Document(s) 12 of 14

Introduction

Biotechnology holds promise for millions of people, particularly in developing countries (Cohen 1994). Biotechnology could enhance agricultural productivity and quality with the same quantity of inputs or possibly even a reduction. But, some of the new biotechnology developments (that involve genetic modification in either the food production process or the final product or both) require huge investments and have greater social and economic risks due to the use of novel techniques such as genetic engineering. As a result, superior technology does not necessarily translate into successful commercial products because of increasing public scrutiny. The uncertainty in the technological innovation process underscores the need for careful assessment of biotechnology research opportunities.

Improved information and improved procedures can assist biotechnology decision-making by identifying present and future food supply and demand situations, and how they will be affected by new technology; by identifying to what extent research contributes to national goals and objectives; by establishing future goals and priorities; by predicting the likely impacts of alternative policies; and by reducing research management risks.

The goal of this paper is to highlight the importance of systematic procedures and information collection in decision-making for biotechnology. To achieve the goal, this paper will first delineate the different levels of decision-making at issue. It will then outline a decision-making procedure and, finally, will present current Intermediary Biotechnology Service (IBS) activities that contribute vital information to enhance strategic thinking and decisions of National Agricultural Research Systems (NARs) on biotechnology.

Levels of Decision-Making

Scientific Project Level

Users/Consumers: Even though most initial research decisions are based on technical feasibility, demand studies for biotechnologically-derived products must be conducted. With increased accountability for research, managers need information on market potential and chances of nonacceptance. At the scientific project level, therefore, research on willingness to consume, adopt, and pay for potential products has to be conducted. User/consumer-related research is routinely conducted by the private sector because their tolerance for product failure is much lower.

In times of tight resources, the public sector research system should also be conducting demand studies (e.g., contingent valuation) to assist in prioritizing the research agenda and to focus on areas that give the greatest return to stakeholders. For export products, demand studies should be assessed for those export markets. Different cultures and taste preferences influence the value one places on goods and services. It is essential to have market intelligence on these consumption and purchasing decisions to have an advantage in technology design and afterwards in pricing strategies.

Benefit/Cost: Other important information concerns the benefit/cost ratios of various biotechnologies. If estimations are conducted with appropriate methodologies, they will be very useful for guiding biotechnology research decisions.

National Policy and Planning Level

To evaluate economic growth, socioeconomic research will evaluate the potential for income generation and employment opportunities. For biotechnology in particular the prospects for facilitating higher productivity and better quality in nontraditional commodities are promising.

There are a number of income-distribution issues of importance in considering biotechnology research. One is the impact on the current structure of the industry, especially concerning size of exploitations and employment. Other issues related to equity are gender, size and quality of farm resources, region, staple versus cash crop, etc.

International Level

The potential upheaval caused by biotechnology makes it imperative for countries to monitor the world market closely. Selecting the types of information to be gathered, however, is a challenge. Countries that are export-oriented need information on public acceptance of biotechnology products with modified genetic construct in key export markets. Information of this nature is gaining importance as public acceptance is playing an increasing role in defining feasible technological innovations. Because information is so easily transmitted, we must not overlook the power of external influence on local users and consumers even though countries differ in culture and economic opportunities.

Actions of private research organizations, such as multinational enterprises, will have an impact on national goals and objectives. Technologies that require more commercial inputs and less labour, for example (such as herbicide-resistant crops), have a direct impact on the income distribution of a country. Documenting biotechnology developments in other countries could assist in the selection of the most appropriate technologies to adopt or to develop. Determining whether or when to include biotechnology in national research programs requires careful consideration. Global intelligence information can improve decisions. Because economic competition is inherently based on the exploitation of advantages over competitors, information is an essential input to develop strategies for self-preservation. Without new technologies and good information the prospects for economic returns on development investments in any country are grim.

Decision-Making Procedure for Biotechnology Research

The Intermediary Biotechnology Service (IBS) approaches the decision-making process for biotechnology in the context of the objectives established for national agricultural research. As such, biotechnology is viewed as an enabling tool that could better assist in meeting those goals and objectives. Determining strategies, priorities, and policies relevant to biotechnology, therefore, relies on a firm understanding of national goals and objectives, as well as the information and technical needs specific to biotechnology. Coupling this information with the relevant socioeconomic analyses and considerations is then accomplished through the following six steps.

Procedure for Integrating Impact Assessment into the Decision-Making Proces

Step 2. Defining Research Objectives In this step, the research objectives need to be defined according to the goals and objectives established in Step 1. There are no set limits for what should or should not be included in the decisions, however, the scope of enquiry is limited (aside from researchers' productivity) by the demands of the client or sponsors, by the deadline set, and by the amount of money available (Paschen and Gressen 1974). It is important that research hypotheses and objectives are clearly delineated reflecting the scope and types of technology impacts to be assessed. This step should include decision-makers, sociologists, economists, and interest group representatives.

Step 3. Defining Feasible Technologies Here it is important to include feasible technologies that could potentially contribute to the goals and objectives. It is important that technologies not be eliminated based on a single criterion (e.g., yield). Instead, judgment should be reserved until all the technologies have been evaluated against all the criteria. This step should include researchers and scientists.

Step 4. Deriving Measurement Standards for Criteria After defining the feasible technologies, measurement standards have to be derived using criteria that allow for objective and systematic comparisons (Janssen 1994). There are two problems related to this point. One is that ex-ante impacts are difficult to quantify and the other is that the advancement of technology assessment lags behind the actual technology generation. Particularly when it involves public acceptance and environmental and perceived health risks, more efforts are needed to develop methodologies to quantify these social values. The difficulty in the quantification process is that it becomes more complex as we move away from direct impacts to indirect impacts.

Another challenge is to determine the limits of the technological impact in terms of temporal and spatial distribution. According to Lord Kelvin (Bohn 1994) in 1890:

When you can measure what you are speaking about, and expressing it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind ...

Step 5. Performance Assessment of Technology Alternatives Once measurement standards have been derived, data can be collected for performance assessment. Performance assessment can be conducted by evaluating how the alternatives affect the chosen criteria. Predictions on each criteria should be made with practical assumptions on the state of other factors that influence performance. A word of caution: forecasts of impacts are only as good as the predictions we make regarding expected outcomes and future value standards.

Each step of the process should be transparent to avoid problems with interest groups and their value judgments. Also, the assessment has to be argumentative, i.e., in the course of these processes, new issues, alternatives, and actions may continually crop up that require reassessment based on different assumptions.

This step should include economists, political scientists, sociologists, and statisticians. Because there are a number of research objectives and the measurement standards for each are different, a simple assessment method may be required to evaluate against all criteria. If one research objective is more important than another, a weighing scheme might be useful to rank the technologies. It is imperative in this step that all those who are affected be involved.

Step 6. Approval and Implementation After the assessment has been subjected to peer and other expert evaluation, the findings should be presented to the decision-makers and to a wider audience. Public scrutiny is crucial to form solutions based on a consensus that reflects society's values.

Table 1 illustrates the way in which sequential steps could be applied to biotechnology program priority setting and planning.

Click here to view Table 1

IBS Activities

IBS Directory of Expertise

In addition, the database is structured such that aggregate analysis of its information can be undertaken, with searches possible by collaborating countries as well as by the technical details of international biotechnology efforts. Such a tool is valuable when looking at investments and decisions made by the international donors and their effect on and relation to national program needs. Much information remains to be extracted from this data, including an analysis of how socioeconomic considerations are being undertaken by the programs represented.

IBS/ISNAR Research Reports and Policy Seminars

There are a number of issues to be considered when integrating biotechnology into any research program. When is the most opportune time for a country to enter into the biotechnology field? What technique and species should a country be engaged in? What are the costs and benefits of the various biotechnology activities? The ability to derive answers to the above issues would enhance the probability of successful integration of biotechnology programs. A survey was conducted in April 1995 to gather some financial and technical data on existing biotechnology projects from participants attending an IBS/ISNAR-sponsored regional policy seminar on planning, priorities, and policies for agricultural biotechnology in sub-Saharan Africa. A summary of the findings will be found in the forthcoming proceeding from the IBS/ISNAR regional seminar on Planning Priorities and Policies for Agricultural Biotechnology.

Commissioned Reports

The cocoa report argues that an approach called the Policy Analysis Matrix (PAM) developed by Monke and Pearson (1989) to analyze the impact of government policy on efficiency and competitiveness of agricultural production systems could also be "...particularly well suited to empirical analysis of technological change." The theoretical framework of the PAM is a partial equilibrium model and can be seen as an expansion of social benefit–cost analysis. Its basic structure is a matrix that distinguishes between private and social profitability. The first refers to the profits of an agricultural production system of the producer, whereas the second reveals the comparative advantage for the country.

Private profits are important for the analysis of adoption behaviour of producers regarding new technologies as they indicate responsiveness to the provided incentives. Social profits are a measure for the efficiency of a production system. Comparisons of two budgets (with and without the technology under consideration) give the necessary information about the impact on private profits and other economic measures such as the change in input requirement or in comparative advantage.

In addition, the PAM approach was originally developed for the analysis of agricultural policy to provide results on the distortions of national agricultural factor and product markets and their impact with respect to the adoption of new technologies. For example, the introduction of a particular biotechnological innovation in a production system could significantly improve the comparative advantage of a country (measured as social profitability in the PAM matrix) but, at the same time, the profits for the producers (measured as a private profitability) could deteriorate because of the distorted cost, and/or price structure leading to nonadoption of this new technology. The PAM approach, therefore, can be used to generate results showing the extent of trade-off between efficiency and nonefficiency objectives according to the priorities of the country.

As the potential biotechnological change will only occur in the future, assumptions on exogenous prices and costs and with various social values have to be made for appropriate assessments of its impact. It is critical, therefore, that sensitivity analysis be conducted to test the robustness of any PAM results.

Summary

References

• Bohn, R.E. 1994. Measuring and managing technological knowledge. Sloan Management Review, Fall.

• Braunschweig, T.; Gotsch, N. 1995. New biotechnology and competitiveness: The case of cocoa. Guidelines for assessing the potential economic impact of future biotechnology developments on national cocoa production, April. (Forthcoming)

• Busch, L. 1994. Socioeconomic analysis of biotechnology: A concept paper for IBS. Department of Sociology, Michigan State University, East Lansing, MI, US.

• Cohen, J.I.; Komen, J. 1994. Biotechnology priorities, planning, and policies. A framework for decision-making. A biotechnology research management study. International Service for National Agricultural Research (ISNAR), ISNAR Research Report No. 6. The Hague, Netherlands.

• _____ 1995. Priority setting and program development in biotechnology. Paper prepared for the second conference on agricultural biotechnology, Jakarta, Indonesia. IBS/ISNAR, The Hague, Netherlands. (Forthcoming)

• Janssen, W. 1994. Biotechnology priority setting in the context of national objectives: State of the art. Paper presented at Asia regional seminar on planning, priorities and policies for agricultural biotechnology, Singapore. IBS/ISNAR, The Hague, Netherlands.

• Monke, E.A.; Pearson, S.R. 1989. The policy analysis matrix for agricultural development. Cornell University Press, Ithaca and London, UK.

• Paschen, H.; Gresser, K. 1974. Some remarks and proposals concerning the planning and performance of technology assessment studies. Research Policy 2, 306–321.

• Sinclair, C. 1971/1972. The incorporation of health and welfare risks into technological forecasting. Research Policy, 1, 40–58.

• Solleiro, J.S.; Quintero, R. 1993. Research and development priorities in agro-food biotechnology. International Development Research Centre (IDRC), Ottawa, ON, Canada.

Document(s) 12 of 14