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DC Field | Value | Language |
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dc.contributor.advisor | Anderson, William P. | en_US |
dc.contributor.author | Yarish, Michael B. | en_US |
dc.date.accessioned | 2014-06-18T16:56:20Z | - |
dc.date.available | 2014-06-18T16:56:20Z | - |
dc.date.created | 2012-01-04 | en_US |
dc.date.issued | 1998-04 | en_US |
dc.identifier.other | opendissertations/6673 | en_US |
dc.identifier.other | 7740 | en_US |
dc.identifier.other | 2429793 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/11725 | - |
dc.description.abstract | <p>This thesis attempts to unveil the underlying determinants of the geography of office location by examining the intrametropolitan location decisions of new office establishments in major industrial categories. Its empirical focus is the locations of new office establishments in metropolitan Toronto for the year 1995.</p> <p>The specific objectives of the thesis are (i) to identify own-industry and inter-industry office clusters and, (ii) to identify the most significant factors responsible for major office industries locating in Toronto. Thus, the methodology is in two parts. The first part of the study addresses the first objective by utilizing powerful spatial statistical techniques. Spatial statistics are introduced as a new methodology for office and business location research. Kernel estimation and univariate K function techniques are conducted on twenty distinct office activity point patterns (i.e., event patterns) to identify the existence and geographic locations of intra-industry office clusters. Specifically, the K function is used to detect whether locational patterns are clustered, or alternatively, dispersed. Bivariate K functions are conducted to determine if inter-industry office activities are interacting.</p> <p>The second part of the thesis attempts to further office location research by developing and testing an office location model to identify potential factors that might influence office location in Toronto. The analysis is similar to that of Thlanfeldt and Raper (1990) and Shukla and Waddell (1991). It utilizes a multinomial logit model to estimate the effects of a set of explanatory variables defined as determinants of spatial choice. Real estate zones are used to characterize the set of alternatives available to profit maximizing firms. Unlike previous studies, this research uses dis aggregated firm level data for twenty-two different office activity types. Logit models are estimated individually for each activity type.</p> <p>Results indicate that the event patterns formed by all office industries in metropolitan Toronto are clustered in distinct office nodes and centres located throughout the city. Furthermore, significant interactions exist among certain pairs of office activities indicating the presence of possible agglomeration economies. Logit results confirm the existence of agglomeration economies among similar office activity functions. The results also display marginal evidence of polycentric locational tendencies in most activities. The results confirm the findings of previous studies which indicate that locational patterns of office activities in Canadian cities are unlike those in American cities.</p> | en_US |
dc.subject | Geography | en_US |
dc.subject | Geography | en_US |
dc.title | Intrametropolitan Location of New Office Finns in Metropolitan Toronto | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Geography | en_US |
dc.description.degree | Master of Arts (MA) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 82.05 MB | Adobe PDF | View/Open |
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