Influencing Factors of Social Commerce Behavior in Saudi Arabia

Razi, Mohamed Jalaldeen Mohamed; Sarabdeen, Masahina; Tamrin, Mohd Izzuddin Mohd; Kijas, A.C. Muhammadu

doi:10.1109/iccisci.2019.8716463

Cited by 3 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Alotaibi [31] highlighted that in terms of m-commerce consumer loyalty, there were no major variations across gender, age, or experience. Razi et al [32] have found that students are actively engaged in social commerce activities, which impact their purchase intentions and behavior positively.…”

Section: Related Workmentioning

confidence: 99%

An Empirical Study of Mobile Commerce and Customers Security Perception in Saudi Arabia

et al. 2022

View full text Add to dashboard Cite

Digital transformation of businesses has seen tremendous growth recently, moreover, COVID-19 has increased online shopping. However, it is important for businesses that customers’ online shopping experience is secure and joyful. In this paper, customers’ security perception regarding some leading mobile commerce applications in Saudi Arabia is explored. Our survey questions focused on three aspects, namely: Consumer rating, trustworthiness, and credit card security. The results highlight that consumers perceive that mobile commerce applications in Saudi Arabia need further improvement in security. In this work, a model to improve customers’ security perception in Saudi Arabia is presented. This model can be generalized to other geographical regions as well. The model outlines different actions for practitioners and policymakers that help in improving security infrastructure, authentication mechanisms, and trustworthiness.

show abstract

Section: Related Workmentioning

confidence: 99%

An Empirical Study of Mobile Commerce and Customers Security Perception in Saudi Arabia

et al. 2022

View full text Add to dashboard Cite

show abstract

“…College students are considered as the most vibrant group in terms of the use of social networking sites due to their technology-education orientated and information seeking as well as multi-tasking nature. The use of social networks for college students creates a lasting environment where according to Razi et al (2017) they feel bonded in terms of closeness and emotionally. Thus they anticipate some form of social and moral support from social network colleagues.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Social Commerce Purchase and Recommendation Intentions Within the Context of Swift Guanxi Among Chinese College Students

2023

View full text Add to dashboard Cite

This study examined the factors determining social commerce purchase and recommendation intentions within the context of swift guanxi. The data analysis was conducted with Smart PLS 3.0 using the structural equation modeling technique. The results have illustrated that perceived usefulness and perceived ease of use were significant in determining both the recommendation and social commerce purchase intentions. In addition, eWOM was also a significant predictor of both social commerce purchase and recommendation intentions. Interestingly the results showed that trust in social network sites was not significant in influencing social commerce purchase and recommendation intentions. Also, mutual understanding and relationship harmony were found to predict the social commerce purchase and recommendation intentions. The implications of these and other results findings of the study are discussed.

show abstract

“…The use of social media and technology appropriate for aspects of shopping has become a major problem for retailers and related businesses [8]. The number of factors that influence the growth of social commerce is due to the increase of popularity of social media, network notification, social search and online collaborative shopping tools [9].…”

Section: Introductionmentioning

confidence: 99%

Classification of User Comment Using Word2vec and SVM Classifier

Kurnia¹

2020

IJATCSE

View full text Add to dashboard Cite

Social media provides data that can be used for text classification, but these social media do not have a rating system. Comments taken from social media such as Twitter, does not provide a rating system which can help to classify comments based on their rating score. The goal of this study is to build a comment classification model using Word2vec and SVM classifier that can classify comments based on a rating scale from 1-5. The training data will be taken from user comments from play.google.com website in which each comment already has a rating. The purpose of the model is to classify comments from social media about mobile network applications. Comment classification is performed in order to help these businesses, as well as the users, to know the overall satisfaction of users who use these applications. The best F1 score obtained from this research using class elimination and stop word removal is 0.795.

show abstract

Influencing Factors of Social Commerce Behavior in Saudi Arabia

Cited by 3 publications

References 12 publications

An Empirical Study of Mobile Commerce and Customers Security Perception in Saudi Arabia

An Empirical Study of Mobile Commerce and Customers Security Perception in Saudi Arabia

Determinants of Social Commerce Purchase and Recommendation Intentions Within the Context of Swift Guanxi Among Chinese College Students

Classification of User Comment Using Word2vec and SVM Classifier

Contact Info

Product

Resources

About