Development of a Geographical Framework for Census Workplace Data

Martin, David; Cockings, Samantha; Harfoot, Andrew

doi:10.1111/j.1467-985x.2012.01054.x

Cited by 25 publications

(33 citation statements)

References 16 publications

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“…The presence of workplace populations within city centres, out of town office developments or an industrial centre, for example, may represent important drivers of demand for local services, including the retail sector. Retail demand originating from these populations may not be adequately captured by traditional census-based population statistics which are primarily based on residential geographies (Martin, Cockings, and Harfoot 2013). We assess whether recently published output geographies and population statistics related to workplace populations can support the evaluation of retail demand and retail store performance in localities which experience an inflow of workplace populations.…”

Section: Workplaces As a Driver Of Retail Demandmentioning

confidence: 99%

“…Workplaces are a key driver of non-residential daytime population distributions and associated origindestination flows driven by the journey to work (Martin, Cockings, and Leung 2015;Martin, Cockings, and Harfoot 2013;Smith and Fairburn 2008). The presence of workplace populations within city centres, out of town office developments or an industrial centre, for example, may represent important drivers of demand for local services, including the retail sector.…”

Section: Workplaces As a Driver Of Retail Demandmentioning

confidence: 99%

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Using workplace population statistics to understand retail store performance

Berry

Newing

Davies

et al. 2016

The International Review of Retail, Distribution and Consumer R

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We explore the value of recently released workplace geographies and accompanying census-based workplace zone statistics (WZS) and an associated classification of workplace zones (COWZ). We consider how these data could support retailers in their operational and strategic decision making, including the evaluation of retail demand and retail store performance in localities where trade is driven by non-I UK The Co-operative Group characteristics using a series of case study stores within Inner London. We use empirical store trading data to identify store and product category level temporal sales fluctuations attributable to workplace populations. We also use census-derived flow data to identify the spatial origins of workplace population inflow. We identify that store performance exhibits characteristics attributable to demand driven by these populations. We conclude that workplace population geographies, WZS and the COWZ afford considerable potential for understanding drivers of store performance, observed store trading patterns and evaluation of retail store performance. We suggest that the next step is to build these populations and their micro geography spatial and temporal characteristics into predictive models and evaluate their potential for store performance evaluation and location-based store and network decision making within this sector.

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Section: Workplaces As a Driver Of Retail Demandmentioning

confidence: 99%

Section: Workplaces As a Driver Of Retail Demandmentioning

confidence: 99%

Using workplace population statistics to understand retail store performance

Berry

Newing

Davies

et al. 2016

The International Review of Retail, Distribution and Consumer R

View full text Add to dashboard Cite

show abstract

“…Conversely, COWZ-EW takes advantage of a new type of small geographical units for workplace statistics from the latest census of England and Wales in 2011. These units, known as workplace zones (WZs) (Martin et al, 2013), allowed for a classification based on the characteristics of the workplace population at places of work to be constructed for the first time in England and Wales (Cockings et al, 2015). The 2011 OAC and COWZ-EW share some input variables, such as employment types.…”

Section: Methodsmentioning

confidence: 99%

“…Without an accompanying workplace classification, the scope for geodemographic analysis of travel to work flow data are limited. The creation of the Classification of Workplace Zones for England and Wales, or COWZ-EW (Cockings et al, 2015), using a new workplace geography of England and Wales (Martin et al, 2013) is therefore an important development. Combining the 2011 OAC and COWZ-EW to profile places of work and residence allows for a unique insight into the population flows into London.…”

Section: Introductionmentioning

confidence: 99%

Geodemographic travel to work flows into London, UK

Gale¹,

Martin²

2016

GIScience

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We present a method for using geodemographic classifications to profile travel-to-work flows into and within London, UK. Geodemographics have been used in the past to profile these flows, but have focused on the residential locations of flow origins due to limitations in data availability and appropriate spatial units. The 2011 census in England and Wales introduced new spatial units designed specifically for workplace data, leading to creation of a classification of workplaces and workers. Combining this workplace classification with a residential based equivalent means the flows between each can be calculated. This innovative approach results in a two-way classification which can be interrogated to better understand and simplify the complexities of commuting into and within London, thus exploring travel to work within a global city at fine spatial resolution.

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“…The most coarse level remains the same -district level -but at finer scales different reporting geographies were used. The level below 'district' is referred to in the output (Martin et al 2013), with the aim of a better spatial representation of employment related statistics than can be done with extant geographies, which reflect the residential distribution of population. The 1991 SWS were based on a 10% sample of data, and were not used for this analysis, as a cell count of one does not necessarily represent a population unique.…”

Section: Assessment Of Aggregate Workplace Flow Datamentioning

confidence: 99%

Location Tracing and Potential Risks in Interaction Data Sets

Duke‐Williams¹

2017

Appl. Spatial Analysis

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Location-aware mobile phone handsets have become increasingly common in recent years, giving rise to a wide variety of location based services that rely on a person's mobile phone reporting its current location to a remote service provider. Previous research has demonstrated that services that geo-code status updates may permit the estimation of both the rough location of users' home locations and those of their workplaces. The paper investigates the disclosure risks of a priori knowledge of a person's home and workplace locations, or of their current and previous home locations. Detailed interaction data sets published from censuses or other sources are characterised by the sparsity of the contained data, such that unique combinations of two locations may often be observed. In the most detailed 2011 migration data 37% of migrants had a unique combination of origin and destination, whilst in the most detailed journey to work data, 58% of workers had a unique combination of home and workplace. The amount of additional attribute data that might be disclosed is limited. When more coarse geographies are used their still remain a non-trivial number of persons with unique location combinations, with considerably more attributes potentially disclosable.

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Development of a Geographical Framework for Census Workplace Data

Cited by 25 publications

References 16 publications

Using workplace population statistics to understand retail store performance

Using workplace population statistics to understand retail store performance

Geodemographic travel to work flows into London, UK

Location Tracing and Potential Risks in Interaction Data Sets

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