Previous PageTable Of ContentsNext Page

Risk management tools for dryland farmers in southwest Queensland: an action research approach

Nam Nguyen1,2, Malcolm Wegener1, Iean Russell1

1 School of NRSM, University of Queensland, www.nrsm.uq.edu.au Email: malcolm.wegener@uq.edu.au, irussell@uq.edu.au
2
Faculty of Agri.Economics & Rural Dev., National Economics University, Vietnam, www.neu.edu.vn Email: n.nguyen@uq.edu.au

Abstract

Australian farmers operate in one of the most risky environments in the world. They have to cope with many sources of risk in their farming businesses but weather variability is one of the most important sources of risk for these farmers. There has been little prior work reported that examines the sources of risk, the practical risk management strategies employed by Queensland dryland farmers, or their attitudes towards risk management.

The potential for dryland farmers to manage the various risks affecting their farm management decisions is being assessed and we expect to formulate a plan of action to improve risk management capability among dryland farmers in southwest Queensland. Once sources of risk, current strategies, interests and attitudes of farmers towards risk management are understood, a program to improve risk management among dryland farmers in southwest Queensland will be developed in collaboration with the GRDC-funded Western Farming Systems project.

The study employs an action research approach including a literature review, preliminary interviews, focus group discussions, an expert survey, training workshops, and evaluation surveys. The paper will document the background to the study, state the study’s objectives, and report on the work completed to date.

Three key learnings: (1) Soil moisture management and crop choice were the most serious issues concerning dryland farmers in dealing with risks. (2) A training workshop using decision support tools has improved the farmers’ ability to manage soil moisture and make planting decisions. (3) It appears that a simple decision support tool that can aid planting decisions would be a useful aid for dryland farmers

Key Words

Risk, decision support systems, extension methods, Queensland dryland farmers

Introduction

Background information

The Chinese maxim says: “Plans are man’s, but the odds are God’s”. We live in a world of uncertainty. We always try to make our plans with great consideration and anticipation of all likely events happening. However, we still face risk regularly (Nguyen, 2002).

Risk is an inevitable part of life, and most certainly of farming life. Generations of Australian farmers have lived with risk since agriculture first began here in this continent. In fact, Australian farmers operate in one of the most risky environments in the world. They farm an island continent where the weather variables (climate inputs to production) are uncertain and unreliable when compared to many of their competitors. For example, the 2002 drought, the worst in recorded history in Australia, had a major impact on farmers and the wider Australian community. The drought was reported to have cut farm incomes by 58 percent in 2003-04 (Potter, 2003). In addition to weather variability, up to 80 percent of some Australian agricultural products are destined for international markets (Clark and Brinkley, 2001), where prices fluctuate in the competitive global economy. The variability and uncertainty associated with these two risks (weather variability and wide price fluctuations for commodities), together with the other risks that farmers face (such as financial and institutional risks) establish the basic business environment in which Australian farmers form judgments, plan strategies, and position their businesses to capture the benefits of future scenarios.

There is an extensive literature on risk and risk management in general as well as in agriculture in particular. The strategies to manage price and marketing risks in agriculture have been identified by several authors, for example, Trapp (1989), Duncan et al. (1991), Lubulwa and Beare (1998), Williams and Schroder (1999), Meuwissen (2001), Wilson and Wagner (2002). Similarly, strategies related to agricultural production risk management have been discussed in various publications, e.g. Hammer et al.(1996), Gaynor (1998), Meinke et al.(2001), Cooper et al.(2003), Marra et al.(2003), and Robertson et al.(2003).

Nevertheless, little prior work that examines the sources of risk, practical risk management strategies employed by farmers, or their interests and attitudes towards risk management has been reported in literature. Moreover, there has been little investigation so far into the needs of decision support tools of Queensland dryland farmers and how these needs can be met.

Accordingly, this study will seek to determine the opportunity for farmers to manage the various risks affecting their farm management and to formulate a plan of action to assist dryland farmers in southwest Queensland improve their risk management strategies. Thus sources of risk, current strategies, interests and attitudes of farmers towards risk management will be identified and investigated. Once these are understood, the feasibility of developing a risk management improvement program for farmers will be examined.

Research methods

The methodological framework chosen for this study is action research. The theory of action research was laid down in the mid-1940s by Kurt Lewin, an American psychologist (McKernan, 1991). Broadly speaking, action research is defined as a family of research methodologies that pursue the dual outcomes of action learning and research (Dick, 2000). In the literature, there are many definitions of action research (e.g. Kemmis and McTaggert, 1990; Masters, 2000; and Frost, 2002). Generally, these definitions all include four basic themes: empowerment of participations, collaboration through participation, acquisition of knowledge, and social change. The research process to achieve these themes is a spiral of action research cycles consisting of four major phrases: planning, acting, observing, and reflecting (Zuber-Skerritt, 1993; Cherry, 1999). An action research model is illustrated in Figure 1.

Figure 1. An extended action research model (modified from McNiff and Whitehead, 2002 and Costello, 2003)

Support for the rigour of action research and its potential for application has been spelled out in many publications, e.g. Dick (1997), Macintyre (2000), and Robson (2002). According to those authors, the choice of action research for this study is justified because both action and research are its intended outcomes. Action research provides the flexibility and responsiveness that is needed for effective change at the same time as it provides a check on the adequacy of data and conclusions.

Many methods can be chosen in an action research project. This study uses literature review, interviews, focus group discussions, training workshops, and evaluation. This is consistent with Dick (2000) who noted that the methods used most commonly for data collection were interviewing and focus groups.

Literature review

Key articles

Reviewing literature is one of the essential preliminary tasks when undertaking a research study. It is an important step in the process of defining the research problem (Cavana et al., 2001).

The authors of this study adopted the suggestions from well-regarded texts on research methods, such as Kumar (1996), Burns (2000) and Cavana et al. (2001), that the literature review should be written around themes that have emerged from reading the literature. The chosen themes should be precise, descriptive of the contents, and should follow a logical progression. Thus the review of literature in this study was organised into different sections, ranging from general to specific themes including risk management, decision making, and decision theory. There is a special section on risk management in agricultural literature and decision support systems and simulation models applied to risk management with emphasis on the Australian and Queensland agricultural context.

Research questions defined

Four fundamental questions have been emerged from the review of literature:

Research question 1: What are the current trends in the theory and practice of risk management in general and in agriculture in particular with a focus on farming in Queensland?

Research question 2: What are the sources of risks that dryland farmers in southwest Queensland have to deal with? How do they perceive and rank these risks?

Research question 3: How do dryland farmers manage farming risks?

Research question 4: Which decision support tools or simulation models can be used to help southwest Queensland farmers make better decisions under risky conditions?

Objectives of the study

In addressing these questions, this study aims to evaluate and improve risk management strategies for dryland farmers in southwest Queensland. The main objectives of the study are:

  • to review the current trends in the theory and practice of risk management in general and in agriculture in particular;
  • to identify and review different sources of farming risk that farmers in southwest Queensland have to face as well as document their perceptions of farming risks;
  • to investigate the risk management strategies currently employed by farmers and understand their interests in and attitudes towards risk management;
  • to help farmers cope better with the risks they face, to assist them to make good decisions under risky conditions, and encourage them to apply appropriate risk management tools in their businesses.

Preliminary interviews

How was it done?

It was recognised during the literature review phase that the study needed to be discussed with experts in the field for refinement and constructive comments. Consequently, in June 2004, a series of face-to-face and email interviews were conducted with QDNRM, QDPI, and CSIRO staff involved in the APSRU modelling group. These people have usually been working in risk management or related areas for many years.

In late November 2004, a presentation of this study was given to a group of farmers at Roma (centre of the study area) and some preliminary interviews were conducted with some of them to understand how they were managing their farms and identify problems that they were facing.

What happened?

Interviewed experts shared a common understanding that very few formal ‘tools’ such as models, and information derived from modelling, were used by farmers to manage risks. They suggested that several risk management strategies were being used by Queensland dryland farmers. These included maintaining a high level of equity, keeping overhead costs low, reinvesting profits into the farm business, diversifying, checking and testing alternative farming systems, including the use of long fallows to accumulate moisture. Many of these strategies rely on high levels of technical competence. Overall, it was concluded that the risk management strategies adopted by farmers were quite similar in principle to those applied by most risk averse managers.

Several issues have emerged from the discussions with farmers at Roma. First of all, it was claimed that risk is very difficult to identify. In addition, farmers normally do not know what the probabilities of particular events occurring are. It was stressed that it is important to “get the timing right” as one of the essential features in risk management and making decisions. Timeliness is important because one of the farmers said “Every time it rains, it brings income opportunities”. Other farmers added: “Sometimes doing the right thing is not as important as doing it at the right time”. This is true because as Gilovich and Griffin (2002) noted, successful ideas must not only be good, but timely – even lucky. Thirdly, it was largely agreed that experience and preferences are very important in decision making. This relates especially to decisions regarding crop planting. Production risks were mentioned as the main source of farming risk and weather variability is the obvious factor driving this. Other sources of farming risk identified in the literature review were also mentioned by farmers but it seems that the things that concern them most of all are what to grow and when to plant it. Finally, owning machinery or using contractors is another essential issue concerning many farmers since it has a big impact on managing risk in this uncertain environment.

What does this mean?

By and large, the preliminary interviews with experts did give some insights into the possible direction of the study as well as help to refine the research questions. The experts interviewed all agreed that it was essential before building a risk management program to conduct focus group discussions and survey farmers to find out how they perceive sources of farming risk and what are their current risk management strategies.

The discussions with these farmers did not necessarily imply the situation in the whole study area since the discussions were conducted with a fairly small number of farmers. However, they indicate what farmers are actually doing, as well as describing their problems. As such, their comment could be used to provide guidance for the focus group discussions and design of risk management tools that were expected to occur in later stages of this study.

Focus group discussions

How was it done?

Focus groups were selected for the second stage in the investigation because they have many advantages as a method of gathering qualitative data (Krueger and Casey, 2000; Berg, 2001; Coutts, 2004). The main objectives of the focus group discussions were to explore the research questions, identify what risks farmers face, and learn how they deal with them. In addition, we hoped to assess farmers’ needs in regards to risk management tools and learn how these needs might be met.

Wolff et al. (1993) noted that the selection of group participants is typically purposive and based more on suitability or convenience rather than representativeness. In this study, the participants asked to participate in the focus group discussions were suggested by QDPI staff in Roma, and were relatively representative of farmers in the study area. Thus the information that was generated was regarded as being generally useful to the wider population in ways suggested by Kennedy (1979).

Following suggestions for successful focus groups , e.g. by Morgan (1988) and Krueger (1988), the two focus groups (conducted on 18 February, 2005) had moderators and were fairly small, having six and ten participants respectively.

What happened?

Generally, farmers’ definitions of risk are not as long or as complicated as those used by scholars, e.g. Hardaker et al. (1997), Williams and Schroder (1999), or Just et al. (2003). In the discussions, there was a general agreement that risk is anything that threatens the farm enterprise. “Risk is something that would prevent you from gaining profit or [taking advantage of] profitable opportunities which farmers would expect to get”. All participants accepted the fact that farming is risky. “You can’t go into farming without risk. In other words, you can’t be a no-risk farmer”.

Like the colours in the spectrum, the range of business risk contains many shades and variations. Generally speaking, it may depend on the study objectives but scholars often categorise sources of risk differently. According to some scholars, e.g. Boehlje and Trede (1977), Fleisher (1990), Hardaker et al. (1997), and Kay and Edwards (1999), the main sources of risk in farming include production, marketing, institutional, personal, and financial risks. These same sources of risk were mentioned by participants in the focus groups; with many examples raised about how changes in weather, personnel, business environment, and government policy affect the risks they face.

Participants in the focus groups were asked to select three sources of risk that they considered most important. Weather variability was ranked as the most important source of risk in both discussion groups. This was followed by financial and government policy risks in the first group and government policy and marketing risks in the second group.

Farmers in the Roma area of southwest Queensland were using a variety of different strategies to manage the range of risks that they face. These strategies included having cattle as the predominant enterprise, with complementary farming of cash crops, and using different strategies to spread the risk. Most farmers were concentrating on growing the crop rather than worrying about marketing it, and managing weather variability by conserving moisture and using zero till planting. To manage marketing risk, they were selling only part of farm production at any one time. Other risk management strategies mentioned included practising good business management methods and having off-farm investments. There was little discussion about how to manage the risk that government policy might change although this source of risk was claimed by participants as something “out of control”.

Participants questioned the effectiveness of most of the decision support tools and programs that were available and commented on their complex nature. There was a general conclusion that knowing what is available was a problem and learning how to use these new tools could take a lot of time. The cost-effectiveness of these tools/programs was another aspect questioned by participants.

What does this mean?

Results of the focus group discussions revealed that soil moisture management and crop choice were the topics that concerned farmers most in dealing with the risks they face. Overall, it was concluded that it would be useful if participants had something that could help them understand the ways to store water and utilise it better or choose the right crop at planting time to make most effective use of available water. It appeared that some sort of decision support tool would be useful to them.

Expert survey

How was it done?

The main objective in interviewing experts working with decision support systems (DSS) was to ask for advice and suggestions from leading practitioners in the field of DSS about designing a DSS for farmers and to understand the adoption of DSS in Australian agriculture. We also wanted to preview the likely future development of DSS and to assess the possibility and appropriateness of designing something (a decision support tool) to help dryland farmers make better crop choices and more appropriate planting decisions.

During June 2005, questionnaires were emailed to various experts and consultants who were knowledgeable about the development and application of DSS in Australian agriculture. This method of data collection was regarded as appropriate at that stage of the study, considering the relevant constraints such as time, location, and budget. Interviewees were chosen on the basis of their publication record in the field of DSS and their working experiences in this field.

In total, questionnaires were emailed to 20 experts and three consultants. The experts worked for various universities and research and extension organisations in Australia. The consultants were from three private agricultural companies working in the study area. Three main questions were asked to pursue the objectives described previously. The response rate (19 responses from 23 requests) was impressive, given factors such as the time pressure on respondents, the fact that the questions were very open-ended, and most of interviewees knew very little about the enquirer or his study.

What happened?

Generally, respondents agreed that the issues which have been identified (soil moisture and crop choice) are critical issues related to managing risk in dryland cropping. The following points summarise the guidelines that the experts suggested should influence the design of DSS for farmers:

  • Being relevant to something that is causing considerable concern to farmers;
  • Working closely with farmers throughout the design phase;
  • Trying to take the farmers’ point of view;
  • Being simple and quick to use;
  • Having easily accessed information sources;
  • Including the range of options that the farmer may need to choose from; and
  • Finding a place within the process for communication between scientists and farmers.

Experts’ opinions about the current level of adoption of DSS in Australian agriculture were that:

  • The rate of adoption of DSS is extremely low and they are not widely used; and
  • The main audience is farm advisors.
  • Some considered DSS tools for farmers were mostly a waste of time and money; although
  • Younger farmers and new agricultural graduates are becoming more accepting of DSS.

The role suggested for DSS was to enhance the knowledge of farm advisors/consultants and enhance the value of information they provide to farmers. These DSS were also useful in a workshop setting. Another contribution could be in research and training “They might be more useful to the people who build them to structure their knowledge, than to the farmers”.

Many reasons were given that claimed to explain the slow uptake of DSS by farmers:

  • Farmers can make good decisions without using DSS;
  • Most farmers are not computer oriented;
  • Most DSS are not well designed and are too complex;
  • Farmers deal with issues in different ways to researchers;
  • DSS are too general and not specific to each farmer’s own circumstances;
  • Farmers are often short of time (to learn and use a DSS); and
  • DSS have not been well marketed.

Ideally, farmers need a substantial and active role in the whole process of initiating the design, production, and testing of DSS. In reality, however, they have not been involved to any extent in many cases. It was generally concluded that the farmers are left out of the process when they should be included.

It was generally stated that future for development of DSS is not good. Concerns were also expressed that the commercial market for DSS is likely to remain small so there is likely to be few commercial opportunities for private investment in DSS. There was a comment that DSS will continue to be developed regularly on all sorts of issues; but “… farmers will continue to not use them”. Nevertheless, some experts optimistically believed that useful DSS would have been and will be adopted.

Respondents suggested many conditions to improve the adoption rate for DSS including:

  • Widespread and serious problems (rather than trivial issues) need to be addressed;
  • These products need to be location specific;
  • Initial users need to provide strong support ;
  • Developers need to rely on relevance, simplicity, effectiveness, and low cost as key attributes;
  • Products other than computer-based products should be considered; and
  • Users need to be involved in the development of these products.

What does this mean?

The responses from experts and consultants contributed many valuable suggestions and insights that affected the direction of this study. The guidelines suggested by experts were considered carefully and will be applied in designing the ‘final product’ of this study (whether it will be a computer program, a spreadsheet, a decision tree, a chart, or something else). At this stage of the study, it seems that the ‘final product’ might be something simple to aid planting decisions. However, to be appropriate and more useful, it needs to be tested with farmers in the study area. After comprehensive discussion with advisers and experts in the field, two existing DSS tools, the “Howwet?” and “Howoften?” programs, were chosen as appropriate tools to use in the next phase of this study. The next section will report on the perceptions of farmers about these tools which will help when it comes to designing the ‘final product’.

Workshops

How was it done?

A workshop was held in Roma in August 2005 to introduce two decision making aids – “Howwet?” and “Howoften?”. The main objective of this workshop was to improve farmers’ knowledge about soil moisture management and to provide them with knowledge to help them to make better planting decisions. Another objective was to assess the usefulness and usability of the tools, as a guide to further work on designing other tools for risk management.

In late June 2005, invitation letters were sent out to all 16 farmers who had participated in the focus group discussions in February 2005. During July 2005, personal phone contacts were made and follow-on letters were sent to potential workshop participants. Initially, 10 farmers agreed to attend the workshop, which was organised on 3 August, 2005. However, only six of them were present on the day and the other four could not come to the workshop because of unexpected reasons.

What happened?

The first half hour of the workshop was used for scenario testing. The predominant aim was to investigate the type of information that participants need in making planting decisions. Another aim was try to understand participants’ farming conditions and their processes for choosing a crop to plant. The initial question asked to start discussion was: ‘What is the decision making process you use for planting and crop choices? (for example, take 1st May 2005 as a starting point and consider the decision you made and the information you needed [to choose which winter crop to plant])’

Participants listed nine identifiable pieces of information, which they considered were essential to know when making planting decisions. These sources included stored soil moisture, soil conditions, planting window, weather outlook, crop rotation, weeds present, financial situation, diseases incidence, and other external sources of information (e.g. DPI notes). In regard to crop choice, participants have had a strong preference to plant wheat in the past although other crops, such as chickpeas, canola, and lucerne, have now come into the suite of crops mentioned because of their ability to contribute nitrogen or break weed and disease build-up in the crop rotation.

Most of the workshop was used for the presentation of two decision support tools – “Howwet?” and “Howoften?”. These tools were introduced and presented to participants by two staff from QDNRM in Toowoomba, Dr David Freebairn, the developer of these tools, and Mr Norman Gurner.

Basically, “Howwet?” is a Windows based program that uses farm rainfall records to estimate how much plant available water has been stored in the soil as well as estimating the amount of organic nitrogen that has been converted to an available form during a fallow (non-crop period). “Howoften?” is a computer program for examining historic rainfall records to determine the odds or chances of future rainfall events. The basic question that “Howoften?” answers is: ‘How often does ‘x’ mm rain fall in ‘y’ days within a specified time period’? Further information about these programs is available at the APSRU website (www.apsru.gov.au/apsru/) and can be downloaded without cost by farmers.

Throughout the presentation, participants were seated in pairs provided with a laptop computer to learn how to use these tools, and were shown how to do exercises by the presenters. Each participant was then given a CD containing notes on soil and soil water and copies of these two programs. These were able to take them home to try the programs themselves.

Workshop evaluation

At the end of the workshop, participants were asked to fill in a workshop evaluation sheet. Workshop participants had used various tools to estimate soil moisture. All of them stated that they have been using and will continue to use rainfall records and a push probe. Half of them (3/6) have used soil cores and one has used a neutron probe moisture meter. None of the workshop participants was currently using Howwet? but four out of six participants said that they would use the program on their farm in coming seasons.

A Likert scale rating (Burns, 2000) was used to get participants to make an assessment of the workshop, its organisation, and its usefulness. Impressively, all participants said they valued the day, noted that it was well organised and useful to them. They also stated that similar workshops would be useful for them. The consensus among participants was that attending the workshop had improved their ability to assess and use tools for monitoring soil moisture, calculate how much soil water is stored, and use soil water and climate information in making more informed cropping decisions.

All participants indicated the importance of soil moisture and past crop history in making planting decisions. Expected yield and expected in-crop rain were also mentioned by most of them (5/6) as being important. Participants indicated that if they had a spreadsheet or program to assist with planting decisions, they would like to see wheat and chickpeas included.

Only one participant in the workshop reported that the programs that had been demonstrated met his needs. The other five said they were not sure if the programs could answer their information needs, or not until they tried them more extensively

The WhopperCropper (WC) program (Cox et al., 2004) was mentioned to participants as an existing program which allows a lot of planting scenarios and hypothetical crop choices to be evaluated. Only half of the participants said they had heard of the program; the other half could not recall having heard of it. The program had been used by only one of the farmers and it was acknowledged as being useful. The rest of participants all expressed interest in trying this program.

There was one workshop participant who did not express preference for computer-based or paper-based tools. Another one preferred paper-based tools. The four remaining participants were comfortable with computer-based tools although they said they must be kept as simple as possible. All participants emphasised that they would be happy to continue to be involved in this study about risk management tools for dryland farmers in southwest Queensland.

Generally, participants claimed that they miss one day in most planting seasons. There is not much cost if the day missed is at the start of the planting window. If the day missed was at the end of the planting window, it might mean that up to 50 ha of crop might have to be left to fallow. This could cost several thousand dollars in foregone income depending on the potential crop yield and prices.

What does this mean?

The workshop has introduced a small group of farmers in the region to some existing decision support tools. Participants have valued the usefulness of these tools. They also expressed the view that the workshop improved their ability in terms of managing soil moisture and making planting decisions. The feedback from them opened the way for the study to organise another workshop at which the WhopperCropper program will be presented and further discussion about the information needed to design a planting decision support tool will be possible.

Conclusion

In summary, this article reports on-going research. The key learnings so far have documented that:

  • Soil moisture management and crop choice were the most serious issues concerning dryland farmers in dealing with risks.
  • A training workshop using DSS has improved the farmers’ ability to manage soil moisture and make planting decisions.
  • It appears that a simple decision support tool that can aid planting decisions would be a useful aid for dryland farmers.

Acknowledgments

The authors would like to thank Katherine Snars and Richard Routley for their assistance in conducting the focus groups. All of the farmers and experts are acknowledged for being involved so willingly in the focus group discussions and survey. This study is supported by an International Postgraduate Research Scholarship (IPRS) at The University of Queensland and the GRDC-funded Western Farming Systems project.

References

Berg, B. L. (2001). Qualitative research methods for the social sciences, Allyn & Bacon, MA, USA.

Boehlje, M. D. and Trede, L. D. (1977). 'Risk management in agriculture', Journal of the American Society of Farm Managers and Rural Appraisers, 41, pp 20-29.

Burns, R. B. (2000). Introduction to research methods, Pearson Education Australia, NSW.

Cavana, R. Y., Delahaye, B. L. and Sekaran, U. (2001). Applied business research: qualitative and quantitative methods, John Wiley & Sons Australia, Ltd, Brisbane, Australia.

Cherry, N. (1999). 'The Action Research Paradigm', In QRM series: Action Research: A pathway to action, knowledge and learning, (Cherry, N., Ed.), RMIT University Press, Melbourne, Australia, pp. 1-15.

Clark, A. and Brinkley, T. (2001). Risk management: for climate, agriculture and policy, Bureau of Rural Sciences, Canberra.

Cooper, I., Nguyen, N. and Hancock, J. (2003). 'Rotations, Risk and Reward: Farming system choice on the Eyre Peninsula of South Australia', Australian Agricultural and Resource Economics Society, 47th Annual Conference, 12-14th February, 2003, Perth, Australia.

Costello, P. J. M. (2003). Action research, MPG Books, London, UK.

Coutts, J. (2004). Interviews and Focus Groups: How to make the most of talking with people when data collecting, CRRI-Q, The University of Queensland, Gatton, QLD.

Cox, H. W., Hammer, G., McLean, G. B. and King, C. (2004). 'National WhopperCropper - risk management discussion support software', 4th International Crop Science Congress, Brisbane, Qld.

Dick, B. (1997). Approaching an action research thesis: an overview, [Online] Accessed: 8 July 2005, Available at:http://www.scu.edu.au/schools/gcm/ar/arp/phd.html.

Dick, B. (2000). Postgraduate programs using action research, [Online] Accessed: 6 July 2005, Available at: http://www.scu.edu.au/schools/gcm/ar/arp/ppar.html.

Duncan, R., Holden, D., Hazell, P. and Pritchard, A. (1991). 'Commodity price risk management and financial markets', Risk in agriculture: proceedings of the Tenth Agriculture Sector Symposium, OQEH.

Fleisher, B. (1990). Agricultural risk management, Lynne Rienner Publishers Inc., Boulder, Colorado; USA.

Frost, P. (2002). 'Principles of the action research cycle', In Action Research: A Guide for Teachers, (Ritchie, R., Pollard, A., Frost, P. and T., E., Ed.), National Primary Trust, Birmingham, UK, pp. 24-32.

Gaynor, H. (1998). 'Risk management on the farm', National Agricultural and Resource Outlook Conference, Canberra.

Gilovich, T. and Griffin, D. (2002). 'Introduction - Heuristics and Biases: Then and Now', In Heuristics and Biases: the Psychology of Intuitive Judgment, (Gilovich, T., Griffin, D. and Kahneman, D., Ed.), Cambridge University Press, New York, USA, pp. 1-18.

Hammer, G. L., Holzworth, D. P. and Stone, R. (1996). 'The value of skill in seasonal climate forecasting to wheat crop management in a region with high climatic variability', Australian Journal of Agricultural Research, 47, pp 717-737.

Hardaker, J. B., Huirne, R. B. and Anderson, J. R. (1997). Coping with risk in agriculture, CAB International, Wallingford, U.K.

Just, D. R., Wolf, S. and Zilberman, D. (2003). 'Principles of risk management service relations in agriculture', Agricultural Systems, 75, pp 199-213.

Kay, R. D. and Edwards, W. M. (1999). Farm Management, WCB/McGraw-Hill.

Kemmis, S. and McTaggert, R. (1990). The Action Research Planner, Deakin University Press, Geelong, Australia.

Kennedy, M. (1979). 'Generalizing from single case studies', Evaluation Quarterly, 3, pp 661-678.

Krueger, R. A. (1988). Focus groups: A practical guide for applied research, SAGE Publication, Inc, Newbury Park, CA, USA.

Krueger, R. A. and Casey, M. A. (2000). Focus Groups: A practical guide for applied research, SAGE Publications, Inc., Thousand Oaks, California.

Kumar, R. (1996). Research methodology: a step-by-step guide for beginners, Addison Wesley Longman Australia Pty Limited, Melbourne, Australia.

Lubulwa, M. and Beare, S. (1998). 'Use of the Sydney futures exchange wool futures contract in price risk management', Chicago board of trade 1998 Asia Pacific futures research symposium, Sydney, Australia.

Macintyre, C. (2000). The Art of Action Research in the Classroom, David Fulton Publishers, London, UK.

Marra, M., Pannell, D. J. and Abadi Ghadim, A. (2003). 'The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: Where are we on the learning curve?' Agricultural Systems, 75, pp 215-234.

Masters, J. (2000). The history of action research, [Online] Accessed: 6 July 2005, Available at: http://www2.fhs.usyd.edu.au/arow/arer/003.htm.

McKernan, J. (1991). Curriculum Action Research: A Handbook of Methods and Resources for the Reflective Practitioner, Kogan Page, London, UK.

McNiff, J. and Whitehead, J. (2002). Action research: principles and practice, RoutledgeFalmer, London, UK.

Meinke, H., Baethgen, W. E., Carberry, P. S., Donatellic, M., Hammer, G. L., Selvaraju, R. and Sto ckle, C. O. (2001). 'Increasing profits and reducing risks in crop production using participatory systems simulation approaches', Agricultural Systems, 70, pp 493-513.

Meuwissen, M. P. M., Hardaker, J. B., Huirne, R. B. M. and Dijkhuizen, A. A. (2001). 'Sharing risks in agriculture; principles and empirical results', Netherlands Journal of Agricultural Science, 49, pp 343-356.

Morgan, D. L. (1988). Focus groups as a qualitative research, SAGE Publication, Inc, Newbury Park, CA, USA.

Nguyen, C. N. (2002). Farming risks in the Upper Eyre Peninsula, M.Agr.Bus, University of Adelaide, Roseworthy Campus, SA.

Potter, M. (2003). 2004-05 Pre-Budget Submission, National Farmers' Federation Limited, ACT, Australia.

Robertson, M. J., Cawthray, S., Birch, C. J., Bidstrup, R. and Hammer, G. L. (2003). 'Improving the confidence of dryland maize growers in the northern region by developing low-risk production strategies. Solutions for a better environment', Proceedings of the 11th Australian Agronomy Conference, Geelong, Victoria.

Robson, C. (2002). Real World Research, Blackell, Oxford.

Trapp, J. N. (1989). 'A commodity market simulation game for teaching market risk management', Southern Journal of Agricultural Economics, 21, pp 139-147.

Williams, J. and Schroder, W. R. (1999). Agricultural price risk management : the principles of commodity trading, Oxford University Press, Melbourne.

Wilson, W. W. and Wagner, R. (2002). Price risk management strategies for grain importers, Department of Agribusiness and Applied Economics, North Dakota State University.

Wolff, B., Knodel, J. and Sittitrai, W. (1993). 'Focus group and surveys as complementary research methods: A case example', In Successful focus groups: Advancing the State of the Art, (Morgan, D. L., Ed.), SAGE Publication, Inc, Newbury Park, California, USA, pp. 118-135.

Zuber-Skerritt, O. (1993). 'Improving learning and teaching through action learning and action research', Higher Education Research and Development, 12, pp 45-58.

Previous PageTop Of PageNext Page