Supporting and inhibiting factors of e-commerce adoption: Exploring the sellers' side in Indonesia

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7 Citations (Scopus)

Abstract

In 2015, the number of internet user in Indonesia, already reached 88.1 million. There are around 5 million SMEs in Indonesia, but only about 75 thousand are already using e-commerce which means that the adoption of e-commerce by SMEs is still relatively low. Hence, this research aims to investigate what are the supporting and inhibiting factors for sellers (SMEs) in adopting e-commerce. The initial list of factors from the literature review are validated by 11 experts which resulted 25 supporting and 17 inhibiting factors grouped by using a combination of TOE framework and UTAUT model, namely I-TOE framework. Then, we distributed questionnaires on the basis of Fuzzy-AHP to rank the factors. The results show the top supporting factors are "Perceived ease of use", "Technology infrastructure available", "Customer communication improved", and "Encouragement from environment culture" while the top inhibiting factors are "Perceived no benefit gain", "Supporting infrastructure unavailable", "Lack of business compatibility", and "Vendor less friendly to customer".

Original languageEnglish
Title of host publication2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-214
Number of pages8
ISBN (Electronic)9781509046294
DOIs
Publication statusPublished - 6 Mar 2017
Event8th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016 - Malang, Indonesia
Duration: 15 Oct 201616 Oct 2016

Publication series

Name2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016

Conference

Conference8th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
Country/TerritoryIndonesia
CityMalang
Period15/10/1616/10/16

Keywords

  • Indonesia
  • TOE
  • UTAUT
  • e-commerce adoption
  • fuzzy-AHP

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