Measuring construction industry competitiveness: A holistic approach

The link between competitiveness and sustained prosperity of a nation, industry or firm, is a well established argument and serves as the basis for making policy decisions and directing strategic change. The importance of construction industry competitiveness is currently receiving considerable attention from countries such as Finland, Sweden and the UK. This paper critically reviews the existing measures of competitiveness, challenges productivity and profitability as the dominant measures of construction industry competitiveness and introduces a more holistic set of measures that addresses the needs of investors, employees, clients and overall society. The research also reports upon the application of this more holistic set of measures for measuring competitiveness and presents results for the Swedish construction industry. The paper principally sets out to present the preliminary findings of an ongoing research project, which will eventually compare the competitiveness of the Swedish construction industry with that of Finland and the UK.

Green noise or green value? Measuring the price effects of environmental certification in commercial buildings

This paper investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and non-certified buildings. First, certified buildings offer a bundle of benefits to occupiers relating to business productivity, image and occupancy costs. Second, due to these occupier benefits, certified buildings can result in higher rents and lower holding costs for investors. Third, certified buildings may require a lower risk premium. Drawing upon the CoStar database of US commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. We first estimate the rental regression for a sample of 110 LEED and 433 Energy Star as well as several thousand benchmark buildings to compare the sample to. The results suggest that, compared to buildings in the same metropolitan region, certified buildings have a rental premium and that the more highly rated that buildings are in terms of their environmental impact, the greater the rental premium. Furthermore, based on a sample of transaction prices for 292 Energy Star and 30 LEED-certified buildings, we find price premia of 10% and 31% respectively compared to non-certified buildings in the same metropolitan area

Measuring educational performance and disparities in educational outcomes in an international comparative context

Includes bibliography

Measuring educational performance and disparities in educational outcomes in an international comparative context

Includes bibliography

The employment situation in Latin America and the Caribbean: Advances and challenges in measuring decent work

At 6.4%, the unemployment rate for the Latin American and Caribbean region overall was the lowest for the past few decades, down from 6.7% in 2011. This is significant, in view of the difficult employment situation prevailing in other world regions. Labour market indicators improved despite modest growth of just 3.0% in the region’s economy. Even with sharply rising labour market participation, the number of urban unemployed fell by around 400,000, on the back of relatively strong job creation. Nevertheless, around 15 million are still jobless in the region. Other highlights of 2012 labour market performance were that the gender gaps in labour market participation, unemployment and employment narrowed, albeit slightly; formal employment increased; the hourly underemployment rate declined; and average wages rose. This rendering was obviously not homogenous across the region. Labour market indicators worsened again in the Caribbean countries, for example, reflecting the sluggish performance of their economies. The sustainability of recent labour market progress is also a cause for concern. Most of the new jobs in the region were created as part of a self-perpetuating cycle in which new jobs and higher real wages (and greater access to credit) have boosted household purchasing power and so pushed up domestic demand. Much of this demand is for non-tradable goods and services (and imports), which has stimulated expansion of the tertiary sector and hence its demand for labour, and many of the new jobs have therefore arisen in these sectors of the economy. This dynamic certainly has positive implications in terms of labour and distribution, but the concern is whether it is sustainable in a context of still relatively low investment (even after some recent gains) which is, moreover, not structured in a manner conducive to diversifying production. Doubt hangs over the future growth of production capacity in the region, given the enormous challenges facing the region in terms of innovation, education quality, infrastructure and productivity. As vigorous job creation has driven progress in reducing unemployment, attention has turned once again to the characteristics of that employment. Awareness exists in the region that economic growth is essential, but not in itself sufficient to generate more and better jobs. For some time, ILO has been drawing attention to the fact that it is not enough to create any sort of employment. The concept of decent work, as proposed by ILO, emphasized the need for quality jobs which enshrine respect for fundamental rights at work. The United Nations General Assembly endorsed this notion and incorporated it into the targets set in the framework of the Millennium Development Goals. This eighth issue of the ECLAC/ILO publication “The employment situation in Latin America and the Caribbean” examines how the concept of decent work has evolved in the region, progress in measuring it and the challenges involved in building a system of decent work indicators, 14 years after the concept was first proposed. Although the concept of decent work has been accompanied since the outset by the challenge of measurement, its first objective was to generate a discussion on the best achievable labour practices in each country. Accordingly, rather than defining a universal threshold of what could be considered decent work —regarding which developed countries might have almost reached the target before starting, while poor countries could be left hopelessly behind— ILO called upon the countries to define their own criteria and measurements for promoting decent work policies. As a result, there is no shared set of variables for measuring decent work applicable to all countries. The suggestion is, instead, that countries move forward with measuring decent work on the basis of their own priorities, using the information they have available now and in the future. However, this strategy of progressing according to the data available in each country tends to complicate statistical comparison between them. So, once the countries have developed their respective systems of decent work indicators, it will be also be important to work towards harmonizing them. ECLAC and ILO are available to provide technical support to this end. With respect to 2013, there is cautious optimism regarding the performance of the region’s labour markets. If projections of a slight uptick —to 3.5%— in the region’s economic growth in 2013 are borne out, labour indicators should continue to gradually improve. This will bring new increases in real wages and a slight drop of up to 0.2 percentage points in the region’s unemployment rate, reflecting a fresh rise in the regional employment rate and slower growth in labour market participation.

Towards measuring the complexity of introducing semantics into a company

The Semantics Difficulty Model (SDM) is a model that measures the difficult of introducing semantics technology into a company. SDM manages three descriptions of stages, which we will refer to as ?snapshots?: a company semantic snapshot, data snapshot and semantic application snapshot. Understanding a priory the complexity of introducing semantics into a company is important because it allows the organization to take early decisions, thus saving time and money, mitigating risks and improving innovation, time to market and productivity. SDM works by measuring the distance between each initial snapshot and its reference models (the company semantic snapshots reference model, data snapshots reference model, and the semantic application snapshots reference model) with Euclidian distances. The difficulty level will be "not at all difficult" when the distance is small, and becomes "extremely difficult" when the the distance is large. SDM has been tested experimentally with 2000 simulated companies with arrangements and several initial stages. The output is measured by five linguistic values: "not at all difficult, slightly difficult, averagely difficult, very difficult and extremely difficult". As the preliminary results of our SDM simulation model indicate, transforming a search application into integrated data from different sources with semantics is a "slightly difficult", in contrast with data and opinion extraction applications for which it is "very difficult".

Analysis of productivity : enhancing capital investment opportunities.

One of series of five special reports expanding on the contents of the summary report titled "Measuring and enchancing productivity in the Federal Governments" conducted as a joint project by CSC/GAO/OMB.

A combined neural network and DEA for measuring efficiency of large scale datasets

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement of the efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper proposes a neural network back-propagation Data Envelopment Analysis to address this problem for the very large scale datasets now emerging in practice. Neural network requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large datasets. Finally, the back-propagation DEA algorithm is applied to five large datasets and compared with the results obtained by conventional DEA.

Evaluation of research in efficiency and productivity:a survey and analysis of the first 30 years of scholarly literature in DEA

Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available. This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007. A listing of the most utilized/relevant journals, a keyword analysis, and selected statistics are presented.

Technical efficiency:efficiency, change, technical progress and productivity growth in the national health systems of continental African countries

In May 2006, the Ministers of Health of all the countries on the African continent, at a special session of the African Union, undertook to institutionalise efficiency monitoring within their respective national health information management systems. The specific objectives of this study were: (i) to assess the technical efficiency of National Health Systems (NHSs) of African countries for measuring male and female life expectancies, and (ii) to assess changes in health productivity over time with a view to analysing changes in efficiency and changes in technology. The analysis was based on a five-year panel data (1999-2003) from all the 53 countries of continental Africa. Data Envelopment Analysis (DEA) - a non-parametric linear programming approach - was employed to assess the technical efficiency. Malmquist Total Factor Productivity (MTFP) was used to analyse efficiency and productivity change over time among the 53 countries' national health systems. The data consisted of two outputs (male and female life expectancies) and two inputs (per capital total health expenditure and adult literacy). The DEA revealed that 49 (92.5%) countries' NHSs were run inefficiently in 1999 and 2000; 50 (94.3%), 48 (90.6%) and 47 (88.7%) operated inefficiently in 2001, 2002, and 2003 respectively. All the 53 countries' national health systems registered improvements in total factor productivity attributable mainly to technical progress. Fifty-two countries did not experience any change in scale efficiency, while thirty (56.6%) countries' national health systems had a Pure Efficiency Change (PEFFCH) index of less than one, signifying that those countries' NHSs pure efficiency contributed negatively to productivity change. All the 53 countries' national health systems registered improvements in total factor productivity, attributable mainly to technical progress. Over half of the countries' national health systems had a pure efficiency index of less than one, signifying that those countries' NHSs pure efficiency contributed negatively to productivity change. African countries may need to critically evaluate the utility of institutionalising Malmquist TFP type of analyses to monitor changes in health systems economic efficiency and productivity over time. African national health systems, per capita total health expenditure, technical efficiency, scale efficiency, Malmquist indices of productivity change, DEA

Measurement efficiency and productivity in SAS/OR

This paper explores the use of the optimisation procedures in SAS/OR software with application to the measurement of efficiency and productivity of decision-making units (DMUs) using data envelopment analysis (DEA) techniques. DEA was originally introduced by Charnes et al. [J. Oper. Res. 2 (1978) 429] is a linear programming method for assessing the efficiency and productivity of DMUs. Over the last two decades, DEA has gained considerable attention as a managerial tool for measuring performance of organisations and it has widely been used for assessing the efficiency of public and private sectors such as banks, airlines, hospitals, universities and manufactures. As a result, new applications with more variables and more complicated models are being introduced. Further to successive development of DEA a non-parametric productivity measure, Malmquist index, has been introduced by Fare et al. [J. Prod. Anal. 3 (1992) 85]. Employing Malmquist index, productivity growth can be decomposed into technical change and efficiency change. On the other hand, the SAS is a powerful software and it is capable of running various optimisation problems such as linear programming with all types of constraints. To facilitate the use of DEA and Malmquist index by SAS users, a SAS/MALM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear-programming models based on the selected DEA. An example is given to illustrate how one could use the code to measure the efficiency and productivity of organisations.

Managing service productivity using data envelopment analysis

This chapter provides the theoretical foundation and background on data envelopment analysis (DEA) method. We first introduce the basic DEA models. The balance of this chapter focuses on evidences showing DEA has been extensively applied for measuring efficiency and productivity of services including financial services (banking, insurance, securities, and fund management), professional services, health services, education services, environmental and public services, energy services, logistics, tourism, information technology, telecommunications, transport, distribution, audio-visual, media, entertainment, cultural and other business services. Finally, we provide information on the use of Performance Improvement Management Software (PIM-DEA). A free limited version of this software and downloading procedure is also included in this chapter.