Theory Acceptance Model and Purchase Intention in Online Shopping

Ananda, Nova Adhitya; Fietroh, Muhammad Nur; Mikhratunnisa, Mikhratunnisa; Rizqi, Reza Muhammad

doi:10.2991/assehr.k.200827.042

Cited by 8 publications

(10 citation statements)

References 3 publications

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“…The findings suggest that consumers believe PEOU to be a key element in determining the PU of online shopping (p < 0.05). This result was confirmed by the prior studies which done by [21], 20,19]. When the online shopping is simple to be accessed by users, they can attain their shopping objectives easily, and thus, increase the perceived usefulness on online shopping among them.…”

Section: Discussionsupporting

confidence: 79%

“…Rattanaburi and Vongurai [19] explained that PEOU of the mobile shopping applications is significantly affected the PU among the Generation Y in Thailand. Additionally, this relationship has also been empirically investigated by several researchers and found to have positive relationship in various contexts [20,21]. Hence, it is hypothesized that: H1: There is a positive relationship between perceived usefulness and perceived ease of use of using online shopping during the Covid-19 pandemic.…”

Section: Relationship Between Perceived Usefulness (Pu) and Perceived...mentioning

confidence: 97%

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Upsurge of Online Shopping in Malaysia during COVID-19 Pandemic

Moorthy¹,

Ci²,

Kamarudin³

et al. 2023

Business, Management and Economics

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The aim of this study is to assess the factors, perceived usefulness (PU), perceived ease of use (PEOU), subjective norms (SN), perceived risk (PR) and situational influences (SI)) that influence the consumers’ behavioral intention to use online shopping during the Coronavirus time. This research has adopted the Technology Acceptance Model (TAM) as its theoretical base. This research is a quantitative research wherein data were collected through online questionnaire using convenience sampling method. A total of 203 valid samples were collected from Malaysian respondents from selected States. Then, single and multiple linear regression analysis were conducted to test the hypotheses. The results concluded that perceived usefulness, perceived ease of use and situational influences have significant influence on Malaysian consumers’ behavioral intention to adopt online shopping during pandemic times. However, subjective norms and perceived risk have showed an insignificant relationship with consumers’ behavioral intention. The findings have implications for Malaysian government and SME companies in Malaysia in promoting online business.

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Section: Discussionsupporting

confidence: 79%

Section: Relationship Between Perceived Usefulness (Pu) and Perceived...mentioning

confidence: 97%

Upsurge of Online Shopping in Malaysia during COVID-19 Pandemic

Moorthy¹,

Ci²,

Kamarudin³

et al. 2023

Business, Management and Economics

View full text Add to dashboard Cite

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“…Numerous studies in the e-commerce domain related to consumer behavior relied on TAM from the perspectives of website characteristics or customer characteristics (Ananda et al, 2020;Aref & Okasha, 2020;Kalpoe, 2020;Makame et al, 2014;Nasution et al, 2019;Valencia et al, 2019).The TAM model focuses on functional and hedonic values that arise from website use and their impact on consumers, it pays little attention to the impact of service dimension on consumers' continued intention to engage in e-commerce transactions. It is not surprising that, TAM, if generally applied, does not capture or contradict some of the unique contextual logistics of last-mile features due to a lack of domain specifics.…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

The Relationship Between E-Commerce Last-Mile Logistics and Online Repurchasing Intention in Egypt

عبد الحميد

2024

المجلة الدولية للسياسات العامة في مصر

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The widespread accessibility of the Internet, alongside the rapid advancements in digital technologies, has resulted in a marked surge in the adoption of e-commerce, both on a global scale and within the Egyptian market. Online shopping has increased significantly due to consumers' convenient access to a wide range of goods and services they may purchase anywhere and anytime. This significant change has caused businesses to operate differently and influenced how consumers behave, creating new challenges to overcome and opportunities for businesses to grow. The final customer touchpoint of delivering physical products, last-mile logistics, has always been known for its complexity and cost within the supply chain. This crucial stage involves navigating busy cities, handling large volumes of deliveries, and meeting specific customer needs. Recognizing the importance of last-mile delivery for e-commerce success, this study aimed to uncover the challenges and opportunities to understand its impact on customer satisfaction. Delving into the heart of Egypt's B2C e-commerce scene, this research investigates the relationship between consumer experiences with last-mile logistics and their tendency to repurchase from online platforms. Here, "last-mile logistics" encompasses both the forward delivery of products to customers and the reverse logistics of managing returns. The study focused on consumer electronics, a dominant category in Egypt's online market, accounting for over 60% of online purchases (Statista.com, 2022). The study was applied on Amazon.eg. to account for the diverse performances across different platforms and ensure a comprehensive examination of research hypotheses. The analysis revealed a strong association between order fulfillment, reverse logistics, and the likelihood of repeat online purchasing in Egypt. It also highlighted the pivotal role the refunding process plays for return orders and how these returns are managed.

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“…Even with the plethora of tools, techniques, and methods that are available -the domain faces inherent challenges when dealing with data mining concerning its storage due to the lengthy size of the dataset, features evolution during its analysis, and concept evolution with the extraction of useful data [10], [11]. Mining a large collection of the dataset to extract meaningful data thus, often requires a great ordeal of improved technique, methods, and tools to aid in the effective management of the stored data vis-àvis data generated with user access to the Internet daily [12]- [14].…”

Section: Introductionmentioning

confidence: 99%

FePARM: The Frequency-Patterned Associative Rule Mining Framework on Consumer Purchasing-Pattern for Online Shops

Malasowe,

Okpako,

Ashioba

et al. 2024

AIMS Research Journal

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Transaction data often is a true presentation of consumers’ buying behavior, stored as a set of relational records, which properly harnessed via mining – can help businesses improve their sales volume as a decision support system. Managing such a system can pose many issues to biz such as feature evolution, concept evolution, concept drift, and infinite data length – and often makes it impractical to effectively store such big-data. To curb this, previous studies have assumed data to be stationary in using associative rule mining. This has deprived such systems of the flexibility and adaptiveness required to handle the dynamics of concept drift that characterizes transaction datasets. Our study thus proposes a basket frequent pattern growth trained associative rule mining model to handle large data. The dataset was retrieved from the Delta-Mall Asaba and consists of 556,000 transaction consumer records. The model consists of six-layers, and yields the best result with a 0.1 value for both the confidence and support level(s) at a 94% accuracy, sensitivity of 87%, and a specificity of 32% with a 20-second convergence and processing time. Keywords: Big-Data Analysis, Feature Evolution, Inventory Model, Market Basket Analysis, Businesses, Transactional Data Streams, Concept Drift CISDI Journal Reference Format Malasowe, B.O., Okpako, E.A., Ashioba, N.O., Ejeh, P.O., Ojugo, A.A. & Ako, R.E. (2024): FePARM: The Frequency-Patterned Associative Rule Mining Framework on Consumer Purchasing-Pattern for Online Shops. Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 15 No 2, Pp 1-14. dx.doi.org/10.22624/AIMS/CISDI/V15N2P2. Available online at www.isteams.net/cisdijournal

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Theory Acceptance Model and Purchase Intention in Online Shopping

Cited by 8 publications

References 3 publications

Upsurge of Online Shopping in Malaysia during COVID-19 Pandemic

Upsurge of Online Shopping in Malaysia during COVID-19 Pandemic

The Relationship Between E-Commerce Last-Mile Logistics and Online Repurchasing Intention in Egypt

FePARM: The Frequency-Patterned Associative Rule Mining Framework on Consumer Purchasing-Pattern for Online Shops

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