Scenario planning at business unit level

The scenario planning literature is focused on corporate level interventions. There is a general consensus on the method, but there is little debate about the stages involved in building and using the scenarios. This article presents a case study of a scenario planning intervention, which was conducted at a business unit of the British division of one of the largest beauty and cosmetic products multinationals. The method adopted in this case study has some fundamental differences to the existing models used at corporate level. This research is based on the principles of autoethnography, since its purpose is to present self-critical reflections, enhanced by reflective and reflexive conversations on a scenario planning method used at business unit level. The critical reflections concern a series of critical incidents which distinguish this method from existing intuitive logic scenario planning models which are used at corporate level planning. Ultimately this article contributes to the scenario planning method literature by providing insights into its practice at business unit level. © 2012 Elsevier Ltd.

Strategic Human Resources Management Performance Metrics for Unit-Level Managers: An Exploratory Study of U.S Casual Restaurants

Many restaurant organizations have committed a substantial amount of effort to studying the relationship between a firm’s performance and its effort to develop an effective human resources management reward-and-retention system. These studies have produced various metrics for determining the efficacy of restaurant management and human resources management systems. This paper explores the best metrics to use when calculating the overall unit performance of casual restaurant managers. These metrics were identified through an exploratory qualitative case study method that included interviews with executives and a Delphi study. Experts proposed several diverse metrics for measuring management value and performance. These factors seem to represent all stakeholders’interest.

The employee satisfaction -performance link: A unit -level analysis

In this dissertation, I present an integrated model of organizational performance. Most prior research has relied extensively on testing individual linkages, often with cross-sectional data. In this dissertation, longitudinal unit-level data from 559 restaurants, collected over a one-year period, were used to test the proposed model. The model was hypothesized to begin with employee satisfaction as a key antecedent that would ultimately lead to improved financial performance. Several variables including turnover, efficiency, and guest satisfaction are proposed as mediators of the satisfaction-performance relationship. The current findings replicate and extend past research using individual-level data. The overall model adequately explained the data, but was significantly improved with an additional link from employee satisfaction to efficiency, which was not originally hypothesized. Management turnover was a strong predictor of hourly level team turnover, and both were significant predictors of efficiency. Full findings for each hypothesis are presented and practical organizational implications are given. Limitations and recommendations for future research are provided. ^

Work stressors, strains and hospital unit performance

Hospital employees who work in an environment with zero tolerance to error, face several stressors that may result in psychological, physiological, and behavioural strains, and subsequently, in suboptimal performance. This thesis includes two studies which investigate the stressor-to-strain-to-performance relationships in hospitals. The first study is a cross-sectional, multi-group investigation based on secondary data from 65,142 respondents in 172 acute/specialist UK NHS trusts. This model proposes that senior management leadership predicts social support and job design which, in turn, moderate stressors-to-strains across team structure. The results confirm the model's robustness. Regression analysis provides support for main effects and minimal support for moderation hypotheses. Therefore, based on its conclusions and inherent limitations, study one lays the framework for study two. The second study is a cross-sectional, multilevel investigation of the strain-reducing effects of social environment on externally-rated unit-level performance based on primary data from 1,137 employees in 136 units, in a hospital in Malta. The term "social environment" refers to the prediction of the moderator variables, which is to say, social support and decision latitude/control, by transformational leadership and team climate across hospital units. This study demonstrates that transformational leadership is positively associated with social support, whereas team climate is positively associated with both moderators. At the same time, it identifies a number of moderating effects which social support and decision latitude/control, both separately and together, had on specific stressor-to-strain relationships. The results show significant mediated stressor-to-strain-to-performance relationships. Furthermore, at the higher level, unit-level performance is positively associated with shared unit-level team climate and with unit-level vision, the latter being one of the five sub-dimension of transformational leadership. At the same time, performance is also positively related to both transformational leadership and team climate when the two constructs are tested together. Few studies have linked the buffering effects of the social environment in occupational stress with performance. Therefore, this research strives to make a significant contribution to the occupational stress and performance literature with a focus on hospital practice. Indeed, the study highlights the wide-ranging and far-reaching implications that these findings provide for theory, management, and practice.

An Empirical Investigation of the Relationships among Climate, Capabilities, and Unit Performance

For the current study, the authors examined the relationships among two dimensions of organizational climate and several indices of individual- and unit-level effectiveness. Specifically, the article proposes that an organization ’s service and training climate would be related to employee capabilities—operationalized in terms of frontline service capabilities and managerial support capabilities—and that such capabilities would be related to unit- level measures of employee turnover and sales growth. Using survey and operational data from 201 management and frontline staff members in 22 units of a national restaurant chain, the results from correlation and regression analyses generally supported the proposed relationships. This study replicates and extends previous research and provides a foundation for future conceptual development and empirical work in this research area.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

Assurance of learning – are academics and senior management singing from the same hymn sheet?

Assurance of learning (AoL) is an important process in quality education, designed to measure the accomplishment of educational aims at the core of an institution’s programs, whilst encouraging faculty to continuously develop and improve the programs and courses. This paper reports on a study of Australian business schools to investigate current AoL practices through semi structured interviews with senior faculty leaders followed by focus group interviews with groups of senior program leaders and groups of academic teaching staff. Initial findings indicate there are significant challenges in encouraging academic staff to commit to the process and recognise the benefits of assuring learning. The differences in understanding between the various leaders and the academics were highlighted through the different focus groups. Leaders’ stressed strategic issues such as staff engagement and change, while academics focussed on process issues such as teaching graduate attributes and external accreditation. Understanding the differences in the perspectives of leaders and faculty is important, as without a shared understanding between the two groups, there is likely to be limited engagement, which creates difficulties in developing effective assurance of learning processes. Findings indicate that successful strategies developed to foster shared values on assurance of learning include: strong senior leaders’ commitment; developing champions among program and unit level staff; providing professional development opportunities; promoting and celebrating success and effectiveness; and ensuring an inclusive process with academics of all levels collaborating in the development and implementation of the process.

Implementing an enhanced repository statistics system for QUT ePrints

Queensland University of Technology (QUT) was one of the first universities in Australia to establish an institutional repository. Launched in November 2003, the repository (QUT ePrints) uses the EPrints open source repository software (from Southampton) and has enjoyed the benefit of an institutional deposit mandate since January 2004. Currently (April 2012), the repository holds over 36,000 records, including 17,909 open access publications with another 2,434 publications embargoed but with mediated access enabled via the ‘Request a copy’ button which is a feature of the EPrints software. At QUT, the repository is managed by the library.QUT ePrints (http://eprints.qut.edu.au) The repository is embedded into a number of other systems at QUT including the staff profile system and the University’s research information system. It has also been integrated into a number of critical processes related to Government reporting and research assessment. Internally, senior research administrators often look to the repository for information to assist with decision-making and planning. While some statistics could be drawn from the advanced search feature and the existing download statistics feature, they were rarely at the level of granularity or aggregation required. Getting the information from the ‘back end’ of the repository was very time-consuming for the Library staff. In 2011, the Library funded a project to enhance the range of statistics which would be available from the public interface of QUT ePrints. The repository team conducted a series of focus groups and individual interviews to identify and prioritise functionality requirements for a new statistics ‘dashboard’. The participants included a mix research administrators, early career researchers and senior researchers. The repository team identified a number of business criteria (eg extensible, support available, skills required etc) and then gave each a weighting. After considering all the known options available, five software packages (IRStats, ePrintsStats, AWStats, BIRT and Google Urchin/Analytics) were thoroughly evaluated against a list of 69 criteria to determine which would be most suitable. The evaluation revealed that IRStats was the best fit for our requirements. It was deemed capable of meeting 21 out of the 31 high priority criteria. Consequently, IRStats was implemented as the basis for QUT ePrints’ new statistics dashboards which were launched in Open Access Week, October 2011. Statistics dashboards are now available at four levels; whole-of-repository level, organisational unit level, individual author level and individual item level. The data available includes, cumulative total deposits, time series deposits, deposits by item type, % fulltexts, % open access, cumulative downloads, time series downloads, downloads by item type, author ranking, paper ranking (by downloads), downloader geographic location, domains, internal v external downloads, citation data (from Scopus and Web of Science), most popular search terms, non-search referring websites. The data is displayed in charts, maps and table format. The new statistics dashboards are a great success. Feedback received from staff and students has been very positive. Individual researchers have said that they have found the information to be very useful when compiling a track record. It is now very easy for senior administrators (including the Deputy Vice Chancellor-Research) to compare the full-text deposit rates (i.e. mandate compliance rates) across organisational units. This has led to increased ‘encouragement’ from Heads of School and Deans in relation to the provision of full-text versions.

Interactions between organizational culture, trustworthiness, and mechanisms for inter-project knowledge sharing

This research used a multiple-case study approach to empirically investigate the complex relationship between factors influencing inter-project knowledge sharing—trustworthiness, organizational culture, and knowledge-sharing mechanisms. Adopting a competing values framework, we found evidence of patterns existing between the type of culture, on the project management unit level, and project managers’ perceptions of valuing trustworthy behaviors and the way they share knowledge, on the individual level. We also found evidence for mutually reinforcing the effect of trust and clan culture, which shape tacit knowledge-sharing behaviors.

Relationship between job strain and smoking cessation: the Finnish Public Sector Study

Aims: To examine whether job strain (ie, excessive demands combined with low control) is related to smoking cessation.

Methods: Prospective cohort study of 4928 Finnish employees who were baseline smokers. In addition to individual scores, coworker-assessed work unit level scores were calculated. A multilevel logistic regression analysis, with work units at the second level, was performed.

Results: At follow-up, 21% of baseline smokers had quit smoking. After adjustment for sex, age, employer and marital status, elevated odds ratios (ORs) for smoking cessation were found for the lowest vs the highest quartile of work unit level job strain (OR 1.43, 95% CI 1.17 to 1.75) and for the highest vs the lowest quartile of work unit level job control (OR 1.61, 95% CI 1.31 to 1.96). After additional adjustment for health behaviours and trait anxiety, similar results were observed. Further adjustment for socioeconomic position slightly attenuated these associations, but an additional adjustment for individual strain/control had little effect on the results. The association between job strain and smoking cessation was slightly stronger in light than in moderate/heavy smokers. The results for individual job strain and job control were in the same direction as the work unit models, although these relationships became insignificant after adjustment for socioeconomic position. Job demands were not associated with smoking cessation.

Conclusions: Smoking cessation may be less likely in workplaces with high strain and low control. Policies and programs addressing employee job strain and control might also contribute to the effectiveness of smoking cessation interventions.

Work-place social capital and smoking cessation: The Finnish Public Sector Study

AIMS:
To examine whether high social capital at work is associated with an increased likelihood of smoking cessation in baseline smokers.
DESIGN:
Prospective cohort study.
SETTING:
Finland.
PARTICIPANTS:
A total of 4853 employees who reported to be smokers in the baseline survey in 2000-2002 (response rate 68%) and responded to a follow-up survey on smoking status in 2004-2005 (response rate 77%).
MEASUREMENTS:
Work-place social capital was assessed using a validated and psychometrically tested eight-item measure. Control variables included sex, age, socio-economic position, marital status, place of work, heavy drinking, physical activity, body mass index and physician-diagnosed depression.
FINDINGS:
In multi-level logistic regression models adjusted for all the covariates, the odds for being a non-smoker at follow-up were 1.26 [95% confidence interval (CI)=1.03-1.55] times higher for baseline smokers who reported high individual-level social capital than for their counterparts with low social capital. In an analysis stratified by socio-economic position, a significant association between individual-level social capital and smoking cessation was observed in the high socio-economic group [odds ratio (OR) (95% CI)=1.63 (1.01-2.63)], but not in intermediate [(OR=1.10 (0.83-1.47)] or low socio-economic groups [(OR=1.28 (0.86-1.91)]. Work unit-level social capital was not associated with smoking cessation.
CONCLUSIONS:
If the observed associations are causal, these findings suggest that high perceived social capital at work may facilitate smoking cessation among smokers in higher-status jobs.

Social capital at work as a predictor of employee health: Multilevel evidence from work units in Finland

The majority of previous research on social capital and health is limited to social capital in residential neighborhoods and communities. Using data from the Finnish 10-Town study we examined social capital at work as a predictor of health in a cohort of 9524 initially healthy local government employees in 1522 work units, who did not change their work unit between 2000 and 2004 and responded to surveys measuring social capital at work and health at both time-points. We used a validated tool to measure social capital with perceptions at the individual level and with co-workers' responses at the work unit level. According to multilevel modeling, a contextual effect of work unit social capital on self-rated health was not accounted for by the individual's socio-demographic characteristics or lifestyle. The odds for health impairment were 1.27 times higher for employees who constantly worked in units with low social capital than for those with constantly high work unit social capital. Corresponding odds ratios for low and declining individual-level social capital varied between 1.56 and 1.78. Increasing levels of individual social capital were associated with sustained good health. In conclusion, this longitudinal multilevel study provides support for the hypothesis that exposure to low social capital at work may be detrimental to the health of employees. (c) 2007 Elsevier Ltd. All rights reserved.

Potentially harmful excipients in neonatal medicines: A pan-European observational study

Objectives We aimed to describe administration of eight potentially harmful excipients of interest (EOI)-parabens, polysorbate 80, propylene glycol, benzoates, saccharin sodium, sorbitol, ethanol and benzalkonium chloride-to hospitalised neonates in Europe and to identify risk factors for exposure. Methods All medicines administered to neonates during 1 day with individual prescription and demographic data were registered in a web-based point prevalence study. Excipients were identified from the Summaries of Product Characteristics. Determinants of EOI administration (geographical region, gestational age (GA), active pharmaceutical ingredient, unit level and hospital teaching status) were identified using multivariable logistical regression analysis. Results Overall 89 neonatal units from 21 countries participated. Altogether 2095 prescriptions for 530 products administered to 726 neonates were recorded. EOI were found in 638 (31%) prescriptions and were administered to 456 (63%) neonates through a relatively small number of products (n=142; 27%). Parabens, found in 71 (13%) products administered to 313 (43%) neonates, were used most frequently. EOI administration varied by geographical region, GA and route of administration. Geographical region remained a significant determinant of the use of parabens, polysorbate 80, propylene glycol and saccharin sodium after adjustment for the potential covariates including anatomical therapeutic chemical class of the active ingredient. Conclusions European neonates receive a number of potentially harmful pharmaceutical excipients. Regional differences in EOI administration suggest that EOI-free products are available and provide the potential for substitution to avoid side effects of some excipients.

Inférence robuste à la présence des valeurs aberrantes dans les enquêtes

Cette thèse comporte trois articles dont un est publié et deux en préparation. Le sujet central de la thèse porte sur le traitement des valeurs aberrantes représentatives dans deux aspects importants des enquêtes que sont : l’estimation des petits domaines et l’imputation en présence de non-réponse partielle. En ce qui concerne les petits domaines, les estimateurs robustes dans le cadre des modèles au niveau des unités ont été étudiés. Sinha & Rao (2009) proposent une version robuste du meilleur prédicteur linéaire sans biais empirique pour la moyenne des petits domaines. Leur estimateur robuste est de type «plugin», et à la lumière des travaux de Chambers (1986), cet estimateur peut être biaisé dans certaines situations. Chambers et al. (2014) proposent un estimateur corrigé du biais. En outre, un estimateur de l’erreur quadratique moyenne a été associé à ces estimateurs ponctuels. Sinha & Rao (2009) proposent une procédure bootstrap paramétrique pour estimer l’erreur quadratique moyenne. Des méthodes analytiques sont proposées dans Chambers et al. (2014). Cependant, leur validité théorique n’a pas été établie et leurs performances empiriques ne sont pas pleinement satisfaisantes. Ici, nous examinons deux nouvelles approches pour obtenir une version robuste du meilleur prédicteur linéaire sans biais empirique : la première est fondée sur les travaux de Chambers (1986), et la deuxième est basée sur le concept de biais conditionnel comme mesure de l’influence d’une unité de la population. Ces deux classes d’estimateurs robustes des petits domaines incluent également un terme de correction pour le biais. Cependant, ils utilisent tous les deux l’information disponible dans tous les domaines contrairement à celui de Chambers et al. (2014) qui utilise uniquement l’information disponible dans le domaine d’intérêt. Dans certaines situations, un biais non négligeable est possible pour l’estimateur de Sinha & Rao (2009), alors que les estimateurs proposés exhibent un faible biais pour un choix approprié de la fonction d’influence et de la constante de robustesse. Les simulations Monte Carlo sont effectuées, et les comparaisons sont faites entre les estimateurs proposés et ceux de Sinha & Rao (2009) et de Chambers et al. (2014). Les résultats montrent que les estimateurs de Sinha & Rao (2009) et de Chambers et al. (2014) peuvent avoir un biais important, alors que les estimateurs proposés ont une meilleure performance en termes de biais et d’erreur quadratique moyenne. En outre, nous proposons une nouvelle procédure bootstrap pour l’estimation de l’erreur quadratique moyenne des estimateurs robustes des petits domaines. Contrairement aux procédures existantes, nous montrons formellement la validité asymptotique de la méthode bootstrap proposée. Par ailleurs, la méthode proposée est semi-paramétrique, c’est-à-dire, elle n’est pas assujettie à une hypothèse sur les distributions des erreurs ou des effets aléatoires. Ainsi, elle est particulièrement attrayante et plus largement applicable. Nous examinons les performances de notre procédure bootstrap avec les simulations Monte Carlo. Les résultats montrent que notre procédure performe bien et surtout performe mieux que tous les compétiteurs étudiés. Une application de la méthode proposée est illustrée en analysant les données réelles contenant des valeurs aberrantes de Battese, Harter & Fuller (1988). S’agissant de l’imputation en présence de non-réponse partielle, certaines formes d’imputation simple ont été étudiées. L’imputation par la régression déterministe entre les classes, qui inclut l’imputation par le ratio et l’imputation par la moyenne sont souvent utilisées dans les enquêtes. Ces méthodes d’imputation peuvent conduire à des estimateurs imputés biaisés si le modèle d’imputation ou le modèle de non-réponse n’est pas correctement spécifié. Des estimateurs doublement robustes ont été développés dans les années récentes. Ces estimateurs sont sans biais si l’un au moins des modèles d’imputation ou de non-réponse est bien spécifié. Cependant, en présence des valeurs aberrantes, les estimateurs imputés doublement robustes peuvent être très instables. En utilisant le concept de biais conditionnel, nous proposons une version robuste aux valeurs aberrantes de l’estimateur doublement robuste. Les résultats des études par simulations montrent que l’estimateur proposé performe bien pour un choix approprié de la constante de robustesse.