Indonesian Journal of Electrical Engineering and Computer Science Vol. 17, No. 1, January 2020, pp. 440~447 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v17.i1.pp440-447  440 Validating the factors influencing social commerce adoption in small and medium enterprise in malaysia Walid Abdulla Ali, Muriati Mukhtar, Ibrahim Mohamed Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Malaysia Article Info ABSTRACT Article history: Electronic commerce has been growing at a rapid rate in many countries, including developing countries. In recent years, social media and social Received Apr 1, 2019 networking sites have become popular and such popularity has led to a novel Revised Jun 1, 2019 e-commerce branch known as social commerce. In Malaysia, it is observed Accepted Jul 7, 2019 that individuals and organizations have begun to sell and purchase using social media. But studies on s-commerce adoption in Malaysia are still lacking. Therefore, this study aimed to investigate the effects of Keywords: technological, organizational, and trust factors on social commerce adoption among SMEs in Malaysia. This paper presented the factors, collected from Electronic Commerce literature, which influence the adoption of social commerce, and the results Malaysia of an exploratory pilot study. Organizational Factors Social Commerce Technological Factors Copyright © 2020 Institute of Advanced Engineering and Science. Trust Factors All rights reserved. Corresponding Author: Walid Abdulla Ali, Faculty of Information Science and Technology, University Kebangsaan Malayisa, Malayia. Email: [email protected] 1. INTRODUCTION E-commerce is an emerging and convergence of numerous main information technologies in business practices [1]. Electronic commerce (E- commerce) has been growing in a rapid rate in many countries including developing countries such as Arab and Asia countries. In recent years, the increasing popularity of social media and social networking sites has given rise to a new stream of electronic commerce, called social commerce. Social commerce is a new stream and subset of e-commerce [2]. By combining e- commerce activities with social media, social commerce enables consumers to participate, communicate, and interact in the online selling and buying of products and services. However, many e-commerce companies today are still trying to find out which factors influence consumers to participate in social commerce [3]. E-commerce is dividing into three categories: business to business or B2B (Cisco), business to consumer or B2C (Amazon), and consumer to consumer or C2C (eBay [4].S-commerce is different from e- commerce in terms of organization objectives, customer relationships and system procedures. First, the oganizational goal of e-commerce is to increase efficiency with the strategies used in searchers’ one-click purchasing, specification-centered virtual catalogs and recommendations built on the prior shopping pattern of consumers., On the other hand, social commerce is more centered on social goals like networking, cooperation and sharing information, while shopping is only a secondary concern. In respect of customer relations, customers often communicate with e-commerce platforms (individual and independent) from other customers, whereas s-commerce entails online publics supporting social relationship to improve customers’ interaction. Moving on to system interaction, e-commerce refers to a classic form of interaction, ysung one- way browsing. In this approach, customer-derived information is seldom made available to businesses or their rivals. However, in social commerce, social and interactive approaches are developed, allowing Journal homepage: http://ijeecs.iaescore.com Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  441 customers to provide their feedback and to make known their thoughts, and share information with their online community and with businesses [5]. Malaysia is among the first countries in Asia to establish a Ministry of e-commerce development and to be the leader in promoting the growth of ICT with the support of several bodies like the Malaysian Communications and Multimedia Commission and Multimedia Development Corporation [6]. The emergence of s-commerce in Malaysia has been an interesting but challenging phenomenon that cannot be ignored. Majority of the people in Malaysia have begun to sell and purchase using social media, but studies on s-commerce are still lacking, SMEs in developing countries still have a low level of IS adoption, it is important to focus on how to enhance the internal infrastructure of these organizations to increase their level of adoption in Malaysia. and what little there is has focused on forecasts, speculations, experiences and status reports on s-commerce in Malaysia [7]. 2. RESEARCH METHOD This present study began with a comprehensive review of the literature and compiled a detailed list of variables determined as important factors in the adoption and use of social commerce. On the basis of the literature review, this study investigated the influential variables in the adoption of s-commerce (SC) by enterprises from various aspects. First, SC was viewed as a technological innovation; the study examined SMEs’ adoption of SC from an innovation dispersion perspective. Secondly, the success of SC could be influenced by features of the organization itself; therefore, the appropriate trust factors were included in the analysis based on the internal characteristics of the firm. Following a thorough assessment of variables examined earlier, a conceptual model was created (see Figure 1) which facilitated the research direction. The model comprised three aspects of the factors: 1, Technological factors, 2, Organizational factors, and 3, trust factors. Figure 1. Model of social commerce adoption H1: Technological factors positively affect the behavioral intention to use SC among SMEs. H2: Organizational factors positively affect the behavioral intention to use SC among SMEs. H3: Trust factors positively affect the behavioral intention to use SC among SMEs. H4: Behavioral intention to use SC is closely related to the net benefits of SMEs. A quantitative research approach was employed in this pilot study. The participants were Malaysian owners and managers of SMEs. The selection of the participants (N=200) was for the study sample of and done employing random sampling. With regard to he number of the sample, SEM analysis requires the sample to be not less than 100 [8]. Validating the factors influencing social commerce adoption in small and medium … (Walid Abdulla Ali) 4 42  ISSN: 2502-4752 Furthermore, employing smart PLS path modeling indicates that the sample size to be 30-100 cases. Therefore, 100 respondents were deemed adequate. The questionnaire design was based on prior literature adapted accordingly to suit this study[9].The survey questionnaire employed for collection of the data from the sample was derived from earlier works on social commerce and utilised as presented in Table 1. The quesrionnaire consists of 67 items adapted by the researchers based on the objectives of the current study. In response to each item, the participant was required to choose one of the five-point Likert- scales that ranged from (1) “strongly disagree” to (5), “strongly agree.” Copies of the survey questionnaire were disseminated to 100 SME managers in Malaysia online and manually but only 45 returned questionnaires were deemed useful for analysis. The data were analysed wmploying SEM through smart PLS 2 software. Table 1. Varlables and Itmes Constructs Question description References I would find the social commerce services system useful in my work job. Perceived Using social commerce services enables me to accomplish tasks more quickly [10] Usefulness Using social commerce services enables me to accomplish tasks more efficiently. [11] If I use social commerce services, I will spend less time on routine job tasks. Using social commerce services would make it easier to do my job tasks. Using social commerce increases my professional performance. Service quality Social commerce understands the specific needs of its users. I feel safe when I use social commerce. [12] When sellers on social commerce promise to do something by a certain time, they should follow [13] through. [14] Sellers on social commerce must always be willing to help customers. [15] My overall opinion of the services provided by social commerce is very good. [16] The social commerce fits with all aspects of our work Compatibility The social commerce is consistent with our company culture. [14] Transformation towards social commerce adoption in our company is favorable. [17] Social commerce is compatible with our IT infrastructure. The adoption of social commerce is consistent with our business strategy. This s-commerce firm provides sufficient information when I try to make a transaction. Information The web site provides updated information. [18] quality It is easy to find the information that I need. [15] Overall, I think this s-commerce firm provides useful information. [19] The web site provides timely information. This s-commerce firm provides reliable information My top management is likely to consider the adoption of social commerce as strategically Top management important. [20] support  Top management would support the use of social commerce.  Top management would provide resources necessary for the adoption of social commerce [21]  My top management is willing to take risks involved in the adoption of social commerce Our Our management constantly encourages the employees to use new technologies in their daily work. Our organization is well-computerized using a local area network IT Readiness We have a high bandwidth Internet connectivity. [22] Our organization has individuals who are experts and well-skilled in IT and social commerce [16] technologies. We have experts who are able to plan, carry out, and evaluate all procedures related to adoption and implementation of social commerce technology. Our organization is well-computerized using a local area network. My company provided me complete training in using cloud computing. The training gave us confidence in use of cloud computing [21] Training My learning and training is/was useful for online shopping. [23] My level of understanding was substantially improved after going through the training program on cloud computing. I have had training to use social commerce and the internet to shop online. On social commerce, some people would offer suggestions when I needed help. Financial support When faced with difficulties, some people on social commerce would help me discover the cause [24] and provide me with suggestions. [16] When I encountered a problem, some people on social commerce would give me information to [25] help me overcome the problem. When faced with difficulties, some people on social commerce are on my side with me. I believe the financial information I provide with Social Network will not be manipulated by inappropriate parties [26] Security  I am confident that the private financial information I provide with Social Network will be secured [27]  Using credit cards to purchase from this Social Network is safe  In general, making payments online in Social Network is risk free.  I think this Social Network shows great concern for the security of any transactions  I think this Social Network has mechanisms to ensure the safe transmission of its financial Indonesian J Elec Eng & Comp Sci, Vol. 17, No. 1, January 2020 : 440 - 447 Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  443 Constructs Question description References information Most e-commerce systems are capable of processing a large number of transactions, connections, Reliability or large orders efficiently. [28]  E-commerce technologies are effective in keeping the accurate value of data. [14]  The online bookstore shows a sincere interest in solving customer problems.  Transactions with the online bookstore are error-free.  The online bookstore has adequate security  People who are important to me think that I should use social commerce services. Social Influence I would use social commerce services if my colleagues used them. [10]  People who influence my behavior think I should use social commerce services. [29]  Using internet banking service indicate me to have a higher status than those who do not [30]  The government encourages using the social commerce services system.  I think positively about selling products through social commerce. Attitudes  I like to visit social commerce for selling my product. [31]  I like to use the social commerce when contact with buyer [32]  Using social networking sites for social commerce is a good idea. [33]  Using the Internet to purchase a product seems an intelligent idea to me  I intend to use is-commerce service in the near future Behavioural  I predict I would use s-commerce service in the near future [10] Intention  I plan to use s-commerce service in the near future [29] Use S-  We intend to continue using SC in our organization. [34] Commerce  Our organization has sought for adaption of SC technology in our work. Adoption  I will recommend others to use social commerce.  I think that using social networking sites can save me time in conducting social commerce. Perceived Net  The social commerce helps the organization provide new products or services to customers [34] Benefits  The social commerce helps the organization enhance competitiveness or create strategic [31] advantages.  The social commerce enables the organization to respond more quickly to change. [26]  The social commerce helps the organization increase return on investment. [35] [36]  The social commerce helps the organization to achieve its goal and improve job performance  Using this Website enables me to accomplish a shopping task more quickly than using traditional stores.  Using this Website increases my productivity in shopping (e.g. making purchase decisions or finding product information within the shortest time frame).  I intend to use Social Network for my next purchase  I can save money by using this Website  3. RESULTS AND ANALYSIS Partial least squares (PLS) technique through the SmartPLS 2.0 software was applied to analyse the data collected. Components-based structural equation modeling (SEM) such as PLS is rapidly becoming a widely-used alternative to covariance-based SEM. The data analysis was conducted with SPSS version 22 and Smart PLS version 2. Specifically, the sample's descriptive statistics were obtained through the former software. On the other hand, following the suggestion of [37], a two-step analysis approach was adopted in analyzing the data, whereby the measurement model was first estimated prior to assessing the structural model. 3.1. Descriptive Statistics The current study used a descriptive analysis of the profile of the participants. This type of analysis is conducted at the early stage of any data analysis prior to carrying out other types of statistical analyses. In this study, the respondents’ characteristics are important since they provide better insights into or information of the study population. In the current study, a number of 100 questionnaires were distributed to the Malaysia SMEs in Selangor in the year of 2018. However, only 45 questionnaires were collected. From the collected questionnaires, for pilot study only 45 questionnaires were analysed. These results show that the majority of the respondents were females in this study. Moreover, the results showed that in terms of their age, most of the respondents were at the age group of over 40 years. Mainly, the respondents held Bachelor degree. Furthermore, the descriptive analysis reveals that the majority of the population (95.6%) was represented by those small size enterprises having 4-19 employees. The reason behind this higher response rate is due to the greater number of small medium enterprise operating in Selangor Malaysia, the targeted areas where the data was collected for this study. As seen in Table 2, [38]pointed out that the acceptable value of Cronbach’s alpha coefficient is 0.70 or above for an instrument to be considered reliable . The results confirmed that all scales met the required Cronbach’s alpha (0.70) and above ). The results are shown in Table 3. The Cronbach’s alpha value is 0.960, Validating the factors influencing social commerce adoption in small and medium … (Walid Abdulla Ali) 4 44  ISSN: 2502-4752 which is indicative of the excellent reliability. The results confirmed that all items be 0.978 above 0.70 the result is Excellent According to [38]. Table 2. Alpha Coefficient Ranges and Strength Alpha Coefficient Range Strength of Association < 0.6 Poor 0.6- to < 0.7 Moderate 0.7- to < 0.8 Good 0.8- to < 0.9 Very good > 0.9 Excellent Table 3. Reliability Items Of The Questionnaire In Pilot Study Pilot test of measurements ( n=45) Variable No Variables No of Items Cronbach’s alpha 1 Perceived Usefulness 5 0.941 2 Social commerce service quality 4 0.925 3 Compatibility 5 0927 4 Information quality 6 0.918 5 Top management support 5 0.946 6 IT Readiness 5 0.856 7 Financial support for adoption 4 0.947 of social commerce 8 Training 5 0.917 9 Security 5 0.936 10 Reliability 4 0.894 11 Social Influence 5 0.879 12 Attitudes 5 0.923 13 Behavioural intention to use 4 0.954 social-commerce 14 NET Benefit 5 0.972 N of Items 67 0.978 3.2. Measurement Model The measurement model consists of relationships among the latent variables and their (item) indicators. It is necessary to first establish construct validity for the measurement model before assessing the structural model for hypothesis testing. Construct validity concerns the extent to which the indicators reflect their underlying constructs (latent variables). Items in the measurement model need to demonstrate sufficient convergent and discriminant validity as a condition for establishing construct validity. As recommended by [39],factor loadings, composite reliability and average variance extracted (AVE) were used to assess convergent validity. See in Table 4 lists the indicator loadings/weights, reliabilities and AVE for all the items listed in the model. As shown in the Table 4, the CR values ranged from 0.911 to 0. 0.978, while those of the Cronbach’s alpha values were from 0.709to 0.967. Also, AVE values were above (>0.5) All the above values are at the recommended threshold value of 0.70. Moreover, in comparing the CR values with the Cronbach’s alpha values, it is evident that CR is indeed a stronger measuring criterion for assessing the internal consistency reliability. Thus, the results of Cronbach’s alpha and CR indicate that the investigated constructs of the current study have high levels of internal consistency reliability. 4. CONCLUSION The present study aimed to examine the effects of technological, organizational, and trust factors on SC adoption among SMEs in Malaysia. In this study, 45 respondents were chosen from different levels of management to complete the questionnaire and provide their feedback in terms of their understanding of it. Their feedback was used to further refine the instrument and to guarantee its effectiveness in collecting data. The current study was proved to be reliable and valid. This is because the loadings of all investigated factors were above the recommended value 0.7, thus showing that the indicator reliability was acceptable. The results also revealed that the values of the construct composite reliability and Cronbach’s alpha exceeded the suggested value of 0.7, thus implying that the internal consistency reliability was acceptable. Concerning the AVE of the constructs, they also exceeded the value of 0.5 suggested by previous research, indicating acceptable level of the convergent validity. Indonesian J Elec Eng & Comp Sci, Vol. 17, No. 1, January 2020 : 440 - 447 Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  445 Table 4. Results of Measurements Model–Convergent Validity Constructs Items Loading AVE CR Perceived Usefulness PU1 0.922 0.809 0.955 PU2 0.918 PU3 0.871 PU4 0.898 PU5 0.887 Social commerce service quality SCSQ1 0.894 0.816 0.947 SCSQ2 0.914 SCSQ3 0.925 SCSQ4 0.881 Compatibility CM1 0.842 0.775 0.945 CM2 0.927 CM3 0.899 CM4 0.908 CM5 0.821 Information quality IQ1 0.864 0.709 0.936 IQ2 0.864 IQ3 0.791 IQ4 0.820 IQ5 0.841 IQ6 0.871 Top management support TMS1 0.924 0.822 0.958 TMS2 0.918 TM3 0.901 TMS4 0.884 TMS5 0.906 IT Readiness ITR1 0.717 0.636 0.897 ITR2 0.801 ITR3 0.831 ITR4 0.868 ITR5 0.764 Financial support for adoption of social commerce FS1 0.921 0.861 0.961 FS2 0.937 FS3 0.919 FS4 0.935 Training T1 0.676 0.755 0.938 T2 0.921 T3 0.930 T4 0.896 T5 0.895 Security S1 0.883 0.792 0.950 S2 0.895 S3 0.847 S4 0.879 S5 0.941 Reliability R1 0.880 0.748 0.922 R2 0.901 R3 0.807 R4 0.868 Social Influence SI1 0.854 0.672 0.911 SI2 0.709 SI3 0.889 SI4 0.840 SI5 0.795 Attitudes AT1 0.823 0.764 0.942 AT2 0.834 AT3 0.924 AT4 0.899 AT5 0.887 Behavioural intention to use social-commerce BI1 0.903 0.879 0.967 BI2 0.950 BI3 0.943 BI4 0.953 NET Benefit NB1 0.947 0.898 0.978 NB2 0.951 NB3 0.918 NB4 0.956 NB5 0.967 • Factor Loadings (>0.7) • Composite reliability (CR >0.7) • Average variance extracted AVE (>0.5) Validating the factors influencing social commerce adoption in small and medium … (Walid Abdulla Ali) 4 46  ISSN: 2502-4752 ACKNOWLEDGEMENTS The author would like to thank the National University of Malaysia (UKM) for funding this research under research grant, FRGS/2/2014/ICT01/UKM/02/. 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Shee, "Measuring e-learning systems success in an organizational context: Scale development and validation," Computers in Human Behavior, vol. 23, no. 4, pp. 1792-1808, 2007. [37] J. C. Anderson and D. W. J. P. b. Gerbing, "Structural equation modeling in practice: A review and recommended two-step approach," vol. 103, no. 3, p. 411, 1988. [38] J. F. Hair, "Research methods for business," 2007. [39] J. F. Hair, W. C. Black, B. J. Babin, R. E. Anderson, R. L. J. P. P. H. N. J. h. C. Tatham, and r. J. o. A. Psychology, "Multivariate data analysis 6th Edition," vol. 87, pp. 49-74, 2006. BIOGRAPHIES OF AUTHORS Walid Abdulla Ali is PhD student in the Faculty of Information Science and Technology, Universiti Kebangsaan Mlaysia (UKM). His reserch interst areas include soical commerce adoption among SMEs in Malaysia. Muriati Muhktar is currently an Associate Professor at the Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM) and a Head of Service Science Research Group. Her research interst focus on the Service Science , E-Supply Chain and Simulation and Modelling. Ibrahim Mohamed is head of software engineering programme at the Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM). His specialization is on the Accounting Information System , Business Process Modeling, IT Audit and Control. Validating the factors influencing social commerce adoption in small and medium … (Walid Abdulla Ali)