Developing a multidimensional scale for ethical decision making

This article reports on the development of the managerial ethical profile (MEP) scale. The MEP scale is a multilevel, self-reporting scale measuring the perceived influence that different dimensions of common ethical frameworks have on managerial decision making. The MEP scale measures on eight subscales: economic egoism, reputational egoism, act utilitarianism, rule utilitarianism, self-virtue of self, virtue of others, act deontology, and rule deontology. Confirmatory factor analysis (CFA) was used to provide evidence of scale validity. Future research needs and the value of this measure for business ethics are discussed.

Learning multidimensional joint control of a robot using receding horizon locally weighted regression

In this paper we explore the ability of a recent model-based learning technique Receding Horizon Locally Weighted Regression (RH-LWR) useful for learning temporally dependent systems. In particular this paper investigates the application of RH-LWR to learn control of Multiple-input Multiple-output robot systems. RH-LWR is demonstrated through learning joint velocity and position control of a three Degree of Freedom (DoF) rigid body robot.

The Multidimensional Loss Scale : validating a cross cultural instrument for measuring loss in Burmese refugees

The Multidimensional Loss Scale: Initial Development and Psychometric Evaluation The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to measure loss in refugee populations. Researchers developed initial items of the Multidimensional Loss Scale to assess Experience of Loss Events and Loss Distress in a culturally sensitive manner across multiple domains (social, material, intra-personal and cultural). A sample of 70 recently settled Burmese adult refugees completed a battery of questionnaires, including new scale items. Analyses explored the scale’s factor structure, internal consistency, convergent validity and divergent validity. Principal Axis Factoring supported a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Chronbach’s Alphas indicated satisfactory internal consistency for Experience of Loss Events (.85) and Loss Distress (.92). Convergent and divergent validity of Loss Distress were supported by moderate correlations with interpersonal grief and trauma symptoms and weak correlations with depression and anxiety. The new scale was well received by people from refugee backgrounds and shows promise for application in future research and practice

An examination of the factorial invariance and refinement of the multidimensional school anger inventory for five Pacific Rim countries

The validity of the Multidimensional School Anger Inventory (MSAI) was examined with adolescents from 5 Pacific Rim countries (N ¼ 3,181 adolescents; age, M ¼ 14.8 years; 52% females). Confirmatory factor analyses examined configural invariance for the MSAI’s anger experience, hostility, destructive expression, and anger coping subscales. The model did not converge for Peruvian students. Using the top 4 loaded items for anger experience, hostility, and destructive expression configural invariance and partial metric and scalar invariances were found. Latent means analysis compared mean responses on each subscale to the U.S. sample. Students from other countries showed higher mean responses on the anger experience subscale (ds ¼ .37–.73). Australian (d ¼ .40) and Japanese students (d ¼ .21) had significantly higher mean hostility subscale scores. Australian students had higher mean scores on the destructive expression subscale (d ¼ .30), whereas Japanese students had lower mean scores (d ¼ 2.17). The largest latent mean gender differences (females lower than males) were for destructive expression among Australian (d ¼ 2.67), Guatemalan (d ¼ 2.42), and U.S. (d ¼ 2.66) students. This study supported an abbreviated, 12-item MSAI with partial invariance. Implications for the use of the MSAI in comparative research are discussed.

A multidimensional model of client success when engaging external consultants

Too often the relationship between client and external consultants is perceived as one of protagonist versus antogonist. Stories on dramatic, failed consultancies abound, as do related anecdotal quips. A contributing factor to many "apparently" failed consultancies is a poor appreciation by both the client and consultant of the client's true goals for the project and how to assess progress toward these goals. This paper presents and analyses a measurement model for assessing client success when engaging an external consultant. Three main areas of assessment are identified: (1) the consultant;s recommendations, (2) client learning, and (3) consultant performance. Engagement success is emperically measured along these dimensions through a series of case studies and a subsequent survey of clients and consultants involved in 85 computer-based information system selection projects. Validation fo the model constructs suggests the existence of six distinct and individually important dimensions of engagement success. both clients and consultants are encouraged to attend to these dimensions in pre-engagement proposal and selection processes, and post-engagement evaluation of outcomes.

Developing a multidimensional scale of customer-oriented deviance (COD)

Although frontline employees' bending of organizational rules and norms for customers is an important phenomenon, marketing scholars to date only broadly describe over-servicing behaviors and provide little distinction among deviant behavioral concepts. Drawing on research on pro-social and pro-customer behaviors and on studies of positive deviance, this paper develops and validates a multi-faceted, multi-dimensional construct term customer-oriented deviance. Results from two samples totaling 616 frontline employees (FLEs) in the retail and hospitality industries demonstrate that customer-oriented deviance is a four-dimensional construct with sound psychometric properties. Evidence from a test of a theoretical model of key antecedents establishes nomological validity with empathy/perspective-taking, risk-taking propensity, role conflict, and job autonomy as key predictors. Results show that the dimensions of customer-oriented deviance are distinct and have significant implications for theory and practice.

Property-performance control of multidimensional, hierarchical, single-crystalline ZnO nanoarchitectures

Diverse morphologies of multidimensional hierarchical single-crystalline ZnO nanoarchitectures including nanoflowers, nanobelts, and nanowires are obtained by use of a simple thermal evaporation and vapour-phase transport deposition technique by placing Au-coated silicon substrates in different positions inside a furnace at process temperatures as low as 550 °C. The nucleation and growth of ZnO nanostructures are governed by the vapour–solid mechanism, as opposed to the commonly reported vapour–liquid–solid mechanism, when gold is used in the process. The morphological, structural, compositional and optical properties of the synthesized ZnO nanostructures can be effectively tailored by means of the experimental parameters, and these properties are closely related to the local growth temperature and gas-phase supersaturation at the sample position. In particular, room-temperature photoluminescence measurements reveal an intense near-band-edge ultraviolet emission at about 386 nm for nanobelts and nanoflowers, which suggests that these nanostructures are of sufficient quality for applications in, for example, optoelectronic devices.

Public relations and engagement : theoretical imperatives of a multidimensional concept

Engagement has emerged as important concept in public relations, as stakeholders challenge the discourse of organizational primacy and organizations prioritize the need for authentic stakeholder involvement. As a multidimensional concept, engagement offers a foundation for building organizational relationships, and provides a means to facilitate community–organization interaction. This special issue on engagement and public relations presents a body of work that both explicates and expands the theoretical foundations of engagement, and contributes to scholarly understanding of its contexts, processes, and outcomes.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

Multidimensional classroom support to inclusive education teachers in Beijing, China

Classroom support plays a salient role in successful inclusive education, hence it has been widely debated in the literature. Much extant work has only focused on a particular aspect of classroom support. A comprehensive, systematic discussion of classroom support is sporadic in the literature. Relevant research concerning the Chinese context is even more limited. To address this gap, our study developed and validated a multidimensional classroom support model conducive to teachers’ inclusive education practices. Data were drawn from our large-scale survey with inclusive education teachers in Beijing. Further analyses were conducted to compare different dimensions within the classroom support model. Drawing insights from the results, we provide some recommendations for practice and research.

Is the mental wellbeing of young Australians best represented by a single, multidimensional or bifactor model?

Internationally there is a growing interest in the mental wellbeing of young people. However, it is unclear whether mental wellbeing is best conceptualized as a general wellbeing factor or a multidimensional construct. This paper investigated whether mental wellbeing, measured by the Mental Health Continuum-Short Form (MHC-SF), is best represented by: (1) a single-factor general model; (2) a three-factor multidimensional model or (3) a combination of both (bifactor model). 2,220 young Australians aged between 16 and 25 years completed an online survey including the MHC-SF and a range of other wellbeing and mental ill-health measures. Exploratory factor analysis supported a bifactor solution, comprised of a general wellbeing factor, and specific group factors of psychological, social and emotional wellbeing. Confirmatory factor analysis indicated that the bifactor model had a better fit than competing single and three-factor models. The MHC-SF total score was more strongly associated with other wellbeing and mental ill-health measures than the social, emotional or psychological subscale scores. Findings indicate that the mental wellbeing of young people is best conceptualized as an overarching latent construct (general wellbeing) to which emotional, social and psychological domains contribute. The MHC-SF total score is a valid and reliable measure of this general wellbeing factor.

Comprehending adverbs of doubt and certainty in health communication: A multidimensional scaling approach

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.