Brand equity, brand loyalty and consumer satisfaction

This study aims to investigate the mediating effects of consumer satisfaction on the relationship between consumer-based brand equity and brand loyalty in the hotel and restaurant industry. Based on a sample of 378 customers and using structural equation modelling approach, the five dimensions of brand equity—physical quality, staff behaviour, ideal self-congruence, brand identification and lifestyle-congruence—are found to have positive effects on consumer satisfaction. The findings of the study suggest that consumer satisfaction partially mediates the effects of staff behaviour, ideal self-congruence and brand identification on brand loyalty. The effects of physical quality and lifestyle-congruence on brand loyalty are fully mediated by consumer satisfaction.

Exploring the impact of social axioms on firm reputation: a stakeholder perspective

This study proposes a model of how deeply held beliefs, known as ‘social axioms, moderate the interaction between reputation, its causes and consequences with stakeholders. It contributes to the stakeholder relational field of reputation theory by explaining why the same organizational stimuli lead to different individual stakeholder responses. The study provides a shift in reputation research from organizational-level stimuli as the root causes of stakeholder responses to exploring the interaction between individual beliefs and organizational stimuli in determining reputational consequences. Building on a conceptual model that incorporates product/service quality and social responsibility as key reputational dimensions, the authors test empirically for moderating influences, in the form of social axioms, between reputation-related antecedents and consequences, using component-based structural equation modelling (n = 204). In several model paths, significant differences are found between responses of individuals identified as either high or low on social cynicism, fate control and religiosity. The results suggest that stakeholder responses to reputation-related stimuli can be systematically predicted as a function of the interactions between the deeply held beliefs of individuals and these stimuli. The authors offer recommendations on how strategic reputation management can be approached within and across stakeholder groups at a time when firms grapple with effective management of diverse stakeholder expectations.

Unpicking antecedents of CRM adoption: a two-stage model

Most CRM work focuses on consumer applications. This paper addresses the operational adoption issues facing the organisation deploying CRM practices. There are a plethora of challenges facing organisations when adopting CRM. Previous research is limited to either examining the CRM adoption process at an individual/employees level or an organisational level. Hence, in this paper the myriad of organisational, marketing and technical antecedents that seem to impinge upon employee perceptions and organisational implementation of CRM are structured in a two-stage model. Using a stratified sample of ten organisations across four sectors, seven hypotheses are tested on data collected from 301 practitioners. A two-stage model is analysed using structural equation modelling. Findings reveal that CRM implementation relates to employee perceptions of CRM. This paper deepens our understanding of organisational practices to adopt CRM, so as an organisation properly profits from the expected benefits of CRM.

Entrepreneurial ecosystems in cities: establishing the framework conditions

This study focuses on regional entrepreneurial ecosystems and offers a complex model of start-ups, Regional Entrepreneurship and Development Index (REDI) and six domains of the entrepreneurial ecosystem (culture, formal institutions, infrastructure and amenities, IT, Melting Pot and demand). Altogether they capture the contextual features of socioeconomic, institutional and information environment in cities. To explain variations in entrepreneurship in a cross-section of 70 European cities, we utilize exploratory factor analysis and structural equation modelling for regional systems of entrepreneurship using individual perception surveys by Eurostat and the REDI. This study supports policymakers and scholars in development of new policies conducive to regional systems of innovation and entrepreneurship and serves as a basis for future research on urban entrepreneurial ecosystems.

Environmental factors and features that influence visual search in a 3D WIMP interface

The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth. Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.

Relational architecture and relational capability: organisational levers to support strategic supplier relationships

The resource based view of strategy suggests that competitiveness in part derives from a firms ability to collaborate with a subset of its supply network to co-create highly valued products and services. This relational capability relies on a foundational intra and inter-organisational architecture, the manifestation of strategic, people, and process decisions facilitating the interface between the firm and its strategic suppliers. Using covariance-based structural equation modelling we examine the relationships between internal and external features of relational architecture, and their relationship with relational capability and relational quality. This is undertaken on data collected by mail survey. We find significant relationships between both internal and external relational architecture and relational capability and between relational capability and relational quality. Novel constructs for internal and external elements of relational architecture are specified to demonstrate their positive influence on relational capability and relationship quality.

Design and analysis of climate model experiments for the efficient estimation of anthropogenic signals

Presented herein is an experimental design that allows the effects of several radiative forcing factors on climate to be estimated as precisely as possible from a limited suite of atmosphere-only general circulation model (GCM) integrations. The forcings include the combined effect of observed changes in sea surface temperatures, sea ice extent, stratospheric (volcanic) aerosols, and solar output, plus the individual effects of several anthropogenic forcings. A single linear statistical model is used to estimate the forcing effects, each of which is represented by its global mean radiative forcing. The strong colinearity in time between the various anthropogenic forcings provides a technical problem that is overcome through the design of the experiment. This design uses every combination of anthropogenic forcing rather than having a few highly replicated ensembles, which is more commonly used in climate studies. Not only is this design highly efficient for a given number of integrations, but it also allows the estimation of (nonadditive) interactions between pairs of anthropogenic forcings. The simulated land surface air temperature changes since 1871 have been analyzed. The changes in natural and oceanic forcing, which itself contains some forcing from anthropogenic and natural influences, have the most influence. For the global mean, increasing greenhouse gases and the indirect aerosol effect had the largest anthropogenic effects. It was also found that an interaction between these two anthropogenic effects in the atmosphere-only GCM exists. This interaction is similar in magnitude to the individual effects of changing tropospheric and stratospheric ozone concentrations or to the direct (sulfate) aerosol effect. Various diagnostics are used to evaluate the fit of the statistical model. For the global mean, this shows that the land temperature response is proportional to the global mean radiative forcing, reinforcing the use of radiative forcing as a measure of climate change. The diagnostic tests also show that the linear model was suitable for analyses of land surface air temperature at each GCM grid point. Therefore, the linear model provides precise estimates of the space time signals for all forcing factors under consideration. For simulated 50-hPa temperatures, results show that tropospheric ozone increases have contributed to stratospheric cooling over the twentieth century almost as much as changes in well-mixed greenhouse gases.

Robust nonlinear model identification methods using forward regression

In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on either experimental design criteria that optimizes model adequacy, or the predicted residual sums of squares (PRESS) statistic that optimizes model generalization capability, respectively. Three robust identification algorithms are introduced, i.e., combined A- and D-optimality with regularized orthogonal least squares algorithm, respectively; and combined PRESS statistic with regularized orthogonal least squares algorithm. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalization scheme in orthogonal least squares or regularized orthogonal least squares has been extended such that the new algorithms are computationally efficient. Numerical examples are included to demonstrate effectiveness of the algorithms.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

The impact of maternal control on children’s anxious cognitions, behaviours and affect: an experimental study

Controlling parenting is associated with child anxiety however the direction of effects remains unclear. The present study implemented a Latin-square experimental design to assess the impact of parental control on children’s anxious affect, cognitions and behaviour. A non-clinical sample of 24 mothers of children aged 4-5 years were trained to engage in (a) controlling and (b) autonomy-granting behaviours in interaction with their child during the preparation of a speech. When mothers engaged in controlling parenting behaviours, children made more negative predictions about their performance prior to delivering their speech and reported feeling less happy about the task, and this was moderated by child trait anxiety. In addition, children with higher trait anxiety displayed a significant increase in observed child anxiety in the controlling condition. The pattern of results was maintained when differences in mothers’ levels of negativity and habitual levels of control were accounted for. These findings are consistent with theories that suggest that controlling parenting is a risk factor in the development of childhood anxiety.

An experimental manipulation of responsibility in children: a test of the inflated responsibility model of obsessive-compulsive disorder

The objective of this study was to investigate whether Salkovskis (1985) inflated responsibility model of obsessive-compulsive disorder (OCD) applied to children. In an experimental design, 81 children aged 9– 12 years were randomly allocated to three conditions: an inflated responsibility group, a moderate responsibility group, and a reduced responsibility group. In all groups children were asked to sort sweets according to whether or not they contained nuts. At baseline the groups did not differ on children’s self reported anxiety, depression, obsessive-compulsive symptoms or on inflated responsibility beliefs. The experimental manipulation successfully changed children’s perceptions of responsibility. During the sorting task time taken to complete the task, checking behaviours, hesitations, and anxiety were recorded. There was a significant effect of responsibility level on the behavioural variables of time taken, hesitations and check; as perceived responsibility increased children took longer to complete the task and checked and hesitated more often. There was no between-group difference in children’s self reported state anxiety. The results offer preliminary support for the link between inflated responsibility and increased checking behaviours in children and add to the small but growing literature suggesting that cognitive models of OCD may apply to children.

HR attributions and the dual commitment of outsourced IT workers

Purpose – Outsourced information technology (IT) workers establish two different employment relationships: one with the outsourcing company that hires them and another with the client organization where they work daily. The attitudes that an employee has towards both organisations may be influenced by the interpretations or attributions that employees make about the reasons behind the human resource (HR) management practices implemented by the outsourcing company. This paper aims to propose that commitment‐focused HR attributions are positively and control‐focused HR attributions are negatively related to the affective commitment to the client organization, through the affective commitment to the outsourcing company. Design/methodology/approach – These hypotheses were tested with a sample of 158 highly skilled outsourced employees from the IT sector. Data were analyzed with structural equation modeling (SEM). Findings – The paper's hypotheses were supported. It can conclude that, if an employee interprets the HR practices as part of a commitment‐focused strategy of the outsourcing company, it has clear attitudinal benefits. The study found that the relationship between HR attributions and the commitment to the client organization is mediated by the commitment to the outsourcing company. Practical implications – These findings hint at the critical role of outsourcing companies in managing the careers of these highly marketable employees. Originality/value – This paper is the first to apply the concept of HR attributions to contingent employment literature in general and to outsourced IT workers in particular.

Regulation of early steps of GPVI signal transduction by phosphatases: a systems biology approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.