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This paper proposes a new metric, named Operational Space Efficiency (OpSE), intended to diagnose and quantify the inefficient use of floor space for stocking materials in industrial workstations. OpSE presents a formulation analogous to the well-known Overall Equipment Effectiveness and can be obtained as the product of three distinct indicators: Standard Compliance Effectiveness, Standards Selection Effectiveness and Design Space-usage Effectiveness.

This indicator scrutinizes how usefully floor space in workstations is used to temporarily stock materials in the form of raw materials, semi-finished products, parts and components. It is suited for analyzing fixed-position layouts as well as product layouts typical of repetitive manufacturing settings, such as assembly lines in the automotive sector. The proposed indicator leverages an appropriate loss structure that features those factors affecting floor space utilization in workstations with regard to supplying and stocking materials.

An Italian manufacturer in the field of electro-technology was used as an industrial case study for the application of the methodology. The application shows how the three indicators work in practice, the effectiveness of OpSE and the methodology as a whole, in diagnosing floor space usage inefficiencies and in properly addressing improvement actions of the internal logistics in industrial settings.

The paper scrutinizes some important Key Performance Indicators (KPIs) dealing with space usage efficiency and identifies some significant drawbacks. Then it suggests a new, inclusive structure of losses and a KPI that not only measures efficiency but also allows to identify viable countermeasures.

The purpose of this study is to estimate an empirical model for new office space development starts, based on the theoretical treatment of urban growth. The study introduces a new parameter, namely, office space-usage pattern, to the office space development equation and tests whether developers respond to non-price measures in deciding to commence new developments.

The study first introduces a co-integration approach based on an error correction model to test for long-run relations and short-run dynamics of new office space development. A multivariate regression model is then introduced to identify significant determinants that influence office development starts. The study uses annual data over a time span of 30 years.

Estimated results provide strong evidence that the newly introduced parameter exerts a positive impact on new office space development. It suggests that if the average floor space per employee changes by one percentage point, new office development starts would change by 1.5 percentage point, indicating even a marginal change in floor-space usage per employee (SPE) would have a significant impact on new office space development. Empirical estimates also suggest a strong response of office development starts to the lagged land supply and office space stock.

The paper raises the concern about the importance of non-price measures of the supply-side of the office market. There is scope to address the research questions using better data sets. It is also possible to model the supply adjustment process more dynamically in an error correction framework.

The findings would suggest that non-price measures, such as space-usage pattern, need to be taken into account when planning and estimating future office space needs. This finding provides valuable insight for our current knowledge on factors affecting new office supply.

This is the first study to introduce office floor space usage as a determinant of office development starts in an urban growth conceptual framework for the Hong Kong office market.

This paper outlines how Design for Lean Six Sigma methods aided a medical device manufacturing company in developing a new strategic space management and approval process for its manufacturing site.

The project demonstrates the application of the Design for Lean Six Sigma and structured Define, Measure, Analyse, Design, and Verify methodology in designing and implementing a process that enables the case study manufacturing site to improve its space utilisation and free up space.

The project was validated in one manufacturing department, and the Design for Lean Six Sigma methodology resulted in creating 15% new space for that area, with opportunities identified to free up 44.7% of the total manufacturing floor space and realise over €2.2 million cost savings as well as start to manufacture new products launched.

The manuscript highlights for the first time how the Design for Lean Six Sigma methodology can be utilised for space utilisation and can be leveraged by other manufacturers. The current study's limitations are that it is a single-site case study application. Future longitudinal case studies on Design for Lean Six Sigma application in more manufacturing space utilisation projects would be useful. This study has implications for identifying best practices for Design for Lean Six Sigma methodology application in the device industry, thus improving the state of the art for introducing new manufacturing lines.

This is the first published work to utilise Design for Lean Six Sigma methodology for space utilisation in a medical device company. This review will provide medical devices and other manufacturing organisations with recommendations on utilising Design for Lean Six Sigma and design for improved space utilisation to reduce costs.

Residential crowding and underlying causes of crowding have been changing across the globe over time. The aim of this paper is to examine the dynamics of housing consumption and residential crowding in Hong Kong.

While the two‐step Engle‐Granger co‐integration approach based on an error correction model (ECM) is used to test for long‐run relation and short‐run dynamics of housing consumption, the study also uses a multivariate regression model to analyze the factors affecting residential crowding. Along with other variables in previous literature, the study introduces a new institutional factor, i.e. land supply, into the model that analyzes these two issues over a time span of 25 years.

The study's results suggest that many households in Hong Kong still have inadequate housing, and residential overcrowding is a serious issue. Coupled with market forces (e.g. income, housing price, household size), the new land supply factor noticeably has exerted significant influence on the two subject issues under investigation.

The paper provides policy implications that to address such deficiencies, the government should change its current land supply policy. A policy shift is recommended away from its “high‐land price” policy towards comprehensive developments in outer urban areas. This institutional change should help improve housing consumption in the territory overall.

This study adds knowledge to previous works in analyzing residential crowding and its underlying causes over the years, rather than in a particular point in time. It is also the first of its kind in Hong Kong.

The primary purpose of this study is to illustrate a practical approach for industrial work process design that, in an integrative manner, captures essential concerns from different parties associated with manufacturing. It aims explicitly to incorporate utility expectation from the perspectives of operational managers, floor workers, and financial planners into the decision making process.

Through a real industrial scenario, the case study illustrates the use of a Bayesian belief network (BBN)‐based expert system and influence diagram in work process design. What‐if analysis is performed. Statistical tests are then used to benchmark and validate the experimental results and actual data.

The results suggest that the proposed BBN framework is effective in modeling and solving the work design problem. The findings can draw meaningful insights into the adoption and capacity of BBN in the fields of ergonomics, worker health management, and performance improvement.

Practically, the industrial problem is to compare the new stand‐up sewing cells against the traditional sit‐down sewing layout while taking into consideration of ergonomic effect (repetitive motion injury (RMI) likelihood), floor space (SF), yield (%), and cost ($). The study illustrates the use of an expert system and influence diagram to evaluate different alternatives for ergonomic work design in production process.

The results of this study can potentially improve health safety management and worker ergonomics.

The paper is among the few systematic studies that have applied BBN and influence diagram to production ergonomics and worker health management. A methodological framework utilizing these probabilistic reasoning techniques are developed. This new framework can capture essential concerns from different parties in manufacturing.

Considers the benefits of allocating the correct space to each of a hotel′s various functions. Stresses the importance of appropriate distance between, and access to, inter‐related services; and avoiding congestion when operating leisure and conference facilities. Discusses car parking and lists common design faults in hotel planning.

In the Poudre School District of Northern Colorado, USA, Fort Collins High School (FCHS) and Fossil Ridge High School (FRHS) have similar square footages, mechanical systems, and architectural capacities. While FRHS (built 2005) is leadership in energy and environmental design (LEED)‐Silver and Energy Star (2009) certified, FCHS (built 1995) is not. Despite the sustainable features of FRHS, the whole‐building electric use intensities (EUIs) were comparable for the schools. The purpose of this paper is to evaluate electricity consumption and use patterns at these schools.

To investigate whole‐building EUI and identify areas of high consumption, the buildings were divided into workspaces for which workspace‐specific EUIs were calculated and compared. Further, workspace EUIs were partitioned into their heating ventilation and air conditioning (HVAC), lighting, plug load, food service and residual components for analysis.

Significantly, more electricity is used for lighting and HVAC at FCHS (44.04 and 33.16 per cent of total, respectively) compared to FRHS (36.90 and 29.17 per cent of total, respectively). However, plug load consumption accounted for 24.99 per cent of electric use at FRHS but only 16.35 per cent at FCHS. Component EUI analysis identified high‐wattage lighting at FCHS and high computer density at FRHS as areas for possible efficiency improvements.

Whole‐building EUI values are most useful for comparing energy performance of buildings dedicated to a single use. Workspace‐to‐workspace EUI comparisons offer improved energy performance indicators for facility managers. Component EUI analysis identifies specific consumptive activities which should be targeted for potential reduction in electricity use and expenditure.

Workspace and component EUIs provide for more insight than whole‐building EUI when comparing electric consumption of multi‐use facilities.

To develop a conceptual model that links specific antecedent improvements in supply chain processes to improved financial performance indicators.

A case study was conducted to document one electronics manufacturing company's evolving integration of JIT‐driven processes in the supply chain. Data were collected by interviewing key members of the senior management team, site visits, and analysis and review of company documents.

Point‐of‐use systems, assemble‐to‐order systems, elimination of physical inventory counts, and the online supplier program are linked to improved processes such as physical plan layout and use, material handling, quality control and manufacturing efficiency, that resulted in improvements in financial performance.

A single site case study limits the generalizability of the findings. Additional research is necessary to replicate the findings in other firms/industries.

By disaggregating JIT‐driven processes and by incorporating some improvements in production processes in the supply chain, the model enables managers to utilize these processes to improve financial outcomes.

A conceptual model that integrates and delineates links between three sets of variables, i.e. JIT‐driven processes in the supply chain, improvements in production processes, and financial performance indicators.

Over the past few years there has been a significant upsurge of interest in building performance and its appraisal. As the expectations and standards of property users increase, appraisers of buildings have had to develop improved evaluation methods. Building surveyors, as key technical appraisal specialists in construction, have a contribution to make in this growing field. A great deal of the extant research on building performance has been at the “micro‐level” where either individual building elements or aspects of a building′s internal environment have been critically evaluated. Such work can highlight component failures and cryptoclimate problems, but it does little to enlarge our understanding of how buildings perform overall. Discusses some of the current issues assessing the total performance of buildings. Refines the model labelled property efficiency appraisal (PEA) for evaluating the total performance of existing buildings. Considers the key factors and influences for a “macro‐level” assessment of the total performance of existing buildings and points the way ahead.

The purpose of this paper is to investigate the functionality and effectiveness of the Carbon Risk Real Estate Monitor (CRREM tool). The aim of the project, supported by the European Union’s Horizon 2020 research and innovation program, was to develop a broadly accepted tool that provides investors and other stakeholders with a sound basis for the assessment of stranding risks.

The tool calculates the annual carbon emissions (baseline emissions) of a given asset or portfolio and assesses the stranding risks, by making use of science-based decarbonisation pathways. To account for ongoing climate change, the tool considers the effects of grid decarbonisation, as well as the development of heating and cooling-degree days.

The paper provides property-specific carbon emission pathways, as well as valuable insight into state-of-the-art carbon risk assessment and management measures and thereby paves the way towards a low-carbon building stock. Further selected risk indicators at the asset (e.g. costs of greenhouse gas emissions) and aggregated levels (e.g. Carbon Value at Risk) are considered.

The approach described in this paper can serve as a model for the realisation of an enhanced tool with respect to other countries, leading to a globally applicable instrument for assessing stranding risks in the commercial real estate sector.

The real estate industry is endangered by the downside risks of climate change, leading to potential monetary losses and write-downs. Accordingly, this approach enables stakeholders to assess the exposure of their assets to stranding risks, based on energy and emission data.

The CRREM tool reduces investor uncertainty and offers a viable basis for investment decision-making with regard to stranding risks and retrofit planning.

The approach pioneers a way to provide investors with a profound stranding risk assessment based on science-based decarbonisation pathways.