{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/42869"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/42869","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Proactive industrial targeting: an application of the Analytical Hierarchy Process","abstract":"The purpose of this study is to devise a methodology to target industries that would incorporate community preferences in the targeting process. A case-study approach was taken and included three Virginia counties. The most distinctive feature of this research is the use of the Analytical Hierarchy Process (AHP), a method that allows participants to weigh the importance of subjective and objective criteria. Seven firm impacts are used to score the attractiveness of a firm, including economic, public, and environmental impacts. The vector of priority weights obtained from the AHP are applied to the initial score calculated for the impacts of each industry, creating a ranking of preferred industries that are recommended for targeting. From this research it is concluded that community preferences should be an integral part of industrial targeting and economic development in general. State-level policies should be as flexible as possible in order for local level governments to be able to use those policies to attract firms that help that community meet its goals. Rather than focusing energy creating a large number of jobs, community preferences indicate that more effort needs to be spent to attract non-polluting firms that offer higher paying jobs.","abstract_html":"The purpose of this study is to devise a methodology to target industries that would incorporate community preferences in the targeting process. A case-study approach was taken and included three Virginia counties. The most distinctive feature of this research is the use of the Analytical Hierarchy Process (AHP), a method that allows participants to weigh the importance of subjective and objective criteria. Seven firm impacts are used to score the attractiveness of a firm, including economic, public, and environmental impacts. The vector of priority weights obtained from the AHP are applied to the initial score calculated for the impacts of each industry, creating a ranking of preferred industries that are recommended for targeting. From this research it is concluded that community preferences should be an integral part of industrial targeting and economic development in general. State-level policies should be as flexible as possible in order for local level governments to be able to use those policies to attract firms that help that community meet its goals. 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