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Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges are also often recorded. Such covariate data should be used in conjunction with preference data when drawing inferences about judges.

To cluster a population of judges, the population is modeled as a collection of homogeneous groups. The Plackett-Luce model for ranked data is employed to model a judge's ranked preferences within a group. A mixture of Plackett- Luce models is employed to model the population of judges, where each component in the mixture represents a group of judges.

Mixture of experts models provide a framework in which covariates are included in mixture models. Covariates are included through the mixing proportions and the component density parameters. A mixture of experts model for ranked preference data is developed by combining a mixture of experts model and a mixture of Plackett-Luce models. Particular attention is given to the manner in which covariates enter the model. The mixing proportions and group specific parameters are potentially dependent on covariates. Model selection procedures are employed to choose optimal models.

Model parameters are estimated via the ‘EMM algorithm’, a hybrid of the expectation–maximization and the minorization–maximization algorithms. Examples are provided through a menu survey and through Irish election data. Results indicate mixture modeling using covariates is insightful when examining a population of judges who express preferences.

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact on the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between alternative oil market models, let alone the basis for the sometimes divergent conclusions reached in the literature. The purpose of this survey is to provide a guide to this literature. Our focus is on the econometric foundations of the analysis of oil market models with special attention to the identifying assumptions and methods of inference.

Sustainable development may best be achieved by enhancing the commitment of local communities. Stewart and Hams (1991) argue that the requirements of sustainable development cannot merely be imposed but that active participation by local communities is needed. However, the terms ‘community’, ‘host community’ and ‘participation’ can be interpreted in a myriad of ways. Before entering a full discussion of host community participation in tourism planning, it is first necessary to explore the various potential interpretations of these terms and to define their meaning and function. This chapter therefore clarifies some of the issues surrounding the terms community, host, host community and participation. The major typologies and available models in relation to host communities’ participation in sustainable planning for tourism are also reviewed.

In recent years, a wide range of psychosocial health interventions have been implemented among military service members and their families. However, there are questions over the evaluative rigor of these interventions. We conducted a systematic review of this literature, rating each relevant study (k = 111) on five evaluative rigor scales (type of control group, approach to participant assignment, outcome quality, number of measurement time points, and follow-up distality). The most frequently coded values on three of the five scales (control group type, participant assignment, and follow-up distality) were those indicating the lowest level of operationally defined rigor. Logistic regression results indicate that the evaluative rigor of intervention studies has largely remained consistent over time, with exceptions indicating that rigor has decreased. Analyses among seven military sub-populations indicate that interventions conducted among soldiers completing basic training, soldiers returning from combat deployment, and combat veterans have had, on average, the greatest evaluative rigor. However, variability in mean scores across evaluative rigor scales within sub-populations highlights the unique methodological hurdles common to different military settings. Recommendations for better standardizing the intervention evaluation process are discussed.

While mail surveys continue to be a widely used research technique, relatively little empirical research exists that assesses their effectiveness among industrial (commercial) organizations. To address this literature void, the present paper reports the findings from a mail survey of international freight forwarders. More specifically, this paper investigates the influence of postcard prenotification with respect to response rates, response speed, response quality, response bias, and response cost effectiveness. The paper also discusses implications of the results and offers suggestions for further research.

This study shows how 152 researchers from several research centers of a Portuguese university perceive the facilitators and barriers to knowledge management. Three domains are considered – knowledge gathering, creation, and diffusion. Three dimensions of barriers and facilitators were considered – individuals, socio‐organizational processes, and technology. Regarding both barriers and facilitators, but mainly barriers, the findings suggest that researchers are more sensitive to the “soft” aspects of knowledge management (i.e., individuals, socio‐organizational processes) than to the “hard” ones (i.e., technology). This suggests that, although technology is an important facilitator, it is people and their interactions that create knowledge and promote the knowledge flow.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Tourism management is becoming a necessary component of regional and local planning as the effects of mass tourism build up in host communities. Traditionally, two forces have been at work in tourist areas. On the one hand promotion of the industry by those who are concerned with maximizing its economic return and, on the other, agencies concerned with protecting the local area and its inhabitants from the pressures of tourism. It is the host community's public amenities which often form the nucleus of a tourist attraction and its residents who are expected to provide the hospitality upon which the industry depends. Thus, some form of management is needed if the industry is to develop in accordance with a community's aspirations and capacity. Sir George Young noted the need for balanced development in his seminal study, Tourism: Blessing or Blight? He called for tourist authorities to “act within the context of a national plan which identifies the role of tourism and which blends the requirements.”

The purpose of this chapter is to address the question of how communication studies can prove its value in relation to corporate social responsibility (CSR). As many disciplines seek to understand CSR, the role of communication has been relatively underexplored despite its prevalence in demonstrating and shaping social responsibility positions and practice.

Literature review.

The literature review points to what we consider as four aces. Communication studies alert us to (1) how meaning is constructed through communication, something that has implications for the management of organizations as publics hold different views of CSR and expect different things from them; (2) how a dialogue between an organization and its publics should unfold; (3) how practices of transparency can assist organizations to come across as trustworthy actors; and, importantly, (4) how a complexity view is fruitful to grasp the CSR communication process.

These four key themes could be instructive for practitioners who want to argue for and demonstrate the usefulness of strategic communication for the management of CSR and bridge meso and macro levels of analysis.

This article reviews the literature on the econometric relationship between DSGE and VAR models from the point of view of estimation and model validation. The mapping between DSGE and VAR models is broken down into three stages: (1) from DSGE to state-space model; (2) from state-space model to VAR( ∞ ); (3) from VAR( ∞ ) to finite-order VAR. The focus is on discussing what can go wrong at each step of this mapping and on critically highlighting the hidden assumptions. I also point out some open research questions and interesting new research directions in the literature on the econometrics of DSGE models. These include, in no particular order: understanding the effects of log-linearization on estimation and identification; dealing with multiplicity of equilibria; estimating nonlinear DSGE models; incorporating into DSGE models information from atheoretical models and from survey data; adopting flexible modeling approaches that combine the theoretical rigor of DSGE models and the econometric model’s ability to fit the data.