Location Attributes Research Articles

Matching heterogeneous e-catalogues in B2B marketplaces using vector space model

Competitive pressures require manufacturers to continually find ways to reduce costs and increase market access. Internet-based technologies such as e-procurement (electronic procurement) provide increased buying and selling opportunities to manufacturers. E-catalogues are electronic representations of information about the products and services of an enterprise and play a key role in e-procurement. Matching an e-catalogue from a buyer with product e-catalogues provided by the suppliers helps companies to find partners in e-marketplaces. Since each business actor may use a different structure and classification for e-catalogues, it is not easy to match a product with the e-catalogue requested by another partner. This article uses vector space model (VSM) and customises it to solve the matching problem of the e-catalogues. The proposed approach uses a combinations of values, names and location of attributes of structured documents to find the syntactic correlation of e-catalogues. It also uses ontologies to expand the matching mechanism with semantic relationships of data attributes. The proposed approach makes it possible to use the benefits of all available ontologies and schemas but not to be dependent on them. The experimental results show that the proposed approach provides a more accurate similarity ratio while matching similar e-catalogues compared with the basic approach of just using VSM.

Non-crossing rail-trespassing crashes in the past decade: A spatial approach to analyzing injury severity

Transportation professionals have long recognized the harm of trespassing along railway rights-of-way. However, the non-crossing rail trespassing issue has received less attention compared with highway–rail grade crossing crashes, despite the fact that nearly 8800 rail-trespassing crashes occurred on non-crossing rail tracks during the past decade with a large number of them resulting in fatality. Also, geographic and socio-demographic diversity within the US implies that trespassing crash severity and its correlates may vary across geographic entities or regions. The purpose of this paper is to investigate these issues using rail-trespasser crash data maintained by Federal Railroad Administration (N=8794 over 2004–2013). The unique aspects of the study are the development of a framework that explores correlates of injury severity in crashes and applies appropriate analysis methods. Specifically, using rigorous spatial modeling methods (Geographically Weighted Regression), the study uncovers spatial variations in correlates between rail-trespassing injury and revealed contributing factors. The factors include personal attributes of individuals, environmental and location attributes, time of crash and pre-crash behaviors. The results show that non-crossing trespass crashes are generally severe with 52.1% involving a fatality. Pre-crash behaviors were found to be key factors showing significant associations with the probability of rail-trespassing injury, especially lying or sleeping (on or near tracks). Fundamentally, the basic assumption of spatial stationarity in traditional regression models does not fully hold in the situation explored. Correlates of injury severity are found to be non-stationary across space. Therefore, regional considerations in specific situations should guide the implementation of treatments and policies.

An Analysis of the Field Precision of the CTLA Trunk Formula Method

The CTLA Trunk Formula Method is an industry-standard tool for appraising large trees. The goal of this study was to measure its precision in the field and to look for possible ways to improve the formula or its implementation. Fourteen certified arborists independently appraised the same ten trees, and the results of their appraisals were analyzed. This study focused on the attributes of Trunk Area, Species, Location, and Condition. In the results, the attributes with the highest variance among appraisers were Trunk Area and the Condition Rating. In the past, much of the variation among appraisers has been attributed to personal bias due to lack of experience, and it has been suggested that variance would decrease with experience. These results give evidence to the contrary—the group of appraisers with the highest variance was the group that performed appraisals most frequently. The most valuable information from this study was the identification of four key elements of error involved in the appraisal process: personal value error, personal observation error, measurement error, and systematic error.

Urban configuration, accessibility, and property prices: a case study of Cardiff, Wales

The specification of locational attributes in hedonic houseprice models has traditionally been problematic. Whilst many studies use similar sets of structural attributes the range of locational attributes can be diverse and inconsistent both in their identification and in their measurement. To address this problem, researchers have adopted concepts related to urban configuration such as the monocentric city and the access – space trade-off model, and later multicentric and multiple accessibility models, to structure their enquiry. This has led to issues related to a priori variable specification using geometrically defined accessibility measures that can also lead to problems such as spatial autocorrelation. In this research, we investigate the use of network accessibility metrics in hedonic house price research using Cardiff, Wales as a case study. We hypothesize that a network-modelling approach to measuring accessibility will improve performance compared with conventional planar geometry specifications. We find that estimating centrality variables across a variety of spatial scales allows the impact on property prices of urban configurations to be modelled more accurately. The research shows that not all dimensions of accessibility can be adequately captured by network measures and that conventional planar geometry measures of accessibility can add additional explanatory power in certain circumstances.

Exploring the Elements of Housing Price in Malaysia

This informative study explores the elements of housing price in Malaysia and found the price is affected by many factors. This study of great practical significance has shown that house prices are determined by the demand for attributes, not only of the dwelling units themselves, but also of the region in which the units are located. There are many structural, neighborhood and locational attributes that could have brought impacts on house prices (Chin, Chau, & Ng, 2004). Structural characteristics, location-specific factors, and neighbourhood characteristics may define various sub-markets. Sub-markets may be defined by structure type (e.g. single-family detached, row house, town home, and condominium), by structural characteristics (property age housing consumers may have strong preferences for newly constructed properties or for historic properties), or by neighbourhood characteristics (e.g., public education and public safety). Results show that the housing price in Malaysia evidently depends on population, demand and supply, location, physical characteristic, accessibility, developer, cost of material and income. It is also influenced by neighbourhood factors as people nowadays will likely choose a better neighbourhood. These factors determine whether the housing price will be high or low. In summary, the government must take an active role to monitor and take appropriate measures to control property prices.

The housing experiences of Fijian migrants in Auckland

Purpose – This paper aims to examine the housing experiences of Fijian migrants in Auckland, New Zealand, in response to recent calls for greater attention to be given to the housing experiences of a wider range of migrant groups. The paper seeks to extend the understanding of the housing experiences of a migrant group that have the economic and social resources that are likely to see them achieve housing outcomes beyond the usual “niche” and limited segments of the housing market usually available to migrants. Design/methodology/approach – This paper used a questionnaire survey designed to uncover the housing experiences and levels of satisfaction of Fijian migrants living in Auckland. Developing on the works of literature that have addressed ethnic residential segregation and migrant housing outcomes, this paper addresses the housing experiences of a well-established migrant community that possesses significant human capital (skills, education, English language proficiency) but occupies a hybrid cultural identity. Findings – The majority of the 84 respondents had attained homeownership. Homeownership was prized for conveying a sense of “independence” and was aligned with notions of Fijian Indian culture. Both homeowners and renters expressed high levels of satisfaction with the locational attributes of their homes. While the majority of renters aspired to homeownership, a lack of affordable housing was noted. Homeowners recognised that they had benefitted from accessing homeownership when house prices were more affordable and believed that current and future migrants would struggle to buy a house in the Auckland housing market. Research limitations/implications – In the absence of a sampling frame, this research employed a purposive sampling technique that distributed questionnaires among Fijian migrant community groups and ethnic businesses. As the first study of its kind into the housing experiences of Fijian migrants in Auckland, the sample size (84 respondents) and geographical distribution of respondents was deemed sufficient to offer insights into the community’s housing experiences. The findings of this research could be used to develop a larger-scale analysis of the housing experiences of Fijian migrants in Auckland. Originality/value – While considerable attention has been given to documenting the locational distribution of migrants in Auckland, this is the first study to examine the housing experiences of Fijian migrants. The paper adds to the understandings of the variety of migrant housing outcomes by focussing on the experiences of a well-established migrant group that possesses significant human capital and occupies a distinct ethnic position within Pacific migration flows.

Sense of place: inquiry and application

‘Sense of place’ is a fundamental, yet presumptive concept within the planning and design disciplines. Professional theories have largely remained focused on the physical aspects of place, as this is their primary mode of production. However, the academic literature suggests that sense of place is a multidimensional concept that extends beyond the physical attributes of a given location. A thorough literature review reveals that sense of place is influenced by four primary dimensions. It is argued that this theoretical perspective can better inform the transformation of space into place by linking each dimension with specific design processes.

Firm value, spatial knowledge flow, and innovation: evidence from patent citations

Purpose– The purpose of this paper is to examine the role of geographic location of research-intensive firms in the ability to generate new research and products, which consequently affects firm value.Design/methodology/approach– The authors conduct the empirical study following a three-step process. First, if pharmaceutical firms are more likely to cite the patents of other firms and other innovators that are nearby, as opposed to firms and other innovators that are far away, then location (i.e. close proximity) is likely important when it comes to the ability to learn and to use the knowledge being generated by other innovators. The authors employ a “geographic information systems” (GIS) and geo-code each pair of citing and cited patents. In addition, the authors utilize spatial statistics such as Moran’sIto analyze the spatial clustering pattern of patent citations and knowledge flows. Next, the authors measure the pharmaceutical companies’ ability to generate useful patents as a function of the amount of innovation and industrial activity that is occurring close to them. Finally, the authors test whether a firm’s location relates to its firm value. Specifically, the authors model firm value as a function of its patents quality, but the authors also allow the firm’s patents quality to be a function of its location and locational attributes. In this way, the authors establish a link between location and firm value. Using a simultaneous system of equations, the authors find that location explains patent quality, which, in turn, explains firm value. In other words, there is a positive relationship between firm value, innovation and location.Findings– In empirical tests using pharmaceutical firms and their patents, the authors first find that firms more often cite patents of other firms that are geographically closer to them than those firms that are farther away. The authors then find that a patent’s quality is a function of the firm’s near proximity to other knowledge-intensive institutions and activities. Finally, the authors find that because patent quality is a function of a firm’s geographic location, location consequently affects firm value.Research limitations/implications– For knowledge-intensive firms, geographic location matters. More specifically, the authors contend that research-intensive firms are better able to use and to expand on existing knowledge when they are closer to other research-intensive enterprises. The implication is that firm value maximization involves a location factor.Practical implications– The practical implication for investors is that investors should invest in those firms that are situated in a location that is rich in geographic innovation resources because those firms are more likely to generate more and higher quality patents or innovations.Originality/value– The study is the first to establish the linkage among spatial knowledge diffusion, geographic drivers of innovation, and market valuation of the firm. The study is unique in that the authors not only present evidence on spatial knowledge flows by geo-coding the exact longitude and latitude location coordinates of citing and cited patens, but more importantly, the authors also identify geographic drivers of innovation, and examine their impacts on citation-weighted patent counts and knowledge stock. Finally, using a series of simultaneous equations, the authors show how geographic innovation resources positively affect citation-weighted patent stock and knowledge stock and consequently affect market value of the firm. Thus, the novel approach contributes not only to the literature that measures geographic localization of knowledge flow using patent citations, but also to the literature that examines the impact of geographic sources of innovations on patent outputs and patent quality and, thus on firm value for research-intensive firms.

Analysing the local geography of the relationship between residential property prices and its determinants

Abstract This paper analyses the local geography of the relationship between residential property prices and its determinants. A semiparametric geographically weighted regression (S-GWR) technique is employed to explore this relationship. Selling prices, structural and locational attributes data were collected from the database of the Department of Valuation and Services of Malaysia, selected maps and reports. The outcome of this paper shows a strong geographically varying relationship between residential property prices and its determinants in which the residential property price determinants have a positive impact on prices in some areas but negative or no impact on the others. The magnitude of the effect is also found to be geographically varied; the capitalisation in residential property prices is found greater in some areas but less or with no effect in some other parts of the areas. The use of S-GWR technique makes it possible to reveal such geographically varying relationships, thus leading to a better understanding of the relationship between residential property prices and its determinants.

The influences of past and present residential locations on vehicle ownership decisions

This study explores the relationship between historical exposure to the built environment and current vehicle ownership patterns. The influence of past exposure to the built environment on current vehicle ownership decisions may be causal, but there are alternative explanations. Households may primarily select to live in neighborhoods that facilitate their vehicle ownership preferences, or they may retain preferences that they have developed in the past, irrespective of their current situations. This study seeks to control for these alternative explanations by including the built environment attributes of households’ past residences as an influence on vehicle ownership choices. We use a dataset from a credit reporting firm that contains up to nine previous residential ZIP codes for households currently living in the 13-county Atlanta, Georgia, metropolitan area. Results show that past location is significant, but of marginal influence relative to the attributes of the current location. From a practical perspective, our results suggest that models that include current but not past neighborhood attributes (also controlling for standard socioeconomic variables) can forecast vehicle ownership decisions reasonably well. However, models that include both current and past neighborhood attributes can provide a more nuanced understanding of the built environment’s potentially causal influences on vehicle ownership decisions. This better understanding may provide more realistic forecasts of responses to densification or other travel demand management strategies.

Where are the electric vehicles? A spatial model for vehicle-choice count data

Electric vehicles (EVs) are predicted to increase in market share as auto manufacturers introduce more fuel efficient vehicles to meet stricter fuel economy mandates and fossil fuel costs remain unpredictable. Reflecting spatial autocorrelation while controlling for a variety of demographic and locational (e.g., built environment) attributes, the zone-level spatial count model in this paper offers valuable information for power providers and charging station location decisions. By anticipating over 745,000 personal-vehicle registrations across a sample of 1000 census block groups in the Philadelphia region, a trivariate Poisson-lognormal conditional autoregressive (CAR) model anticipates Prius hybrid EV, other EV, and conventional vehicle ownership levels.Initial results signal higher EV ownership rates in more central zones with higher household incomes, along with significant residual spatial autocorrelation, suggesting that spatially-correlated latent variables and/or peer (neighbor) effects on purchase decisions are present. Such data sets will become more comprehensive and informative as EV market shares rise. This work’s multivariate Poisson-lognormal CAR modeling approach offers a rigorous, behaviorally-defensible framework for spatial patterns in choice behavior.

Obsolescence of Green Office Buildings: A Literature Review

Abstract This paper reviews the elements or features that affect the rental or capital values of green commercial buildings. The green related factors affecting the rental and capital values of commercial property from previous studies can be classified into; (1) Physical environment, (2) Economic factors; (3) Functional attributes; (4) Design attributes; (5) Locational attributes; (6) Operating expenses/ Energy consumption; (7) Lease terms; (8) Occupancy level/ Vacancy rates, and; (9) Economics incentives. By critically reviewing past researches and methodologies, this study proposes the idea of embedding the 6-key features of Green buildings; Water and Energy efficiency, Site and locality, Construction Materials, Indoor Air Quality and Landscape and Design as the elements of commercial property obsolescence.

The influence of environmental factors on property buyers’ choice of residential location in Poland

Th e main aim of this study was to identify the factors responsible for Polish property buyers' choice of residential location, including single-family houses and apartments. Th e following thesis was formulated: analysis of consumers' residential preferences based on their personal experience supports a more reliable evaluation of individual attributes of a residential location. Th is paper overviews the existing literature on the subject and ana- lyzes primary data collected by the computer-assisted web-interviewing (CAWI) method. Th e questionnaire developed by the authors was completed by 269 residents of three Polish regions. Th e respondents evaluated the quality of their residential environment and identifi ed environmental factors that could infl uence their health. Th e data were pro- cessed statistically to reveal that price is the most important factor behind the residential location choice. Other factors identifi ed by the respondents included the sense of security and a quiet neighborhood. High scenic value was regarded as a moderately important factor, although its signifi cance was recognized by the majority of the respondents.

Revisiting the destination ranking procedure in development of an Intervening Opportunities Model for public transit trip distribution

An Enhanced Intervening Opportunities Model (EIOM) is developed for Public Transit (PT). This is a distribution supply dependent model, with single constraints on trip production for work trips during morning peak hours (6:00 a.m.–9:00 a.m.) within the Island of Montreal, Canada. Different data sets, including the 2008 Origin–Destination (OD) survey of the Greater Montreal Area, the 2006 Census of Canada, GTFS network data, along with the geographical data of the study area, are used. EIOM is a nonlinear model composed of socio-demographics, PT supply data and work location attributes. An enhanced destination ranking procedure is used to calculate the number of spatially cumulative opportunities, the basic variable of EIOM. For comparison, a Basic Intervening Opportunities Model (BIOM) is developed by using the basic destination ranking procedure. The main difference between EIOM and BIOM is in the destination ranking procedure: EIOM considers the maximization of a utility function composed of PT Level Of Service and number of opportunities at the destination, along with the OD trip duration, whereas BIOM is based on a destination ranking derived only from OD trip durations. Analysis confirmed that EIOM is more accurate than BIOM. This study presents a new tool for PT analysts, planners and policy makers to study the potential changes in PT trip patterns due to changes in socio-demographic characteristics, PT supply, and other factors. Also it opens new opportunities for the development of more accurate PT demand models with new emergent data such as smart card validations.

Reference-frame specificity of perceptual learning: The effect of practice

One of the hallmarks of perceptual learning is specificity, the lack of transfer of the improved discriminative ability when the trained stimulus changes retinal location, orientation or other basic visual attributes. Specificity has been found also for the trained task and the corresponding attended stimulus feature. Here, we provide evidence for a new form of specificity, called reference-frame specificity, which does not follow from changes in the sensory input or the attended stimulus feature. In our paradigm, specificity was the consequence of the mental frame of reference (vertical or horizontal) used to perform the orientation discrimination task. In addition, we found that reference-frame specificity was exacerbated by prolonged practice. Overall the present findings are in agreement with the "selective reweighting" hypothesis of perceptual learning.

Simultaneous modeling of individuals’ duration and expenditure decisions in out-of-home leisure activities

In this paper, we propose an activity model under time and budget constraints to simultaneously predict the allocation of time and money to out-of-home leisure activities. The proposed framework considers the activity episode level, given that the activity is scheduled. Thus, the model considers the decision of the quantities for duration and expenditure spent during the activity. We use a flexible utility function and show how the simultaneous equations can be estimated by using structural equations model (SEM) estimation techniques to handle the endogeneity problem of time and expenditure. The estimation results are based on a large national leisure diary data set collected in 2008 in the Netherlands, which provides detailed information about time and money spent as well as timing and location attributes of the activities. The analysis reveals that socio-demographics, travel party, timing and location variables influence the duration and expenditure of activity episodes. It shows that various socio-demographic groups display different preferences in terms of the time and money spent on activities. The results also indicate substitution relationships between spending more time and money for various activity categories. Thus it is concluded that the analysis provides useful results for a better understanding of combined time and money allocation decisions for leisure activities.

Spatial Clustering Overview and Comparison: Accuracy, Sensitivity, and Computational Expense

Cluster analysis continues to be an important exploratory technique in scientific inquiry. It is used widely in geography, public health, criminology, ecology, and many other fields. Spatial cluster detection is driven by geographic information corresponding to the location of activities, requiring appropriate and meaningful treatment of space and spatial relationships combined with observed attributes of location and events. To date, this has meant utilizing dedicated measures and techniques to structure and account for distance, neighbors, contiguity, irregular geographic morphology, and so on. Unfortunately, all spatial clustering approaches, regardless of their theoretical underpinning, statistical foundation, or mathematical specification, have limitations in accuracy, sensitivity, and the computational effort required for identifying clusters. As a result, a major challenge in practice is determining which technique(s) will provide the most meaningful insights for a particular substantive issue or planning context. The purpose of this article is to provide an overview and evaluation of spatial clustering techniques, identifying the strengths and weaknesses of the most widely applied approaches. Results suggest that performance varies significantly in terms of accuracy, sensitivity, and computational expense. This is noteworthy because the misidentification of clusters, whether false positives or false negatives, has the potential to bias not only hypothesis formulation but also pragmatic facets of policy, process, and planning efforts within a region.

Regional Aspects of Collaborative Invention Across National Innovation Systems

This article analyzes the association between intraregional collaboration and levels of invention in nine developed countries. Patent data of the Organization for Economic Co-operation and Development (OECD) regions of nine inventive countries are used to determine if a significant positive correlation exists between reliance on own region partners and overall invention. Strong intraregional collaboration is also related to the knowledge bases of technologies and to the tendency for inventors to team up in the first place. Results show strong evidence that inventors in highly inventive regions co-patent more with own region partners and that they have a greater tendency to collaborate in the first place. Support for the hypothesis that information and computer technologies favour own region collaboration and that more biotechnology invention encourages external alliances is mixed. However, there is far less evidence that more biotechnology invention encourages more external alliances. Variation in the results between countries is interpreted as evidence that national innovation systems have distinctive internal locational attributes. The findings refute the assertion that strengthening aspatial network proximities has eclipsed the pivotal role of intraregional linkages in technological advance.

Discrimination and Determinants of Wage in India: An Analysis from NSSO 66 Round Data

This paper analyses determinants of wage in India using NSSO socio-economic survey 66th round (July 2009-June 2010) data and Heckman two step regression procedure. On the basis of results, it attempts to find out the extent of gender discrimination and discrimination due to urban-rural divide applying Oaxaca-Blinder decomposition technique. Results show that socio-economic, demographic, location, and job attributes are significant determinants of wage in India. However, when cost of living index was added as a control along with others, urban-rural divide in wage became marginal (8%) and in decomposition most of the differentials in wage is due to the explained component. However, this study found that wage of an average male is 33.43% higher than wage of an average female, almost all due to unexplained factors indicating substantially high degree of wage discrimination in India even after discounting the role of omitted variables.

Pasar Tradisional Versus Pasar Modern di Daerah Perkotaan (Studi Kasus: Kecamatan Gondokusuman Kota Yogyakarta)

Penelitian ini bertujuan untuk mengetahui bagaimana persaingan yang terjadi antara pasar tradisionalversus pasar modern di daerah perkotaan meliputi aspek karakteristik, jangkauan pelayanan,preferensi serta persepsi konsumen terhadap kedua jenis pasar. Metode penelitian yang digunakanadalah metode kuantitatif. Teknik pengambilan sampel yang digunakan adalah non probabilitiy jenispurposive sampling untuk populasi jenis pasar dan teknik accidental sampling untuk populasikonsumen. Hasil penelitian menunjukkan bahwa dari aspek karakteristik kondisi fisik, pasar tradisionalmasih kalah dibanding pasar modern. Dari aspek jangkauan pelayanan, pasar modern memiliki areapelayanan yang lebih luas. Preferensi belanja konsumen ke pasar tradisional masih lebih tinggi daripada ke pasar modern. Analisis tabulasi silang menunjukkan adanya hubungan yang nyata antaravariabel rentang usia dan pendidikan dengan pemilihan jenis retail (tradisional atau modern). Analisispersepsi konsumen menunjukkan keunggulan pasar modern dibanding pasar tradisional pada atributkeragaman, kualitas barang, kenyamanan, promosi serta lokasi.Kata kunci : pasar tradisional, pasar modern, jangkauan pelayanan, preferensi dan persepsi konsumen