APEM jowatal Advances in Production Engineering & Management Volume 11 | Number 1 | March 2016 | pp 49-58 http://dx.doi.Org/10.14743/apem2016.1.209 ISSN 1854-6250 Journal home: apem-journal.org Original scientific paper Integration of SWOT and ANP for effective strategic planning in the cosmetic industry Al-Refaie, A.a*, Sy, E.b, Rawabdeh, I.a, Alaween, W.c department of Industrial Engineering, The University of Jordan, Amman, Jordan bAteneo de Manila University, Metro Manila, Philippines cDepartment of Industrial Engineering, The University of Jordan, Jordan A B S T R A C T A R T I C L E I N F O Typically, the decision making processes in cosmetics firms are greatly affected by internal and external factors, which as a result affect firms' success. In this research, the Strengths, Weakness, Opportunities, and Threat (SWOT) analysis was used to identify those factors that affect a cosmetics firm's success and consequently lists the feasible strategy alternatives. The analytic network process (ANP) was adopted for calculating the relative importance for each SWOT factors and sub-factors, while taking into consideration the dependency among SWOT factors, as well as among sub-factors. Utilizing the importance values in the super-matrix, the most preferred strategy in a cosmetic industry is identified, which is to open-up new markets on European market. In conclusion, the SWOT and ANP integration may provide great assistance to strategic planners in determining the best strategy alternative that fulfils the firm's desired objectives. © 2016 PEI, University of Maribor. All rights reserved. Keywords: Cosmetic industry Analytic network process (ANP) SWOT analysis Strategic planning *Corresponding author: abbas.alrefai@ju.edu.jo (Al-Refaie, A.) Article history: Received 9 January 2015 Revised 10 September 2015 Accepted 5 January 2016 1. Introduction Strategic management is a collection of actions and decisions taken in order to achieve organization's goals and objectives. Decision making process is greatly affected by internal and external factors. Systematic identification and analysis of the effects of such factors on organization success has received significant research attention [1-8]. The Strengths-Weakness-Opportunities-Threats (SWOT) technique is frequently used to analyse internal and external factors, assess the feasible alternative strategies, and then to determine the best one that helps an organization in achieving its desired objectives and goals. Nevertheless, the SWOT analysis as a qualitative tool does not numerically evaluate the effect of each factor on selected strategies [9-11]. The analytic hierarchy process (AHP) method [12-14] is a powerful technique which assists analysts in selecting the best decision among multiple decisions by structuring the decision problem in a hierarchically structure at different levels. In AHP, each level consists of finite number of decision elements, where the upper level of the hierarchy represents the overall goal, while the lower level represents all possible alternatives and the intermediate levels shape the decision criteria and sub-criteria [15-17]. The AHP allows the assessment of factors, which considered as criteria and the alternative strategies by giving them relative weights. Next, pairwise comparisons are carried out between all factors by assigning weights between one (equal importance) to nine (absolutely more important), whereas reciprocal values are assigned to the inverse comparison. Then, for each factor a pairwise comparison is performed between strate- 49 Ai-Refaie, Sy, Rawabdeh, Aiaween gies using a scale between one and nine. Finally, the integration between relative weight of factors and strategies are utilized to identify the overall weight of each strategy [18]. The AHP method assumes that there are unidirectional relationships between elements of different decision levels along the hierarchy and uncorrelated elements within each cluster as well as between clusters [19]. As a result, AHP is not appropriate for models that deal with interdependent relationships in AHP. The analytic network process (ANP) is introduced to solve this problem [20-23]. The comparison between AHP and ANP tools is depicted in Fig. 1. ANP method is an improved version of AHP, which provides more accurate results in complicated problems. In the ANP method and after clearly defined factors, the pairwise comparisons are performed as done by the AHP method; in addition, the dependencies among factors should be examined in pairwise manner. As a final step, the weighted score for each strategy is determined and then used to identify the best strategy. This research integrates SWOT analysis and ANP technique to determine the best strategy that results in improving the performance of a Jordanian cosmetics sector. The remaining of this research is organized as follows. Section two presents SWOT analysis. Section three introduces the ANP technique. Implementation of the integrated approach is performed in section four. Finally, conclusions are summarized in section five. a) b) Fig. 1 Hierarchy and network structure: a) AHP, and b) ANP 2. SWOT analysis The SWOT matrix treats an organization's strengths and weaknesses as internal factors, whereas the threats and opportunities, as external factors. These factors are utilized to identify and formulate strategies by matching the key internal and external factors. The matching between internal and external factors, what is called TOWS, is the most difficult and challenging part in SWOT analysis. TOWS matrix is utilized to develop four types of strategies. These strategies are shown in Fig. 2. ^Internal External Strengths (S) 1,..., s Weakness (W) 1,., w Opportunities (0) 1,..., o SO strategies WO Strategies Threats (T) 1,., t ST Strategies WT Strategies Fig. 2 SWOT matrix 50 Advances in Production Engineering & Management 11(1) 2016 Integration of SWOT and ANP for effective strategic planning in the cosmetic industry The Strengths-opportunities (SO) strategies utilize internal strengths of an organization to take advantage of external opportunities, weaknesses-opportunities (WO) strategies improve internal weaknesses by taking advantage of external opportunities, strengths-threats (ST) strategies use strengths of organization to avoid or minimize the effect of external threats, and weaknesses-threats (WT) strategies are defensive tactics aimed at reducing internal weaknesses and avoiding external threats. 3. ANP analysis The ANP is used to determine the dependencies and interrelations among factors using four main steps: Step 1: Clearly state and define the decision model as a network structure shown in Fig. 1.b. Once the goal or objective of the decision model is stated, it would further be decomposed into criteria, sub-criteria, and so on until alternatives level is reached. Step 2: Establish pairwise comparison matrices and priority vectors. In each factor pairs of decision elements are compared with respect to their relative importance. Then, the factors themselves are compared pairwise with respect to their contribution to the main goal. Furthermore, the interdependencies among elements of each factor are examined pairwise. The pairwise comparison is done by assigning relative importance values (ap) as shown in Table 1. However, the reciprocal (ap = 1/ap) of this value is assigned to the inverse comparison. Table 1 Preference scale as represented by Saaty (1996) Weight Definition Description 1 Equal importance Factor i and j are of equally important 3 Moderate importance Factor i is weakly more important than j 5 Strong importance Factor i strongly more important than j 7 Very strong importance Factor i is very strongly more important than j 9 Absolute importance Factor i is absolutely more important than j 2, 4, 6, 8 Intermediate values Represent compromise between the priorities The pairwise comparison matrix A, is represented as follows: A = 1 1/^21 «12 1 al(n-l) a2(n-l) aln a2n 1/al(n-l) ••• n 1/a2 r, 1 a(n-l~)n 1/a(n-l)n 1 (1) An estimate of the relative importance of the compared factors is determined using Eq. 2. = Àmaxw (2) where w is the desired to estimate eigenvector and Amax is the largest Eigen value of A. Step 3: Determine the relative importance of all components with dependency effects and then create the super-matrix. The super-matrix adjusts the relative weights in individual matrices to form a new ''overall'' matrix with the eigenvectors of the adjusted relative weights. That is, the eigenvectors obtained in step 2 are grouped and placed in the appropriate positions in the super matrix in a hierarchy manner as goal, factors, sub-factors and alternatives as follows: Advances in Production Engineering & Management 11(1) 2016 51 Ai-Refaie, Sy, Rawabdeh, Aiaween 0 0 0 0 W21 0 0 0 0 W32 0 0 0 0 w43 I where each entry in W is a matrix. The W21 is a matrix which represents the impact of the goal on the factors, W32 is a matrix that represents the impact of the factors on each of the sub-factor, W43 represents the impact of the sub-factors on each of the alternatives, and I is the identity matrix. If there is any dependency among the factors of W, then W22 would be non-zero matrix, and so on. All interdependences can be represented in the same manner. Step 4: Calculate the weights of alternatives from the normalized super-matrix. Step 5: Select the alternative that corresponds to the largest priority as the most preferred alternative. 4. Cosmetics industry The integration of the SWOT and ANP analysis was implemented in cosmetics industry in Jordan and is described as follows. The key internal factors (strengths and weakness) and the most external factors (opportunities and threats) are listed in Table 2. The corresponding ANP structure for cosmetics is shown in Fig. 2. The pairwise comparisons between these factors are presented in Table 3. Then, the matrix Wi, represents the Eigenvector that represents for the SWOT factors is expressed as: W-, = 0.547 0.135 0.272 0.047. (4) The dependency among the SWOT factors is analysed by identifying the impact of each factor on the others in pairwise comparison as shown in Table 4. Consequently, the dependency matrix W2, of the SWOT factors is written as: W, = 1.000 0.649 0.768 0.768 0.587 1.000 0.153 0.153 0.324 0.295 1.000 0.079 0.089 0.057 0.079 1.000 (5) Utilizing Eqs. 4 and 5, the matrix, Wfactors, contains the relative importance of the SWOT factors is determined by multiplying the relative importance matrix Wi, under the assumption of independency by the relative importance matrix W2, considering the dependency among factors. That is: ^factors =W1XW2 = 1.000 0.649 0.768 0.768 0.547 0.880 0.587 1.000 0.153 0.153 X 0.135 0.505 0.324 0.295 1.000 0.079 0.272 0.493 0.089 0.057 0.079 1.000 0.047 0.125 (6) In Eq. 6, it is noted that the largest importance weight (= 0.880) corresponds to the strengths factor, whereas the smallest weight (0.125) associated with the threats. There is significant difference between the relative weight for each factor with and without considering the dependencies. 52 Advances in Production Engineering & Management 11(1) 2016 Integration of SWOT and ANP for effective strategic planning in the cosmetic industry Table 2 TOWS matrix for the cosmetic company Internal Factors Strength Weakness 1. Human expertise and financial resources. 2. Strong and well-known brand name. 3. Depending on neutral material. 1. Loss of trust from different supply chain parties. 2. Falling in utilizing e-commerce capabilities. 3. Price is expensive. 4. Innovation skills and strong research and development. 5. Better products quality relative to rivals.