Relevant bibliographies by topics / Location

Academic literature on the topic 'Location'

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Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Location"

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Bryant, Shannon. "Location, location, location: Anaphor selection in English locative prepositional phrases." Proceedings of the Linguistic Society of America 7, no. 1 (May 5, 2022): 5263. http://dx.doi.org/10.3765/plsa.v7i1.5263.

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This paper presents experimental work on the relative naturalness of subject-oriented reflexives (herself) and pronouns (her) in English locative prepositional phrases (e.g., Michele set a glass next to her/herself). Syntactic approaches to anaphor licensing have tended to focus on the lack of complementarity in such constructions; however, it has long been observed that preferences between forms may depend on verb meaning (change in location vs. perception vs. possession) and spatial relation (+contact vs. -contact), with very strong preferences reported in some cases. This study aims to clarify the extent to which these two factors shape anaphor choice. Results confirm that both play a significant role: reflexives are most natural in the expression of change in location and direct contact, while pronouns pattern oppositely. Importantly, preferences between forms are less stark than those found in constructions where syntactic constraints are assumed to render one form ungrammatical. I suggest that these findings favor a treatment of English anaphora that takes event structure into account.
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Huang, Shengsheng, and John Cantwell. "FDI location choice: the role of locational ambidexterity." Multinational Business Review 25, no. 1 (April 18, 2017): 28–51. http://dx.doi.org/10.1108/mbr-04-2016-0016.

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Purpose This paper proposes locational ambidexterity as a location-specific factor based on an operation flexibility perspective, and explores why and how multinational corporations (MNCs) proactively deal with uncertainty by valuing locational ambidexterity in making location decisions. Design/methodology/approach Location choice data for foreign direct investment (FDI) at a sub-national level in China is used to test the role of locational ambidexterity. Findings We find that FDI generally prefers locations with high ambidexterity. Moreover, investments from a heterogeneous country context are more sensitive to locational ambidexterity than those from a similar country context. However, there is no significant evidence that wholly owned investments favor locational ambidexterity more than do international joint ventures. Research limitations/implications An alternative operationalization of locational ambidexterity may be needed. Future research could explore the sources of locational ambidexterity, identify other firm- and industry-level factors that could alter the value of ambidexterity, investigate how MNCs integrate locational ambidexterity into organization-specific option creation strategies and test the ambidexterity perspective with micro-level location choice data. Practical implications Locational ambidexterity may reduce the overall risk and adjustment cost of future changes. FDI may choose a location with high ambidexterity, i.e. a balanced portfolio of location-specific determinants, under uncertainty about the future. Originality/value Drawing on the notion of location flexibility from Buckley and Casson (1998), this study identifies a new location character, locational ambidexterity, and proposes that MNCs address uncertainty by choosing ambidextrous locations that offer more flexibility for MNCs to change or respond to potential volatility. Selecting locations with high ambidexterity is thus an alternative and complement to the organization-specific flexibility creation strategies suggested by the literature on real option and flexibility.
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Hong, Jennifer, and Mathew Isaac. "Location, Location, Location." Interdisciplinary Journal of Signage and Wayfinding 5, no. 1 (March 31, 2021): 26–40. http://dx.doi.org/10.15763/issn.2470-9670.2021.v5.i1.a77.

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Academic scholars and practitioners uniformly suggest that off-premise signs such as billboards will be more effective if they are installed in high-traffic areas rather than low-traffic areas. In this research, we question the ubiquity of this claim and illustrate potential advantages of installing off-premise signs in low-traffic areas given that these environments also tend to be less cluttered (i.e., having fewer competing signs). Across two studies, we provide converging evidence that consumers evaluate a billboard more favorably when it is displayed by itself than when it is displayed next to other billboards. We show that the same billboard in a low-clutter (vs. high-clutter) location is judged to be more aesthetic, which in turn improves the overall evaluation of the billboard. We further delineate boundary conditions in which the benefits of a low-clutter environment are attenuated.
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Larsonneur, Claire. "Location, location, location." Études britanniques contemporaines, no. 37 (November 19, 2009): 141–52. http://dx.doi.org/10.4000/ebc.3692.

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Kouwenhoven, Bill. "Location, Location, Location." Afterimage 33, no. 5 (March 2006): 6–7. http://dx.doi.org/10.1525/aft.2006.33.5.6.

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Hess, Sharon Folkenroth. "Location, location, location!" Delaware Journal of Public Health 8, no. 3 (August 2022): 116–18. http://dx.doi.org/10.32481/djph.2022.08.019.

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Baker, Jay A. "Location, Location, Location." Journal of Breast Imaging 3, no. 4 (July 6, 2021): 405–6. http://dx.doi.org/10.1093/jbi/wbab047.

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Webb, John R., Katy Milne, and Brad H. Nelson. "Location, location, location." OncoImmunology 3, no. 2 (January 10, 2014): e27668. http://dx.doi.org/10.4161/onci.27668.

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Bartlett, Edmund K., and Udai S. Kammula. "Location, location, location." OncoImmunology 3, no. 5 (May 2014): e28963. http://dx.doi.org/10.4161/onci.28963.

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Fentress-Williams, Judy. "Location, location, location." Bible and Critical Theory 3, no. 2 (June 2007): 20.1–20.8. http://dx.doi.org/10.2104/bc070020.

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Dissertations / Theses on the topic "Location"

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Posada, Mariño Pablo. "Location, location, location choice models." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99091.

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Thesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 109-112).
Cities are, now more than ever before, the main centers of population and production. The growing demand for limited urban space is increasing urban complexity and magnifying both positive and negative externalities of urban agglomeration: increasing productivity, innovation, and social interaction, but also exacerbating living costs, pollution, inequality, congestion, etc. In order to build sustainable cities and have a net positive balance of urban externalities, we need to better understand the motivations of the different agents competing in the race for urban space. Location choice models can help to shine a light on these motivations by providing insights on agents' location preferences. They are also the building blocks of more comprehensive urban models and simulations that can help navigate urban complexity. This thesis explores location choice models for homeowner households and firms in Greater Boston. Specific research questions that these models can help answer include: How do residential location preferences vary with life cycles? What industries value clustering the most? These topics are important given (1) forecasted demographic changes, specifically the aging of the baby-boomers, and (2) the continuing move from a manufacturing-based economy to a service and knowledge-based economy. These changes in population and economy will likely require a change in housing stock in order to better match supply with demand, and changes in the stock of commercial space in order to continue boosting the firms that drive the economy of the region. The thesis also explores the data-related uncertainty of these models (how model estimation changes with different data sources) as well as their temporal transferability (how do preferences change over time). The location choice analysis for households suggests that income has a bigger impact on willingness to pay for location attributes than age of the head of the household or household size. The firm analysis indicates that firms in the professional service and health and education service sector place more value on proximity to jobs in the same industry and density than firms in other sectors. These preferences have strengthened over time. An in-depth analysis, such as the one presented in this thesis, of what city agents look for in a location can, and should, inform planning policies and intervention in order to better match location preferences with opportunities.
by Pablo Posada Mariño.
M.C.P.
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Lee, Sunshin. "Geo-Locating Tweets with Latent Location Information." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/75022.

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As part of our work on the NSF funded Integrated Digital Event Archiving and Library (IDEAL) project and the Global Event and Trend Archive Research (GETAR) project, we collected over 1.4 billion tweets using over 1,000 keywords, key phrases, mentions, or hashtags, starting from 2009. Since many tweets talk about events (with useful location information), such as natural disasters, emergencies, and accidents, it is important to geo-locate those tweets whenever possible. Due to possible location ambiguity, finding a tweet's location often is challenging. Many distinct places have the same geoname, e.g., "Greenville" matches 50 different locations in the U.S.A. Frequently, in tweets, explicit location information, like geonames mentioned, is insufficient, because tweets are often brief and incomplete. They have a small fraction of the full location information of an event due to the 140 character limitation. Location indicative words (LIWs) may include latent location information, for example, "Water main break near White House" does not have any geonames but it is related to a location "1600 Pennsylvania Ave NW, Washington, DC 20500 USA" indicated by the key phrase 'White House'. To disambiguate tweet locations, we first extracted geospatial named entities (geonames) and predicted implicit state (e.g., Virginia or California) information from entities using machine learning algorithms including Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF). Implicit state information helps reduce ambiguity. We also studied how location information of events is expressed in tweets and how latent location indicative information can help to geo-locate tweets. We then used a machine learning (ML) approach to predict the implicit state using geonames and LIWs. We conducted experiments with tweets (e.g., about potholes), and found significant improvement in disambiguating tweet locations using a ML algorithm along with the Stanford NER. Adding state information predicted by our classifiers increased the possibility to find the state-level geo-location unambiguously by up to 80%. We also studied over 6 million tweets (3 mid-size and 2 big-size collections about water main breaks, sinkholes, potholes, car crashes, and car accidents), covering 17 months. We found that up to 91.1% of tweets have at least one type of location information (geo-coordinates or geonames), or LIWs. We also demonstrated that in most cases adding LIWs helps geo-locate tweets with less ambiguity using a geo-coding API. Finally, we conducted additional experiments with the five different tweet collections, and found significant improvement in disambiguating tweet locations using a ML approach with geonames and all LIWs that are present in tweet texts as features.
Ph. D.
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Messer, A'ndrea Elyse Milner George R. "Small ancestral pueblo sites in the Mesa Verde region location, location, location /." [University Park, Pa.] : Pennsylvania State University, 2009. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-3773/index.html.

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Thangavelu, Balajee. "Single-Facility location problem among two-dimensional existing facility locations." Ohio University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175283985.

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Saleem, Muhammad. "Location Analytics for Location-Based Social Networks." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/271131/5/contratMS.pdf.

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The popularity of location empowered devices such as GPS enabled smart-phones has immensely amplified the use of location-based services in social networks. This happened by allowing users to share Geo-tagged contents such as current locations/check-ins with their social network friends. These location-aware social networks are called Location-based Social Networks (LBSN), and examples include Foursquare and Gowalla. The data of LBSNs are being used for providing different kinds of services such as the recommendation of locations, friends, activities, and media contents, and the prediction of user's locations. To provide such services, different queries are utilized that exploit activity/check-in data of users. Usually, LBSN data is divided into two parts, a social graph that encapsulates the friendships of users and an activity graph that maintains the visit history of users at locations. Such a data separation is scalable enough for processing queries that directly utilize friendship information and visit history of users. These queries are called user and activity analytic queries. The visits of users at locations create relationships between those locations. Such relationships can be built on different features such as common visitors, geographical distance, and mutual location categories between them. The process of analysing such relationships for optimizing location-based services is termed Location Analytics. In location analytics, we expose the subjective nature of locations that can further be used for applications in the domain of prediction of visitors, traffic management, route planning, and targeted marketing.In this thesis, we provide a general LBSN data model which can support storage and processing of queries required for different applications, called location analytics queries. The LBSN data model we introduce, segregates the LBSN data into three graphs: the social graph, the activity graph, and the location graph. The location graph maintains the interactions of locations among each other. We define primitive queries for each of these graphs. In order to process an advanced query, we express it as a combination of these primitive queries and process them on corresponding graphs in parallel. We further provide a distributed data processing framework called GeoSocial-GraphX (GSG). GSG implements the aforementioned LBSN data model for efficient and scalable processing of the queries. We further exploit the location graph for providing novel location analytics queries in the domain of influence maximization and visitor prediction. We introduce a notion of location influence. Such influence can capture the interactions of locations based on their visitors and can be used for propagation of information between them. The applications of such a query lie in the domain of outdoor marketing, and simulation of virus and news propagation. We also provide a unified system IMaxer that can evaluate and compare different information propagation mechanisms. We further exploit the subjective nature of locations by analysing the mobility behaviour of their visitors. We use such information to predict the individual visitors as well as the groups of visitors (cohorts) in future for those locations. The prediction of visitors can be used for better event planning, traffic management, targeted marketing, and ride-sharing services.In order to evaluate the proposed frameworks and approaches, we utilize data from four real-life LBSNs: Foursquare, Brightkite, Gowalla, and Wee Places. The detailed LBSN data mining and statistically significant experimental evaluation results show the effectiveness, efficiency, and scalability of our proposed methods. Our proposed approaches can be employed in real systems for providing life-care services.
Doctorat en Sciences de l'ingénieur et technologie
The portal is not showing my complete name. The name (my complete name), I want to have on the diploma is "Muhammad Aamir Saleem". Please correct this issue.
info:eu-repo/semantics/nonPublished
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McGinley, Susan. "Location, Location, Location: The Effect of Riparian Areas on Property Values in Tucson." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2007. http://hdl.handle.net/10150/622138.

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Simkin, L. P. "The assessment of retail store locations : UK retailers' location practices and the development of a predictive retail store location performance model." Thesis, University of Bradford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372163.

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Öner, Özge. "Retail Location." Doctoral thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Economics, Finance and Statistics, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-23753.

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The thesis in hand presents four individual chapters, all of which explore the spatial aspects of the retail sector. The theoretical framework used in all four papers is vastly rooted in the urban and regional economics literature. Using novel data from Sweden for the application of various econometric methods, the thesis investigates (i) the distance sensitivity of demand and market reach for various types of retail activities, (ii) the spatial composition of retail markets and co-location patterns between the various branches of the sector, (iii) the spatial determinants of independent retailers’ productivity, and (iv) the relationship between the retail sector and place attractiveness. The first paper (co-authored with Johan Klaesson) establishes a methodological framework for estimating distance decay and market accessibility for various types of retail activities given a lack of consumer data. The paper addresses the heterogeneous nature of the sector and provides a solid categorization for various types of retail activities. The second paper (coauthored with Johan P. Larsson) employs a unique empirical approach to characterize the location and co-location of retailers in the metropolitan markets. The analysis captures the co-location tendencies between various types of retailers at a highly disaggregated  geographical level, where the importance of access to demand in the pertinent urban landscape is also accentuated. In the third paper, I investigate the spatial determinants of retail productivity. The focus of the paper is on the influence of market size and regional hierarchy on the productivity of independent retailers. The results show a higher productivity premium from the immediate market potential for stores located in central markets compared to stores located in non-central markets. On the other hand, regional market potential is found to play an equally important role for the productivity of stores located both in central and non-central markets. In the fourth paper, I address the role of retail as an urban amenity. In the empirical analysis, to capture the relevance of consumption possibilities for place attractiveness, “access to stores” measures are constructed for both the municipal and regional levels. Although consumption possibilities in the region are found to be positively associated with the place attractiveness of both rural and city municipalities, store access in municipal market boundaries is found to be relevant only for the place attractiveness of city municipalities.
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Poetranto, Groß Dwi Retnani. "Network flow and location (FlowLoc) : the source location problem /." München : Verl. Dr. Hut, 2009. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017179775&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Poetranto, Gross Dwi Retnani. "Network flow and location (FlowLoc) the source location problem." München Verl. Dr. Hut, 2008. http://d-nb.info/992662664/04.

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Books on the topic "Location"

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Meirleir, Marcel De. Location, location, location: A plant location and site selection guide. New York: Haworth Press, 2008.

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Jones, Ken. Location, location, location: Analyzing the retail environment. 2nd ed. Scarborough, Ontario: Nelson Canada, 1993.

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Jones, Kenneth George. Location, location, location: Analyzing the retail environment. Scarborough, Ont: Nelson Canada, 1990.

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Jones, Kenneth George. Location, location, location: Analysing the retail environment. Toronto: Methuen, 1987.

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Jones, Kenneth George. Location, location, location: Analyzing the retail environment. 2nd ed. Scarborough, Ont: Nelson Canada, 1993.

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1936-, Simmons James W., ed. Location, location, location: Analyzing the retail environment. Toronto: Methuen, 1987.

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Gabszewicz, J. Jaskold. "Location". Fontainbleau: INSEAD, 1986.

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Jean, Littlejohn, ed. Location, location: Sources of design. Berkshire [England?]: Double Trouble Enterprises, 2008.

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Jurock, Ozzie. Forget about location, location, location!: The definitive real estate investment guide. Toronto: Stoddart, 2000.

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Clark, Michael, Denis Smith, and Andrew Blowers. Waste Location. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003239819.

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Book chapters on the topic "Location"

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Luque, Jaime P., Nuriddin Ikromov, and William B. Noseworthy. "Location, Location, Location." In Affordable Housing Development, 89–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04064-2_7.

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Lund, Brian. "Location, Location, Location." In Housing in the United Kingdom, 123–59. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04128-1_4.

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Heaume, Owen. "Location, Location, Location." In Understanding Microsoft Intune, 79–92. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8850-4_5.

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Rothman, Stephen. "Location, location, location!" In Proteins Crossing Membranes, 71–78. Boca Raton : Taylor & Francis, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429020810-11.

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Gruenbaum, Ronan. "Location, Location, Location." In Making Social Technologies Work, 78–81. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137024824_12.

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Firmin, Carlene. "Location, Location, Location." In Abuse Between Young People, 137–47. Abingdon, Oxon ; New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315679389-8.

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Ellison, Rachel. "Location location location." In Global Leadership & Coaching, 83–96. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9781315122717-8.

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Svennerberg, Gabriel. "Location, Location, Location." In Beginning Google Maps API 3, 211–42. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2803-5_10.

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Redfern, Gregory I. "Location, Location, Location." In The Patrick Moore Practical Astronomy Series, 59–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00958-8_4.

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Ertel, Pamela A. Kramer, and Madeline Kovarik. "Location, Location, Location." In The ABC's of Classroom Management, 72. 2nd ed. New York: Routledge, 2013. http://dx.doi.org/10.4324/9780203765333-118.

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Conference papers on the topic "Location"

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DeHon, André M. "Location, location, location." In the ACM/SIGDA international symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2435264.2435291.

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Tiwana, Birjodh, Mahesh Balakrishnan, Marcos K. Aguilera, Hitesh Ballani, and Z. Morley Mao. "Location, location, location!" In the Ninth ACM SIGCOMM Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1868447.1868462.

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Granka, Laura, Helene Hembrooke, and Geri Gay. "Location location location." In the 2006 symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1117309.1117328.

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Kliman-Silver, Chloe, Aniko Hannak, David Lazer, Christo Wilson, and Alan Mislove. "Location, Location, Location." In IMC '15: Internet Measurement Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2815675.2815714.

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Thom-Santelli, Jennifer, Alex Ainslie, and Geri Gay. "Location, location, location." In CHI '07 extended abstracts. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1240866.1241064.

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Tayeen, Abu Saleh Md, Abderrahmen Mtibaa, and Satyajayant Misra. "Location, location, location!" In ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3341161.3345334.

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Yilmaz, Emre, Sanem Elbasi, and Hakan Ferhatosmanoglu. "Predicting Optimal Facility Location without Customer Locations." In KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3097983.3098198.

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Calses, Philamer C., Victoria Pham, Erik Verschueren, Noelyn Kljavin, Matt Chang, Kerstin Seidel, Benjamin Haley, et al. "Abstract A18: Location, location, location: Avenues to regulating Hippo." In Abstracts: AACR Special Conference on the Hippo Pathway: Signaling, Cancer, and Beyond; May 8-11, 2019; San Diego, CA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1557-3125.hippo19-a18.

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Zheng, Yu, Lizhu Zhang, Xing Xie, and Wei-Ying Ma. "Mining correlation between locations using human location history." In the 17th ACM SIGSPATIAL International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1653771.1653847.

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Landa, Jeremy. "Location, Location, Location: The Relationship Between Novice Teacher Preparation Location and Turnover From Connecticut." In 2020 AERA Annual Meeting. Washington DC: AERA, 2020. http://dx.doi.org/10.3102/1575435.

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Reports on the topic "Location"

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Card, David, Jesse Rothstein, and Moises Yi. Location, Location, Location. Cambridge, MA: National Bureau of Economic Research, August 2023. http://dx.doi.org/10.3386/w31587.

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Atack, Jeremy, and Robert Margo. "Location, Location, Location!" The Market for Vacant Urban Land: New York 1835-1900. Cambridge, MA: National Bureau of Economic Research, August 1996. http://dx.doi.org/10.3386/h0091.

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Tschofenig, H., and H. Schulzrinne. Trustworthy Location. Edited by B. Aboba. RFC Editor, December 2014. http://dx.doi.org/10.17487/rfc7378.

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Lantis, Robert, and Erik Nesson. The Hot Hand in the NBA 3-Point Contest: The Importance of Location, Location, Location. Cambridge, MA: National Bureau of Economic Research, November 2021. http://dx.doi.org/10.3386/w29468.

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Donath*, Matthew, and Erick Shambarger. DE-EE0007069 – Location, Location, Efficiency! (L.L.E!) Final Technical Report. Office of Scientific and Technical Information (OSTI), January 2020. http://dx.doi.org/10.2172/1581596.

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Veizades, J., E. Guttman, C. Perkins, and S. Kaplan. Service Location Protocol. RFC Editor, June 1997. http://dx.doi.org/10.17487/rfc2165.

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Schulzrinne, H., and H. Tschofenig. Location Types Registry. RFC Editor, July 2006. http://dx.doi.org/10.17487/rfc4589.

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8

Thomson, M., B. Rosen, D. Stanley, G. Bajko, and A. Thomson. Relative Location Representation. RFC Editor, October 2013. http://dx.doi.org/10.17487/rfc7035.

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9

Barnes, R., M. Lepinski, A. Cooper, J. Morris, H. Tschofenig, and H. Schulzrinne. An Architecture for Location and Location Privacy in Internet Applications. RFC Editor, July 2011. http://dx.doi.org/10.17487/rfc6280.

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10

Winterbottom, J., H. Tschofenig, H. Schulzrinne, and M. Thomson. A Location Dereference Protocol Using HTTP-Enabled Location Delivery (HELD). RFC Editor, October 2012. http://dx.doi.org/10.17487/rfc6753.

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