Modifications in interpretive structural modelling methodology to enhance its applicability in group decision process and power of discrimination

Though technology support of group decision making has long been believed to increase the number of ideas generated and the overall quality of decisions, research on this topic has failed to provide consistent support of these outcomes. Facilitation of the group decision process by specially trained experts is believed to add even further to the benefits the technology brings. The effects of facilitation have been tested in many configurations, yet, here too, researchers have not been able to consistently identify the benefits. The literature shows that prior research in this area has been based on the outcomes of the group decision process focusing on the quantity of ideas generated and group member retrospective perceptions of the process. This suggests that researchers took a black box approach to studying the effects of facilitation in group support systems (GSS) adoption and use subsequently ignoring important aspects of group process and the effects of facilitation in that process. To that end, analysis has been done from the lens of adaptive structuration theory (AST) of 48 homogeneous decision groups in terms of setting, task, and prior relevant participant experience; an excellent environment in which to observe how group members act (make appropriation moves) to adopt and use GSS differently in differing facilitative contexts. This study found that process restrictiveness significantly affects the quantity and types of appropriation moves over the course of a decision task. An unprecedented finding was that different individual facilitators affect the quantity and types of appropriation moves even when holding the treatment restrictiveness constant. I also performed an original extension of the method suggested by AST by disaggregating appropriation moves into the source and target of interactions. This study successfully opens the black box of GSS facilitation and shows analysis of process reveals nuanced differences in factors that affect appropriation that have not been apparent from prior, outcomes-based analyses.

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Ranking of barriers for the internet of things implementation in the E-learning platform

10.21203/rs.3.rs-936550/v1 ◽

2021 ◽

Author(s):

Vinay Kumar Yadav ◽

Sanjeev Yadav

Keyword(s):

Internet Of Things ◽

Success Factors ◽

Learning System ◽

The Internet ◽

Technological Advancement ◽

Structural Modelling ◽

Interpretive Structural Modelling ◽

Learning Platform ◽

Modelling Methodology ◽

E Learning

Abstract Learning through the Web or training via e-learning is rising exponentially and is gradually preferred by conventional ways of education and training. This massive change is directly related to digital computer technological advancement. The transformation driven by innovation in computer technology has enhanced the reach of e-learning and education, making the process of sharing knowledge easy, clear, and efficient. The E-learning system relies on various success factors from several viewpoints, such as framework, organisational alignment, instructor, and student support. This paper aims to identify the critical barriers to the Internet of Thing implementation in e-learning and to establish a relational relationship between identified barriers using the Interpretive Structural Modelling approach. This paper has established some primary barriers that are useful for Internet of Things implementation in E-learning by research scholars and industrial practitioners. For the study of the driving force and dependency power of the E-learning barrier, Interpretive Structural Modelling methodology was used to classify interrelationships between barriers for improved understanding and relationships between these barriers, and Management Cross Impact Multiplications were conducted to estimate the magnitude of these relationships. Applied to classification analysis, which is used for analysing the driving power and dependence power of E-learning barriers.

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