Employee social responsibility:development of an ESR measure and a multi-level investigation of antecedent and boundary conditions

The following thesis instigates the discussion on corporate social responsibility (CSR) through a review of literature on the conceptualisation, determinants, and remunerations of organisational CSR engagement. The case is made for the need to draw attention to the micro-levels of CSR, and consequently focus on employee social responsibility at multiple levels of analysis. In order to further research efforts in this area, the prerequisite of an employee social responsibility behavioural measurement tool is acknowledged. Accordingly, the subsequent chapters outline the process of scale development and validation, resulting in a robust, reliable and valid employee social responsibility scale. This scale is then put to use in a field study, and the noteworthy roles of the antecedent and boundary conditions of transformational leadership, assigned CSR priority, and CSR climate are confirmed at the group and individual level. Directionality of these relationships is subsequently alluded to in a time-lagged investigation, set within a simulated business environment. The thesis collates and discusses the contributions of the findings from the research series, which highlight a consistent three-way interaction effect of transformational leadership, assigned CSR priority and CSR climate. Specifically, efforts are made to outline various avenues for future research, given the infancy of the micro-level study of employee social responsibility.

Simultaneous grouping in cochlear implant listeners:can abrupt changes in level be used to segregate components from a complex tone?

A sudden increase in the amplitude of a component often causes its segregation from a complex tone, and shorter rise times enhance this effect. We explored whether this also occurs in implant listeners (n?=?8). Condition 1 used a 3.5-s “complex tone” comprising concurrent stimulation on five electrodes distributed across the array of the Nucleus CI24 implant. For each listener, the baseline stimulus level on each electrode was set at 50% of the dynamic range (DR). Two 1-s increments of 12.5%, 25%, or 50% DR were introduced in succession on adjacent electrodes within the “inner” three of those activated. Both increments had rise and fall times of 30 and 970 ms or vice versa. Listeners reported which increment was higher in pitch. Some listeners performed above chance for all increment sizes, but only for 50% increments did all listeners perform above chance. No significant effect of rise time was found. Condition 2 replaced amplitude increments with decrements. Only three listeners performed above chance even for 50% decrements. One exceptional listener performed well for 50% decrements with fall and rise times of 970 and 30 ms but around chance for fall and rise times of 30 and 970 ms, indicating successful discrimination based on a sudden rise back to baseline stimulation. Overall, the results suggest that implant listeners can use amplitude changes against a constant background to pick out components from a complex, but generally these must be large compared with those required in normal hearing. For increments, performance depended mainly on above-baseline stimulation of the target electrodes, not rise time. With one exception, performance for decrements was typically very poor.

Financial liberalization and dynamics of firm-level financing and investment decisions in the Southeast Asian countries

This thesis examines the dynamics of firm-level financing and investment decisions for six Southeast Asian countries. The study provides empirical evidence on the impacts of changes in the firm-level financing decisions during the period of financial liberalization by considering the debt and equity financing decisions of a set of non-financial firms. The empirical results show that firms in Indonesia, Pakistan, and South Korea have relatively faster speed of adjustment than other Southeast Asian countries to attain optimal debt and equity ratios in response to banking sector and stock market liberalization. In addition, contrary to widely held belief that firms adjust their financial ratios to industry levels, the results indicate that industry factors do not significantly impact on the speed of capital structure adjustments. This study also shows that non-linear estimation methods are more appropriate than linear estimation methods for capturing changes in capital structure. The empirical results also show that international stock market integration of these countries has significantly reduced the equity risk premium as well as the firm-level cost of equity capital. Thus stock market liberalization is associated with a decrease in the cost of equity capital of the firms. Developments in the securities markets infrastructure have also reduced the cost of equity capital. However, with increased integration there is the possibility of capital outflows from the emerging markets, which might reverse the pattern of decrease in cost of capital in these markets.

Low level feature detection in human vision

Influential models of edge detection have generally supposed that an edge is detected at peaks in the 1st derivative of the luminance profile, or at zero-crossings in the 2nd derivative. However, when presented with blurred triangle-wave images, observers consistently marked edges not at these locations, but at peaks in the 3rd derivative. This new phenomenon, termed ‘Mach edges’ persisted when a luminance ramp was added to the blurred triangle-wave. Modelling of these Mach edge detection data required the addition of a physiologically plausible filter, prior to the 3rd derivative computation. A viable alternative model was examined, on the basis of data obtained with short-duration, high spatial-frequency stimuli. Detection and feature-making methods were used to examine the perception of Mach bands in an image set that spanned a range of Mach band detectabilities. A scale-space model that computed edge and bar features in parallel provided a better fit to the data than 4 competing models that combined information across scale in a different manner, or computed edge or bar features at a single scale. The perception of luminance bars was examined in 2 experiments. Data for one image-set suggested a simple rule for perception of a small Gaussian bar on a larger inverted Gaussian bar background. In previous research, discriminability (d’) has typically been reported to be a power function of contrast, where the exponent (p) is 2 to 3. However, using bar, grating, and Gaussian edge stimuli, with several methodologies, values of p were obtained that ranged from 1 to 1.7 across 6 experiments. This novel finding was explained by appealing to low stimulus uncertainty, or a near-linear transducer.

High performance liquid level monitoring system based on polymer fiber Bragg gratings embedded in silicone rubber diaphragm

Liquid-level sensing technologies have attracted great prominence, because such measurements are essential to industrial applications, such as fuel storage, flood warning and in the biochemical industry. Traditional liquid level sensors are based on electromechanical techniques; however they suffer from intrinsic safety concerns in explosive environments. In recent years, given that optical fiber sensors have lots of well-established advantages such as high accuracy, costeffectiveness, compact size, and ease of multiplexing, several optical fiber liquid level sensors have been investigated which are based on different operating principles such as side-polishing the cladding and a portion of core, using a spiral side-emitting optical fiber or using silica fiber gratings. The present work proposes a novel and highly sensitive liquid level sensor making use of polymer optical fiber Bragg gratings (POFBGs). The key elements of the system are a set of POFBGs embedded in silicone rubber diaphragms. This is a new development building on the idea of determining liquid level by measuring the pressure at the bottom of a liquid container, however it has a number of critical advantages. The system features several FBG-based pressure sensors as described above placed at different depths. Any sensor above the surface of the liquid will read the same ambient pressure. Sensors below the surface of the liquid will read pressures that increase linearly with depth. The position of the liquid surface can therefore be approximately identified as lying between the first sensor to read an above-ambient pressure and the next higher sensor. This level of precision would not in general be sufficient for most liquid level monitoring applications; however a much more precise determination of liquid level can be made by linear regression to the pressure readings from the sub-surface sensors. There are numerous advantages to this multi-sensor approach. First, the use of linear regression using multiple sensors is inherently more accurate than using a single pressure reading to estimate depth. Second, common mode temperature induced wavelength shifts in the individual sensors are automatically compensated. Thirdly, temperature induced changes in the sensor pressure sensitivity are also compensated. Fourthly, the approach provides the possibility to detect and compensate for malfunctioning sensors. Finally, the system is immune to changes in the density of the monitored fluid and even to changes in the effective force of gravity, as might be obtained in an aerospace application. The performance of an individual sensor was characterized and displays a sensitivity (54 pm/cm), enhanced by more than a factor of 2 when compared to a sensor head configuration based on a silica FBG published in the literature, resulting from the much lower elastic modulus of POF. Furthermore, the temperature/humidity behavior and measurement resolution were also studied in detail. The proposed configuration also displays a highly linear response, high resolution and good repeatability. The results suggest the new configuration can be a useful tool in many different applications, such as aircraft fuel monitoring, and biochemical and environmental sensing, where accuracy and stability are fundamental. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Identifying the configurational paths to innovation in SMEs:a fuzzy-set qualitative comparative analysis

Using fuzzy-set qualitative comparative analysis (fsQCA), this study investigates the conditions leading to a higher level of innovation. More specifically, the study explores the impact of inter-organisational knowledge transfer networks and organisations' internal capabilities on different types of innovation in Small to Medium size Enterprises (SMEs) in the high-tech sector. A survey instrument was used to collect data from a sample of UK SMEs. The findings show that although individual factors are important, there is no need for a company to perform well in all the areas. The fsQCA, which enables the examination of the impacts of different combinations of factors, reveals that there are a number of paths to achieve better incremental and radical innovation performance. Companies need to choose the one that is closest to their abilities and fits best with their resources.

Managing the multiplicities of graduate level education! Are Master’s students’ expectations matched by their experiences?

With rapid increases in student fees reflecting moves towards a QUASI Market model of Higher Education in the UK and across much of the Western World[1], many universities find themselves having to meet progressively higher levels of student expectations[2]. This is particularly the case at undergraduate level, where increases in fees over the past decade have far exceeded inflation. Yet with so much attention on ‘consumer savvy’ undergraduates, the question of whether Master’s level students’ expectations are matched by their experiences is one which remains largely unanswered. Grounded in an empirically grounded approach to learning and teaching developed by the paper authors[3], this paper sets out to being to answer this question. In doing so it makes a distinctive contribution to debates about graduate level engineering education and concludes with a number of recommendations. Discussion: The ‘MSc: Managing Expectations’ Project analyses the expectations and experiences of Graduate level Engineering Management Students over a two year period. Focusingon the ‘student experience’, three main concepts are identified as being particular relevant to enhancing learning [3]: Relationships: Variety: Synergy. Relationships: Based on empirical research, the significance of Relationships within the academic environment is discussed with particular attention being paid to the value of students’ social and academic support networks, including academic tutoring. Variety: Grounded in a statistical analysis of ‘engagement data’ together with survey and interview findings, the concept of variety critically examines students’ perspectives and experiencesof different approaches to learning and teaching. Synergy: Possibly the most important concept discussed within this paper, the need for constructively aligned curriculum is extended to reflect the students’ apriori knowledge and experienceas well as employer and societal demands and expectations. The conclusion brings the different concepts within the discussion together, providing a set of practical recommendations for colleagues working both at graduate and undergraduate level. References 1.Gibbs, P. (2001) "Higher education as a market: a problem or solution?." Studies in Higher Education 26. 1. pp. 85-94. 2.Tricker, T., (2005) Student Expectations-How do we measure up. University of Sheffield. Available from: http://www.persons.org.uk/tricker%20paper.pdf Accessed 9/10/14 3.Clark, R. & Andrews, J. (2014). Relationships, Variety & Synergy [RVS]: The Vital Ingredients for Scholarship in Engineering Education? A Case-Study. European Journal of Engineering Education. 39.6. pp. 585-600.

Comparing sentence-level features for authorship analysis in Portuguese

In this paper we compare the robustness of several types of stylistic markers to help discriminate authorship at sentence level. We train a SVM-based classifier using each set of features separately and perform sentence-level authorship analysis over corpus of editorials published in a Portuguese quality newspaper. Results show that features based on POS information, punctuation and word / sentence length contribute to a more robust sentence-level authorship analysis. © Springer-Verlag Berlin Heidelberg 2010.