Frontline employees' collaboration in industrial service innovation:routes of co-creation's effects on new service performance

From a Service-Dominant Logic (S-DL) perspective, employees constitute operant resources that firms can draw to enhance the outcomes of innovation efforts. While research acknowledges that frontline employees (FLEs) constitute, through service encounters, a key interface for the transfer of valuable external knowledge into the firm, the range of potential benefits derived from FLE-driven innovation deserves more investigation. Using a sample of knowledge intensive business services firms (KIBS), this study examines how the collaboration with FLEs along the new service development (NSD) process, namely FLE co-creation, impacts on service innovation performance following two routes of different effects. Partial least squares structural equation modeling (PLS-SEM) results indicate that FLE co-creation benefits the NS success among FLEs and firm’s customers, the constituents of the resources route. FLE co-creation also has a positive effect on the NSD speed, which in turn enhances the NS quality. NSD speed and NS quality integrate the operational route, which proves to be the most effective path to impact the NS market performance. Accordingly, KIBS managers must value their FLEs as essential partners to achieve successful innovation from an internal and external perspective, and develop the appropriate mechanisms to guarantee their effective involvement along the NSD process.

AllerTOP - a server for in silico prediction of allergens

Background: Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO/WHO Codex alimentarius guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.Results: A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three z-descriptors (z1, z2 and z3) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), naïve Bayes (NB) and k nearest neighbours (kNN). The best performing model was derived by kNN at k = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at http://www.pharmfac.net/allertop. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.Conclusions: AllerTOP is the first alignment-free server for in silico prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin. © 2013 Dimitrov et al.; licensee BioMed Central Ltd.

Mössbauer spectroscopic study of the thermal spin crossover in [Fe(II)(isoxazole)6](ClO4)2

The Fe Mössbauer spectroscopy of mononuclear [Fe(II)(isoxazole)](ClO) has been studied to reveal the thermal spin crossover of Fe(II) between low-spin (S = 0) and high-spin (S = 2) states. Temperaturedependent spin transition curves have been constructed with the least-square fitted data obtained from the Mössbauer spectra measured at various temperatures between 84 and 270 K during a cooling and heating cycle. This compound exhibits an unusual temperature-dependent spin transition behaviour with T(?) = 223 and T(?) = 213 K occurring in the reverse order in comparison to those observed in SQUID observation and many other spin transition compounds. The compound has three high-spin Fe(II) sites at the highest temperature of study of which two undergo spin transitions. The compound seems to undergo a structural phase transition around the spin transition temperature, which plays a significant role in the spin crossover behaviour as well as the magnetic properties of the compound at temperatures below T. The present study reveals an increase in high-spin fraction upon heating in the temperature range below T, and an explanation is provided.

Data analysis methods in optometry. Part 5: correlation

1. Pearson's correlation coefficient only tests whether the data fit a linear model. With large numbers of observations, quite small values of r become significant and the X variable may only account for a minute proportion of the variance in Y. Hence, the value of r squared should always be calculated and included in a discussion of the significance of r. 2. The use of r assumes that a bivariate normal distribution is present and this assumption should be examined prior to the study. If Pearson's r is not appropriate, then a non-parametric correlation coefficient such as Spearman's rs may be used. 3. A significant correlation should not be interpreted as indicating causation especially in observational studies in which there is a high probability that the two variables are correlated because of their mutual correlations with other variables. 4. In studies of measurement error, there are problems in using r as a test of reliability and the ‘intra-class correlation coefficient’ should be used as an alternative. A correlation test provides only limited information as to the relationship between two variables. Fitting a regression line to the data using the method known as ‘least square’ provides much more information and the methods of regression and their application in optometry will be discussed in the next article.

Using interior point algorithms for the solution of linear programs with special structural features

Linear Programming (LP) is a powerful decision making tool extensively used in various economic and engineering activities. In the early stages the success of LP was mainly due to the efficiency of the simplex method. After the appearance of Karmarkar's paper, the focus of most research was shifted to the field of interior point methods. The present work is concerned with investigating and efficiently implementing the latest techniques in this field taking sparsity into account. The performance of these implementations on different classes of LP problems is reported here. The preconditional conjugate gradient method is one of the most powerful tools for the solution of the least square problem, present in every iteration of all interior point methods. The effect of using different preconditioners on a range of problems with various condition numbers is presented. Decomposition algorithms has been one of the main fields of research in linear programming over the last few years. After reviewing the latest decomposition techniques, three promising methods were chosen the implemented. Sparsity is again a consideration and suggestions have been included to allow improvements when solving problems with these methods. Finally, experimental results on randomly generated data are reported and compared with an interior point method. The efficient implementation of the decomposition methods considered in this study requires the solution of quadratic subproblems. A review of recent work on algorithms for convex quadratic was performed. The most promising algorithms are discussed and implemented taking sparsity into account. The related performance of these algorithms on randomly generated separable and non-separable problems is also reported.

Consumer evaluations of brand extensions in emerging economies : evidences from China

This project explored how consumers in emerging economies evaluate brand extension by using China as a case. Two separate but related studies were conducted, and university students were used as respondents in both the studies. Study one or replication study tested Aaker and Keller's brand extension model in China. Assuming similar methods to Aaker and Keller's, six well-recognised brands were chosen as parent brand and each was extended to three product categories. Totally, 469 respondents completed the survey questionnaire. As each was to evaluate six extensions, this made the cases 2814. The data was analysed using Optimal Least Square regression approach and "residual centred" approach respectively. The result confirmed most of the findings observed in developed countries. Specifically, consumer's attitude towards the extension is primarily driven by the brand affect, the fit between the two product categories, the difficulty of making the extension and moderated via the interactions between the brand affect and the fit variables. Study two refined and extended Aaker and Keller's model by adding new variables and making methodological adjustments. The same stimuli and data analysis techniques as those in the replication were employed. 252 respondents participated in the survey and each evaluated six extensions, making cases 1512. In addition to re-verifying the findings of the replication and providing cross validation to these findings, the extended study found that the image consistency between the parent brand and the extension, the competition intensity of the extension product market were important in determining the success of the extension. Further, consumer differed in evaluating durable extensions and non-durable extensions. The thesis detailed the two studies above, and discussed the findings and their implications by relating to branding literature, to the general situation of the emerging economies as well as the reality of China. It also presented the limitations of the research and the future research directions.

Pricing-to-market for UK export sector

This thesis investigates the pricing-to-market (PTM) behaviour of the UK export sector. Unlike previous studies, this study econometrically tests for seasonal unit roots in the export prices prior to estimating PTM behaviour. Prior studies have seasonally adjusted the data automatically. This study’s results show that monthly export prices contain very little seasonal unit roots implying that there is a loss of information in the data generating process of the series when estimating PTM using seasonally-adjusted data. Prior studies have also ignored the econometric properties of the data despite the existence of ARCH effects in such data. The standard approach has been to estimate PTM models using Ordinary Least Square (OLS). For this reason, both EGARCH and GJR-EGARCH (hereafter GJR) estimation methods are used to estimate both a standard and an Error Correction model (ECM) of PTM. The results indicate that PTM behaviour varies across UK sectors. The variables used in the PTM models are co-integrated and an ECM is a valid representation of pricing behaviour. The study also finds that the price adjustment is slower when the analysis is performed on real prices, i.e., data that are adjusted for inflation. There is strong evidence of auto-regressive condition heteroscedasticity (ARCH) effects – meaning that the PTM parameter estimates of prior studies have been ineffectively estimated. Surprisingly, there is very little evidence of asymmetry. This suggests that exporters appear to PTM at a relatively constant rate. This finding might also explain the failure of prior studies to find evidence of asymmetric exposure in foreign exchange (FX) rates. This study also provides a cross sectional analysis to explain the implications of the observed PTM of producers’ marginal cost, market share and product differentiation. The cross-sectional regressions are estimated using OLS, Generalised Method of Moment (GMM) and Logit estimations. Overall, the results suggest that market share affects PTM positively.Exporters with smaller market share are more likely to operate PTM. Alternatively, product differentiation is negatively associated with PTM. So industries with highly differentiated products are less likely to adjust their prices. However, marginal costs seem not to be significantly associated with PTM. Exporters perform PTM to limit the FX rate effect pass-through to their foreign customers, but they also avoided exploiting PTM to the full, since to do so can substantially reduce their profits.

Seasonal variations of EPG levels in gastro-intestinal parasitic infection in a southeast asian controlled locale:a statistical analysis

We present a data based statistical study on the effects of seasonal variations in the growth rates of the gastro-intestinal (GI) parasitic infection in livestock. The alluded growth rate is estimated through the variation in the number of eggs per gram (EPG) of faeces in animals. In accordance with earlier studies, our analysis too shows that rainfall is the dominant variable in determining EPG infection rates compared to other macro-parameters like temperature and humidity. Our statistical analysis clearly indicates an oscillatory dependence of EPG levels on rainfall fluctuations. Monsoon recorded the highest infection with a comparative increase of at least 2.5 times compared to the next most infected period (summer). A least square fit of the EPG versus rainfall data indicates an approach towards a super diffusive (i. e. root mean square displacement growing faster than the square root of the elapsed time as obtained for simple diffusion) infection growth pattern regime for low rainfall regimes (technically defined as zeroth level dependence) that gets remarkably augmented for large rainfall zones. Our analysis further indicates that for low fluctuations in temperature (true on the bulk data), EPG level saturates beyond a critical value of the rainfall, a threshold that is expected to indicate the onset of the nonlinear regime. The probability density functions (PDFs) of the EPG data show oscillatory behavior in the large rainfall regime (greater than 500 mm), the frequency of oscillation, once again, being determined by the ambient wetness (rainfall, and humidity). Data recorded over three pilot projects spanning three measures of rainfall and humidity bear testimony to the universality of this statistical argument. © 2013 Chattopadhyay and Bandyopadhyay.

A survey based analysis of IT adoption and 3PLs' performance

Purpose: In today's competitive scenario, effective supply chain management is increasingly dependent on third-party logistics (3PL) companies' capabilities and performance. The dissemination of information technology (IT) has contributed to change the supply chain role of 3PL companies and IT is considered an important element influencing the performance of modern logistics companies. Therefore, the purpose of this paper is to explore the relationship between IT and 3PLs' performance, assuming that logistics capabilities play a mediating role in this relationship. Design/methodology/approach: Empirical evidence based on a questionnaire survey conducted on a sample of logistics service companies operating in the Italian market was used to test a conceptual resource-based view (RBV) framework linking IT adoption, logistics capabilities and firm performance. Factor analysis and ordinary least square (OLS) regression analysis have been used to test hypotheses. The focus of the paper is multidisciplinary in nature; management of information systems, strategy, logistics and supply chain management approaches have been combined in the analysis. Findings: The results indicate strong relationships among data gathering technologies, transactional capabilities and firm performance, in terms of both efficiency and effectiveness. Moreover, a positive correlation between enterprise information technologies and 3PL financial performance has been found. Originality/value: The paper successfully uses the concept of logistics capabilities as mediating factor between IT adoption and firm performance. Objective measures have been proposed for IT adoption and logistics capabilities. Direct and indirect relationships among variables have been successfully tested. © Emerald Group Publishing Limited.

Fatty acid composition, antioxidants and lipid oxidation in chicken breasts from different production regimes

Chicken breast from nine products and from the following production regimes: conventional (chilled and frozen), organic and free range, were analysed for fatty acid composition of total lipids, preventative and chain breaking antioxidant contents and lipid oxidation during 5 days of sub-ambient storage following purchase. Total lipids were extracted with an optimal amount of a cold chloroform methanol solvent. Lipid compositions varied, but there were differences between conventional and organic products in their contents of total polyunsaturated fatty acids and n-3 and n-6 fatty acids and n-6:n-3 ratio. Of the antioxidants, a-tocopherol content was inversely correlated with lipid oxidation. The antioxidant enzyme activities of catalase, glutathione peroxidase and glutathione reductase varied between products. Modelling with partial least squares regression showed no overall relationship between total antioxidants and lipid data, but certain individual antioxidants showed a relationship with specific lipid fractions.

Relationships between flavour, lipid composition and antioxidants in organic, free-range and conventional chicken breasts from modelling

Consumers expect organic, free-range and corn-fed chicken to be nutritionally wholesome and have premium flavour characters. Interrelationships between flavour, fatty acids and antioxidants of retailed breasts were explored using simple correlations and chemometrics. Saturated fatty acid C16:0, and n-6 polyunsaturated C20:4 and C22:4 contents were correlated with lipid oxidation products (thiobarbituric acid reactive substances) and in partial least-squares regression (PLS1) with 32 high-resonance gas chromatography (flame ionization) flavour components (r2>0.90), and also linked (r2>0.80) to antioxidants (-tocopherol, glutathione and catalase). A further 10 high-resonance gas chromatography nitrogen phosphorus detector flavour components were correlated (r 2>0.85) with C18:3(n-3) content. Chicken character was correlated with C18:3(n-3), and C18:3(n-6) inversely with oily, off-flavour and lipid oxidation. Sweet, fruity and oily aromas were linked in PLS1 with 13 specific fatty acids (r2>0.6), and bland taste with total summed (six) fatty acid fractions (r2>0.81). Specific antioxidants were correlated with sweet, fruity and chicken aromas, and -tocopherol inversely with lipid oxidation. PLS2 confirmed relationships between fatty acid composition, antioxidants and the subsets of 32 and 10 flavour components. Clear relationships were thus observed between lipid and antioxidant compositions and flavour in chicken breast meat.

Study of thermal spin crossover in [Fe(II)(isoxazole)6](BF4)2 with Mössbauer spectroscopy

57Fe Mössbauer spectroscopy of the mononuclear [Fe(II)(isoxazole)6](BF4) 2compound has been studied to reveal the thermal spin crossover of Fe(II) between low-spin (S = 0) and high-spin (S = 2) states. A temperature-dependent spin transition curve has been constructed with the least-square fitted data obtained from the Mössbauer spectra measured at various temperatures in the 240-60K range during the cooling and heating cycle. The compound exhibits a temperature-dependent two-step spin transition phenomenon with Tsco (step 1) = 92 and Tsco (step2) = 191K. The compound has three high-spin Fe(II) sites at the highest temperature of study; among them, two have slightly different coordination environments. These two Fe(II) sites are found to undergo a spin transition, while the third Fe(II) site retains the high-spin state over the whole temperature range. Possible reasons for the formation of the two steps in the spin transition curve are discussed. The observations made from the present study are in complete agreement with those envisaged from earlier magnetic and structural studies made on [Fe(II)(isoxazole)6](BF4)2, but highlights the nature of the spin crossover mechanism.

Ethnic differences in health related quality of life for patients with type 2 diabetes

Background - The objective of this study was to investigate the association between ethnicity and health related quality of life (HRQoL) in patients with type 2 diabetes. Methods - The EuroQol EQ-5D measure was administered to 1,978 patients with type 2 diabetes in the UK Asian Diabetes Study (UKADS): 1,486 of south Asian origin (Indian, Pakistani, Bangladeshi or other south Asian) and 492 of white European origin. Multivariate regression using ordinary least square (OLS), Tobit, fractional logit and Censored Least Absolutes Deviations estimators was used to estimate the impact of ethnicity on both visual analogue scale (VAS) and utility scores for the EuroQol EQ-5D. Results - Mean EQ-5D VAS and utility scores were lower among south Asians with diabetes compared to the white European population; the unadjusted effect on the mean EQ-5D VAS score was −7.82 (Standard error [SE] = 1.06, p < 0.01) and on the EQ-5D utility score was −0.06 (SE = 0.02, p < 0.01) (OLS estimator). After controlling for socio-demographic and clinical confounders, the adjusted effect on the EQ-5D VAS score was −9.35 (SE = 2.46, p < 0.01) and on the EQ-5D utility score was 0.06 (SE = 0.04), although the latter was not statistically significant. Conclusions - There was a large and statistically significant association between south Asian ethnicity and lower EQ-5D VAS scores. In contrast, there was no significant difference in EQ-5D utility scores between the south Asian and white European sub-groups. Further research is needed to explain the differences in effects on subjective EQ-5D VAS scores and population-weighted EQ-5D utility scores in this context.

Pronounced reduction of postprandial glucagon by lixisenatide:a meta-analysis of randomized clinical trials

Glucagon-like peptide-1 (GLP-1) receptor agonists improve islet function and delay gastric emptying in patients with type 2 diabetes mellitus (T2DM). This meta-analysis aimed to investigate the effects of the once-daily prandial GLP-1 receptor agonist lixisenatide on postprandial plasma glucose (PPG), glucagon and insulin levels. Methods: Six randomized, placebo-controlled studies of lixisenatide 20μg once daily were included in this analysis: lixisenatide as monotherapy (GetGoal-Mono), as add-on to oral antidiabetic drugs (OADs; GetGoal-M, GetGoal-S) or in combination with basal insulin (GetGoal-L, GetGoal-Duo-1 and GetGoal-L-Asia). Change in 2-h PPG and glucose excursion were evaluated across six studies. Change in 2-h glucagon and postprandial insulin were evaluated across two studies. A meta-analysis was performed on least square (LS) mean estimates obtained from analysis of covariance (ANCOVA)-based linear regression. Results: Lixisenatide significantly reduced 2-h PPG from baseline (LS mean difference vs. placebo: -4.9mmol/l, p<0.001) and glucose excursion (LS mean difference vs. placebo: -4.5mmol/l, p<0.001). As measured in two studies, lixisenatide also reduced postprandial glucagon (LS mean difference vs. placebo: -19.0ng/l, p<0.001) and insulin (LS mean difference vs. placebo: -64.8 pmol/l, p<0.001). There was a stronger correlation between 2-h postprandial glucagon and 2-h PPG with lixisenatide than with placebo. Conclusions: Lixisenatide significantly reduced 2-h PPG and glucose excursion together with a marked reduction in postprandial glucagon and insulin; thus, lixisenatide appears to have biological effects on blood glucose that are independent of increased insulin secretion. These effects may be, in part, attributed to reduced glucagon secretion. © 2014 John Wiley and Sons Ltd.

Quantitative online prediction of peptide binding to the major histocompatibility complex

With its implications for vaccine discovery, the accurate prediction of T cell epitopes is one of the key aspirations of computational vaccinology. We have developed a robust multivariate statistical method, based on partial least squares, for the quantitative prediction of peptide binding to major histocompatibility complexes (MHC), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available via a World Wide Web server. We call this server MHCPred. Access to the server is freely available from the URL: http://www.jenner.ac.uk/MHCPred. We have exemplified our method with a model for peptides binding to the common human MHC molecule HLA-B*3501.