by energy efficiency and then by disease reduction. The impact of disease reduction was less than anticipated because the ideal BCS indicated by experts resulted in a simulated increase in the proportion of cows with BCS at calving 3.50. The estimates for disease risks and conception rates, obtained from literature, however, suggested that this increase would result in increased disease incidence. Stochastic variables that had the most influence on NPV were: variable cost increases after technology adoption; the odds ratios for ketosis and milk fever incidence and conception rates at first service associated with varying BCS ranges; uncertainty of the impact of ketosis, milk fever, and metritis on days open, unrealized milk, veterinary costs, labor, and discarded milk; and the change in the percentage of cows with BCS at calving 3.25 before and after technology adoption. The deterministic inputs impacting NPV were herd size, management level, and level of milk production. Investment in this technology may be profitable but results were very herd‐specific. A simulation modeling a deterministic 25 percent decrease in the percentage of cows with BCS at calving ≤3.25 demonstrated a positive NPV in 86.6 percent of 1,000 iterations.

This investment decision can be analyzed with input of herd‐specific values using this model.

Automatic milking systems (AMSs) are a relatively new technology characterized by uncertainty and irreversibility. The choice to invest in such a system is analyzed in a real options framework. Alternative financing arrangements, depreciation methods, and other factors are investigated to determine their influence on the optimal investment decision. The results suggest that farm capital structure, loan term, and depreciation method have little impact on the investment decision. The primary determinant in the AMS technology adoption decision appears to be whether the AMS will last longer than the existing parlor.

This study explains Indonesian consumers' choice of poultry meat attributes and the willingness to pay (WTP) for these attributes using a discrete choice experiment.

The survey was conducted for the traditional and modern channels and involved a sample of 440 respondents in the Greater Jakarta area. A discrete choice experiment was employed as the study framework and in designing the questionnaire. A multinomial logistic regression analysis was used to evaluate consumers' preference for poultry attributes in modern and traditional channels.

Consumers preferred warm poultry meat, government certification and product information labeling on poultry meat. The WTP for warm poultry meat was the highest, which is indicating that freshness is crucial for consumers to ensure quality. Moreover, consumers had more trust in government certification than private certification for food safety and were willing to pay more for product information labeling on poultry meat.

The government can use the model as a decision support to improve poultry meat quality at sales channels in Indonesia including to close sales channels where sick poultry are sold and thus address food safety concerns caused by the avian influenza outbreak.

This study shows that understanding the WTP for poultry meat attributes enables the government to control the poultry sales channels and stimulates producers to supply the market with a safer poultry meat quality using the price mechanism.

The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user‐friendly, farm‐specific, decision‐making tool for dairy producers or their advisers and technology manufacturers.

The basic deterministic model was created in Microsoft Excel (Microsoft, Seattle, Washington). The @Risk add‐in (Palisade Corporation, Ithaca, New York) for Excel was employed to account for the stochastic nature of key variables within a Monte Carlo simulation. Net present value was the primary metric used to assess the economic profitability of investments. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical US dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. In this paper, the model structure and methodology were described in detail.

Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs.

Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers.

The purpose of this paper was to assess the economic impact of investment in different animal welfare–enhancing flooring solutions in Swedish dairy farming.

The authors developed a bio-economic model and used stochastic partial budgeting approach to simulate the economic consequences of enhancing solid and slatted concrete floors with soft rubber covering.

The findings highlight that keeping herds on solid and slatted concrete floor surfaces with soft rubber coverings is a profitable solution, compared with keeping herds on solid and slatted concrete floors without a soft covering. The profit per cow when kept on a solid concrete floor with soft rubber covering increased by 13%–16% depending on the breed.

Promoting farm investments such as improvement in flooring solution, which have both economic and animal welfare incentives, is a potential way of promoting sustainable dairy production. Farmers may make investments in improved floors, resulting in enhanced animal welfare and economic outcomes necessary for sustaining dairy production.

This literature review indicated that the economic impact of investment in specific types of floor improvement solutions, investment costs and financial outcomes have received little attention. This study provides insights needed for a more informed decision-making process when selecting optimal flooring solutions for new and renovated barns that improve both animal welfare and ease the burden on farmers and public financial support.

The aim of this paper is to assess the applicability and impact of private food standards – specifically that of the BRC (British Retail Consortium) – in a European country context, and to classify food companies into groups on the basis of their different perceptions regarding the Global Standard for Food safety impacts.

The research is developed in two stages: a qualitative investigation based on in-depth interviews with quality managers (QMs); a quantitative investigation with a structured questionnaire: with response from 192 food processors in Italy, selected through a probabilistic random sampling method. Data were elaborated with descriptive statistical techniques and subsequently with multivariate analysis (factor and cluster analysis).

QMs agree with most of the assumptions with regard to the impact elements of the BRC food standard. Some characteristics, such as geographic location, size, and type of processing and adoption of ISO 9001, seem to elicit different perceptions between the companies. Through factor analysis, eight factors were extracted; and subsequently, through cluster analysis applied to the factors, five different groups of companies are identified.

The adoption of private food standards is both useful and comprehensible for food operators. However, BRC is a minimum standard and a base level for food suppliers; it cannot wholly substitute a specific retailer's dedicated second-party audit. Findings could be used by the subjects of the certification process to determine ideal marketing strategies.

This paper provides a statistically significant description of the impact of private food standards (via the important BRC standard) in one of the most important European markets.

The aim of this study is to discover the critical success factors (CSFs) for the Halal supply chain management because this area is gaining recognition. Plus, the aim is to use the CSFs for future research.

The study is based on the application of CSFs on the Halal supply chain. A comprehensive literature review is undertaken to discover the CSFs of conventional supply chain and to apply it to the Halal supply chain.

Government support, transportation planning, information technology, human resource management, collaborative relationship, Halal certification and Halal traceability are the CSFs for the Halal supply chain.

This study only discusses the CSFs related to the Halal supply chain and ignoring other forms of Halal businesses. This study only concerns on English literatures and omit other languages. The study lacks empirical evidence and future research should be done to test the CSFs relevancy.

This study addresses stakeholders of the Halal supply chain CSFs, which have not been fully understand and appreciated.

CSFs concept has never been attempted on the Halal supply chain. Therefore, this study appraises the concept of CSFs and adds value to the knowledge on the Halal supply chain.

This paper aims to increase our understanding of perspectives on food traceability in four supply chain risk management (SCRM) approaches to ensure food safety. The occurrence of food safety failures has led to increased attention on food traceability as a means of identifying the causes of deficiencies in supply chains.

This paper presents a literature review and synthesizes the broader domain of food traceability by analyzing perspectives based on SCRM approaches. In all, 129 published papers were selected and evaluated using content analysis.

A framework of SCRM approaches on food traceability is presented. Eight perspectives on food traceability are identified and grouped according to four SCRM approaches: food supply chain complexity and unique identification of goods (logistics management); transparency and interoperability (information management); in-house production and outsourcing (production management); and food quality and safety requirements and the monitoring of food characteristics (quality management).

The findings provide an in-depth understanding and research suggestions for the management of traceability to ensure food safety in food supply chains. Conclusions are drawn from secondary sources, thus excluding empirical evaluation.

The implementation of food traceability can result in changes to existing management systems. This paper addresses the perspectives and management challenges that can influence the implication of food traceability to ensure food safety.

Perspectives on food traceability according to SCRM approaches are presented. Food traceability is analyzed using the philosophy of scientific framework and suggestions for further research are offered.

This systematic literature review integrates the findings of existing studies regarding technical efficiency (TE) in dairy farms. The purpose of this paper is to offer a research framework that assembles TE descriptors, a classification of previous literature that provides the basis for the synthesis and research agenda.

This paper systematically reviews 86 survey research studies using rigorous and reproducible procedures. The review is applied to published survey research.

The framework relates context, inputs, outputs and metrics of TE. There is no agreement among the authors on the context and determinants of TE. The main determinants of TE are geographical location, farm size, investments in veterinary care, feeding and milking practice, TE model estimation techniques, public policy, and management-related variables. This paper offers ten propositions for future research on the controversial results on the determinants of TE. The authors also explore the reasons for the discrepant results based on the Debreu-Farrell’s definition of TE, the contingency theory and the resource-based view of the firm, elucidating the literature and serving as a basis for future investigation. Implications for dairy farmers and researchers close the review.

Meta-analysis and meta-regression studies were long at the forefront of reviews in the TE of dairy farms. This paper offers a novel qualitative research synthesis with frameworks and the classification of previous literature and a research agenda, which provides a new and different perspective for analysis, by innovating over the available quantitative procedures to combine statistical results.

The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE).

The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed.

The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers.

This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement.