Good Governance Principles

Good Governance Principles Governance is the deliberate and conscious management of regime structures for enhancing the public realm.Governance can be viewed from social, political and economic perspectives. Indeed, good governance is pivotal to the development process.Development linked governance has been an issue much debated in the contemporary world. The term governance has taken a much wider meaning and is no longer restricted to rule or administration but is used in a broader sense to imply the manner in which power is exercised. Since power can be exercised in any manner as desired, certain principles would be required in order to judge whether the discourse of the power has been made as per certain standards and norms. Such judgment can be based on several criteria participation of citizens, upholding the rule of law, transparency of the system, responsiveness of the authority, consensus oriented policy, equity and inclusiveness of the policy, accountability of the system, strategic vision of the aut hority, etc. At the end of the Cold War era, the term good governance came into circulation which signified the prescriptions by donor agencies for carrying out economic and political reforms by the recipient countries. These prescriptions were presented by international donor agencies as conditionalities and were expected to be met with compliance.  [4]   The World Bank defines good governance as ..the one epitomized by predictable, open, and enlightened policy-making, a bureaucracy imbued with a professional ethos acting in furtherance of the public good, the rule of law, transparent processes, and a strong civil society participating in public affairs. Poor governance (on the other hand) is characterized by arbitrary policy making, unaccountable bureaucracies, un-enforced or unjust legal systems, the abuse of executive power, a civil society unengaged in public life and widespread corruption.  [5]   The Government of Maharashtra Report on Good Governance sought to elucidate on the concept of good governance.  [6]  At the outset in the Mission Statement of the report, it clarified that the concept of good governance was much larger than mere administrative reforms as understood in the conventional sense of the term as it covered more ground and substance. Good governance has much to do with the ethical grounding of governance and therefore must be evaluated with reference to specific norms and objectives as may be laid down. Apart from looking at the functioning of the given segment of the society from the point of view of its acknowledged stakeholders and beneficiaries and customers and incorporating these perspectives in the course of its actions, it must have firm moorings to certain moral values and principles. As a concept, good governance applies to various and distinct sections of the society; the government, legislature, judiciary, the media, the private sector, the corporate sector, the co-operatives, societies, trusts, organizations and even non-governmental organizations.  [7]  After all, public accountability and transparency are equally relevant for each one of these institutions on which the society derives pillar-strength. Furthermore, only when all these and various other sections of the society conduct their affairs in a socially responsible manner can the objective of achieving larger good for the largest number of people in the society be realized. It must also be mentioned that the foremost test of good governance is the respect for the rule of law. As the often quoted saying goes, the law is supreme and above all its subjects. Governance must always be based on rule of law. Every lawfully established government must govern according to the laws of the land and all its actions must uphold the rule of law and any effort to take the law in ones own hand or to undermine the law by anyone, howsoever high and mighty he may be, must be dealt with speedily, decisively and in an exemplary manner. The Report goes on to observe that it is a matter of great concern that despite over five decades of Independence, it cannot be said with conviction that our governance is based on the rule of law. CHAPTER 2: PRINCIPLES OF GOOD GOVERNANCE 2.1 Principles of Good Governance The pillars of governance include accountability, transparency, predictability and participation these are universally applicable regardless of economic orientation, strategic priorities, or policy choices of the government in question. However, there application must be country-specific and purely based on the economic, social and administrative capacity of the country. The universally accepted characteristics of good governance include participation, rule of law, transparency, responsiveness, equity, inclusiveness, effectiveness, efficiency and accountability.  [8]   The following text shall cover the principles which may be considered as the key principles of good governance in the opinion of the researcher. These key elements have been listed out by the researcher based on their relevance and contribution towards establishing an efficient and objective driven governing authority, covering socio-political and economic considerations. The determinative role that these principles play are supported by the various texts of international governing authorities, like the United Nations, as well as the emphasis laid upon them by the Constitutions of various countries including India. Therefore, these principles are covered not only by hard-law provisions, i.e. legislations, treaties, etc. which make the compliance to such principles mandatory, but also soft-law provisions, i.e. declarations, policies outlining desirable targets, etc. which reflect the consensus of countries and their convergence in thought process vis-à  -vis these principles. (1) Free and Fair Elections Since good governance emphasizes on the significance attached to the right people being involved in the decision making process, a democratic setup where the representatives of the people are in control of the power, ensured by free and fair elections, holds importance towards ensuring good governance. Free and fair elections ensure that the citizens are able to exercise their right to elect their leaders and hence participate in voicing their interests through these leaders. However, such an election process must be free and fair, where the voters have a choice amongst the candidates and the right to the relevant information concerning the candidates in order to elect the leader who according to them could best serve the government. Such elections are open to all persons without discriminating on sex, race or ethnicity and are without interference or coercion by the government.. The right to vote is a constitutionally safeguarded right and is the cornerstone of a democratic society. However, other factors which discussed below are essential to ensure that elections are a means to a democratic society, and not an end by themselves.  [9]   (2) Independent Judiciary The Rule of Law A crucial aspect of the constitutional mechanism is a system of checks and balances that is imposed upon the different organs of the State. While power is granted to the government, its use is overlooked and kept within acceptable limits by the constitutional limits like periodic elections, guarantees of rights, and an independent judiciary which permits the citizens to seek protection of their rights and redress against government actions. In this way, one branch of the government is able to provide accountability for the actions of another. The value attached to an independent judiciary cannot be neglected due to its role in preserving the rule of law.  [10]  The rule of law binds the branches of the government together. It also lays the foundation for the sound establishment of the healthy economic, social and political life. The Courts must uphold the rule of law in the State, fairly and without discrimination, providing equal protection for women and minorities and allow open and fair access to judicial and administrative systems. Political or civil rights must not be denied by reasons of sex, race or ethnicity. Justice should be available for all sections of the society. Good governance requires fair legal frameworks that are enforced impartially. It requires full protection of human rights, particularly those of the minorities. Impartial enforcement of laws requires an independent judiciary and an impartial and incorruptible police force.  [11]   (3) Freedom of Speech Press To function efficiently, a democratic society based on justice must not restrict the free exchange of ideas and information. To achieve this, free and open press and the freedoms of speech and expression are constitutionally safeguarded rights as well to cultivate effective governance. We live in an information driven society, and the access to information provides a vital tool to the public to make informed choices regarding their day to day lives and enables them to participate in the governance process. Such freedoms also serve as a check on the accountability for the government and lets the citizens redress the government for its actions. It facilitates the exchange of political discourse, creating a marketplace of ideas where no view is stifled and the best are chosen.  [12]   (4) Elimination of Corruption Good governance also translates into the elimination of corruption to preserve the integrity of democracy. Governments must strive to rid themselves of bribery as corruption damages economic development and reform, and is an obstacle as far as the ability of developing countries to attract foreign investment is concerned while also hindering the growth of democratic institutions, and concentrating power in the hands of a few. The best way to combat corruption is for governments to be open and transparent. While in certain cases governments have a responsibility to retain secrecy and confidentiality, democratic governments must be sensitive to the citizens right to know. Strong laws against corruption and the presence of law enforcement agencies that work against corruption demonstrate a governments commitment to this principle.  [13]   (5) Investment in People Reaping maximum benefit and managing the limited resources before the country is a task which must be performed by the administration. While following good governance practices, the government must invest in the people to cultivate a human resource base. This means that ample resources must be devoted to preserve the welfare of the citizens, without discrimination, and provide health care, education, etc., and an environment where political, economic and social well being, peace and justice can be achieved.  [14]   (6) Legitimacy Voice All citizens, men and women, must have a voice in the decision making process in good governance compliant State. This may be direct or through legitimate intermediate institutions. Such broad participation is made possible by the freedom of association and expression. Of the principles enumerated thus far, the principle of legitimacy and voice has the strongest claim to universal recognition based on over a half century of United Nations accomplishments in the field of human rights.  [15]  Another facet of good governance is the intention to act on consensus and not on the will of a few, whether strong or weak. This mediates the differing interests to reach a broad consensus on what is in the best interest of the entire society. A long term perspective giving due regard to the holistic effect on the society must be undertaken before the governing authority envisages on a path and focus on sustainable human development. This may include better understanding the historical, cultur al and social contexts of the given society.  [16]   (7) Direction The leaders in particular and the public in general should have a broad and long term perspective on good governance and human development, accompanied with a strong sense of the historical, cultural and social complexities in which that perspective is grounded.  [17]   The leaders and the public should have a broad and long-term perspective on good governance and human development, along with a sense of what is needed for such development. There is also an understanding of the historical, cultural and social complexities in which that perspective is grounded. Governance is thus a checklist of criteria of managing public affairs. As Lewis T. Preston, the World Bank president, categorically stated in hi foreword to Governance and Development, Good governance is an essential complement to sound economic policies. Efficient and accountable management by the public sector and a predictable and transparent policy framework are critical to the efficiency of markets and governments, and hence to economic development.  [18]   (8) Performance Orientation While good governance necessitates the consideration of several other factors, achieving the targets set forth by the government cannot be overlooked. These institutions and processes must attempt to serve all the stakeholders, and produce results that meet the needs while making the best use of the resources.  [19]  The work should always be oriented towards achieving optimal performance. Performance can be divided into two categories responsiveness of the government, and the effectiveness and efficiency of the government. Good governance calls for serving of the stakeholders within a reasonable timeframe which would ensure trust and acceptance of the public. Responsiveness of the government can only be tested if there exists meaningful and serious civil society engagement in the public affairs of the State.  [20]  The concept of efficiency in the context of good governance also covers the sustainable use of natural resources and the protections of the environment. (9) Accountability Information is also associated with the power government exercises. By restricting information, people within government become more powerful that those who are without it. Thus, demand for transparency and information is also about sharing of power. It is possible to misuse power when it is concentrated rather than when it is shared among a broader stream of people. As information grows, the arbitrariness of government tends to reduce.  [21]   Good governance entails the accountability of those who have been entrusted with certain duties and powers. Since the public participates in the decision making through the elected representatives and through the appointed decision makers, these decision makers are accountable to the public for the use of their powers. The level of this accountability may however differ in accordance with the organization in question and the nature of the decision. The private sector and civil society organizations must also be held accountable to the public and their institutional stakeholders. In general, an organization or an institution is accountable to those who will be affected by its decisions or actions.  [22]   Accountability cannot be enforced without transparency and the rule of law. Transparency refers to the taking decisions and enforcing them in accordance with rules and regulations and making the information with regard to such actions accessible for scrutiny by those the decisions affect. In simplistic terms, it means also that sufficient information is provided and that it is provided in easily understandable forms and mediums.  [23]  Transparency depends on the building of a free flow of information. Processes, institutions and information are directly made accessible to those concerned with them and enough information is provided to understand and monitor them.  [24]   (10) Fairness There must prevail a sense of fairness emanating from the decisions of the governing body. The members of the society should feel as equal participants in the society. All persons should be regarded as equals, and certain rights which are considered inalienable to humans must be respected. Discrimination of any kind such as race, color, sex, language, religion, political or other opinion, etc. must not be condoned. Equal opportunity must be given to everyone to improve or maintain their well being. At the same time, certain protected sections of the society must be given special attention if there exists a need for the government to help alleviate their economic, social or political standing. CHAPTER 3 Good Governance in the Indian Context Life of the law is not logic, but experience.  [25]   2.1 Good Governance: Recent Initiatives The pre dominant theme in contemporary debate over administrative reforms in India has been the target of achieving objectives under a regime of good governance. This implies a broader outlook towards management of such matters without exclusively restricting it to public administration. It is suggested that this idea stems from the concept of liberalization which places the individual over collective preferences, and the State shrinks to give place to the market that demands economic efficiency.  [26]   The contemporary efforts towards administrative reforms are not directed against an autonomous State, but instead a bureaucracy that is coming to grips with the changing role of the State. The bureaucracy is itself under an attack; on account of its inefficiency and also because of its association with a political system which has failed to perform, a system which deprived the citizens of their legitimate rights in decision making for far too long.  [27]  Another striking feature of these reforms is their tendency to be more ideologically oriented than before. This context must therefore be kept in mind while debating over the reform initiatives in recent times. The change in the context is primarily seen as an induced effect of the demand generated by the peoples struggle to make the government accountable. It is a change spearheaded by the efforts of the people. It is not a deliberate attempt by a benevolent government to come clean. Kuldeep Mathur makes an interesting observation that the government while reacting to this demand raised by the people has in fact met with resistance from within its own members.  [28]   The Conference of Chief Secretaries on effective and responsive administration in November 1996 gave birth to certain recommendations which were later converted into an Action Plan by the Department of Administrative Reforms and Public Grievances, which also included brainstorming by the Prime Minister, Cabinet Secretary, Chief Ministers and the Chief Secretaries. The Action Plan intends to introduce accountable administration which is effective and speedy in redressing public grievances, empowerment of local bodies, decentralized delivery system, review of laws, transparency and the right to information, code of ethics for civil servants, anti-corruption policies, etc. The central idea behind the action plan seems to be efficiency.  [29]   The Central Government had setup the Working Group on Right to Information and Promotion of Open and Transparent Government in 1997, which observed democracy means choice and a sound and informed choice is possible only on the basis of knowledge. It went on to argue that transparency and openness in the functioning of the government shall have a cleansing effect on the operations of public agencies and approvingly quoted the saying that sunlight is the best disinfectant.  [30]   In May 1997, at the Conference of Chief Ministers, transparency in the government was discussed and a statement issues which provided for an Action Plan for Effective and Responsive government at the Central and State levels, while conceding that the secrecy and lack of openness in transactions had led to widespread corruption. The statement attracted much praise also because it set upon the government 3 months time to ensure easy access to information for the people vis-à  -vis information relating to government activities and decisions, except information which was sensitive in nature. Soon thereafter, political events took over and no progress was made for nearly a decade, much over the 3 month deadline that had been set.  [31]   While the Right to Information Act was introduced in 2005, continuous efforts are underway to introduce more accountability and transparency in the system. While most of the principles of good governance are found in the Indian legal framework in the form of constitutionally guaranteed safeguards, the governance needs to involve the civil society more actively in the decision making and establish the norms of redressal. The lack of transparency, prevalence of corruption, inefficient working and lack of responsiveness continue to be the grey areas. 2.2 Conclusion As a developing country emerging as an economic superpower, India needs to get its act right. Without certain optimum standards of efficiency, the principles of good governance cannot be attained. The peoples movement demanding good governance in India co-relates to the growing unrest in the civil society frustrated with the inefficiency and the opaqueness in the system. The only solution was to re-invent the government, and thus started a chain of events which included the passing of the Right to Information Act as recently as 2005. With the Indian economys growth story making headlines, the country has awakened to the need of the hour on its path to development. The insistence of international institutions like the World Bank that developing countries comply with the principles of good governance has only worked to Indias advantage. While some progress has been made, a lot more still needs to be done. Imbibing the principles of good governance shall ensure that India continues to march towards development, while effectively managing its resources and providing the socio-politico-economic rights that the citizens of this country are entitled to. However, just how effective this approach proves to be shall be determined by the response of the civil society which started this reform movement. CHAPTER 3 CONCLUSION The study of governance opens up new avenues it enables us to wander into intellectual space where we can search for solutions to the problems that have haunted us for far too long. The primary objective of governance is to discuss the role of the government in coping with the public issues and to tackle the myriad predicaments and difficulties that arise from these transactions. It teaches us that means must not be the ends, and both the means and the ends must be duly understood. The study of governance also enables us to effectively factor in the role that must be played by the other players in the arena of governance the role that must be played by the civil society groups and institutions. Governance is an exercise of economic, political and administrative authority for efficiently managing a countrys affairs, at both micro and macro levels, which includes the mechanisms, processes and institutions through which the citizens and civil society groups are able to communicate their interests, make use of their constitutional and legal rights besides meeting their obligations and mediating their differences.  [32]  It is not only desirable, but imperative that governance for development be accountable, participatory, responsive, effective and efficient for promoting the rule of law, safeguarding the interests of citizens and marching towards a holistic development. The principles of good governance are a set of principles which have gained popularity in an almost dogmatic sense. The universal applicability and acceptance of these principles have seen their application reach a new height and there is now a global pressure to conform to these common minimum standards of governance. These principles envisage a model of governance on which the developing countries, which are fast realizing the link between development and efficient governance, seek to fashion their governance on. The driving force behind this changing scenario have been the international institutions pressing for compliance, and the rising peoples movements demanding their legitimate rights to competent governance in an accountable manner. There is a growing sentiment that the convergence over these principles will result in the governments rising above the challenges before them. At the same time, there is caution in the wind. These principles must not be followed as diktats. Their application must be tailored to the specific needs of governance, sensitizing them to the local conditions. This is on account of the socio-politico-economic values that are affected by these principles. Their introduction as a localized experience prevents the alienation of the very people who must reap benefits. Practicing these principles of good and just governance results in a free and open society where people can pursue their hopes and dreams in a healthy and conducive environment. Moreover, robust and open economies would follow which can be trusted by the investors and financial institutions alike, and development shall flourish. It is a matter of strengthening what our Constitution endeavored to provide us. Respecting the human rights; a fruitful partnership between the government and the civil society; efficiency, accountability and transparency in the machinery; performance orientation with strategic vision; useful use of the human resource base and a strong and independent judiciary together they shall prove to be the desired shot in the arm for a re-invented and rejuvenated system of governance. The governance needs to be carried out in a manner that invokes trust and confidence, a manner which convinces the citizens the countrys biggest resources to come forward and fully par ticipate in an enterprise to secure the objectives of development and progress. In the light of what has been discussed above, with special focus on the realization to introduce changed governance practices and the increased restlessness amongst the people in India, it is almost as if a new governance philosophy has emerged. Unlike the traditional public administration systems that focused on bureaucracy and the delivery of public services, the governance model envisages public managers as entrepreneurs of a new, leaner and increasingly privatized government adapting to the practices and values of private businesses.  [33]  The mantra to be followed by the new governance model would be to transform civil services, underlining the reforms as means to (a) reorganize and downsize the government, (b) set-up a performance based organization, (c) adopt private sector management practices and (d) promote customer-orientation of administration.  [34]   For the developing world which is in the grip of serious debt crisis, the World Banks good governance solution with its accompanying micro and macro-accountability formula hold much promise. Institutional capacity building has been the central point of discussion and promotion of sound development management by removing, as far as possible, the possibilities of capture of benefits by the socially powerful is underway.  [35]   There is today an increasing pressure on our political system and the administrative apparatus generated by civil society organizations to share information and make the process of decision-making transparent. There is a shift towards responsive governance. This can be made practically feasible only if the mindset of the politicians and the bureaucrats undergoes a change, and they are receptive to the initiative of sharing information as well as power with the people.  [36]  

Education and Typical Public School

Another problem pestering the quality of Philippine education is the quality and proficiency of the teachers. According to a recent article (Gerochi, 2002), Filipino teachers lack proficiency in English, Science and Mathematics. Many said that these areas should have been trained comprehensively since as teachers, they should be able to teach the students with a more quality for future growth. But with what I see, the teachers have problems of their own. One example, and the most obvious, is the low salary and terrible working condition. Many public school teachers opt to have â€Å"sidelines† during class that sometimes the teacher simply forgets to teach. But who can blame them if their salaries of around 8000-10,000 pesos, plus deductible, who can a teacher provide for his/her family? And with the rising cost of living, these figures are not enough. Others cannot teach well in class because of the ratio of students to a teacher. In a typical public school, in every one teacher there are 50-60 students in a class! The school facilities can also be a factor of the problem. The Philippines, both in private and public, lacks sophisticated laboratories and facilities to cater the needs of the students. For example, many public schools are still lacking the basic computer laboratories and it is so ironic that computer nowadays, computer education is crucial for future Computer Studies student. Without proper training in computer, how can a student be competitive and computer literate? Jose Rizal reminds us how modern and latest technologies are important in a student’s development in his novel El Filibusterismo. Like in the novel, the laboratory equipment are stored shut in a cabinet and never to be used in class because of the insufficient number of equipment. And when it is shown in class, it is presented like a monstrance of a priest! And prophetic as it seems, Rizal’s time is happening all over again in our contemporary times. Lastly, a common problem of our Philippine education is the rising cost of sending a child to school. Private schools charges skyrocketing tuition and miscellaneous fees to a student that parents are having a hard time to cope with the rising cost of education. Even sending a child in a public school doesn’t fare better since even the poorest of the poor cannot afford to send a child in school. I remember vividly a story of a public school teacher with a pupil of him. He said that this student was so poor that teachers pay for everything so she can go to school. The teachers don’t mind this sacrifice because the student is so bright and intelligent. She never went to college after high school since she cannot really afford it anymore. What saddened the teachers is that this student passed UP but with no scholarship. Right now, many see education not as necessity but a luxury they cannot afford (Reyes, 2002). The state of Philippine education is indeed sad and disheartening. We probably are all asking who’s to blame for all this mess. But we cannot simply point finger since we all have responsibilities to solve these problem. The government tries its best to give the country and it seemed not enough. But we should not blame the government entirely since it is just not the government’s problems. It is the problem of each and every one of us. If we want the highest quality of education in the country, we should work together to solve this problem. As a teacher, these problems will be a big cross to bear. But if I can help solve this problem in my own little way, the cross can be lighter and easier to bear. This is the bitter cup of a teacher to bear. But we must remember that the teacher and every one of us will determine the course of our country’s development through education. Even Rizal said that for a country to progress, education is the key to that success. Solving the problems of Philippine education is a long way to go but if we work for the better, we can attain that quality education we all hope for the best.

Decision Analysis

CREATE Research Archive Published Articles & Papers 1-1-1980 Structuring Decision Problems for Decision Analysis Detlof von Winterfeldt University of Southern California, [email  protected] edu Follow this and additional works at: http://research. create. usc. edu/published_papers Recommended Citation von Winterfeldt, Detlof, â€Å"Structuring Decision Problems for Decision Analysis† (1980). Published Articles & Papers. Paper 35. http://research. create. usc. edu/published_papers/35 This Article is brought to you for free and open access by CREATE Research Archive.It has been accepted for inclusion in Published Articles & Papers by an authorized administrator of CREATE Research Archive. For more information, please contact [email  protected] edu. Acta Psychologica 45 (1980) 71-93 0 North-Holland Publishing Company STRUCTURING DECISION PROBLEMS FOR DECISION ANALYSIS * Detlof von WINTERFELDT ** University of Southern California, Los Angeles, CA 90007, USA Structuring decisio n problems into a formally acceptable and manageable format is probably the most important step of decision analysis.Since presently no sound methodology for structuring exists, this step is still an art left to the intuition and craftsmanship of the individual analyst. After introducing a general concept of structuring, this paper reviews some recent advances in structuring research. These include taxonomies for problem identification and new tools such as influence diagrams and interpretative structural modeling. Two conclusions emerge from this review: structuring research is still limited to a few hierarchical concepts and it tends to ignore substantive problem aspects that delineate a problem it its real world context.Consequently structuring research has little to say about distinctions between typical problem classes such as regulation, siting, or budget allocation. As an alternative the concept of â€Å"prototypical decision analytic structures† is introduced. Such st ructures are developed to meet the substantive characteristics of a specific problem (e. g. , siting a specific Liquid Natural Gas plant) but they are at the same time general enough to apply to similar problems (industrial facility siting). As an illustration, the development of a prototypical analytic structure for environmental standard setting is described.Finally, some typical problem classes are examined and some requirements for prototypical structures are discussed. An introduction to problem structuring Decision analysis can be divided into four steps: structuring the problem; formulating inference and preference models; eliciting probabilities and utilities; and exploring the numerical model results. Prac* This research was supported by a grant from the Department of Defense and was monitored by the Engineering Psychology Programs of the Office of Naval Research, under contract # NOOO14-79C-0529.While writing this paper, the author discussed the problem of structuring exte nsively with Helmut Jungermann. The present version owes much to his thought. Please don’t take footnote 3 too seriously. It is part of a footnote war between Ralph Keeney and me. ** Presently with the Social Science Research Institute, University of Southern California, University Park, Los Angeles, CA 90007, (213) 741-6955. 12 D. von Winterfeldt /Structuring decision problems titioners of decision analysis generally agree that structuring is the most important and difficult step of the analysis.Yet, until recently, decision analytic research has all but ignored structuring, concentrating instead on questions of modeling and elicitation. As a result, structuring was, and to some extent still is, considered the ‘art’ part of decision analysis. This paper examines some attempts to turn this art into a science. Trees are the most common decision analytic structures. Decision trees, for example, represent the sequential aspects of a decision problem (see Raiffa 1968 ; Brown et al. 1974). Other examples are goal trees for the representations of values (Keeney and Raiffa 1976) and event trees for the representation f inferential problem aspects (Kelly and Barclay 1973). In fact, trees so much dominate decision analytic structures that structuring is often considered synonymous to building a tree. This paper, however, will adopt a more general notion of decision analytic structuring. According to this notion, structuring is an imaginative and creative process of translating an initially ill-defined problem into a set of welldefined elements, relations, and operations. The basic structuring activities are identifying or generating problem elements (e. g. , events, values, actors, decision alternatives) nd relating these elements by influence relations, inclusion relations, hierarchical ordering relations, etc. The structuring process seeks to formally represent the environmental (objective) parts of the decision problem and the decision makers†™ or experts’ (subjective) views, opinions, and values. Graphs, maps, functional equations, matrices, trees, physical analogues, flow charts, and venn diagrams are all possible problem representations. In order to be useful structures for decision analysis, such representations must facilitate the subsequent steps of modeling, elicitation, and numerical nalysis. Three phases can be distinguished in such a generalized structuring process. In the first phase the. problem is identified. The elements which are generated in this phase are the substantive features of the problem: the decision maker(s); the generic classes of alternatives, objectives, and events; individuals or groups affected by the decision; characteristics of the problem environment. This list is pruned by answering questions such as: what is the purpose of the analysis? For whom is the analysis to be performed? Which alternatives can the decision maker truly control?At this stage only very rough relations betw een problem elements are constructed. Examples include organizational relations D. von Winterfeldt /Structuring decision problems 73 among decision makers, influence relations between classes of actions and events, and rough groupings of objectives. Products of this problem identification step are usually not very formal, and are seldom reported in the decision analytic literature. They may be in the form of diagrams, graphs, or ordered lists. Among the few documented examples are Hogarth et al. (1980) for the problem of city planning and Fischer and von Winterfeldt 1978) for the problem of setting environmental standards. In the second structuring step, an overall analytic structure is developed. The elements generated in this step are possible analytic problem representations. Besides tree structures, these may include more complex structures previously developed for similar problems such as screening structures for siting decisions or signal detection structures for medical decis ion making. Paradigmatic structures of alternative modeling approaches (e. g. , systems dynamics or linear programming) which could fit the problem should also be examined at this step [ 1 I.A creative activity in this structuring phase is to relate and combine part structures, e. g. , simulation structures with evaluation structures, or decision trees of different actors. From the candidate structures and their combinations an overall structure is selected which is judged most representative of the problem and manageable for further modeling and elicitation. Only a handful of analytic structures have been developed which are more complex than decision trees. Gardiner and Ford (in press) combined simulation and evaluation structures.Keeney (in press) developed decision analytic structure for the whole process of siting energy facilities. Von Winterfeldt (1978) constructed a generic structure for regulatory decision making. The third structuring phase coincides with the more traditio nal and limited notion of structuring. In this step the parts of the overall analytic structure are formalized in detail by refining the problem elements and relations identified in the first step. This includes a detailed construction of decision trees, event trees, and goal trees. Linkages between part structures are established, e. g. between simulation and evaluation structures. Decision makers and groups affected by possible decisions are specified together with events or actions linking [l] Although such structures alternatives to decision analytic in the remainder of this paper. structures should be considered, I will ignore 14 D. von Winterfeldt/Structuring decision problems them. Examples of this structuring step can be found in most decision analytic textbooks. This three step structuring process of identifying the problem, developing an analytic structure, and formalizing its detailed content seldom evolves in strict sequence.Instead, the process is recursive, with repeat ed trials and errors. Often the analyst decides on a specific structure and later finds it either unmanageable for modeling or non-representative of the problem. The recognition that a structure needs refmement often follows the final step of decision analysis, if numerical computations and sensitivity analyses point to places that deserve more detailed analysis. Knowing about the recursive nature of the structuring process, it is good decision analysis practice to spend much effort on structuring and to keep an open mind about possible revisions.The above characterization of the structuring process will be used as a format to review the structuring literature. First, the use of problem taxonomies for the step of problem identification is examined. Methods to select analytic approaches are then reviewed as possible aids for the second structuring step. Finally, some recent advances in formalizing part structures are discussed. * Two conclusions emerged from this review and motivated the subsequent sections of this paper: (1) Although structuring research has much to say about analytic distinctions between decision problems and structures (e. . , whether a problem is multiattributed or not), it has little bearing on substantive problem distinction (e. g. , the difference between a typical regulation problem and a typical investment problem). (2) Structuring research is still limited to a few, usually hierarchical concepts and operations. Emphasis is put on simple, operational and computerized structuring. Little effort is spent on creating more complex combinations of structures that represent real problem classes. As an alternative, the concept of prototypical decision analytic structures is introduced.Such structures have more substance and complexity than the usual decision trees or goal trees. They are developed to meet the substantive characteristics of a specific problem, but are at the same time general enough to apply to similar problems. As an illustra tion, IIASA’s [21 development of a prototypical decision analytic [2] International Institute for Applied Systems Analysis, Laxenburg, Austria. D. von Winterfeldt /Structuring decision problems 75 structure for environmental standard setting will be described. Finally, several typical classes of decision problems will be examined and some requirements or prototypical structures will be discussed. Taxonomies for problem identification The taxonomies described in the following typically classify decision problems by analytic categories (e. g. , whether a problem is multiattributed or not) and they attempt to slice the universe of problems into mutually exclusive and exhaustive sets. The purpose of such taxonomies is twofold: to facilitate the identification of an unknown element (e. g. , a medical decision problem) with a class of problems (e:g. , diagnostic problem); and to aid the process of matching classes in the problem taxonomy (e. . , diagnostic problems) with an analyti c approach (e. g. , signal detection structures). Thus, by their own aspiration, problem taxonomies should be useful for the early phases of structuring decision problems. MacCrimmon and Taylor (1975) discuss on a rather general level the relationship between decision problems and solution strategies. Decision problems are classified according to whether they are ill-structured or well-structured, depending on the extent to which the decision maker feels familiar with the initial state of the problem, the terminal state, and the transformations equired to reach a desired terminal state. Three main factors contribute to ill-structuredness: uncertainty, complexity, and conflict. For each category MacCrimmon and Taylor discuss a number of solution strategies. These strategies include, for example, reductions of the perceptions of uncertainty, modeling strategies, information acquisition and processing strategies, and methods for restructuring a problem. Taylor (1974) adds to this class ification scheme four basic types of problems: resource specification, goal specification, creative problems, and well structured problems (see fig. 1).Problem types are identified by the decision maker’s familiarity with the three subparts of the problem. Taylor discusses what types of decision strategies are appropriate for each of these problem categories, for example, brainstorming for creative problems and operations research type solutions for well structured problems. Howell and Burnett (1978) recently developed a taxonomy of tasks 16 D. von Winterfeldt /Structuring Problem Type Initial State decision problems Terminal State Transformation Type 1, Resource Specification Problems UnfamllIar Type 11, Goal Specification Problems Type III, Creative ProblemsType IV, Well-Structured Problems Varies Varies Unfamihar Varies Vanes Familiar Unfamiliar Familiar Fig. 1. Types of problem structures (Taylor 1974). and types of events with the intention of assessing cognitive options for processing probabilistic information for each taxonomy element. Uncertain events are classified according to three dichotomies: frequentistic – not frequentistic; known data generator – unknown data generator; process external – internal to the observer. Task characteristics are complexity, setting (e. g. , real life us. laboratory), span of events, and response mode characteristics. For each vent/task combination Howell and Burnett discuss how different cognitive processes may be operating when making probability judgments. For example, in estimating frequentistic events with unknown data generators, availability heuristics may be operative. Brown and Ulvila (1977) present the most comprehensive attempt yet to classify decision problems. Their taxonomy includes well over 100 possible characteristics. Decision problems are defined according to their substance and the decision process involved. Substantive taxonomic characteristics are mainly derived from th e analytic properties of the situation, i. . , amount and type of uncertainty, and amount D. von Winterfeldt/Structuring decision problems 71 and types of stakes, types of alternatives. Only a few elements of this part of the taxonomy can be directly related to problem content, i. e. , current vs. contingent decision, operating vs. information act. The taxonomic elements of the decision process refer mainly to the constraints of the decision maker, e. g. , reaction time, available resources. The taxonomy by Brown and Ulvila incorporates most previous problem taxonomies which tried to define decision problems by categories derived from decision analysis.These include taxonomies by von Winterfeldt and Fischer (1975), Miller et al. (1976), and Vlek and Wagenaar (1979). To be useful for problem identification, the above taxonomies should lead an analyst to a class of problems which has characteristics similar to the decision problem under investigation. Unfortunately, the existing probl em taxonomies are ill-suited for this purpose, because they use mainly analytic categories to distinguish problems. Such categories are derivatives of the decision analytic models and concepts, rather than characteristics of real world problems. For example, the analytic categorizations f problems into risky vs. riskless classes is based on the distinction between riskless and risky preference models. Analytic categories create more or less empty classes with little or no correspondence to real problems. For example, none of the above taxonomies allows distinguishing between a typical siting problem and a typical regulation problem in a meaningful way. It appears that substantive rather than analytic characteristics identify real problems. Substantive characteristics are generalized content features of the problems belonging to the respective class. For example, a substantive eature of regulation problems is the involvement of three generic decision makers: the regulator, the regula ted, and the beneficiary of regulation. To become useful for problem identification, taxonomies need to include such substantive problem characteristic& Methods for selecting an overall analytic structure Most taxonomies include some ideas or principles for matching lems with analytic structures or models. MacCrimmon and attempted to match their basic type of decision problems with tive solution strategies, Howell and Burnett speculated on which tive processes may be invoked by typical task/event classes in probTaylor ognicogniproba- 18 D. von Winterfeldt /Structuring decision problems bility assessment; von Winterfeldt and Fischer identified for each problem category appropriate multiattribute utility models. But in none of these papers explicit matching principles or criteria for the goodness of a match are given. Rather, matches are created on the basis of a priori reasoning about the appropriateness of a strategy, model, or a cognitive process for a particular class of decision problems. Brown and Ulvila (1977) attempted to make this selection process more explicit by creating an analytic taxonomy in correspondence with the problem taxonomy.The analytic taxonomy classifies the main options an analyst may have in structuring and modeling a decision problem. The taxonomy includes factors such as user’s options (amount to be expended on the analysis), input structure (type of uncertainty), elicitation techniques (type of probability elicitation). These categories identify options, both at a general level (optimization, simulation, and Bayesian inference models) and special techniques (e. g. , reference gambles, or Delphi technique). To match problems with analytic approaches Brown and Ulvila created a third taxonomy, called the â€Å"performance measure taxonomy†.This taxonomy evaluates analytic approaches on attributes like â€Å"time and cost measures†, â€Å"quality of the option generation process†, â€Å"quality of communicat ion or implementation†, etc. Different problem classes have different priority profiles on the performance measure categories. Similarly, different analytic approaches have different scoring profiles on the performance measures. The analytic approach chosen should perform well on the priority needs of a particular problem, Brown and Ulvila discuss the ‘goodness of fit’ of several analytic approaches to a number of decision situations in terms of these performance measures.For example, they argue that a contingency type analysis (an element of the analytic taxonomy) is appropriate for decision problems that occur repeatedly and require a fast response (elements of the decision situation taxonomy) because contingency type analysis allows fast calculations (elements of the performance measure taxonomy). Several authors have developed logical selection schemes, which can identify an appropriate analytic approach or model based on selected MacCrimmon (1973), for exampl e, developed a problem features. sequential method for selecting an appropriate approach for multiattrib&e evaluation.The first question to be answered is whether the purpose of the analysis is normative or descriptive. Further questions D. von Winterfeldt /Structuring decision problems 79 include whether the type of problem has occurred frequently before, if there are multiple decision makers with conflicting preferences, and whether alternatives are available or have to be designed. All questions are of the yes-no type and together create a flow chart for selecting among 19 possible approaches. For example, if the purpose of the analysis is normative, if direct assessments of preferences (e. g. ratings) are valid and reliable, and if the type of problem has frequently occurred before, regression models or ANOVA type approaches would be appropriate. Johnson and Huber (1977) and Kneppreth et al. (1977) discuss a three step procedure for selecting a multiattribute utility assessment approach. In the first step, the characteristics of the multiattribute problem are listed, including discreteness vs. continuity of dimensions, uncertainty vs. no uncertainty, and independence considerations. In the second step the evaluation situation is characterized on the basis of judgments about the task complexity, mount of training required for assessment, face validity required, assessment time, accuracy and flexibility. In the third and final step the profile describing the evaluation problem is compared with a profile characterizing five different generic assessment models or methods. The technique that best matches the situation profile is selected. For example, lottery assessment methods and models would be appropriate if the evaluation problem involves uncertainties, does not require high face validity, and allows for a good amount of training of the assessor. Both the taxonomy riented and the sequential selection methods for matching problems and analysis suffer from c ertain drawbacks. As stated earlier, problem characteristics used in taxonomies typically neglect substantive aspects of the decision problem. Consequently, an analyst may choose an analytic approach based on a match with a spuriously defined problem class. For example, when facing a medical diagnosis problem, an analyst may find that some detailed substantive characteristics of the problem (e. g. , the way doctors process information, the physical format of information, etc. ) suggest a signal detection structure.Yet, as far as I can see, none of the above matching processes would directly lead to such a structure. Advances in formalizing structures Influence diagrams are a recent development in decision analytic structuring (see Miller et al. 1976). Influence diagrams draw a graphical 80 D. von Winterfeldt /Structuring decision problems picture of the way variables in a decision model influence each other, without superimposing any hierarchical structure. For example, a decision v ariable (price) may ‘influence’ a state variable (demand) and thus ‘influence’ a final state (successful introduction of a new product into market). Influence diagrams have been conceived mainly as an initial pre-structuring tool to create a cognitive map of a decision maker’s or expert’s view of a decision problem. In the present stage influence diagrams are turned into hierarchical structures and analyzed with traditional tools. But research is now underway at SRI International on the use of influence diagrams directly in EV or EU computations. Another generalization of the tree approach is Interpretative Structural Modeling (ISM) developed, for example, in Warfield (1974) and Sage (1977). In interpretative structural modeling, matrix and graph heory notions are used to formally represent a decision problem. First, all elements of the problem are listed and an element by element matrix is constructed. The structure of the relationships betwe en elements is then constructed by filling in the matrix with numerical judgments reflecting the strength of the relationship, or by simply making O-l judgments about the existence/non-existence of a relation. Computer programs can then be used to convert the matrix into a graph or a tree that represents the problem. Influence diagrams, value trees, decision trees, and inference trees can all be thought of as special cases of ISM.For example, in value tree construction, the analyst may begin with a rather arbitrary collection of value relevant aspects, attributes, outcomes, targets and objectives. Using alternative semantic labels for the relationships between these elements (e. g. , ‘similar’, ‘part of’), an element by element matrix can be filled. Finally, the analyst can explore whether a particular relational structure leads to useful goal tree structure. Besides these generalizations of traditional hierarchical structuring tools, several refinements of special structuring techniques have been suggested, particularly for evaluation roblems. Keeney and Raiffa (1976) devoted a whole chapter to the problem of structuring a value tree. They suggest a strategy of constructing a value tree by beginning with general objectives and disaggregating by using a pure explication logic (i. e. , what is meant by this general objective? ). This approach has previously been advocated by Miller (1970) and others. Mannheim and Hall (1967) suggest in addition the possibility of disaggregating general D. van Winterfeldt /Structuring decision problems 81 objectives according to a means-ends logic (how can this general objective be achieved? ).Other disaggregation logics (problem oriented, process oriented, etc. ) could be analyzed in the ISM context. There are a number of papers that suggest more empirical or synthetic approaches to value tree construction. Of particular interest is a repertory grid technique described by Humphreys and Humphreys (1975) and Humphreys and Wisuda (1979). In this procedure similarity and dissimilarity judgments are used to span the value dimensions of alternatives. Several computer aids have been developed recently to aid decision makers or experts in structuring decision problems. Some of these are discussed in Kelly ( 1978), and Humphreys (1980).These aids typically rely on empty structuring concepts (decison trees, value trees, inference trees, or influence diagrams) and they guide the decision maker/expert in the analytic formulation of his/her problem. Special aids are OPINT for moderately complex problems which can easily be formulated into a decision tree or matrix structure, the decision triangle aid for sequential decision problems with a focus on changing probabilities, and EVAL for multiattribute utility problems (Kelly 1978). In addition to these structuring and assessment aids, there are now computerized aids under development xploiting the idea of influence diagrams and fuzzy set theory . Influence diagrams, ISM, and computer aids are indicative of a trend in structuring research and perhaps in decision analysis as a whole. This trend turns the fundamentally empty structures of decision trees, goal trees, and inference trees into more operational, computerized elicitation tools, without adding problem substance. There are clear advantages to such an approach: a wide range of applicability, flexibility, user involvement, speed, limited training, and feedback, to name only a few. It also reduces the demands on the decision analyst’s time.There is, of course, the other extreme, the prestructured, precanned problem specific version of decision analysis applicable to essentially identical situations. A military example is Decisions and Designs Inc. % SURVAV model (Kelly 1978) which applies to routing decisions for ships to avoid detections by satellites. Such a structure and model can routinely be implemented with almost no additional training. In turn it gives u p generalizability. Neither extreme is totally satisfactory. Empty general structures must consider each problem from scratch. Substantive specific struc- 82 D. von Winterfeldt /Structuring ecision problems tures have limited generalizability. The middleground of problem driven but still generalizable structures and models needs to be filled. Problem taxonomies may help here by identifying generic classes of problems. But as was discussed earlier, existing taxonomies are ill equipped for this task since they neglect substantive problem features. The question of filling in the middleground between ‘too general’ structures and ‘too specific’ structures thus becomes a question of searching for generalizable content features of problems that identify generic classes of decisions.These generic classes can then be modelled and structured by â€Å"prototypical decision analytic structures† which are specific enough to match the generalizable problem feature s and general enough to transfer easily to other problems of the same class. At the present stage of research this search process will necessarily be inductive because too little is known about problem substance to develop a problem driven taxonomy and matching analytic structures. An inductive research strategy may attempt to crystallize the generalizable features of a specific application, . or compare a number of similar applications (e. . , with siting problems), or simply use a phenomenological approach to delineate problem classes in a specific application area (e. g. , regulation). In the following two sections some possibilities for developing prototypical decision analytic structures will be discussed. An example of developing a prototypical structure The following example describes the structuring process in the development of a decision aiding system for environmental standard setting and regulation. The work was performed as part of IIASA’s (see fn. 2) standard se tting project (see von Winterfeldt et al. 1978), which had oth descriptive and normative intentions (how do regulators presently set standards? how can analytic models help in the standard setting process? ). Because of this wide approach of the standard setting project, the research group was not forced to produce workable models for specific decision problems quickly. Consequently, its members could afford and were encouraged to spend a substantial amount of time on structuring. Inputs into the structuring process were: – retrospective case studies of specific mental protection agencies; standard processes of environ- national Railway Corporation energylevelmeasure 3 measurefor aeroplanenoise 1 Japanese dB’ ‘SO†, AT SOURCE RULES ROUTING USE SCHEMES SCHEMES LAND Fig. 2. Regulatory alternatives for Shinkansen noise pollution. IMPLEMENTATION AND MEASUREMENT INSTRUMENT /I ALTERNATIVE OF HOUSE IN HOUSE IN FRONT lMldB(A) WCPNLl MEAS†6iiA~â€Å"> 30 †“ d&i) MEASURED LEO’ EQUIP- TION FICA- SPECI- MENT SPE:D CONTROL RES+RlCT TIMES OPERATION 84 D. von Winterfeldt /Structuring decision problems – previous models suggested for standard setting; – field studies of two ongoing standard setting processes (oil pollution and noise standards).In addition, the structuring process benefited much from continuing discussions with leading members of environmental agencies in the United Kingdom, Norway, Japan and the United States. Although the structuring effort was geared towards decision analysis, substantial inputs were given by an environmental economist (D. Fischer), an environmental modeller (S. Ikeda), a game theorist (E. Hopfinger), and two physicists (W. Hafele and R. Avenhaus), all members of IIASA’s standard setting research team. The overall question was: how can standard setting problems best be formulated nto a decision analytic format and model such that the model is specific enough to capture the ma in features of a particular standard setting problem and, at the same time, general enough to apply to a variety of such problems? In other words, what is a prototypical decision analytic structure for standard setting? Since the regulator or regulatory agency was presumed to be the main client of such models, the initial structuring focussed on regulatory alternatives and objectives. In one attempt a wide but shallow alternative tree was conceived which included a variety of regulatory ptions ranging from emission standards, land use schemes, to direct interventions. An example for noise pollution standards is presented in fig, 2. Coupled with an appropriate tree of regulatory objectives, a decision analysis could conceivably be performed by evaluating each alternative with a simple MAU procedure. A possible value tree is presented in fig. 3 for the same noise pollution problem. This simple traditional structure was rejected since regulators seldom have to evaluate such a wide rang e of alternatives and because it does not capture the interaction between the regulators and the regulated.Also, regulators are much concerned about monitoring and implementation of standards, an aspect which a simple MAU structure does not address. The second structure was a narrow but deep decision tree, exemplified in fig. 4 for an oil pollution problem. In addition to the regulator’s alternatives, this tree includes responses of the industry to standards, possible detection of standards violations, and subsequent sanctions. This structure was geared at fine tuning the regulators’ definitions of D. von Winterfeldt /Structuring decision problems 85 of hospitals, schools, retwement homes MINIMIZE f residential life DISTURBANCE other / EEggF M,NIM,zE HEALTH Hearing EFFECTS < PsychologIcal Synergetic (aggravation of existing illness) Investment for pollution equipment MINIMIZE COST ~—–< Operation of pollution eqwpment RAILWAY CORP. OBJECTIVES Speed MAXIMIZ E SERVICE -< Aeliablllty ClXlllOrt wth mtemational regulation CONSISTENCY OF REGULATION with other national â€Å"cise standards (car, mr. other trams) POLITICAL OBJECTIVES -/ Enwonmental policy AGREEMENT POLICY WITH GOVERNMENT Transportation policy t Ewnomtc growih policy Fig. 3. Regulatory objectives for noise pollution control. he standard level (maximum emission, etc. ) and monitoring and sanction schemes, and to assessing environmental impacts. The structure is specific in terms of the regulatory alternatives. But by considering industry responses as random events, and by leaving out responses of environmental groups, it fails to address a major concern of regulatory decision making. The third structure was a three decision maker model, in which the regulator, the industry/developer and the environmentalists/impactees are represented by separate decision analytic models (see von Winterfeldt 1978).A signal detection type model links the regulator’s decision through poss ible detections of violations and sanction schemes to the the industry model. An event tree of pollution generating events and effects links the developer’s decisions to the impactee model (see fig. 5). The model can be run as follows: the regulator’s alternatives are left 86 EPA average UK aver,, UK maximum Norway average DEFINITIONS OF OIL EMISSION STANDARDS parts per million ofoil No pollution – Grawty Separator c&ugated Plate Inter- equipment Gas Flotation Filters ceptrr n ob STANDARD LEVEL in watt r ofoil POLLUTION EQUIPMENT PERFORMANCE o00 patis per milhon in water n First vidabon of No udat#on of standard occurs at tulle DETECTION STATES standard dunng all opemons n t POLLUTION EQUIPMENT DECISION BY THE OIL INDUSTRY PENALTY No pdlution equipment Gravity separator Gas Flotatux corrugated Plate bltw- Pais Filters EQUIPMENT PERFORMANCE per million n Second wdation POLLUTION EQUIPMENT DECISION BY THE OIL INDUSTRY No more vidations DETECTION STATES Find eflect s~ on environment (pdlution levels) FINAL EFFECTS – industry (cost) – regulatlx (political) Fig. 4. Segment of a decision tree for setting oil pollution standards. A standard is usually defined by the number of samples to be taken, how many samples form an average, and how many exemptions from a violation are allowed. For example, the EPA average definition is as follows: four samples are to be taken daily, the average of the four samples may not exceed the standard level (e. g. , 50 ppm) more than twice during any consecutive 30 day period. 87 D. von Winterfeldt /Structuring decision problems REGULATORY 1 DECISION MODEL I U R (0 1 DETECTION OF REGULATION VIOLATION DEVELOPER – SANCTIONS POLLUTION GENERATING EVENTS I IMPACTEE DECISION MODELPOLLUTION EFFECTS Fig. 5. Schematic representation of the regulator-developer-impactee model. 1: variable standard of the regulator d(r): expected utility maximizing treatment decision of the developer a[d(r)]: expected utility maximizing decision of the impactees variable. The developer’s response is optimized in terms of minimizing expected investment, operation, and detection costs or maximizing equivalent expected utilities. Finally, the impactees are assumed to maximize their expected utility conditional on the regulator’s and the developer’s decision. At this point the model stops.The structure only provides for a Pareto optimality analysis of the three expected utilities accruing to the generic decision units. This model allows some detailed analyses of the probabilities and value aspects of the standard setting problem, and it proved feasible in a pilot application to chronic oil discharge standards (see von Winterfeldt et al. 1978). Regulators who were presented with this model, con- 88 D. von Winterfeldt /Structuring decision problems REGULATOR’S CHOICE Fig. 6. Game theoretic structure of the regulation I problem. sidered it meaningful, and it offered several insights into the standard setting problematique.Yet, there was a feeling among analysts and regulators that the static character of the model and the lack of feedback loops required improvement. The final structure considered was a game theoretic extension of the three decision maker model. The structure of the game theoretic model is presented in fig. 6. In this model the standard setting process in explicitly assumed to be dynamic, and all feedbacks are considered. In addition, transitions from one stage to another are probabilistic. The model was applied in a seven stage version in a pilot study of noise standard setting for rapid trains (Hapfinger and von Winterfeldt 1978).The game theoretic model overcomes the criticisms of the static decision analytic model, but in turn it gives up the possibility for fine tuning and detailed modeling of trade-offs and probabilities. Considering such aspects in detail would have made the running of the model impossible. Therefore, relatively arbitrar y (linear) utility functions and simple structures of transition probabilities have to be assumed. Although the appropriateness of the different structures was not explicitly addressed in this study, two main criteria come to mind when judging structures: representativeness of the problem and manageability for further analysis.Each of these criteria can be further broken down. For example, representativeness includes judgments about the adequacy of the structural detail, and coverage of important problem aspects. The overall conclusions of many discussion with regulators, analysts, D. von Winterfeldt /Structuring decision problems 89 industry representatives, and the results of the pilot applications led us to accept the third structure as a prototypical decision analytic structure for relatively routine emission standard setting problems. The model is presently considered for further applications in emission tandard setting and an extension to safety standards will be explored. Tow ards a kit of prototypical decision analytical structures Not every decision analysis can afford to be as broad and time consuming as the previous study. Decision analysis usually has a much more specific orientation towards producing a decision rather than developing a generic structure. Still I think that it would be helpful if analysts were to make an effort in addressing the question of generalizability when modeling a specific problem, and in extracting those features of the problem and the model that are transferable. Such an inductive pproach could be coupled with more research oriented efforts and with examinations of similarities among past applications. Such an approach may eventually fill the middleground between too specific and too general models and structures. But rather than filling this middleground with analytically specific but substantively empty structures and models, it would be filled with prototypical structures and models such as the above regulation model, more refined signal detection models, siting models, etc. In the following, four typical classes of decision problems (siting, contingency planning, budget allocation, and regulation) are examined nd requirements for prototypical structures for these problems are discussed. Facility siting clearly is a typical decision problem. Keeney and other decision analysts have investigated this problem in much detail and in a variety of contexts (see the examples in Keeney and Raiffa 1976). A typical aspect of such siting problems is sequential screening from candidate areas to possible sites, to a preferred set, to final site specific evaluations. Another aspect is the multiobjective nature with emphasis on generic classes of objectives: investment and operating cost, economic benefits, environmental impacts, social impacts, and political onsiderations. Also, the process of organizing, collecting, and evaluating information is similar in many siting decisions. Thus, it should be possible to develop a prototypical structure for facility siting decisions, 90 D. von Winterfeldt /Structuring decision problems simply by assembling the generalizable features of past applications [ 31. Contingency planning is another recurring and typical problem. Decision and Design Inc. addressed this problem in the military context, but it also applies to planning for actions in the case of disasters such as Liquid Natural Gas plant explosions or blowouts from oil platforms.Substantive aspects that are characteristic of contingency planning are: strong central control of executive organs, numerous decisions have to be made simultaneously, major events can drastically change the focus of the problem, no cost or low cost information comes in rapidly, and organizational problems may impede information flows and actions. Although, at first glance, decision trees seem to be a natural model for contingency planning, a prototypical decision model would require modifying a strictly sequential appr oach to accommodate these aspects.For example, the model should be flexible enough to allow for the ‘unforeseeable’ (rapid capacity to change the model structure), it should have rapid information updating facilities without overstressing the value of information (since most information is free), and it should attend to fine tuning of simultaneous actions and information interlinkages. Budget allocation to competing programs is another typical problem. In many such problems different programs attempt to pursue similar objectives, and program mix and balance has to be considered besides the direct benefits of single programs.Another characteristic of budgeting decisions is the continuous nature of the decision variable and the constraint of the total budget. MAU looks like a natural structure for budget allocation decision since it can handle the program evaluation aspect (see Edwards et al. 1976). But neither the balance issue nor the constrained and continuous characte ristics of the budget are appropriately adressed by MAU. A prototypical decision analytic structure would model an evaluation of the budget apportionment, or the mix of programs funded at particular levels.Such a structure would perhaps exploit dependencies or independencies among programs much like independence assumption for preferences. Regulation covers a class of decision problems with a number of recurrent themes: three generic groups involved (regulators, regulated, [,3] I believe that. Keeney’s forthcoming book on siting energy facilities is a major step in that direction. Of. course, it could also be a step in the opposite direction. Or in no direction at all (see also first asterisked footnote at the beginning of the article). D. von Winterfeldt /Structuring decision problems 91 beneficiaries of regulation), importance f monitoring and sanction schemes, usually opposing objectives of the regulated and the benefrciaries of regulation, and typically highly political o bjectives of the regulator. In the previous section, the more specific regulation problem of standard setting was discussed, and a prototypical decision analytic structure was suggested. A decision analytic structure for regulation in general can build on the main features of the standard setting model. This list could be extended to include private investment decisions, product mix selection, resource development, diagnostic problems, etc. But the four examples hopefully re sufficient to demonstrate how prototypical decision analytic structuring can be approached in general. In my opinion, such an approach to structuring could be at least as useful for the implementation of decision analysis as computerization of decision models. Besides the technical advantages of trahsferability, prototypical decision analytic structures would serve to show that decision analysts are truly concerned about problems. Today decision analysis books have chapters such as ‘simple decisions under uncertainty’ and ‘multiattribute evaluation problems’. I am looking forward to chapters such as ‘siting industrial acilities’, ‘pollution control management’, and ‘contingency planning’. References Brown, R. V. and J. W. Ulvila, 1977. Selecting analytic approaches for decision situations. (Revised edition. ) Vol. I: Overview of the methodology. Technical report no. TR77-7-25, Decisions and Designs, Inc. , McLean, VA. Brown, R. V. , A. S. Kahr and C. Peterson, 1974. Decision analysis for the manager. New York: Holt, Rinehart, and Winston. Edwards, W. , M. Guttentag and K. Snapper, 1976. A decision-theoretic approach to evaluation research. In: E. L. Streuning and M. Guttentag (eds. ), Handbook of evaluation research, I. 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The Mosquito Coast Essay example - 1150 Words

Navigating the Global explores the challenges and complexities confronted by individuals embarking on a quest for a greater meaning in their lives. The concept of globalization is an ever growing understanding of the complexities and challenges of the late 20th to 21st century world where the increase in technology and communication has lead to the homogenization of cultural values. The concept of navigating through these complexities is referred to by critic T. Friedman as â€Å"An inevitable process of western civilization battling forces of primitivism and localism† Which can be seen in the 1981 novel The Mosquito Coast (TMC) by Paul Theroux and the 2007 film Into the wild directed by Sean Penn (ITW) demonstrates the consequences brought by†¦show more content†¦The initial flashback to Chris’ rites of passage highlights the conflicting values imposed upon him by his parents and society† I see them standing at the formal gates of their colleges. The red tiles glinting like bent plates of blood behind his head.† The dark imagery presented by the omniscient narrator along with the cinematograp hy of mortar boards being thrown in the air depicts the inner conflict presents within individuals under the superficial mask of western expectations which results in the Chris’ escape â€Å"into the wild† The challenges faced by navigation of the global through a â€Å"woven world† can be seen in the figure of Allie Fox where manifestations within himself prove to have destructive consequences. Allie’s insistence of being the â€Å"last man† and feeling â€Å"like god† ironically, demonstrates Allie raising himself to a secular figure despite rejecting religion. This superbia is portrayed in the intertextual allusion to Frankstein, assuming God’s role at the ultimate creation â€Å"man is god† as Jeronimo becomes a personified embodiment of Allie’s dream. Allie’s creation of â€Å"Fat boy† an ominous allusion to nuclear destruction â€Å"plants scorched and stems blistered like flesh† highlighting the resultant destruction of â€Å"the forces of western civilization and localism†. Allie’s failure to adopt the local is contrastedShow MoreRelatedEssay on The Mosquito Coast524 Words   |  3 Pages The Mosquito Coast nbsp;nbsp;nbsp;nbsp;nbsp;The Mosquito Coast depicts the story of an unstable, antisocial individual whose unsubstantiable paranoia causes him to dramatically alter the courses of his and other peoples lives. The mans continual fear of a nuclear invasion by an irate, immoral country eventually this man to move himself and his family to a remote jungle area of Honduras where he planned to establish a utopian society of his own design. Some themes that are conveyed throughRead MoreThe Effects Of Malaria On A Global Scale1225 Words   |  5 Pagesareas and/or over a time period. Where malaria occurs is principally reliant on the climate. 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