1,720,967 research outputs found
Spring 2020 Regional Economic Indicators Forum Brochure
No full textHaynes, Monica; Chiodi Grensing, Gina; Hockert, Matthew; College of St. Scholastica; University of Wisconsin-Superior. (2020). Spring 2020 Regional Economic Indicators Forum Brochure. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/225390
Economic Impacts of the Tourism Industry in Duluth
No full textThe UMD Labovitz School of Business and Economics’ research bureau, the Bureau of Business and Economic Research (BBER), was asked to study and estimate the economic impact of the tourism industry in Duluth. The study area used in the analysis includes all Duluth zip codes.
The research objectives of this study included the following:
• Show current size of Duluth’s tourism industry in terms of employment and value added.
• Show recent trends in employment for the tourism industry.
• Model economic impacts of 0.5%, 2%, and 4% increases in the Duluth tourism industry.Haynes, Monica; Chiodi Grensing, Gina; Brand, Nathan; Hockert, Matthew. (2020). Economic Impacts of the Tourism Industry in Duluth. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218016
Accountability Through Accessibility: Measuring What Matters for Departments of Transportation
Get PDFTo accurately measure the impacts generated by the actions of Departments of Transportation (DOTs), changes to land use and land value that result from changes to the transportation network must be included. We argue in this paper for the use of Accessibility measures in system performance and project prioritization for DOTs, to fully account for DOT decisions. Accessibility, or measurement of how easily people can connect to their desired destinations, is not a new concept, yet progress has been slow in adopting measures which focus on people rather than vehicle movement and delay. To spur further consideration of Accessibility, we document the theoretical and practical basis for Accessibility, describe available data, explore change in metrics over short and long time scales, and recommend approaches for inclusion into DOT decision making. Ultimately the full impact of DOT actions cannot be fully captured by the vehicle movement metrics which comprise the status quo. Accessibility metrics offer a way to evaluate what DOTs are providing, where, and to whom, in terms of connection to destinations and changes in land use.Lind, Eric M.; Owen, Andrew; Liu, Shirley Shiqin; Hockert, Matthew. (2025). Accountability Through Accessibility: Measuring What Matters for Departments of Transportation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/276879
Economic Impact of the Hermantown Amateur Hockey Association on Duluth, Hermantown, and Proctor, Minnesota
No full textThe Bureau of Business and Economic Research (BBER) at the University of Minnesota Duluth’s Labovitz School of Business and Economics was contacted by HAHA to estimate the economic impacts of Hermantown hockey on the study area. For the purpose of this report, Hermantown hockey includes all of HAHA’s youth games and tournaments, the Hermantown High School hockey program (uses the Hermantown arena), and the operations of the Hermantown Arena. HAHA also requested research on the potential economic impacts of adding a second sheet of ice to the arena that would add capacity for additional games and tournaments throughout the season. The BBER first focused on Hermantown hockey’s current impacts on the economy and then estimated the possible impacts of expanding the existing arena.Haynes, Monica; Chiodi Grensing, Gina; Brand, Nathan; Hockert, Matthew; Badger, Megan. (2020). Economic Impact of the Hermantown Amateur Hockey Association on Duluth, Hermantown, and Proctor, Minnesota. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218018
Valuation of Energy Efficient Investments by Duluth Landlords and Tenants
No full textThe purpose of this study is to build upon the findings from the BBER’s 2016 study, expand the knowledge base related to the split incentive and its impact on student renters, and address the proposed adjustments to the previous research. Specifically, this investigation addressed the following research questions:
1. Are renters willing to pay more in rent for energy efficient upgrades to be installed in their rental property?
2. What monetary value do renters place on a monthly savings in utility payments?
3. Is there a significant difference between student and non-student renters in these two areas (willingness to pay and value placed on utility savings)?
4. What are landlords willing to pay for various energy efficient upgrades?
5. What portion of the cost for various energy efficient upgrades are landlords willing to pay
themselves, and what portion would they expect to pass on to renters?
6. Are there any social or demographic factors that influence renter and/or landlord behaviors in this area?Carlson School of Management, Wells Fargo FoundationHaynes, Monica; Chiodi Grensing, Gina; McIntosh, Christopher; Olafson, Tommy; Brand, Nathan; Hockert, Matthew; Badger, Megan. (2020). Valuation of Energy Efficient Investments by Duluth Landlords and Tenants. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218017
Economic Impact of Ferrous and Nonferrous Mining on Minnesota and the Arrowhead Region with Douglas County, Wisconsin
No full textThe UMD Labovitz School of Business and Economics’ research bureau, the Bureau of Business and Economic Research (BBER), was contacted by the Iron Mining Association of Minnesota and Mining Minnesota to study and estimate the economic impacts of construction and operations for ferrous and nonferrous mining on Minnesota and the Arrowhead Region including Douglas County, Wisconsin.
The objectives of the study include:
• To study the recent economic trends of the ferrous and nonferrous mining industries and describe the size of the mining industry relative to the economic base of the study area.
• To model the economic impacts of the ferrous and nonferrous mining industry, including the current and projected impacts of the industry’s operations and projected capital expenditures.
• To report on Minnesota mining-related taxes paid by the mining industry.
• To report on the business confidence of mining-related firms in the study area.Haynes, Monica; Chiodi Grensing, Gina; Badger, Megan; Brand, Nathan; Hockert, Matthew; Thorsgard, Haakan. (2020). Economic Impact of Ferrous and Nonferrous Mining on Minnesota and the Arrowhead Region with Douglas County, Wisconsin. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/216463
Duluth Bethel Program Evaluation
No full textThe Duluth Bethel (Bethel) is a private non-profit 501c(3) organization that provides community corrections and inpatient and outpatient chemical dependency services to individuals in Duluth and the surrounding region. Roughly half of the individuals served by Bethel in a given year receive treatment for chemical dependency through the Port Rehabilitation program, while the rest participate in one of the facility’s Community Corrections programs (either the Work Release or Female Offender Programs). This project outlines an evaluation strategy for Bethel and assesses the costs and outcomes of the organization’s primary programs. The team utilized data for four years, 2015-2018. The analysis has four primary goals. First was the development of an agency-wide logic model that includes program resources and inputs; actions and outputs; and short-term, medium-term, and long-term outcomes on both clients and the community. Second, data currently being collected by Bethel on its programs and clients as well as any important measures not currently being collected were summarized. Third, common client scenarios (or pathways) for Bethel’s clients were identified, and the costs and outcomes of Bethel’s programs were compared with the most likely alternatives for clients (e.g. jail, prison, treatment). And fourth, a list of recommendations for the organization, based on the study results, existing literature, and feedback from staff and subject-matter experts was developed.Haynes, Monica; Chiodi Grensing, Gina; Dauner, Kim; Brand, Nathan; Olafson, Tommy; Badger, Megan; Hockert, Matthew. (2019). Duluth Bethel Program Evaluation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218029
Access Across America: Auto 2024 Data
Get PDFThis dataset provides a summary of the worker-weighted access by different census geography levels and travel times for the state. The worker-weighted access here represents the average number of jobs a person can reach from a specific census area within a given travel time threshold. The travel time threshold are in integer minutes, at intervals from 5 min to 60 min (1 hour). Census levels included in this dataset are: Block, Block Group, Census Tract, County, and State. The file-naming system for the data files is [state]_[statecode]_[mode]_[census_level]_[year].csv: These files contain the census level data by mode, year.
**Important Note: Due to its large size, the 'Block' level data file should not be opened outside of a person's coding platform. Attempting to open this file in Excel or a similar spreadsheet program would cut off a significant amount of data points.**
Data fields included in the data are: 1. mode: the type of travel modes, one of auto, bike, or transit; 2. year: National Accessibility Evaluation data year, the year for which this dataset is relevant; 3. parent_area: the ID of the containing geography within which the data averages are calculated; 4. summary_level: the level of geography at which averages are calculated - one of state, county, census tract, block group, or block; 5. geoid: the ID of the particular census geography for which the data averages are calculated; 6. threshold: the travel time threshold in seconds, ranging from 300 to 3600 seconds; 7. weighted_average: the average number of jobs a person can reach from a given census area within the travel time threshold for a specific mode.These data were created as part of a study that examined the accessibility to jobs by auto in the 50 largest (by population) metropolitan areas in the United States. The data include access at realistic observed driving speeds by time of day and road segment. The underlying speed data inputs restrict data sharing to participating sponsor states. The data available describe access to jobs by auto in the states/districts of California, Connecticut, District of Columbia, Florida, Illinois, Maryland, Massachusetts, Michigan, Minnesota, North Carolina, Texas, and Virginia; and the metropolitan areas within these states. These data are part of a longitudinal study. Auto data for additional years can be found in the Accessibility Observatory Data collection: http://hdl.handle.net/11299/200592Federal Highway Administration, Transportation Pooled Fund program, TPF-5(455) to MnDOTOwen, Andrew; Liu, Shirley Shiqin; Hockert, Matthew; Lind, Eric M. (2026). Access Across America: Auto 2024 Data. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/r4yf-zt89
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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