How user diversity and country of origin impact the readiness to adopt E-health technologies: an intercultural comparison

In recent years, due to the demographical change and the resulting overload of healthcare systems, there has been an increasing interest focusing on the global proliferation of assistive medical technologies (=E-health) in home environments. The present study examines how users' diversity influences the readiness to adopt novel medical technologies, comparing users' attitudes in terms of perceived advantages and disadvantages in three technically and culturally different countries: Germany, Poland and Turkey. This investigation also intended to verify if acceptance of information and communication technologies is associated with the sensitive acceptance of E-health. Results revealed overall a considerably higher motivation to use medical technology compared to perceived barriers, with Polish users more willing to use E-health, higher than German or Turkish ones. Older participants showed a highly positive attitude, comparable to young and middle-aged respondents' receptiveness, differing from the latter in terms of greater appreciation of the advantage of higher independency when being supported by medical technology. With respect to gender, woman showed higher motivation to use E-health technology than men, although utilization barriers were not gendered. Following these results, an unconditional transfer of acceptance from information and communication to medical technology is not justified.     

Collective consumption: an application to the passive drinking effect

This study introduces a new collective complete demand system with individual Engel effects that is easy to estimate and permits undertaking policy analysis at the individual rather than household level. Previous estimations of collective demand were limited to single equations. The empirical application investigates the passive drinking effect, that is, whether consumption of alcohol affects the distribution of resources among household members and their level of wellbeing. The results show that a high level of alcohol consumption of one household member significantly affects the allocation of household resources and suggest thought-provoking policy implications.     

Supervisors’ power to deal with employees’ inner resignation: How perceived power of the organization and the supervisor relate to employees’ voluntary and enforced work behavior

Power is fundamental in organizations and is exerted on employees by the organization itself as well as by supervisors. In this study, I applied the slippery slope framework (SSF) and interpersonal power interaction (IPI) model to shed light on how power dynamics relate to employees’ inner resignation and contextual performance.Survey data was obtained from 1102 employees of Austrian and German organizations. In line with expectations, the results of path modeling revealed that perceived coercive power of the organization and supervisors positively relates to employees’ inner resignation. Perceived legitimate power of the organization and supervisors is positively associated with contextual performance and negatively associated with inner resignation. Finally, supervisor reward power further strengthens the beneficial relationship between legitimate organizational power and inner resignation. The results are discussed in light of self-determination theory and the effort-reward imbalance model.     

Strategie- und Organisationsentwicklung in KMUs – von der Abstraktion zur Konkretisierung

Despite the importance of strategic measures for organizational development in small and medium sized companies, it often remains quite difficult to integrate such activities. Access to consultancy and continuing education on offer in this field is being impeded by lack of resources, such as time, personnel and finance, as well as by the abstract nature of the theme itself and the lack of familiarity with this learning and counseling situation. Three fields of tension are focused on: Teaching and learning as a management of contradictions, strategy between myth and reality, and the role that tools play in working with strategies. Against the backdrop of the experiences in a project that combined elements of research, counseling and continuing education the article points out challenges for institutions promoting economic development, for entrepreneurs, and for researchers or consultants in such a context.     

Order selection in finite mixtures of linear regressions

Finite mixture models can adequately model population heterogeneity when this heterogeneity arises from a finite number of relatively homogeneous clusters. An example of such a situation is market segmentation. Order selection in mixture models, i.e. selecting the correct number of components, however, is a problem which has not been satisfactorily resolved. Existing simulation results in the literature do not completely agree with each other. Moreover, it appears that the performance of different selection methods is affected by the type of model and the parameter values. Furthermore, most existing results are based on simulations where the true generating model is identical to one of the models in the candidate set. In order to partly fill this gap we carried out a (relatively) large simulation study for finite mixture models of normal linear regressions. We included several types of model (mis)specification to study the robustness of 18 order selection methods. Furthermore, we compared the performance of these selection methods based on unpenalized and penalized estimates of the model parameters. The results indicate that order selection based on penalized estimates greatly improves the success rates of all order selection methods. The most successful methods were \(MDL2\) , \(MRC\) , \(MRC_k\) , \(ICL\) – \(BIC\) , \(ICL\) , \(CAIC\) , \(BIC\) and \(CLC\) but not one method was consistently good or best for all types of model (mis)specification.     

Generalized linear models and transformations for unreplicated factorial experiments in the presence of dispersion effects

For the analysis of replicated designs, many different methods have been suggested. These allow for the estimation of functional dependencies between mean and variance as well as possible dispersion effects within the same model framework. However, in the situation of unreplicated designs, most methods known so far rely on the assumption of constant variances, or a functional relationship between mean and variance as the only source of heteroscedasticity. In this paper, we propose two methods for dealing with unreplicated data, when dispersion effects might also be of importance. One of these is an extension of the Box–Cox-method [Box, G.E.P., Cox, D.R., 1964. An analysis of transformations. Journal of the Royal Statistical Society B 26, 211–252], the other is based on double generalized linear models. Both these methods turn out to yield approximately equivalent results in the case of comparable assumptions, whereas the double generalized linear model is the more general one and allows further extensions. If this class of models is assumed, consistency, asymptotic efficiency and normality of the resulting estimates are shown.     

Optimal two-level conjoint designs with constant attributes in the profile sets

We propose a simple strategy to construct D-, A-, G- and V-optimal two-level designs for rating-based conjoint studies with large numbers of attributes. In order to simplify the rating task, the designs hold one or more attributes at a constant level in each profile set. Our approach combines orthogonal designs and binary incomplete block designs with equal replication. The designs are variance-balanced meaning that they yield an equal amount of information on each of the part-worths.     

Maternal situations: sectarianism and civility in a divided city

This paper explores the tensions between civility and sectarianism in contemporary Belfast. Drawing on interviews with mothers engaged in raising young children in the largely working‐class and divided inner city, the paper offers a situated account of the dynamics of social reproduction and change. This is pursued through an analysis of the interplay between expectations of civility and sectarianism in three situations: walking, shopping and playing. The tensions and dilemmas of maternal action as the divided inner city is navigated indicate the gendered character of civility, an important emerging norm facilitating social change in the post‐conflict era. The situation of motherhood itself, both at the centre of ethno‐national reproduction and at the interface of public and private life, is not insignificant in routinely drawing mothers into the everyday dynamics of post‐conflict continuity and change.     

Personality, perceptions and retrenchment decisions of managers in response to decline: Evidence from a decision-making study

Drawing on the strategic leadership and leadership cognition literature, we develop a theoretical framework linking personal characteristics of strategic leaders with their perceptions of organizational decline and retrenchment activities. Our hypotheses are tested using a sample of 110 experienced MBA students in a scenario-based study. The findings of this exploratory study suggest that strategic leaders' perceptions of the severity of a firm's decline play an important role in the recommendation of extensive retrenchment activities in response to decline. However, perceptions of the severity of decline vary substantially across decision makers and are influenced by an individual's locus of strategic control, functional background and maturity. The study's findings that perceptions of decline and planned responses to decline vary substantially and predictably across individuals are discussed in light of existing theory and practice.     

Comparing Two-Stage Segmentation Methods for Choice Data with a One-Stage Latent Class Choice Analysis

Market segmentation is a key concept in marketing research. Identification of consumer segments helps in setting up and improving a marketing strategy. Hence, the need is to improve existing methods and to develop new segmentation methods. We introduce two new consumer indicators that can be used as segmentation basis in two-stage methods, the forces and the dfbetas. Both bases express a subject’s effect on the aggregate estimates of the parameters in a conditional logit model. Further, individual-level estimates, obtained by either estimating a conditional logit model for each individual separately with maximum likelihood or by hierarchical Bayes (HB) estimation of a mixed logit choice model, and the respondents’ raw choices are also used as segmentation basis. In the second stage of the methods the bases are classified into segments with cluster analysis or latent class models. All methods are applied to choice data because of the increasing popularity of choice experiments to analyze choice behavior. To verify whether two-stage segmentation methods can compete with a one-stage approach, a latent class choice model is estimated as well. A simulation study reveals the superiority of the two-stage method that clusters the HB estimates and the one-stage latent class choice model. Additionally, very good results are obtained for two-stage latent class cluster analysis of the choices as well as for the two-stage methods clustering the forces, the dfbetas and the choices.