Trust across borders: buyer-supplier trust in global business-to-business E-commerce.
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This study focuses on trust formation and development in global buyer-supplier relationships. Trust affects all business relationships, especially global business-to-business (B2B) transactions due to the distances between buyers and suppliers. We use information signaling theory to examine how information indices and signals affect buyers’ trust in suppliers in global B2B commerce. Specifically, we examine how buyers’ trust is affected by (1) their perceptions of the national integrity and legal structure of suppliers’ country, and (2) third-party verifications of suppliers on B2B exchanges. Because buyer-supplier relationships usually evolve over time, we study how the effects of indices and signals change as the number of transactions between the partners increases. A survey of global organizational buyers finds that perceptions of national integrity, legal structure, and supplier verifications are all positively related to buyers’ trust. However, the number of prior transactions between buyers and suppliers moderates the impact of perceived legal structure on buyers’ trust.
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Cross-border transactional processes usually involve delivery risks and crossing language barriers, which may increase consumers' perceived risks and uncertainties and deter consumers from taking full advantage of cross-border e-commerce.
“For instance, the transactional processes usually involve delivery risks and crossing language barriers, which may increase consumers’ perceived risks and uncertainties and deter consumers from taking full advantage of cross-border e-commerce (Koh et al., 2012; Guo et al., 2018).”
From How Live Streaming Features Impact Consumers’ Purchase Intention in the Context of Cross-Border E-Commerce? A Research Based on SOR Theory (2021) · cites this paper as Koh et al., 2012
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- Authors
- Hong Kong University of Science and Technology, Koh, T., Fichman, M., Carnegie Mellon University, Kraut, R., & Carnegie Mellon University
- Affiliations
- Hong Kong University of Science and Technology (HK)
- Carnegie Mellon University (US)
- Venue
- Journal of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2012-11
- Volume
- 13
- Issue
- 11
- Pages
- 886-922
- ISSN
- 1536-9323 (ISSN-L)
- OpenAlex
- W3122186323
- Cited by
- 73
- References
- 82
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 8 · 2023: 7 · 2022: 7 · 2021: 7 · 2020: 9 · 2019: 4 · 2018: 4 · 2017: 3 · 2016: 2 · 2015: 6 · 2014: 5 · 2013: 1
- FWCI
- 8.84
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the Association for Information Systems (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Carnegie Mellon University
- Topics
- Social Sciences › Business, Management and Accounting › Business and International Management › E-commerce and Technology Innovations
- Social Sciences › Business, Management and Accounting › Management Information Systems › Outsourcing and Supply Chain Management
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- buyer-supplier trust, national integrity, legal structure, transaction volume, organizational buyers, cross-border relationships
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 ›
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