Hierarchical Clustering for Functionalities E-Commerce Adoption
DOI:
https://doi.org/10.21107/kursor.v10i3.230Keywords:
Functionality e-commerce; Hierarchical clustering, E-commerce adoptionAbstract
Web functionality is one driver for e-commerce adoption. It is appeared the level of technological capabilities as well as the accentuation of the strategy put on e-commerce by the organization. Web functionality is related to the level of e-commerce relocation. Website with more functionality will give way better benefits for shoppers and trade partners. Functionalities of web are components that support the achievement of adoption benefits. Hierarchical clustering and ranking availability of e-commerce functionality is a challenging task. Ward Linkage algorithm was used to measure distance. This study proposed to get a grouping of e-commerce functionalities that influence e-commerce adoption and to get the ranking of the groups that most influence the achievement of these benefits. Result shows that functionalities that supports the achievement of every benefit of e-commerce has been clustered into two or three clusters, where each cluster also has been ranked to facilitate the achievement of these benefits
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[2] S. Kurnia, J. Choudrie, R. M. Mahbubur, and B. Alzougool, “E-commerce technology adoption: A Malaysian grocery SME retail sector study,†J. Bus. Res., vol. 68, no. 9, pp. 1906–1918, Sep. 2015.
[3] R. Awiagah, J. Kang, and J. I. Lim, “Factors affecting e-commerce adoption among SMEs in Ghana,†Inf. Dev., vol. 32, no. 4, pp. 815–836, Sep. 2016.
[4] H. O. Awa, O. U. Ojiabo, and B. C. Emecheta, “Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs,†J. Sci. Technol. Policy Manag., vol. 6, no. 1, pp. 76–94, Mar. 2015.
[5] N. Al-Qirim, Electronic Commerce in Small to Medium-Sized Enterprises: Frameworks, Issues and Implications,. USA: IDEA Group Publishing, 2004.
[6] J. Bao and X. Sun, “A Conceptual Model of Factors Affecting e-Commerce Adoption by SMEs in China,†in 2010 Fourth International Conference on Management of e-Commerce and e-Government (ICMeCG), 2010, pp. 172–175.
[7] E. Triandini, A. Djunaidy, and D. Siahaan, “Development of a conceptual model of E-commerce adoption for SMEs in Indonesia,†in 2013 International Conference on Information Technology and Electrical Engineering (ICITEE), 2013, pp. 93–96.
[8] R. Govindaraju and D. R. Chandra, “E-commerce adoption by Indonesian small, medium, and micro enterprises (SMMEs): Analysis of goals and barriers,†in 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN), 2011, pp. 113–117.
[9] S. Shah Alam, “Adoption of internet in Malaysian SMEs,†J. Small Bus. Enterp. Dev., vol. 16, no. 2, pp. 240–255, May 2009.
[10] S. Rao and G. Metts, “Electronic Commerce Development in Small and Medium Sized Enterprises A Stage Model and Its Implications,†Bus. Process Manag. J., vol. 9, pp. 11–32, 2003.
[11] E. Triandini, A. Djunaidy, and D. Siahaan, “Mapping Requirements into E-commerce Adoption Level : A Case Study Indonesia SMEs,†in The 5th International Confrencen on Information Technology for Cyber and IT Service Management, 2017, pp. 282–286.
[12] E. Santarelli and S. D’Altri, “The Diffusion of E-commerce among SMEs: Theoritical Implications and Empirical Evidence,†Small Bus. Econ., vol. 21, pp. 273–283, 2003.
[13] P. McCole, “A Profile of Adopters and Non-adopters of eCommerce in SME Professional Service Firms,†Australas. Mark. J., vol. 13, pp. 36–48, 2005.
[14] S. Chong, “Success in Electronic Commerce Implementation: A Cross Country Study of small and Medium-Sized Enterprises,†J. Enterp. Inf. Manag., vol. 21, no. 5, pp. 468–492, 2008.
[15] F. Ying and L. Fengli, “Empirical Research on Interaction between Electronic Commerce Adoption and Effect Evaluation in China SMEs,†in International Conference on Information Management, Innovation Management aand Industrial Engineering, 2012, pp. 5–8.
[16] M. Shaharudin, M. Omar, S. Elias, M. Ismail, S. Ali, and M. Fadzil, “Determinants of electronic commerce adoption in Malaysian SMEs’ furniture industry,†African J. Bus. Manag., vol. 6, pp. 3648–3661, 2012.
[17] W. Hong and Ke. Zhu, “Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level,†Inf. Manag., vol. 43, pp. 204–221, 2006.
[18] E. Triandini, A. Djunaidy, and D. Siahaan, “A Maturity Model for E-Commerce Adoption By Small And Medium Enterprises In Indonesia,†J. Electron. Commer. Organ., vol. 15, no. 1, pp. 44–58, 2017.
[19] E. Triandini, A. Djunaidy, and D. Siahaan, “Development of a conceptual model of E-commerce adoption for SMEs in Indonesia,†2013 Int. Conf. Inf. Technol. Electr. Eng., pp. 93–96, 2013.
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[21] C.-H. Tang, A.-C. Huang, M.-F. Tsai, and W.-J. Wang, “An efficient distributed hierarchical-clustering algorithm for large scale data,†2010, pp. 869–874.
[22] F. Chen, P. Deng, J. Wan, D. Zhang, A. V. Vasilakos, and X. Rong, “Data Mining for the Internet of Things: Literature Review and Challenges,†Int. J. Distrib. Sens. Networks, vol. 11, no. 8, p. 431047, Aug. 2015.
[23] R. Asif, A. Merceron, S. A. Ali, and N. G. Haider, “Analyzing undergraduate students’ performance using educational data mining,†Comput. Educ., vol. 113, pp. 177–194, Oct. 2017.
[24] Vijaya, A. Sinha, and R. Bateja, “A Review on Hierarchical Clustering Algorithms,†J. Eng. Appl. Sci., vol. 12, no. 24, pp. 7501–7507, 2017.
[25] R. Tibshirani, “Data Mining: Distances between Clustering, Hierarchical Clustering,†Department of Statistics and Machine Learning, Carnegie Mellon University, 2009
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2020-07-10
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