استفاده از فرآیند تحلیل سلسله مراتبی (AHP) در تجزیه و تحلیل SWOT - یک روش ترکیبی و کاربرد آن برای موارد صدور مجوز جنگلی
کد مقاله | سال انتشار | تعداد صفحات مقاله انگلیسی |
---|---|---|
5312 | 2000 | 12 صفحه PDF |
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Forest Policy and Economics, Volume 1, Issue 1, 1 May 2000, Pages 41–52
چکیده انگلیسی
The present study examines a new hybrid method for improving the usability of SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. A commonly used decision analysis method, the Analytic Hierarchy Process (AHP), and its eigenvalue calculation framework are integrated with SWOT analysis. AHP’s connection to SWOT yields analytically determined priorities for the factors included in SWOT analysis and makes them commensurable. The aim in applying the hybrid method is to improve the quantitative information basis of strategic planning processes. The hybrid method was tested in connection with a Finnish case study on forest certification. In the case study, the results were presented in an illustrative way by utilizing the quantitative information achieved by the hybrid method. The results indicated that certification could be a potential strategic alternative in our case study farm. In addition, the needed pairwise comparisons were found useful, because they force the decision maker to think over the weights of the factors and to analyze the situation more precisely and in more depth.
مقدمه انگلیسی
Forestry and forest planning are influenced by changes within internal and external operational environments. In forest planning, most of the concern has traditionally been placed on the internal environment assuming the external environment to be stable. Recently, applications and methods dealing with changes arising from the external environment have been presented and applied in forest planning. These methods include, for example, connecting the exogenous timber-demand factor and lagged price adjustment to a timber management planning model (Mykkänen, 1995), participatory planning, which means responding to the objectives of external interest groups (e.g. Kangas et al., 1996a and Pykäläinen et al., 1999), and including stochasticity, arising, for example, from changes in timber prices and the level of tree growth, with forest planning by using risk and scenario techniques (e.g. Pukkala and Kangas, 1996). However, common strategic planning approaches are fundamentally based on adjusting to changes in the external environment and there exists a wide range of planning methods that are well-suited for analyzing the interactions of both environments simultaneously. These methods are available and can be further developed to be used in forest planning. SWOT (the acronym standing for Strengths, Weaknesses, Opportunities and Threats) analysis is a commonly used tool for analyzing internal and external environments in order to attain a systematic approach and support for a decision situation (e.g. Kotler, 1988 and Wheelen and Hunger, 1995). The internal and external factors most important to the enterprise’s future are referred to as strategic factors and they are summarized within the SWOT analysis. The final goal of strategic planning process, of which SWOT is an early stage, is to develop and adopt a strategy resulting in a good fit between internal and external factors. SWOT can also be used when strategy alternative emerges suddenly and the decision context relevant to it has to be analyzed. If used correctly, SWOT can provide a good basis for successful strategy formulation. Nevertheless, it could be used more efficiently (e.g. McDonald, 1993). When using SWOT, the analysis lacks the possibility of comprehensively appraising the strategic decision-making situation; merely pinpointing the number of factors in strength, weakness, opportunity or threat groups does not pinpoint the most significant group. In addition, SWOT includes no means of analytically determining the importance of factors or of assessing the fit between SWOT factors and decision alternatives. The further utilization of SWOT is, thus, mainly based on the qualitative analysis, capabilities and expertise of the persons participating in the planning process. As planning processes are often complicated by numerous criteria and interdependencies, it may be that the utilization of SWOT is insufficient. In their study, Hill and Westbrook (1997) found that none of the 20 case companies prioritized individual SWOT factors, one grouped factors further into subcategories, and only three companies used SWOT analysis as an input for a new mission statement. In addition, the expression of individual factors was of a very general nature and brief. Thus, it can be concluded that the result of SWOT analysis is too often only a superficial and imprecise listing or an incomplete qualitative examination of internal and external factors. Applications for gaining extra value from SWOT analysis in further strategic planning processes have been presented. Weihrich (1982) presented the TOWS matrix, which helps to systematically identify relationships between threats, opportunities, weaknesses and strengths, and offers a structure for generating strategies on the basis of these relationships. Proctor (1992) presented a computer package partly based on Weihrich’s TOWS matrix. In Proctor’s (1992) package, computer-aided creativity produces words for decision makers to use in identifying strengths, weaknesses, opportunities and threats. In addition, Proctor’s (1992) method includes creative generation and systematic evaluation of strategic alternatives. Flett (1989) introduced a method of initiating and crystallizing conceptual thinking. His method is a mix of Kipling’s five Ws (What, When, Where, Who, Why), McCarthy’s four Ps plus one additional P (Product, Price, Place, Promotion and People) and SWOT analysis and its rating. The method results in a broad-in-scope and innovative strategic management planning framework. Some examples of weighting and subdividing SWOT lists have been presented. Kotler (1988) presented that external factors could be classified according to their attractiveness and success probability (opportunities) and seriousness and probability of occurrence (threats). Internal factors could be rated by their performance and importance. In addition, he subdivided SWOT by business unit. Wheelen and Hunger (1995) summarized the external and internal strategic factors into EFAS (Synthesis of External Strategic Factors) and IFAS (Synthesis of Internal Strategic Factors). They showed how internal and external factors can be weighted and rated to illustrate how well management is responding to these specific factors (rating) in light of their perceived importance to the company (weight). Weighting was carried out at scale from 0.0 (not important) to 1.0 (most important) so that the sum of the weights was 1.0 and rating at scale 1 (poor) to 5 (outstanding). The product of these two was a weighted score indicating how well the company is responding to current and expected strategic factors in its environment. In addition to EFAS and IFAS, Wheelen and Hunger (1995) weighted and rated SFAS (Strategic Factors Analysis Summary), which included the most important external and internal strategic factors. In addition to weighting and rating individual SWOT factors, Hemmi (1995) suggested weighting four SWOT groups and using these weights as additional multipliers for individual factors to assess their overall importance. However, none of these approaches presented a systematic technique for determining importances. The decision analysis tool employed in the present study, the Analytic Hierarchy Process (AHP), is a mathematical method for analyzing complex decision problems with multiple criteria. It was originally developed by Saaty, 1977 and Saaty, 1980. Basically, AHP is a general theory of measurement based on some mathematical and psychological foundations. AHP can deal with qualitative attributes as well as quantitative ones. It has been found to be a useful decision-analysis technique and it has been applied in cases dealing with strategic planning, including marketing applications (Wind and Saaty, 1980), design and evaluation of business and corporate strategy (Wind, 1987). It has also been combined with the Delphi technique when integrating interactive expert knowledge in decision analysis (Kangas et al., 1996b). AHP is a widely used method also in forestry and forest management planning. A list of applications from a variety of areas of decision making is reported by Zahedi (1986), and applications concerning natural resource management were recently reviewed by Mendoza (1997). Forest certification has rapidly become a major topic in the debate dealing with the issue of how to improve the ways in which the world’s forests can be sustainably managed. It has been developed alongside a growing trend for ecolabelling of consumer products. It endeavors to link market demands for forest products produced according to high environmental and social standards with producers, who can meet such demands (Bass, 1997). The decision to adopt certified forestry concerns the entire chain of events from the forest to the final user. Forest certification may be defined as the action of a third-party in demonstrating that forest management and forest operations are in conformity with specific standards. These standards embody ecological, economic and social aspects. It can also be said that certification is a guarantee that such forests have been sustainably managed. Utilizing certification in marketing operations requires a label (‘eco-label’), which indicates that certified raw materials have been used in the production of a certain product. At the forest owner level, certification is a strategic decision: Should a forest owner adopt certified timber production with strict environment-friendly criteria instead of continuing with conventional timber production? What are the costs of obtaining a certificate and what are the expected gains? How rapidly can or should the change take place? Clearly, forest certification is a possibility in forestry mainly brought about by external environmental factors. These factors, and the forest owner’s capabilities to respond to them, must be examined. The decision situation at hand is a strategic planning situation in which SWOT and AHP can both be used. SWOT provides the basic frame within which to perform an analysis of the decision situation and AHP assists in carrying out SWOT more analytically. The possible advantages of using AHP in SWOT analysis lie in the quantitative examination of the SWOT factors and inclusion of preferences of the decision maker(s) in the planning situation. In addition, AHP and SWOT are both widely used, basic methods, and they are relatively easy to understand. Thus, they both are well suited to be used also in practical forest planning. The present study deals with the development of SWOT analysis connected to a decision situation of whether or not to adopt a certification system. Its rationale and justification are based on the importance of versatile environmental analysis in strategy formulation and strategic decision-making processes and in suggesting the potential usability of the common strategic planning tools in forest planning. Environmental analysis includes in-depth and critical examination of internal and external factors. It is not sufficient just to collect the relevant factors. Moreover, managers must view these factors from different standpoints and identify the foremost internal factors, which may be called critical success factors. The comparison of a firm’s position relative to its main competitors can be based on these factors. In addition, external factors should be appraised in relation to internal strengths and weaknesses. Following these analyses, managers will have their cornerstones, e.g. the factors on which future success and strategies should be based. The objective of this study is to look into SWOT factors in greater detail and more systematically. An application utilizing pairwise comparisons of AHP technique in SWOT analysis is presented. Also, a strategic decision-making situation of certificating a non-industrial private forest holding in Finland is provided to illustrate the use of this application. Finally, the suitability of the presented method and the possibilities for its further application in different situations are discussed.
نتیجه گیری انگلیسی
In this study, a common strategic planning tool, SWOT, was used in a case study concerning certification of the forests of a private woodlot. Although SWOT is in common use as a planning tool, it has some weaknesses. The objective of this study was to present an application where some of these weaknesses can be avoided, and thereby SWOT can be used more effectively. This was done by linking SWOT with a decision analysis method (AHP). The result was a hybrid method, which produces the quantitative values for the SWOT factors. Due to its simplicity, effectiveness and ability to deal with qualitative as well as quantitative criteria (this was also indicated by the results of this study), AHP is well-suited to dealing with the factors in SWOT analysis. One problem with SWOT analysis is in the uncertainty related to the future development and outcomes of different factors. This may complicate comparisons. However, AHP analysis is capable of handling decision-making situations with some uncertainties and inconsistencies. The recommendation is that the number of factors within the strengths, weaknesses, opportunities or threats should be limited to 10, but this probably induces the user to avoid overlapping and carelessness when constructing SWOT lists. On the other hand, the limitation is not so strict, and the problem of having a large number of comparisons can be avoided by at least two different techniques. Firstly, by grouping the variables and adding a new level to the comparison hierarchy (Saaty, 1980). If, for example, the number of opportunities is large, they can be grouped into two or three subgroups. Opportunities, for example, may be divided into ‘General Environmental Opportunities’ and ‘Competitive Environmental Opportunities’ (Dess and Miller, 1993). Secondly, new data recording and analysis techniques offer possibilities to include more factors in decision analysis. For example, Alho and Kangas (1997) presented a regression version of AHP formulated in Bayesian terms. Their version can be developed and utilized so that not all comparisons need to be performed. AHP provides quantitative priorities to be used in decision support. It does not, however, include statistical assessment of the uncertainty of the results. The measure of the consistency of the comparisons made, the consistency ratio, resulting from AHP calculations provides no direct information about the uncertainty of the priorities obtained. Other methods for analyzing uncertainties in pairwise comparisons have been presented. Alho et al. (1996) suggested a variance components modeling approach, where uncertainty or variation of the judgments in the case of multiple judges can be divided into three parts: (1) interpersonal variation around the population mean; (2) possible shared logical inconsistency of the judgments among the judges; and (3) residual uncertainty. Alho and Kangas (1997) extended that formulation to a multilevel, multiple-objective choice problem by using regression technique and the Bayesian approach. As a result, it was possible to attach probability to the resulting priorities. These techniques might also be used in the approach based on the combined use of SWOT and AHP. Numerical results, the priorities of SWOT factors, are of use when formulating or choosing strategy. It is useful to compare the external possibilities in relation to the internal capabilities, because all factors are, at the same, on the numerical scale. For example, when it is observed that one single weakness is bigger than all the strengths, the strategy chosen could perhaps be aimed at eliminating this weakness. Similarly, choosing a new strategy should probably not be based merely on the opportunities and omitting the existing threats if they are of same magnitude. In the case study illustrating the use of the hybrid method, the results, based on preliminary calculations, indicated that certification could be adopted. Certification can be considered to be a potential strategy alternative and it can be used as a competitive advantage on our case farm. The decision to adopt certification is not, however, permanent. Forests, when compared to some other factors of production, e.g. machinery, are quite flexible, and it is not impossible to make a reverse decision after some years should certification prove to be as an unfavorable decision. The results of our case study were presented in an illustrative way, which is often needed to clarify the interactions of numerous and contradictory factors. In strategic planning, this is often implemented via matrixes or graphs. Well known examples of these instruments are the Boston Consulting Group’s Business Portfolio Matrix (business growth rate and relative competition position), General Electric’s approach (market attractiveness and competitive position), and Ansoff’s product/market expansion grid, and others (e.g. Ansoff, 1965, Hofer and Schendel, 1978 and Dess and Miller, 1993). The hybrid method presented here is suitable for many kinds of strategic planning situations, including forest planning situations. In the case study, the situation investigated was one where a new strategy option emerged. The method can also be used in situations where strategic options have not yet been created. After defining the priorities of the SWOT factors, new strategies can be constructed based partly on the information resulting from comparisons. A connection with Weihrich’s (1982) and Proctor’s (1992) applications utilizing priorities to find out the most important factors when creating new strategies according to their suggestions is also possible. In addition, it is possible to compare two or more strategic options and find out which one best matches the SWOT factors. This can be done by adding strategy alternatives at the lowest level of the comparison hierarchy and comparing them with respect to each factor in the SWOT list. The result is a quantitative value indicating the priority or preference of each strategy option. One approach to dealing with the uncertainties involved in the assessment of future development might be the application of scenario modeling. In this approach, each possible future scenario would have its own SWOT analysis and AHP comparisons. Appraising the probabilities to scenarios and weighting the SWOT factors with them could yield a more comprehensive picture of the effects of the various future outcomes. Weihrich (1982), too, proposed a dynamic SWOT analysis, where changes in internal and external factors over time are included by preparing TOWS matrixes at different points of time. According to the experiences of this study, the results of the combined use of AHP and SWOT analysis were promising. Making pairwise comparisons forces the decision maker to think over the weights of the factors and to analyze the situation more precisely and in more depth. The applicability of the method in participatory planning will be studied in future. Public participation could be implemented by allowing all participants to perform their own SWOT analysis and pairwise comparisons, and then to proceed by summing up the separate results after weighting the participants by their individual importances. This would result in new alternatives from the participants’ viewpoints and probably include more creativity in the planning process. It is evident that a lot of managerial decision making is based on intuition and subjective judgments instead of the outcomes of formal planning. Expanding the presented formulation to cover a wider range of decision makers and experts to introduce their ideas and estimates could benefit the planning process. Interaction, learning and consensus can all be achieved by, for example, including the Delphi technique in the planning process (e.g. Kangas et al., 1996b). The hybrid method of AHP and SWOT increases and improves the information basis of strategic planning processes. It provides an effective framework for learning in strategic decision support in numerous situations. It can also be used as a tool in communication and education in decision making processes where multiple decision makers or judges are involved.