Investigating the impact of social media advertising and risk factors on customer online buying behavior: a trust-based perspective DOI Creative Commons
Riffut Jabeen, Kashif Ullah Khan,

Fahad Zain

и другие.

Future Business Journal, Год журнала: 2024, Номер 10(1)

Опубликована: Дек. 18, 2024

Abstract In the realm of ever-changing e-commerce, understanding dynamics customer online buying behavior (COBB) is pivotal. This study investigates impact risk factors—financial (FR), time (TR), and psychological (PR) along with social media advertising (SMA) on COBB mediating effect trust. Grounded stimulus–organism–response theory, research targets diverse segments including students, businessmen, employees, working women, housewives. To ensure a high response rate, an questionnaire was distributed via email, WhatsApp, groups buyers. Convenience sampling used to collect primary data from 350 respondents. Data analysis that employed Statistical Package for Social Sciences, descriptive statistics, correlation analysis, normality testing, regression performed reliability, validity hypothesis testing. The findings underscore significant negative factors (FR, TR, PR) building trust subsequent shopping behavior. has positive COBB. Furthermore, emerged as determinant COBB, thereby validating its pivotal role in consumer decision-making processes. Moreover, mediates relationship between factors, SMA consists both practical theoretical contributions, offering insights into nuanced interplay perceptions, effectiveness, dynamics, These are essential marketers, policymakers, researchers navigating evolving landscape e-commerce.

Язык: Английский

Leveraging Generative AI for Course Learning Outcome Categorization Using Bloom’s Taxonomy DOI Creative Commons
Omaima Almatrafi, Aditya Johri

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100404 - 100404

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Automatic Short Answer Grading in the LLM Era: Does GPT-4 with Prompt Engineering beat Traditional Models? DOI
Rafael Ferreira Mello, Cleon Pereira Júnior, Luiz Rodrigues

и другие.

Опубликована: Фев. 21, 2025

Язык: Английский

Процитировано

0

LLMs Performance in Answering Educational Questions in Brazilian Portuguese: A Preliminary Analysis on LLMs Potential to Support Diverse Educational Needs DOI
Luiz Rodrigues, Cleon Pereira Júnior, Newarney T. Costa

и другие.

Опубликована: Фев. 21, 2025

Язык: Английский

Процитировано

0

Evaluating the performance of ChatGPT and GPT-4o in coding classroom discourse data: A study of synchronous online mathematics instruction DOI Creative Commons
Simin Xu, Xiaowei Huang, Chung Kwan Lo

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер unknown, С. 100325 - 100325

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

1

HiBenchLLM: Historical Inquiry Benchmarking for Large Language Models DOI
Mathieu Alexandre Chartier,

Nabil Dakkoune,

G. Bourgeois

и другие.

Data & Knowledge Engineering, Год журнала: 2024, Номер unknown, С. 102383 - 102383

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0

ChatGMP: a case of AI chatbots in chemical engineering education towards the automation of repetitive tasks DOI Creative Commons
Fiammetta Caccavale, Carina L. Gargalo, Julian Kager

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер unknown, С. 100354 - 100354

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0

Near Feasibility, Distant Practicality: Empirical Analysis of Deploying and Using LLMs on Resource-Constrained Smartphones DOI

Mateus Monteiro Santos,

Aristoteles Peixoto Barros,

Luiz Rodrigues

и другие.

Опубликована: Дек. 9, 2024

Язык: Английский

Процитировано

0

Investigating the impact of social media advertising and risk factors on customer online buying behavior: a trust-based perspective DOI Creative Commons
Riffut Jabeen, Kashif Ullah Khan,

Fahad Zain

и другие.

Future Business Journal, Год журнала: 2024, Номер 10(1)

Опубликована: Дек. 18, 2024

Abstract In the realm of ever-changing e-commerce, understanding dynamics customer online buying behavior (COBB) is pivotal. This study investigates impact risk factors—financial (FR), time (TR), and psychological (PR) along with social media advertising (SMA) on COBB mediating effect trust. Grounded stimulus–organism–response theory, research targets diverse segments including students, businessmen, employees, working women, housewives. To ensure a high response rate, an questionnaire was distributed via email, WhatsApp, groups buyers. Convenience sampling used to collect primary data from 350 respondents. Data analysis that employed Statistical Package for Social Sciences, descriptive statistics, correlation analysis, normality testing, regression performed reliability, validity hypothesis testing. The findings underscore significant negative factors (FR, TR, PR) building trust subsequent shopping behavior. has positive COBB. Furthermore, emerged as determinant COBB, thereby validating its pivotal role in consumer decision-making processes. Moreover, mediates relationship between factors, SMA consists both practical theoretical contributions, offering insights into nuanced interplay perceptions, effectiveness, dynamics, These are essential marketers, policymakers, researchers navigating evolving landscape e-commerce.

Язык: Английский

Процитировано

0