Web-Based Recruitment: Strategies for Attracting LGBT Employees

Organizations are interested in workforce diversity for a variety of reasons. One way to foster employee diversity is through the use of targeted recruitment practices. While this topic has received attention in the literature, most of the work has examined the effectiveness of recruiting people whose minority status is apparent. Thus, the goal of this research is to explore the effectiveness of recruitment strategies targeted toward individuals whose minority status is not immediately obvious, namely lesbian, gay, bisexual, and transgender adults. Two specific recruitment strategies were used: providing information about domestic partner benefits and providing information about community partnerships. The results of this study suggest that the targeted recruitment strategies were equally effective in eliciting higher levels of perceived P–O fit and organizational attraction among a sample of LGBT adults. These findings suggest that organizations can effectively use targeted recruiting to influence LGBT people’s perceptions of organizations. Future research can help identify whether targeted recruitment has a negative impact on straight people’s perceptions of organizations that use recruitment strategies targeted toward members of the LGBT community

Three Essays on Consumers\u27 Activities in the Online Domain

Nowadays, with the explosive growth in the usage of the Internet, consumers are performing all kinds of activities over the Internet like searching or buying. We want to study the different activities of consumers in the online domain. In our daily lives, people are often making various kinds of product purchases. When making such purchases, a lot of factors can affect consumers\u27 decisions. This includes the nature of the product category, and especially in the online domain, the nature of their search activities. In the first essay/chapter, we develop an econometric model to understand the relationships between different dimensions of on-line search and purchase behavior. Our approach uses endogeneity corrections to develop a model that is more correct than the typical non-endogeneity corrected model. Thus we believe our results to be truly reflective of what is happening in the search-buying domain. We use extensive empirical data to test several hypotheses that we developed. Parameters from our model estimations reveal that there are interesting variations in the search-purchase behavior relationships across types of product categories. This difference is especially evident between utilitarian and hedonic goods. Our findings have important theoretical and managerial implications. The amount of information in text reviews is tremendously greater than that in typical numerical data. A major challenge for marketers is how to extract the most relevant information from this big data source. In our second essay/chapter, we do this by using a text mining methodology that draws on machine learning algorithms. We collect data using a Java WebCrawler type programming approach. We use a word-based model to predict consumers\u27 recommendations. Model prediction accuracy was high. In the marketing literature there has been almost no work where such a methodology has been used to make predictions of recommendations based on big data stemming from textual information. An interesting finding from our research is that as the number of textual features increases, the predictive accuracy of the model increases only up to a point. Beyond that, inclusion of more words in the model leads to a decrease in predictive accuracy. We also use a diagnostic approach to identify key words that are determinants of user recommendations. Since our model deals with big data, we address in details the issue of scalability; our computations show that our approach is very scalable. Potential for marketing implications seems considerable. Marketers are always interested in predicting market sales so that they can arrange the firm activities accordingly. In the meantime, this market sales information can also help the consumers to make right buying decisions. However the high cost and long period of collecting the available data with a lag makes it very inconvenient and out of date. With the rise of multi-social media sharing websites such as YouTube, Flickr, and various blogs, consumers can search and learn various types of information from these websites. The availability of large amounts of data on the Internet enables us to use large scale data mining algorithms for solving complex problems. The users\u27 online searching activities can be captured for predicting the market sales. In the third essay/chapter, we focus on the impacts of different search behavior and marketing outcomes like product sales. We examined the three major online search areas including text, image, and video from search engines like Google to help us accurately and easily predict the sales of automobiles. We believe that our work here opens a brand new arena for using multimedia search activities and will have a big impact on marketing sciences

Cognitive representation of facial asymmetry

The human face displays mild asymmetry, with measurements of facial structure differing from left to right of the meridian by an average of three percent. Presently this source of variation is of theoretical interest primarily to researchers studying the perception of beauty, but a very limited amount of research has addressed the question of how this variation contributes to the cognitive processes underlying face recognition. This is surprising given that measurement of facial asymmetry can reliably distinguish between even the most similar of faces. Furthermore, brain regions responsible for symmetry detection support face-processing regions, and detection of symmetry is superior in upright faces relative to inverted and contrast-reversed face stimuli. In addition, facial asymmetry provides a useful biometric for automatic face recognition systems, and understanding the contribution of facial asymmetry in human face recognition may therefore inform the development of these systems. In this thesis the extent to which facial asymmetry is implicated in the process of recognition in human participants is quantified. By measuring the effect of left-right reversal on various tasks of face processing, the degree to which facial asymmetry is represented by memory is investigated. Marginal sensitivity to mirror reversal is demonstrated in a number of instances, and it is therefore concluded that cognitive representations of faces specify structural asymmetry. Reversal effects are typically slight however and on a number of occasions no reliable effect of this stimulus manipulation is detected. It is likely that a general tendency to treat mirror reversals as equivalent stimuli, in addition to an inability to recall lateral orientation of objects from memory, somewhat obscure the effect of reversal. The findings are discussed in the context of existing literature examining the way in which faces are cognitively represented

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Fear appeals and mortgage protection insurance – a quantitative study

Managers in charge of sales process designs are constantly in the need to optimise their communication strategy to improve advisory quality and take-up rates. This is especially true for mortgage protection insurance (MPI), where buying insurance means buying an immaterial product that creates a perception of security which protects one of the most important assets in life – one’s home. It is key for a successful advisory to find communication approaches that overcome the psychological barriers of customers. One possible approach is the use of fear appeals, which confront the customer with negative consequences. Despite their widespread use in the public field, and continuous academic interest since the 1950s, the effectiveness of fear appeals remains equivocal. A detailed chronological examination of fear appeal research is presented suggesting that the field of insurance distribution was neglected from research. The effect of specific individual differences (optimism, pessimism, risk-taking) on cognitions, emotions, and behaviour outcomes are identified as gaps in the literature. The primary aim of this thesis was to determine the effectiveness of fear appeals in the context of MPI on behaviour outcomes and on willingness-to-pay to enhance the advisory quality of mortgage salespersons. To achieve this a research framework was developed that utilises the constructs of the Extended Parallel Process Model, conceptualises a fear appeal into three message characteristics (vivid image, message frame, message direction) and integrates individual differences. Using data from a randomised experiment (N = 1,014), the research framework was tested using ANOVAs, t-tests, regression analysis, and PROCESS calculations. The results delivered valuable insights. Firstly, vivid images created fear and uncomfortable feelings but did not influence cognitions or behaviour outcomes. Secondly, cognitive appraisal values indicated that the product information was well suited for business needs. Moreover, perceived susceptibility to a threat, as did optimism and risk-taking, showed a significant positive effect on willingness-to-pay. Lastly, a significantly positive effect was achieved on attitude towards MPI with the integration of the treatment. This project has demonstrated important factors for improving the sales process of MPI salespersons

The dynamic interplay of external and internal attention

During natural behaviour, our attention is in constant flux, seamlessly transitioning between information available in the external environment and internal representations stored in working memory. However, as past research has primarily investigated external and internal attention in isolation, relatively little is known regarding the dynamic interplay between these two attentional domains. In this doctoral thesis, I explore scenarios where individuals encounter both external and internal information in quick succession, necessitating rapid shifts between perception and working memory. The experimental work in this thesis can be divided into two main branches. The first branch explores cross-domain attentional modulations; that is, how attention within one domain influences attention within the alternative domain. The second branch takes a deeper dive into the intricacies of shifting attention between domains. To provide an overview of previous contributions, Chapter 1 reviews past studies on external and internal attention, both as independent facets of attention and as interdependent phenomena. Building on this, Chapter 2 investigates the behavioural consequences of attentional shifts and examines how these can be modulated. Chapter 3 explores between-domain shifts by employing neural measures to examine the timing of reactivating internal representations following engagement in an external task. To understand the overarching nature of between-domain shifts, Chapters 4 and 5 introduce a novel, combined perception and working-memory task that allows within- and between-domain shifts to be contrasted in each respective domain. While Chapter 4 focusses on the behavioural correlates of between-domain shifts, Chapter 5 investigates the neural signatures associated with these transitions. Finally, in Chapter 6, I discuss the implications of my results and suggest potential avenues for future research. The findings of my doctoral research reveal that the dynamic interplay between attentional domains imposes behavioural costs; however, these costs are not immutable and can be influenced by various modulatory factors from multiple sources. Further, I demonstrate that prompt (but not always complete) shifts between attentional domains can be triggered by various events. Taken together, this thesis advocates for a holistic approach to examining external and internal attention

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

Decoding attentional load in visual perception: a signal processing approach

Previous research has established that visual perception tasks high in attentional load (or ‘perceptual load’, defined operationally to include either a larger number of items or a greater perceptual processing demand) result in reduced perceptual sensitivity and cortical response for visual stimuli outside the focus of attention. However, there are three challenges facing the load theory of attention today. The first is to describe a neural mechanism by which load-induced perceptual deficits are explained; the second is to clarify the concept of perceptual load and develop a method for estimating the load induced by a visual task a priori, without recourse to measures of secondary perceptual effects; and the third is to extend the study of attentional load to natural, real-world, visual tasks. In this thesis we employ signal processing and machine learning approaches to address these challenges. In Chapters 3 and 4 it is shown that high perceptual load degrades the perception of orientation by modulating the tuning curves of neural populations in early visual cortex. The combination of tuning curve modulations reported is unique to perceptual load, inducing broadened tuning as well as reductions in tuning amplitude and overall neural activity, and so provides a novel low-level mechanism for behaviourally relevant failures of vision such as inattentional blindness. In Chapter 5, a predictive model of perceptual load during the task of driving is produced. The high variation in perceptual demands during real-world driving allow the construction of a direct fine-scale mapping between high-resolution natural imagery, captured from a driver's point-of-view, and induced perceptual load. The model therefore constitutes the first system able to produce a priori estimates of load directly from visual characteristics of a natural task, extending research into the antecedents of perceptual load beyond the realm of austere laboratory displays. Taken together, the findings of this thesis represent major theoretical advances into both the causes and effects of high perceptual load

Image and Video Forensics

Nowadays, images and videos have become the main modalities of information being exchanged in everyday life, and their pervasiveness has led the image forensics community to question their reliability, integrity, confidentiality, and security. Multimedia contents are generated in many different ways through the use of consumer electronics and high-quality digital imaging devices, such as smartphones, digital cameras, tablets, and wearable and IoT devices. The ever-increasing convenience of image acquisition has facilitated instant distribution and sharing of digital images on digital social platforms, determining a great amount of exchange data. Moreover, the pervasiveness of powerful image editing tools has allowed the manipulation of digital images for malicious or criminal ends, up to the creation of synthesized images and videos with the use of deep learning techniques. In response to these threats, the multimedia forensics community has produced major research efforts regarding the identification of the source and the detection of manipulation. In all cases (e.g., forensic investigations, fake news debunking, information warfare, and cyberattacks) where images and videos serve as critical evidence, forensic technologies that help to determine the origin, authenticity, and integrity of multimedia content can become essential tools. This book aims to collect a diverse and complementary set of articles that demonstrate new developments and applications in image and video forensics to tackle new and serious challenges to ensure media authenticity