Neuroimaging and psychophysiological measurement in organizational research:an agenda for research in organizational cognitive neuroscience

Although organizational research has made tremendous strides in the last century, recent advances in neuroscience and the imaging of functional brain activity remain underused. In fact, even the use of well-established psychophysiological measurement tools is comparatively rare. Following the lead of social cognitive neuroscience, in this review, we conceptualize organizational cognitive neuroscience as a field dedicated to exploring the processes within the brain that underlie or influence human decisions, behaviors, and interactions either (a) within organizations or (b) in response to organizational manifestations or institutions. We discuss organizational cognitive neuroscience, bringing together work that may previously have been characterized rather atomistically, and provide a brief overview of individual methods that may be of use. Subsequently, we discuss the possible convergence and integration of the different neuroimaging and psychophysiological measurement modalities. A brief review of prior work in the field shows a significant need for a more coherent and theory-driven approach to organizational cognitive neuroscience. In response, we discuss a recent example of such work, along with three hypothetical case studies that exemplify the link between organizational and psychological theory and neuroscientific methods.

The impact of performance measurement in strategic planning

Purpose – To investigate the impact of performance measurement in strategic planning process. Design/methodology/approach – A large scale survey was conducted online with Warwick Business School alumni. The questionnaire was based on the Strategic Development Process model by Dyson. The questionnaire was designed to map the current practice of strategic planning and to determine its most influential factors on the effectiveness of the process. All questions were close ended and a seven-point Likert scale used. The independent variables were grouped into four meaningful factors by factor analysis (Varimax, coefficient of rotation 0.4). The factors produced were used to build regression models (stepwise) for the five assessments of strategic planning process. Regression models were developed for the totality of the responses, comparing SMEs and large organizations and comparing organizations operating in slowly and rapidly changing environments. Findings – The results indicate that performance measurement stands as one of the four main factors characterising the current practice of strategic planning. This research has determined that complexity coming from organizational size and rate of change in the sector creates variation in the impact of performance measurement in strategic planning. Large organizations and organizations operating in rapidly changing environments make greater use of performance measurement. Research limitations/implications – This research is based on subjective data, therefore the conclusions do not concern the impact of strategic planning process' elements on the organizational performance achievements, but on the success/effectiveness of the strategic planning process itself. Practical implications – This research raises a series of questions about the use and potential impact of performance measurement, especially in the categories of organizations that are not significantly influenced by its utilisation. It contributes to the field of performance measurement impact. Originality/value – This research fills in the gap literature concerning the lack of large scale surveys on strategic development processes and performance measurement. It also contributes in the literature of this field by providing empirical evidences on the impact of performance measurement upon the strategic planning process.

Comparative performance measurement in regulation: The case of English and Welsh sewerage services

This paper discusses the use of comparative performance measurement by means of Data Envelopment Analysis in the context of the regulation of English and Welsh water companies. Specifically, the use of Data Envelopment Analysis to estimate potential cost savings in sewerage is discussed as it fed into the price review of water companies carried out by the regulator of water companies in 1994. The application is used as a vehicle for highlighting generic issues in terms of assessing the impact of factors on the ranking of units on performance, the insights gained from using alternative methods to assess comparative performance, and the issue of assessing comparative performance when few in number but highly complex entities are involved. The paper should prove of interest to those interested in regulation and, more generally, in the use of methods of comparative performance measurement.

An inter-laboratory validation of methods of lipid peroxidation measurement in UVA-treated human plasma samples

Lipid peroxidation products like malondialdehyde, 4-hydroxynonenal and F(2)-isoprostanes are widely used as markers of oxidative stress in vitro and in vivo. This study reports the results of a multi-laboratory validation study by COST Action B35 to assess inter-laboratory and intra-laboratory variation in the measurement of lipid peroxidation. Human plasma samples were exposed to UVA irradiation at different doses (0, 15 J, 20 J), encoded and shipped to 15 laboratories, where analyses of malondialdehyde, 4-hydroxynonenal and isoprostanes were conducted. The results demonstrate a low within-day-variation and a good correlation of results observed on two different days. However, high coefficients of variation were observed between the laboratories. Malondialdehyde determined by HPLC was found to be the most sensitive and reproducible lipid peroxidation product in plasma upon UVA treatment. It is concluded that measurement of malondialdehyde by HPLC has good analytical validity for inter-laboratory studies on lipid peroxidation in human EDTA-plasma samples, although it is acknowledged that this may not translate to biological validity.

Efficiency measurement in fuzzy additive data envelopment analysis

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This paper extends the conventional DEA models to a fuzzy framework by proposing a new fuzzy additive DEA model for evaluating the efficiency of a set of decision-making units (DMUs) with fuzzy inputs and outputs. The contribution of this paper is threefold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA, (2) we propose a new fuzzy additive DEA model derived from the a-level approach and (3) we demonstrate the practical aspects of our model with two numerical examples and show its comparability with five different fuzzy DEA methods in the literature. Copyright © 2011 Inderscience Enterprises Ltd.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Clinical measurement in assessing obesity and the prediction of biomarkers in association to cardovascular diseases and type-II diabetes

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Influence of macroscopic residual stress fields on fatigue crack growth measurement in SiC particulate reinforced 8090 aluminium alloy

The effect of residual stresses, induced by cold water quenching, on the morphology of fatigue crack fronts has been investigated in a powder metallurgy 8090 aluminium alloy, with and without reinforcement in the form of 20 wt-%SiC particles. Residual stress measurements reveal that the surface compressive stresses developed in these materials are significantly greater than in conventional metallurgy ingot 8090, because surface yielding occurs on quenching. The yield stresses of the powder route materials are greater than those of ingot produced 8090 and hence greater surface stresses can be maintained. In fatigue, severe crack front bowing is observed in the powder formed materials as a result of the reduction of the R ratio (minimum load/maximum load) by the compressive residual stresses at the sides of the specimen, causing premature crack closure and hence reducing the local driving force for fatigue crack growth ΔKeff. This distortion of the crack fronts introduces large errors into measurements of crack growth rate and threshold values of ΔK.

MRI pressure and stress measurement in novel homogeneous soft solids

This paper presents MRI measurements of a novel semi solid MR contrast agent to pressure. The agent is comprised of potassium chloride cross linked carageenan gum at a concentration of 2% w/v, with micron size lipid coated bubbles of air at a concentration of 3% v/v. The choice for an optimum suspending medium, the methods of production and the preliminary MRI results are presented herein. The carageenan gum is shown to be ideally elastic for compressions relating to volume changes less than 15%, in contrast to the inelastic gellan gum also tested. Although slightly lower than that of gellan gum, carageenan has a water diffusion coefficient of 1.72×10-9 m2.s-1 indicating its suitability to this purpose. RARE imaging is performed whilst simultaneously compressing test and control samples and a maximum sensitivity of 1.6% MR signal change per % volume change is found which is shown to be independent of proton density variations due to the presence of microbubbles and compression. This contrast agent could prove useful for numerous applications, and particularly in chemical engineering. More generally the method allows the user to non-invasively image with MRI any process that causes, within the solid, local changes either in bubble size or bubble shape. © 2008 American Institute of Physics.

A hybrid measurement systems analysis and uncertainty of measurement approach for industrial measurement in the light controlled factory

The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.

Intelligent outcome measures in liaison psychiatry:essential even if not desirable. Commentary on... a multidimensional Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP)

Service development is guided by outcome measures that inform service commissioners and providers. Those in liaison psychiatry should be encouraged to develop a positive approach that integrates the collection of outcome measures into everyday clinical practice. The Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP) is a very useful tool to measure service quality and clinical effectiveness, using a combination of clinician-rated and patient-rated outcome measures and patient-rated experience measures. However, it does not include measures of cost-effectiveness or training activities. The FROM-LP is a significant step towards developing nationally unified outcome measures.

Optical sensor based on hybrid LPG/FBG in D-fiber for simultaneous refractive index and temperature measurement

A dual-parameter optical sensor has been realized by UV-writing a long-period and a Bragg grating structure in D-fiber. The hybrid configuration permits the detection of the temperature from the latter and measuring the external refractive index from the former responses, respectively. The employment of the D-fiber allows as effective modification and enhancement of the device sensitivity by cladding etching. The grating sensor has been used to measure the concentrations of aqueous sugar solutions, demonstrating the potential capability to detect concentration changes as small as 0.01%.

Optical sensor based on hybrid LPG/FBG in D-fiber for simultaneous refractive index and temperature measurement

A dual-parameter optical sensor has been realized by UV-writing a long-period and a Bragg grating structure in D-fiber. The hybrid configuration permits the detection of the temperature from the latter and measuring the external refractive index from the former responses, respectively. The employment of the D-fiber allows as effective modification and enhancement of the device sensitivity by cladding etching. The grating sensor has been used to measure the concentrations of aqueous sugar solutions, demonstrating the potential capability to detect concentration changes as small as 0.01%.