Facility Location Decision for Global Entrepreneurial Small-to-Medium Enterprises Using Similarity Coefficient-based Clustering Algorithms

dc.contributor.advisorHamid Seifoddini
dc.contributor.committeememberWilkistar Otieno
dc.contributor.committeememberBrett Peters
dc.contributor.committeememberSeyed Hosseini
dc.contributor.committeememberXiaohang Yue
dc.creatorSerbaya, Suhail H.
dc.date.accessioned2025-01-16T18:03:54Z
dc.date.available2025-01-16T18:03:54Z
dc.date.issued2017-05-01
dc.description.abstractDecisions on location selection are critical for the survival of small-to-medium entrepreneurial organizations from the time they are established until later stages of operation and expansion. The selection of location for small and medium entrepreneurial businesses requires a selection strategy that incorporates relevant factors, quantifies these factors and develops a methodology that analyzes data for better decision-making. In the era of globalization where borders have become easier to transcend, many small ventures tend to choose more attractive international markets as a potential location for their operations where they can obtain higher returns on their investment. Thus, significant changes in the location decision process of the small and medium entrepreneurial companies have received great attention in the literature about small firms with global orientation as a response to the international entrepreneurship phenomenon. Therefore, consideration should be given to factors and attributes that reinforce the appeal of the international market to new businesses. These factors and attributes will provide the decision maker with an effective methodology for data analysis that will provide a framework for decision-making in the selection of locations for the entrepreneurial organization. In this research, the most frequent and critical attributes to select the best location for the entrepreneurial firms (globally) are extracted from relevant literature. Then, a similarity-based cluster analysis approach is introduced to quantify these attributes based on the existing data of economic metrics, such as technological advancement, expenditures on education, expenditures on research and development, the quality of the labor force, unemployment rates, domestic competitiveness, etc. Subsequently, the resulting outcomes are used to identify groups of prospective sites that fit the needs of the entrepreneurial firm. Last, the validity of the adopted methodology will be tested via numerical examples.
dc.identifier.urihttp://digital.library.wisc.edu/1793/85868
dc.relation.replaceshttps://dc.uwm.edu/etd/1538
dc.subjectEntrepreneurship
dc.subjectFacility Location
dc.subjectGlobal Market
dc.subjectLocation Decision
dc.subjectSmall Ventures
dc.subjectSMES
dc.titleFacility Location Decision for Global Entrepreneurial Small-to-Medium Enterprises Using Similarity Coefficient-based Clustering Algorithms
dc.typedissertation
thesis.degree.disciplineEngineering
thesis.degree.grantorUniversity of Wisconsin-Milwaukee
thesis.degree.nameDoctor of Philosophy

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