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Searching for a job is an important process that influences short- and long-term career outcomes as well as well-being and psychological health. As such, job search research has grown tremendously over the last two decades. In this chapter, the authors provide an overview of prior research, discuss important trends in current research, and suggest areas for future research. The authors conceptualize the job search as an unfolding process (i.e., a process through which job seekers navigate through stages to achieve their goal of finding and accepting a job) in which job seekers engage in self-regulation behaviors. The authors contrast research that has taken a between-person, static approach with research that has taken a within-person, dynamic approach and highlight the importance of combining between- and within-person designs in order to have a more holistic understanding of the job search process. Finally, authors provide some recommendations for future research. Much remains to be learned about what influences job search self-regulation, and how job self-regulation influences job search and employment outcomes depending on individual, contextual, and environmental factors.

The extant literature provides much-needed support to understand marketing accountability and how marketing actions are related to financial performance (FP). However, we have limited understanding of the relationships between marketing actions and firms' social performance (SP) and environmental performance (EP). Understanding these links is critical to enhancing sustainable FP, SP, and EP. Moreover, the literature provides limited understanding of the measures by which SP and EP may be operationalized, or the data necessary to reach a conclusion. This study bridges these gaps by extensively reviewing the extant literature to offer a set of measures and data sources to operationalize SP and EP, and empirically show their relationships with marketing actions. We find that greenhouse gas (GHG) emission, environmental disclosure score, waste reduction, energy consumption, and recycling are prominent measures of EP, and that social disclosure score, philanthropy or community spending, and diversity of gender and race are prominent measures of SP. The KLD, ASSET4, and Bloomberg are prominent sources of data that can be used to operationalize SP, to which CDP may be added for EP. We also show that marketing actions positively affect EP and SP. This study contributes to the extant literature on SP and EP by identifying measures and data sources and linking marketing actions to both performance types. It contributes to policy development by identifying the importance of EP and SP and how marketing actions can help achieve such performance.

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

Top management support is recognized as the most critical factor for the success of large information system (IS) projects. However, getting this support is often difficult, because top management has multiple priorities and one has to compete with others to obtain such support. Political maneuvering is thus an integral and necessary part of the process of obtaining top management support. In this chapter the authors review current research on this topic and organize and synthesize our findings into a framework. The authors then propose four specific strategies which can be used to obtain top management support, including the following: (1) social capital, (2) social engagement, (3) rational persuasion, and (4) exchange strategies. While the authors argue that all four strategies should be applied, the specific circumstances in which they should be applied vary. A two-stage process is proposed that identifies the appropriate criteria for determining the most appropriate strategy. The criteria are: (1) the type of top management support needed (i.e., durable vs immediate) and (2) the level of top management-project team trust (i.e., high vs low).

This chapter provides a comprehensive review of research and developments relating to the use of Web 2.0 technologies in education. As opposed to early educational uses of the Internet involving publication of static information on web pages, Web 2.0 tools offer a host of opportunities for educators to provide more interactive, collaborative, and creative online learning experiences for students. The chapter starts by defining Web 2.0 tools in terms of their ability to facilitate online creation, editing, and sharing of web content. A typology of Web 2.0 technologies is presented to illustrate the wide variety of tools at teachers’ disposal. Educational uses of Web 2.0 technologies such as wikis, blogs, and microblogging are explored, in order to showcase the variety of designs that can be utilized. Based on a review of the research literature the educational benefits of using Web 2.0 technologies are outlined, including their ability to facilitate communication, collaborative knowledge building, student-centered activity, and vicarious learning. Similarly, issues surrounding the use of Web 2.0 tools are distilled from the literature and discussed, such as the possibility of technical problems, collaboration difficulties, and plagiarism. Two case studies involving the use Web 2.0 tools to support personalized learning and small group collaboration are detailed to exemplify design possibilities in greater detail. Finally, design recommendations for learning and teaching using Web 2.0 are presented, again based on findings from the research literature.