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It is widely established that many hiring managers view social networking websites (SNWs) such as LinkedIn and/or Facebook in the employment selection process, leading to the acceptance or rejection of job applicants. Due to the rapid evolution of social media, scientific study of SNWs has been substantially outpaced by organizational practice. This chapter focuses on a wide range of issues related to SNW screening relevant to research and practice.

The chapter: (1) reviews the current state of SNW screening practices, (2) describes a wide range of HR issues that should be considered such as privacy, discrimination, negligent hiring, validity, reliability, generalizability, impression management, applicant reactions, and utility, (3) draws connections to related issues already addressed by established employment selection methods to inform SNW screening, (4) discusses pros and cons of potential SNW screening approaches, and (5) provides a framework of best practices that should be incorporated into social network screening policies.

As an emerging employment selection approach, SNW screening demonstrates potential as a rich source of applicant information, but includes numerous legal and ethical issues. Further, these potential benefits and risks vary widely depending on the approaches used.

Provides HR practitioners with a wide range of information necessary to develop an effective social network screening policy, while making the case for academics to pursue research in this nascent area.

Purpose: In reality, financial decisions are made under conditions of asymmetric information that results in either favorable or adverse selection. As far as financial decisions affect growth of the firm, the latter must also be affected by either favorable or adverse selection. Therefore, the core objective of this chapter is to examine the determinants of each financial decision and the effects on growth of the firm under conditions of information asymmetry.

Design/Methodology/Approach: This chapter uses data for the non-financial firms listed in S&P 500. The data cover quarterly periods from 1989 to 2014. The statistical tests include linearity, fixed, and random effects and normality. The generalized method of moments estimation method is employed in order to examine the relative significance and contribution of each financial decision on growth of the firm, respectively. Standard and proposed proxies of information asymmetry are discussed.

Findings: The results conclude that there is a variation in the impact of financial variables on growth of the firm at high and low levels of information asymmetry especially regarding investment and financing decisions. A similar picture emerges in the cases of firm size and industry effects. In addition, corporate dividen d policy has a similar effect on firm growth across all asymmetric levels. These findings prove that information asymmetry plays a vital role in the relationship between corporate financial decisions and growth of the firm. Finally, the results contribute to the vast literature on the estimation of information asymmetry by demonstrating that the classical and standard proxies for information asymmetry are not consistent in terms of the ability to differentiate between favorable or adverse selection (which corresponds to low and high level of information asymmetry).

Originality/Value: This chapter contributes to the related literature in two ways. First, this chapter offers updated empirical evidence on the way that financing, investment, and dividends decisions are made under conditions of favorable and adverse selection. Other related studies deal with each decision separately. Second, the study offers new proxies for measuring information asymmetry in order to reach robust estimates of the effects of financial decisions on growth of the firm under conditions of agency problems.

Corporate acquisitions have received less attention than the “make-versus-buy” paradigm problem within transaction cost economics. However, recent research that has been conducted on acquisitions is a valuable source of ideas that can be put to use in organizational governance studies more broadly. In this paper, I provide a brief review of the M&A literature with the aim of developing two arguments. First, information economics has provided important theoretical underpinnings for this literature and complements transaction cost economics by emphasizing the ex ante exchange hazards that economic actors face. Second, research using information economics offers the potential to enrich the organizational economics research agenda in strategic management and vice versa.

Purpose — To provide an overview of recent research that examined how search engine users evaluate and select Web search results and how alternative search engine interfaces can support Web users' credibility assessment of Web search results.

Design/methodology/approach — As theoretical background, Information Foraging Theory (Pirolli, 2007; Pirolli & Card, 1999) from cognitive science and Prominence-Interpretation-Theory (Fogg, 2003) from communication and persuasion research are presented. Furthermore, a range of recent empirical research that investigated the effects of alternative SERP layouts on searchers' information quality or credibility assessments of search results are reviewed and approaches that aim at automatically classifying search results according to specific genre categories are reported.

Findings — The chapter reports on findings that Web users often rely heavily on the ranking provided by the search engines without paying much attention to the reliability or trustworthiness of the Web pages. Furthermore, the chapter outlines how alternative search engine interfaces that display search results in a format different from a list and/or provide prominent quality-related cues in the SERPs can foster searchers' credibility evaluations.

Research limitations/implications — The reported empirical studies, search engine interfaces, and Web page classification systems are not an exhaustive list.

Originality/value — The chapter provides insights for researchers, search engine developers, educators, and students on how the development and use of alternative search engine interfaces might affect Web users' search and evaluation strategies during Web search as well as their search outcomes in terms of retrieving high-quality, credible information.

We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes, the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to predict, that is, the process of selecting the factors is not supervised by the predictand. We propose a simple and operational supervised method, based on selecting the factors on the basis of their significance in the regression of the predictand on the predictors. Given a potentially large number of predictors, we consider linear transformations obtained by principal components analysis. The orthogonality of the components implies that the standard t-statistics for the inclusion of a particular component are independent, and thus applying a selection procedure that takes into account the multiplicity of the hypotheses tests is both correct and computationally feasible. We focus on three main multiple testing procedures: Holm's sequential method, controlling the familywise error rate, the Benjamini–Hochberg method, controlling the false discovery rate, and a procedure for incorporating prior information on the ordering of the components, based on weighting the p-values according to the eigenvalues associated to the components. We compare the empirical performances of these methods with the classical diffusion index (DI) approach proposed by Stock and Watson, conducting a pseudo-real-time forecasting exercise, assessing the predictions of eight macroeconomic variables using factors extracted from an U.S. dataset consisting of 121 quarterly time series. The overall conclusion is that nature is tricky, but essentially benign: the information that is relevant for prediction is effectively condensed by the first few factors. However, variable selection, leading to exclude some of the low-order principal components, can lead to a sizable improvement in forecasting in specific cases. Only in one instance, real personal income, we were able to detect a significant contribution from high-order components.

In vol. 6, 1976, of Advances in Librarianship, I published a review about relevance under the same title, without, of course, “Part I” in the title (Saracevic, 1976). [A substantively similar article was published in the Journal of the American Society for Information Science (Saracevic, 1975)]. I did not plan then to have another related review 30 years later—but things happen. The 1976 work “attempted to trace the evolution of thinking on relevance, a key notion in information science, [and] to provide a framework within which the widely dissonant ideas on relevance might be interpreted and related to one another” (ibid.: 338).

The author takes a comprehensive look at the accessibility of e-resources for all people, including those with disabilities, in the context of collection development (CD).

Employing a combination of research methodologies — policy analysis, content analysis, and phone survey—the author explores the extent to which the needs of people with disabilities are considered.

Several professional library organizations recommend accessibility-sensitive selection and procurement procedures. However, not all students enrolled in library school programs might learn about the issue. Few books on the subject cover the issue adequately. Nationwide, CD policies requiring conformance to accessibility standards are the exception; and when librarians meet to make decisions about the selection of specific e-resources, the needs of people with disabilities are rarely on their radar screens.

Researchers conducting similar surveys in the future might want to not only select a statistically more representative sample of academic libraries but also widen their focus and include both accessibility and usability in their investigations.

Textbook authors and course instructors in the area of CD need to address accessibility and usability. Librarians need to raise the issue with database and e-book vendors during license negotiations.

The acquisition of e-resources designed to be accessible and usable for all will enable people with disabilities to participate more fully in our information-driven society.

The data collected provide for a broad discussion of the extent to which the needs of people with disabilities are considered in connection with CD.

This chapter provides an overview of two generally applicable frameworks relating to the use of technology-enhanced learning – ‘affordances’ and multimedia learning effects. First, the concept of ‘affordances’ as action potentials of technologies is identified as a way to think through technology-enhanced learning design possibilities, so as to help make technology selection decisions. Second, multimedia learning effects including the multimedia effect, the modality effect, the redundancy effect, the split-attention effect, and the personalization effect are presented as a scientific basis for understanding how to create cognitively effective learning experiences using text, images, sound, and video. Both affordances and multimedia learning effects are characterized as ongoing areas of research that are somewhat related, with the successful utilization of each depending on critical application by the designer.