APPLICATION OF DIGITAL CELLULAR RADIO FOR MOBILE LOCATION ESTIMATION IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 MULTICRITERIA DECISION MAKING ON SUPPLIER SELECTION USING SOCCER MODEL INTEGRATED WITH ANALYTICAL HIERARCHY PROCESS MUATAZ AL HAZZA1*, AZURA DAPIT2, ISLAM FAISAL BOURINI3, ZUBAIDAH MUATAZ2 AND MOHAMMAD YEAKUB ALI4 1 Mechanical and Industrial Engineering, School of Engineering, American University of Ras Al Khaimah, Road - Ras al Khaimah, Ras Al Khaimah, UAE 2 Department of Manufacturing and Materials Engineering, International Islamic University Malaysia, Jalan Gombak, 53100 Selangor, Malaysia 3 Dubai Business School, University of Dubai, Dubai, UAE 4 Mechanical Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei Darussalam * Corresponding author: muataz.alhazza@aurak.ac.ae (Received: 8 March 2023; Accepted: 18 May 2023; Published on-line: 4 July 2023) ABSTRACT: Supplier evaluation and selection are key components in the supply chain because supplier performance directly affects the supply chain's efficiency. Therefore, companies should think strategically when they need to select their suppliers. Thus, selecting and evaluating new suppliers is essential in shaping the supply chain's smoothness and efficiency. Selecting suppliers is a complex issue as it involves many factors and decisions to be considered and needs to be assessed with an auditing process. However, a supplier audit is an expensive way to evaluate supplier capability. This research aims to propose a supplier selection model for a corrugated carton manufacturing company. The SOCCER model, developed by Steve Rogers, was used as the supplier selection criteria. Analytical Hierarchy Process (AHP) was used in the supplier selection. A face-to-face interview method was used in collecting data. The results show that the cost structure is the ultimate concern on supplier selection which bears 44.2% of the SOCCER model, followed by operational capability (23%), customer approach (13.5%), economic performance (8.3%), strategic direction (6.9%), and lastly research and development (4.1%). The percentages inform the company how much attention they need to pay when evaluating and selecting a new supplier. ABSTRAK: Penilaian dan pemilihan pembekal adalah kunci utama dalam rantaian bekalan kerana prestasi pembekal secara langsung melibatkan kecekapan rantaian bekalan. Oleh itu, syarikat perlu memikirkan secara strategik apabila ingin memilih pembekal. Dengan demikian, pemilihan dan penilaian pembekal baru adalah penting dalam pembentukan kelancaran rantaian bekalan dan kecekapan. Pemilihan pembekal adalah isu kompleks kerana ianya melibatkan banyak faktor dan keputusan perlu difikirkan dan perlu dinilai bersama proses audit. Namun, audit pembekal adalah mahal bagi menilai kemampuan pembekal. Kajian ini mencadangkan model pemilihan pembekal bagi syarikat pembekal kotak karton. Model SOCCER dicipta oleh Steve Rogers, telah digunakan sebagai kritia pemilihan pembekal. Proses Hirarki Analitikal (AHP) digunakan dalam pemilihan pembekal. Kaedah temuduga bersemuka digunakan dalam pengumpulan data. Dapatan kajian menunjukkan struktur harga adalah kehendak utama dalam pemilihan pembekal iaitu 44.2% daripada model SOCCER, diikuti kemampuan operasi (23%), pendekatan pelanggan (13.5%), prestasi ekonomi (8.3%), misi strategik (6.9 %), dan 239 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 akhirnya penyelidikan dan pembangunan (4.1%). Peratusan ini berguna untuk syarikat dalam memberi keutamaan dalam penilaian dan pemilihan pembekal baru. KEYWORDS: supplier selection; AHP; MCDM; SOCCER 1. INTRODUCTION Today, with a rapidly changing world and markets, companies face a vital challenge to stay competitive [1]. Markets nowadays are witnessing major changes due to the global nature of trade and rapid technological development that leads to aggressive competition between manufacturers. This rapid technological advancement changed supply chain work and made it easier to communicate and faster to deliver goods. As a result, manufacturers have realized that suppliers’ performance is one of the main and important factors to survive in the market. Capable suppliers are essential to ensure the supply chain runs smoothly and efficiently. Thus, establishing a strong relationship and partnering with suppliers will result in a win-win situation where both parties would gain advantages through this relationship. However, supplier selection is complex as it should consider many factors [2]. Researchers spend most of their time finding and determining the best supplier selection criteria, resulting in many approaches and checklist assessments [3]. Each company may have different selection criteria as they have their own goals, needs, and industry types. Selecting the best supplier is a complex and challenging procedure. Therefore, choosing the best method has become one of the main success factors for manufacturers and thus, multicriteria decision-making methods (MCDM) will be useful and effective. 2. LITERATURE REVIEW MCDM methodology is a decision-support framework that can consider multiple inconsistent criteria [4]. It is a method in which different criteria are traded off to achieve the best alternative. It includes quantitative and qualitative factors, which are considered complex decision-making tools, making it the most widely used and favorable decision methodology in many fields [5]. Different MCDM techniques employ different approaches. Throughout their analysis research, Velasquez and Hester [6] identified eleven different MCDM. However, supplier selection is a complex critical problem that must trade off various conflicting criteria such as price, quality, and delivery time. These methods have been used and applied by different researchers in supplier selection such as Multi-Attribute Utility Theory [8], Analytic Hierarchy Process (AHP) [7], Fuzzy Set Theory [9], Case- Based Reasoning [10], Data Envelopment Analysis [11], Goal Programming [12], ELECTRE method [13], Simple Additive Weighing [14], and Fuzzy TOPSIS Technique [15]. Other researchers prefer integrating two methods or techniques to have better and more effective decisions as an efficient approach [16-20]. Many researchers [21-22] claim that merging AHP with one of the intelligent methods such as Fuzzy Set Theory is favorable in decision making on the selection of suppliers due to high uncertainty in this decision-making process. However, each multicriteria technique has its advantages and disadvantages. Thus, integrating several techniques is common in multicriteria decision-making to overcome deficiencies [6]. One of the most specific multicriteria frameworks in supplier selections is the SOCCER model [3]. The acronym represents the six main criteria, S- Strategic Direction, O- Operational Capability, C- Customer Approach, C- Cost Structure, E- Economic Performance and R-Research & Development. Rogers, in his book [3], explained that the supplier assessment is needed to make sure that the supplier can handle the orders. 240 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Therefore, the SOCCER model is simply one of the most effective checklists when auditing suppliers. Ho et al. [23] have reviewed the literature of the MCDM approaches for supplier selection in the international journals from 2000 to 2008. However, in this research, the integration between AHP as one of the effective tools in multicriteria methods with SOCCER model as one of the effective checklists in suppliers' selection auditing was implemented. 2.1 Analytical Hierarchical Process Thomas Saaty introduced the Analytical Hierarchical Process (AHP) in 1970 [24-25]. AHP is a structured method for dealing with complex decision-making. It aids the decision- maker in setting priorities and making the best decision. It derives relative priorities on absolute scales (invariant under the identity transformation) from discrete and continuous paired comparisons in multilevel hierarchical structures [26]. AHP is a method that merges a decision's subjective and objective characteristics. The AHP considers a group of evaluation criteria and different options, among which the most effective decision will be created. First, the AHP generates a weight for every evaluation criterion according to the decision-makers pairwise comparisons of the factors. The higher Weight, the more essential is the corresponding criterion. Next, the AHP assigns a score to every possibility for a set criterion according to the decision maker's pairwise comparisons of the choices based on that criterion. The higher the score, the better the performance of choice concerning the considered criterion. Finally, the AHP combines the criteria weights and the choices’ scores, determining a global score for every option and a consequent ranking. The global score for a given possibility is a weighted total of the scores it obtained concerning all the criteria. Sipahi and Timor [27] presented a comprehensive review of applications of AHP method and ANP from 2005 to 2009. The paper additionally contains fuzzy AHP and fuzzy ANP applications. Ishizaka and Labib [28] presented a theoretically-view of the AHP articles instead of classifying them by application areas. Their paper mentioned problem modeling, pairwise comparisons, judgment scales, derivation techniques, consistency indices, incomplete matrix, synthesis of the weights, sensitivity analysis, and group decision problems. Subramanian and Ramanathan [29] reviewed and methodologically analyzed applications of AHP in operations management from 1990 to 2009. They classified 291 application research of AHP into operations strategy, process, and product style, designing and planning resources, project management, and managing the supply chain. AHP-primarily based techniques for supplier analysis were studied by Bruno et al. [30]. Their study underlined that the weak and strong points are rising from applying the AHP in a greater supply chain. 2.2 SOCCER Model The SOCCER model was developed by Rogers [3] to focus on the main factors in any supplier selection and what is needed for supplier analysis. The acronym represents the six main criteria, S- Strategic Direction, O- Operational Capability, C- Customer Approach, C- Cost Structure, E- Economic Performance and R-Research & Development. Each of the criteria has five sub-criteria, as shown in Fig. 1. Finally, after a sweeping review of the current literature in the area, it was identified that various investigators used diverse criteria and different methods. In this research, the integration between the SOCCER model developed by Steve C. Rogers and the Analytical 241 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Hierarchy Process (AHP) will add value to the area of knowledge and will reduce the risk of selecting an inappropriate supplier. AHP aids in developing a relative weighting and prioritizing the different criteria based on the organization's objectives. This integration considers the advantages of using a powerful qualitative method presented by the AHP method that focuses on the pairwise comparisons for every two main criteria and strengthens it by using a well-established framework that considers six main dimensions: Strategic Direction, Operational Capability, Customer Approach, Cost Structure, Economic Performance, and Research & Development. Each of those dimensions has a sub-criteria that covers all the possible factors. Fig. 1: Supplier analysis factors [3]. 3. RESEARCH METHODOLOGY In this research, the integration between AHP with SOCCER framework was implemented. The advantage of using the AHP method is that it focuses on pairwise comparisons for every two main criteria. To enhance the output of using the AHP method and strengthens it by using a well-established detailed framework that considers six main dimensions: Strategic Direction, Operational Capability, Customer Approach, Cost Structure, Economic Performance, and Research & Development. Each of those dimensions has a sub-criteria that covers all the possible factors. A sequential feedback loop is summarized in Fig. 2. The main steps of the research can be concluded in the following steps: 1. Analyze the suitability of using the SOCCER framework 2. Integrate the framework with the AHP method 3. Select the internal expertise in supplier selection for the company: quality assurance, customer service, and purchasing 4. Design the interview framework: Interview questions were designed to utilize the pairwise matrix. 5. Creating the pairwise matrix based on the interview results. 6. Test the consistency by avoiding bias due to the area of the expertise 7. Develop a conceptual framework The consistency was determined using the followings steps [9,30]: 1. Calculating the consistency index CI, using Eq, (1), where n is the number of criteria in the comparison. CI =(Max Eigenvalue- n)/(n-1) (1) 242 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 2. Dividing its value by the random consistency index, which is stated by Saaty depending on the value of n. The results are shown in Table 14. 3. Calculating the Consistency Ratio (CR) value using equation (2) where the value below 10% is considered consistent. CR=CI/RI<0.1~10% (2) where CI is the consistency index, CR is the Consistency Ratio, and RI is the Random Consistency Index Fig. 2: Research methodology flow chart. 4. RESULTS Supplier selection is a complex issue involving many factors and decisions due to the difficulties of trading off financial and performance evaluation. The data were gathered through interview sessions using the criteria based on the SOCCER model. The relative "priority" given to each element in the hierarchy is determined by comparing pairwise using the AHP method. The criteria ranking is decided through pairwise comparisons, and the preference scale ranking the hierarchy. An industrial company was selected to implement SOCCER and AHP. The representatives from three different departments: quality assurance, customer service, and purchasing, were interviewed through a comprehensive individual interview session designed in order to fit for pairwise comparison. The results were concluded based on the SOCCER model. The results were analyzed based on two steps: STEP 1: Developing a decision matrix of the SOCCER model for the main factors for each interviewee. The results are shown in Tables 1, 2, and 3. The results show an agreement on the cost structure with the higher priority of 0.45, 0.42, and 0.44 for the quality assurance, customer service, and purchasing departments. Moreover, all the experts show agreement that the second essential criterion is the operational capability with the values of 0.27, 0.27, and 0,23. 243 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 1: Decision matrix of SOCCER model by Quality Assurance Strategic Direction Operational Capability Customer Approach Cost Structure Economic Performance R&D Priority Vector Strategic Direction 1 1/7 1/4 1/8 3 3 0.060 Operational Capability 7 1 3 1/3 6 7 0.270 Customer Approach 4 1/3 1 1/5 5 6 0.150 Cost Structure 8 3 5 1 9 6 0.450 Economic Performance 1/3 1/6 1/5 1/9 1 1/3 0.030 R & D 1/3 1/7 1/6 1/6 3 1 0.040 CI = 0.1116, RI = 1.24, CR = 0.09 < 0.1 OK Table 2: Decision matrix of SOCCER model by Customer Services Strategic Direction Operational Capability Customer Approach Cost Structure Economic Performance R&D Priority Vector Strategic Direction 1 1/6 1/5 1/8 ½ 2 0.050 Operational Capability 6 1 3 1/2 4 5 0.270 Customer Approach 5 1/3 1 1/4 2 4 0.140 Cost Structure 8 2 4 1 5 8 0.420 Economic Performance 2 1/4 1/2 1/5 1 2 0.080 R & D ½ 1/5 1/4 1/8 1/2 1 0.040 CI = 0.0372, RI = 1.24, CR = 0.03 < 0.1 OK Table 3: Decision matrix of SOCCER model by Purchasing Strategic Direction Operational Capability Customer Approach Cost Structure Economic Performance R&D Priority Vector Strategic Direction 1 1/5 1/3 1/6 1 3 0.070 Operational Capability 5 1 3 1/4 2 5 0.230 Customer Approach 3 1/3 1 1/3 2 3 0.140 Cost Structure 6 4 3 1 4 7 0.440 Economic Performance 1 1/2 1/2 1/4 1 2 0.090 R & D 1/3 1/5 1/3 1/7 1/2 1 0.040 CI = 0.0868, RI = 1.24, CR = 0.07 < 0.1 OK 244 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 STEP 2: Developing a decision matrix of the SOCCER model for each interviewee for each sub criterion. Tables 4, 5, 6, 7, 8, and 9 show the decision matrix for quality assurance. Table 4: Decision matrix of Strategic Direction by Quality Assurance Strategic Direction Management Approach Business Structure Corporate strategy Corporate Governance Management team Priority Vector Management Approach 1 1/5 1/3 5 1/6 0.070 Business Structure 5 1 4 7 1 0.360 Corporate strategy 3 1/4 1 6 1/6 0.130 Corporate Governance 1/5 1/7 1/6 1 1/8 0.030 Management team 6 1 6 8 1 0.410 CI = 0.0784, RI = 1.12, CR = 0.07 < 0.1 OK Table 5: Decision matrix of Operational Capability by Quality Assurance Operational Capability Product Quality Human Resource Admin Systems Logistical Capability Information Technology Priority Vector Product Quality 1 1/5 1/3 5 1/6 0.070 Human Resources 5 1 4 7 1 0.360 Admin Systems 3 1/4 1 6 1/6 0.130 Logistical Capability 1/5 1/7 1/6 1 1/8 0.030 Information Technology 6 1 6 8 1 0.410 CI = 0.1008, RI = 1.12, CR = 0.09 < 0.1 OK Table 6: Decision matrix of Customer Approach by Quality Assurance. Customer Approach Key Customers Market Position Customer Relations Customer Approach External Relations Priority Vector Key customers 1 9 1/2 2 6 0.330 Market Position 1/9 1 1/6 1/4 1/3 0.040 Customer Relation 2 6 1 1 5 0.340 Customer Approach 1/2 4 1 1 4 0.220 External Relation 1/6 3 1/5 1/4 1 0.070 CI = 0.0784, RI = 1.12, CR = 0.07 < 0.1 OK. 245 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 7: Decision matrix of Cost Structure by Quality Assurance Cost Structure Wage Base Overhead Costs Supply Base Cost Product Cost Delivery Cost Priority Vector Wage Base 1 1/3 1/2 1/8 1/7 0.040 Overhead Costs 3 1 3 1/5 1/4 0.110 Supply Base Cost 2 1/3 1 1/7 1/6 0.060 Product Cost 8 5 7 1 4 0.520 Delivery Cost 7 4 6 1/4 1 0.270 CI = 0.1008, RI = 1.12, CR = 0.09 < 0.1 OK Table 8: Decision matrix of Economic Performance by Quality Assurance Economic Performance Profit Level Profit Centers Financial Structure Risk Exposure Cash Flow Priority Vector Profit Level 1 1/2 1/6 1/3 1/4 0.050 Profit Centers 2 1 1/7 1/2 1/5 0.070 Financial Structure 6 7 1 4 3 0.500 Risk Exposure 3 2 1/4 1 1/2 0.140 Cash Flow 4 5 1/3 2 1 0.240 CI = 0.0336 RI = 1.12, CR = 0.03 < 0.1 OK. Table 9: Decision matrix of Research & Development by Quality Assurance Research & Development Core Competency Research Competency Process Scale- Up Project Management Intellectual Property Priority Vector Core Competency 1 4 7 1/4 1/2 0.180 Research Competency 1/4 1 3 1/9 1/5 0.060 Process Scale- Up 1/7 1/3 1 1/6 1/3 0.040 Project Management 4 9 6 1 2 0.470 Intellectual Property 2 5 3 1/2 1 0.240 CI = 0.0784, RI = 1.12, CR = 0.07 < 0.1 OK The results are concluded in Table 10. The priority vector of Strategic Direction, Operational Capability, Customer Approach, Cost Structure, Economic Performance, and R & D were management team, product quality, customer relation, Product Cost, financial structure, and project management were 0.41,0.41, 0.43, 0.52, 0.50, and 0.74, respectively. The SOCCER model overall Weight by the Quality Assurance is concluded in Table 10. The Quality Assurance preferred Cost structure (45%), followed by Operational Capability (27%), Customer Approach (15%), Strategic direction (6%), Research & Development (4%), and Economic performance (3%). 246 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 10: Results of SOCCER model (Quality Assurance) Factor Item Priority Vector (%) Sub-Criteria Weight According to Main-Criteria Weight (%) Strategic Direction (6%) Management Approach 7.00 0.42 Business Structure 36.00 2.16 Corporate strategy 13.00 0.78 Corporate Governance 3.00 0.18 Management team 41.00 2.46 Operational Capability (27%) Product Quality 38.00 10.26 Human Resources 5.00 1.35 Admin Systems 25.00 6.75 Logistical Capability 26.00 7.02 Information Technology 6.00 1.62 Customer Approach (15%) Key customers 33.00 4.95 Market Position 4.00 0.60 Customer Relations 34.00 5.10 Customer Approach 22.00 3.30 External Relations 7.00 1.05 Cost Structure (45%) Wage Base 4.00 1.80 Overhead Costs 11.00 4.95 Supply Base Cost 6.00 2.70 Product Cost 52.00 23.40 Delivery Cost 27.00 12.15 Economic Performance (3%) Profit Level 5.00 0.15 Profit Centres 7.00 0.21 Financial Structure 50.00 1.50 Risk Exposure 14.00 0.42 Cash Flow 24.00 0.72 Research & Development (4%) Core Competency 18.00 0.72 Research Competency 6.00 0.24 Process Scale-Up 4.00 0.16 Project Management 47.00 1.88 Intellectual Property 24.00 0.96 The decision matrices for each main criteria for the customer service are shown in Tables 11,12, 13, 14, 15, and 16. 247 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 11: Decision matrix of Strategic Direction by Customer Service Strategic Direction Management Approach Business Structure Corporate Strategy Corporate Governance Management Team Priority Vector Management Approach 1 2 3 4 1/2 0.250 Business Structure 1/2 1 2 3 1/4 0.140 Corporate strategy 1/3 1/2 1 2 1/5 0.090 Corporate Governance 1/4 1/3 1/2 1 1/6 0.060 Management team 2 4 5 6 1 0.460 CI = 0.0112, RI = 1.12, CR = 0.01 < 0.1 OK Table 12: Decision matrix of Operational Capability by Customer Service Operational Capability Product Quality Human Resource Admin Systems Logistical Capability Information Technology Priority Vector Product Quality 1 8 6 4 3 0.500 Human Resources 1/8 1 1 1/5 1/4 0.050 Admin Systems 1/6 1 1 1/5 1/3 0.060 Logistical Capability 1/4 5 5 1 3 0.250 Information Technology 1/3 4 3 1/3 1 0.150 CI = 0.0896, RI = 1.12, CR = 0.08 < 0.1 OK Table 13: Decision matrix of Customer Approach by Customer Service Customer Approach Key customers Market Position Customer Relations Customer Approach External Relations Priority Vector Key customers 1 4 1/3 1/5 4 0.140 Market Position 1/4 1 1/6 1/8 1/2 0.040 Customer Relation 3 6 1 1/3 4 0.250 Customer Approach 5 8 3 1 7 0.510 External Relation 1/4 2 1/4 1/7 1 0.060 CI = 0.056, RI = 1.12, CR = 0.05 < 0.1 OK 248 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 14: Decision matrix of Cost Structure by Customer Service Cost Structure Wage Base Overhead Costs Supply Base Cost Product Cost Delivery Cost Priority Vector Wage Base 1 1/5 1/2 1/9 1/8 0.030 Overhead Costs 5 1 3 1/6 1/5 0.110 Supply Base Cost 2 1/3 1 1/8 1/5 0.050 Product Cost 9 6 8 1 3 0.520 Delivery Cost 8 5 5 1/3 1 0.290 CI = 0.0784, RI = 1.12, CR = 0.07 < 0.1 OK Table 15: Decision matrix of Economic Performance by Customer Service Economic Performance Profit Level Profit Centers Financial Structure Risk Exposure Cash Flow Priority Vector Profit Level 1 1/2 1/7 1/4 1/5 0.040 Profit Centers 2 1 1/6 1/3 1/4 0.070 Financial Structure 7 6 1 5 4 0.520 Risk Exposure 4 3 1/5 1 1/3 0.130 Cash Flow 5 4 1/4 3 1 0.230 CI = 0.0784 RI = 1.12, CR = 0.07 < 0.1 OK Table 16: Decision matrix of Research & Development by Customer Service Research & Development Core Competency Research Competency Process Scale- Up Project Management Intellectual Property Priority Vector Core Competency 1 2 4 1/6 1/5 0.100 Research Competency 1/2 1 2 1/7 1/4 0.070 Process Scale- Up 1/4 1/2 1 1/8 1/5 0.040 Project Management 6 7 8 1 3 0.520 Intellectual Property 5 4 5 1/3 1 0.270 CI = 0.0672, RI = 1.12, CR = 0.06 < 0.1 OK. The results are concluded in Table 17. The priority vector of Strategic Direction, Operational Capability, Customer Approach, Cost Structure, Economic Performance, and R & D were management team, product quality, customer relation, product cost, financial structure, and project management were 0.46, 0.50, 0.51, 0.52, 0.52, and 0.52, respectively. The Quality Assurance Preferred Cost structure (42%), followed by Operational Capability (27%), Customer Approach (14%), Economic performance (8%), Strategic direction (6%), and Research & Development (4%). 249 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 17: Results of R1 based on SOCCER model (Customer Service) Factor Item Priority Vector (%) Sub-Criteria Weight According to Main-Criteria Weight (%) Strategic Direction (5%) Management Approach 25.00 1.25 Business Structure 14.00 0.70 Corporate strategy 9.00 0.45 Corporate Governance 6.00 0.30 Management team 46.00 2.30 Operational Capability (27%) Product Quality 50.00 13.50 Human Resources 5.00 1.35 Admin Systems 6.00 1.62 Logistical Capability 25.00 6.75 Information Technology 15.00 4.05 Customer Approach (14%) Key customers 14.00 1.96 Market Position 4.00 0.56 Customer Relations 25.00 3.50 Customer Approach 51.00 7.14 External Relations 6.00 0.84 Cost Structure (42%) Wage Base 3.00 1.26 Overhead Costs 11.00 4.62 Supply Base Cost 5.00 2.10 Product Cost 52.00 24.84 Delivery Cost 29.00 12.18 Economic Performance (8%) Profit Level 4.00 0.32 Profit Centers 7.00 0.56 Financial Structure 52.00 4.16 Risk Exposure 13.00 1.04 Cash Flow 23.00 1.84 Research & Development (4%) Core Competency 10.00 0.4 Research Competency 7.00 0.28 Process Scale-Up 4.00 0.16 Project Management 52.00 2.08 Intellectual Property 27.00 1.08 The results are concluded in Table 24. The priority vector of Strategic Direction, Operational Capability, Customer Approach, Cost Structure, Economic Performance, and R&D were management team, product quality, customer relation, product cost, financial structure, and project management with 0.46, 0.51, 0.50, 0.52, 0.51, and 0.51, respectively. However, the unexpected outcome was that Logistical Capability ranked first with the priority vector of 0.517. The quality assurance preferred cost structure (44%), followed by operational Capability (23%), customer approach (14%), economic performance (9%), strategic direction (7%), and research & development (4%). 250 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 5. SUPPLIER SELECTION CRITERIA FRAMEWORK The overall priority vector of the interviewees is concluded in Table 25, which shows that the cost structure has the highest number by 0.442, which makes it 44.2% from the SOCCER model. The second highest was an operational capability with 23%, however, other factors of customer approach, economic performance, strategic direction, and R&D, had the remaining weightage of 13.5%, 8.3%, 6.9%, and 4.1, respectively. The decision matrix for each main criteria for the purchasing department representer are shown in tables 18, 19, 20, 21, 22, and 23. Table 18: Decision matrix of Strategic Direction by Purchasing Strategic Direction Management Approach Business Structure Corporate strategy Corporate Governance Management team Priority Vector Management Approach 1 3 4 5 1/2 0.290 Business Structure 1/3 1 2 3 1/4 0.130 Corporate strategy 1/4 1/2 1 1 1/6 0.070 Corporate Governance 1/5 1/3 1 1 1/6 0.060 Management team 2 4 6 6 1 0.460 CI = 0.0224, RI = 1.12, CR = 0.02 < 0.1 OK Table 19: Decision matrix of Operational Capability by Purchasing Operational Capability Product Quality Human Resource Admin Systems Logistical Capability Information Technology Priority Vector Product Quality 1 7 5 1/4 3 0.260 Human Resources 1/7 1 1/2 1/8 1/4 0.040 Admin Systems 1/5 2 1 1/6 1/3 0.060 Logistical Capability 4 8 6 1 4 0.510 Information Technology 1/3 4 3 1/4 1 0.130 CI = 0.0896, RI = 1.12, CR = 0.08 < 0.1 OK Table 20: Decision matrix of Customer Approach by Purchasing Customer Approach Key customers Market Position Customer Relations Customer Approach External Relations Priority Vector Key customers 1 5 1/3 2 4 0.240 Market Position 1/5 1 1/8 1/5 1/2 0.040 Customer Relation 3 8 1 4 6 0.500 Customer Approach 1/2 5 1/4 1 2 0.150 External Relation 1/4 2 1/6 1/2 1 0.070 CI = 0.0336, RI = 1.12, CR = 0.03 < 0.1 OK 251 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Table 21: Decision matrix of Cost Structure by Purchasing Cost Structure Wage Base Overhead Costs Supply Base Cost Product Cost Delivery Cost Priority Vector Wage Base 1 1/5 1/3 1/9 1/8 0.030 Overhead Costs 5 1 3 1/7 1/5 0.100 Supply Base Cost 3 1/3 1 1/7 1/5 0.060 Product Cost 9 7 7 1 3 0.520 Delivery Cost 8 5 5 1/3 1 0.290 CI = 0.0896, RI = 1.12, CR = 0.08 < 0.1 OK Table 22: Decision matrix of Economic Performance by Purchasing Economic Performance Profit Level Profit Centers Financial Structure Risk Exposure Cash Flow Priority Vector Profit Level 1 1/2 1/9 1/6 1/7 0.030 Profit Centers 2 1 1/7 1/5 1/6 0.050 Financial Structure 9 7 1 6 3 0.510 Risk Exposure 6 5 1/6 1 1/3 0.140 Cash Flow 7 6 1/3 3 1 0.270 CI = 0.0896RI = 1.12, CR = 0.08 < 0.1 OK. Table 23: Decision matrix of Research & Development by Purchasing Research & Development Core Competency Research Competency Process Scale- Up Project Management Intellectual Property Priority Vector Core Competency 1 3 5 1/5 1/3 0.130 Research Competency 1/3 1 2 1/7 1/4 0.060 Process Scale- Up 1/5 1/2 1 1/8 1/7 0.040 Project Management 5 7 8 1 3 0.510 Intellectual Property 3 4 7 1/3 1 0.260 CI = 0.056, RI = 1.12, CR = 0.05 < 0.1 OK. Table 24: Results of R1 based on SOCCER model Factor Item Priority Vector (%) Sub-Criteria Weight According to Main-Criteria Weight (%) Strategic Direction (7%) Management Approach 29.00 2.03 Business Structure 13.00 0.91 Corporate strategy 7.00 0.49 Corporate Governance 6.00 0.42 Management team 46.00 3.22 Operational Capability (23%) Product Quality 26.00 5.98 Human Resources 4.00 0.92 Admin Systems 6.00 1.38 252 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Logistical Capability 51.00 11.73 Information Technology 13.00 2.99 Customer Approach (14%) Key customers 24.00 3.36 Market Position 4.00 0.56 Customer Relations 50.00 7.00 Customer Approach 15.00 2.10 External Relations 7.00 0.98 Cost Structure (44%) Wage Base 3.00 1.32 Overhead Costs 10.00 4.40 Supply Base Cost 6.00 2.64 Product Cost 52.00 22.88 Delivery Cost 29.00 12.76 Economic Performance (9%) Profit Level 3.00 0.27 Profit Centers 5.00 0.45 Financial Structure 51.00 4.59 Risk Exposure 14.00 1.26 Cash Flow 27.00 2.43 Research & Development (4%) Core Competency 13.00 0.52 Research Competency 6.00 0.24 Process Scale-Up 4.00 0.16 Project Management 51.00 2.04 Intellectual Property 26.00 1.04 Table 25: Results of R1 based on SOCCER model Factor Item Priority Vector (%) Sub-Criteria Weight According to Main-Criteria Weight (%) Strategic Direction (6.9%) Management Approach 29.00 2.00 Business Structure 12.90 0.89 Corporate strategy 6.70 0.46 Corporate Governance 6.00 0.41 Management team 45.50 3.14 Operational Capability (23%) Product Quality 25.50 5.87 Human Resources 3.80 0.87 Admin Systems 6.00 1.38 Logistical Capability 51.70 11.89 Information Technology 12.90 2.97 Customer Approach (13.5%) Key customers 23.50 3.17 Market Position 4.30 0.58 Customer Relations 50.30 6.79 253 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Customer Approach 14.60 1.97 External Relations 7.30 0.99 Cost Structure (44.2%) Wage Base 3.10 1.37 Overhead Costs 10.60 4.69 Supply Base Cost 5.90 2.61 Product Cost 52.10 23.03 Delivery Cost 28.40 12.55 Economic Performance (8.3%) Profit Level 3.30 0.27 Profit Centres 4.90 0.41 Financial Structure 52.00 4.32 Risk Exposure 14.10 1.17 Cash Flow 25.80 2.14 Research & Development (4.1%) Core Competency 13.30 0.55 Research Competency 6.10 0.25 Process Scale-Up 3.70 0.15 Project Management 51.30 2.10 Intellectual Property 25.60 1.05 Finally, the overall weight supplier selection criteria were calculated. Figure 3 shows the percentages of the SOCCER model supplier selection criteria. The results show that cost structures are the first criteria in supplier selection, with 44.2% of the total weight. However, out of this weight, 23% focused on product cost. These results are understandable, especially when analyzing the importance of criteria in small and medium companies. Operational Capability came next, with about 23% of the total weightage. However, it is unexpected that Logistical Capability ranked first with a priority vector of 0.517 with 11.89%. Next in the Ranks is the Customer Approach, with 13.5% of the overall weight. Customer Relations was the most focused on Customer Approach in supplier selection criteria, priority vector of 0.503. Following this were the Key Customers (0.235), Customer Approach (0.146), External Relation (0.073), and 55, and lastly Market Position (0.043). The Market Position showed a low percentage of 0.58% of overall weights due to filtering. Thus, considering market position was the last thing they would consider. The Economic Performance stood in the second last place with 8.3% of overall weight. Altogether, the interviewees agreed that Financial Structures (0.520) was the foremost factor to be considered. Financial structure is the long-term and short-term company sources of capital composition. The suppliers manage their liabilities and equity to finance their operations. Financial Structures are significant if the company wants to have a long-term relationship with the suppliers to predict the supplier's performance in the future. A well- planned financial structure means stability and will build trust in the company in the long run. Finally, the overall weight showed that cost structure, operational capability, and customer approach with a total of 80.7% were the factors that contribute the most to supplier selection. 254 IIUM Engineering Journal, Vol. 24, No. 2, 2023 Al Hazza et al. https://doi.org/10.31436/iiumej.v24i2.2787 Fig. 3: Overall weight supplier selection criteria. 6. CONCLUSIONS This paper has illustrated a case study for the supplier selection in manufacturing corrugated cartons company in Malaysia. The Research outputs can be concluded as the followings: 1. The SOCCER model is one of the most comprehensive models covering most essential supplier selection criteria. 2. Integrating the AHP method and the SOCCER model gave a practical and valid framework. 3. Consulting the company's internal expertise will make the framework better understood. 4. Success in data gathering needs to recognize the bias due to specialty. 5. 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