Response-based segmentation using Finite Mixture Partial Least Squares: theoretical foundations and an application to American Customer Satisfaction Index Data

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

Job satisfaction and teamwork:The role of supervisor support

The link between teamwork and job satisfaction was investigated in a sample of 48 manufacturing companies comprising 4708 employees. Two separate research questions were addressed. First, it was proposed that supervisor support would be a weaker source of job satisfaction in companies with higher levels of teamworking. Multilevel analysis indicated that the extent of teamwork at the company level of analysis moderated the relationship between individual perceptions of supervisor support and job satisfaction. Second, it was proposed that the extent of teamwork would be positively related to perceptions of job autonomy but negatively related to perceptions of supervisor support. Further, it was proposed that the link between teamwork and job autonomy would be explained by job enrichment practices associated with teamwork. Analyses of aggregated company data supported these propositions and provided evidence for a complex mediational path between teamwork and job satisfaction. Implications for implementing teamwork in organizations are discussed. Copyright © 2001 John Wiley & Sons, Ltd.

Effect of mobility on violence in a bi-communal population

We develop a multi-agent based model to simulate a population which comprises of two ethnic groups and a peacekeeping force. We investigate the effects of different strategies for civilian movement to the resulting violence in this bi-communal population. Specifically, we compare and contrast random and race-based migration strategies. Race-based migration leads the formation of clusters. Previous work in this area has shown that same-race clustering instigates violent behavior in otherwise passive segments of the population. Our findings confirm this. Furthermore, we show that in settings where only one of the two races adopts race-based migration it is a winning strategy especially in violently predisposed populations. On the other hand, in relatively peaceful settings clustering is a restricting factor which causes the race that adopts it to drift into annihilation. Finally, we show that when race-based migration is adopted as a strategy by both ethnic groups it results in peaceful co-existence even in the most violently predisposed populations.

Environmental and nature conservation : a facet study of concern for the quality of the natural environment

A multi-variate descriptive model of environmental and nature conservation attitudes and values is proposed and empirically supported. A mapping sentence is developed out of analysis of data from a series of Repertory Grid interviews addressing conservation employees' attitudes towards their profession's activities. The research is carried out within the meta-theoretical framework of Facet Theory. A mapping sentence is developed consisting of 9 facets. From the mapping sentence 3 questionnaires were constructed viewing the selective orientations towards environmental concern. A mapping sentence and facet model is developed for each study. Once the internal structure of this model had been established using Similarity Structure Analysis, the elements of the facets are subjected to Partial Order Scalogram Analysis with base coordinates. A questionnaire was statistically analysed to assess the relationship between facet elements and 4 measures of attitudes towards, and involvement with, conservation. This enabled the comparison of the relative strengths of attitudes associated with each facet element and each measure of conservation attitude. In general, the relationship between the social value of conservation and involvement pledges to conservation were monotonic; perceived importance of a conservation issue appearing predictive of personal involvement. Furthermore, the elements of the life area and scale facets were differentially related to attitude measures. The multi-variate descriptive model of environmental conservation values and attitudes is discussed in relation to its implications for psychological research into environmental concern and for environmental and nature conservation.

Ranking efficient decision-making units in data envelopment analysis using fuzzy concept

This paper introduces a new mathematical method for improving the discrimination power of data envelopment analysis and to completely rank the efficient decision-making units (DMUs). Fuzzy concept is utilised. For this purpose, first all DMUs are evaluated with the CCR model. Thereafter, the resulted weights for each output are considered as fuzzy sets and are then converted to fuzzy numbers. The introduced model is a multi-objective linear model, endpoints of which are the highest and lowest of the weighted values. An added advantage of the model is its ability to handle the infeasibility situation sometimes faced by previously introduced models.

The effect of social influence and curfews on civil violence

We investigate the policies of (1) restricting social influence and (2) imposing curfews upon interacting citizens in a community. We compare and contrast their effects on the social order and the emerging levels of civil violence. Influence models have been used in the past in the context of decision making in a variety of application domains. The policy of curfews has been utilised with the aim of curbing social violence but little research has been done on its effectiveness. We develop a multi-agent-based model that is used to simulate a community of citizens and the police force that guards it. We find that restricting social influence does indeed pacify rebellious societies, but has the opposite effect on peaceful ones. On the other hand, our simple model indicates that restricting mobility through curfews has a pacifying effect across all types of society.

The effects of perceived business uncertainty, external consultants and risk management on organisational outcomes

Purpose: The purpose of this paper is to investigate the relations between perceived business uncertainty (PBU), use of external risk management (RM) consultants, formalisation of RM, magnitude of RM methods and perceived organisational outcomes. Design/methodology/approach: This paper is based on a questionnaire survey of members of the Chartered Institute of Management Accountants in the UK. Using AMOS 17.0, the paper tests the strength of the direct and indirect effects among the variables and explores the fit of the overall path model. Findings: The results indicate significant and positive associations exist between the extent of PBU and the level ofRMformalisation, as well as between the level ofRMformalisation and the magnitude of RMmethods adopted. The use of externalRMconsultants is also found to have a significant and positive impact on the magnitude of RM methods adopted. Finally, both the extent of RM formalisation and the magnitude of RM methods adopted are seen to be significantly associated with overall improvement in organisational outcomes. Research limitations/implications: The study uses perceptual measures of the level of business uncertainty, usage of RM and organisational outcomes. Further, the respondents are members of a management accounting professional body and the views of other managers, such as risk managers, who are also important to the governance process are not incorporated. Originality/value: This study provides empirical evidence on the impact ofRMdesign and usage on improvements in organisational outcomes. It contributes to the RM literature where empirical research is needed in order to be comparable with the traditional management control system literature.

Psychosoziale Merkmale der Arbeit, Überforderungserleben und Depressivität

Die vorliegende Studie untersuchte die im Job-Demand-Control-Support-Modell und Effort-Reward-Imbalance-Modell beschriebenen Tätigkeitsmerkmale in Bezug auf Depressivität in einer Stichprobe von 265 Erwerbstätigen. Anhand konfirmatorischer Faktorenanalysen wurden Gemeinsamkeiten und Unterschiede beider Modelle geprüft. Anschließend wurde die Bedeutung der nachweisbaren Tätigkeitsmerkmale für die Vorhersage von Depressivität getestet und untersucht, inwieweit die Effekte durch Überforderungserleben mediiert werden. Die Analysen zeigten, dass die Modelle sowohl gemeinsame (Arbeitsintensität bzw. berufliche Anforderungen) als auch distinkte Arbeitsmerkmale (Tätigkeitsspielraum, Arbeitsplatzsicherheit, beruflicher Status, soziale Anerkennung) erfassen. Hohe Arbeitsintensität, geringe Arbeitsplatzsicherheit und fehlende soziale Anerkennung standen in signifikantem Zusammenhang mit Depressivität. Anders als erwartet war der berufliche Status positiv mit Depressivität assoziiert, während für den Tätigkeitsspielraum keine signifikanten Effekte nachweisbar waren. Das Pfadmodell bestätigte sowohl direkte als auch durch Überforderungserleben vermittelte Zusammenhänge zwischen den Tätigkeitsmerkmalen und Depressivität (39 % Varianzaufklärung). Die Ergebnisse bieten eine Grundlage für die Identifizierung potenzieller Risikofaktoren für das Auftreten depressiver Symptome am Arbeitsplatz. This study examined the job characteristics in the Job-Demand-Control-Support Model and in the Effort-Reward Imbalance Model with regard to depression in a sample of 265 employees. First, we tested by means of confirmatory factor analysis similarities and differences of the two models. Secondly, job characteristics were introduced as predictors in a path model to test their relation with depression. Furthermore, we examined whether the associations were mediated by the experience of excessive demands. Our analyses showed the demand/effort component to be one common factor, while decision latitude and reward (subdivided into the three facets of job security, social recognition, and status-related reward) remained distinctive components. Employees with high job demands/effort, low job security, low social recognition, but high status-related rewards reported higher depression scores. Unexpectedly, status-related rewards were positively associated with depression, while we found no significant effects for decision latitude. The path models confirmed direct as well as mediation effects (through experienced excessive demands) between job characteristics and depression (39 % explained variance in depression). Our results could be useful to identify possible job-related risk factors for depression.

Looking under the bonnet:factors affecting student adoption of e-learning systems in Jordan

The primary questions addressed in this paper are the following: what are the factors that affect students’ adoption of an e-learning system and what are the relationships among these factors? This paper investigates and identifies some of the major factors affecting students’ adoption of an e-learning system in a university in Jordan. E-learning adoption is approached from the information systems acceptance point of view. This suggests that a prior condition for learning effectively using e-learning systems is that students must actually use them. Thus, a greater knowledge of the factors that affect IT adoption and their interrelationships is a pre-cursor to a better understanding of student acceptance of e-learning systems. In turn, this will help and guide those who develop, implement, and deliver e-learning systems. In this study, an extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The TAM was populated using data gathered from a survey of 486 undergraduate students using the Moodle based e-learning system at the Arab Open University. The model was estimated using Structural Equation Modelling (SEM). A path model was developed to analyze the relationships between the factors to explain students’ adoption of the e-learning system. Whilst findings support existing literature about prior experience affecting perceptions, they also point to surprising group effects, which may merit future exploration.

A spatiotemporal Data Envelopment Analysis (S-T DEA) approach:the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.

Blurred edges look faint, and faint edges look sharp:The effect of a gradient threshold in a multi-scale edge coding model

A multi-scale model of edge coding based on normalized Gaussian derivative filters successfully predicts perceived scale (blur) for a wide variety of edge profiles [Georgeson, M. A., May, K. A., Freeman, T. C. A., & Hesse, G. S. (in press). From filters to features: Scale-space analysis of edge and blur coding in human vision. Journal of Vision]. Our model spatially differentiates the luminance profile, half-wave rectifies the 1st derivative, and then differentiates twice more, to give the 3rd derivative of all regions with a positive gradient. This process is implemented by a set of Gaussian derivative filters with a range of scales. Peaks in the inverted normalized 3rd derivative across space and scale indicate the positions and scales of the edges. The edge contrast can be estimated from the height of the peak. The model provides a veridical estimate of the scale and contrast of edges that have a Gaussian integral profile. Therefore, since scale and contrast are independent stimulus parameters, the model predicts that the perceived value of either of these parameters should be unaffected by changes in the other. This prediction was found to be incorrect: reducing the contrast of an edge made it look sharper, and increasing its scale led to a decrease in the perceived contrast. Our model can account for these effects when the simple half-wave rectifier after the 1st derivative is replaced by a smoothed threshold function described by two parameters. For each subject, one pair of parameters provided a satisfactory fit to the data from all the experiments presented here and in the accompanying paper [May, K. A. & Georgeson, M. A. (2007). Added luminance ramp alters perceived edge blur and contrast: A critical test for derivative-based models of edge coding. Vision Research, 47, 1721-1731]. Thus, when we allow for the visual system's insensitivity to very shallow luminance gradients, our multi-scale model can be extended to edge coding over a wide range of contrasts and blurs. © 2007 Elsevier Ltd. All rights reserved.

Response normalization and blur adaptation:data and multi-scale model

Adapting to blurred or sharpened images alters perceived blur of a focused image (M. A. Webster, M. A. Georgeson, & S. M. Webster, 2002). We asked whether blur adaptation results in (a) renormalization of perceived focus or (b) a repulsion aftereffect. Images were checkerboards or 2-D Gaussian noise, whose amplitude spectra had (log-log) slopes from -2 (strongly blurred) to 0 (strongly sharpened). Observers adjusted the spectral slope of a comparison image to match different test slopes after adaptation to blurred or sharpened images. Results did not show repulsion effects but were consistent with some renormalization. Test blur levels at and near a blurred or sharpened adaptation level were matched by more focused slopes (closer to 1/f) but with little or no change in appearance after adaptation to focused (1/f) images. A model of contrast adaptation and blur coding by multiple-scale spatial filters predicts these blur aftereffects and those of Webster et al. (2002). A key proposal is that observers are pre-adapted to natural spectra, and blurred or sharpened spectra induce changes in the state of adaptation. The model illustrates how norms might be encoded and recalibrated in the visual system even when they are represented only implicitly by the distribution of responses across multiple channels.

From practice to field:a multi-level model of practice-driven institutional change

This article develops a model of practice-driven institutional change - or change that originates in the everyday work of individuals but results in a shift in field-level logic. In demonstrating how improvisations at work can generate institutional change, we attend to the earliest moments of change, which extant research has neglected; and we contrast existing accounts that focus on active entrepreneurship and the contested nature of change. We outline the specific mechanisms by which change emerges from everyday work, becomes justified, and diffuses within an organization and field, as well as precipitating and enabling dynamics that trigger and condition these mechanisms. © Academy of Management Journal.