The influence of office location on commuting behaviour

To fully appreciate the environmental impact of an office building, the transport-related carbon dioxide (CO2) emissions resulting from its location should be considered in addition to the emissions that result from the operation of the building itself. Travel-related CO2 emissions are a function of three criteria, two of which are influenced by physical location and one of which is a function of business practice. The two spatial criteria are, first, the location of the office relative to the location of the workforce, the market, complementary business activities (and the agglomeration benefits this offers) and, second, the availability and cost of transport modes. The business criterion is the need for, and therefore frequency of, visits and this, in turn, depends on the requirement for a physically present workforce and face-to-face contact with clients. This paper examines the commuting-related CO2 emissions that result from city centre and out-of-town office locations. Using 2001 Census Special Workplace Statistics which record people’s residence, usual workplace and mode of transport between them, distance travelled and mode of travel were calculated for a sample of city centre and out-of-town office locations. The results reveal the extent of the difference between transport-related CO2 emitted by commuters to out-of-town and city centre locations. The implications that these findings have for monitoring the environmental performance of offices are discussed.

The location of executive suites and business centers in the United States: an exploratory analysis

Increasingly, corporate occupiers seek more flexible ways of meeting their accommodation needs. One consequence of this process has been the growth of the executive suite, serviced office or business centre market. This paper, the final report of a research project funded by the Real Estate Research Institute, focuses upon the geographical distribution of business centers offering executive suites within the US. After a brief review of the development of the market, the paper examines the availability of data, provides basic descriptive statistics of the distribution of executive suites by state and by metropolitan statistical area and then attempts to model the distribution using demographic and socio-economic data at MSA level. The distribution reflects employment in key growth sectors and the position of the MSA in the urban hierarchy. An appendix presents a preliminary view of the global distribution of suites.

Location and collocation advantages in international innovation

Purpose – This paper examines the role of location-specific (L) advantages in the spatial distribution of multinational enterprise (MNE) R&D activity. The meaning of L advantages is revisited. In addition to L advantages that are industry-specific, the paper emphasises that there is an important category of L advantages, referred to as collocation advantages. Design/methodology/approach – Using the OLI framework, this paper highlights that the innovation activities of MNEs are about interaction of these variables, and the essential process of internalising L advantages to enhance and create firm-specific advantages. Findings – Collocation advantages derive from spatial proximity to specific unaffiliated firms, which may be suppliers, competitors, or customers. It is also argued that L advantages are not always public goods, because they may not be available to all firms at a similar or marginal cost. These costs are associated with access and internalisation of L advantages, and – especially in the case of R&D – are attendant with the complexities of embeddedness. Originality/value – The centralisation/decentralisation, spatial separation/collocation debates in R&D location have been mistakenly viewed as a paradox facing firms, instead of as a trade-off that firms must make.

Why the home region matters: location and regional multinationals

Much of the literature in international business analysing the multinational enterprise uses the country as the relevant environmental parameter. This paper presents both theoretical and empirical evidence to demonstrate that country-level analysis now needs to be augmented by analysis at the ‘regional’ level of the broad triad markets of Europe, North America and the Asia Pacific. The great majority of the world's 500 largest firms concentrate their activities within their home region of the triad. This study uses variance component analysis and finds that this home region effect outperforms the country effect. Together, the regional and industry effects explain most of the geographic expansion of multinational enterprises (MNEs), whereas country, firm and year effects are very minor. The new data and variance component analysis on the activities of large MNEs reported here suggest that new thinking is required about the importance of large regions of the triad as the relevant unit of analysis for business strategy to supplement the conventional focus on the country.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

Bohemian graduates in the UK: disciplines and location determinants for entering creative careers

The human capital and regional economic development literature has become increasingly interested in the role of the ‘Bohemian occupations’ on economic growth. Using UK higher education student micro-data, we investigate the characteristics and location determinants of creative (bohemian) graduates. We examine three specific sub-groups: creative arts & design graduates; creative media graduates; other creative graduates. We find these disciplines influence the ability of graduates to enter creative occupations and be successful in the labour market. We also highlight the role of geography, with London and the South East emerging as hubs for studying and providing Bohemian graduates with more labour market opportunities.