Advances in artificial intelligence and deep neural networks have led to a rise in synthetic media, i.e., automatically and artificially generated or manipulated photo, audio, and video content. Synthetic media today is highly believable and "true to life"; so much so that we will no longer be able to trust what we see or hear is unadulterated and genuine. Among the different forms of synthetic media, the most concerning forms are deepfakes and general adversarial networks (GANs). For IT professionals, it is important to understand what these new phenomena are. In this article, we explain what deepfakes and GANs are, how they work and discuss the threats and opportunities resulting from these forms of synthetic media.

Purpose The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis. Design/methodology/approach To illustrate the use of AI-enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: reliability, validity and efficiency. Findings Relative to manual and computer-aided approaches, AI-enabled content analysis provides clear advantages with high reliability, high validity and moderate efficiency. Research limitations/implications - This paper offers three contributions. First, it highlights the continued importance of the content analysis research method, particularly with the explosive growth of natural language-based user-generated content. Second, it provides a road map of how to use AI-enabled content analysis. Third, it applies and compares AI-enabled content analysis to manual and computer-aided, using leadership speeches. Practical implications - For each of the three approaches, nine steps are outlined and described to allow for replicability of this study. The advantages and disadvantages of using AI for content analysis are discussed. Together these are intended to motivate and guide researchers to apply and develop AI-enabled content analysis for research in marketing and other disciplines. Originality/value To the best of the authors' knowledge, this paper is among the first to introduce, apply and compare how AI can be used for content analysis.

Attracting and retaining the best talent is a concern, particularly for knowledge-based firms in high-turnover industries, which rely on a limited supply of highly qualified individuals (Ewing, Pitt, De Bussy, & Berthon, 2002). In 2014, 36% of global employers criticized talent shortages, and in a 2015 study, 73% of CEOs reported being concerned about the availability of workers with key skills (Mosley, 2015). Employer branding is a key human resource and marketing strategy that contributes to the company’s brand, enhances the firm’s reputation as a great place for employees to work, and attracts a new workforce (Ahmad & Daud, 2016). An employer brand’s and its employer branding value propositions’ (EBV) ability to attract new employees and increase retention will provide benefits for the entire organization.

EBV defines the employer’s attractiveness (Berthon et al., 2005), is a key aspect of the employer branding process, and provides differentiation for the firm (Alnıaçık & Alnıaçık, 2012; Backhaus & Tikoo, 2004; Berthon et al., 2005; Leekha Chhabra & Sharma, 2014; Moroko & Uncles, 2008) to attract and retain employees. Existing research viewed employer branding and its EBV from one or two views—employee or employer—and lacked multiview approaches to employer branding and employer attractiveness. This research focused on a holistic approach and addressed the question: “How do different EBVs affect the perceptions of employer attractiveness? To answer this question holistically, the following research subquestions emerged:

RQ1: How do employees perceive the EBV of employer attractiveness?

RQ2: How do current and former employees perceive the EBV of employer attractiveness?

RQ3: How do potential employees perceive the EBV of employer attractiveness?

RQ4: How do employers manage how employees perceive EBV?

This research consisted of four empirical papers and focused on the information technology (IT) industry context. The first study focused on employee views from all industries, whereas the second study concentrated on the IT industry and compared current and former employees. Study 3 considered potential employees in the IT industry and operationalized the employee attractiveness construct and EBVs. The final study explored EBVs from the employer’s view in an IT firm and compared its employees’ views regarding the psychological contract. The design of this research is a mixed approach with descriptive and exploratory methodologies. IBM Watson’s artificial intelligence content analysis was used in Studies 1, 2, and 4.

Contributions to the body of knowledge includes operationalizing the employee attractiveness construct as a set of EBVs. This research viewed EBVs holistically and extended the set of EBVs from five to eight value propositions for the IT industry. It also defined employer brand intelligence as a tool for practitioners to develop insights for their employer brand.

The document is organized with an introductory chapter describing the overall research approach, followed by a literature review chapter, methodology chapter, and summary of findings and contributions. The four papers are included in the final chapter.

Att attrahera och behålla de bästa talangerna är ett bekymmer, särskilt för kunskapsbaserade företag inom sektorer med hög omsättning som förlitar sig på ett begränsat utbud av högkvalificerade individer (Ewing, Pitt, De Bussy, & Berthon, 2002). Under 2014 kritiserade 36% av de globala arbetsgivarna brist på talangfull arbetskraft och i en studie från 2015 rapporterade 73% av de verkställande direktörerna att de var oroliga för tillgången på arbetare med nyckelfärdigheter (Mosley, 2015). Employer branding är en viktig HR- och marknadsföringsstrategi som bidrar till företagets varumärke, förbättrar företagets rykte som en utmärkt plats för anställda att arbeta och attraherar ny arbetskraft (Ahmad & Daud, 2016). Ett arbetsgivarvarumärke och förmågan hos employer branding värdeerbjudandena (EBV), att attrahera nya anställda och öka bibehållandet av personal, kommer att ge fördelar för hela organisationen.

EBV definierar arbetsgivarens attraktivitet (Berthon et al., 2005), är en viktig aspekt av employer branding-processen och förser företaget med differentiering (Alnıaçık & Alnıaçık, 2012; Backhaus & Tikoo, 2004; Berthon et al., 2005; Leekha Chhabra & Sharma, 2014; Moroko & Uncle, 2008) för att attrahera och behålla anställda. Befintlig forskning såg employer branding och dess EBV från ett eller två perspektiv – som anställd eller arbetsgivare - och saknade strategier med flera synvinklar för employer branding och arbetsgivares attraktivitet. Denna studie fokuserade på en helhetssyn och adresserade frågan: ”Hur påverkar olika EBV:er uppfattningen av arbetsgivares attraktivitet? För att holistiskt besvara denna fråga etablerades följande forskningsunderfrågor:

FF1: Hur uppfattar anställda EBV:et för arbetsgivarattraktivitet?

FF2: Hur uppfattar nuvarande och tidigare anställda EBV:et för arbetsgivarattraktivitet?

FF3: Hur uppfattar potentiella arbetstagare EBV:et för arbetsgivarattraktivitet?

FF4: Hur hanterar arbetsgivare hur anställda uppfattar EBV?

Denna studie bestod av fyra empiriska artiklar och fokuserade på kontext inom branschen för informationsteknik (IT). Den första studien fokuserade på anställdas perspektiv från alla branscher, medan den andra studien inriktades på IT-branschen och jämförde nuvarande och tidigare anställda. Studie 3 handlade om potentiella arbetstagare inom IT-branschen. Den slutliga studien undersökte EBV:er från arbetsgivarens synvinkel i ett IT-företag och jämförde de anställdas åsikter och det psykologiska kontraktet. Designen för denna studie baseras på en blandad forskningsansats med deskriptiva och explorativa undersökningsformer. Studierna 1, 2 och 4 använde en stor mängd data från Glassdoor.com:s webbplats för medarbetarrecensioner och använde IBM Watsons innehållsanalys framtagen via artificiell intelligens för att utveckla insikter. Studie 3 utvecklas och färdigställdes med hjälp av studenter som läste datorvetenskap och informationsteknik på ett stort universitet i västra USA. I Studie 4 genomfördes semistrukturerade intervjuer med en arbetsgivare i Silicon Valley i Kalifornien.

Studie 1 har bidragit till att utvidga de fem värdeerbjudandena: ekonomiskt, socialt, tillämpnings, utvecklings- och intressevärde för arbete framtagna av Berthon et al. (2005) till sju genom att identifiera två nya värdeerbjudanden: balans mellan arbete och liv samt hantering för alla industrier. En 2x2-matris för sju värdeerbjudanden utvecklades för varje värdeerbjudande. De två eller tre främsta värdeerbjudandena stod för 65% till 83% av anställdas kommentarer. Studien definierade en arbetsgivares varumärkesintelligens som ett nytt verktyg för chefer för att utveckla insikt och studien identifierade även sju konsekvenser för ledarskap.

Studie 2 har bidragit till att utvidga de sju värdeerbjudandena i Studie 1 genom att identifiera ett nytt värdeerbjudande; varumärkesimage eller organisationsimage inom IT-branschen. De sociala och ekonomiska värdena är nyckelfaktorer för beröm från både nuvarande och tidigare anställda medan värdet för ledarskap är en stor klagomålsfaktor för tidigare IT-anställda. Varumärkesimage är en annan primär klagomålsfaktor för både nuvarande och tidigare anställda.

Studie 3 bekräftade att de åtta värdeerbjudandena som är viktiga för nuvarande och tidigare anställda också är viktiga för potentiella arbetstagare. Studien operationaliserade arbetsgivares attraktivitet, utvecklade ett instrument för att mäta EBV:er samt utvecklade och testade ett nytt, mer omfattande instrument för att utvärdera EBV:er.

Studie 4 bekräftade att de åtta värdeerbjudandena som var viktiga i studie 2 också är viktiga för arbetsgivaren. Däremot finns det stora skillnader mellan arbetsgivaren och nuvarande och tidigare anställda, vilket kan bidra till att det psykologiska kontraktet bryts och problem med att behålla personal. Arbetsgivaren bryr sig mer om sociala värden än vad nuvarande anställda gör. Det finns ett betydande gap mellan arbetsgivares och anställdas uppfattning angående intressevärdet. Ett annat gap finns mellan arbetsgivares och anställdas uppfattningar för utvecklingsvärdet. Nuvarande anställda bryr sig mer om varumärkets imagevärde än vad arbetsgivaren gör.

Dokumentet är organiserat med ett inledande kapitel som beskriver den övergripande forskningsansatsen, följt av ett litteraturkapitel, metodkapitel och en sammanfattning av resultat och bidrag. De fyra artiklarna ingår i det sista kapitlet.

Consumers seek out other consumers’ input to facilitate and remove some of the ambiguity and risk from the purchase decision-making process through online word of mouth (eWOM) (Sparks and Browning 2011). This makes consumer reviews important for anyone seeking to sell products and services both inside and outside the sharing economy. The eWOM literature largely focuses on review authenticity and credibility from the point of view of fake online reviews (i.e., astroturfing), such as reviews created by business owners or generated using artificial intelligence (c.f. Castillo et al. 2013) or the deletion of negative reviews (c.f. Bamman et al. 2012). However, there is scant attention given to customer reviews and ratings that do not reflect customers’ true opinions and feelings of their experience. For example, consider ridesharing services, such as Uber and Lyft, where consumers have little knowledge outside of the numerical evaluation ratings other customers give their drivers. On these platforms, researchers have observed rating inflation where customers give drivers top marks even when things go wrong and expectations are not met (Cook 2015; Etzioni 2017). This pattern of rating inflation exists in other sharing economy contexts as well including, notably, the accommodation sharing industry (Zervas et al. 2015, 2014). This article proposes that customers perceive an organization’s own market label by processing marketing positioning information, such as those found on websites. A market label is a metaphoric word or phrase that expresses an organization’s identity and constructs relationships between the organization and other stakeholders. This paper examines whether the customer reviews and the sentiment within them corresponds to how an organization positions or presents itself in the marketplace. Specifically, we introduce the professional and amateur market labels and analyze the impact of the organization’s sales pitches. References Available Upon Request

Our previous paper "How do Employers conceptualize characteristics of employer branding in the IT industry?" demonstrated an eight value proposition for employer branding. This work was focused primarily on current and former information technology employees. As an extension to that work, the discussion will focus on a follow-up study examining the characteristics of successful employer branding from the employer perspective.

Attracting and retaining IT talent remains challenging for IT ecutives. The limited supply of highly skilled candidates, combined th high workforce mobility, results in considerable hiring, training, d developing costs. To help IT employers overcome these challenges, e authors discuss employer branding as one strategy to manage firms' putations as "great places to work." Based on a content analysis of arly 15 000 employee reviews, this article identifies and describes ght values that IT professionals care about when evaluating IT ployers, highlights which values are most important, and provides commendations for how IT firms can use employer brand intelligence to tract and retain IT talent to remain competitive.

Purpose The purpose of this paper is to develop an instrument to measure employer branding in the information age. Firms increasingly migrate from matter-intensive business models to information-intensive models, where value lies in information rather than the physical objects. This shift has, in turn, led to a change in employee work skills. This is particularly true in the information technology (IT) sector, where firms rely on a limited supply of skilled labor. Employer branding, a firm's reputation as a place to work, is an important strategy to attract and retain employees. Design/methodology/approach From the literature, the authors developed and refined an instrument to measure key value propositions of employer brands. The potential IT employees surveyed in the study were students enrolled in the disciplines of computer science and information systems at a comprehensive university in North America. The study went through three stages resulting in an instrument for psychometric properties. Findings This research revealed eight employer branding value propositions that future IT employees care about. These dimensions are important for both IT firms and industries competing for skilled IT labor to understand and manage. Originality/value This paper extends the work of Berthon et al. (2005) on employer branding to the information intensive age and particularly the IT sector. It allows executives to manage and measure their employer brand so as to maximize competitive advantage in attracting and retaining skilled employees.

In this paper, the authors demonstrate how IBM Watson, a super computer that uses artificial intelligence (AI), can be used in academic and managerial research. A brief description of how Watson originated and operates is followed by four examples of how Watson can be used in academic marketing research. The first two examples use Watson’s personality and insight services to analyze qualitative depth interviews. The last two examples use Watson’s emotion and sentiment analysis on textual data and qualitative depth interviews. These examples emphasize the value of Watson in the age of big data and its ability to analyze issues that would otherwise be too complex. The paper concludes with limitations, managerial implications, and future research. 

This paper explores the possibility of creating a new category of Facebook ads based on the personality of the user. The introduction of social media channels such as Facebook has provided a new platform for performing self-affirmation theory tests and related behavioral studies. This paper is based on the subsidiary hypothesis that while self-affirming themselves, Facebook users disclose information about their personality. A lexical analysis of each user’s Facebook posts can therefore be used for the purpose of profiling the user. The analysis and categorization of users’ posts based on their behavioral and personality traits can potentially assist marketers interested in targeted marketing to reach a specific audience through this powerful online channel. Hence, this study proposes an innovative method that measures narcissistic personality by analyzing a user’s Facebook posts. 

In their attempts to reduce the uncertainty associated with knee replacement surgeries, patients turn to social media, where they commonly rely on the experiences expressed by other patients. In this study, we first employ IBM Watson to examine how patients talk about their emotions and express sentiment through their comments online. We then use a latent class cluster modelling procedure to segment these patients into distinct groups, according to their emotions (anger, disgust, fear, happiness, sadness and surprise), sentiment and their overall satisfaction with knee replacement surgery. Our findings show how qualitative online data can be transformed into quantitative insights regarding underlying market segments, which could then be targeted through different strategies by both marketers and healthcare practitioners.