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Article . 2023
License: CC BY
Data sources: ZENODO
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Article . 2023
License: CC BY
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
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Pengembangan Model Penerimaan Website eCommerce pada Pelaku UMKM berbasis Teori Penerimaan Teknologi

Authors: Faradillah, Muhammad Fadhiel Alie;

Pengembangan Model Penerimaan Website eCommerce pada Pelaku UMKM berbasis Teori Penerimaan Teknologi

Abstract

Penelitian ini bertujuan untuk mengembangkan model maupun teori penerimaan teknologi agar selanjutnya dapat digunakan untuk mengukur tingkat penerimaan teknologi masyarakat/orang (people) terhadap inovasi maupun teknologi yang telah ada dalam upaya optimalisasi keberlangsungan bisnis proses dalam suatu organisasi. Pengujian Model dilakukan melalui pendekatan SEM dengan bantuan Smart PLS dalam pengolahan dan analisis data. Pada penelitian ini, beberapa variabel yang diidentifikasi dapat mendukung penerapan teknologi dijadikan constructs dalam mengembangkan model penerimaan yang telah ada, yaitu: TAM, IDT, dan ECT. Hasil pengujian inner dan outer model menunjukkan hasil yang signifikan pada hampir semua dugaan yang telah dibangun. Selain itu, semua constructs yang diusulkan juga terbukti secara empiris valid dan reliabel dalam membangun model pengembangan ini. Aspek lain seperti budaya masyarakat, lingkungan, infrastruktur TI selanjutnya dapat dikaji lebih dalam dan menjadi constructs tambahan untuk penelitian sejenis. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green