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The purpose of this paper is to explore how both gender and facial attractiveness affect job candidates’ chances of obtaining interviews in China’s dynamic internet job board labor market. It examines how discrimination based on these attributes varies over occupation, location, and firms’ ownership type and size.

The authors carry out a resume audit (correspondence) study. Resumes of fictitious applicants are first carefully crafted to make candidates appear equally productive in terms of their work histories and educational backgrounds. The authors control gender and facial attractiveness. The authors establish the facial attractiveness of candidate photos via an online survey. In total, 24,192 applications are submitted to 12,096 job postings across four occupations in six Chinese cities. Callbacks are carefully tracked and recorded. Discrimination is estimated by calculating the differences in the rates of callbacks for interviews received by individuals whose applications vary only in terms of facial attractiveness and gender. The authors reuse the same resumes repeatedly through this project such that names and photos of each of the candidates: attractive man, attractive woman, unattractive man, and unattractive woman is attached to each resume hundreds of times for each occupation in each city.

The authors find sizable differences in the interview callback rates of attractive and unattractive job candidates. Job candidates with unattractive faces need to put in 33 percent more applications than their attractive counterparts to obtain the same number of interview callbacks. Women are preferred to men in three of the four occupations. Women, on average need put in only 91 percent as many applications as men to obtain the same number of interview callbacks.

The analysis of this paper focusses on only four different occupations. Its scope is also limited to exploring only the first part of the hiring process – obtaining a job interview. Furthermore, its fictitious applicants are all young people, approximately 25 years old. It would be useful to explore how gender and facial attractiveness affect candidates’ chances of landing a job after getting an interview.

This paper contributes to and expands the literature on hiring through China’s internet job boards. It also contributes to the literature on the role of facial attractiveness in hiring.

The rapid proliferation of mobile context aware applications has resulted in an increased research interest towards developing specialized context data management strategies for mobile entities. The purpose of this paper is to aim to develop a new way to model mobile entities and manage their contexts accordingly.

This paper proposes the concept of “Mobile Space” to model mobile entities and presents strategies to manage the various contexts associated therein. To handle availability related issues, two system services are designed: the “Availability Updating Service” which is an identifier based mechanism and is designed to keep track of mobile objects and handle availability related issues, and the “Application Callback Service” which is a publish/subscribe based mechanism to handle application disruptions and interruptions arising due to mobility.

The paper presents a detailed study of the proposed framework and a description of the underlying services and the components therein to validate the framework. Experimental results carried out in WiFi and 3G environments indicate that the proposed techniques can support mobile applications and minimize application disruptions with minimal overhead.

The proposed context management framework is generic in nature and is not designed for a specific class of applications. Any mobile context aware application can leverage on the framework and utilize the provided functionalities to manage application disruptions. Also, the decoupling of mobile application layer and the underlying context data management layer renders context data management layer transparent to the application design.

Are White and Asian job applicants advantaged in access to professional jobs relative to Black and Latinx job applicants at the initial screening stage of the hiring process? And, are the mechanisms of advantage for White applicants different than the mechanisms for Asian applicants? In this chapter, the author proposes a theoretical framework of “parallel mechanisms” of White and Asian advantage during hiring screening – that White and Asian applicants are advantaged compared to Black and Latinx applicants, but that the mechanisms of advantage subtly differ. The author focuses specifically on mechanisms related to two important factors at the hiring interface: referrals and educational attainment. The author applies the concept of parallel mechanisms to a case study of software engineering hiring at a midsized high technology firm in Silicon Valley. The author finds that at this firm, White applicants are advantaged at initial screening relative to Black and Latinx applicants due to average racial differences in applicant characteristics – namely having a referral – as well as differences in treatment by recruiters. For Asian applicants, average racial differences in possession of elite educational credentials, as well as racial differences in recruiter treatment, explain the racial disparity in callbacks. The author discusses the implications of parallel mechanisms of advantage for racial inequality in a multiracial context, and for organizational policy meant to address racial disparities during organizational hiring processes.

This paper aims to propose an open service access (OSA) service capability server (SCS) architecture that supports the network capabilities to the Application Server (AS).

Based on this architecture, the service capability feature (SCF) provides the OSA Application programming interface functions by implementing the SCF service logic module and callback module. The SCF uses the XML communication module to interact with service capability (SC), which is the bearer to realize services by implementing the SC service logic module. The SC service logic interacts with mobile core network through the session initiation protocol (SIP)‐based session control module and the SIP Callback module.

The push to talk over cellular service is used to illustrate how the proposed OSA SCS interacts with the AS and the mobile core network elements.

In the design, when implementing a new service (i.e. to create a new SCS), one only needs to create the Callback module and the Service Logic modules, and other SC/SCF modules can be reused.

Through this modulized SCS design, the OSA service deployment can be speeded up.

The purpose of this paper is to investigate whether there is unequal treatment in hiring depending on whether a job applicant signals living in a bad (deprived) neighborhood or in a good (affluent) neighborhood.

The authors conducted a field experiment where fictitious job applications were sent to employers with an advertised vacancy. Each job application was randomly assigned a residential address in either a bad or a good neighborhood. The measured outcome is the fraction of invitations for a job interview (the callback rate).

The authors find no evidence of general neighborhood signaling effects. However, job applicants with a foreign background have callback rates that are 42 percent lower if they signal living in a bad neighborhood rather than in a good neighborhood. In addition, the authors find that applicants with commuting times longer than 90 minutes have lower callback rates, and this is unrelated to the neighborhood signaling effect.

Empirical evidence of causal neighborhood effects on labor market outcomes is scant, and causal evidence on the mechanisms involved is even more scant. The paper provides such evidence.

The purpose of this paper is to assess field experiments of labour and product markets that have attached photos to identify applicants (in the case of labour markets) or sellers/crowd funders (in the case of product markets).

The experiments seek to identify the contribution of attractiveness, race/ethnicity, skin colour, sexual orientation or religion to the behaviour of agents in markets. These experiments attach photos to CV to signal attractiveness, or the basis of being tested such as race/ethnicity, skin colour or religion.

Many experiments report significant findings for the impact of attractiveness or the identity revealed on positive callbacks to applicants.

The issue considered here, however, is to what extent it is attractiveness or other perceived characteristics that may have had an impact on the behaviour recorded in the experiments. The results of the studies covered in this paper, to a lesser extent those of Weichselbaumer (2004) and Baert (2017), are compromised by including photos, with the possibility the responses received were influenced not only by the basis being tested such as attractiveness, race/ethnicity or religion but by some other characteristic unintended by the researcher but conveyed by the photo.

There is evidence in the experimental work of a range of characteristics that photos convey of individuals and their impact on labour and product market outcomes such as success in obtaining a positive response to job applications and success in obtaining funding to finance projects in the product market. Suggestions are made for future experiments: evaluation of photos for a range of characteristics; use of a “no photo” application together with the photo applications; and evaluation of responses for any bias from unobservable characteristics using Neumark (2012).

This paper discusses for the first time three questions with some tentative answers. First, the researcher faces introducing further unobservable characteristics by using photos. Second, the researcher cannot fully control the experimental approach when using photos. Third, the researcher is able to accurately evaluate the impact of the photos used on the response/probability of call back. Field experiments using photos need to ensure they do this for the range of factors that have been shown to affect judgments and therefore potentially influence call back response. However, the issue remains whether the researcher has, in fact, identified all potential characteristics conveyed by the photos.

Open service access (OSA) is a flexible and efficient approach for mobile service deployment. In OSA, network functionality offered to application servers (ASs) is defined by a set of service capability features (SCFs). The AS implements services by accessing the service capability through the standardized OSA application programming interface.

The paper shows how the AS provides services by integrating the services supported by the SCFs. Then it uses the OSA mutual authentication and the push to talk over cellular service to illustrate the interaction among the AS modules and how the AS interacts with the framework and the SCFs.

With this environment, the service developers are not required to access the details of the underlying mobile network, and thus the service deployment can be sped up. The purpose of this paper is to propose an AS architecture.

This paper proposed an OSA AS architecture. Based on this architecture, a new application is created by implementing the appLogic module that invokes the SCFs through the appService modules and appService callback modules.

This paper tests whether employers responded particularly negatively to African American job applicants during the deep U.S. recession that began in 2007. Theories of labor queuing and social closure posit that members of privileged groups will act to minimize labor market competition in times of economic turbulence, which could advantage Whites relative to African Americans. Although social closure should be weakest in the less desirable, low-wage job market, it may extend downward during recessions, pushing minority groups further down the labor queue and exacerbating racial inequalities in hiring. We consider two complementary data sources: (1) a field experiment with a randomized block design and (2) the nationally representative NLSY97 sample. Contrary to expectations, both analyses reveal a comparable recession-based decline in job prospects for White and African American male applicants, implying that hiring managers did not adapt new forms of social closure and demonstrating the durability of inequality even in times of structural change. Despite this proportionate drop, however, the recession left African Americans in an extremely disadvantaged position. Whites during the recession obtained favorable responses from employers at rates similar to African Americans prior to the recession. The combination of experimental methods and nationally representative longitudinal data yields strong evidence on how race and recession affect job prospects in the low-wage labor market.

This article deals with the impact of ethnic origin on individual employability, focussing on the first stage of the hiring process. Deeply, the authors’ goal is to fathom whether there is a preference for native job candidates over immigrants, decomposing the discrimination against minority groups into its statistical and taste-based components by means of a new approach.

The authors built up a data set by means of an ad hoc field experiment, conducted by sending equivalent fictitious CVs in response to 1000 real online job openings in Italy. The authors developed the discrimination decomposition index using first- and second-generation immigrants.

The authors’ main result is that both first- and second-generation immigrants are discriminated compared to Italians. In between the two categories, second-generation candidates are discriminated especially if their ethnicities are morphologically different from those of natives (i.e. Chinese and Moroccans). This last finding is a clear symptom of discrimination connected to taste-based reasons. On the other hand, first-generation immigrants of all nationalities but Germans are preferred for hard-work jobs.

The authors develop the discrimination decomposition index to measure the proportion of the two kinds of discrimination (statistical and taste-based) over the total one and apply a probit model to test the statistical significance of the difference in treatment between the three groups of natives, first-generation and second-generation immigrants.

The main goal of this paper is to test whether older Hungarian women face age discrimination in the job market. The theoretical framework of this paper measures the level of discrimination and highlights that age discrimination leads to a waste of human resources.

Two pairs of fictitious CVs were created; each pair included a younger (34 years old) and an older woman (60 years old) with an age difference of 26 years. One pair was designed for office assistant positions, the other for economic analyst positions. The contents of the CVs with photos were entirely fabricated except for active email addresses and phone numbers to allow responses to be tracked. LinkedIn accounts were also created for the analysts. Applications were sent over a four-month period from November 2019. The rate of invitation to interviews was analysed with mathematical statistical methods and a small probability model.

The younger job seekers were invited to interviews about 2.2 times more often than the older ones. Based on the authors’ probability model, employers evaluate the skills of older applicants at only 45–67% of their actual skills.

The experiment had to be stopped due to the Covid-19 lockdown as there were no new job postings.

The experiment demonstrates that age discrimination exists in Hungary. In addition to traditional audit job applications through HR portals, we used LinkedIn too. The small probability model applies an old framework in a new environment.