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The inclinations to take measured risks and to be market driven are just two characteristics common to those companies that have achieved the most success in commercializing new technology.

The number of options for Research and Development (R&D) and technology development are growing. For many American companies their investment in this area is their single most important investment. Therefore it is essential that they explore all options for technology development to get the best return for their investment. It is important that companies look beyond their own facilities and staff in their quest for the new technology they will need to keep them out in front.

Recent accounting research using data envelopment analysis (DEA) measures firm performance using accounting measures from annual reports, which are readily available from electronic databases (e.g. Demerjian et al., 2013; Schwab, 2022). This approach differs from conventional DEA studies that analyse productivity and use internal data about physical quantities of production inputs and outputs. Using accounting measures instead of physical measures presents challenges as accounting measures aggregate physical quantities using unknown but fluctuating prices. This raises the issue of what these DEA models measure. This study aims to examine how price variability influences DEA results when measuring firm performance and identifies implications for future accounting research.

This study uses a Cobb–Douglas function to simulate physical data for input and output quantities, which are then priced to form accounting measures that incorporate different levels of price variability. These simulated accounting data are used to estimate DEA results. The results using physical data and accounting data are compared to identify the impact of increasing levels of price variation and sample size on the comparability of DEA results.

The study confirms the theoretical argument that accounting measures can be used in DEA to measure productivity when prices are identical across a sample of firms. Moreover, where price variability is low, large samples can also reliably estimate productivity when using accounting measures. This measure of productivity fundamentally underpins financial performance and provides a new dimension of firm performance that can be measured by accounting measures. However, where price variability is high, DEA using accounting measures cannot estimate productivity and can only be used for benchmarking financial performance. In this case, DEA provides an alternative measure for financial performance, which incorporates multiple dimensions and can extend traditional financial analysis approaches by providing a more comprehensive measure.

Despite calls for investigation (Camanho et al., 2024; Färe et al., 2017; Zelenyuk, 2020), evidence has been scarce regarding the impact of price variability when using accounting measures in DEA. Understanding this impact is key to understanding the nature of DEA results produced using accounting measures, as this can affect the interpretation and use of those results. This study is the first to focus on the impact of price variability on accounting measures within DEA and suggests new avenues for accounting research using this performance measurement method.

The purpose of this paper is to examine the suitability of free carbon calculators aimed at the agricultural industry, for use in greenhouse gas (GHG) emission benchmarking, using the European dairy industry as an example.

Carbon calculators which were claimed to be applicable to European dairy farms were identified and tested using six production scenarios based on data from real European farms supplemented using published literature. The resulting GHG emission estimates, together with estimates apportioned using three functional units, were then compared to determine the robustness of the benchmarking results.

It was found that although there was a degree of agreement between the seven identified carbon calculators in terms of benchmarking total farm emissions, once a suitable functional unit was applied little agreement remained. Tools often ranked farms in different orders, thereby calling into question the robustness of benchmarking in the studied sector.

The scenario-based approach taken has identified issues liable to result in a lack of benchmarking robustness within this sector; however, there remains considerable scope to evaluate these findings in the field, both within this sector and others in the agricultural industry.

The results suggest that there are significant hurdles to overcome if GHG emission benchmarking is to aid in driving forward the environmental performance of the dairy industry. In addition, eco-labelling foods based on GHG benchmarking may be of questionable value.

At a time when environmental benchmarking is of increasing importance, this paper seeks to evaluate its applicability to sectors in which there is considerable scope for variation in the results obtained.

This chapter opens the second part of the Volume, focusing on the small farms' role and dynamics within the evolving food system. Assessing small farmers' actual and potential contribution to the change towards a sustainable food and nutrition security requires a deep understanding of their strategic decision-making processes. These processes take place in a context highly conditioned by internal and external conditions, including the complex relations between farm and household, which are mapped and described. Building on an adaptation of Porter's model (Porter, 1990), the chapter investigates how farmers, given those conditions, define their strategies (in particular their innovation strategies) aimed at economic and financial sustainability through a multidisciplinary analysis of scientific literature. Internal conditions are identified in the light of the Agricultural Household Model (Singh & Subramanian, 1986) which emphasizes how family farming strategies aim at combining business-related objectives, and family welfare. Then, a comprehensive set of external conditions is identified and then grouped within eight categories: ‘Factors’, ‘Demand’, ‘Finance and Risk’, ‘Regulation and Policy’, ‘Technological’, ‘Ecological’, ‘Socio-institutional’ and ‘Socio-demographic’. Similarly, six types of strategies are identified: ‘Agro-industrial competitiveness’, ‘Blurring farm borders’, ‘Rural development’, ‘Risk management’, ‘Political support’ and ‘Coping with farming decline’.

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.

If child custody decisions are based on erroneous beliefs, family courts may not be acting in the best interests of children. This study examined family court professionals' beliefs about family violence. Respondents (N = 410) of diverse professions, including child custody mediators, evaluators, and therapists, family law attorneys and judges, victim advocates and university students, completed a 10‐item multiple‐choice quiz. Results revealed low rates of correct responding, with respondents correctly answering approximately three out of 10 items on average, based on current research in the field. Overall, response rates were highly consistent with the discredited patriarchal paradigm. Shelter workers and victim advocates had the lowest average score, and men were found to have slightly higher scores than women. More troubling, students' scores were not significantly lower than those of family court professionals. Implications are discussed with respect to decision‐making in the context of child custody disputes.

Since the 1950s four distinct inductive research traditions developed in California, following the migrations of Herbert Blumer, Erving Goffman, Anselm Strauss, Harold Garfinkel, Jack Douglas, and others. Each of these traditions has made intellectual, organizational, service, pedagogical, financial, and personal contributions to the growth and development of symbolic interaction.

The purpose of this paper is to estimate and analyse the technical efficiency (TE) component of productivity for a sample of winegrowers from the Douro Demarcated Region in Portugal.

The data were collected through face-to-face surveys and includes a sample of 110 farmers’ vineyards with specific input-output information and other data about production systems during the year of 2017. The authors use a two-stage data envelopment analysis using bootstrap techniques to obtain TE scores in the farmers’ vineyards and to examine the determinants of its efficiency.

The results show that some farmers’ vineyards have a low efficiency level and that there are essential determinants of the production system, which can influence its efficiency. This suggests considerable opportunities for improvement of wine grape productivity through better use of available resources considering the state of technology.

This work has overcome the lack of data in the farmers’ vineyards, the lack of efficiency studies in the region and also allowed to evaluate the production systems and to assess their impact on efficiency.