Suchergebnisse

"Decision Support Systems" published on by Oxford University Press.

ABSTRACTA stream of research over the past decade that identifies predictors of e‐learning success suggests that there are several critical success factors (CSFs) that must be managed effectively to fully realize promise for e‐learning. Grounded in constructivist learning theories, this study advances previous work on CSFs in university online education. Structural equation modeling is applied to examine the determinants of students' satisfaction and their perceived learning outcomes in the context of university online courses. The independent variables of motivation (intrinsic and extrinsic), student self‐regulation, dialogue (instructor‐student, and student‐student), instructor, and course design are examined as potential determinants of online learning outcomes. A total of 372 responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicate that instructor‐student dialogue, student‐student dialogue, instructor, and course design significantly affect students' satisfaction and learning outcomes. However, both extrinsic student motivation and student self‐regulation have no significant relationship with user satisfaction and learning outcomes. Finally, intrinsic student motivation affects learning outcomes but not user satisfaction. The findings suggest that course design, instructor, and dialogue are the strongest predictors of user satisfaction and learning outcomes.

As the globalization of business activities broadens and diversifies
logistics operations, many logistics managers have found themselves
challenged by extreme complexities and uncertainties. Consequently,
planning and control of multinational firms (MNFs) have become onerous
due to the multiplicity of international decision environments. Perhaps
the most effective way of coping with such challenges is to utilize an
integrated decision support system (IDSS) linking world‐wide
communication and distribution networks among the parent company, its
foreign business partners and third‐party logisticians. In response to
such a need, provides important guidelines for the design and
development of an integrated DSS that helps the multinational firm
centrally to control and co‐ordinate international transfers.

ABSTRACTThe past several decades of e‐learning empirical research have advanced our understanding of the effective management of critical success factors (CSFs) of e‐learning. Meanwhile, the proliferation of measures of dependent and independent variables has been overelaborated. We argue that a significant reduction in dependent and independent variables and their measures is necessary for building an e‐learning success model, and such a model should incorporate the interdependent (not independent) process nature of e‐learning success. We applied structural equation modeling to empirically validate a comprehensive model of e‐learning success at the university level. Our research advances existing literature on CSFs of e‐learning and provides a basis for comparing existing research results as well as guiding future empirical research to build robust e‐learning theories. A total of 372 valid unduplicated responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicated that the e‐learning success model satisfactorily explains and predicts the interdependency of six CSFs of e‐learning systems (course design quality, instructor, motivation, student‐student dialog, student‐instructor dialog, and self‐regulated learning) and perceived learning outcomes.

ABSTRACTIn this study, structural equation modeling is applied to examine the determinants of students' satisfaction and their perceived learning outcomes in the context of university online courses. Independent variables included in the study are course structure, instructor feedback, self‐motivation, learning style, interaction, and instructor facilitation as potential determinants of online learning. A total of 397 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest were used to examine the structural model. The results indicated that all of the antecedent variables significantly affect students' satisfaction. Of the six antecedent variables hypothesized to affect the perceived learning outcomes, only instructor feedback and learning style are significant. The structural model results also reveal that user satisfaction is a significant predictor of learning outcomes. The findings suggest online education can be a superior mode of instruction if it is targeted to learners with specific learning styles (visual and read/write learning styles) and with timely, meaningful instructor feedback of various types.