The impacts of market orientation and corporate social responsibility on firm performance:evidence from China

Purpose – The purpose of this paper is to investigate the joint effects of market orientation (MO) and corporate social responsibility (CSR) on firm performance. Design/methodology/approach – Data were collected via a questionnaire survey of star-rated hotels in China and a total of 143 valid responses were received. The hypotheses were tested by employing structural equation modelling with a maximum likelihood estimation option. Findings – It was found that although both MO and CSR could enhance performance, once the effects of CSR are accounted for, the direct effects of MO on performance diminish considerably to almost non-existent. Although this result may be due to the fact that the research is conducted in China, a country where CSR might be crucially important to performance given the country's socialist legacy, it nonetheless provides strong evidence that MO's impact on organizational performance is mediated by CSR. Research limitations/implications – The main limitations include the use of cross-sectional data, the subjective measurement of performance and the uniqueness of the research setting (China). The findings provide an additional important insight into the processes by which a market oriented culture is transformed into superior organizational performance. Originality/value – This paper is one of the first to examine the joint effects of MO and CSR on business performance. The empirical evidence from China adds to the existing literature on the respective importance of MO and CSR.

Radioimmunoassay of insulin and glucagon with studies on the obese hyperglycaemic syndrome in mice

Sensitive and precise radioimmunoassays for insulin and glucagon have been established. Although it was possible to employ similar precepts to the development of both hormone assays, the establishment of a reliable glucagon radioimmunoassay was complicated by the poor immunogenicity and instability of the peptide. Thus, unlike insulin antisera which were prepared by monthly injection of guinea pigs with crystalline insulin emulsified in adjuvant, the successful production of glucagon antisera was accomplished by immunisation of rabbits and guinea pigs with glucagon covalently linked to bovine plasma albumin. The conventional chloramine-T iodination with purification by gel chromatography was only suitable for the production of labelled insulin. Quality tracer for use in the glucagon radioimmunoassay was prepared by trace iodination, with subsequent purification of monoiodinated glucagon by anion exchange chromatography. Separation of free and antibody bound moieties by coated charcoal was applicable to both hormone assays, and a computerised data processing system, relying on logit-log transformation, was used to analyse all assay results. The assays were employed to evaluate the regulation of endocrine pancreatic function and the role of insulin and glucagon in the pathogenesis of the obese hyperglycaemic syndrome in mice. In the homozygous (ob/ob) condition, mice of the Birmingham strain were characterised by numerous abnormalities of glucose homeostasis, several of which were detected in heterozygous (ob/+) mice. Obese mice exhibited pancreatic alpha cell dysfunction and hyperglucagonaemia. Investigation of this defect revealed a marked insensitivity of an insulin dependent glucose sensing mechanism that inhibited glucagon secretion. Although circulating glucagon was of minor importance in the maintenance of hyperinsulinaemia, lack of suppression of alpha cell function by glucose and insulin contributed significantly to both the insulin insensitivity and the hyperglycaemia of obese mice.

In vivo and in vitro aspects of imidazoline-2(1/2)sites within the central nervous system

The in vivo and in vitro characteristics of the I2 binding site were probed using the technique of drug discrimination and receptor autoradiography. Data presented in this thesis indicates the I2 ligand 2-BFI generates a cue in drug discrimination. Further studies indicated agmatine, a proposed endogenous imidazoline ligand, and a number of imidazoline and imidazole analogues of 2-BFI substitute significantly for 2-BFI. In addition to specific I2 ligands the administration of NRl's (noradrenaline reuptake inhibitors), the sympathomimetic d-amphetamine, the α1-adrenoceptor agonist methoxamine, but not the β1 agonist dobutamine or the β2 agonist salbutamol, gave rise to significant levels of substitution for the 2-BFI cue. The administration of the α1-adrenoceptor antagonist WB4101, prior to 2- BFI itself significantly reduced levels of 2-BFI appropriate responding. Administration of the reversible MAO-A inhibitors moclobemide and Ro41-1049, but not the reversible MAO-B inhibitors lazabemide and Ro16-6491, gave rise to potent dose dependent levels of substitution for the 2-BFI cue. Further studies indicated the administration of a number of β-carbolines and the structurally related indole alkaloid ibogaine also gave rise to dose dependent significant levels of substitution. Due to the relationship of indole alkaloids to serotonin the 5-HT releaser fenfluramine and a number of SSRI's (selective serotonin reuptake inhibitor) were also administered and these compounds gave rise to significant partial (20-80% responses to the 2-BFI lever) levels of substitution. The autoradiographical studies reported here indicate [3H]2-BFI labels I2 sites within the rat arcuate nucleus, area postrema, pineal gland, interpeduncular nucleus and subfornical organ. Subsequent experiments confirmed that the drug discrimination dosing schedule significantly increases levels of [3H]2-BFI 12 binding within two of these nuclei. However, levels of [3H]2-BFI specific binding were significantly reduced within four of these nuclei after chronic treatment with the irreversible MAO inhibitors deprenyl and tranylcypromine but not pargyline, which only reduced levels significantly in two. Further autoradiographical studies indicated that the distribution of [3H]2-BFI within the C57/B mouse compares favourably to that within the rat. Comparison of these levels of binding to those from transgenic mice who over-express MAO-B indicates two possibly distinct populations of [3H]2-BFI 12 sites exist in mouse brain. The data presented here indicates the 2-BFI cue is associated with the selective activation of α1-adrenoceptors and possibly 5-HT receptors. 2-BFI trained rats recognise reversible MAO-A but not MAO-B inhibitors. However, data within this thesis indicates the autoradiographical distribution of I2 sites bears a closer resemblance to that of MAO-B not MAO-A and further studies using transgenic mice that over-express MAO-B suggests a non-MAO-B I2 site exists in mouse brain.

Quasi-lossless spans for broadband transmission and data processing

We present the first experimental implementation of a recently designed quasi-lossless fibre span with strongly reduced signal power excursion. The resulting fibre waveguide medium can be advantageously used both in lightwave communications and in all-optical nonlinear data processing.

The impact of employees' customer orientation and service orientation behaviours on customers' service evaluation

In this paper the authors conceptualize and test the effects of service employees’ customer orientation and service orientation behaviors within an extended service evaluation model encompassing service quality, service encounter quality, perceived value and customer satisfaction. The context is 271 Indian retail customers. Data analysis incorporates confirmatory factor analysis and structural equation modeling. We find that Findings indicate that: 1) customer orientation is positively related to service orientation, customers’ perceptions of service encounter quality and service quality; 2) service orientation influences customers’ perceptions of service encounter quality and service quality; 3) customers’ perceptions of service encounter quality influence customers’ perceptions of service quality and customer satisfaction; 4) customers’ perceptions of service quality influence value perceptions; 5) service quality influences customer satisfaction; and 6) customer satisfaction influences customers’ behavioral intentions. The importance of these findings for practitioners and academics, research limitations and future research avenues are subsequently discussed.

The influence of formulation and manufacturing process parameters on the characteristics of lyophilized orally disintegrating tablets

Gelatin is a principal excipient used as a binder in the formulation of lyophilized orally disintegrating tablets. The current study focuses on exploiting the physicochemical properties of gelatin by varying formulation parameters to determine their influence on orally disintegrating tablet (ODT) characteristics. Process parameters, namely pH and ionic strength of the formulations, and ball milling were investigated to observe their effects on excipient characteristics and tablet formation. The properties and characteristics of the formulations and tablets which were investigated included: glass transition temperature, wettability, porosity, mechanical properties, disintegration time, morphology of the internal structure of the freeze-dried tablets, and drug dissolution. The results from the pH study revealed that adjusting the pH of the formulation away from the isoelectric point of gelatin, resulted in an improvement in tablet disintegration time possibly due to increase in gelatin swelling resulting in greater tablet porosity. The results from the ionic strength study revealed that the inclusion of sodium chloride influenced tablet porosity, tablet morphology and the glass transition temperature of the formulations. Data from the milling study showed that milling the excipients influenced formulation characteristics, namely wettability and powder porosity. The study concludes that alterations of simple parameters such as pH and salt concentration have a significant influence on formulation of ODT. © 2011 by the authors; licensee MDPI, Basel, Switzerland.

Simultaneous clock recovery and data regeneration using a nonlinear optical loop mirror as an all-optical mixer

High-speed optical clock recovery, demultiplexing and data regeneration will be integral parts of any future photonic network based on high bit-rate OTDM. Much research has been conducted on devices that perform these functions, however to date each process has been demonstrated independently. A very promising method of all-optical switching is that of a semiconductor optical amplifier-based nonlinear optical loop mirror (SOA-NOLM). This has various advantages compared with the standard fiber NOLM, most notably low switching power, compact size and stability. We use the SOA-NOLM as an all-optical mixer in a classical phase-locked loop arrangement to achieve optical clock recovery, while at the same time achieving data regeneration in a single compact device

Quasi-lossless spans for broadband transmission and data processing

We present the first experimental implementation of a recently designed quasi-lossless fibre span with strongly reduced signal power excursion. The resulting fibre waveguide medium can be advantageously used both in lightwave communications and in all-optical nonlinear data processing.

Energy aware data gathering based on adaptive modulation scaling in wireless sensor networks

Energy consumption has been a key concern of data gathering in wireless sensor networks. Previous research works show that modulation scaling is an efficient technique to reduce energy consumption. However, such technique will also impact on both packet delivery latency and packet loss, therefore, may result in adverse effects on the qualities of applications. In this paper, we study the problem of modulation scaling and energy-optimization. A mathematical model is proposed to analyze the impact of modulation scaling on the overall energy consumption, end-to-end mean delivery latency and mean packet loss rate. A centralized optimal management mechanism is developed based on the model, which adaptively adjusts the modulation levels to minimize energy consumption while ensuring the QoS for data gathering. Experimental results show that the management mechanism saves significant energy in all the investigated scenarios. Some valuable results are also observed in the experiments. © 2004 IEEE.

Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

Applications of Nonclassical Logic Methods for Purposes of Knowledge Discovery and Data Mining

* The work is partially supported by Grant no. NIP917 of the Ministry of Science and Education – Republic of Bulgaria.

Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network

In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

The Fifth National Information Day: Open Access to Scientific Information and Data

This work was supported in part by the EU „2nd Generation Open Access Infrastructure for Research in Europe" (OpenAIRE+). The autumn training school Development and Promotion of Open Access to Scientific Information and Research is organized in the frame of the Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage—DiPP2014 (September 18–21, 2014, Veliko Tarnovo, Bulgaria, http://dipp2014.math.bas.bg/), organized under the UNESCO patronage. The main organiser is the Institute of Mathematics and Informatics, Bulgarian Academy of Sciences with the support of EU project FOSTER (http://www.fosteropenscience.eu/) and the P. R. Slaveykov Regional Public Library in Veliko Tarnovo, Bulgaria.

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.

Degree of vertical integration and its buffering effects on political uncertainty

The focus of this study is on the governance decisions in a concurrent channels context, in the case of uncertainty. The study examines how a firm chooses to deploy its sales force in times of uncertainty, and the subsequent performance outcome of those deployment choices. The theoretical framework is based on multiple theories of governance, including transaction cost analysis (TCA), agency theory, and institutional economics. Three uncertainty variables are investigated in this study. The first two are demand and competitive uncertainty which are considered to be industry-level market uncertainty forms. The third uncertainty, political uncertainty, is chosen as it is an important dimension of institutional environments, capturing non-economic circumstances such as regulations and political systemic issues. The study employs longitudinal secondary data from a Thai hotel chain, comprising monthly observations from January 2007 – December 2012. This hotel chain has its operations in 4 countries, Thailand, the Philippines, United Arab Emirates – Dubai, and Egypt, all of which experienced substantial demand, competitive, and political uncertainty during the study period. This makes them ideal contexts for this study. Two econometric models, both deploying Newey-West estimations, are employed to test 13 hypotheses. The first model considers the relationship between uncertainty and governance. The second model is a version of Newey-West, using an Instrumental Variables (IV) estimator and a Two-Stage Least Squares model (2SLS), to test the direct effect of uncertainty on performance and the moderating effect of governance on the relationship between uncertainty and performance. The observed relationship between uncertainty and governance observed follows a core prediction of TCA; that vertical integration is the preferred choice of governance when uncertainty rises. As for the subsequent performance outcomes, the results corroborate that uncertainty has a negative effect on performance. Importantly, the findings show that becoming more vertically integrated cannot help moderate the effect of demand and competitive uncertainty, but can significantly moderate the effect of political uncertainty. These findings have significant theoretical and practical implications, and extend our knowledge of the impact on uncertainty significantly, as well as bringing an institutional perspective to TCA. Further, they offer managers novel insight into the nature of different types of uncertainty, their impact on performance, and how channel decisions can mitigate these impacts.