Smes’ E-Commerce Adoption Towards Consumer Experience

Taufik, Nuryanti; Prabowo, Faizal Haris Eko; Santosa, Allicia Deana; Mandasari, Andina Eka

doi:10.24198/jbm.v21i2.373

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…The study showed that agribusiness SME owners' experience, benefit from e-commerce use, observability, Trialability and years of business were significant factors that influence the adoption of e-commerce. Taufik et al (2020) reported that the good experience of consumers of e-commerce influences e-commerce significantly because the ability of the consumer to operate an ecommerce device has the potential to motivate the consumer to purchase other devices. However, this study supports the findings of Hossain et al (2022), Ahmad et al (2015, and Pearson and Grandon (2005), who found that as SMEs' experience grows, they become less willing to push for e-commerce adoption, owing to consumer goodwill and market understanding.…”

Section: Objective 3: Factors Influencing Agribusiness Smes Adoption ...mentioning

confidence: 99%

Adoption of electronic commerce by agribusiness small medium enterprises in the upper east region of Ghana

Selorm¹,

Akaba²,

William³

2022

J. Dev. Agric. Econ.

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Technological evolution has triggered more advanced market-based approaches to the transfer of goods, services, and information. In Ghana, Agribusiness small-medium enterprises' electronic commerce adoption is concentrated in Accra and Kumasi. This study spotting the research gap in Agribusiness small-medium enterprises' electronic commerce adoption selected the Upper East Region for the study. The study is centered on examining e-commerce adoption by agribusiness small-medium enterprises' and the preferred electronic commerce applications adopted by Agribusiness smallmedium enterprises' in the Upper East region of Ghana. A simple random sampling technique was adopted for the study. The results of the study show that 91% of agribusiness had adopted electronic commerce for their operations with the major observation that being electronic commerce environment is good for business. The major barrier to adoption was the high cost of adoption of electronic commerce applications. Owner experience, observability, benefits from electronic commerce, trialability and years in business were all found to be factors influencing agribusiness small-medium enterprises' adoption of electronic commerce. Furthermore, the results also indicated that Agribusiness smallmedium enterprises in the Upper East region use electronic commerce applications mostly for customer relation management and interorganisation system. In conclusion to the study, electronic commerce adoption was observed to be rising among agribusiness small-medium enterprises in the Upper East region but the greatest hurdle to their adoption was the high cost of adoption of these applications. The study, therefore, recommends that financial institutions, electronic commerce application manufacturers, and the government should collaborate to subsidy the cost of these electronic applications to agribusiness small-medium enterprises.

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Section: Objective 3: Factors Influencing Agribusiness Smes Adoption ...mentioning

confidence: 99%

Adoption of electronic commerce by agribusiness small medium enterprises in the upper east region of Ghana

Selorm¹,

Akaba²,

William³

2022

J. Dev. Agric. Econ.

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“…The Drastic changes in the market followed by the development of information technology have created various opportunities and challenges on the growth of the internet, paid online learning sites and information technology by generating new ways of learning in understanding consumers [1]. The evolution and development of the internet, especially regarding the way of transactions such as on online shopping sites has not only changed the way people buy but also changed the strategies used for marketing and payment methods to attract and retain customers by adjusting communication in a certain way [2].…”

Section: Introductionmentioning

confidence: 99%

“…It is estimated that the pay later usage rate will grow by 33.3% during 2022-2028 in Asia Pacific, with total money transactions on pay later predicted to increase from 82.81 billion dollars in 2021 to 749.22 billion dollars in 2028 [7]. One of the reasons the pay later feature is growing rapidly in Indonesia is because of the various conveniences offered that really help its use to meet daily needs, such as to manage finances, fulfill needs and simplify the payment transaction process from traveling to shopping [2].…”

Section: Introductionmentioning

confidence: 99%

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Pay Later Risk Management: A Review of FMECA and Potential Customer Prediction Frameworks Through the Application of Machine Learning

Nugraha Adz Zikri,

Suwarningsih

2023

International Journal of Advances in Data and Information Syste

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The development of technology continues to develop and gradually change the way people buy such as on online shopping sites. The increase in internet use, especially in the use of E Commerce, has given birth to great potential in the market, especially in Indonesia. These changes prompted the birth of various payment methods. One of them is Pay Later. 27% of the 3560 samples decided to use Pay Later with all the conveniences offered. However, the development of Pay Later is not synchronized with good risk management. The use of Pay Later, which is not targeted at the right consumers, causes PT. XYZ suffered losses due to 22.37% of users defaulting on Pay Later installments. The purpose of this study is to reduce Pay Later default users by answering what factors cause consumers to default. To support this study, the authors used FMECA, Cause Effect Diagrams and conducted tests using Machine Learning to improve company efficiency. Through critical matrix analysis, the author gets 3 priority failure modes, Users default, users disappear, and users experience payment delays. In solving the problems in this study, the authors provide recommendations in the form of a new framework in the form of analyzing the best Pay Later offers by analyzing consumer behavior patterns in an E Commerce by utilizing Machine Learning. However, future research will need to be conducted correlation analysis and static testing in testing attribute correlation before testing algorithms when building machine learning models. The authors also suggested comparing using other methods to improve risk management in this study.

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Smes’ E-Commerce Adoption Towards Consumer Experience

Cited by 2 publications

References 10 publications

Adoption of electronic commerce by agribusiness small medium enterprises in the upper east region of Ghana

Adoption of electronic commerce by agribusiness small medium enterprises in the upper east region of Ghana

Pay Later Risk Management: A Review of FMECA and Potential Customer Prediction Frameworks Through the Application of Machine Learning

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