The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance
Abstract
Purpose: The purpose of this paper is to test the moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance. Design/methodology/approach: Based on a survey questionnaire with 151 participants in the Thai automotive industry supply chain, hierarchical regressions are used to test the moderating effects. Findings: Internal and supplier integration, but not customer integration, were positively associated with customer delivery performance. Technological and demand uncertainties were found to moderate the relationships between internal integration and customer delivery performance, and supplier integration and customer delivery performance. Research limitations/implications: The moderating effects of technological and demand uncertainties in the Thai automotive just‐in‐time (JIT) environment are explained. This research contributes to the development of a contingency theory of supply chain integration suggesting that the impacts of supply chain integration on customer delivery performance vary under different levels of technological and demand uncertainties. Practical implications: Managers recognize the diminishing effects of internal integration and supplier integration under demand uncertainty, and the increasing effect of supplier integration under high technological uncertainty. Originality/value: This study contributes to the supply chain management literature by clarifying the moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An updated paradigm for scale development incorporating unidimensionality and its assessment
Gerbing, D. W., & Anderson, J. C. (1988) · Journal of Marketing Research · doi:10.1177/002224378802500207 · Cited by 6,293
The impact of supply chain integration on performance: A contingency and configuration approach
Flynn, B. B., Huo, B., & Zhao, X. (2010) · Journal of Operations Management · doi:10.1016/j.jom.2009.06.001 · Cited by 3,310
Stevens, G. C. (1989) · International Journal of Physical Distribution & Materials Management · doi:10.1108/eum0000000000329 · Cited by 1,560
Liao, K., & Tu, Q. (2007) · Journal of Manufacturing Technology Management · doi:10.1108/17410380810843444 · Cited by 30
Cited by
Analysing supply chain integration through a systematic literature review: a normative perspective
Mustafa Kamal, M., & Irani, Z. (2014) · Supply Chain Management: An International Journal · doi:10.1108/scm-12-2013-0491 · Cited by 139
The role of outsourcing management process in improving the effectiveness of logistics outsourcing
Zhu, W., Ng, S. C. H., Wang, Z., & Zhao, X. (2017) · International Journal of Production Economics · doi:10.1016/j.ijpe.2017.03.004 · Cited by 110
Metadata
- Authors
- Boon‐itt, S., & Yew Wong, C.
- Venue
- International Journal of Physical Distribution & Logistics Management
- Publisher
- Emerald
- Published
- 2011-04-19
- Volume
- 41
- Issue
- 3
- Pages
- 253-276
- ISSN
- 0960-0035 (ISSN-L)
- OpenAlex
- W2120465336
- Cited by
- 178
- References
- 4
- FWCI
- 22.01
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance. https://app.cochat.ai/papers/10.1108/09600031111123787
- The paper
- Boon‐itt, S., & Yew Wong, C. (2011). The moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance. International Journal of Physical Distribution & Logistics Management. https://doi.org/10.1108/09600031111123787
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
