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Record W4400654315 · doi:10.5267/j.ijdns.2024.4.013

Linking the role of e-commerce and financial literacy on MSME's sustainability performance during the digital era

2024· article· en· W4400654315 on OpenAlexvenueno aff
Sri Dewi Wahyundaru, Windhu Putra, Mukti Wibowo, Elvia Ivada, Preatmi Nurastuti, Cornelius Damar Sasongko, Moh. Miftachul Choiri, Dwi Yuzaria

Bibliographic record

VenueInternational Journal of Data and Network Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilitySmall and medium-sized enterprisesBusinessSimple random samplePopulationSample (material)Descriptive statisticsLiteracyKnowledge managementMarketingEnvironmental economicsFinanceComputer scienceEconomicsStatisticsEconomic growthMathematics

Abstract

fetched live from OpenAlex

In recent years, E-Commerce has experienced a very significant increase. E-commerce provides a broad overview of technology, processes and practices that can be carried out without using paper as a means of transactions. E-commerce can be a solution to the paper waste problem which is an environmental issue that can lead to social problems. Thus, e-commerce has a vital role in achieving business sustainability performance. E-commerce has had a big influence on the social and economic growth of today's society. Business management's ability to manage financial information is an important indicator in influencing Micro, Small and Medium Enterprises’ (MSME's) business performance. Good managements’ financial literacy equips MSMEs with knowledge and skill empowering MSMEs to make informed financial decisions, manage resources effectively and promote sustainable development. This research aims to analyze the relationship between E-Commerce and the sustainability performance of MSMEs and analyze the relationship between financial literacy and its positive and significant relationship with the sustainability performance of MSMEs. The research method uses a descriptive method with a quantitative approach. The population in this research are MSMEs managers in Indonesia who have comprehensive knowledge regarding the operations and performance of MSMEs. In this study, researchers used a simple random sampling technique with a sample size of 478 MSME managers. Data analysis in this research uses the Partial Least Square (PLS) technique which is an alternative method based on the variance of the variables used. The stages of data analysis are validity testing, reliability testing and hypothesis testing. The independent variables in this research are e-commerce and financial literacy, while the dependent variable is MSME sustainability performance. The results of this research show that e-commerce has a positive and significant relationship with MSME sustainability performance and financial literacy has a positive and significant relationship to MSME sustainability performance. In addition, e-commerce has a significant influence on the sustainability performance of MSMEs because the presence of e-commerce is one of the marketing alternatives used to reach more vendors and customers which can change the supply chain leads to social problem solution such as food distribution. Further, e-commerce may minimize traveling long distances for shopping resulting to the carbon footprint reduction. MSMEs have the same opportunity to use e-commerce as an alternative to maximize performance. However, not all MSMEs have the capability to use and utilize e-commerce optimally. After all, knowing good financial management will make it easier to make sustainable decisions since the higher the level of financial literacy, the MSME players can optimize their sustainability performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.302
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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