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Given the increasing complexity of the agro-food sector, the analysis of financial performance alone may not be sufficient to assess the economic sustainability of farmers. This paper presents a practical method to measure the performance of farm businesses by combining the Balanced Scorecard (BSC) theoretical framework and Importance–Performance Analysis (IPA). The proposed model of Business Performance Indicators (BPI) measurement allows identification and validation of the indicators that consistently measure the latent dimension of the BSC framework while allowing identification Buin of the BPI areas where farm businesses need to concentrate their efforts to assure economic sustainability. The method was applied to small ruminant farm businesses across Europe through visits and interviews. The case study application showed that the model could help measure the performance of small farms while allowing detection of the areas of fragility and intervention. The case study results showed that finance and internal business management were the most relevant farmers’ weaknesses, alongside low priority given to innovation. In conclusion, to prevent the potential long-term decline of the sector, the study provided evidence for policy changes to support the farmers’ innovation potential and a higher level of integration in the supply chain.
Danilo Gambelli; Francesco Solfanelli; Stefano Orsini; Raffaele Zanoli. Measuring the Economic Performance of Small Ruminant Farms Using Balanced Scorecard and Importance-Performance Analysis: A European Case Study. Sustainability 2021, 13, 3321 .
AMA StyleDanilo Gambelli, Francesco Solfanelli, Stefano Orsini, Raffaele Zanoli. Measuring the Economic Performance of Small Ruminant Farms Using Balanced Scorecard and Importance-Performance Analysis: A European Case Study. Sustainability. 2021; 13 (6):3321.
Chicago/Turabian StyleDanilo Gambelli; Francesco Solfanelli; Stefano Orsini; Raffaele Zanoli. 2021. "Measuring the Economic Performance of Small Ruminant Farms Using Balanced Scorecard and Importance-Performance Analysis: A European Case Study." Sustainability 13, no. 6: 3321.
The aim of this study was to analyse the economic aspects related to organic aquaculture through a systematic review of the scientific literature. Production from organic aquaculture has grown rapidly over the last few years, although it remains at low volumes worldwide. We followed the ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses’ procedures for literature selection, and performed a qualitative review of the selected studies. The review is based on three research questions: “What are the main factors that affect the socio-economic development of organic aquaculture?“; “Is there evidence for better economic performance of organic aquaculture with respect to conventional aquaculture?“; “Do consumers show tangible preference for organically farmed seafood?” The main results show that profitability in organic aquaculture is not guaranteed for all aquaculture species, and the feed and fixed costs can be an issue if they are not balanced by adequate price premiums. Lack of homogenisation of organic standards for aquaculture is considered to be the main issue. Socio-economic aspects of organic aquaculture are particularly relevant in developing countries, where this farming practice can contribute to an improved livelihood and can integrate effectively with local farming practices. Consumers show a generally positive attitude towards organic seafood, although other aspects such as local origin might represent more relevant attributes. Consumer knowledge of organic aquaculture standards is also limited.
Danilo Gambelli; Daniela Vairo; Francesco Solfanelli; Raffaele Zanoli. Economic performance of organic aquaculture: A systematic review. Marine Policy 2019, 108, 103542 .
AMA StyleDanilo Gambelli, Daniela Vairo, Francesco Solfanelli, Raffaele Zanoli. Economic performance of organic aquaculture: A systematic review. Marine Policy. 2019; 108 ():103542.
Chicago/Turabian StyleDanilo Gambelli; Daniela Vairo; Francesco Solfanelli; Raffaele Zanoli. 2019. "Economic performance of organic aquaculture: A systematic review." Marine Policy 108, no. : 103542.
The availability of timely and good-quality data on the organic farming sector is a crucial factor for the development of the organic food market. While data on hectares and farms are now widely available in Europe, data on organic yields are still relatively sparsely reported by official statistical sources for most European countries, including Italy. Information on organic yields is crucial to determine the volumes of organic production and supply. Issues such as the potential of organic farming for feeding the world, the understanding of the optimal conditions for conversion and the appropriate policy measures for supporting the organic sector are all dependent on the knowledge of organic productivity. In this study, we show how a statistical method known as multiple imputation can contribute to the improvement of the availability of organic data, through systematic exploitation of data from different sources. We apply the method to estimate missing data on organic fruit crop yields for the central regions of Italy, based on data from official national statistics and expert assessments. The results illustrate the advantages and limitations of such methods for estimating missing data on organic crops.
Francesco Solfanelli; Danilo Gambelli; Daniela Vairo; Raffaele Zanoli. Estimating missing data for organic farming by multiple imputation: the case of organic fruit yields in Italy. Organic Agriculture 2018, 9, 295 -303.
AMA StyleFrancesco Solfanelli, Danilo Gambelli, Daniela Vairo, Raffaele Zanoli. Estimating missing data for organic farming by multiple imputation: the case of organic fruit yields in Italy. Organic Agriculture. 2018; 9 (3):295-303.
Chicago/Turabian StyleFrancesco Solfanelli; Danilo Gambelli; Daniela Vairo; Raffaele Zanoli. 2018. "Estimating missing data for organic farming by multiple imputation: the case of organic fruit yields in Italy." Organic Agriculture 9, no. 3: 295-303.
This paper investigated if the inspection procedures in organic certification may be improved exploiting information that is generally available from the control bodies involved in the certification process. The analysis was based on data from the archives of one of the largest Italian organic control bodies, containing information on operators’ characteristics, and including: risk scores for farmers, inspectors’ characteristics, type of inspection and the outcome of the inspection in terms of the type of non-compliance detected. The analysis considered both irregularities, i.e. mainly formal or bureaucratic non-compliance, and infringements, i.e. more substantial non-compliance. A bivariate probit model with random parameters was used to estimate the likelihood of, presumably correlated, irregularities and infringements, conditional to a set of covariates concerning risk assessment of the operators, inspector’s characteristics, and modalities of the inspections, including the period of the year scheduled for the inspections. The results showed that irregularities and infringements were actually correlated and that there is scope for improving the effectiveness of inspections, particularly using an appropriate timing for inspections and taking samples more frequently during inspections.
Danilo Gambelli; Francesco Solfanelli; Raffaele Zanoli. Improving controls in organic farming by timely inspections: a statistical analysis. Biological Agriculture & Horticulture 2017, 34, 186 -198.
AMA StyleDanilo Gambelli, Francesco Solfanelli, Raffaele Zanoli. Improving controls in organic farming by timely inspections: a statistical analysis. Biological Agriculture & Horticulture. 2017; 34 (3):186-198.
Chicago/Turabian StyleDanilo Gambelli; Francesco Solfanelli; Raffaele Zanoli. 2017. "Improving controls in organic farming by timely inspections: a statistical analysis." Biological Agriculture & Horticulture 34, no. 3: 186-198.
Danilo Gambelli; Francesca Alberti; Francesco Solfanelli; Daniela Vairo; Raffaele Zanoli. Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks. Energy Policy 2017, 103, 165 -178.
AMA StyleDanilo Gambelli, Francesca Alberti, Francesco Solfanelli, Daniela Vairo, Raffaele Zanoli. Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks. Energy Policy. 2017; 103 ():165-178.
Chicago/Turabian StyleDanilo Gambelli; Francesca Alberti; Francesco Solfanelli; Daniela Vairo; Raffaele Zanoli. 2017. "Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks." Energy Policy 103, no. : 165-178.
This paper describes the Italian and German organic certification systems, including the institutions involved and the definitions of non-compliance and sanctions. Although they are both implementations of the same EU regulatory framework, these systems differ in many respects. Case study data from control bodies on non-compliance and sanctions are presented and analysed using binary choice models. This analysis shows that the occurrence of slight non-compliance and greater farm acreage are significant risk factors that explain severe non-compliance in both countries. However, to implement an efficient risk-based inspection system in the future, the data collection process must be improved and extended to examine personal attributes of farmers and operators.\u
Danilo Gambelli; Francesco Solfanelli; Raffaele Zanoli; Alexander Zorn; Christian Lippert; Stephan Dabbert. Non-compliance in organic farming: A cross-country comparison of Italy and Germany. Food Policy 2014, 49, 449 -458.
AMA StyleDanilo Gambelli, Francesco Solfanelli, Raffaele Zanoli, Alexander Zorn, Christian Lippert, Stephan Dabbert. Non-compliance in organic farming: A cross-country comparison of Italy and Germany. Food Policy. 2014; 49 ():449-458.
Chicago/Turabian StyleDanilo Gambelli; Francesco Solfanelli; Raffaele Zanoli; Alexander Zorn; Christian Lippert; Stephan Dabbert. 2014. "Non-compliance in organic farming: A cross-country comparison of Italy and Germany." Food Policy 49, no. : 449-458.
Purpose – The purpose of this paper is to provide an analysis of the risk factors influencing non-compliance in UK organic farming. Design/methodology/approach – The paper uses a formal econometric model of risk analysis to provide empirical evidence on the determinants of non-compliance in organic farming. A panel of data from the archives of the largest control body in the UK for 2007-2009 is used, and specific analyses are performed for two types of non-compliances. A zero inflated count data model is used for the estimation, taking into account the fact that the occurrences of non-compliance are very sparse. Findings – Results show the existence of strong co-dependence of non-compliant behaviours (i.e. the occurrence of major and critical non-compliance increases the probability of occurrence of the minor one; similarly the probability of occurrence of major non-compliance increases when minor non-compliance occur). Besides, livestock production and farm size are relevant risk factors. Research limitations/implications – Albeit highly representative, the findings are based on Soil Association data only and not on all UK organic farms. Practical implications – The paper provides practical indications for control bodies, concerning aspects that could be strengthened for more efficient risk-based inspections. The paper advocates the use of financial information like turnover or capital stock, and of data concerning the characteristics of the farmers, that could substantially improve the probability of detecting the most severe non-compliances. Social implications – Certification is essential for organic farming, and an improvement of inspection procedures through a risk-based approach could add efficiency and effectiveness to the whole organic food system, with obvious advantages for consumers and the society as a whole. Originality/value – This paper provides for the first time empirical evidence concerning the implementation of the organic certification system in the UK.
Raffaele Zanoli; Danilo Gambelli; Francesco Solfanelli; Susanne Padel. Assessing the risk of non-compliance in UK organic agriculture. British Food Journal 2014, 116, 1369 -1382.
AMA StyleRaffaele Zanoli, Danilo Gambelli, Francesco Solfanelli, Susanne Padel. Assessing the risk of non-compliance in UK organic agriculture. British Food Journal. 2014; 116 (8):1369-1382.
Chicago/Turabian StyleRaffaele Zanoli; Danilo Gambelli; Francesco Solfanelli; Susanne Padel. 2014. "Assessing the risk of non-compliance in UK organic agriculture." British Food Journal 116, no. 8: 1369-1382.
Certification is an essential feature in organic farming, and it is based on inspections to verify compliance with respect to European Council Regulation—EC Reg. No 834/2007. A risk‐based approach to noncompliance that alerts the control bodies to activate planning inspections would contribute to a more efficient and cost‐effective certification system. An analysis of factors that can affect the probability of noncompliance in organic farming has thus been developed. This article examines the application of zero‐inflated count data models to farm‐level panel data from inspection results and sanctions obtained from the Ethical and Environmental Certification Institute, one of the main control bodies in Italy. We tested many a priori hypotheses related to the risk of noncompliance. We find evidence of an important role for past noncompliant behavior in predicting future noncompliance, while farm size and the occurrence of livestock also have roles in an increased probability of noncompliance. We conclude the article proposing that an efficient risk‐based inspection system should be designed, weighting up the known probability of occurrence of a given noncompliance according to the severity of its impact.
Raffaele Zanoli; Danilo Gambelli; Francesco Solfanelli. Assessing Risk Factors in the Organic Control System: Evidence from Inspection Data in Italy. Risk Analysis 2014, 34, 2174 -2187.
AMA StyleRaffaele Zanoli, Danilo Gambelli, Francesco Solfanelli. Assessing Risk Factors in the Organic Control System: Evidence from Inspection Data in Italy. Risk Analysis. 2014; 34 (12):2174-2187.
Chicago/Turabian StyleRaffaele Zanoli; Danilo Gambelli; Francesco Solfanelli. 2014. "Assessing Risk Factors in the Organic Control System: Evidence from Inspection Data in Italy." Risk Analysis 34, no. 12: 2174-2187.
A risk-based inspection system might improve the efficiency of the organic farming certification system and ultimately provide a basis for increased competitiveness of this sector. This requires the definition of an effective inspection procedure that allows statistical evaluation of critical risk factors for noncompliance. In this article, we present a study based on data from selected control bodies in five European countries that is aimed at determining the feasibility of risk-based inspections in the organic sector according to the data that are currently routinely recorded. Bayesian networks are used for identification of the factors that can affect the risk of noncompliance. The results show that previous/concurrent noncompliant behavior explains most of the risk, and that the risk increases with farm size and the complexity of their operations. The data currently recorded by control bodies appear to be insufficient to establish an effective risk-based approach to these inspections
Danilo Gambelli; Francesco Solfanelli; Raffaele Zanoli. Feasibility of risk-based inspections in organic farming: results from a probabilistic model. Agricultural Economics 2013, 45, 267 -277.
AMA StyleDanilo Gambelli, Francesco Solfanelli, Raffaele Zanoli. Feasibility of risk-based inspections in organic farming: results from a probabilistic model. Agricultural Economics. 2013; 45 (3):267-277.
Chicago/Turabian StyleDanilo Gambelli; Francesco Solfanelli; Raffaele Zanoli. 2013. "Feasibility of risk-based inspections in organic farming: results from a probabilistic model." Agricultural Economics 45, no. 3: 267-277.
Scenario analysis is a qualitative tool for strategic policy analysis that enables researchers and policymakers\ud to support decision making, and a systemic analysis of the main determinants of a business or sector.\ud In this study, a scenario analysis is developed regarding the future development of the market of organic\ud food products in Europe. The scenario follows a participatory approach, exploiting potential interactions\ud among the relevant driving forces, as selected by experts. Network analysis is used to identify the roles of\ud driving forces in the different scenarios, and the results are discussed in comparison with the main findings\ud from existing scenarios on the future development of the organic sector
Raffaele Zanoli; Danilo Gambelli; Daniela Vairo. Scenarios of the organic food market in Europe. Food Policy 2012, 37, 41 -57.
AMA StyleRaffaele Zanoli, Danilo Gambelli, Daniela Vairo. Scenarios of the organic food market in Europe. Food Policy. 2012; 37 (1):41-57.
Chicago/Turabian StyleRaffaele Zanoli; Danilo Gambelli; Daniela Vairo. 2012. "Scenarios of the organic food market in Europe." Food Policy 37, no. 1: 41-57.
The maintenance of organic farming production schemes is a theme receiving a growing interest now that there are signs of a slowing in organic farming uptake in Italy. The present study develops a model based on a Bayesian network (BN) that is aimed at investigating the factors that affect the exit of a farm from the organic sector and to simulate the probability of maintaining an organic scheme for different farm types. The model is based on a database of organic farms, which has been integrated with qualitative information. Farm-type simulation and sensitivity analysis of most of the relevant variables have been carried out. Main results show that arable farm types are those with a higher probability to stay in the organic sector, while farmers’ age, Province the farm is situated in and farm size are the factors mostly influencing probability scores.
Danilo Gambelli; V. Bruschi. A Bayesian network to predict the probability of organic farms’ exit from the sector: A case study from Marche, Italy. Computers and Electronics in Agriculture 2010, 71, 22 -31.
AMA StyleDanilo Gambelli, V. Bruschi. A Bayesian network to predict the probability of organic farms’ exit from the sector: A case study from Marche, Italy. Computers and Electronics in Agriculture. 2010; 71 (1):22-31.
Chicago/Turabian StyleDanilo Gambelli; V. Bruschi. 2010. "A Bayesian network to predict the probability of organic farms’ exit from the sector: A case study from Marche, Italy." Computers and Electronics in Agriculture 71, no. 1: 22-31.
Danilo Gambelli; Daniela Vairo; Raffaele Zanoli. Exploiting Qualitative Information for Decision Support in Scenario Analysis. Journal of Decision Systems 2010, 19, 1 .
AMA StyleDanilo Gambelli, Daniela Vairo, Raffaele Zanoli. Exploiting Qualitative Information for Decision Support in Scenario Analysis. Journal of Decision Systems. 2010; 19 (4):1.
Chicago/Turabian StyleDanilo Gambelli; Daniela Vairo; Raffaele Zanoli. 2010. "Exploiting Qualitative Information for Decision Support in Scenario Analysis." Journal of Decision Systems 19, no. 4: 1.
Jernej Turk; Emil Erjavec; Danilo Gambelli. Supply Trends in Slovenian Agriculture under Transition to the Market. Eastern European Economics 1999, 37, 06 -33.
AMA StyleJernej Turk, Emil Erjavec, Danilo Gambelli. Supply Trends in Slovenian Agriculture under Transition to the Market. Eastern European Economics. 1999; 37 (3):06-33.
Chicago/Turabian StyleJernej Turk; Emil Erjavec; Danilo Gambelli. 1999. "Supply Trends in Slovenian Agriculture under Transition to the Market." Eastern European Economics 37, no. 3: 06-33.
The research analyses small and medium enterprises (SMEs), i.e. township and village enterprises (TVEs), operating in rural China over the last decade. It focuses on factors that affect the growth of TVEs run by Township and Village (TV), defined as collective, at provincial level. The paper examines SME theory and the role of human capital in the SMEs development. Following this, it analyses the development of Chinese TVEs and their role in the socio-economic development of rural areas and of the national economy. A panel analysis is then performed, using provincial panel data of collective TVEs over the period 1986–93, in order to capture the major determinants of provincial growth. The results of the panel estimations highlight some important features of TVEs run by TV sector, and provide empirical evidence in support to the positive role of clustering (measured through a new index) and human capital in the provincial growth of this sector. Copyright © 1999 John Wiley & Sons, Ltd.
Mario Biggeri; Danilo Gambelli; Christine Phillips. Small and medium enterprise theory: evidence for Chinese TVEs. Journal of International Development 1999, 11, 197 -219.
AMA StyleMario Biggeri, Danilo Gambelli, Christine Phillips. Small and medium enterprise theory: evidence for Chinese TVEs. Journal of International Development. 1999; 11 (2):197-219.
Chicago/Turabian StyleMario Biggeri; Danilo Gambelli; Christine Phillips. 1999. "Small and medium enterprise theory: evidence for Chinese TVEs." Journal of International Development 11, no. 2: 197-219.
The research analyses small and medium enterprises (SMEs), i.e. township and village enterprises (TVEs), operating in rural China over the last decade. It focuses on factors that affect the growth of TVEs run by Township and Village (TV), defined as collective, at provincial level. The paper examines SME theory and the role of human capital in the SMEs development. Following this, it analyses the development of Chinese TVEs and their role in the socio-economic development of rural areas and of the national economy. A panel analysis is then performed, using provincial panel data of collective TVEs over the period 1986–93, in order to capture the major determinants of provincial growth. The results of the panel estimations highlight some important features of TVEs run by TV sector, and provide empirical evidence in support to the positive role of clustering (measured through a new index) and human capital in the provincial growth of this sector. Copyright © 1999 John Wiley & Sons, Ltd.
Mario Biggeri; Danilo Gambelli; Christine Phillips. Small and medium enterprise theory: evidence for Chinese TVEs. Journal of International Development 1999, 11, 197 -219.
AMA StyleMario Biggeri, Danilo Gambelli, Christine Phillips. Small and medium enterprise theory: evidence for Chinese TVEs. Journal of International Development. 1999; 11 (2):197-219.
Chicago/Turabian StyleMario Biggeri; Danilo Gambelli; Christine Phillips. 1999. "Small and medium enterprise theory: evidence for Chinese TVEs." Journal of International Development 11, no. 2: 197-219.