Keywords : SEM


Heuristic Evaluation of E-Learning

Hale H. Turhangil Erenlergil Erenler

International Journal of Organizational Leadership, Volume 7, Issue 2, Pages 195-210
DOI: 10.33844/ijol.2018.60235

As Knowledge Management applications, E-learning platforms have been used in many organizations. Universities as knowledge management appliers and early adopters of E-learning platforms as knowledge-sharing channels, making education independent of time and location, created new opportunities for students to become active and collaborative participants of their learning. In this respect, learning management systems offered tools and modules to facilitate knowledge construction, knowledge gathering and sharing among its participants. This study examined the critical factors of usability evaluation of the learning management system Moodle as part of students’ blended learning in a computer literacy course at a funded University in Turkey. The model based on Nielsen’s 10 heuristics and was tested with data from 236 students. Descriptive statistics showed that students generally agreed with the system and did not face problems when working with it. The study used structural equation modeling (SEM) for data analysis and found eight factors to be significant in the research model after an exploratory factor analysis.

A new Integration Model to Evaluate Strategic Performance of Supply Chain

Gholamreza Gholampour; Abdul Rahman Bin Rahim

International Journal of Organizational Leadership, Volume 3, Issue 2, Pages 127-140
DOI: 10.33844/ijol.2014.60274

Nowadays, Supply Chain Management (SCM) is one of the most important and complex issues for automakers in the world. The main objectives of this research were to investigate the factors that predict strategic performance of supply chain by doing quantitative research at Iran Khodro Company (IKCO) in Iran. Based on supply chain theories, strategic performance of supply chain was predicted by Information Technology (IT), Organizational Learning (OL), and Product Innovation (PRI) in our research at the first time in an automotive company. Stratified random sampling was used to determine the sample size. Accordingly, 250 questionnaires were distributed among experts and supply chain specialists at IKCO. According to Supplying Automotive Parts Company (SPSC) variable as the main dependent variable, Path Analysis (PA) technique was used to explore casual relationships among variables using multiple regression analysis in SPSS. The Confirmatory Factor Analysis (CFA) was utilized based on Maximum Likelihood (ML) analysis of normality, outliers, composite reliability, and validity to test hypotheses by using AMOS. PA, measurement model, and structural model were analyzed in order to examine the conceptual model. The results from multiple regression, path analysis, and Structural Equation Modeling (SEM) were same. Thus, all hypotheses were supported by SPSS and SEM analyses. The findings of the study are discussed in detail.