Smaller scale New Zealand dairy farmers: long term plans and key challenges

Farmer wellbeing has been defined as “a dynamic process that gives people a sense of how their lives are evolving” (Nimpagariste & Culver, 2010). In order to support and enhance the wellbeing of farmers in New Zealand, the farmers’ goals, future plans and challenges to their plans all need to be understood. A particular group of interest is smaller scale dairy farmers. The average size of dairy farms in developed agricultural nations is increasing and New Zealand is no different. A high proportion (62%) of NZ dairy herds are smaller scale, milking less than 400 cows at peak. Their wellbeing, now and in the future, is important to the New Zealand dairy industry as a whole. Consequently, the aim of this study is to develop an understanding of smaller-scale dairy farmers’ future goals, plans and challenges so that recommendations can be made to enhance and support their wellbeing in the future. Farms who peak milked less than 400 cows were surveyed via telephone. A total of 346 surveys were completed, in Taranaki (n=103), the Waikato (n=144) and Northland (n=99). The majority of respondents’ were owner-operators (75%), male (67%), born and bred in a rural area (79%), and between 40 and 60 years old (57%). Overall, the mean farm size was 97ha, with 240 cows producing 86,789kgMS with 0.83 of a full time employee. Respondents’ had high (67%) equity levels in their businesses and a third (35%) had non-farming investments. Farmers’ most likely future investments were related to their current farming business, that is reducing debt to very low levels and increasing production by more than 10%. Based on farmers future plans and challenges reported and discussed in this study, it is clear the smaller scale dairy farmers would like knowledge and assistance in five key areas; succession, regulation and compliance, staff, technology and cash-flow/profitability. This report concludes with suggestions for each of these areas, which has the potential to maintain or increase the wellbeing of smaller scale dairy farmers in New Zealand. [Executive summary]DairyNZ Ltd, Ministry for Primary Industry (NZ

Rating and ranking firms with fuzzy expert systems: the case of Camuzzi

In this paper we present a real-life application of a fuzzy expert system aimed at rating and ranking firms. Unlike standard DCF models, it integrates financial, strategic and business determinants and processes both quantitative and qualitative variables. Twenty-one value drivers are defined, concerning the target firm (strategic assets in place and expected financial performance), the acquisition (synergies, quality of management) and the sector (intensity of competition, entry barriers). Their combination via “if-then” rules leads to the definition of an output represented by a real number in the interval [0,1]. Such a number expresses the value-generating power of the target firm inclusive of synergies with the bidder (Strategic Enterprise Value). The system may be used for rating and ranking firms operating in the same sector. A regression analysis using hostile takeovers multiples may be employed to translate the score into price. The real-life case refers to Camuzzi (a natural gas distributor), acquired by Enel, the Italian ex monopolist of electric energy.Corporate finance, firm, rating, ranking, expert system, fuzzy, evaluation

Rating and ranking firms with fuzzy expert systems: the case of Camuzzi

In this paper we present a real-life application of a fuzzy expert system aimed at rating and ranking firms. Unlike standard DCF models, it integrates financial, strategic and business determinants and processes both quantitative and qualitative variables. Twenty-one value drivers are defined, concerning the target firm (strategic assets in place and expected financial performance), the acquisition (synergies, quality of management) and the sector (intensity of competition, entry barriers). Their combination via “if-then” rules leads to the definition of an output represented by a real number in the interval [0,1]. Such a number expresses the valuegenerating power of the target firm inclusive of synergies with the bidder (Strategic Enterprise Value). The system may be used for rating and ranking firms operating in the same sector. A regression analysis using hostile takeovers multiples may be employed to translate the score into price. The real-life case refers to Camuzzi (a natural gas distributor), acquired by Enel, the Italian ex monopolist of electric energy.Corporate finance, firm, rating, ranking, expert system, fuzzy logic, evaluation

What lies beneath? The role of informal and hidden networks in the management of crises

Crisis management research traditionally focuses on the role of formal communication networks in the escalation and management of organisational crises. Here, we consider instead informal and unobservable networks. The paper explores how hidden informal exchanges can impact upon organisational decision-making and performance, particularly around inter-agency working, as knowledge distributed across organisations and shared between organisations is often shared through informal means and not captured effectively through the formal decision-making processes. Early warnings and weak signals about potential risks and crises are therefore often missed. We consider the implications of these dynamics in terms of crisis avoidance and crisis management

Economic Concepts of Organic Certification

Certification is a key element in marketing organic food products. Based on economic theory, this report wants to illustrate the economic reasoning for certification. The intention is to provide a description of economic concepts, which is understandable for a wider audience. We are focusing on the basic economic literature. Chapter 1 “Organic certification system” describes the current control system in the European Union. Why this is necessary, will then be explained based on a synopsis of economic literature. Of specific significance for organic certification and the CERTCOST project are the concepts of institutional economics and economics of crime. The relevant points of economic theory will be presented and discussed in chapter 2 “Theoretical framework”. Finally, the costs and benefits of organic certification will be illustrated in chapter 3 “Costs and benefits of organic certification”

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework

"It's all up here": adaptation and improvisation within the modern project

This paper considers organisational improvisation, and in particular, adaptation as a specific component of improvisational work(Miner et al., 2001), and how it may assist in resolving or assisting with some of the challenges surrounding recent shifts in our understanding of project-based management. Examples focus on the use of adaptation to cope with ambiguity and uncertainty, caused by execution in problematic and turbulent organisational environments. The literature on improvisation suggests that adapting previously successful interventions reduces and manages the risk of improvising by engaging with the 'adaptation component of organisational improvisation. This practice assists in ensuring that the additional risk of completely novel activity is avoided. This paper explores adaptation within the project domain, and also unpicks the rhetoric from the reality of adaptation within projects, confirming its benefits, setting out the circumstances where experience informs the practice, and offering readily usable and applicable insights

EXPERT SYSTEMS

In recent decades IT and computer systems have evolved rapidly in economic informatics field. The goal is to create user friendly information systems that respond promptly and accurately to requests. Informatics systems evolved into decision assisted systems, and such systems are converted, based on gained experience, in expert systems for creative problem solving that an organization is facing. Expert systems are aimed at rebuilding human reasoning on the expertise obtained from experts, stores knowledge, establishes links between knowledge, have the knowledge and ability to perform human intellectual activities. From the informatics development point of view, expert systems are based on the principle of the knowledge separation from the treating program. Expert systems simulate the human experts reasoning on knowledge available to them, multiply the knowledge and explain their own lines of reasoning.expert systems, artificial intelligence, knowledge, expertise

Operational Risk Management using a Fuzzy Logic Inference System

Operational Risk (OR) results from endogenous and exogenous risk factors, as diverse and complex to assess as human resources and technology, which may not be properly measured using traditional quantitative approaches. Engineering has faced the same challenges when designing practical solutions to complex multifactor and non-linear systems where human reasoning, expert knowledge or imprecise information are valuable inputs. One of the solutions provided by engineering is a Fuzzy Logic Inference System (FLIS). Despite the goal of the FLIS model for OR is its assessment, it is not an end in itself. The choice of a FLIS results in a convenient and sound use of qualitative and quantitative inputs, capable of effectively articulating risk management's identification, assessment, monitoring and mitigation stages. Different from traditional approaches, the proposed model allows evaluating mitigation efforts ex-ante, thus avoiding concealed OR sources from system complexity build-up and optimizing risk management resources. Furthermore, because the model contrasts effective with expected OR data, it is able to constantly validate its outcome, recognize environment shifts and issue warning signals.Operational Risk, Fuzzy Logic, Risk Management Classification JEL:G32, C63, D80