**Evaluation of The Best E-commerce Websites in Malaysia Using Fuzzy AHP** \*\*Double blind review, please do not include authors information in this version \*\* Received Date: \*date Accepted Date: \*date Published Date: \*date **HIGHLIGHTS** - Fuzzy AHP is the method used in the study to ensure the researcher decides which e-commerce websites in Malaysia are the best. - The criteria and sub-criteria are important for determining the rank of a website. - The ranking of three alternatives which are Shopee, Lazada and PGMall shows which one is the best. **ABSTRACT** *E-commerce, often known as electronic commerce, is a method of doing business that involves purchasing and selling products and services via a digital network like the internet. The Fuzzy AHP method was used in this study to select the best e-commerce websites in Malaysia. The research aim is to determine the criteria when choosing e-commerce websites, identify sub-criteria that impact e-commerce website rankings and investigate the best rank of e-commerce in Malaysia. In this study, two decision-makers examine three criteria and eight sub-criteria to determine the best e-commerce websites in Malaysia. There are three websites to choose from Shopee, Lazada, and PGMall. The criteria are system quality, information quality, and service quality. At the same time, the sub-criteria are access speed, visual appearance, response time, reliable information, update information, accurate information, tracking order status, and payment alternatives. The primary data was used by distributing a set of questionnaires to the experts in the field. Shopee is the best e-commerce website in Malaysia, according to the results, with a normalised score of 0.4488. Lazada comes in second with a normalised 0.4360, and PGMall with a normalised 0.1153. As a result, Shopee outperforms the other two online transaction platforms, Lazada and PGMall.* ***Keywords:** E-commerce, Fuzzy AHP, Criteria, Sub-criteria, Decision makers, best e-commerce websites* # INTRODUCTION The internet has been the most significant thing in this world. The development of the technology in the system requires the internet to operate steadily. The Internet provides us with effective and efficient tools to gain information and services. It includes the communication tools that have been the basic tools in the interactive market for products and services. The growth of internet technology has had a significant impact on global commerce. The internet has entered a new phase of e-commerce and offers opportunities to connect businesses worldwide through the internet (Samsudin & Ahmad, 2014). E-commerce was introduced years ago, and people love to use it as it gives many benefits for them. According to Kabugumila (2016), e-commerce, also known as electronic commerce, is where we can buy and sell goods and services through an electronic network, such as the internet. We can also make payments and send data through e-commerce. E-commerce can be clarified into four categories which are business-to-business (B2B), business-to-customer (B2C), consumer-to-consumer (C2C) and consumer-to-business (C2B). B2B refers to the exchange of goods, information, or services between two companies. At the same time, B2C is a form of e-commerce where the company supplies goods or services directly to their customers. Next, consumer-to-consumer (C2C) is the consumer who sells or exchanges products with another consumer and C2B (consumer-to-business) is an e-commerce approach in which an individual sells a product or service to businesses. E-commerce can be used by consumers to browse the online store using their device to place orders for the products and services. Due to the fast internet network and their hectic daily schedule, most Malaysians utilise online shopping applications to purchase various things. Besides, buyers may look at the goods and compare prices with only one click. Online purchases are useful since purchasers may verify whether the item is available or out of stock without incurring any effort (Why E-Commerce Business Is Getting Important In Malaysia | Webshop999 Blog, 2013). Nevertheless, online purchasing techniques have gained popularity in recent years since it is convenient for them to shop as they do not have to face a long queue at the counter or the busy mall (Salman et al., 2020). Moreover, during the pandemic of covid-19, e-commerce in Malaysia continued expanding since everyone is required to stay at home to prevent outbreaks of the disease. Based on the Department of Statistics Malaysia Official Portal (2021), the income of e-commerce in 2020 is RM896.4 billion, which is increasing 32.7 per cent from 2019. As the pandemic begins in early 2020, e-commerce is proving to be the instrument of choice for people to purchase throughout the crisis. Furthermore, the growing smartphone usage in this generation causes them to access e-commerce websites more often than before. Since there are various types of e-commerce websites in Malaysia likes Lazada, Shopee and PGMall, the consumers have difficulties choosing which e-commerce websites to access for online shopping. The organisation also finds it hard to make a judgement about which sites to use for their online transactions. In addition, the rivalry among e-commerce websites to become the most popular e-commerce site has intensified. The website's quality can influence the mindset of the consumer to choose the websites. Therefore, it is important for the websites to satisfy the customer level to be the best e-commerce. Other than that, the change in the taste of some customers towards the online shopping sites creates curiosity from the company. Besides, human judgement for decision making is not reliable in our daily life. So, the study proposed the method of Fuzzy AHP to measure the performance of each of the e-commerce. Therefore, the study proposed to evaluate the e-commerce websites in Malaysia using Fuzzy AHP. The main objective of the research is to value the best e-commerce websites in Malaysia. Therefore, the sub-objectives for this study are to determine the criteria that are needed when choosing e-commerce websites, to identify sub-criteria that impact e-commerce website rankings and to investigate the best rank of e-commerce in Malaysia. The study is focused on evaluating the e-commerce websites based on the three criteria and three sub-criteria for each criterion. The criteria are system quality, information quality and service quality and the sub-criteria are access speed, visual appearance, response time, providing reliable information, providing update information, providing accurate information, tracking order status and payment alternatives. Three top e-commerce websites in Malaysia which are Shopee, Lazada and PGMall will be investigated to determine which one is the best. In addition, there are two experts from e-commerce websites who will be questioned about the study to get the result. # Fuzzy Analytical Hierarchy Process The Fuzzy Analytical Hierarchy Process (AHP) is one of the methods used in the multicriteria decision-making process. Fuzzy AHP develops the Analytical Hierarchy Process and fuzzy set theory method. Thomas Saaty (1980) invented the AHP to deal with complicated decision-making effectively. AHP is one of the strategies for using perception, preference, experience, and intuition in decision-making systems and is also a method for logically combining personal judgement and ideals (Afriliansyah et al., 2019). Based on the study by Patil (2018), this method helps the decision-maker define priorities and make the optimal conclusion. Thus, by reducing complex judgements to a set of pairwise comparisons and then synthesising the results, to capture both subjective and objective components of a decision. Crisp data is insufficient to simulate real-world situations in many Multiple Attribute Decision Making (MADM) scenarios. The fuzzy set theory may be employed in decision-making processes because of the inadequacies caused by the subjectivity of human judgements and the ambiguity of evidence (Aydın & Kahraman, 2013). Zadeh came up with a fuzzy set theory, and Bellman and Zadeh explained how to make decisions in fuzzy situations. Since then, many people have used fuzzy set theory to solve problems in uncertain conditions. Similarly, this research incorporates fuzzy decision-making theory, which takes into account the possibility of erroneous subjective judgements throughout the assessment process (Chen et al., 2005). On the other hand, although the traditional AHP technique uses crisp judgements to assess criteria and options, many real-world issues need fuzzy judgements. Experts may not be able to perform pairwise comparisons. Due to uncertainty and limited knowledge, professionals may not give precise numerical values when making pairwise comparisons. As a result, the fuzzy set theory and AHP are integrated into Fuzzy AHP to utilise interval values rather than crisp values. In this method, fuzzy numbers will be used in the judgement matrix for pairwise comparison (Aydın & Kahraman, 2013). The technique used is similar to the AHP method. AHP evaluates criteria and options using a 1–9 scale. It helps decision-makers create a hierarchy to choose the best option from a set of choices. A hierarchical structure has at least three levels. The first level at the top, which is the goal, in the centre consists of the specified qualities and lastly alternatives at the bottom. After establishing the hierarchy, pairwise comparisons of alternatives or criteria are used to determine priority. Lastly, the preferences collected are pooled to identify the optimal option. The Fuzzy AHP approach converts the AHP scale into a fuzzy triangular scale accessible in priority order (Aydın & Kahraman, 2013) (Dwi Putra et al., 2018). # METHODOLOGY The survey is conducted to evaluate the best e-commerce websites in Malaysia. The data was collected using the primary data. Then, the questionnaire distributed to two experts in e-commerce from e-commerce companies in Malaysia. The questionnaire consists of four sections which are Part A (demographic), Part B (the evaluation on the criteria, Part C (evaluation on the sub-criteria) and Part D (evaluation on the alternatives). Furthermore, three criteria and eight sub-criteria needed to be evaluated to find the best e-commerce in Malaysia. # Formula Implementation Step 1: Since our study aims to determine the best e-commerce in Malaysia using the fuzzy AHP, we need to construct the hierarchy structure. Our goal is to select the best e-commerce in Malaysia. Three main criteria have been chosen to be evaluated, namely quality system, information quality and service system. Each of the criteria has been divided into sub-criteria. The quality and information system comprises three sub-criteria which are access speed, visual appearance, response time, reliable information, updated information, and accurate information, respectively. Besides, the service system is divided into two sub-criteria which are tracking order status and payment alternatives. Three alternatives have been chosen to rank: Shopee, Lazada and PGMall. ![Diagram Description automatically generated](6309e32f81dfa_media/media/image1.png) **Figure 1**: Hierarchy structure of e-commerce selection Step 2: The decision-makers compare the criteria, sub-criteria and alternatives via linguistics terms shown in Table 1. **Table 1**: Linguistic terms and the corresponding triangular fuzzy numbers | Saaty scale | Definition | Fuzzy Triangular Scale | | ----------- | -------------------------- | ---------------------- | | 1 | Equally importance (EI) | (1,1,1) | | 3 | Weakly importance (WI) | (2,3,4) | | 5 | Fairly importance (FI) | (4,5,6) | | 7 | Strongly importance (SI) | (6,7,8) | | 9 | Absolutely importance (AI) | (9,9,9) | | 2 | The intermittent values | (1,2,3) | | 4 | | (3,4,5) | | 6 | | (5,6,7) | | 8 | | (7,8,9) | Source: Saaty (1980) Equation (1) below shows the pairwise contribution matrix. The triangular numbers indicate the decision-makers preference of criterion over criterion. Besides, the "tilde" represents the triangular number demonstration. (1) Step 3: Check for the consistency index or consistency ratio to assure the consistency of expert judgement in the evaluation phase. The consistency of an evaluation analysed using Equation (2), (2) where is consistency index, is the largest eigenvalue of the comparison matrix, and N is the dimension of matrix or number of criteria. The consistency ratio (CR) is being used to solve the final inconsistency in the pairwise comparisons. (2.1) where RI is the random index obtained from averaging the CI of a randomly generated reciprocal matrix (Saaty 1980). RI can be seen in Table 2. **Table 2**: Random index | N | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | | ----------------- | - | - | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | | Random index (RI) | 0 | 0 | 0.52 | 0.89 | 1.11 | 1.25 | 1.35 | 1.40 | 1.45 | 1.49 | Source: Saaty (1980) The closer the consistency index to zero, the greater the consistency. The consistency index should be equal to or lower than 0.10 to accept the comparison. If the result is greater than 0.10, it shows the inconsistency of the judgement. So, the decision-makers should go back and redo the assessments and comparisons. Step 4: Since there are more than one decision-maker, the average of the preference of each decision-maker ( ) will be calculated as shown in Equation (3) below. (3) Step 5: The updated pair wise contribution matrices is shown after the average of preference. (4) Step 6: Calculate the vector weight by the following step below: Step 6.1: Geometric mean method by (Buckley et al, 1985) of fuzzy comparison values of each criterion is calculated based on equation (5) below. (5) Step 6.2: Calculate the fuzzy weight of each criterion according to the step below. Step 6.2.1: Find the vector summation using equation (3.6.) given by vector summation = (6) Step 6.2.2: Find the inverse of the summation vector and arrange it in increasing order. (6.1) Step 6.2.3: Find the fuzzy weight of criterion ( ) by multiplying each r with the inverse vector. (6.2)  Step 7: De-fuzzified the fuzzy weight for criterion since it is still in fuzzy triangular numbers using the Centre of the area by applying Equation (7). (7) Step 8: Normalised the ![straight E subscript straight i](6309e32f81dfa_media/media/image17.png "{\"mathml\":\"\\\\E\\i\\\\\"}") because it is not a fuzzy number via Equation (8) (8) Step 2 to step 8 above is used to calculate the normalised weights of the criterion, sub-criterion, and alternatives. Then the multiplication of sub-criterion weight with respect to criteria weight needs to be obtained to get the sub-criteria's global weight. Next, the score for the alternatives can be calculated after the multiplication of the global weight sub-criterion with respect to alternatives weight. The final score for each alternative is obtained by carrying out a fuzzy arithmetic sum over each global weight of alternatives. The result will indicate the ranking of the alternatives. The alternative with the highest score is suggested to the decision-maker. The highest score defines the best e-commerce in Malaysia. **FINDINGS AND DISCUSSIONS** **Table 3**: Fuzzy Weight of criteria | **Criteria** | **Weight** | | ------------------- | ---------- | | System Quality | 0.5600 | | Information Quality | 0.3388 | | Service Quality | 0.1012 | | Total | 1 | The table 3 shows the result of the weight of criteria after calculating using the equation 1 to 8 by following each step at the methodology section. **Table 4**: Global Weight of sub-criteria | **Criteria** | **Sub-criteria** | **Global Weight** | | ------------------- | --------------------- | ----------------- | | System Quality | Access Speed | 0.3630 | | | Visual Appearance | 0.1513 | | | Respond Time | 0.0457 | | Information Quality | Reliable Information | 0.1691 | | | Update Information | 0.1183 | | | Accurate Information | 0.0515 | | Service Quality | Tracking Order Status | 0.0911 | | | Payment Alternative | 0.0101 | | | | **Shopee** | **Lazada** | **PGMall** | | ------------------------ | --------------------- | ---------- | ---------- | ---------- | | System Quality | Access Speed | 0.1707 | 0.1707 | 0.0217 | | | Visual Appearance | 0.0632 | 0.0632 | 0.0250 | | | Respond Time | 0.0188 | 0.0188 | 0.0082 | | Information Quality | Reliable Information | 0.0814 | 0.0760 | 0.0117 | | | Update Information | 0.0503 | 0.0457 | 0.0222 | | | Accurate Information | 0.0219 | 0.0199 | 0.0097 | | Service Quality | Tracking Order Status | 0.0380 | 0.0380 | 0.0150 | | | Payment Alternative | 0.0045 | 0.0038 | 0.0018 | | **Total** | **0.4488** | **0.4360** | **0.1153** | | | **Decreasing Order** | **0.4488** | **0.4360** | **0.1153** | | | **Rank Of Alternatives** | **1** | **2** | **3** | | Table 4 shows the global weight of sub-criteria after the weight of sub-criteria is multiply by the weight of criteria. **Table 5:** Rank of alternatives Table 5 shows that Shopee is the best e-commerce website in Malaysia, with a normalised 0.4488. Lazada comes in second place, with a normalised score of 0.4360. Finally, with a normalised score of 0.1153, PGMall is the lowest ranked of the three websites studied. It can conclude that Shopee is the first e-commerce websites at Malaysia based on the criteria that have been evaluated by the decision makers. Even though Lazada is the first established websites among these three, it cannot pass through Shopee in becoming the best websites. The result from the evaluation of the two experts on some of the criterion that have been investigated in this research shown that Shopee is the best than others. It is leading the websites to become first websites in Malaysia after the calculation using Fuzzy AHP in the research. **CONCLUSION AND RECOMMENDATIONS** This study aims to evaluate the best e-commerce websites in Malaysia based on the criterion and the sub-criterion studied in this research by using fuzzy AHP. The objectives are to determine the requirements for selecting e-commerce websites, identify sub-criteria that influence e-commerce website rankings, and investigate the best rank of e-commerce in Malaysia. In this study, all these objectives were met. According to the findings, the criteria and sub-criteria are important for determining the rank of a website. Furthermore, the ranking for the best e-commerce websites in Malaysia was a success. According to the results, Shopee is the best e-commerce website, with a normalised score of 0.4480. Second, Lazada is the best website after Shopee, with a score of 0.4360, and PGMall is the lowest ranked e-commerce website in Malaysia, with a score of 0.1153. As a result, we can conclude that Shopee is the superior e-commerce website in Malaysia, surpassing Lazada and PGMall. Even though the research only uses two experts in evaluating the e-commerce websites in Malaysia, the result is still acceptable since there are still two different opinions in evaluated the websites. The Fuzzy AHP method is one of the methods used to assist the researcher in making a decision. Assume the researcher wants to use the Fuzzy AHP method in the future. In that case, it is recommended to increase the number of decision-makers to ensure that different perspectives can evaluate the evaluation. As a result, the research can obtain more accurate results from the observation. Aside from that, there are numerous other methods for selecting e-commerce websites likes other MCDM methods. For the example Fuzzy TOPSIS, PROMETHEE, Fuzzy Delphi. **ACKNOWLEDGMENT** **REFERENCES** Afriliansyah, T., Nababan, E., & Situmorang, Z. (2019). Performance Analysis of Fuzzy AHP in The Rankings. *Proceedings Of The Proceedings Of The 1St Workshop On Multidisciplinary And Its Applications Part 1*, WMA-01 2018, 19-20 January 2018, Aceh, Indonesia. https://doi.org/10.4108/eai.20-1-2018.2281865 Aydin, S., & Kahraman, C. (2013). A New Fuzzy Analytic Hierarchy Process and Its Application to Vendor Selection Problem. *Journal Of Multiple-Valued Logic and Soft Computing, 20*(3-4), 353-371. https://www.researchgate.net/publication/267097528\_A\_New\_Fuzzy\_Analytic\_Hierarchy\_Process\_and\_Its\_Application\_to\_Vendor\_Selection\_Problem. Chen, M., Tzeng, G., & Tang, T. (2005). FUZZY MCDM APPROACH FOR EVALUATION OF EXPATRIATE ASSIGNMENTS. *International Journal Of Information Technology & Decision Making, 04*(02), 277-296. https://doi.org/10.1142/s0219622005001520 *Department of Statistics Malaysia Official Portal*. (2021, July 6). Department of Statistics Malaysia Official Portal. https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat\&cat=489\&bul\_id=c1FiaHRCQnlRdkxzUUFkNFJncWtEQT09\&menu\_id=b0pIV1E3RW40VWRTUkZocEhyZ1pLUT09 Kabugumila, M., Lushakuzi, S., & E. Mtui, J. (2016). E-Commerce: An Overview of Adoption and Its Effective Implementation. *International Journal Of Business And Social Science, 7*(4), 243-252. http://www.ijbssnet.com/journals/Vol\_7\_No\_4\_April\_2016/27.pdf. Patil, A. N. (2018, May). FUZZY AHP METHODOLOGY AND ITS SOLE APPLICATIONS. *International Journal of Management Research & Review, 8*(5), 24-32. https://www.researchgate.net/publication/329706185\_FUZZY\_AHP\_METHODOLOGY\_AND\_ITS\_SOLE\_APPLICATIONS Salman, A., Yusoff, M. A., Ling, T. P., & Sofiah, A. (2020). Determinants of online purchasing decisions among university students. *SEARCH Journal of Media and Communication Research*, 61– 73. https://www.researchgate.net/publication/342707952 Samsudin, & Ahmad. (2014). ONLINE SHOPPING PERCEPTION AMONG MALAYSIAN PROFESSIONALS. *Journal of Technology Management and Business, 1*(2). https://publisher.uthm.edu.my/ojs/index.php/jtmb/article/view/980 Saaty, T.L. (1980) The Analytic Hierarchy Process, McGrawHill, New York *Why E-commerce Business Is Getting Important In Malaysia | Webshop999 Blog*. (2013, April 17). Build Web Store Webshop | Malaysia E-commerce Website Solutions | Webshop999.http://www.webshop999.com/blog/why-e-commerce-business-is-getting-important-in-malaysia/