What triggers impulse purchase in Facebook commerce?

Leong, Lai Ying; Jaafar, Noor Ismawati; Sulaiman, Ainin

doi:10.1504/ijmc.2018.092679

Cited by 19 publications

(14 citation statements)

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“…Besides CMB, we also compared the late and early respondents using an independent t-test to assess the non-response bias (Leong, Jaafar, & Ainin, 2018b). Table 6 shows that the differences are insignificant and thus there is no nonresponse bias in this study.…”

Section: Non-response Biasmentioning

confidence: 98%

Predicting trust in online advertising with an SEM-artificial neural network approach

Leong

Hew

Ooi

et al. 2020

Expert Systems with Applications

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Section: Non-response Biasmentioning

confidence: 98%

Predicting trust in online advertising with an SEM-artificial neural network approach

Leong

Hew

Ooi

et al. 2020

Expert Systems with Applications

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“…Social influence refers to how perceptions of others influence a target person's beliefs (Chen et al , 2017) and can be used as an indirect stimulus of inspiration (Leong et al , 2018). Social influence was regarded by numerous scholars in previous innovation technology studies and accepted as an essential driving factor in behavioural purpose to embrace technology (Fang et al , 2016; Alavijeh et al , 2018; Bhattacharya et al , 2019; Giao et al , 2020).…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

“…Xiang et al (2016) claim that other people’s beliefs can impact the behaviour of others and this is also the case in the field of online shopping. This is why the social influence of online shopping can be exploited in the sense of consumer intentions and attitudes through relational benefit and site commitment (Chen et al , 2017; Leong et al , 2018; Giao et al , 2020; Zafar et al , 2020).…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Consumers’ sustainable online purchase behaviour during COVID-19 pandemic: the role of relational benefit and site commitment

Polas

Tabash

Jahanshahi

et al. 2022

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Purpose This study aims to investigate the factors that influence the sustainable online purchase intentions of consumers during the COVID-19 pandemic. This study also examines the role of relational benefit and site commitment in the study model. Design/methodology/approach Data were obtained from a survey of 356 Bangladeshi consumers who were voluntarily using the internet during the COVID-19 pandemic. Data were analyzed using partial least square structural equation modelling with Smart PLS 3.0 and SPSS V25 tools. Findings The results show a positive and significant relationship between consumers’ personal innovativeness and impulse purchase orientation with their relational benefit and site commitment, social influence with relational benefit, relational benefit with site commitment, site commitment with the intention to purchase. Moreover, the study found that relational benefit mediates the relationship between impulse purchase orientation and social influence with site commitment. The results also indicate that site commitment mediates the relationship between personal innovativeness and impulse purchase orientation with the intention to purchase. The results further indicate that site commitment mediates the relationship between relational benefit and intention to purchase. Practical implications The findings allow online stores to consider crucial factors in their policies when making strategic decisions regarding the factors impacting consumers’ online purchasing intention during the COVID-19 pandemic. Originality/value In this study, a research framework is developed with a focus on the sustainable consumer intention to purchase. This study, therefore, adds to the existing literature by analyzing the factors that determine online purchase intentions during the COVID-19 pandemic in Bangladesh, given the limited number of studies on the online consumer behavioral intentions in related circumstances to COVID-19.

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“…Purposive sampling was the most used sampling technique (see Table 4). Additionally, various product categories were tested in previous works, where apparel was the most used product category [108], [109], followed by restaurant coupons [73]. Many studies did not specify the type of product.…”

Section: B Online Impulsive Product Categories Research Context Popmentioning

confidence: 99%

“…On the other hand, it is not necessary that consumers actually purchase the product if they encounter a strong UBI [112], and therefore, UBI and the actual impulsive buying are considered to be different concepts. Previous studies either focused on UBI [14], [15], [36], [37], [73], [111] or actual impulsive buying [14], [88], [109], [110]. Few studies considered both the impulse buying responses [40], [105], [112], [114], wherein the UBI was a mediator, and the outcome referred to the actual impulsive buying.…”

Section: ) Outcomesmentioning

confidence: 99%

Understanding Online Impulse Buying Behavior in Social Commerce: A Systematic Literature Review

et al. 2020

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What triggers impulse purchase in Facebook commerce?

Cited by 19 publications

References 0 publications

Predicting trust in online advertising with an SEM-artificial neural network approach

Predicting trust in online advertising with an SEM-artificial neural network approach

Consumers’ sustainable online purchase behaviour during COVID-19 pandemic: the role of relational benefit and site commitment

Understanding Online Impulse Buying Behavior in Social Commerce: A Systematic Literature Review

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