The role of the sales employee in securing customer satisfaction

Purpose: Previous research has emphasized the pivotal role that salespeople play in customer satisfaction. In this regard, the relationship between salespeople's attitudes, skills, and characteristics, and customer satisfaction remains an area of interest. The paper aims to make three contributions: first, it seeks to examine the impact of salespeople's satisfaction, adaptive selling, and dominance on customer satisfaction. Second, this research aims to use dyadic data, which is a better test of the relationships between constructs since it avoids common method variance. Finally, in contrast to previous research, it aims to test all of the customers of salespeople rather than customers selected by salespeople. Design/methodology/approach: The study employs multilevel analysis to examine the relationship between salespeople's satisfaction with the firm on customer satisfaction, using a dyadic, matched business-to-business sample of a large European financial service provider that comprises 188 customers and 18 employees. Findings: The paper finds that customers' evaluation of service quality, product quality, and value influence customer satisfaction. The analysis at the selling firm's employee level shows that adaptive selling and employee satisfaction positively impact customer satisfaction, while dominance is negatively related to customer satisfaction. Practical implications: Research shows that customer-focus is a key driver in the success of service companies. Customer satisfaction is regarded as a prerequisite for establishing long-term, profitable relations between company and customer, and customer contact employees are key to nurturing this relationship. The role of salespeople's attitudes, skills, and characteristics in the customer satisfaction process are highlighted in this paper. Originality/value: The use of dyadic, multilevel studies to assess the nature of the relationship between employees and customers is, to date, surprisingly limited. The paper examines the link between employee attitudes, skills, and characteristics, and customer satisfaction in a business-to-business setting in the financial service sector, differentiating between customer- and employee-level drivers of business customer satisfaction.

Expatriate-local interactions:an investigation in China

Purpose: This study aims to build on recent research, by investigating and examining how likely it is that Chinese locals (i.e. host country nationals (HCNs)) would offer support to expatriates from India and the USA. Design/methodology/approach: Data were gathered from 222 participants in Chinese organizations, asking them to respond to questions about their willingness to offer support to expatriates. Findings: As predicted, perceived values similarity was significantly related to higher dogmatism, which had a significant positive relationship with ethnocentrism. Further, ethnocentrism had a significant negative relationship with willingness to offer support. Research limitations/implications: All data were collected from the participants at one point in time, so the study's results are subject to common method bias. Also, it only included India and the USA, as the two countries of origin of the expatriates. Practical implications: Given HCNs do not automatically offer support to all expatriates, organizations might consider sending expatriates who are culturally similar to HCNs, as they are more likely to receive support, which will help their adjustment and thus organizational effectiveness. Originality/value: This study adds to the small, but growing, number of empirical investigations of HCN willingness to support expatriates. © Emerald Group Publishing Limited.

Optimising Pichia pastoris induction

A common method for inducing the production of recombinant proteins in Pichia pastoris is through the use of methanol. However, the by-products of methanol metabolism are toxic to yeast cells and therefore its addition to recombinant cultures must be controlled and monitored throughout the process in order to maximise recombinant protein yields. Described here are online and off-line methods to monitor and control methanol addition to bench-top-scale bioreactors. © 2012 Springer Science+business Media, LLC.

Statnote 11: the two-factor analysis of variance

Experiments combining different groups or factors are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the number of replications required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the degrees of freedom (DF) of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than simply the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for each error term of the ANOVA. Finally, in a factorial experiment, it is important to define the design of the experiment in detail because this determines the appropriate type of ANOVA. We will discuss some of the common variations of factorial ANOVA in future statnotes. If there is doubt about which ANOVA to use, the researcher should seek advice from a statistician with experience of research in applied microbiology.

The use of analysis of variance (ANOVA) in applied microbiology

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the number of replications required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the DF of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for each error term of the ANOVA. Finally, it is important to consider the design of the experiment because this determines the appropriate ANOVA to use. Some of the most common experimental designs used in the biosciences and their relevant ANOVAs are discussed by. If there is doubt about which ANOVA to use, the researcher should seek advice from a statistician with experience of research in applied microbiology.

Common variance in amplitude envelope perception tasks and their impact on phoneme duration perception and reading and spelling in Finnish children with reading disabilities

Our goal was to investigate auditory and speech perception abilities of children with and without reading disability (RD) and associations between auditory, speech perception, reading, and spelling skills. Participants were 9-year-old, Finnish-speaking children with RD (N = 30) and typically reading children (N = 30). Results showed significant group differences between the groups in phoneme duration discrimination but not in perception of amplitude modulation and rise time. Correlations among rise time discrimination, phoneme duration, and spelling accuracy were found for children with RD. Those children with poor rise time discrimination were also poor in phoneme duration discrimination and in spelling. Results suggest that auditory processing abilities could, at least in some children, affect speech perception skills, which in turn would lead to phonological processing deficits and dyslexia.

An introduction to analysis of variance (ANOVA) with special reference to data from clinical experiments in optometry

This article is aimed primarily at eye care practitioners who are undertaking advanced clinical research, and who wish to apply analysis of variance (ANOVA) to their data. ANOVA is a data analysis method of great utility and flexibility. This article describes why and how ANOVA was developed, the basic logic which underlies the method and the assumptions that the method makes for it to be validly applied to data from clinical experiments in optometry. The application of the method to the analysis of a simple data set is then described. In addition, the methods available for making planned comparisons between treatment means and for making post hoc tests are evaluated. The problem of determining the number of replicates or patients required in a given experimental situation is also discussed. Copyright (C) 2000 The College of Optometrists.

The application of analysis of variance (ANOVA) to different experimental designs in optometry

Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered. © 2002 The College of Optometrists.

Statnote 23: Non-parametric analysis of variance (ANOVA)

To carry out an analysis of variance, several assumptions are made about the nature of the experimental data which have to be at least approximately true for the tests to be valid. One of the most important of these assumptions is that a measured quantity must be a parametric variable, i.e., a member of a normally distributed population. If the data are not normally distributed, then one method of approach is to transform the data to a different scale so that the new variable is more likely to be normally distributed. An alternative method, however, is to use a non-parametric analysis of variance. There are a limited number of such tests available but two useful tests are described in this Statnote, viz., the Kruskal-Wallis test and Friedmann’s analysis of variance.

The two-dose measles, mumps, and rubella (MMR) immunisation schedule: factors affecting maternal intention to vaccinate

BACKGROUND: In the light of sub-optimal uptake of the measles, mumps, and rubella (MMR) vaccination, we investigated the factors that influence the intentions of mothers to vaccinate. METHOD: A cross-sectional survey of 300 mothers in Birmingham with children approaching a routine MMR vaccination was conducted using a postal questionnaire to measure: intention to vaccinate, psychological variables, knowledge of the vaccine, and socioeconomic status. The vaccination status of the children was obtained from South Birmingham Child Health Surveillance Unit. RESULTS: The response rate was 59%. Fewer mothers approaching the second MMR vaccination (Group 2) intended to take their children for this vaccination than Group 1 (mothers approaching the first MMR vaccination) (Mann-Whitney U = 2180, P < 0.0001). Group 2 expressed more negative beliefs about the outcome of having the MMR vaccine ('vaccine outcome beliefs') (Mann-Whitney U = 2155, P < 0.0001), were more likely to believe it was 'unsafe' (chi 2 = 9.114, P = 0.004) and that it rarely protected (chi 2 = 6.882, P = 0.014) than Group 1. The commonest side-effect cited was general malaise, but 29.8% cited autism. The most trusted source of information was the general practitioner but the most common source of information on side-effects was television (34.6%). Multiple linear regression revealed that, in Group 1, only 'vaccine outcome beliefs' significantly predicted intention (77.1% of the variance). In Group 2 'vaccine outcome beliefs', attitude to the MMR vaccine, and prior MMR status all predicted intention (93% of the variance). CONCLUSION: A major reason for the low uptake of the MMR vaccination is that it is not perceived to be important for children's health, particularly the second dose. Health education from GPs is likely to have a considerable impact.

A statistical method for the identification and aggregation of regional linguistic variation

This paper introduces a method for the analysis of regional linguistic variation. The method identifies individual and common patterns of spatial clustering in a set of linguistic variables measured over a set of locations based on a combination of three statistical techniques: spatial autocorrelation, factor analysis, and cluster analysis. To demonstrate how to apply this method, it is used to analyze regional variation in the values of 40 continuously measured, high-frequency lexical alternation variables in a 26-million-word corpus of letters to the editor representing 206 cities from across the United States.

Statnote 12: the split-plot analysis of variance

In some experimental situations, the factors may not be equivalent to each other and replicates cannot be assigned at random to all treatment combinations. A common case, called a ‘split-plot design’, arises when one factor can be considered to be a major factor and the other a minor factor. Investigators need to be able to distinguish a split-plot design from a fully randomized design as it is a common mistake for researchers to analyse a split-plot design as if it were a fully randomised factorial experiment.

Statnote 13: a more complex analysis of variance incorporating a 'repeated measures' factor

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the sample size required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the degrees of freedom (DF) of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for the error term of the ANOVA testing effects of particular interest. Finally, it is important to always consider the design of the experiment because this determines the appropriate ANOVA to use. Hence, it is necessary to be able to identify the different forms of ANOVA appropriate to different experimental designs and to recognise when a design is a split-plot or incorporates a repeated measure. If there is any doubt about which ANOVA to use in a specific circumstance, the researcher should seek advice from a statistician with experience of research in applied microbiology.

Data analysis methods in optometry Part 4: an introduction to analysis of variance (ANOVA)

In any investigation in optometry involving more that two treatment or patient groups, an investigator should be using ANOVA to analyse the results assuming that the data conform reasonably well to the assumptions of the analysis. Ideally, specific null hypotheses should be built into the experiment from the start so that the treatments variation can be partitioned to test these effects directly. If 'post-hoc' tests are used, then an experimenter should examine the degree of protection offered by the test against the possibilities of making either a type 1 or a type 2 error. All experimenters should be aware of the complexity of ANOVA. The present article describes only one common form of the analysis, viz., that which applies to a single classification of the treatments in a randomised design. There are many different forms of the analysis each of which is appropriate to the analysis of a specific experimental design. The uses of some of the most common forms of ANOVA in optometry have been described in a further article. If in any doubt, an investigator should consult a statistician with experience of the analysis of experiments in optometry since once embarked upon an experiment with an unsuitable design, there may be little that a statistician can do to help.

The relationship between measurement method and corneal structure on apparent intraocular pressure in glaucoma and ocular hypertension

Purpose: To analyse the relationship between measured intraocular pressure (IOP) and central corneal thickness (CCT), corneal hysteresis (CH) and corneal resistance factor (CRF) in ocular hypertension (OHT), primary open-angle (POAG) and normal tension glaucoma (NTG) eyes using multiple tonometry devices. Methods: Right eyes of patients diagnosed with OHT (n=47), normal tension glaucoma (n=17) and POAG (n=50) were assessed, IOP was measured in random order with four devices: Goldmann applanation tonometry (GAT); Pascal(R) dynamic contour tonometer (DCT); Reichert(R) ocular response analyser (ORA); and Tono-Pen(R) XL. CCT was then measured using a hand-held ultrasonic pachymeter. CH and CRF were derived from the air pressure to corneal reflectance relationship of the ORA data. Results: Compared to the GAT, the Tonopen and ORA Goldmann equivalent (IOPg) and corneal compensated (IOPcc) measured higher IOP readings (F=19.351, p<0.001), particularly in NTG (F=12.604, p<0.001). DCT was closest to Goldmann IOP and had the lowest variance. CCT was significantly different (F=8.305, p<0.001) between the 3 conditions as was CH (F=6.854, p=0.002) and CRF (F=19.653, p<0.001). IOPcc measures were not affected by CCT. The DCT was generally not affected by corneal biomechanical factors. Conclusion: This study suggests that as the true pressure of the eye cannot be determined non-invasively, measurements from any tonometer should be interpreted with care, particularly when alterations in the corneal tissue are suspected.