Development of measures to assess the ERP adoption of small and medium enterprises
Abstract
Purpose: The purpose of this paper is to contribute to the development of measures to assess the ERP adoption of small and medium‐sized enterprises. Design/methodology/approach: The paper follows Churchill's guideline for developing measures that have desirable reliability and validity. The pilot data are used to develop a proper measurement. The survey data, based on the 126 valid responses of 328 companies, are analysed by structural equation modelling (SEM) statistical methods. Findings: The paper finds that the dimensions affecting ERP adoption show that characteristics of the CEO and perceived benefits possess positive effects on ERP adoption, while cost and technology have negative effects on ERP adoption. However, only “perceived benefits” is a significant dimension. It is surprising that the cost of the ERP system does not significantly affect ERP adoption. Research limitations/implications: The paper shows that the sample size should be taken into consideration when generalising the findings, and extended data and measures are required for further in‐depth investigation in specific areas. Practical implications: The paper points out that the managers of SMEs with limited resources can find many ways to get more resources from governments. Government managers should be more realistically set the goal of helping firms in a healthy condition to adopt e‐business instead of setting the goal of improving the e‐business readiness of all SMEs. To help all CEOs of SMEs to realise the potential benefits, governments can work with academic research groups to set up forums and workshops to broadcast knowledge. Originality/value: The paper develops measurements to assess the ERP adoption of small and medium‐sized enterprises. The results offer practical help for government managers to better understand ERP adoption with institutional help in Taiwan. Meanwhile, researchers interested in IT/IS can use the information provided here to guide their future enquiries.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
SMEs rarely have the cognate experience and resources to effectively implement ERP solutions.
“Though SMEs rarely have the cognate experience and resources to effectively implement ERP solutions (Chuang, Nakatani, & Zhou, 2009;Shiau et al., 2009)”
From Using T-O-E theoretical framework to study the adoption of ERP solution (2016) · cites this paper as Shiau et al., 2009
The citation lists haven’t been fetched yet
References 71 · Cited by 129
- Authors
- Shiau, W., Hsu, P., & Wang, J.
- Affiliations
- Ming Chuan University (TW)
- National Central University (TW)
- Venue
- Journal of Enterprise Information Management
- Publisher
- Emerald
- Published
- 2009-02-13
- Volume
- 22
- Issue
- 1/2
- Pages
- 99-118
- ISSN
- 1741-0398 (ISSN-L)
- OpenAlex
- W2159588344
- Cited by
- 129
- References
- 71
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 2 · 2021: 8 · 2020: 5 · 2019: 5 · 2018: 4 · 2017: 6 · 2016: 11 · 2015: 15 · 2014: 11 · 2013: 14 · 2012: 10
- FWCI
- 15.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Enterprise Information Management (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Keywords
- enterprise resource planning, ERP adoption, small and medium-sized enterprises, perceived benefits, CEO characteristics, technology adoption, e-business adoption, SME support, Taiwan
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
