翻译！求高手翻译德尔菲法文章！~急要！！！
展开全部
The Delphi technique is a method for obtaining forecasts from a panel of independent experts over two or more rounds. Experts are asked to predict quantities. After each round, an administrator provides an anonymous summary of the experts’ forecasts and their reasons for them. When experts’ forecasts have changed little between rounds, the process is stopped and the final round forecasts are combined by averaging. Delphi is based on well-researched principles and provides forecasts that are more accurate than those from unstructured groups (Rowe and Wright 1999, Rowe and Wright 2001).
The technique can be adapted for use in face-to-face meetings, and is then called mini-Delphi or Estimate-Talk-Estimate (ETE). Delphi has been widely used in business.
Free software to support Delphi forecasting and references are available on the Principles of Forecasting site.
[edit] History of the Delphi method
The Delphi method was developed, over a period of years, at the Rand Corporation at the beginning of the cold war to forecast the impact of technology on warfare. [1] A number of events influenced the development.
In 1944, General Arnold ordered the creation of the report for the U.S. Air Force on the future technological capabilities that might be used by the military. Two years later, Douglas Aircraft company started Project RAND to study "the broad subject of inter-continental warfare other than surface".
Different approaches were tried, but the shortcomings of traditional forecasting methods, such as theoretical approach, quantitative models or trend extrapolation, in areas where precise scientific laws have not been established yet, quickly became apparent. To combat these shortcomings, the Delphi method was developed in RAND Corporation during the 1950-1960s (1959) by Olaf Helmer, Norman Dalkey, and Nicholas Rescher.[1]
The Delphi method was used by Rand Experts when they were asked to give their opinion on the probability, frequency and intensity of possible enemy attacks. Other experts could anonymously give feedback. This process was repeated several times till a consensus emerged.
[edit] Role of the facilitator
The person co-ordinating the Delphi method can be known as a facilitator, and facilitates the responses of their panel of experts, who are selected for a reason, usually that they hold knowledge on an opinion or view. The facilitator sends out questionnaires, surveys etc. and if the panel of experts accept, they follow instructions and present their views. Responses are collected and analysed, then common and conflicting viewpoints are identified. If consensus is not reached, the process continues through thesis and antithesis, to gradually work towards synthesis, and building consensus.
[edit] The Delphi method and forecasting
The Delphi method is a systematic interactive forecasting method based on independent inputs of selected experts.
The name "Delphi" derives from the Oracle of Delphi. The authors of the method were not happy with this name, because it implies "something oracular, something smacking a little of the occult", whereas in reality precisely the opposite is involved. The Delphi method recognizes the value of expert opinion, experience and intuition and allows using the limited information available in these forms, when full scientific knowledge is lacking.
Delphi method uses a panel of carefully selected experts who answer a series of questionnaires. Questions are usually formulated as hypotheses, and experts state the time when they think these hypotheses will be fulfilled. Each round of questioning is followed with the feedback on the preceding round of replies, usually presented anonymously. Thus the experts are encouraged to revise their earlier answers in light of the replies of other members of the group. It is believed that during this process the range of the answers will decrease and the group will converge towards the "correct" answer. After several rounds the process is complete and the median scores determine the final answers. From that the road-map or timetables of future developments can be derived.
The following key characteristics of the Delphi method help the participants to focus on the issues at hand and separate Delphi from other methodologies:
Structuring of information flow
Regular feedback
Anonymity of the participants
[edit] Structuring of information flow
The initial contributions from the experts are collected in the form of answers to questionnaires and their comments to these answers. The panel director controls the interactions among the participants by processing the information and filtering out irrelevant content. This avoids the negative effects of face-to-face panel discussions and solves the usual problems of group dynamics.
[edit] Regular feedback
Participants comment on their own forecasts, the responses of others and on the progress of the panel as a whole. At any moment they can revise their earlier statements. While in regular group meetings participants tend to stick to previously stated opinions and often conform too much to group leader, the Delphi method prevents it.
[edit] Anonymity of the participants
Usually all participants maintain anonymity. Their identity is not revealed even after the completion of the final report. This stops them from dominating others in the process using their authority or personality, frees them to some extent from their personal biases, minimizes the "bandwagon effect" or "halo effect", allows them to freely express their opinions, encourages open critique and admitting errors by revising earlier judgments.
[edit] Applications
First applications of the Delphi method were in the field of science and technology forecasting. The objective of the method was to combine expert opinions on likelihood and expected development time, of the particular technology, in a single indicator. One of the first such reports, prepared in 1964 by Gordon and Helmer, assessed the direction of long-term trends in science and technology development, covering such topics as scientific breakthroughs, population control, automation, space progress, war prevention and weapon systems.
Later the Delphi method was applied in other areas, especially those related to public policy issues, such as economic trends, health and education. It was also applied successfully and with high accuracy in business forecasting. For example, in one case reported by Basu and Schroeder (1977), the Delphi method predicted the sales of a new product during the first two years with inaccuracy of 3–4% compared with actual sales. Quantitative methods produced errors of 10–15%, and traditional unstructured forecast methods had errors of about 20%.
[edit] Acceptance
Overall the track record of the Delphi method is mixed. There have been many cases when the method produced poor results. Still, some authors attribute this to poor application of the method and not to the weaknesses of the method itself. It must also be realised that in areas such as science and technology forecasting the degree of uncertainty is so great that exact and always correct predictions are impossible, so a high degree of error is to be expected.
Another particular weakness of the Delphi method is that future developments are not always predicted correctly by iterative consensus of experts, but instead by unconventional thinking of amateur outsiders.
One of the initial problems of the method was its inability to make complex forecasts with multiple factors. Potential future outcomes were usually considered as if they had no effect on each other. Later on, several extensions to the Delphi method were developed to address this problem, such as cross impact analysis, that takes into consideration the possibility that the occurrence of one event may change probabilities of other events covered in the survey. Still the Delphi method can be used most successfully in forecasting single scalar indicators.
Despite these shortcomings, today the Delphi method is a widely accepted forecasting tool and has been used successfully for thousands of studies in areas varying from technology forecasting to drug abuse.
[edit] Delphi applications not aiming at consensus
Traditionally the Delphi method has aimed at a consensus of the most probable future by iteration. The Policy Delphi launched by Murray Turoff instead is a decision support method aiming at structuring and discussing the diverse views of the preferred future. The Argument Delphi developed by Osmo Kuusi focuses on ongoing discussion and finding relevant arguments rather than focusing on the output. The Disaggregative Policy Delphi developed by Petri Tapio uses cluster analysis as a systematic tool to construct various scenarios of the future in the latest Delphi round. The respondent's view on the probable and the preferable future are dealt with as separate cases.
[edit] Directing the flow to a predetermined goal
The Delphi Technique can also be abused to give an appearance of community input when in reality the facilitator is directing the flow to a predetermined goal.
德尔菲法（Delphi method）是对预防政策的评价，审核的一种流行病学方法。
该政策的预防，评价领导小组通过匿名方式对专家们进行几轮征询意见。领导小组对每一轮的专家意见进行汇总整理，并将整理过的材料再寄给每位专家，供专家们分析判断，专家在整理后材料的基础上提出新的论证意见。如此多次反复，意见逐步趋于一致，得到一个比较一致的并且可靠性较大的结论或方案。
德尔菲法是系统分析方法在意见和价值判断领域内的一种有效方法。它突破了传统的数量分析限制，为更合理地制订政策开阔思路。
http://www.istis.sh.cn/updata/editor/UploadFile/20041019131733689.pdf
http://www.istis.sh.cn/updata/editor/UploadFile/20041019131659618.pdf
The technique can be adapted for use in face-to-face meetings, and is then called mini-Delphi or Estimate-Talk-Estimate (ETE). Delphi has been widely used in business.
Free software to support Delphi forecasting and references are available on the Principles of Forecasting site.
[edit] History of the Delphi method
The Delphi method was developed, over a period of years, at the Rand Corporation at the beginning of the cold war to forecast the impact of technology on warfare. [1] A number of events influenced the development.
In 1944, General Arnold ordered the creation of the report for the U.S. Air Force on the future technological capabilities that might be used by the military. Two years later, Douglas Aircraft company started Project RAND to study "the broad subject of inter-continental warfare other than surface".
Different approaches were tried, but the shortcomings of traditional forecasting methods, such as theoretical approach, quantitative models or trend extrapolation, in areas where precise scientific laws have not been established yet, quickly became apparent. To combat these shortcomings, the Delphi method was developed in RAND Corporation during the 1950-1960s (1959) by Olaf Helmer, Norman Dalkey, and Nicholas Rescher.[1]
The Delphi method was used by Rand Experts when they were asked to give their opinion on the probability, frequency and intensity of possible enemy attacks. Other experts could anonymously give feedback. This process was repeated several times till a consensus emerged.
[edit] Role of the facilitator
The person co-ordinating the Delphi method can be known as a facilitator, and facilitates the responses of their panel of experts, who are selected for a reason, usually that they hold knowledge on an opinion or view. The facilitator sends out questionnaires, surveys etc. and if the panel of experts accept, they follow instructions and present their views. Responses are collected and analysed, then common and conflicting viewpoints are identified. If consensus is not reached, the process continues through thesis and antithesis, to gradually work towards synthesis, and building consensus.
[edit] The Delphi method and forecasting
The Delphi method is a systematic interactive forecasting method based on independent inputs of selected experts.
The name "Delphi" derives from the Oracle of Delphi. The authors of the method were not happy with this name, because it implies "something oracular, something smacking a little of the occult", whereas in reality precisely the opposite is involved. The Delphi method recognizes the value of expert opinion, experience and intuition and allows using the limited information available in these forms, when full scientific knowledge is lacking.
Delphi method uses a panel of carefully selected experts who answer a series of questionnaires. Questions are usually formulated as hypotheses, and experts state the time when they think these hypotheses will be fulfilled. Each round of questioning is followed with the feedback on the preceding round of replies, usually presented anonymously. Thus the experts are encouraged to revise their earlier answers in light of the replies of other members of the group. It is believed that during this process the range of the answers will decrease and the group will converge towards the "correct" answer. After several rounds the process is complete and the median scores determine the final answers. From that the road-map or timetables of future developments can be derived.
The following key characteristics of the Delphi method help the participants to focus on the issues at hand and separate Delphi from other methodologies:
Structuring of information flow
Regular feedback
Anonymity of the participants
[edit] Structuring of information flow
The initial contributions from the experts are collected in the form of answers to questionnaires and their comments to these answers. The panel director controls the interactions among the participants by processing the information and filtering out irrelevant content. This avoids the negative effects of face-to-face panel discussions and solves the usual problems of group dynamics.
[edit] Regular feedback
Participants comment on their own forecasts, the responses of others and on the progress of the panel as a whole. At any moment they can revise their earlier statements. While in regular group meetings participants tend to stick to previously stated opinions and often conform too much to group leader, the Delphi method prevents it.
[edit] Anonymity of the participants
Usually all participants maintain anonymity. Their identity is not revealed even after the completion of the final report. This stops them from dominating others in the process using their authority or personality, frees them to some extent from their personal biases, minimizes the "bandwagon effect" or "halo effect", allows them to freely express their opinions, encourages open critique and admitting errors by revising earlier judgments.
[edit] Applications
First applications of the Delphi method were in the field of science and technology forecasting. The objective of the method was to combine expert opinions on likelihood and expected development time, of the particular technology, in a single indicator. One of the first such reports, prepared in 1964 by Gordon and Helmer, assessed the direction of long-term trends in science and technology development, covering such topics as scientific breakthroughs, population control, automation, space progress, war prevention and weapon systems.
Later the Delphi method was applied in other areas, especially those related to public policy issues, such as economic trends, health and education. It was also applied successfully and with high accuracy in business forecasting. For example, in one case reported by Basu and Schroeder (1977), the Delphi method predicted the sales of a new product during the first two years with inaccuracy of 3–4% compared with actual sales. Quantitative methods produced errors of 10–15%, and traditional unstructured forecast methods had errors of about 20%.
[edit] Acceptance
Overall the track record of the Delphi method is mixed. There have been many cases when the method produced poor results. Still, some authors attribute this to poor application of the method and not to the weaknesses of the method itself. It must also be realised that in areas such as science and technology forecasting the degree of uncertainty is so great that exact and always correct predictions are impossible, so a high degree of error is to be expected.
Another particular weakness of the Delphi method is that future developments are not always predicted correctly by iterative consensus of experts, but instead by unconventional thinking of amateur outsiders.
One of the initial problems of the method was its inability to make complex forecasts with multiple factors. Potential future outcomes were usually considered as if they had no effect on each other. Later on, several extensions to the Delphi method were developed to address this problem, such as cross impact analysis, that takes into consideration the possibility that the occurrence of one event may change probabilities of other events covered in the survey. Still the Delphi method can be used most successfully in forecasting single scalar indicators.
Despite these shortcomings, today the Delphi method is a widely accepted forecasting tool and has been used successfully for thousands of studies in areas varying from technology forecasting to drug abuse.
[edit] Delphi applications not aiming at consensus
Traditionally the Delphi method has aimed at a consensus of the most probable future by iteration. The Policy Delphi launched by Murray Turoff instead is a decision support method aiming at structuring and discussing the diverse views of the preferred future. The Argument Delphi developed by Osmo Kuusi focuses on ongoing discussion and finding relevant arguments rather than focusing on the output. The Disaggregative Policy Delphi developed by Petri Tapio uses cluster analysis as a systematic tool to construct various scenarios of the future in the latest Delphi round. The respondent's view on the probable and the preferable future are dealt with as separate cases.
[edit] Directing the flow to a predetermined goal
The Delphi Technique can also be abused to give an appearance of community input when in reality the facilitator is directing the flow to a predetermined goal.
德尔菲法（Delphi method）是对预防政策的评价，审核的一种流行病学方法。
该政策的预防，评价领导小组通过匿名方式对专家们进行几轮征询意见。领导小组对每一轮的专家意见进行汇总整理，并将整理过的材料再寄给每位专家，供专家们分析判断，专家在整理后材料的基础上提出新的论证意见。如此多次反复，意见逐步趋于一致，得到一个比较一致的并且可靠性较大的结论或方案。
德尔菲法是系统分析方法在意见和价值判断领域内的一种有效方法。它突破了传统的数量分析限制，为更合理地制订政策开阔思路。
http://www.istis.sh.cn/updata/editor/UploadFile/20041019131733689.pdf
http://www.istis.sh.cn/updata/editor/UploadFile/20041019131659618.pdf
本回答由提问者推荐
已赞过
已踩过<
评论
收起
你对这个回答的评价是？
展开全部
THE DELPHI METHOD 德尔菲法
Definition and Historical Background
The objective of most Delphi applications is the reliable and creative exploration of ideas or the production of suitable information for decision making. The Delphi Method is based on a structured process for collecting and distilling knowledge from a group of experts by means of a series of questionnaires interspersed with controlled opinion feedback (Adler and Ziglio, 1996). According to Helmer (1977) Delphi represents a useful communication device among a group of experts and thus facilitates the formation of a group judgement. Wissema (1982) underlines the importance of the Delphi Method as a monovariable exploration technique for technology forecasting. He further states that the Delphi method has been developed in order to make discussion between experts possible without permitting a certain social interactive behavior as happens during a normal group discussion and hampers opinion forming. Baldwin (1975) asserts that lacking full scientific knowledge, decision-makers have to rely on their own intuition or on expert opinion. The Delphi method has been widely used to generate forecasts in technology, education, and other fields (Cornish, 1977).
The technology forecasting studies which eventually led to the development of the Delphi method started in 1944. At that time General Arnold asked Theodor von Karman to prepare a forecast of future technological capabilities that might be of interest to the military (Cornish, 1977). Arnold got the Douglas Aircraft company to establish in 1946 a Project RAND (an acronym for Research and Development) to study the "broad subject of inter-continental warfare other then surface." In 1959 Helmer and fellow RAND researcher Rescher published a paper on "The Epistemology of the Inexact Sciences," which provide a philosophical base for forecasting (Fowles, 1978). The paper argued that in fields that have not yet developed to the point of having scientific laws, the testimony of experts is permissible. The problem is how to use this testimony and, specifically, how to combine the testimony of a number of experts into a single useful statement. The Delphi method recognizes human judgement as legitimate and useful inputs in generating forecasts. Single experts sometimes suffer biases; group meetings suffer from "follow the leader" tendencies and reluctance to abandon previously stated opinions (Gatewood and Gatewood, 1983, Fowles, 1978). In order to overcome these shortcomings the basic notion of the Delphi method, theoretical assumptions and methodological procedures developed in the 1950s and 1960s at the RAND Corporation. Forecasts about various aspect of the future are often derived through the collation of expert judgement. Dalkey and Helmer developed the method for the collection of judgement for such studies (Gordon and Hayward, 1968).
Fowles (1978) asserts that the word Delphi refers to the hallowed site of the most revered oracle in ancient Greece. Forecasts and advices from gods were sought through intermediaries at this oracle. However Dalkey (1968) states that the name "Delphi" was never a term with which either Helmer or Dalkey (the founders of the method) were particularly happy. Dalkey (1968) acknowledged that it was rather unfortunate that the set of procedures developed at the RAND Corporation, and designed to improve methods of forecasting, came to be known as "Delphi". He argued that the term implies "something oracular, something smacking a little of the occult", whereas, as a matter of fact, precisely the opposite is involved; it is primarily concerned with making the best you can of a less than perfect kind of information.
One of the very first applications of the Delphi method carried out at the RAND Corporation is illustrated in the publication by Gordon and Helmer (1964). Its aim was to assess the direction of long-range trends, with special emphasis on science and technology, and their probable effects on society. The study covered six topics: scientific breakthroughs; population control; automation; space progress; war prevention; weapon systems (Gordon and Helmer, 1968). The first Delphi applications were in the area of technological forecasting and aimed to forecast likely inventions, new technologies and the social and economic impact of technological change (Adler and Ziglio, 1996). In terms of technology forecasting, Levary and Han (1995) state the objective of the Delphi method as to combine expert opinions concerning the likelihood of realizing the proposed technology as well as expert opinions concerning the expected development time into a single position. When the Delphi method was first applied to long-range forecasting, potential future events were considered one at a time as though they were to take place in isolation from one another. Later on, the notion of cross impacts was introduced to overcome the shortcomings of this simplistic approach (Helmer, 1977).
According to Wissema (1982), unfortunately the Delphi method is also sometimes used for a normal inquiry among a number of experts. Delphi has found its way into industry, government, and finally, academe. It has simultaneously expanded beyond technological forecasting (Fowles, 1978). Since the 1950s several research studies have used the Delphi method, particularly in public health issues (such as, policies for drug use reduction and prevention of AIDS/HIV) and education areas (Adler and Ziglio, 1996; Cornish, 1977).
The Basics of the Delphi Method
The Delphi method is an exercise in group communication among a panel of geographically dispersed experts (Adler and Ziglio, 1996). The technique allows experts to deal systematically with a complex problem or task. The essence of the technique is fairly straightforward. It comprises a series of questionnaires sent either by mail or via computerized systems, to a pre-selected group of experts. These questionnaires are designed to elicit and develop individual responses to the problems posed and to enable the experts to refine their views as the group’s work progresses in accordance with the assigned task. The main point behind the Delphi method is to overcome the disadvantages of conventional committee action. According to Fowles (1978) anonymity, controlled feedback, and statistical response characterize Delphi. The group interaction in Delphi is anonymous, in the sense that comments, forecasts, and the like are not identified as to their originator but are presented to the group in such a way as to suppress any identification.
In the original Delphi process, the key elements were (1) structuring of information flow, (2) feedback to the participants, and (3) anonymity for the participants. Clearly, these characteristics may offer distinct advantages over the conventional face-to-face conference as a communication tool. The interactions among panel members are controlled by a panel director or monitor who filters out material not related to the purpose of the group (Martino, 1978). The usual problems of group dynamics are thus completely bypassed. Fowles (1978) describes the following ten steps for the Delphi method:
Formation of a team to undertake and monitor a Delphi on a given subject.
Selection of one or more panels to participate in the exercise. Customarily, the panelists are experts in the area to be investigated.
Development of the first round Delphi questionnaire
Testing the questionnaire for proper wording (e.g., ambiguities, vagueness)
Transmission of the first questionnaires to the panelists
Analysis of the first round responses
Preparation of the second round questionnaires (and possible testing)
Transmission of the second round questionnaires to the panelists
Analysis of the second round responses (Steps 7 to 9 are reiterated as long as desired or necessary to achieve stability in the results.)
Preparation of a report by the analysis team to present the conclusions of the exercise
Delbecq et al., (1975) argue that the most important issue in this process is the understanding of the aim of the Delphi exercise by all participants. Otherwise the panelists may answer inappropriately or become frustrated and lose interest. The respondents to the questionnaire should be well informed in the appropriate area (Hanson and Ramani, 1988) but the literature (Armstrong, 1978; Welty, 1972) suggest that a high degree of expertise is not necessary. The minimum number of participants to ensure a good group performance is somewhat dependent on the study design. Experiments by Brockhoff (1975) suggest that under ideal circumstances, groups as small as four can perform well.
Before deciding whether or not the Delphi method should be used, it is very important to consider thoroughly the context within which the method is to be applied (Delbecq et al. 1975). A number of questions need to be asked before making the decision of selecting or ruling out the Delphi technique (Adler and Ziglio, 1996):
What kind of group communication process is desirable in order to explore the problem at hand?
Who are the people with expertise on the problem and where are they located?
What are the alternative techniques available and what results can reasonably be expected from their application?
Only when the above questions are answered can one decide whether the Delphi method is appropriate to the context in which it will be applied. Adler and Ziglio (1996) further claim that failure to address the above questions may lead to inappropriate applications of Delphi and discredit the whole creative effort.
The outcome of a Delphi sequence is nothing but opinion. The results of the sequence are only as valid as the opinions of the experts who made up the panel (Martino, 1978). The panel viewpoint is summarized statistically rather than in terms of a majority vote.
The Delphi method has got criticism as well as support. The most extensive critique of the Delphi method was made by Sackman (1974) who criticizes the method as being unscientific and Armstrong (1978) who has written critically of its accuracy. Martino (1978) underlines the fact that Delphi is a method of last resort in dealing with extremely complex problems for which there are no adequate models. Helmer (1977) states that sometimes reliance on intuitive judgement is not just a temporary expedient but in fact a mandatory requirement. Makridakis and Wheelright (1978) summarize the general complaints against the Delphi method in terms of (a) a low level reliability of judgements among experts and therefore dependency of forecasts on the particular judges selected; (b) the sensitivity of results to ambiguity in the questionnaire that is used for data collection in each round; and (c) the difficulty in assessing the degree of expertise incorporated into the forecast. Martino (1978) lists major concerns about the Delphi method:
Discounting the future: Future (and past) happenings are not as important as the current ones, therefore one may have a tendency to discount the future events.
The simplification urge: Experts tend to judge the future of events in isolation from other developments. A holistic view of future events where change has had a pervasive influence cannot be visualized easily. At this point cross-impact analysis is of some help.
Illusory expertise: some of the experts may be poor forecasters. The expert tends to be a specialist and thus views the forecast in a setting which is not the most appropriate one.
Sloppy execution: there are many ways to do a poor job. Execution of the Delphi process may loose the required attention easily.
Format bias: it should be recognized that the format of the questionnaire may be unsuitable to some potential societal participants.
Manipulation of Delphi: The responses can be altered by the monitors in the hope of moving the next round responses in a desired direction.
Goldschmidt (1975) agrees that there have been many poorly conducted Delphi projects. However, he warns that it is a fundamental mistake to equate the applications of the Delphi method with the Delphi method itself, as too many critics do. There is, in fact, an important conceptual distinction between evaluating a technique and evaluating an application of a technique.
On the other hand there have been several studies (Ament, 1970; Wissema, 1982; Helmer, 1983) supporting the Delphi method. A study conducted by Milkovich et al. (1972) reports the use of the Delphi method in manpower forecasting. The results of the comparison indicated high agreement between the Delphi estimate and the actual number hired and less agreement between quantitative forecasts and the number hired. Another study by Basu and Schroeder (1977) reports similar results in a general forecasting problem. They compared Delphi forecasts of five-year sales with both unstructured, subjective forecasts and quantitative forecasts that used regression analyses and exponential smoothing. The Delphi forecasting consisted of three rounds using 23 key organization members. When compared against actual sales for the first two years, errors of 3-4% were reported for Delphi, 10-15% for the quantitative methods, and of approximately 20% for the previously used unstructured, subjective forecasts.
In general, the Delphi method is useful in answering one, specific, single-dimension question. There is less support for its use to determine complex forecasts concerning multiple factors. Such complex model building is more appropriate for quantitative models with Delphi results serving as inputs (Gatewood and Gatewood, 1983). This point is supported by Gordon and Hayward (1968) who claim that the Delphi method, based on the collation of expert judgement, suffers from the possibility that reactions between forecasted items may not be fully considered. The need for the cross impact matrix method of forecasting integrated with the Delphi method is pointed out by many researchers (Gordon and Hayward, 1968; Gatewood and Gatewood, 1983; Adler and Ziglio, 1996). An improvement in forecasting reliability over the Delphi method was thought to be attainable by taking into consideration the possibility that the occurrence of one event may cause an increase or decrease in the probability of occurrence of other events included in the survey (Helmer, 1978). Therefore cross impact analysis has developed as an extension of Delphi techniques.
Definition and Historical Background
The objective of most Delphi applications is the reliable and creative exploration of ideas or the production of suitable information for decision making. The Delphi Method is based on a structured process for collecting and distilling knowledge from a group of experts by means of a series of questionnaires interspersed with controlled opinion feedback (Adler and Ziglio, 1996). According to Helmer (1977) Delphi represents a useful communication device among a group of experts and thus facilitates the formation of a group judgement. Wissema (1982) underlines the importance of the Delphi Method as a monovariable exploration technique for technology forecasting. He further states that the Delphi method has been developed in order to make discussion between experts possible without permitting a certain social interactive behavior as happens during a normal group discussion and hampers opinion forming. Baldwin (1975) asserts that lacking full scientific knowledge, decision-makers have to rely on their own intuition or on expert opinion. The Delphi method has been widely used to generate forecasts in technology, education, and other fields (Cornish, 1977).
The technology forecasting studies which eventually led to the development of the Delphi method started in 1944. At that time General Arnold asked Theodor von Karman to prepare a forecast of future technological capabilities that might be of interest to the military (Cornish, 1977). Arnold got the Douglas Aircraft company to establish in 1946 a Project RAND (an acronym for Research and Development) to study the "broad subject of inter-continental warfare other then surface." In 1959 Helmer and fellow RAND researcher Rescher published a paper on "The Epistemology of the Inexact Sciences," which provide a philosophical base for forecasting (Fowles, 1978). The paper argued that in fields that have not yet developed to the point of having scientific laws, the testimony of experts is permissible. The problem is how to use this testimony and, specifically, how to combine the testimony of a number of experts into a single useful statement. The Delphi method recognizes human judgement as legitimate and useful inputs in generating forecasts. Single experts sometimes suffer biases; group meetings suffer from "follow the leader" tendencies and reluctance to abandon previously stated opinions (Gatewood and Gatewood, 1983, Fowles, 1978). In order to overcome these shortcomings the basic notion of the Delphi method, theoretical assumptions and methodological procedures developed in the 1950s and 1960s at the RAND Corporation. Forecasts about various aspect of the future are often derived through the collation of expert judgement. Dalkey and Helmer developed the method for the collection of judgement for such studies (Gordon and Hayward, 1968).
Fowles (1978) asserts that the word Delphi refers to the hallowed site of the most revered oracle in ancient Greece. Forecasts and advices from gods were sought through intermediaries at this oracle. However Dalkey (1968) states that the name "Delphi" was never a term with which either Helmer or Dalkey (the founders of the method) were particularly happy. Dalkey (1968) acknowledged that it was rather unfortunate that the set of procedures developed at the RAND Corporation, and designed to improve methods of forecasting, came to be known as "Delphi". He argued that the term implies "something oracular, something smacking a little of the occult", whereas, as a matter of fact, precisely the opposite is involved; it is primarily concerned with making the best you can of a less than perfect kind of information.
One of the very first applications of the Delphi method carried out at the RAND Corporation is illustrated in the publication by Gordon and Helmer (1964). Its aim was to assess the direction of long-range trends, with special emphasis on science and technology, and their probable effects on society. The study covered six topics: scientific breakthroughs; population control; automation; space progress; war prevention; weapon systems (Gordon and Helmer, 1968). The first Delphi applications were in the area of technological forecasting and aimed to forecast likely inventions, new technologies and the social and economic impact of technological change (Adler and Ziglio, 1996). In terms of technology forecasting, Levary and Han (1995) state the objective of the Delphi method as to combine expert opinions concerning the likelihood of realizing the proposed technology as well as expert opinions concerning the expected development time into a single position. When the Delphi method was first applied to long-range forecasting, potential future events were considered one at a time as though they were to take place in isolation from one another. Later on, the notion of cross impacts was introduced to overcome the shortcomings of this simplistic approach (Helmer, 1977).
According to Wissema (1982), unfortunately the Delphi method is also sometimes used for a normal inquiry among a number of experts. Delphi has found its way into industry, government, and finally, academe. It has simultaneously expanded beyond technological forecasting (Fowles, 1978). Since the 1950s several research studies have used the Delphi method, particularly in public health issues (such as, policies for drug use reduction and prevention of AIDS/HIV) and education areas (Adler and Ziglio, 1996; Cornish, 1977).
The Basics of the Delphi Method
The Delphi method is an exercise in group communication among a panel of geographically dispersed experts (Adler and Ziglio, 1996). The technique allows experts to deal systematically with a complex problem or task. The essence of the technique is fairly straightforward. It comprises a series of questionnaires sent either by mail or via computerized systems, to a pre-selected group of experts. These questionnaires are designed to elicit and develop individual responses to the problems posed and to enable the experts to refine their views as the group’s work progresses in accordance with the assigned task. The main point behind the Delphi method is to overcome the disadvantages of conventional committee action. According to Fowles (1978) anonymity, controlled feedback, and statistical response characterize Delphi. The group interaction in Delphi is anonymous, in the sense that comments, forecasts, and the like are not identified as to their originator but are presented to the group in such a way as to suppress any identification.
In the original Delphi process, the key elements were (1) structuring of information flow, (2) feedback to the participants, and (3) anonymity for the participants. Clearly, these characteristics may offer distinct advantages over the conventional face-to-face conference as a communication tool. The interactions among panel members are controlled by a panel director or monitor who filters out material not related to the purpose of the group (Martino, 1978). The usual problems of group dynamics are thus completely bypassed. Fowles (1978) describes the following ten steps for the Delphi method:
Formation of a team to undertake and monitor a Delphi on a given subject.
Selection of one or more panels to participate in the exercise. Customarily, the panelists are experts in the area to be investigated.
Development of the first round Delphi questionnaire
Testing the questionnaire for proper wording (e.g., ambiguities, vagueness)
Transmission of the first questionnaires to the panelists
Analysis of the first round responses
Preparation of the second round questionnaires (and possible testing)
Transmission of the second round questionnaires to the panelists
Analysis of the second round responses (Steps 7 to 9 are reiterated as long as desired or necessary to achieve stability in the results.)
Preparation of a report by the analysis team to present the conclusions of the exercise
Delbecq et al., (1975) argue that the most important issue in this process is the understanding of the aim of the Delphi exercise by all participants. Otherwise the panelists may answer inappropriately or become frustrated and lose interest. The respondents to the questionnaire should be well informed in the appropriate area (Hanson and Ramani, 1988) but the literature (Armstrong, 1978; Welty, 1972) suggest that a high degree of expertise is not necessary. The minimum number of participants to ensure a good group performance is somewhat dependent on the study design. Experiments by Brockhoff (1975) suggest that under ideal circumstances, groups as small as four can perform well.
Before deciding whether or not the Delphi method should be used, it is very important to consider thoroughly the context within which the method is to be applied (Delbecq et al. 1975). A number of questions need to be asked before making the decision of selecting or ruling out the Delphi technique (Adler and Ziglio, 1996):
What kind of group communication process is desirable in order to explore the problem at hand?
Who are the people with expertise on the problem and where are they located?
What are the alternative techniques available and what results can reasonably be expected from their application?
Only when the above questions are answered can one decide whether the Delphi method is appropriate to the context in which it will be applied. Adler and Ziglio (1996) further claim that failure to address the above questions may lead to inappropriate applications of Delphi and discredit the whole creative effort.
The outcome of a Delphi sequence is nothing but opinion. The results of the sequence are only as valid as the opinions of the experts who made up the panel (Martino, 1978). The panel viewpoint is summarized statistically rather than in terms of a majority vote.
The Delphi method has got criticism as well as support. The most extensive critique of the Delphi method was made by Sackman (1974) who criticizes the method as being unscientific and Armstrong (1978) who has written critically of its accuracy. Martino (1978) underlines the fact that Delphi is a method of last resort in dealing with extremely complex problems for which there are no adequate models. Helmer (1977) states that sometimes reliance on intuitive judgement is not just a temporary expedient but in fact a mandatory requirement. Makridakis and Wheelright (1978) summarize the general complaints against the Delphi method in terms of (a) a low level reliability of judgements among experts and therefore dependency of forecasts on the particular judges selected; (b) the sensitivity of results to ambiguity in the questionnaire that is used for data collection in each round; and (c) the difficulty in assessing the degree of expertise incorporated into the forecast. Martino (1978) lists major concerns about the Delphi method:
Discounting the future: Future (and past) happenings are not as important as the current ones, therefore one may have a tendency to discount the future events.
The simplification urge: Experts tend to judge the future of events in isolation from other developments. A holistic view of future events where change has had a pervasive influence cannot be visualized easily. At this point cross-impact analysis is of some help.
Illusory expertise: some of the experts may be poor forecasters. The expert tends to be a specialist and thus views the forecast in a setting which is not the most appropriate one.
Sloppy execution: there are many ways to do a poor job. Execution of the Delphi process may loose the required attention easily.
Format bias: it should be recognized that the format of the questionnaire may be unsuitable to some potential societal participants.
Manipulation of Delphi: The responses can be altered by the monitors in the hope of moving the next round responses in a desired direction.
Goldschmidt (1975) agrees that there have been many poorly conducted Delphi projects. However, he warns that it is a fundamental mistake to equate the applications of the Delphi method with the Delphi method itself, as too many critics do. There is, in fact, an important conceptual distinction between evaluating a technique and evaluating an application of a technique.
On the other hand there have been several studies (Ament, 1970; Wissema, 1982; Helmer, 1983) supporting the Delphi method. A study conducted by Milkovich et al. (1972) reports the use of the Delphi method in manpower forecasting. The results of the comparison indicated high agreement between the Delphi estimate and the actual number hired and less agreement between quantitative forecasts and the number hired. Another study by Basu and Schroeder (1977) reports similar results in a general forecasting problem. They compared Delphi forecasts of five-year sales with both unstructured, subjective forecasts and quantitative forecasts that used regression analyses and exponential smoothing. The Delphi forecasting consisted of three rounds using 23 key organization members. When compared against actual sales for the first two years, errors of 3-4% were reported for Delphi, 10-15% for the quantitative methods, and of approximately 20% for the previously used unstructured, subjective forecasts.
In general, the Delphi method is useful in answering one, specific, single-dimension question. There is less support for its use to determine complex forecasts concerning multiple factors. Such complex model building is more appropriate for quantitative models with Delphi results serving as inputs (Gatewood and Gatewood, 1983). This point is supported by Gordon and Hayward (1968) who claim that the Delphi method, based on the collation of expert judgement, suffers from the possibility that reactions between forecasted items may not be fully considered. The need for the cross impact matrix method of forecasting integrated with the Delphi method is pointed out by many researchers (Gordon and Hayward, 1968; Gatewood and Gatewood, 1983; Adler and Ziglio, 1996). An improvement in forecasting reliability over the Delphi method was thought to be attainable by taking into consideration the possibility that the occurrence of one event may cause an increase or decrease in the probability of occurrence of other events included in the survey (Helmer, 1978). Therefore cross impact analysis has developed as an extension of Delphi techniques.
参考资料： http://www.iit.edu/~it/delphi.html
已赞过
已踩过<
评论
收起
你对这个回答的评价是？
推荐律师服务：
若未解决您的问题，请您详细描述您的问题，通过百度律临进行免费专业咨询
