OSIPP Discussion Paper : DP-2019-E-012
JOB FAIRS AND PERCEPTIONS OF COMPANY ATTRACTIVENESS:
EVIDENCE FROM JAPANESE COMPANIES RECRUITING OVERSEAS
November 28, 2019

Yani Karavasilev1
Research Fellow, Asia Pacific Institute of Research
Chika Yamanami2
Diversity & Engagement Dept., Sony Corporate Services Corporation
Miki Kohara3
Osaka School of International Public Policy, Osaka University
ABSTRACT: Research on impression management has continuously highlighted theimportance of a company’s brand equity in attracting talent. Whereas the determinants ofcompany attractiveness are well documented, less is known about the effects of recruitment
tactics, particularly in non-Western settings. We investigated these effects using survey
data from 13 Japanese multinational companies (MNCs) and 436 international job seekers
collected before and after a large-scale career fair held in Singapore in 2017. The
unconventional setup of the fair allowed us to conduct the survey in a semi-experimental
setting. Using endogeneity-robust linear, logit and probit models, we found that recruitment
tactics significantly affect perceptions of company attractiveness regardless of job seekers’
pre-existing beliefs. The effect is larger in cases of high person-organization fit. The
mechanism modulating this effect is the image of personnel heterogeneity a company is able
to project through the characteristics of its recruiting staff. We identify the key dimensionsof heterogeneity and provide estimates of the optimal personnel heterogeneity levels. Ourfindings build on previous research on targeted recruitment in Western settings, showingthat the success of international recruitment is contingent not only on fixed firm
characteristics, but also on a firms’ impression management tactics throughout therecruitment process.
KEY WORDS: Impression management, job matching, job fairs, international recruitment,
company image, optimal staff heterogeneity
JEL CODES: M5, J5karavasilev-y@apir.or.jp; Research Fellow, Asia Pacific Institute of Research, Knowledge Capital
Tower C, Grand Front Osaka, 3-1 Ofuka-cho, Kita-ku, Osaka 530-0011, Japan
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Chika.Yamanami@sony.com; Diversity & Engagement Dept., Sony Corporate Services Corporation
kohara@osipp.osaka-u.ac.jp; Osaka School of International Public Policy, Osaka University
The authors are affiliated with the School of International Public Policy at Osaka University. They are grateful tocomments received by Prof. David G. Allen, Editor-in-Chief of the Journal of Management during the 9thInternational Research Meeting in Business and Management in Nice, France, as well as to comments by Prof.
Masayuki Kudamatsu (Osaka University), Prof. Harald Conrad (University of Sheffield) and Prof. Hendrik
Meyer-Ohle (National University of Singapore). They are also grateful to the organizers of the ASEAN Career Forumin Singapore. The survey conducted for this study was financed by JSPS Kakenhi Grant Number JP15K03512. The
authors declare that they have no relevant or material financial interests that relate to the research described in thispaper.

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INTRODUCTION
There is a consensus in academic literature that a company’s success is impingent upon the quality andthe productivity of its workforce. These are affected by numerous variables, but three categories stand out
the most in existing human resource management (HRM) literature: incentives, work organization andrecruitment practices. For more than four decades academic literature mainly focused on the former two(Oyer & Schaefer, 2011; Griffeth, Tenbrink & Robinson, 2013). Accordingly, whereas how a firm canmotivate an employee has largely been understood, meta studies have shown that existing empiricalliterature supplies significantly less evidence on how a firm should go about finding the right employee inthe first place (Chapman, Uggerslev, Carroll, Piasentin, & Jones, 2005; Rynes & Cable, 2003). In view ofthis, and of increasing employee turnover accompanying the decline of lifetime employment worldwide,
academic attention has increasingly shifted toward the topics of recruitment and job search, especiallytargeted recruitment of minority, international and highly skilled candidates. (Dineen & Soltis, 2011;
Rynes-Weller Reeves & Darnold, 2013; Darnold & Rynes, 2013; Breaugh, 2014). The relevance of thisresearch area became evident with the publication of the Oxford Handbook of Recruitment in 2013, which
provides a thorough review of existing theories and research.
An in-depth inspection of recruitment-related literature reveals that how companies are perceived andevaluated by prospective candidates is crucial for attracting talent. Academic publications on bothjob-search and recruitment have continuously highlighted the importance of a company’s image (brandequity) in attracting talent (Theurer Tumasjan, Welpe & Lievens, 2016; Da Motta Veiga & Turban, 2014;
Collins & Kanar, 2013; Collins, 2007; Chapman et al., 2005; Cable & Turban, 2003; Turban & Cable,
2003). In fact, impression management (IM), defined as “the conscious or unconscious attempt to control
images that are projected in real or imagined social interactions” (Schlenker, 1980: 6), has been one of themost studied topics in HRM literature in the last two decades. Although the majority of IM studies havefocused on the job applicants’ personal IM (PIM) and the outcomes of employment interviews (Scandura2

& Williams, 2000; Tsai & Huang, 2013), another line of organization-level IM research has been attracting
academic attention. Known as ‘organizational impression management’ (OIM), it has been defined as “anyaction purposefully designed and carried out to influence an audience perception of an organization”(Elsbach, Sutton & Principe, 1998: 68). Within the recruitment context it can be understood as therecruitment tactics adopted by a firm to modify its image in the eyes of job seekers and thereby influence
their job application intentions. Recruitment-related OIM research, however, has remained limited, as
early literature (e.g. Powell, 1984; Taylor & Bergmann, 1987) suggested that recruitment tactics play only
a minor role in affecting applicant decisions (Bolino, Kacmar, Turnley & Gilstrap, 2008). Accordingly,
while the determinants of employer attractiveness have been thoroughly researched both empirically andtheoretically, there has been little research on how companies can modify these perceptions. The
overwhelming majority of studies related to job matching focus on the former, and tend to either (1)compare the characteristics of different companies and identify which of them make a firm more attractivein general, or (2) explore the personal characteristics of job applicants with the purpose of determining
what kind of candidates are attracted to certain companies, without specifically addressing the issue of
how the way a single company can modify the image it projects in the eyes of job seekers. Job seekers’
attitudes, in turn, have also been tacitly treated as non-modifiable (Chapman et al., 2005).
Consequently, one of the biggest challenges in IM research is to disentangle the effects of a firm’s
non-modifiable characteristics from those of a firm’s recruitment tactics (Challenge 1), especially in viewof the fact that more recent studies indicate that recruiters play a significant role in applicant job choice(Chapman et al., 2005), and that this influence is most pronounced in the case of highly skilled candidates
with multiple job offers. Since research in this area could have important implications for the selection andtraining of a firm’s recruiting personnel, the main goal of this study is to investigate whether a firm’s
recruitment tactics can help improve its attractiveness as an employer in the eyes of job seekers, and if yes,through what channels.

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In doing so, it is indispensable to consider both sides of the job matching process, which we identified
to have been another major challenge in existing empirical literature (Challenge 2). Integrating therecruitment perspective, which refers to a company’s hiring tactics, and the job search perspective, which
focuses on job seekers’ employment search activities. While literature on either side of the job matchingprocess abounds, few scholars have addressed empirically the challenge of integrating the two sides of thejob matching process. Notwithstanding the necessity to incorporate these two perspectives into one
academic endeavor has become increasingly salient, as both applicants’ and recruiters’ assessments of fit
play an important role in organizational entry (Da Motta Veiga & Turban, 2014; Kristof-Brown Reeves &Follmer, 2013), this has eluded most existing empirical research, owing to the difficulty of collecting datafrom both sources. Considering this, one of the major motivations for this study is to integrate both
perspectives by collecting responses to identical questions from employers and job seekers alike in asetting where both parties have almost symmetric information about each other.
Another major challenge faced by empirical research on job matching is related to the applicability toreal-world settings, considering the survey methods used so far (Challenge 3). Existing empirical researchon recruitment practices tends to study job seekers’ attitudes and behavioral intentions more than theiractual behaviors utilizing mostly content analysis-based policy capturing methods or controlled laboratory
experiments. Due to the use of such methodologies, most studies do not clearly delineate among the
temporal and sequential processes of recruitment, which also raises concerns about endogeneity issues(Rynes-Weller et al., 2013; Carlson & Mecham, 2013), as well as questions about the validity of findings
in a real-life context. Consequently, this study utilizes a field survey rather than policy capturing methods
or a controlled laboratory experiment, which is a major advantage over previous studies. Using a sample
of real job seekers, we analyzed their actual behaviors (we collected information on whether they applied
or interviewed with the companies they evaluated), and we investigated how subjects’ perceptions
changed before versus after being exposed to a company’s recruitment activities on the recruitment day,4

which adds a clear temporal dimension to our survey while restricting the scope of the survey to the initialpart of the job-matching process.
Last but not least, the overwhelming majority of existing empirical research is focused on domestic
recruitment in Western settings, especially the US (Chapman et al., 2005), which raises questions as towhat extent findings are applicable to non-Western settings. Another major challenge, therefore, is toextend the generalizability of existing findings (Challenge 4). We address this issue by providing evidence
from international recruitment in a non-Western setting, namely Japanese multinational corporations
recruiting in the ASEAN region. This was done in view of the fact that the ASEAN has become by far themost preferred region for international recruitment by Japanese companies. The ratio of Japanese firms
wishing to employ ASEAN nationals has almost doubled since 2014, reaching 76%, a ratio far larger thanany other region’s, including China, which had long been the traditional source of foreign labor forJapanese firms. The number of ASEAN workers increased dramatically between 2001 and 2016: theproportion of visas issued to ASEAN nationals among all foreign workers jumped from 5% to 24% in that
period (DISCO, 2018). In addition, despite being the backbone of a major developed economy, Japanesefirms are lagging behind their Western counterparts in attracting skilled foreign workers. Although thecase of ageing and labor-scarce Japan is of particular relevance to the topic of international recruitment,with multinational enterprises increasingly focusing on Southeast Asia as a source of talent, academic
research on this topic is virtually non-existent. To the best of our knowledge, this study is the first
empirical endeavor to provide that missing piece of evidence.
The rest of the paper is organized as follows: the next section provides background on major theoriesof the interaction between organizational image and perception changes, and introduces our hypotheses
and empirical model. Section three introduces the survey design and the data we collected, and section
four presents the results from the empirical analysis. Section five concludes with some recommendations
concerning recruitment practices, and discusses the limitations of this study while suggesting potential

5paths for future research.

THEORETICAL BACKGROUND AND HYPOTHESES
Since the main concern of this study is to address the issue of changing perceptions of a company’s
image, as well as to identify the existence of any tactics during the recruitment process that a company canemploy in order to improve its perceived attractiveness as an employer in the eyes of prospective
candidates, a review of major theories related to changes in perceptions and attitudes is essential forformulating testable hypotheses. As mentioned, the majority of exiting studies explore the impact of
non-modifiable company and applicant characteristics on organizational attractiveness and job application
intentions. Job candidates’ attitudes tend to be seen as an extension of their personal values, and are either
not viewed as manipulable, or at least their modifiability has not been seen as a key factor in the job
matching process so far. According to various theories however, it is possible for a company to influencecandidates’ perceptions. As these theories come from disciplines ranging from labor economics to social
psychology, their validity in recruitment settings has not been tested systematically. A key contribution ofthis study is that it validates empirically some of the most prominent of these theories in a recruitment
context, and provides evidence of the exact channels through which they work. The most influential andrelevant theories, selected after a comprehensive review of the Oxford Handbook of Recruitment (2013),
are discussed in the following paragraphs.

The Elaboration Likelihood Model and Media Richness Theory
The Elaboration Likelihood Model (ELM) was developed in the social psychology literature to explain
the cognitive processes associated with persuasion (Petty & Cacioppo, 1981, 1986a, 1986b). The
framework postulates that processing persuasive message is influenced by the extent to which individuals
have the ability and motivation to process the message itself. When both ability and motivation are high,6message recipients are likely to centrally process the persuasive message, and evaluations are based on thecontent of the message. Conversely, when either processing ability or motivation is lacking, evaluations
are based on positive or negative reactions to peripheral cues associated with the message, such as themedium of communication or the message source, i.e. the communicator (Hovland, Janis & Kelly, 1953).
Since peripheral processing involves less thought-related effort than central processing, it leads to lessstable attitudes. For example, with regard to job advertisements, academics have argued that message
content and design affects job seekers’ motivation to process. As such, job advertisements have thepotential to influence important outcomes such as P-O fit perceptions (Roberson, Collins & Oreg, 2005),
organizational attractiveness (Walker, Field, Giles & Bernerth, 2008) and effort expended to evaluate thejob ad itself (Jones, Schultz & Chapman, 2006). We interpret recruitment activities as modifiable
peripheral routes of attitude formation, as graphically represented in Figure 2, and we aim to test the
hypothesis that these activities can be thought of as ‘persuasive messages’ within the ELM framework,
which can be instrumental in enhancing the attractiveness of a company in the eyes of job seekers.

-----------------------------Figure 1 about here------------------------------In order to empirically test the validly of the claim that company attractiveness is modifiable, we
considered all recruitment types discussed in existing literature. An exhaustive list of these was provided
by Miller & Guo (2013), who identify twelve categories of recruitment practices: (1) ads in the media, (2)job rotation/transfer, (3) direct/walk-in, (4) employee referrals/word of mouth, (5) college campus
recruiting, (6) employment agencies, (7) internal recruitment/promotion, (8) online recruiting, (9) job fairs,(10) internships/temp jobs, (11) inheritance of jobs, and (12) government appointment.

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Of these, (1), (5), (8) and (9) would be the most suitable settings to test the peripheral routemechanism described in Figure 1, as in the other case either the motivation on either side of the job
matching process is asymmetric (walk-ins, referrals) or completely absent (inheritance, appointments), or
the condition of a short-term exposure not satisfied (internships). Since we would like to exclude theeffects of intermediary (non-company) recruiters, we do not consider employment agencies either.
Drawing from the Media Richness Theory (MRT), which posits that communication effectiveness isdependent on the stimulus transmission capacity, i.e. the ‘richness’ of a medium of communication (Daft& Lengel, 1984; 1986), with richer media being characterized by (1) the opportunity for two-way
communication, (2) the ability to convey multiple cues (i.e. nonverbal), (3) the ability to convey a sense of
personal focus (i.e. warmth), and (4) language variety (Schmitz & Fulk, 1991), we exclude print ads andonline recruiting, as these do not possess these characteristics, and are therefore suboptimal for detecting
the effects of peripheral routes. Allen, Van Scotter, J. R. & Orondo (2004) applied MRT in a recruitment
context and showed that the media used to communicate recruitment information significantly influenced
job applicants’ perception of the amount of information presented, personal focus, social presence andsymbolism. Furthermore, Cable & Yu (2006) found that career fairs were rated higher in perceived
richness than company web sites or electronic bulletin boards.
The abovementioned considerations imply that the best way to test the ELM mechanism in the job
matching context would be campus recruitment or a career fair. We choose the latter, as they are usually
not as targeted in terms of institutions and majors as college campus recruitment. In addition, job fairs
have already been found to serve as an important source of information on companies and could therefore
influence prospective applicants’ reputation perceptions (Da Motta Veiga & Turban, 2014; Collins, 2007;
Barber, 1998). Considering this, we conclude a career fair is the best setting to investigate changes inperceptions of company attractiveness, and we formulate our first testable hypothesis.

8Hypothesis 1: Job fair recruitment activities, being rich in stimuli and information transmission paths,
can act as a peripheral route of attitude formation, thereby enhancing the attractiveness of a company
regardless of pre-existing attitudes.

Assuming job fairs are instrumental in enhancing a firm’s attractiveness as an employer, the next stepis to establish the precise mechanism of perception changes. Since peripheral routes could be any
combination of factors ranging from recruiters’ behaviors, their physical characteristics, the amount of
information provided, the information medium, the scale of the presentation, etc., we draw from empiricalresearch on targeted recruitment in order to narrow down the scope of potential factors and formulate atestable hypothesis concerning the peripheral route mechanism.

Targeted Recruitment and Signaling Theory
Empirical research on targeted recruitment, which is overwhelmingly focused on racial or ethnic
monitories in Western settings, is largely based on the premises of the Signaling Theory proposed by
Spence (1973) addressing the issue of information asymmetry in job matching. In this model potential
employees send a signal about their ability level to the employer by acquiring education credentials.
Education is manipulable by an applicant and is referred to as a ‘signal’. It is differentiated from
non-manipulable attributes, such as age, for example, referred to as an ‘index’. On the basis of previous
experience of the market, the employer is supposed to have conditional probability assessments overapplicants’ productive capacity given a certain combination of indices and signals. The employer updates
his beliefs by observing the employee characteristics.
In the context of job search, the theory treats job seekers as the employer in Spence’s model, andpostulates that since early in the recruitment process job seekers know little about potential employers,
they rely on environmental cues (indexes and signals) during the recruitment process to update their9beliefs (Rynes, 1991). Several scholars have conducted empirical research on what these environmental
cues might be, especially in the context of job advertisements, which have been shown to signal unknown
organizational attributes, especially when it comes to diversity.
Most prominently, a number of studies by Avery and colleagues demonstrate that minority job seekers
are more attracted to organizations when they are presented with evidence that the organization welcomesminorities (Avery, Hernandez & Hebl, 2004; Avery, 2003). Companies might be perceived as more
attractive by minority, international or female seekers if they ingratiate these job seekers in job ads orincrease demographic diversity in ads (Avery & McKay, 2006). Volpone, Thomas, Sinisterra & Johnson(2013) review the literature surrounding tactics related to targeted (minority) recruitment and establish thatdiversity messages and images in formal recruitment advertisements have a significant impact on minority
applicants’ behavior.
We extend this theory to international instead of minority job seekers, and investigate whether thisholds true for ASEAN job seekers who would like to work for Japanese companies. Based on the
Signaling Theory, we expect that the characteristics of recruiters will have a major impact on an
applicant’s perception of the recruiter’s company, especially when it comes to diversity, which is our
second testable hypothesis.

Hypothesis 2. A company can improve its desirability as an employer by projecting a more diverse
working environment to international job seekers.

We measure diversity by coding the perceived gender, nationality and seniority level/perceived age ofthe recruiters representing the company, and approachability by the ratio of recruiters dressed relatively
casually (i.e. not wearing suits) at the career forum. Although the dimensions of diversity andapproachability are admittedly subjective, we are more concerned with defining these in opposition to the10traditional image of a Japanese firm, whose typical representative is a male Japanese formally dressed
middle-aged/senior employee.
Importantly, since we are reversing the original scenario of Spence’s signaling paradigm, we treat allobservable characteristics of company representatives at the job fair as ‘signals’, as opposed to a mixtureof signals and indexes. Since every participating company can make conscious decisions regarding theobservable characteristics of the recruiters they dispatch to the fair as representatives of the firm,
characteristics such as age, race and gender are in this case manipulable, and hence viewed as signals.

The Person-Organization Fit Framework
The Person-Organization (P-O) Fit framework emphasizes the importance of the congruence between
job seeker characteristics and recruiting organization characteristics in the former’s evaluation of potential
employers. Early HRM research suggested that individuals define themselves in terms of organizational
membership when their perceptions of fit are high (Ashforth & Mael, 1989; O’Reilly, Chatman &Caldwell, 1991), and empirical studies generally support these predictions.
In the recruitment context, the theory suggest that information provided during the recruitment process
helps candidates assess P-O fit, and affects organizational image and job decisions. Cable & Judge (1997)
have shown P-O fit is more important for hiring decisions than person-job (P-J) fit. Empirical studies
show that enhanced P-O perceptions can influence job choice decisions (Walker & Hinojosa, 2013), andformal information sources, such as job advertisements, have been related to job applicants’ P-O fit
perceptions (Saks & Ashforth, 1997; Cable & Judge, 1996). Therefore, based on the P-O fit framework,
the third testable hypothesis was formulated in the following way:

Hypothesis 3: The impact of factors influencing changes in perceptions is larger for applicants who
are an objectively good fit for the company (high P-O candidates).

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It should be noted that in this study ‘fit’ is defined as a mix of skills and personal characteristics.
Accordingly, no specific mentions of skills or personal characteristics were made in the survey, using theword ‘strength’ instead. This was done with the intention of removing the effects of any potential
intervening variables related to whether applicants and companies emphasize personal qualities versus
skills during the job-matching process. This is considered particularly relevant in the case of Japanesefirms, which traditionally hire for organizational fit, based on the premise that skills can be taught but
personalities are innate (Robinson, 2003), which might be different from recruitment cultures in othercountries, like the ones in ASEAN, which are focus of our analysis.

METHODOLOGY
The empirical investigation was based on data collected via a job seeker survey, a company survey andan independent evaluation of company booths during the ASEAN Career Fair (ACF) held in February
2017 in Singapore. The job fair has been held annually since 2013, and is organized collaboratively by the
ASEAN Career Fair Japan Committee (Energize Inc. & Global Human Capital Corp.), the JapaneseChamber of Commerce in Singapore, the ASEAN University Network, and Osaka University, including
the authors of this paper. As organizers, we had the opportunity to conduct large-scale surveys among the
13 well-known Japanese companies and 604 prospective applicants from the ASEAN region who attended
the fair. The average job seeker visited 40% of all booths, which approximates the ACF setting to an ideal
experiment-like scenario of having all subjects attend all booths. In addition, the fact that all 13 companies
are Japanese reduces the likelihood of self-selection. At a job fair featuring a mix of Japanese andnon-Japanese firms, job seekers who are interested in working for the former will self-select into attending
only the booths of Japanese companies, and even if they do not, they might be biased to report better
attitudes towards them. In this case, every attendee is interested in working for Japanese companies by

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default, and compares the recruitment methods of attending companies only to those of similar companies.
All these characteristics of the ACF fair make our sample especially well-suited for analyzing the effects
of impression management.

Data collection: Job Seekers
Upon entering the venue, all 604 attendees were handed a survey (response rate n=436, 72.2%)
inquiring about their skills, values, job preferences, social status, opinions about Japanese firms and mostimportantly, their evaluation of the image of participating companies before and after attending theirbooths on a five-point Likert Scale, which was used as the main dependent variable in the econometricmodel (a relevant excerpt from the survey is available in Appendix B). The survey was distributed at theentrance prior to front desk registration, and was collected upon leaving at a collection point located at the
only entrance to the venue. As organizers, we were able to locate the survey collection point in a key andprominent location, between the front desk and the company booths, which played an important role inattaining a high response rate. Job seekers were kindly asked to complete the survey, with specificinstructions to answer the ‘before’ and ‘after’ parts of company evaluation question respectively before
and after visiting the company booths. Applicants were told that upon completing the survey they would
be provided with a modest gift (e.g. a pen, a clear file, etc.). In order to further stimulate the survey
response rate, participants were informed that a number of additional gift stickers has been randomly
inserted into the files containing the survey, so that the respondents who had a sticker in their file would
receive an additional present. Although some of the surveys were not answered completely, the overall
response rate was quite high at 72.2%.

Data collection: Recruiters
The survey distributed to the representatives of the participating companies, on the other hand,13consisted of two parts. The first part consisted of four questions concerning the company, including whatskills and personal characteristics were considered desirable in prospective candidates. These questions
were identical to ones the one job seekers were asked, and they were used later to create our highperson-organization (P-O) fit subsample. The second part of the survey contained nine questions inquiring
about the recruiter’s personal characteristics and their evaluation of various aspects of Japanese companies
in general. Those questions were also identical to the ones the job seekers were asked but they were notused in creating the high P-O fit subsample. 50 representatives of the 13 companies received the survey,
and the response rate was 100 %.
In addition to the survey, four trained coders affiliated with Osaka University recorded thecharacteristics of the attending companies’ booths at the fair (e.g. number of company representatives,
their seniority level (perceived age), gender, dress, visual characteristics, presentation methods, etc.) atthree different points in time (at the beginning, the middle and the end of the fair). Information such as theappearance of the recruiters at the booth, the number of job seekers looking at the booth, the availability ofparaphernalia, brochures, presentation methods, available information etc. was recorded for every booth.

Creating the High Person-Organization Fit Subsample
The question used to establish the presence of a high P-O fit level between companies and job seekers
was about the strengths (i.e. a mixture of personal qualities and skills, as discussed in the previous section)
they were looking for and able to offer, respectively. Both recruiters and applicants were asked to select up
to three items. Respondents were able to select among 15 skills and traits, carefully selected based onnationwide surveys inquiring Japanese employers about their demand for human resources conductedby DISCO (2018) and other recruitment support providers (Energize Inc. etc.), and they were able to add
their own to the list (the full list is available in Appendix A).
Since respondents were asked to select only up to three skills or traits, if one of the items that an

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applicant indicated coincided with an item a company representative selected, it was considered a match.
Although the theoretical probability of a match is quite low, the actual matching rate was 73.9 %,reflecting the careful and targeted selection of the attending job seekers. 5% of all responses (7% of allmatches) were complete three-skill matches, meaning all three skills a company representative and acandidate chose were identical.
Since the high P-O fit subsample is a major element of this study, all descriptive statistics hereafter are
shown for the entire sample, as well as for the “lower P-O fit” versus “higher P-O fit” sub-samples, i.e. forcandidates who had no skills or traits matching any of those that any of the companies were looking for,versus candidates who had at least one such skill or trait. The descriptive statistics, discussed next, reveal
no significant differences between lower versus higher P-O fit candidates.

Descriptive Statistics: Job Seekers
The valid sample of job seekers consisted of 436 respondents from the ASEAN region, most of themfinal year undergraduate and graduate students from top-ranking universities across ASEAN countries. A
special feature of the ASEAN Career Fair was that access was not open to anyone. Attendees are selectedbased on several criteria, most importantly their GPA, the ranking of their university and theirself-reported English proficiency. Japanese language skills were not required in order to participate in theevent – in fact 40% had zero proficiency in Japanese. Applicants who were selected to take part in theevent were eligible to receive up to USD 200 as a reimbursement to help cover travel expenses from theirrespective country to the venue in Singapore. In this way, the sample of job seekers was limited only topeople who 1) are originally from the ASEAN region (including a few Chinese and Indian nationals
studying in ASEAN countries), 2) are interested in working for Japanese companies and 3) have an
excellent academic record.
Table 1 shows the descriptive statistics of the job seekers. The sample is well-balanced in terms of15

genders, majors and nationalities. All parts of the ASEAN region were represented in a relatively
proportional way, with Indonesians, Malaysians and Singaporeans cumulatively accounting for about 60%
of all respondents, and Filipinos, Vietnamese, Chinese and Thai respondents comprising another one-third.
The average number of booths an applicant visited was 5. 65% of respondents reported an improved
impression of the companies after attending the fair, 25% reported no change, and less than 10% reported
a deterioration in their impression.

-----------------------------Table 1 about here------------------------------

While otherwise balanced, the sample is conspicuously homogeneous in terms of geographicallocation and skill-level. By targeting only highly skilled job seekers from a region which has rather
uniform in work-related values (authors’ observations based on the World Values Survey), the cultural andskill-level heterogeneity of the sample was minimized, making it unnecessary to include an excessive
number of control variables in the estimation. Considering that applicant heterogeneity has often been
cited as a major impediment to conducting empirical investigations on hiring practices (Oyer & Schaefer,2011), our relatively homogeneous sample could be considered a unique advantage of our dataset.
Another unique advantage of our sample is that it allows for a semi-experimental setup. Althoughattending job seekers are generally interested in working for Japanese companies, Japanese companies are
not necessarily their first choice: about half (58%) reported that if they were to choose the nationality of
the company they would like to work for, a Japanese company would be their top preference (multiple
answers were not possible). The fact that the average job seeker in the sample tends to be on the fence
when it comes to choosing Japanese versus employers of other nationalities, suggesting that their attitudes

16are relatively malleable, allowed us to examine the effects of recruitment-day activities with a high levelof statistical validity. This would not have been the case if every subject in the sample was firmly
determined to work for a Japanese company.

Descriptive Statistics: Recruiters
The sample of recruiters, on the other hand, included 50 representatives of all 13 participatingcompanies. A unique feature of ACF is that due to the small number of companies, unlike other fairs,
participants do not go there solely for a pre-arranged interview, but rather for a window-shopping-style job
search. For example, in the case of some of the largest career fairs featuring Japanese firms overseas, suchas the Boston Career Forum, the large number (n>250) and the high level of heterogeneity of participating
firms (Japanese, American, European) do not allow for this kind of setup. Instead, most job seekers havethree to four pre-arranged interview appointments, and the average number of visited booths by a job
seeker is barely eight, or about 3% of attending companies (DISCO, 2018). In contrast, at ACF job seekers
have the chance to attend all 13 booths within the span of the day, and arrange interviews wheneverpossible.
Table 2 shows the descriptive statistics of the recruiters. The average number of company
representatives per booth was 4.3 and approximately half of the people appeared to be in non-senior
positions (their perceived age was used as a proxy, approximately in their early 30s or younger). The
majority of company representatives at the booths were coded as male (61.6%), Japanese (64.5%), andformally dressed (about 50% wore business suits). Accordingly, we refer to formally dressed mid-age
male Japanese company representatives as “default” or “homogeneous”, and use these characteristics asdummy variables to estimate the effect of projected staff heterogeneity on changes in prospective
candidates’ impressions.

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------------------------------

Table 2 about here------------------------------

Empirical Model and Variables
In order to test Hypotheses 2 and 3, as well as to estimate the impact of the recruitment day activities onchanges in prospective job applicants’ perceptions of a company’s image, the following econometricmodel was formulated and estimated using the collected data:

Yij = α + βBoothj + γXij + eij(Eq.1)

Y is the dependent variable, the difference between applicant i’s impression of company j after versus
before visiting company j’s booth. By using the changes in perceptions before and after rather thanabsolute score values, we are able to mitigate the effects of individual evaluation standards (someapplicants might be inherently more generous than others in their evaluation benchmarks). α is theconstant, Booth is a set of company j’s booth characteristics, X is a vector of control variables including
both applicants’ and companies’ characteristics. The error term, eij, is assumed to be composed of λi and εji(eij = λi + εji), where λ stands for the time-invariant individual error component and ε is white noise. The
inclusion of the individual component λ in the error term helps address the problem of endogeneity, whicharises from the fact that there are unobserved heterogeneities among applicants that are correlated withother explanatory variables and that might determine their impression of company. If that were the case,the estimates would be biased. In order to ensure the results from such a bias, we estimate both
fixed-effects and random-effects models. Although the coefficients in both estimations were almost
identical, the Hausman tests suggested that the fixed-effects model is more appropriate.
The survey was designed with the intention to collect data on all variables that were to be included in18the empirical model. Based on previous research on factors that might influence prospective applicants’
perceptions of organizational attractiveness, we collected information on over 70 variables directly related
to applicants’ skill set, personal traits, strengths, preferences when it comes to job search, in addition to aset of variables related to personal characteristics such as age, gender, university, major etc. These factors
were included as independent variables and controls in the empirical model. For a comprehensive
overview of dependent and independent variables used in past research on the topic, we refer to
Rynes-Weller et al. (2013).
Most importantly, the variables that present a significant contribution to existing research are ones
related to job seekers’ impressions of a company (i.e. the image or the reputation of a company) before
and after visiting the respective company’s booth. Applicants were asked to evaluate each company on ascale of 1 to 5 before and after visiting their booth and the difference between the two scores was utilized
as a dependent variable in the empirical model. The average number of booths an applicant visited is 5,
resulting in 944 applicant-booth dyad evaluations – a number which was considered sufficient for
conducting an empirical analysis.

RESULTS AND DISCUSSION
Changes in Booth Impression Scores
Testing Hypothesis 1 is fairly straightforward. The fact that job fair activities enhance theattractiveness of a company regardless of pre-existing attitudes can be gleaned from descriptive statistics,
and confirmed with a simple repeated-measures t-test. In the clear majority of their evaluations ofcompanies (65%), job seekers reported an improved impression. A deterioration in their impressions was
registered in less than 10% of the cases. The average score before attending the booths (pre-treatment) was
3.32 out of 5.00 and the one after attending the booths (post-treatment) was 3.74 out of 5.00. The
difference between the means was significant at the 1% level, confirming Hypothesis 1 (Table 3).

19-----------------------------Table 3 about here------------------------------The Determinants of Impression Changes
The results from the diagnostic OLS regression (Table 4) reveal that the ratio of female company
representatives at the booth was positively correlated with an improvement in the prospective job
applicants’ perceptions of the image of that company. Conversely, a higher ratio of Japanese-looking orformally dressed staff is associated with a smaller change in image perceptions. The seniority level(perceived age) of the booth staff does appear as a significant factor in shaping the image of the company.
The results align with the proposition in Hypothesis 2 that projecting an image implying diversity
through a heterogeneous group of company representatives at the booth can boost a firm’s image as
perceived by international job seekers.
The ‘firm evaluation score before visiting the booth’ variable has a negative coefficient indicating thatthe higher the initial evaluation is, the smaller the change in perception is likely to be. This is in line withexpectations, as low initial evaluations logically provide more room for improvement within a scale thathas an upper limit (1 to 5) – if the initial evaluation of the image of the company was 5, then an enhanced
perception after visiting the booth could not possibly be reflected in the survey, resulting in a reported lackof change.
All control variables have signs in line with expectations. For example, the number of foreigners
employed the previous year by a company appears as a very robust predictor of enhanced image
perceptions, which relates well to the concept of heterogeneity discussed above. Since this is an objective
measure of a company’s openness to non-majority individuals (as compared to projections of diversity,

20

which are not necessarily representative of the true state of attains at a company), it provides an additional
level of validity to our results.
The number of company representatives at the booth also appears as a significant factor. Assumingthat dispatching more people to the job fair is costly for a company suggests that the effort the company isputting into recruiting is appreciated by job seekers. The signs for the bottom three variables is negative,
implying a smaller positive change in the perceptions of job seekers who prefer Japanese firms, speak
Japanese and evaluate Japanese firms highly before visiting their booths, which is exactly what we expect,assuming their initial evaluations of the companies were higher, allowing for a smaller increase within thebounds of 5-point evaluation scale.

-----------------------------Table 4 about here------------------------------As mentioned, there might exist individual unobserved heterogeneities, which affect both impression
changes and explanatory variables including companies’ and individuals’ characteristics. In that case, the
OLS estimates shown in Table 4 are biased. Therefore, we conducted the panel estimations (Table 5),
which treat job seekers’ unobserved characteristics as fixed effects.

-----------------------------Table 5 about here------------------------------

The coefficients and their significance levels are both very similar to the OLS estimations. That is, the21results remain robust even after removing unobserved heterogeneities or existing beliefs and attitudes thatmight modulate the applicants’ impression changes of companies.
As a robustness check, an ordered logit model was estimated. The results from the estimation are once
again very similar to those obtained using the OLS and the fixed-effects panel models, thereby confirming
the robustness of the results. The results from the ordered logit were not reported here for brevity.

High Person-Organization Fit Job Seekers
In order to test Hypothesis 3, the model was re-estimated by isolating the subsample of applicants who
had indicated at least one skill or trait matching that indicated by a recruiter (id = 165, n = 721) – i.e. thehigh P-O fit job seekers – from the full sample (id = 171, n =944). The results of the fixed-effects model
are reported in Table 6 and show that the effects of diversity projections are significantly larger for highP-O fit job seekers (compare with Table 5).

-----------------------------Table 6 about here------------------------------In order to confirm that the effects of a matching skill/trait set are not spurious we re-estimated themodels while splitting the sample of job seekers along other potentially skill or trait-related but notnecessarily matching characteristics, such as job seekers with better versus worse than average English or
Japanese language skills, and job seekers who selected Japanese companies as their first choice (54%)
versus those who did not (46%). The results, not reported here for brevity, further support Hypothesis 3 –the effects are indeed larger for high P-O fit candidates than any other subsample. Notably, none of thecoefficients changes its sign. Only the size of the effect changes, which confirms the robustness of the22results obtained using the entire sample in addition to confirming Hypothesis 3.

Optimal Levels of Heterogeneity
Having established the importance of projecting an image of staff heterogeneity in a company’s
impression management activities, we proceed to ascertain the exact amount of heterogeneity. Since bydefinition diversity suggests a balanced mix of majority and minority representatives, while companies
certainly do not want to project an image of excessive orientation to majority, they do not want to project
an excessively minority-heavy image either. Therefore, finding the optimal ratio of majority to
non-majority representatives during recruitment activities is essential.
Assuming a concave curve or the effects of staff heterogeneity, we include squared terms in ourestimation model of Equation 1 and re-estimate it:

Yij = α + β1Boothj +β2Boothj2 + γXij+ λi +εji

(Eq.2)The results show that the improvement in the perceived attractiveness of a company is indeed
modulated by a non-linear concave relationship, as can be observed by the negative signs of the squared
terms in Table 7 (the opposite in the case of the ratio of senior-level representatives). Since𝜕𝑌 ⁄𝜕𝐵𝑜𝑜𝑡ℎ = 𝛽 𝐵𝑜𝑜𝑡ℎ + 2𝛽 𝐵𝑜𝑜𝑡ℎ, we can find the level of Booth characteristics which maximize thelevel of Y, if 𝛽 is positive and 𝛽 is negative, holding the other effects as given.

-----------------------------Table 7 about here------------------------------

23

We find that the optimal ratio of female representatives is 57%, that of Japanese staff is 43%, offormally dressed people – 41%, and of senior employees – 88%. These percentages align with the “goldenmean” concept in philosophy, which represents the desirable middle between two extremes, one of excess
and the other of deficiency. The perceived seniority of company representatives is more ambivalent, which
could be explained by the possibility that the presence of more senior company representatives at the job
fair might signal to job seekers that the company is taking its recruitment very seriously, and can therefore
override preferences for approachable recruiters, usually associated with less senior representatives.

LIMITATIONS AND FUTURE RESEARCH
More research is necessary to ascertain whether changes in perceptions for job seekers with different
profiles from the ones in our sample (e.g. mid-career, non-highly skilled etc.) would be influenced to thesame extent by the factors outlined in the previous sections. Rynes-Weller et al. (2013) point out that thevast majority of recruitment research has focused on a small portion of the labor market, specifically newcollege graduates, and since our sample also focuses on prospective college graduates, using a different
sample might shed more light on the effects of the recruitment day.
Rynes-Weller et al. (2013) also note that empirical research on recruitment practices tends to study
attitudes and behavioral intentions more than actual behaviors. In that sense, another limitation of thisstudy is that we were unable to track how exactly the positive change in prospective applicants’impressions influenced their job search behavior after the job fair.
The need for a more controlled experimental setting cannot be understated. Although the ASEAN
Career Forum (ACF) provided us with an opportunity to conduct a quasi-experimental study with theaverage job seeker attending 40% of company booths. In order to measure perception changes with aneven higher degree of validity, however, ideally job seekers would attend all booths, especially booths offictitious companies or ones they have never heard of.

24

Furthermore, in identifying high P-O fit individuals special attention should be paid to differentiatingskills from personal traits, which we could not do at ACF in 2017, due to our assumptions concerning
hiring practices by Japanese companies. We did, however, draw a clear distinction between these when
conducting a similar survey during the ASEAN Career Forum in 2018.
Finally, relating to the issue raised by Backhaus & Tikoo (2004), of whether companies should
develop a unified brand and market it internationally or if they should rather tailor their image to theculture of the country where they wish to recruit, it would also be meaningful to explore whether our
findings hold true for other world regions.

CONCLUSION
This study uses a novel dataset collected via surveying both job seekers and recruiters in a
non-Western context, which is to the best of our knowledge the first evidence of its kind in related
academic literature. Utilizing a quasi-experimental survey design, as well as fixed-effects panel data
estimations in techniques to resolve issue of heteroscedasticity and endogeneity, the results of theempirical analysis offers three main contributions to recruitment and HRM literature. These are thefindings that (1) recruitment-day activities

significantly improve prospective job seekers’ perceptions of

the attractiveness of a company, regardless of their pre-existing attitudes, also in a non-Western context;(2) the heterogeneity (diversity) of company representatives at the booth in terms of gender, perceived
ethnicity, seniority level (perceived age) level of formality, play an important role as peripheral cues inshaping foreign applicants’ perceptions of company attractiveness; and that (3) recruitment-day activities
impact impression changes to a significantly larger extent for those job seeker’s whose skills or
personality traits match the ones sought after by the companies, the so-called high person-organization(P-O fit) candidates. In addition, as an extension to the second finding, we estimated the optimal levels ofheterogeneity. The estimates suggest that a balanced mix of majority and minority representatives is25essential if companies for successfully projecting an image of employee diversity.
The results from our estimations confirm the empirical validity of the Elaboration Likelihood Model(ELM) theory as applied to recruitment, and they build on previous findings from empirical literature on
targeted (minority) hiring in the United States, extending their generalizability to non-Western settings.
The results remain robust across various specifications and sensitivity checks. Consequently, we formulate
several recommendations for companies wishing to increase their attractiveness among prospective
international job applicants through the recruitment process. Our findings suggest that companies wishing
to attract international talent might consider participating actively in job fairs as well as sending a larger
number of company representatives in order to demonstrate engagement with the recruitment process andgive more attention to each interested candidate. In doing so, they might benefit from projecting an imageof high levels of employee heterogeneity, specifically by ensuring a good balance among what they
consider to be majority and minority representatives. The findings also suggest that special attention
should be aid to gender, perceived ethnicity and seniority level in the firm. Last but not least, providing
more explicit information on the types of personality traits and skills firms are looking for might provide asignal to potential high P-O fit candidates, thereby increasing the chances of a successful match.
We hope that this investigation will inspire other similar studies in regions other than the ASEAN, andthat other scholars will be able to resolve the issues we were not able to address in this study. In themeantime, we believe that our current findings will be useful in enhancing the efficiency of job fairs andother activities aiming to match job seekers and companies, such as intermediary agencies, independent
recruiters and headhunters.

26

REFERENCES
Allen, D. G., Van Scotter, J. R. & Orondo, R. F. 2004. “Recruitment communication media: Impact onprehire outcomes”, Personnel Psychology, 57: 143-171.
Ashforth, B. & Mael, F. 1989. “Social identity theory and the organization”, Academy of Management
Review, 7: 218-230.
Avery, D. R. 2003. “Reactions to diversity in recruitment advertising – Are there differences black andwhite?”, Journal of Applied Psychology, 88: 672-679.
Avery, D. R. & McKay, P. F. 2006. “Target practice: An organizational impression management approachto attracting minority and female job applicants”, Personnel Psychology, 59: 157-187.
Avery, D. R., Hernandez, M. & Hebl, M. R. 2004. “Who’s watching the race? Racial salience inrecruitment advertising”, Journal of Applied Social Psychology, 34: 146-161.
Backhaus, K. & Tikoo, S. 2004. “Conceptualizing and Researching Employer Branding”, Career
Development International, 9 (5): 501-517.
Barber, A. E. 1998. Recruiting employees: Individual and organizational perspectives. Thousand Oaks,
CA: Sage.
Bolino, M. C., Kacmar, K M., Turnley, W. H., & Gilstrap, J. B. 2008. “A multilevel review of impression
management motives and behaviors”, Journal of Management, 34: 1080-1109.
Breaugh J. 2014. “Employee Recruitment”. In V. D. Miller and M. E. Gordon (Eds.), Meeting the
Challenge of Human Resource Management: A Communication Perspective. Routledge.
Cable, D. M. & Yu, K. Y. T. 2006. “Managing job seekers’ organizational image beliefs: The role of media
richness and media credibility”, Journal of Applied Psychology, 91: 828-840.
Cable, D. M. & Graham, M. 2000. “The determinants of organizational reputation: A job search
perspective”, Journal of Organizational Behavior, 21 (8): 929–947.
Cable, D. M. & Turban, D.B. 2003. “The value of organizational reputation in the recruitment context: A

27

brand-equity perspective”, Journal of Applied Psychology, 33: 2244–2266.
Carlson, K. D., & Mecham, R. L. 2013. “Research Design in Evaluating Recruitment Effectiveness: Past,
Present, Future”. In D. M. Cable & K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford
Library of Psychology.
Chapman, D. S., Uggerslev, K. L., Carroll, S. A., Piasentin, K. A., & Jones, D. A. 2005. “Applicant
Attraction to Organizations and Job Choice: A Meta-Analytic Review of the Correlates of Recruiting
Outcomes”, Journal of Applied Psychology, 90(5): 928-944.
Collins, C. J. & Kanar, A. M. 2013. “Employer Brand Equity and Recruitment Research”. In D. M. Cable& K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
DISCO. 2018. DISCO Inc. Company survey reports. Accessed on 8 October 2018. Retrieved fromhttps://www.disc.co.jp/research_archive_category/company/.
Da Motta Veiga, S. P. & Turban, D. B. 2014. “Who Is Searching for Whom? Integrating Recruitment and
Job Search Research”. In U. C. Klehe & E. A. J. van Hooft (Eds.), The Oxford Handbook of Job Loss
and Job Search. Oxford University Press.
Daft, R. L. & Lengel, R. H. 1984. “Information richness: A new approach to managerial information
processing and organization design”. In B. Staw and L. Cummings (eds.), Research in Organizational
Behavior (pp.191-233). Greenwich, CT: JAI Press.
Daft, R. L. & Lengel, R. H. 1986. “Organizational information requirements, media richness, andstructural design”. Management Science, 32: 554-571.
Darnold, T. & Rynes, S. L. 2013. “Recruitment and Job Choice Research: Same as It Ever Was?”. In N. W.
Schmitt, S. Highhouse & I.B. Weiner (Eds.), Handbook of Psychology, Vol 12. Industrial andOrganizational Psychology. Hoboken, NJ: John Wiley & Sons, Inc.
Dineen, B. & Soltis, S.M. 2011. “Recruitment: A review of research and emerging directions”, APA
Handbook of Industrial and Organizational Psychology.

28

Elsbach, K. D., Sutton, R. I. & Principe, K. E. 1998. “Averting expected challenges through anticipatory
impression management: A study of hospital billing”, Organization Science, 9: 68-86.
Griffeth, R. W., Tenbrink, A. & Robinson, S. 2013. “Recruitment Sources: A Review of Outcomes”. In D.
M. Cable & K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
Hovland, C.I., Janis I. L., & Kelly, H.H. 1953. Communication and Persuasion. New Haven: Yale
University Press.
Jones, D. A., Schultz, J. W., & Chapman, D. S. 2006. “Recruiting through job advertisements: The effectsof cognitive elaboration on decision making”, International Journal of Selection and Assessment, 14:
167-179.
Kristof-Brown, A. L., Reeves, C. J. & Follmer, E. H. 2013. “The Goldilocks Pursuit During
Organizational Entry: Applicants’ and Recruiters’ Search for the “Perfect Fit”. In D. M. Cable & K. Y. T.
Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
Miller, J. K. & Guo G. C. 2013. “Recruitment: International Cross-Cultural Perspectives”. In D. M. Cable& K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
Oyer, P. & Schaefer, S. 2011. “Personnel Economics: Hiring and Incentives”. In O. Ashenfelter & D. Card
(Eds.), Handbook of Labor Economics, 4b: 1769-1823.
O’Reilly, C. A., Chatman, J. A. & Caldwell, D. F. 1991. “People and organizational culture: A
profile-comparison approach to assessing person-organization fit”, Academy of Management Journal,
34: 487-516.
Petty, R. E. & Cacioppo, J. T. 1981. Attitudes and persuasion: Classic and contemporary approaches.
Dubuque, IA: William C. Brown.
Petty, R. E. & Cacioppo, J. T. 1986a. Communication and persuasion: Central and peripheral routes toattitude change. New York: Springer-Verlag.
Petty, R. E. & Cacioppo, J. T. 1986b. “The elaboration likelihood model of persuasion”, Advances in29

Experimental Social Psychology, 19: 123-205.
Powell, G. N. 1984. “Effects of job attributes and recruiting practices on applicant decisions: A
comparison”, Personnel Psychology, 37: 721-732.
Roberson Q. M., Collins, C. J. & Oreg, S. 2005. “The effect of recruitment message specificity on
applicant attraction to organizations”, Journal of Business and Psychology, 19: 319-339.
Robinson, P. 2003. “The embeddedness of Japanese HRM practices: The case of recruiting”, Human
Resource Management Review, 13: 439-465.
Rynes, S. L. 1991. “Recruitment, job choice, and post-hire consequences: A call for new research
directions”. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational
psychology Vol. 2 (2nd ed.). Palo Alto, CA: Consulting Psychologists Press.
Rynes, S. L. & Cable, D. M. 2003. “Recruitment research in the twenty-first century”. In W. C. Borman, D.
R. Ilgen & R. J. Klimoski (Eds.), Handbook of psychology: Vol. 12. Industrial and organizational
psychology. Hoboken, NJ: John Wiley & Sons, Inc.
Rynes-Weller, S. L., Reeves, C. J. & Darnold, T. C. 2013. “The History of Recruitment Research”. In D.
M. Cable & K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
Saks, A. M. & Ashforth, B. E. 1997. “A longitudinal investigation of the relationships between job
information sources, applicant perceptions of fit, and work outcomes”, Personnel Psychology, 50:
395-426.
Scandura, T. A. & Williams, E. A. 2000. “Research methodology in management: Current practices, trends,
and implications for future research”, Academy Management Journal, 43: 1248-1264.
Schlenker, B. R. 1980. Impression management: The self-concept, social identity, and interpersonal
relations. Monterey, CA: Brooks/Cole.
Schmitz, J., & Fulk, J. 1991. “Organizational colleagues, media richness, and electronic mail: A test of thesocial influence model of technology use”, Communication Research, 18: 487-523.

30

Spence, M. 1973. “Job Market Signaling”, Quarterly Journal of Economics, 87 (3): 355-374.
Taylor, M. S. & Bergmann, T. J. 1987. “Organizational recruitment activities and applicants’ reactions at
different stages of the recruitment process”, Personnel Psychology, 40: 261-285.
Theurer, C., Tumasjan, A., Welpe, I. & Lievens, F. 2016. “Employer Branding: A Brand Equity-based
Literature Review and Research Agenda”, International Journal of Management Reviews.
Tsai W. C. & Huang, T. C. 2013. “Impression Management during the Recruitment Process”. In D. M.
Cable & K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.
Turban, D. B., Lau, C. M., Ngo, H. Y., Chow, I. H. S. & Si, S. X. 2001. “Organizational attractiveness offirms in the People’s Republic of China: A person– organization fit perspective”, Journal of Applied
Psychology, 86: 194-206.
Turban, D. B., & Cable, D. M. 2003. “Firm reputation and applicant pool characteristics”, Journal of
Organizational Behavior, 24(6): 733-745.
Volpone, S. D., Thomas., K. M., Sinisterra, P. & Johnson, L. 2013. “Targeted Recruiting: Identifying
Future Employees”. In D. M. Cable & K. Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford
Library of Psychology.
Walker, H. J., Field, H. S., Giles, W. F. & Bernerth, J. B. 2008. “The interactive effects of job
advertisement characteristics and applicant experience on reactions to recruitment messages”, Journalof Occupational and Organizational Psychology, 81: 19-638.
Walker, H. J. & Hinojosa, A. S. 2013. “Recruitment: The role of job advertisements”. In D. M. Cable & K.
Y. T. Yu (Eds.), The Oxford Handbook of Recruitment. Oxford Library of Psychology.

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TABLES AND FIGURES
Figure 1
The authors’ conceptualization of the mechanism though which recruitment activities affect job seekers’
attractiveness perceptions based on the Elaboration Likelihood Model

32

Table 1
Descriptive statistics of the job seekers
Full sample
Prefers Japanese firms over other firms (%)
GPA (1-4)
Science major (%)
Male (%)
Cannot speak Japanese (%)
Fluent in English (%)
Near-native English speaker (%)
Has visited Japan (%)
Relative standard of living (1-10)
Relative standard of living at age 15 (1-10)
Top priority in a job:
High salary
Short working hours
Advancement opportunities
Task attractivenessOn the job training
Organization atmosphere
BenefitsN

Subsamples by number of skills matching
No matching skills

At least one matching skill

0.555（0.497）3.488（0.523）0.696（0.460）0.521（0.499）0.427（0.494）0.518（0. 499）0.424（0.494）0.452（0.498）6.843（1.494）5.912（1.757）0.534（0.500）3.537（0.562）0.677（0.468）0.534（0.500）0.430（0. 496）0.448（0.498）0.520（0.500）0.448（0.498）6.740（1.592）5.861（1.64）

0.562(0.50)
3.472(0.509)0.702(0.457)0.517(0.500)0.426(0.494)0.540(0.498)0.394(0.489)0.454(0.498)6.875(1.461)5.927(1.793)0.282（0.450）0.082（0.274）0.517（0.500）0.261（0.439）0.242（0.428）0.194（0.395）0.212（0.408）944

0.211（0.408）0.081（0.274）0.538（0.499）0.291（0.455）0.251（0.434）0.188（0.391）0.251（0.434）223

0.304(0.460)0.083(0.275)0.510(0.500)0.251(0.433)0.239(0.426)0.196(0.396)0.200(0.400)721

33

Table 2
Descriptive statistics of recruiters by booths attended by job seekers
Full sample
Ratios of
Female recruiters
Japanese recruiters
Formally dressed recruiters
Senior recruiters
Number of visited boothsN

Subsamples by number of matching skills
No matching skills

At least one matching skill

0.386（0.312）0.628（0.305）0.428（0.233）0.470（0.300）8.094（3.837）223

0.388(0.286)0.628(0.296)0.446(0.237)0.479(0.298)8.103(3.681)721

0.388（0.292）0.628（0.298）0.438（0.236）0.477（0.298）8.101（3.717）944

34

Table 3
Means and two-tailed t-test for company booth evaluations by job seekers before versus after visiting theboothsVariable
Booth impression score

Mean

Std. Dev.

Before

3.324

0.893

After

3.735

0.956

Note: N = 944.

35

Difference(After-Before)
0.411

t valuep value

11.919***0.000

Table 4
The effects of diversity projections on changes in company attractiveness perceptions, OLS estimation
Dependent variable: Difference in job seekers’ company
evaluation scores before versus after visiting the booth
VARIABLES
Recruitment day tactics
Female recruiter ratio

(1)

(2)

(3)

0.374
(0.133)[0.017]

Japanese recruiter ratio-0.443(0.218)[0.067]

Formally dressed recruiter ratio-0.593(0.110)[0.000]Senior recruiter ratio

Number of booth staff

(4)

0.045
(0.020)[0.051]

0.054(0.026)[0.064]0.029(0.016)[0.095]-0.046(0.108)[0.676]0.023(0.015)[0.155]Company controls
Foreigners employed the year before

0.168
0.201
0.159
0.125
(0.024)(0.044)(0.019)(0.027)[0.000][0.001][0.000][0.001]
Number of branches in Asia
0.004
0.005
0.003
0.001
(0.002)(0.003)(0.001)(0.002)[0.057][0.091][0.062][0.443]Firm evaluation score before job fair
-0.653-0.651-0.654-0.644(0.038)(0.039)(0.038)(0.036)[0.000][0.000][0.000][0.000]Constant
1.598
1.896
2.169
1.990
(0.433)(0.419)(0.467)(0.446)[0.004][0.001][0.001][0.001]
Controls
Yes
Yes
Yes
Yes
R-squared
0.373
0.372
0.375
0.368
N
944
944
944
944
Notes: Standard errors in parentheses, p values in square brackets. Controls include applicants’ gender,
nationality, university, major, GPA, living standard now and at age 15, English and Japanese language
skills, perceptions of salaries and working hours at Japanese companies, type of industry of the firm.

36

Table 5
The effects of diversity projections on changes in company attractiveness perceptions, fixed-effects
estimation
Dependent variable: Difference in company evaluation
scores by job seekers before versus after visiting the booth
VARIABLES
Female, ratio

(1)
0.317
(0.127)[0.013]

Japanese, ratio

(2)

(3)

(4)

-0.368(0.175)[0.037]

Formal attire, ratio-0.487(0.170)[0.005]

Senior, ratio-0.060(0.146)[0.682]
Candidate fixed effects
Yes
Yes
Yes
Yes
Company controls
Yes
Yes
Yes
Yes
R-squared
0.277
0.275
0.279
0.271
Observations
944
944
944
944
Number of id
171
171
171
171
Notes: Standard errors in parentheses, p values in square brackets. Company controls include the type ofindustry, number of booth staff, number of foreigners employed the previous year, number of branches in
Asia and firm evaluation score before visiting the booth.

37

Table 6
The effects of diversity projections on changes in company attractiveness perceptions for highperson-organization fit individuals, fixed-effects estimation
Dependent variable: Difference in company evaluation scores byprospective jo candidates before and after visiting the booth
VARIABLES
Female, ratio

(1)
0.375
(0.144)[0.010](2)

Japanese, ratio

(3)

(4)

-0.456(0.202)[0.025]

Formal attire, ratio-0.571(0.188)[0.003]

Senior, ratio-0.091(0.167)[0.589]Candidate fixed effects
Yes
Yes
Yes
Yes
Company controls
Yes
Yes
Yes
Yes
R-squared
0.279
0.277
0.282
0.271
Observations
721
721
721
721
Number of id
165
165
165
165
Notes: Standard errors in parentheses, p values in square brackets. Company controls include the type ofindustry, number of booth staff, number of foreigners employed the previous year, number of branches in
Asia and firm evaluation score before visiting the booth.

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Table 7
Optimal levels of heterogeneity
Dependent variable: Difference in company evaluation scores byprospective jo candidates before and after visiting the booth
VARIABLES
Female ratio

Female ratio, square

(1)
0.811
(0.398)[0.043]-0.706(0.513)[0.171](2)

Japanese ratio

(3)

0.739
(0.558)[0.187]-0.868(0.438)[0.049]Japanese ratio, square

Formal attire ratio

0.910(0.951)[0.340]-1.104(0.749)[0.143]

Formal, square

Senior ratio

Senior, square

Candidate fixed effects
Company controls
Observations
R-squared
Number of id

(4)

Yes
Yes
944
0.279
171

Yes
Yes
944
0.279
171

Yes
Yes
944
0.281
171

-0.134(0.486)[0.783]0.077(0.506)[0.880]
Yes
Yes
944
0.271
171

Notes: Standard errors in parentheses, p values in square brackets. Company controls include the type ofindustry, number of booth staff, number of foreigners employed the previous year, number of branches in
Asia and firm evaluation score before visiting the booth.

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APPENDIX A
Question 4 from the job seeker survey corresponding to Question 1 in the company survey was used tocreate the high P-O fit subsample. For job seeks the question was phrased: “Question 4. During your job
search activities, (1) what do you think your strengths are? Choose up to THREE from the list below.” Forcompany representatives the question was phrased: “Question 1. What is YOUR company looking for in aforeign candidate? Please select UP TO THREE from the list below.” The answer sheet is provided below.
Example1

Human relationship skills (leadership, cooperativeness, etc.)2

Self-control skills (stress tolerance, persistence, etc.)

3

Problem detection and solving skills

4

Logical thinking skills

5

Expert knowledge/ skills

6

Desire to succeed7

Confidence

8

Name of college/ university

9

Major in college/ university

10

Lived overseas, studied overseas

11Japanese Language skills

12

English Language skills

13

Work experience (business experience, internships, etc.)

14

IT skills (programming, network expertise, etc.)

15

Occupational qualification

16

Other (

✔

✔

✔
)

40

Your answer

APPENDIX B
Question 16 from the job seeker survey was used to create the dependent variable (firm evaluation scoreafter attending the booth minus the score before attending the booth). The question was phrased: “Pleaseevaluate the participating companies on the following three: (1) Did you visit the booth? (2) Did you havean interview? (3), (4) What was your impression of each company BEFORE and AFTER today’s fair?
(1=worst, 5=best)”.

41