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A Multi-Methodology Study of the Historic Impact of Soft Systems Methodology and Its Associated Data Visualization Approach in the Context of Operations and Business Strategy (open access)

A Multi-Methodology Study of the Historic Impact of Soft Systems Methodology and Its Associated Data Visualization Approach in the Context of Operations and Business Strategy

The purpose of this three-essay dissertation was to expand knowledge and theory regarding soft systems methodologies (SSMs) and data visualization approaches in business, engineering, and other social sciences. The first essay depicts a bibliometric analysis study of the historic impacts of SSM from 1980-2018 on business, engineering, and other social sciences fields. This study found 285 articles that described or employed SSM for research and included outcomes such as top SSM authors, author citation impacts, common dissemination outlets, time-bound distribution of publications, and other relevant findings. This study provided a picture of who, what, why, when, and where SSM has had the greatest impact on academic thought and practice. The second essay presents research on the academic impact of Systemigrams, an associated data visualization approach, finding examples of conceptual or research development that employed Systemigrams to depict complex problem situations. Recommendations for improvement of designing these data visualizations to increase their field use resulted from this study. The final essay leverages a selection of the articles as use cases to produce a grounded theory study to identify phenomena that arose from the use of SSM for operations and firm strategy research. This study identified two broad themes including (i) scope, …
Date: December 2018
Creator: Warren, Scott Joseph
System: The UNT Digital Library
A Grounded Theory Model of the Relationship between Big Data and an Analytics Driven Supply Chain Competitive Strategy (open access)

A Grounded Theory Model of the Relationship between Big Data and an Analytics Driven Supply Chain Competitive Strategy

The technology for storing and using big data is evolving rapidly and those that can keep pace are likely to garner additional competitive advantages. One approach to uncovering existing practice in a manner that provides insights for building theory is the use of grounded theory. The current research employs qualitative research following a grounded theory approach to explore gap in understanding the relationship between big data (BD) and the supply chain (SC). In this study eight constructs emerged: Organizational and environmental factors, big data and supply chain analytics, alignment, data governance, big data capabilities, cost of quality, risk analysis and supply chain performance. The contribution of this research resulted in a new theoretical framework that provides researchers and practitioners with an ability to visualize the relationship between collection and use of BD and the SC. This framework provides a model for future researchers to test the relationships posited and continue to extend understanding about how BD can benefit SC practice. While it is anticipated that the proposed theoretical framework will evolve as a result of future examination and enhanced understating of the relationships shown the framework presented represents a critical first step for moving the literature and practice forward.
Date: December 2018
Creator: Baitalmal, Mohammad Hamza
System: The UNT Digital Library