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INDEXED PUBLICATIONS2
CROSSREF CITATIONS0
CROSSREF · CITED PUBLICATIONS0.0%
CROSSREF · MEAN CITATIONS0.0

Crossref citation coverage: 2 / 2 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.

Research collection

2 publications

JOURNAL ARTICLE

Insights into employee satisfaction: Assessing job facilities and factors influencing contentment in the workplace among insurance companies in Bangladesh

Mohammad Ariful Islam Ariful · Md Golam Ramij Ramij · Jannatul Ferdous Rupa Rupa

International Journal of Research in Business and Social Science · 2024

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This study examines the Job facilities and the factors affecting employee satisfaction levels and how significantly they are correlated to each other. In the world of business research, one of the vital challenges is employee commitment toward the company. According to research, employee dedication and performance are strongly correlated with employee contentment. That is why employers and researchers are constantly looking for explanations for employee happiness. Several aspects affect employee satisfaction, some of which are obvious while others are not. This study explores how certain financial and non-financial variables relate to employee contentment. The survey has been done by a Likert scale questionnaire on a total of 200 employees from 10 Insurance companies in Bangladesh. According to this empirical study, a few non-financial variables, except salary, have a substantial relationship with employee satisfaction.

DOI 10.20525/ijrbs.v13i7.35500 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Online shopping behaviour on social media platforms from the perspective of trust and flow experience: a SEM-Neural Network Modeling

Tazizur Rahman · Mohammad Islam · Abul Khayer · Tania Islam

International Journal of Research in Business and Social Science · 2024

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This study aims to examine online shopping behaviour on social media platforms. This study formulates a research model integrating trust with the flow theory and some basic constructs of the UTAUT. To analyze the data from an online survey involving 305 participants actively making online purchases through social media platforms. This study applied the Structural Equation Modeling-Artificial Neural Networks (SEM-ANN) technique. Incorporating statistically significant SEM findings, the ANN model was used to analyze linear and nonlinear interactions among proposed variables. The research findings demonstrate that flow emerges as the most significant determinant, succeeded by effort expectancy, social influence, and performance expectancy, in defining the concept of trust. However, the sensitivity analysis using ANN indicates that effort expectancy is the most important factor in establishing trust, followed by flow, social influence, and performance expectancy. The predictive power of intention to use is noteworthy in determining actual use behaviour, with trust and flow emerging as influential factors favourably impacting this intention.

DOI 10.20525/ijrbs.v13i5.34140 Crossref citations0 OpenAlex citations