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3 1293 02048
ZCC’O

LIBRARY

Michigan State
Unlversity

 

 

 

 

This is to certify that the

thesis entitled

ACHIEVING RECRUITING GOALS: APPLYING WHAT
WE KNOW ABOUT PERSON-ORGANIZATION FIT ACROSS
A RANGE OF ORGANIZATIONAL IMAGE

presented by

Christine Renee Scheu

has been accepted towards fulﬁllment
of the requirements for

M.A. degree in Psychology

 

 

 

 

0-7639 MS U i: an Afﬁrmative Action/Equal Opportunity Institution

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before datedue.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE

DATE DUE

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IL—IUE 941.:
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moo animus-p.14

 

ACHIEVING RECRUITING GOALS:
APPLYING WHAT WE KNOW ABOUT PERSON-ORGANIZATION FIT ACROSS A
RANGE OF ORGANIZATIONAL IMAGE

By

Christine Renee Scheu

ATHESIS

Submitted to
Michigan State University
In partial fulﬁllment of the requirements for the degree of

MASTERS OF ARTS

Department of Industrial/Organizational Psychology

2000

ABSTRACT
ACHIEVING RECRUITING GOALS: APPLYING WHAT WE KNOW ABOUT
PERSON-ORGANIZATION FIT ACROSS A RANGE OF ORGANIZATIONAL
IMAGE
By

Christine Renee Scheu

The current study investigated the possibility of manipulating the type of information
provided in recruiting brochures to inﬂuence applicant behavior and perceptions.
Speciﬁcally, the extent to which, the type of information provided in a recruiting context
(i.e., ﬁt information) inﬂuences applicant intentions to apply, organizational image, and
applicant quality and quantity was examined. A conceptual model is presented to explain
the relationships between ﬁt, image, familiarity, information type, and applicant quality.
A 3 (company image: positive, neutral, negative) x 2 (type of ﬁt information:
complementary or supplementary) between subjects design was employed. The
manipulation for type of information provided failed; as a result, type of information
provided had no impact on intentions to apply, organizational image, or applicant quality
and quantity. However, the results indicate that organizational image inﬂuences
intentions to apply, organizational image is malleable, and that familiarity inﬂuences the
amount of change that can be expected in organizational image. Implications for future

research and practice are discussed.

For my father, George Scheu

iii

ACKN OWLEGEMENT S

I would like to thank the members of my committee, Ann Marie Ryan, Rick DeShon, and
Kevin Ford for their guidance and patience throughout the thesis process. I would also
like to thank my family for continually reminding me to have faith in my own ideas and
abilities no matter what obstacles I encountered. And last but certainly not least, I would
like to thank my friends, and colleagues who provided words of encouragement and

support during the times I needed it most.

iv

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................... viii
LIST OF FIGURES ................................................................................................... ix
CHAPTER 1 .............................................................................................................. 1
INTRODUCTION.............., ...................................................................................... 1
Recruiting Literature ..................................................................................... 5
Person Organization Fit ................................................................................. 8
Supplementary Fit ............................................................................. 9
Complementary Fit ............................................................................ 12
General Image Literature .............................................................................. 18
Image Deﬁned ................................................................................... 19
Explaining the Relationship Between Image and Applicant
Attraction ........................................................................................... 20
Studies Relating Applicant Attraction and Organizational Image 24
Current Study .................................................................................... 32
Overview of the Conceptual Model .................................................. 33
Effects on Intentions to Apply .......................................................... 34
Hypothesis 1 .......................................................................... 35
Hypothesis 2 .......................................................................... 36
Hypothesis 3 .......................................................................... 37
Hypothesis 4 .......................................................................... 38
Hypothesis 5 .......................................................................... 38
Effects on Post Image ........................................................................ 38
Hypothesis 6 .......................................................................... 39
Hypothesis 7 .......................................................................... 40
CHAPTER 2 .............................................................................................................. 40
METHOD .................................................................................................................. 40
Subjects ......................................................................................................... 40
Design ............................................................................................................ 41
Procedure ....................................................................................................... 41
Measures ........................................................................................................ 44
CHAPTER 3 .............................................................................................................. 46
RESULTS .................................................................................................................. 46
Pilot Data ....................................................................................................... 46

Preliminary Analyses .................................................................................... 48

Company Analyses ........................................................................................ 55
Hypothesis Tests ........................................................................................... 58
Model Overview ............................................................................................ 62
CHAPTER 4 .............................................................................................................. 65
DISCUSSION ........................................................................................................... 65
Role of Image ................................................................................................ 66
Type of Information ...................................................................................... 71
Limitations .................................................................................................... 74
Conclusions ................................................................................................... 76
APPENDICES ........................................................................................................... 77
Appendix A. .................................................................................................. 78
Appendix B. .................................................................................................. 79
Appendix C. .................................................................................................. 85
Appendix D. .................................................................................................. 86
Appendix E .................................................................................................... 87
Appendix F. ................................................................................................... 92
REFERENCES .......................................................................................................... 93

vi

LIST OF TABLES

Table 1. Descriptive Statistics & Correlations for the Pilot Data ................ 47
Table 2. Reliability of All Measures ............................................................ 50
Table 3. Descriptive Statistics for the Experimental Data Overall ............... 51
Table 4. DescriptiveStatistics for the Experimental Data By Condition ...... 52
Table 5. Intercorrelations for All Scales and Measures ............................... 53
Table 6. Frequencies for the Fit Manipulation Check .................................. 56

Table 7. Independent Samples t-tests Comparing Intentions to Apply
Means for the Supplementary and Complementary Fit Condition 59

Table 8. Moderated Regression: Intentions to Apply Regressed on Fit and

Quality ............................................................................................ 60
Table 9. Moderated Regression: Post-Image Regressed on Pre-Irnage and
Type of Information ....................................................................... 62
Table 10. Moderated Regression: Post-Image Regressed on Pre-Image and
Familiarity ................................................................................... 63
Table 11. Paired Samples t-tests Comparing PrelPost Image Means .......... 64

vii

LIST OF FIGURES

Figure 1. Conceptual Model ..................................................................................... 4

Figure 2. Relationship between pre and post image as a function of familiarity ..... 63

viii

Chapter 1
INTRODUCTION

As early as the 1960’s, researchers have been warning us that the pool of qualiﬁed
applicants is shrinking, and as a result, organizations will ﬁnd themselves competing for
employees (Behling, Labovtiz, & Gainer, 1968). This prediction has borne itself out, as
unemployment rates are lower than they have been in decades (Nassar, 1999) and growth
in the labor force will soon be at its lowest level since the 1930’s (Johnston & Packer,
1987).

Recognition of this competition for employees has led researchers and
organizations alike to place more emphasis on recruiting and attracting applicants
(Barber, 1998; Highhouse, Zickar, Thorsteinson, Stierwalt, & Slaughter, 1999; Rynes,
1991; Stroops, 1984). In fact, some argue that recruiting has become a critical aspect of
the selection process (Barber, 1998; Werbel & Landau, 1996). Speciﬁcally, in the early
stages of the stafﬁng process, recruiting can inﬂuence the size of the selection pool and
ultimately affect selection ratios and utility (Barber, 1998; Boudreau & Rynes, 1985;
Barber & Roehling, 1993), while later in the process it can mean the difference between
an applicant’s acceptance or decline of a job offer (Barber, 1998). It is estimated that
with all the resources invested in this process, an organization’s average cost per hire is in
the thousands (Martin & Raju, 1992).

Although the recruiting literature has expanded in recent years, most of the
empirical research focuses on post-offer decisions (Barber & Roehling, 1993) as opposed
to decisions made by applicants at early stages, such as choosing which organizations to

apply to. As Barber (1998) points out, it is critical that we understand the activities and

decisions of this initial stage because they are the foundation for later recruiting stages,
selection, and job choice.

The research that does focus on this initial stage of recruitment suggests that
potential applicants frequently have a limited amount of information upon which to base
their initial application decisions (Rynes, 1991). Furthermore, the information applicants
collect about a company typically comes from a variety of sources including company
employees, products, advertisements, word-of-mouth, and recruiting materials (Barber,
1998; Gatewood, Gowan, & Lautenschlager, 1993; Saks & Ashford, 1997). Based on
these sources, applicants are likely to develop general impressions or perceptions of an
organization; Two perceptions that have recently come to the forefront of the recruiting
and stafﬁng literature are person organization (PO) ﬁt, or the degree of compatibility
between a person and an organization (Kristoff, 1996), and organizational image, a loose
structure of knowledge, beliefs, and feelings about an organization (T om, 1971).

The empirical literature suggests that both PO ﬁt and image perceptions inﬂuence
applicant attraction and intentions to apply (Belt & Paolillo, 1982; Bretz, Ash, & Dreher,
1989; Cable & Judge, 1994; Cable & Judge, 1996; Gatewood et al., 1993; Highhouse et
al., 1999; Judge & Bretz, 1992; Kristoff, 1996; Rynes, Bretz, & Gerhart, 1990; Saks &
Ashford, 1997; Tom, 1971; Turban & Greening, 1996; Turban & Keon, 1993); however,
the literature has not examined the relationship between these two constructs even though
researchers frequently conduct studies in both areas and cite the same empirical piecesl.
Furthermore, the research has yet to focus on developing recruiting materials to capitalize

on the effects of PO ﬁt and image on applicant behavior. Speciﬁcally, can the content of

 

I As will be discussed in-depth in later sections, image and PO ﬁt are expected to have a
recursive relationship.

recruiting materials be manipulated to optimize the balance between applicant quantity
and quality for organizations across a range of image (i.e., organizations with positive,
negative, and neutral images)? In today’s competitive market, it would be in an
organization’s best interest to vary the content of its brochures to inﬂuence applicant
behavior and meet current organizational needs. However, the same strategies are not
likely to be equally successful across the range of organizational image. For instance, an
organization with a negative image may have to settle for simply attracting more
applicants, while a popular positive image ﬁrm may be looking to reduce costs by having
‘ unqualiﬁed applicants self-select out of the process.

Additionally, considering the impact image has on applicant attraction and
intentions to apply, organizations with neutral or negative images would be well served if
they could change or improve their corporate image. However, the image/recruiting
literature has yet to address this issue. That is, is organizational image malleable and if it
is, how might a ﬁrm change these general impressions?

Given that organizational image is likely to have such a large impact on applicant
behavior and perceptions, the current study examines how organizational image is
affected by the type of information in recruiting brochures. Speciﬁcally, working within a
recruiting context, can the type of information provided (i.e., ﬁt information) inﬂuence
applicant intentions to apply, organizational image, and applicant quality and quantity?
The conceptual model for the current study is presented in Figure 1 and will be discussed
in depth in later sections. The following pages will outline what we know about
recruiting materials, PO ﬁt, and image in an effort to lay the groundwork for the current

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Recruiting Literature

Considering that recruiting materials are one of the few applicant informational
sources that organizations have direct control over, it is not surprising that researchers
have investigated the role played by various recruiting materials (e.g., advertisements and
brochures) in a job seeker’s application decisions. It is believed that most job seekers
will review recruiting materials before deciding where to apply and that these materials
will inﬂuence their decisions (Barber, 1998). The following paragraphs will outline what
we know about how these materials inﬂuence applicant decisions.

The practitioner literature largely focuses on the appearance of recruiting
materials and their impact on attracting an applicant’s attention (Barber, 1998). This
literature indicates that design features such as color, type of font, and advertisement size
(Redman & Matthews, 1992), as well as the novelty of approach (Koch, 1990) are
important to attracting attention. However, due to the rapid changes in what is new and
likely to draw one’s attention, there is virtually no academic literature addressing these
issues (Redman & Matthews, 1992).

The academic recruiting literature has largely focused on the content of recruiting
materials and how it may impact potential applicants (Barber, 1998). Speciﬁcally, these
studies have addressed the amount of information provided, the impact of speciﬁc types
of information, and the speciﬁcity of information. Studies addressing the amount of
information provided suggest that it is positively related to intentions to apply (Barber &
Roehling, 1993; Gatewood et al., 1993; Herriot & Rothwell, 1981); that is, potential
applicants prefer more information. This is not especially surprising considering that

most applicants have access to a limited amount of information at this point in the

process (Rynes, 1991). Although, it is possible that information overload could hinder
this relationship, there are no studies addressing this issue (Barber, 1998).

Several studies have addressed the impact of job attributes and other speciﬁc
types of information including compensation, geographic location, and human resource
practices. The practitioner and academic literatures indicate that it is important to include
compensation information in recruiting materials and that this information can inﬂuence
decisions to apply (Barber and Roehling, 1993; Cable & Judge, 1994; Laabs, 1991;
Redman & Matthews, 1992; Rynes, Schwab, & Heneman, 1983; Schwoerer & Rosen,
1989). Similarly, geographic location has been found to be an important factor in the
application decision (Barber & Roehling, 1993; Rynes & Lawler, 1983) although a study
by Noe, Steffy, and Barber (1988) suggests that the inﬂuence of location may vary as a
result of family status and community ties, such that, those who are more established are
less likely to consider relocation. Finally, various human resource practices such as
family friendly policies, beneﬁts, and reward systems have been found to inﬂuence
applicant attraction and intentions to apply (Bretz & Judge, 1994; Honeycutt & Rosen,
1997). It is believed that differences in human resource practices are perceived by
applicants as signals to company beliefs, culture, and PO ﬁt (Bretz & Judge, 1994).
Simply stated, potential applicants tend to draw inferences based on available information
that will allow them to differentiate between organizations.

A handful of studies have addressed the speciﬁcity of the information presented in
recruiting materials. In general, these studies have focused on manipulating how
speciﬁcally job qualiﬁcations are described in recruiting advertisements. The basic

premise of this research is that individuals will self-select out of the application process if

they do not perceive a good ﬁt between their knowledge, skills, and abilities (KSAs) and
those sought by an organization (Kristoff, 1996; Schneider, 1987). However, studies
addressing speciﬁcity have found mixed results. Belt and Paollio (1982) manipulated the
speciﬁcity of job requirements in advertisements for fast food managers and found no

. signiﬁcant differences in intention to apply. The researchers suggest that the failure to
ﬁnd speciﬁcity effects stemmed from either the overwhelming effect found for other
variables in the study (i.e., corporate image) or the instructions may have implied that all
subjects were qualiﬁed for the position. Mason and Belt (1986) investigated the
speciﬁcity of job descriptions and job qualiﬁcations and found that more detailed job
requirements successfully reduced the number of unqualiﬁed applicants intending to
apply (i.e., self-select out). However, no effect was found for the speciﬁcity of job
descriptions. Similarly, Thorsteinson, Ryan, and McFarland (1997) manipulated the
speciﬁcity of job descriptions and job qualiﬁcations and found that applicants were less
likely to respond to ads that included speciﬁc exclusionary job qualiﬁcations. Overall,
although the results are somewhat mixed, there is evidence to suggest that speciﬁcally
stating job requirements will cause less qualiﬁed applicants to self-select out of the
process.

In summary, the literature suggests that applicants are seeking information and
that they will react to and draw inferences from the available recruiting materials. That
is, applicants will use the available information as signals or indicators of other
organizational factors that the available information does not directly address (e. g., fit,
image, organizational polices and culture; Bretz & Judge, 1994; Rynes, Bretz, & Gerhart,

1991; Spence, 1973). However, most of the studies to date have focused on a very

limited set of content or organizational attributes (e. g., compensation, and location); thus,
it is unclear how applicants would respond to other types of information (e. g., ﬁt
information; Barber, 1998). Additionally, we still know very little about how
information can affect organizational image. That is, can an organization’s image be
changed or improved by providing potential applicants with certain types of information
(e.g., ﬁt information)?
Person Organization Fit

In recent years, the concept of PO ﬁt has received a great deal of attention in the
empirical literature. References to PO ﬁt can be found in research involving job choice,
selection, recruiting, socialization, and performance outcomes. Although the concept of
PO ﬁt has been deemed somewhat elusive (Rynes & Gerhart, 1990), in a global sense PO
ﬁt is the degree of compatibility between a person and an organization (Kristoff, 1996).
The literature has demonstrated that PO ﬁt is related to multiple outcomes and attitudes
including attraction, job choice, performance, work attitudes, and turnover; such that a
good ﬁt or the perception of a good ﬁt yields higher levels of attraction, performance,
work attitudes, and organizational tenure (Bretz & Judge, 1994; Cable & Judge, 1996;
Chan, 1996; Chatman, 1991; Judge & Bretz, 1992; Kristoff, 1996; Rynes & Gerhart,
1990; Turban & Keon, 1993; Vancouver & Schmitt, 1991). Considering the number of
positive outcomes associated with good PO ﬁt, it would be in an organization’s best
interest to focus on ﬁt early in the job search and recruiting process.

However, the literature suggests that there is a disconnect between the type of fit
organizations initially focus on (i.e., complementary ﬁt or resources, opportunities, or

KSAs) and the type of ﬁt applicants initially focus on (i.e., supplementary ﬁt or goals,

values, and norms; Cable & Judge, 1996; Kristoff, 1996). Speciﬁcally, it appears that
organizations are interested in identifying a set of individuals with the necessary KSAs
while applicants place more emphasis on ﬁnding an organization that has characteristics
(e. g., values, personality, goals, etc.) similar to their own.

Before further exploring this disconnect, it is important to understand how these
two types of ﬁt differ. As previously mentioned, the concept of PO ﬁt has been
considered somewhat elusive (Rynes & Gerhart, 1990). This elusive nature stems from
the many ways researchers have chosen to deﬁne ﬁt in recent years (e.g., need-supplies
ﬁt, demands-ability ﬁt, supplementary ﬁt, complementary ﬁt; Kristoff, 1996). Kristoff
(1996) recognized that these deﬁnitions were not all mutually exclusive and attempted to
organize these multiple perspectives into the two broad categories of supplementary and
complementary ﬁt. In Kristoff’s model, supplementary ﬁt involves a person-organization
match on characteristics such as goals, values, norms, and attitudes; complementary ﬁt
involves a match of resources, opportunities, or KSAs. These broader deﬁnitions provide
us with an organizing framework for both the effects of PO ﬁt and the existing empirical
literature; however, this is not to say that there is no overlap between supplementary and
complementary ﬁt. In fact, Kristoff’s model does concede some degree of overlap
between the categories. The following paragraphs will outline the ﬁndings of the job
search and recruiting literature associated with these two broad categories of PO ﬁt.
Supplementm Fit

As previously mentioned, supplementary ﬁt involves a person-organization match
on characteristics such as goals, values, norms, and attitudes. Furthermore, the literature

suggests that applicants place a good deal of emphasis on supplementary ﬁt (Cable &

Judge, 1996; Kristoff, 1996). Several studies have addressed issues regarding the effects
of supplementary ﬁt or perceived supplementary ﬁt in the early stages of the job search.
These studies suggest that applicants prefer organizations whose values and personality
closely match their own (Barnett, Vaughan, & Moody, 1997; Cable & Judge, 1996;
Chatman, 1991; Judge & Cable, 1996; Judge & Bretz, 1992; Keon, Latack, & Wanous,
1982; Tom, 1971). Furthermore, applicants make job choice decisions that are consistent
with their PO ﬁt perceptions and these perceptions are inﬂuenced by recruitment efforts
(Cable & Judge, 1996; Saks & Ashford, 1997).

It is also important to note that individual differences in applicants can impact
how much inﬂuence ﬁt perceptions have on applicant application and job choice
decisions. Speciﬁcally, applicants who have, or believe they have, more job
opportunities have the freedom to seek positions with a better ﬁt; that is, these applicants
can be more selective (Breaugh, 1983; Cable & Judge, 1996; Chatman, 1991).
Additionally, the literature suggests that conscientious and self-aware job seekers will
place more emphasis on PO ﬁt when making career decisions than those who are less
conscientious and self-aware (Kristoff, 1996).

From an organization’s perspective, supplementary ﬁt is likely to come into play
later in the stafﬁng process (Kristoff, 1996). The literature suggests that interviewers
may be making PO ﬁt judgements (Bretz, Rynes, & Gerhart, 1993; Cable and Judge,
1997; Rynes, & Gerhart, 1990). When speciﬁcally targeting the inﬂuence of
supplementary ﬁt on interviewers’ decisions the literature suggests that perceived ﬁt
perceptions have large effects on interviewers’ hiring decisions (Cable & Judge, 1997).

Although a focus on supplementary ﬁt at this point in the process should beneﬁt

10

organizations by increasing employee tenure (Carlson & Connerly, 1999), organizations
may be attracting the wrong type of applicants by not emphasizing supplementary ﬁt
earlier in the process (e.g., in brochures and other recruiting materials) which is when
applicants place more emphasis on this type of information. Furthermore, it is important
for organizations to recognize that applicants will draw inferences from the information
available to them. Thus, if organizations do not provide information regarding company
goals, values, personality, etc., applicants are likely to infer this information from other
sources. That is, applicants will use other experiences or pieces of information (e.g.,
beneﬁts, compensation, company policies) as indicators or signals of company goals and
values (i.e., supplementary ﬁt; Rynes et al., 1991)2. Due to the limited information
available to applicants, they may draw incorrect conclusions; thus, it may be in an
organization’s best interest to emphasize supplementary ﬁt up front.

In addition to providing the type of information applicants are looking for,
directly addressing supplementary ﬁt in recruiting materials may have an additional
beneﬁt for many organizations. Speciﬁcally, providing information regarding company
personality, goals, or values may impact organizational image (i.e., a loose structure of
knowledge, beliefs, and feelings about an organization). The literature suggests that
supplementary ﬁt information will have a stronger effect on attitudinal outcomes than
will complementary ﬁt (Kristoff, 1996). If one extends this notion, supplementary ﬁt
information should impact knowledge, attitudes, beliefs, and feelings about an
organization or organizational image. This may be particularly helpful for an

organization with a negative image.

 

2A more in-depth discussion of signaling theory is provided in the subsequent section on
organizational image.

11

Additionally, if applicants perceive a good ﬁt with an organization, chances are
they will feel more positively towards it for self-preservation reasons. Social identity
theory suggests that our self-concepts are in-part shaped by the organizations we identify
with (Dutton, Dukerich & Harquail, 1994; Tajfel & Turner, 1985); thus, if we determine
that an organization holds values similar to our own (i.e., supplementary ﬁt), it becomes
more difﬁcult for us to view that organization in a negative light. As a result, one’s
general feelings or impressions of the organization (i.e., image) should improve making
one more likely to pursue employment with the organization.

Although none of the existing empirical research has addressed the relationship
between ﬁt and image, past conceptual work suggests that the ﬁt/image relationship is
recursive. That is, image and ﬁt perceptions will affect each other. For instance, if an
individual holds a negative image of an organization she will be less likely to believe she
ﬁts, although if the individual perceives a good ﬁt with an organization she may adjust
her image perceptions (i.e., for self preservation or to appear consistent). As this is an
individual cognitive process, we can not predict the direction of the adjustments to ﬁt and
image for any given individual; we can merely predict that these two perceptions should
affect each other.

Complementgy ﬁt

As previously mentioned, complementary ﬁt involves a match of resources,
opportunities, or KSAs. From the practical perspective, it is important to note that
organizations typically focus on complementary ﬁt early in the stafﬁng process.
Speciﬁcally, organizations are interested in identifying a set of individuals with the

necessary KSAs. From this set of individuals the literature suggests that the organization

12

will ultimately select the applicants it perceives as having the best supplementary ﬁt and
offer these applicants positions (Bowen, Ledford, & Nathan, 1996; Cable & Judge, 1997;
Kristoff, 1996). From a research perspective, there are several studies on the early stages
of job choice and recruiting with aspects that can be classiﬁed as complementary ﬁt
focused (Kristoff, 1996). However, it is important to note that this distinction was made
by Kristoff (1996) post hoc and not by the original authors; thus, many of these studies
still make references to values, which is now recognized as an aspect of supplementary
ﬁt. Furthermore, all the published studies since Kristoff’s 1996 article have focused on
supplementary ﬁt issues, thus leaving our understanding of complementary ﬁt somewhat
incomplete.

Only one of the studies classiﬁed as complementary ﬁt focuses on the
organization’s perspective. Speciﬁcally, Rynes and Gerhart (1990) investigated
interviewers’ assessments of applicants’ PO ﬁt. Their results suggest that interviewers
are looking for more than basic employability; that is, they are looking for individuals
who will ﬁt the organization. Once basic job qualiﬁcations are accounted for,
interviewers use characteristics such as warmth, goal orientation, applicant attractiveness,
and leadership skills to evaluate applicants. However, the interviewers’ ﬁrst priority was
identifying candidates with the necessary KSAs. This study supports the notion
discussed above that organizations are interested in identifying a set of individuals with
the necessary KSAs and from this set of individuals the organization will select the
applicants it perceives as having the best supplementary ﬁt (Bowen, Ledford, & Nathan,

1996; Cable & Judge, 1997; Kristoff, 1996).

13

The remaining studies on complementary ﬁt focus on application and job
decisions made by job seekers on the basis of complementary ﬁt based information.
Bretz, Ash, and Dreher (1989) investigated applicant attraction to organizations offering
either individual or organizational based reward systems. Their results suggest that
individuals who were high in need for achievement would be more likely to apply to
organizations offering individual based reward systems therefore improving the potential
for P0 ﬁt. Similar results regarding reward systems were found by Turban and Keon
(1993). Speciﬁcally the study found that subjects who were high in need for achievement
were more attracted to organizations that offered performance based as opposed to
seniority based reward systems. Along the same lines, Cable and Judge (1994) found that
different types of compensation systems (e. g., ﬁxed vs. contingent, individual vs. group,
and job based vs. skill based) attracted different types of people. That is, people holding
different types of goals and values were attracted to organizations offering different
compensation systems, which suggests that organizations can improve PO ﬁt and attract
different types of people by offering a particular compensation system. Finally, Rynes,
Bretz, and Gerhart (1991) found that job characteristics (some of which were
complementary ﬁt in focus; e.g., training and advancement opportunities) played a
critical role in applicants’ ﬁt assessments.

As one might ascertain from the discussion above, skill-based ﬁt is often
overlooked in the complementary/PO ﬁt literature (Carlson & Connerley, 1999). The
majority of the complementary ﬁt literature focuses on rewards and opportunities and
ignores KSAs; however, a fair amount of person-job (PJ) ﬁt literature has focused on

KSAs (Chan, 1996; Saks & Ashford, 1997). The underlying notion of P] ﬁt is

14

demand/abilities ﬁt or the idea that an individual has the KSAs that a particular job
requires (Chan, 1996). The literature suggests that PJ ﬁt is related to job satisfaction,
performance, and tenure (Saks, 1994; Saks & Ashford, 1997). Additionally, the
gravitational hypothesis suggests that individuals will gravitate towards occupations/jobs
that match their ability level (McCormick, DeNisi & Shaw, 1979; McCormick, Jeanneret,
& Mecham, 1972). A recent study by Wilk and Sackett (1996) found empirical support
for this hypothesis. Speciﬁcally, the study found evidence that individuals will change
jobs until they achieve an ability-complexity ﬁt.

Essentially, both the complementary and PJ ﬁt literatures suggest that applicants
will use reward, opportunity, and skill based information as signals of PO ﬁt. However,
there are no PO ﬁt studies directly addressing the effects of KSA information on
applicant behavior. The failure to address KSAs in the complementary/PO ﬁt literature
probably stems from the traditional belief that jobs are the core of the organization and
that jobs are clearly deﬁned and comprised of a speciﬁc static set of responsibilities
(McCormick, Jeanneret, & Mecham, 1972; Lawler, 1994). However, the nature of
organizations has dramatically changed over the past 20-30 years. Organizations and the
positions within them change at a rapid rate, organizations are ﬂatter and more
decentralized increasing the need for employees to self-manage, and the concept of teams
has increased the need for cross-training and a wider array of skills (Bowen, Ledford, &
Nathan, 1996; Lawler, 1994; McFadden & Hubbard, 1998). These changes suggest a
need to move away from the traditional job-based organization and focus on broader
classiﬁcations of characteristics and KSAs that cut across positions in the organization

(Carlson & Connerley, 1999; Lawler, 1994). These broader classiﬁcations are typically

15

referred to as competencies (e. g., communication skills, and employee/peer development)
and can be addressed at the organization level as Opposed to the job level. Additionally,
it is likely that there are a number of very popular core competencies that will be
consistent across organizations (Carlson & Connerley, 1999) making it possible for
researchers to address competency issues and still conduct generalizeable research. That
is, researchers can focus on competencies that are not speciﬁc to a particular organization
making the results relevant to multiple organizations.

Both the practitioner and the popular literature suggest that many organizations
are adopting the competency approach (Caudron, 1997; Laabs, 1997; McFadden &
Hubbard, 1998; Nichols & Sikes, 1996). Once a company establishes its core
competencies, these competencies permeate most human resource functions including
training, promotions, pay, and selection (Lawler, 1994). Thus, it is a logical step to
incorporate competencies into recruiting efforts as well. In today’s competitive market,
organizations would be well served if they could reduce costs by attracting fewer
unqualiﬁed applicants (Carlson & Connerley, 1999). The literature suggests that one way
to accomplish this goal would be to speciﬁcally (Mason & Belt, 1986; Thorsteinson, et
al., 1997) or more accurately describe (Carlson & Connerley, 1999) the competencies an
organization is looking for in recruiting materials. As previously discussed, there is
evidence to suggest that providing speciﬁc information regarding job qualiﬁcations will
lead to fewer unqualiﬁed applicants applying for positions (Mason & Belt, 1986;
Thorsteinson, et al., 1997). Additionally, the gravitational hypothesis suggests that
applicants are looking to achieve an ability-complexity ﬁt (McCormick, DeNisi & Shaw,

1979; McComrick, Jeanneret, & Mecham, 1972; Wilk & Sackett, 1996); thus, it follows

16

that advertising the competencies required to succeed in an organization would assist
applicants in achieving this sense of ﬁt.

The bottom line is that for many organizations the goal is to attract qualiﬁed
applicants, not simply more applicants, and providing competency based complementary
ﬁt information may be the way to achieve this goal. However, it is important to note that
additional research is needed to disentangle the roles of different types of ﬁt (Carlson &
Connerley, 1999). As previously mentioned, the research has typically addressed PO ﬁt
as an area; that is, the complementary and supplementary ﬁt distinctions were made post
hoc and I am not aware of any studies that have attempted to separate ﬁt into the
classiﬁcations provided by Kristoff (1996; i.e., supplementary vs. complementary) and
study their effects.

In summary, there are two broad classiﬁcations of PO ﬁt, namely supplementary
and complementary. Based on past research there is reason to believe that applicants
initially place greater emphasis on supplementary ﬁt and organizations initially place
greater emphasis on complementary ﬁt. This disconnect could have implications for
organizations in terms of the size and quality of their selection pool. That is, the type of
information communicated to potential applicants early in the stafﬁng process may
inﬂuence application behaviors and perceptions of the organization (i.e., PO ﬁt and
image). Speciﬁcally, complementary ﬁt information is expected to cause less qualiﬁed
applicants to self-select out of the process. Additionally, the literature suggests that job
seekers are initially interested in supplementary ﬁt information, thus, by providing this

information one is likely to attract additional applicants. Finally, supplementary ﬁt

17

information is expected to inﬂuence organizational image more than complementary ﬁt
information. This image-ﬁt relationship is further explored in the following section.
General Image Literature

As previously mentioned, image appears to play a key role early in the job choice
decision process (Fombrun & Shanley, 1990; Gatewood et al. 1993; Rynes, 1991);
however, it is important to note that the existing image literature is sparse and lacks a
clear focus. Despite the state of the literature, there have been some consistent ﬁndings
and accepted assumptions, which are described below.

Primarily, it is agreed upon that applicants typically have limited information on
which to base their application decisions (Rynes, 1991). As a result, applicants are likely
to rely on and make inferences about the characteristics of an organization based on the
information available (e.g., recruiting materials, advertisements; Rynes, Bretz, & Gerhart,
1991; Spence, 1973). Furthermore, the literature clearly indicates that organizational
image is related to intentions to pursue further contact with a ﬁrm (Belt & Paolillo, 1982;
Gatewood et al., 1993; Turban & Greening, 1996; Highouse et al., 1999). And ﬁnally,
not everyone holds the same corporate image (Gatewood et al., 1993). There is evidence
that executives hold corporate images that are not only different from those of applicants
but based on different criteria. Speciﬁcally, executives, from outside the ﬁrm, base their
corporate image perceptions on economic indicators, whereas, applicants largely base
their perceptions on familiarity (Fombrun & Shanley, 1990; Gatewood et al., 1993).
However, based on the current literature it appears that potential applicants generally
have similar perceptions of organizations. Speciﬁcally, Belt and Paolillo (1982) found no

differences in image rankings when they divided their sample into 8 subgroups on the

18

basis of race, sex, and student status. Similarly, Hi ghhouse et al. (1999) found virtually
no differences in the fast-de restaurant image perceptions of their high school and
senior citizen samples. Overall, however, we still know very little about how image
impressions work, when they come into play, what they are based on, the magnitude of
their effects, or their malleability.

Image Deﬁned

One of the key questions for this area of study is what is organizational image
from an outsider’s perspective? The insider/outsider distinction is important one thus, it
is important to note that all the studies discussed below are deﬁning image from the
perspective of an organizational outsider (e. g., potential applicant) as opposed to the
image held by a member of an organization which may be affected by numerous other
variables such as work group culture and climate.

The “what is organizational image?” question is not easily addressed because
each study seems to deﬁne image in a slightly different manner. Tom (1971) deﬁned
image as a loose structure of knowledge, beliefs, and feelings about an organization.
Although this is a rather broad deﬁnition, it does seem to capture the highly subjective
nature of the term image and it is similar to deﬁnitions used in ﬁelds such as marketing
(Dieter, 1985 as cited in Barber, 1998). Since Tom (1971), researchers have attempted to
deﬁne image in a narrower sense by focusing on different types of image. Belt and
Paolillo (1982) looked at corporate image, which they deﬁned as a set of attributes about
a particular ﬁrm, which can be induced from the way the employer deals with its
employees, customers, clients, and society. Gatewood et al. (1993) interpreted this

deﬁnition as simply a reaction to a company name and have tried to differentiate

19

corporate image from recruitment image, or the reaction to recruitment advertisements or
materials. And most recently, Highhouse et al. (1999) focused on what they called
company employment image or an organization’s image as a place to work.

In my opinion, these narrower deﬁnitions are largely splitting hairs. This opinion
is based on the fact that we actually know very little about image, its effects, or its
dimensions. Furthermore, we know that the typical applicant has a limited amount of
information about potential employers; thus it is unlikely that they have enough
information to create multiple images of a company, not to mention ones that are
completely independent. With this in mind, the current study deﬁned image as Tom
(1971) did, as a loose structure of knowledge, beliefs, and feelings about an organization
held by a potential applicant.

In addition to the issue of how to deﬁne or conceptualize image as discussed
above, it is important to note that the image literature does not always measure or
operationalize image in a manner that is consistent with the deﬁnition. For instance,
some studies (e. g., Tom, 1971) have deﬁned image in a broad manner, while measuring
image in a very speciﬁc or detailed manner (Barber, 1998). Others have narrower/more
detailed deﬁnitions and then simply employ company rankings or a rating on a single
item as a measure of image (i.e., a very general or generic means of measuring image;
Belt & Paolillo, 1982; Gatewood et al., 1993; Turban & Greening, 1996). This issue will
be addressed in more detail with regard to speciﬁc studies.

Explaining the Relationship Between Image and Applicant Attraction
Regardless of how one chooses to deﬁne image, the next logical question is why

should image be related to recruitment and applicant attraction? From a cognitive

20

perspective, social identity theory suggests that our self-concepts are in-part shaped by
the organizations to which we belong (Dutton, Dukerich & Harquail, 1994; Tajfel &
Turner, 1985). That is, when an individual identiﬁes strongly with an organization, the
attributes he/she uses to deﬁne it also deﬁne him/her. This perspective is bolstered by the
ﬁndings of Tom (1971) who found that an individual’s most preferred employer was the
one most similar to themselves. As a result, membership in an organization that the
individual or others perceive negatively can lead to negative personal outcomes such as
stress and depression (Dutton et al., 1994). The more strongly one identiﬁes with an
organization, the stronger the positive or negative effects (Dutton et al., 1994).
Considering the central role work plays in many people’s lives, it would follow that
individuals would be attracted to organizations with a positive image (Dutton et al., 1994;
Tajfel & Turner, 1985).

In a more indirect fashion, familiarity with an organization may inﬂuence image
development, applicant attraction, and recruiting efforts. Cognitive psychology suggests
that individuals will pay more attention to and more easily recall familiar items than
unfamiliar ones (Catelli & Zogmaister, 2000; Christie & Klien, 1995). Additionally,
consumer research has demonstrated that pairing new products with familiar established
products (e. g., through product comparison ads) is an effective strategy for increasing
consumer recognition and awareness of new products and brand names (Dube & Schmitt,
1999). Similarly, research in education has demonstrated that it takes less attention to
comprehend articles and learn material on familiar topics than unfamiliar both in written
and video/verbal formats (Shimoda, 1993; Thorson & Lang, 1992). Thus, it follows that

potential applicants may pay more attention to or need less attention to recall

21

advertisements and information regarding familiar companies. Over time, this
accumulation of information from various sources will develop into an organization
image (Behling, Labovtiz, & Gainer, 1968). As a result, applicants may have
impressions of organizations or pre-existing images that developed long before they were
exposed to recruiting materials (Barber, 1998; Behling, Labovtiz, & Gainer, 1968).
Potential applicants’ prior impressions (i.e., pre-existing image) and degree of familiarity
with an organization may affect how much subsequent recruiting efforts inﬂuence one's
opinions of an organization (Gatewood et al., 1993). For example, if a potential applicant
is very familiar with and has a well developed image for company X, the information
presented in the recruiting materials may have less impact than it would for someone less
familiar with the organization. Additionally, familiarity may inﬂuence how much one’s
pre-existing image is affected or altered by the recruiting materials.

Other factors that may affect the impact of recruiting materials on applicant
perceptions and ultimately image are the marketing theories of signaling and umbrella
banding. The basic premise of these theories is that consumers do not like uncertainty so
companies try to send signals regarding product quality to consumers (Erdem, 1998;
Wemerfelt, 1988). These signals generally come in the form of warranties and service
guarantees because the high quality companies know that lower quality companies can
not afford to match these signals (Boulding & Kimani, 1993). Based on these signals,
consumers draw conclusions about companies and their products and avoid some of the
uncertainty associated with purchases (Boulding & Kimani, 1993; Erdem, 1998;
Wemerfelt, 1988). Over time, consumers become familiar with the companies and the

quality of their products, allowing companies to extend the types of products and services

22

they offer (i.e., umbrella branding; Erdem, 1998; Wemerfelt, 1988) while capitalizing on
the quality perceptions of their parent products. Consumers do not consider a new line of
products as high risk because of their previous experiences with the company and its
products serve as a bond with the consumer (Erdem, 1998; Wemerfelt, 1988). If one
extends this concept to image and recruiting, it follows that potential applicants will draw
on various signals and past experiences with a company such as its products, employees,
and advertising to reduce uncertainty when evaluating whether a company will make a
good employer3. As previously mentioned, recent studies have found support for
signaling theory such that applicants interpret information and experiences provided
during the recruiting process as indicators of broader organizational characteristics (e. g.,
image and PO ﬁt; Bretz & Judge, 1994; Rynes et al., 1991).

Essentially, reliance on company image and signals is likely related to a lack of
information (Rynes et al., 1991). As previously mentioned, many applicants have very
little information on which to base their application decisions and as a result may base
their decisions on their generalized perceptions of the organization’s image. Although
there has been no direct test of this hypothesis in the recruiting or image literature, a
similar phenomenon has been observed in the social psychology literature. Speciﬁcally,
research has shown that individuals can and will form an impression of someone based
on a very limited encounter (Ambady & Rosenthal, 1993; Borkenau & Lietiousness,
1992; Kenny, Homer, Kasher & Chu, 1992). With this in mind, it follows that

individuals develop pre-existing images of organizations over time based on signals and

 

3 A similar application of signaling theory was used by Spence (1973). Spence
essentially applied this theory in reverse by suggesting that organizations use signals
from applicants such as education level and past experience to reduce the uncertainty
involved in the hiring process.

23

limited encounters with company products, employees, advertisements etc. When a

I potential applicant is provided with additional information from organizational recruiting
materials, this new information should be incorporated into and have some impact on the
pre-existing image of the organization. That is, there is good reason to believe that image
is malleable. Furthermore, as previously discussed there is reason to believe that
supplementary ﬁt information should have a greater impact on organizational image (i.e,
knowledge, beliefs, and feelings about an organization) and other attitudinal outcomes
than complementary ﬁt information; thus, organizations concerned about their image may

want to emphasize supplementary ﬁt information.

Studies Relating Applicant Attraction and Organizational Image

 

There are very few studies that have speciﬁcally investigated the relationship
between applicant attraction and organizational image. One of the ﬁrst empirical studies
of applicant attraction and image in the recruiting literature was conducted by Tom
(1971). The primary objective of the study was to determine if applicants preferred
employers whose image was similar to their own self-concept. In this study, image was
deﬁned as a loose structure of knowledge, beliefs, and feelings about an organization.
The study involved 100 students from the University of California who were registered
with the school’s career placement services. The students completed a 15 scale
personality measure (Adjective Check List) and a six scale values measure (Study of
Values) for their most and least favored employer; at least a week later, participants
completed the same measures to describe themselves. The results indicated that
participants preferred organizations whose image was similar to their own image or self-

concept.

24

In many ways this was largely a ﬁt study. That is, applicants indicated that they
felt more favorably about organizations they perceived to be similar to themselves in
terms of values and personality (i.e., measures commonly used in supplementary ﬁt
studies). This tells us little about how or why potential applicants were considering these
organizations in the ﬁrst place, or where these organizations fell on the continuum of
organizational image. For instance, did the least favored employer have a negative
organizational image, was it simply the least similar to the applicant, or the least
favorable of the positive image employers? Additionally, the conceptual and operational
deﬁnitions employed in this study are inconsistent. Speciﬁcally, Tom (1971) deﬁned
image in a broad manner, however, the study measured image using instruments designed
to target speciﬁc constructs, namely personality and values (Barber, 1998).

The next study addressing applicant attraction and organizational image was not
published until 1982 by Belt and Paolillo. The goals of the study were to determine if
potential applicants are more likely to 1) respond to a newspaper ad for a positive image
ﬁrm or a negative image ﬁrm and 2) respond to an ad with speciﬁc or non-speciﬁc job
requirements. In a pilot test, 218 students were asked to rank 20 local fast food
restaurants from most favorable to least favorable. The rankings for each company were
summed to create an image index. After dividing the sample into 8 sub-samples on the
basis of race, sex, and student status (i.e., graduate or undergraduate) it was determined
that image rankings were consistent across the samples". The actual experiment involved
200 students divided into four conditions; positive image low speciﬁcity, positive image

high speciﬁcity, negative image low speciﬁcity, negative image high speciﬁcity. Each

 

4 The positive image ﬁrm fell within the top three for each sub-group and the negative
image ﬁrm was within the bottom three for each sub-group.

25

subject viewed 5 neutral ads5 and one experimental ad where the company name and the
position qualiﬁcations were manipulated. All advertised for a fast food manager position
and were similar in terms of size, shape, content, layout and use of white space (i.e.,
factors previously determined to inﬂuence the effectiveness of advertisements (Redman
& Matthews, 1992). The students were asked to read each advertisement and indicate
how likely they were to respond. The results indicated that 30% of the likelihood in
responding could be attributed to corporate image and there was no signiﬁcant difference
in response likelihood of speciﬁc and non-speciﬁc advertisements.

Practically, this study has several limitations. For example, the participants were
shown newspaper advertisements that were very similar in terms of both design and
content. As a result, applicants had very little information on which to base their
impressions or differentiate between these companies. That is, applicants with little
information use what is available; thus, if the information provided fails to differentiate
between the organizations, their pre-existing image becomes more salient. This tells us
little about the role image plays when there is other information available which
differentiates between the organizations or how pre-existing image may be altered by
additional information. A second limitation is that the researchers did not collect any
information regarding the subjects’ familiarity with the companies; thus, it is possible
that the negative image companies were simply the least familiar. Furthermore, this
study only looked at the extremes, that is, positive and negative image companies and
does not tell us anything about those companies that have a neutral organizational image.
Finally, the conceptual and operational deﬁnitions of image are somewhat inconsistent.

Speciﬁcally, image was deﬁned as a set of attributes about a particular ﬁrm, which can be

 

5 The neutral advertisements used companies that fell in the middle rankings.

26

induced from the way the employer deals with its employees, customers, clients, and
society; however, image was merely based on ranking company names. That is, no
questions regarding how the ﬁrms dealt with its employees, customers, clients, or society
were factored into the image index.

Gatewood et al. (1993) attempted to address four questions in their study: 1) are
potential applieants’ image perceptions consistent with those of executives, 2) is there a
difference between the general corporate image and the image held by potential
applicants (i.e., recruiting image), 3) what are the dimensions and correlates of the
recruiting image and, 4) if general image and the recruiting image differ, are they both
related to applicants’ intentions to apply? The study used ﬁve groups of business majors
from the University of Georgia; the researchers used a different group of students for
each part of the study. Students used to assess corporate image were provided with the
company name, while those used to assess recruiting image viewed advertisements from
the College Placement Council Annual (i.e., a campus recruitment publication). Twenty-
six ﬁrms from the Fortune 500 list and 13 ﬁrms that had recruiting advertisements in the
College Placement Council Annual were used in the study. For the 26 m; 500 ﬁrms,
corporate image was assessed using the same eight scales (i.e., quality of management;
quality of products or services; long-term investment value; innovativeness; ﬁnancial
soundness; ability to attract, develop and keep talented people; community and
environmental responsibility; and use of corporate assets) completed by the executives in
the m survey. For the thirteen ﬁrms from the College Placement Council Annual,

overall corporate image and recruitment image were assessed using a ﬁve point rating.

27

The results indicated that potential applicant’s image perceptions were not
consistent with the perceptions of executives in the Fombrun and Shanley study (1990)6
and that potential applicants do not rely on the market and accounting performance
indicators used by executives. The researchers also concluded that general corporate
image (i.e., reactions to a ﬁrm’s name) is different from recruiting image (i.e., reactions
to recruiting advertisements) although both types of image are related to application
intentions. Finally, these researchers concluded that image perceptions are largely a
function of the amount of information available to a potential applicant and that
applicants will perceive a company more positively as long as they have additional
information, regardless of its content.

The primary weakness of Gatewood et al’s (1993) study is that the conclusions
drawn from the results are somewhat extreme. Speciﬁcally, it is highly unlikely that
corporate image is entirely separate from recruiting image. It is possible that applicants
may hold a company in very high regard and never consider working there; however, it is
hard to believe that corporate image would not inﬂuence their impressions regardless of
what the recruiting materials may say. This ﬁnding may result from the use of different
samples for each aspect of the study instead of measuring both corporate and recruiting
image for the same group of applicants. A study conducted by Scheu, Ryan, and Nona
(1999) found that the ratings provided based on company name alone (general corporate

image) were highly correlated with ratings of the company after reviewing the recruiting

 

6 Fombrun and Shanley (1990) investigated the components of company reputation (i.e.,
image). The study looked at 292 ﬁrms rated in Fortune’s 1985 survey of executives.
These executive ratings form the basis for Fortune’s annual corporate reputational
rankings by industry. The results indicated that corporate executives (i.e., company
outsiders) use market and accounting signals as indicators of economic performance,
institutional signals (e.g., media visibility and social responsibility) as indicators of

28

portion of its web site (recruiting image). Furthermore, the assertion that perceptions will
improve with mere exposure to information is hard to believe. In fact the authors
themselves indicate that one would expect potential applicants to evaluate the
information they are presented with, even if it is all positive, in terms of ﬁt. Scheu et al.
(1999) found that after viewing the recruiting sections of company web-sites the
impressions of some companies declined while others improved, suggesting that potential
applicants do evaluate the information and alter company perceptions as a result.

Turban and Greening (1996) investigated the relationships between corporate
social performance (i.e., a ﬁrm’s tendency to act responsibly when dealing with
employees, customers and the community), reputation (i.e., image), and applicant
attraction. The study used corporate social performance data for 189 companies obtained
from the Kinder, Lydenberg, Domini & Co. Company Proﬁles database. Each of these
companies’ reputations was rated on a ﬁve point scale by 75 students; however, 28 ﬁrms
were eliminated from the study because less then 2/3 of the students indicated they were
familiar enough with the companies to provide reputation ratings. Attractiveness ratings
were obtained for the remaining companies (161) from 34 college seniors. The stimulus
for all ratings was simply company name. The results indicated that corporate social
performance is positively related to reputation and attractiveness as an employer and that
reputation is positively related to attractiveness.

One practical limitation of this and most other studies is the focus on familiar
organizations. If image is a large component of attraction, what can companies with no

or very weak images do to attract applicants? Furthermore, although this study included

 

conformity to social norms, and strategy signals (e.g., diversiﬁcation) as signals of
strategic postures when determining where a ﬁrm falls relative to its competitors.

29

organizations whose image ratings ranged from 2.47 - 4.87 (on a ﬁve point scale), we
still don’t know how an organization’s pre-existing image may be affected by the type of
information available to applicants, or when/how the effects of a negative organizational
image can be overcome.

The most recent study was conducted by Highhouse et al. (1999). Although the
primary purpose of this study was to illustrate techniques for identifying image
dimensions and benchmarking by industry, the study did address potential applicant
attraction. Speciﬁcally, the study investigated the perceptions of a group of high school
students and a group of retirees towards 20 local fast food chains. Company employment
image or an organization’s image as a place to work was measured using a ﬁve-item
scale adapted from Turban and Keon’s (1993) applicant attraction scale. Each subject
was randomly assigned a questionnaire with one company’s logo and asked to respond to
each item as it applied to the company indicated. The results indicated that the 15 image
dimensions the study identiﬁed for fast food restaurants (e.g., advancement opportunities,
work atmosphere, advertising, chain size, hours, location, respectability, pay, etc.) were
equally predictive of intentions to apply for both the high school (n= 336) and retiree (n=
102) samples and that image perceptions were similar for both samples. These ﬁndings
suggest that recruitment strategies for these two applicant pools may not need to be very
different despite the large age difference.

This study has a couple of weaknesses. The ﬁrst is that this study deﬁned
company employment image as an organization’s image as a place to work, which is
somewhat inconsistent with the image questions asked. Speciﬁcally, company

employment image was measured using an adapted applicant attraction scale. Examples

30

of the adapted question include “I’d prefer a job there over a job in most other fast-food
restaurants” and “HI were looking for a fast-food job, a job there would be very
appealing.” These adapted questions still appear to be measuring applicant attraction as
opposed to the company’s image as a place to work. The second potential weakness of
this study is the assertion that the ﬁfteen dimensions found represent image. A number of
these dimensions including location, pay, work hours, work variety, and task demands
would be more accurately described as job attributes. As previously mentioned, job
attribute information has been shown to be an important factor in application decisions
(Barber & Roehling, 1993; Bretz & Judge, 1994; Cable & Judge, 1994; Honeycutt &
Rosen, 1997; Laabs, 1991; Noe, Steffy, & Barber, 1988; Redman & Matthews, 1992;
Rynes, Schwab, & Heneman, 1983; Rynes & Lawler, 1983; Schwoerer & Rosen, 1989),
which is a viable alternative to the study’s ﬁndings.

Although these studies have increased our understanding of the role image plays
in the recruiting process, as discussed above, they each have their limitations. It is
important to note that one of the most prevalent and serious limitations is inconsistency in
the deﬁnition and operationalization of image. Speciﬁcally, some studies employ very
global assessments of image such as a single item rating, while others equate image with
values, personality, or job attributes. Furthermore, the stimuli vary greatly between
studies. Speciﬁcally, some studies provide applicants with advertisements while others
simply use company name. As a whole, these limitations leave several questions
unanswered. Speciﬁcally, none of the research has directly addressed the full range of
image; that is, most have not considered positive and negative image ﬁrms and no study

has considered the levels in-between (i.e., neutral). Without this knowledge it is difﬁcult

31

to determine the magnitude of image effects, the relative importance of image under
various conditions, or how and when companies can compensate for a negative image.

Similarly, information or a lack thereof appears to play a critical role and should
be further investigated. Speciﬁcally, is the key the amount or content of the information
provided, and can providing certain types of information (e.g., supplementary ﬁt
information) compensate for, or even change, an applicant’s pre-existing image of a
company? As previously discussed, the literature suggests that supplementary ﬁt
information will have a stronger effect on attitudinal outcomes than will complementary
ﬁt (Kristoff, 1996). If one extends this notion, supplementary ﬁt information should
impact organizational image.

Another issue that needs to be further addressed is that of familiarity. Previous
research suggests that familiarity should inﬂuence a company’s image, and how a
potential applicant responds to recruitment materials; however, very little is known about
how potential applicants respond to unfamiliar companies for which they have a very
weak or no image perceptions. Additionally, studying unfamiliar companies may shed
light on how potential applicants develop an image by investigating what types of
information potential applicants depend on, and how they interpret various recruitment
materials. The current study addressed a number of these questions and issues.

Current Studv

As previously discussed, the pool of qualiﬁed applicants is shrinking and as a
result organizations ﬁnd themselves competing for employees (Behling, Labovtiz &
Gainer, 1968). In today’s competitive market, it would be in an organization’s best

interest to vary the content of its brochures to inﬂuence applicant behavior and meet

32

current organizational needs. The current study investigated the possibility of
manipulating the type of information provided in recruiting brochures to inﬂuence
applicant behavior and perceptions. Speciﬁcally, working within a recruiting context,
can the type of information provided (i.e., supplementary or complementary ﬁt) inﬂuence
applicant intentions to apply, organizational image, and applicant quality and quantity?
The relationships between these concepts are depicted in the study’s conceptual model
(see Figure 1). A brief overview of the model is provided below. The model and its
speciﬁc links will be discussed in detail throughout this section.

Overview of the Conceptual Model

In this model (see Figure 1), it is proposed that job seekers start out with a pre-
existing image of potential employers. As previously discussed, this pre-existing image
develops over time based on signals and limited encounters with company products,
employees, advertisements, etc. Similarly, job seekers will vary on the degree of
familiarity they have with potential employers and this is expected to affect how much
job seekers will be inﬂuenced by the recruiting process. As these job seekers enter the
recruiting process they will receive various types of information that is likely to inﬂuence
their knowledge, beliefs, and feelings about an organization (i.e., image; Tom, 1971),
resulting in a revised or post-image of the organization. Similarly, based on the available
information job seekers will make some determination of how well they would ﬁt at
various organizations (i.e., perceived ﬁt assessment). However, due to the need for self-
preservation and consistency, job seekers’ ﬁt assessments and post-images are expected
to inﬂuence each other. Ultimately, the available information, post-image, and ﬁt

assessments will impact job seekers’ intentions to apply. Finally, the relationship

33

between information type and intentions to apply is expected to be weaker for the more
selective qualiﬁed applicants.

Effects on Intentions to Apply

The literature suggests that there are a number of factors that may inﬂuence job
seekers’ application decisions, including the recruiting/selection process, job attributes
(e. g., compensation, location, beneﬁts, etc), company polices (e. g., reward systems,
promotion systems, family friendly and diversity programs, etc), individual differences
(e. g., conscientiousness, conﬁdence of employability, etc), the available information,
organizational image, and ﬁt perceptions to name a few (Barber, 1998; Barber &
Roehling, 1993; Belt & Paolillo, 1982; Breaugh, 1983; Bretz, Ash, & Dreher, 1989; Bretz
& Judge, 1994; Cable & Judge, 1994; Cable & Judge, 1996; Chatman, 1991; Gatewood
et al., 1993; Highhouse et al., 1999; Honeycutt & Rosen, 1997; Judge & Bretz, 1992;
Kristoff, 1996; Laabs, 1991; Noe, Steffy, & Barber, 1988; Redman & Matthews, 1992;
Rynes, Bretz & Gerhart, 1990; Rynes, Schwab, & Heneman, 1983; Rynes & Lawler,
1983; Saks & Ashford, 1997; Schwoerer & Rosen, 1989; Tom, 1971; Turban &
Greening, 1996; Turban & Keon, 1993). As indicated by the model (see Figure l), the
current study addressed the inﬂuence of post-image (link b), type of information (link d),
and perceived ﬁt (link c) on application intentions.

Previous research on organizational image clearly suggests image is related to
applicant attraction and intentions to pursue further contact with a ﬁrm (Belt & Paolillo,
1982; Gatewood et al., 1993; Highhouse et al., 1999; Tom, 1971; Turban & Greening,
1996). Speciﬁcally, the literature indicates that applicants prefer organizations with a

positive image over organizations with a negative image (Belt & Paolillo, 1982;

34

Gatewood et al., 1993; Highhouse et al., 1999; Turban & Greening, 1996). However, it is
important to note that previous research has failed to look at the entire range of
organizational image (i.e., positive, neutral, and negative image). The current study
expanded upon past research by addressing this issue. Based on the results of past
research it is hypothesized that:

H1: Intentions to apply will increase as post-image increases. (link b)

The current study also investigated the effects of information type on applicant
intentions. The existing literature indicates that applicants are seeking information and
that they will react to and draw inferences from recruiting materials. However, past
research has typically focused on a very limited set of content/organizational attributes,
thus, it is unclear how job seekers would respond to other types of information. The
current study was particularly interested in how potential applicants’ perceptions and
behaviors may be affected by supplementary vs. complementary ﬁt information and how
various organizations can capitalize on these effects to achieve their recruiting goals.
Speciﬁcally, negative and neutral image organizations generally have to settle for
attracting applicants, not weeding out applicants; while positive image ﬁrms may be
looking to reduce costs by having unqualiﬁed applicants self-select out of the process.
Because recruiting brochures can only be so long, it would be very useful to know what
types of information (i.e., supplementary vs. complementary) companies should
emphasize to achieve the desired results (i.e., quality vs. quantity).

As previously discussed, applicants place a good deal of emphasis on
supplementary ﬁt, make job choice decisions that are consistent with their ﬁt perceptions,
which are in turn are inﬂuenced by recruitment efforts (Barnett, Vaughan, & Moody,

1997; Cable & Judge, 1996; Chatman, 1991; Judge & Cable, 1996; Judge & Bretz, 1992;

35

Kristoff, 1996; Keon, Latack, & Wanous, 1982; Saks & Ashford, 1997; Tom, 1971).
Additionally, if supplementary ﬁt information is not provided, applicants will infer this
information from other sources. Thus, by providing supplementary ﬁt information
organizations increase the likelihood that applicants will draw accurate ﬁt conclusions.
Although some job seekers may choose not to apply to the organization because they
perceive a poor ﬁt, these numbers should not be especially large because the value and
goal information provided is typically general, very positive, and non-exclusionary.

Complementary ﬁt information, on the other hand, could be perceived as
exclusionary and reduce the number of applicants. Speciﬁcally, based on the existing
literature, there is reason to believe that recruiting materials containing information about
speciﬁc competencies (i.e., complementary ﬁt information) will cause less qualiﬁed
applicants to self select out of the process (Mason & Belt, 1986; McCormick, DeNisi &
Shaw, 1979; McCormick, Jeanneret, & Mecham, 1972; Thorsteinson, Ryan, &
McFarland, 1997; Wilk & Sackett, 1996). If one extends this to the current study, it
follows that complementary ﬁt information provided early in the recruiting process
should deter less qualiﬁed applicants while supplementary ﬁt information should deter
comparatively fewer applicants due to its non-exclusionary nature. Thus it is
hypothesized that:

H2: Intentions to apply will be higher when applicants are supplied with

supplementary fit information than when supplied with complementary
fit information. (see Figure 1 link (1)

Along the same lines, past research indicates that individual differences can
impact how much inﬂuence ﬁt perceptions have on applicant application and job choice
decisions. Speciﬁcally, applicants who have (or believe they have) more job

opportunities have the freedom to seek positions with a better ﬁt, that is, qualiﬁed

36

applicants can be more selective (Cable & Judge, 1996; Chatman, 1991; Breaugh, 1983).
As a result, these applicants tend to look for reasons to weed out organizations. Thus, for
qualiﬁed applicants, complementary ﬁt information should provide little to discourage
them; however, if anything in the supplementary ﬁt information is perceived negatively,
they are likely to self select out of the process. Thus it is hypothesized that:

H3: Applicant quality will moderate the relationship between the type of
information provided and intentions to apply such that type of
information provided will have less of a relationship to intentions to
apply for qualiﬁed applicants. (link h)

Another factor that is expected to inﬂuence applicant attraction and intentions to
apply is perceived ﬁt with an organization (link c). Perceived ﬁt refers to one’s beliefs or
expectations regarding compatibility with an organization. Although these beliefs or
perceptions may or may not be accurate, (i.e., Accuracy is generally associated with
actual as opposed to perceived ﬁt) they are expected to play a critical role in the initial
decision process. That is, if potential applicants do not hold positive ﬁt perceptions they
may not apply to an organization, thus, making actual ﬁt or the accuracy of these
perceptions irrelevant. As previously discussed, the literature clearly suggests that
applicants prefer organizations whose characteristics are similar to their own (Barnett,
Vaughan, & Moody, 1997; Cable & Judge, 1996; Chatman, 1991; Judge & Cable, 1996;
Judge & Bretz, 1992; Keon, Latack, & Wanous, 1982; Tom, 1971), that applicants make
job choice decisions that are consistent with their PO ﬁt perceptions, and that these
perceptions are inﬂuenced by recruitment efforts (Cable & Judge, 1996; Saks & Ashford,
1997). It is important to reiterate that past research has typically addressed global ﬁt

assessments and has made no effort to investigate or measure different types of ﬁt

assessments (i.e., complementary and supplementary). In keeping with past research, the

37

current study employed one ﬁt measure; however, the questions have been adapted to
reﬂect both types of ﬁt and a factor analysis will be run to determine if there are two
factors. Thus it is hypothesized that:

H4: Intentions to apply will be positively related to assessments of fit. (link C)

When discussing ﬁt perceptions, it is also important to mention that the image ﬁt
relationship is expected to be recursive (link g). As previously discussed, this is an
individual cognitive process; thus, we can not predict the direction of the adjustments to
ﬁt and image for any given individual. We can merely predict that these two perceptions
should be related each other. That is, in some cases individuals will adjust their ﬁt
perceptions to be more in line with their image perceptions while in other cases
individuals will adjust their image perceptions to make them more consistent with their
ﬁt perceptions. Furthermore, it is expected that there will only be a moderate correlation
between post image and the perceived ﬁt assessment. This expectation is based on the
notion that although ﬁt and image will affect each other, they remain separate constructs.
Thus it is hypothesized that:

H5: Post image and the perceived fit assessment will be moderately
correlated.

Effects on Post Im_ag§

In addition to application intentions, the current study also sought to expand past
research by addressing the possibility of image malleability. That is, can an organization
improve or change its image? Considering the impact image has on applicant attraction
and intentions to apply, organizations with neutral or negative images would be well
served if they could change or improve their corporate image. It is believed that

individuals develop pre-existing images of organizations over time based on signals and

38

limited encounters with company products, employees, advertisements, etc. When a
potential applicant is provided with additional information from recruiting materials, this
new information should be incorporated into and have some impact on the pre-existing
image of the organization (link a).

The current study was speciﬁcally interested in the effects of ﬁt information on
organizational image (link f). As previously discussed, providing applicants with
supplementary ﬁt information (i.e., company personality, goals, or values) may impact
perceptions of organizational image. The literature suggests that supplementary ﬁt
information will have a stronger effect on attitudinal outcomes than will complementary
ﬁt (Kristoff, 1996). If one extends this notion, supplementary ﬁt information should
impact knowledge, attitudes, beliefs, and feelings about an organization or organizational
image and complementary ﬁt information should have less of an effect. Thus the current.
study hypothesizes that:

H6: The type of ﬁt information provided will moderate the pre/post image
relationship such that the greatest changes in image perceptions will be
found when applicants are supplied with supplementary ﬁt information.
(link i)

Another factor that is likely to moderate the pre-post image relationship is an
applicant’s familiarity with an organization (link e). Past studies suggest that familiarity
with an organization may inﬂuence image development, applicant attraction, and
recruiting efforts. Speciﬁcally, there is good reason to believe that applicants are not
‘blank slates’ (Barber, 1998). That is, over time, potential applicants accumulate
information from various sources and this information forms the basis for an organization

image (Behling, Labovtiz, & Gainer, 1968). As a result, applicants may have

impressions of organizations or pre-existing images that developed long before they were

39

exposed to recruiting materials (Barber, 1998; Behling, Labovtiz & Gainer, 1968).
Potential applicants’ pre-existing image perceptions and degree of familiarity with an
organization may affect how much subsequent recruiting efforts inﬂuence opinions of an
organization (Gatewood et al., 1993). For example, if a potential applicant is very
familiar with and has a well developed image for company X, the information presented
in the recruiting materials may have less impact than it would for someone less familiar
with the organization. Additionally, familiarity may inﬂuence how much one’s pre-

existing image is affected or altered by the recruiting materials. Thus, it is hypothesized

that:
H7: Familiarity will moderate the pre/post image relationship such that the
less familiar the applicant is with the organization the more image will
change from pre to post. (link e)
Chapter 2
METHODS
Subjects

All participants were recruited from psychology classes at a large mid-westem
university and received course credit for their participation. The pilot study included 25
participants. 76% of the participants were female and 84% were White. 52% of the
participants were between the ages of 18 and 20 and 56% were juniors and seniors. The
experiment included 203 participants total and there were approximately 34 people in
each of the six cells. 75% of the participants were female and 86% were white. 74% of
the participants were between the ages of 18-20 and 42% were juniors and seniors.
Demographic comparisons of the pilot and experimental samples indicate that there were

no signiﬁcant differences between the two groups of participants. Additionally,

40

comparisons of the two experimental conditions indicated that there were no signiﬁcant
demographic differences between the groups.
De_sign

A 3 (company image: positive, neutral, negative) x 2 (type of ﬁt information:
complementary or supplementary) between subjects design was employed. A between
subject design was used because it allowed the information provided to the subjects to
remain constant (i.e., complementary or supplementary) across organizations and avoid
potential order effects. Subjects were randomly assigned to one of the 6 conditions using
the roll of a die and were asked to review one of two sets of recruiting materials and
answer a series of questions.
Procedure

A pilot study was conducted to select three companies for the experiment.
Participants were informed that the purpose of the study was to investigate student
perceptions of various companies and were asked to complete a consent form (see
Appendix A). Each participant then received a survey that instructed them to rate 10-15
manufacturing based m 500 companies using the image scale developed for this
study (see Appendix B for measures). In addition to image questions, the survey
contained demographic questions for later comparisons of the pilot and experimental
samples and the familiarity scale to establish some sense of how the sample varies in its
familiarity within and between the organizations. Past research indicates that students are
not familiar with many companies found on lists such as the Fo_rtu_r_ip 500 (Scheu et al.,
1999; Turban & Greening, 1996), and this should be taken into consideration when

selecting organizations for the experiment. After completing the survey, participants

41

were provided with a debrieﬁng form (see Appendix C). The goal of the pilot was to
identify companies that varied in image and ultimately include 1 positive, 1 negative, and
1 neutral image organization in the experiment. The ﬁnal decision regarding which
companies to include was based on the means and variances of the image data.

The data for the actual experiment was collected in two parts. At least 24 hours
prior to the actual experiment, participants completed a self-evaluation of their
competencies as part of the pre-screening questionnaires completed on the subject pool
web site (see Appendix E). Additional competency questions were included to draw
attention away from the competencies relevant to the experiment. The goal was to collect
this information at a separate point in time to prevent participants from making any
connection between the competencies advertised in the complementary ﬁt condition and
the self-ratings. Experiment participants were informed that the purpose of the study was
to evaluate recruiting materials and were asked to complete a consent form (see
Appendix D). Each participant received a packet for one of the six conditions. Each
packet contained either the supplementary (i.e., values) or complementary (i.e.,
competencies) based recruiting materials developed for this study (see Appendix E for
recruiting materials). For this study, values were deﬁned as “enduring beliefs that a
speciﬁc mode of conduct or end-state is preferred to its opposite, thereby guiding
individuals’ attitudes, judgements, and behaviors” (Cable & Judge, 1996; Chatman, 1989,
Rokeach, 1973). The speciﬁc company values described in the supplementary ﬁt
condition included Ravlin and Meglino’s (1987) four values and an additional 5 values

from the Organizational Cultural Proﬁle (OCP)7; these ﬁve values were among the most

 

7 The OCP was used as a measure of organizational values by Cable & Judge (1996,
1997)

42

frequently mentioned values on company web sites (Scheu et al., 1999). For this study,
competencies were deﬁned as broad classiﬁcations of characteristics and skills that cut
across positions in organizations. The speciﬁc competencies described in the
complementary ﬁt condition were selected from a taxonomy developed by Tett and his
colleagues (1999). After conducting a detailed literature review and a series of surveys,
Tett (1999) identiﬁed 9 dimensions and 53 competencies. The current study included one
competency from each of the nine dimensions. The packets contained demographic
questions, a pre-image measure, a familiarity scale, a post-image measure, and questions
regarding their intentions to apply (see Appendix B).

Instructions in the packet informed participants that company X (i.e., the company
they were assigned to) was updating segments of its recruiting materials and that the
company wanted to see how students respond to the current draft. As research indicates
that design features can inﬂuence the impact of recruiting materials (Redman &
Matthews, 1992), participants were informed that company X is concerned with the
content of the materials not the layout or design. Before reviewing any materials, the
participants completed the demographic questions, the familiarity scale, and the pre-
image scale. After completing these questions, participants were asked to review the
materials, pretend they were looking for a job and answer the remaining questions
accordingly. As previously mentioned, past research has indicated that job attributes can
play an important factor in job choice decisions (Barber & Roehling, 1993; Bretz &
Judge, 1994; Cable & Judge, 1994; Honeycutt & Rosen, 1997; Laabs, 1991; Noe, Steffy,
& Barber, 1988; Redman & Matthews, 1992; Rynes, Schwab, & Heneman, 1983; Rynes

& Lawler, 1983; Schwoerer & Rosen, 1989); in an effort to take job attributes out of the

43

equation, participants were also informed that they should assume the company has a
position they would be interested in, the position pays well relative to similar positions in
other companies, and there are positions available in good locations. After participants
completed the questions in the packet, they were provided with a debrieﬁng form (see
Appendix F).

Measures

The subjects completed a variety of measures, which are described below. The
items are provided in Appendix B.

Familiarity. This scale assessed respondents’ familiarity with the organizations
included in the study. The familiarity scale consisted of 10 items rated on a 5-point likert
scale, which ranged from “strongly disagree” to “strongly agree.” The questions
composing the scale were adapted from Gatewood et al. (1993).

Intentions to apply. This scale assessed respondents’ intentions to apply to the
organization. The scale consisted of 4 items rated on a 5-point likert scale which ranged
from “strongly disagree” to “strongly agree” and two items that were rated as yes, no, or
maybe. These questions were developed for the study in an attempt to capture more of a
behavioral component of application intentions. The ﬁrst 4 questions were adapted from
Ployhart and Ryan (1998). In past studies, the reliability estimates ranged from .72 to .88.

PrelPost Image. This scale assessed image as a loose structure of knowledge,
beliefs, and feelings about an organization held by a potential applicant. The scale
consisted of 18 items rated on a 5-point likert scale, which ranged from “strongly

disagree” to “strongly agree.” The scale was developed by compiling items from a

number of sources including Barber and Roehling (1993), Cable and Judge (1997), Goltz
and Giannantonio (1995), and Highhouse et al. (1999).

Fit Assessment. This scale assessed respondents’ perceived ﬁt with the
organization. The scale consisted of 6 items rated on a 5-point likert scale, which ranged
from “strongly disagree” to “strongly agree.” The scale was developed by compiling
items from Cable and Judge, (1996), and Goltz and Giannantonio (1995).

Compptency Assessment. This scale assessed respondents’ perceived
competencies (e.g., team building, customer focus, creative thinking, self-development).
The scale consisted of 9 items rated on a 5-point likert type scale, which ranges from “not
at all skilled” to “very skilled.” The scale was developed for the purpose of this study.

Demoggaphics. Information regarding various demographic variables including
sex, race, age, years in college.

Applicant Qpality. Scores for applicant quality were derived by standardizing and
subsequently summing individuals’ competency assessment scores, GPA, and ACT
scores (or the SAT equivalent to the ACT). The competencies relevant to the study were
summed to create a single value; this approach was taken to reduce the weight attributed
to self-ratings in the quality composite. Finally, missing GPA and ACT information was
addressed by using mean replacement.

Manipulation Check. These 4 questions were designed to see if the participants
understood the content of the information they received. The pre-image measure served
as a manipulation check to ensure that the participants perceived the organization as

being in the correct image grouping (i.e., positive, neutral, negative).

45

Distrpcter Questions. These 6 questions were included to make the experiment
more believable. The instructions indicated that that company X is updating segments of
its recruiting materials and the company wants to see how students respond to the current
draft; as a result, students would expect to provide their comments or reactions to the
materials. The items were rated on a 5-point likert scale, which ranged from “strongly
disagree” to “strongly agree.”

Chapter 3
RESULTS
Pilot Data

To reiterate, a pilot study was conducted in an effort to identify three companies
that varied in organizational image (i.e., 1 positive, 1 negative and 1 neutral). 25
participants rated 15 companies on image and familiarity. The means and standard
deviations for image and familiarity are presented in Table 1. The three companies
selected for the experiment were: (a) Kodak, a high image organization, (b) Proctor and
Gamble, a neutral image organization and (c) Phillip Morris, a low image organization.
These particular companies were selected because they spanned the range of image and
varied on degree of familiarity. There was a noticeable relationship between familiarity
and image such that as familiarity increased image perceptions generally increased (see
Table 1). The average correlation between ﬁt and image was r = .31. Finally, coefﬁcient
alpha was calculated for each of the image and familiarity scales. The alphas for
familiarity ranged from .42 to .96 with an average of .75. The alphas for image ranged

from .90 to .94 with an average of .91.

46

Table 1

mscriptive Statistics & Correlations for the Pilot Data

 

 

 

Image Familiarity Image/
Familiarity

Company Mean SD Mean SD Correlation
Boeing 61.28 7.00 21.32 6.84 .695**
ConAgra 53.64 0.91 15.70 5.63 -.004
Dow Chemical 60.92 8.45 27.48 6.12 .121
Du Pont 60.60 5.40 25.40 4.37 .469*
Ford 62.76 9.26 32.28 4.38 .155
General Motors 63.48 6.95 30.92 6.15 .403*
Intel 65.40 7.89 27.96 5.14 .442*
International Paper 53.56 5.36 17.76 5.90 .364
Kodak 66.92 7.14 31.84 4.10 .371
Lockheed Martin 55.48 3.85 17.72 6.69 .595**
Lucent Technologies 58.84 8.80 22.32 9.50 .707**
Microsoft 66.72 9. 16 34.24 3.72 .300
Philip Morris 53.00 9.00 22.04 8.20 .046
Proctor and Gamble 60.44 6.94 26.76 6.98 .091
R. J. Reynolds 57.84 9.10 24.20 6.47 .519**

 

Note. Organizations in bold were chosen for the ﬁnal experiment. N= 25. *p 5 .05.
**p 5 .01. Possible scores on the image scale ranged from 18-90. The average range for
image across the 15 organizations was 25.2 with a low of 4 and a high of 51.

47

Preliminm Analyses

A series of exploratory factor analyses were run to examine the factor structure of
the ﬁt and image measures. Traditionally, PO ﬁt measures have been comprised of 14
questions and have acceptable alphas (i.e., .70 or above). In most cases the same types of
measures were employed regardless of the type of ﬁt being investigated. The current
study used both the traditional ﬁt questions (Cable & Judge, 1997; Goltz &
Giannantonio, 1995) which are more reﬂective of overall and supplementary ﬁt (e. g.,
values) and included additional questions with a complementary ﬁt (e. g., skills and

abilities) focus. A principal axis factor analysis with a varimax rotation indicated that
the items all loaded on a single factor. This factor was the only factor with an eigenvalue
over one, and accounted for approximately 50% of the variance. Based on the results of
this analysis and the high alphas, a single ﬁt scale was used for all analyses.

As previously discussed, past research has not adequately or consistently
measured organizational image as a construct. As a result, a new measure was deve10ped
for this study. A series of principal axis factor analyses with varimax rotations were
conducted on the pre and post image measures across all the data to examine the
dimensionality of this measure. The measure appears to be multidimensional but the
factors are not interpretable and they are not consistent from pre to post image. Thus, the
factor structure of this measure was examined within company and from pre to post;
however, these factors were also uninterpretable. This is not surprising considering that
the measure is comprised of 18 items and the samples within company (i.e.,
approximately, 68) are too small to yield stable factors (Fabrigar, Wegener, MacCallum,

& MacCallum, 1999).

48

Finally, a principal components8 factor analysis with varimax rotation was
conducted on the image and ﬁt measures to further examine the relationship between
these constructs. Due to the difﬁculties associated with interpreting the image factor
analyses discussed above, the analysis was run forcing two factors. The results indicate
that image and ﬁt are distinct constructs; that is the image and ﬁt items load on different
factors. The ﬁrst factor was, composed of image items, had an eigenvalue of 8.34, and
accounted for approximately 35% of the variance. The second factor was composed of
ﬁt items, had an eigenvalue of 2.52, and accounted for approximately 11% of the
variance.

Coefﬁcient alpha was calculated for each of the measures across all data and
within company and ﬁt conditions (See Table 2). Alpha was at or above .70 for all
measures with the exception of Kodak’s familiarity alpha. Kodak’s alpha may have been
lower than the others due to a high familiarity with its products and advertisements and
low familiarity with the organization as an employer. Similarly, the means and standard
deviations were calculated for all measures across all data (See Table 3) and within
company and ﬁt conditions (See Table 4). Table 5 presents the intercorrelations between
all the measures and demographic information.

Of particular interest is the signiﬁcant correlation between self-reported
competencies and ﬁt r = .28 p < .01. Speciﬁcally across all the data, those who reported

higher competency ratings perceived a better ﬁt. Examining the correlations by ﬁt

 

8 Due to the amount of shared variance between the two variables, the principal axis
analysis failed and the more lenient principal components analysis was used instead.

49

 

 

 

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53

condition reveals a higher correlation for respondents in the complementary fit condition
r = .34 p < .01 (i.e., those who reviewed recruiting materials stressing competencies) than
the supplementary ﬁt condition r = .24 p_ < .05. A Fisher’s Z transformation for
comparing correlations from independent samples indicates that these correlations are not
signiﬁcantly different from each other. This suggests that the relationship between ﬁt
and self-reported competencies may simply be a reﬂection of applicant conﬁdence rather
than a ﬁt assessment based on the competencies emphasized in the complementary ﬁt
condition. Another potentially interesting correlation is the one between gender and post-
image r = .15 p < .05. Speciﬁcally, females typically gave higher post-image ratings than
males. This correlation suggests gender differences in image perceptions and image
malleability and should be addressed in future research.

Manipulation checks were performed for both image and ﬁt perceptions. For
image, the manipulation involved selecting companies that were generally thought of as
high, neutral, and low image organizations. Based on the pilot data, Kodak, Proctor &
Gamble, and Philip Morris were selected as the high, neutral, and low image
organizations respectively. To determine if the image manipulation was effective a one-
way AN OVA with contrasts was conducted using the pre-image measure. The result of
this analysis indicates that there was a signiﬁcant difference in the image means between
companies, E (2,199)=35.72, p <.Ol. Furthermore, the pattern of means indicates that the
image manipulation was successful; that is, Kodak’s initial image ratings were higher
than Proctor & Gamble’s, which in turn were higher than Philip Morris’ (i.e., the
contrasts indicate that the pre-image means for each of the organizations are signiﬁcantly

different from each other; see Table 3).

54

For type of information, the manipulation involved providing participants with
either supplementary (i.e., information regarding the company’s values), or
complementary ﬁt information (i.e., information regarding the competencies an employee
needs to be successful). To assess the effectiveness of this manipulation, all participants
answered 4 yes/no questions regarding the type of information they received (see Table
6). An overall Pearson chi-square test indicates that there was a signiﬁcant relationship
between ﬁt condition and the type of information the participants believed they received
for the ﬁrst x2 (1, u: 203) = 6.91, second p_ < .05, 2 x2 (1, E= 203) = 8.12, p < .05, and
fourth x2 (1, 13: 200) = 17.22, p_ < .05 questions. A signiﬁcant relationship was not found
for question three 380, 13: 202) = 2.78, p > .05. The raw frequency information for
these questions, however, both overall and broken down by ﬁt type and company
indicates that for all practical purposes the manipulation failed (see Table 6). In nearly
all cases, the vast majority of participants believed that they received both supplementary
(i.e., information regarding the company’s goals and values) and complementary (i.e.,
information regarding the type of characteristics, skills, and abilities the company is
looking for in new employees) ﬁt information, regardless of the ﬁt condition. Due to the
signiﬁcance of the chi-squares, one may argue that there are mixed results and that the
manipulation was simply too weak to influence the majority of participants.

Company Analyses
Before addressing the speciﬁc hypotheses which consider the data set as a whole,

potential differences between the three companies are discussed to provide the reader

55

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56

with a better feel for the data. As previously mentioned, this is one of the first studies to
attempt to consider a full range of organizational image; as a result, a series of analyses
were conducted to explore potential differences between the three companies. As part of
the experimental manipulation, three organizations were selected that initially differed on
organizational image. As previously discussed, this manipulation was successful (see
Table 3 for contrast results). Additionally, a one-way ANOVA comparing post-image
means indicated that signiﬁcant differences between the companies remained even after
reviewing the recruiting materials E (2, 200): 9.02, p_ <.01. Speciﬁcally, Kodak’s image
ratings were still higher than Proctor and Gamble’s, which in turn were higher than Philip
Morris’; however the means for Proctor and Gamble and Philip Morris were not
signiﬁcantly different from each other (see Table 3 for contrast results).

Due to the potential for differences across the range of organizational image, one-
way AN OVA89 with contrasts were conducted within each company for each of the key
measures in the study. A one-way ANOVA comparing ﬁt perception means indicated
that there were no signiﬁcant differences between companies, E (2, 200): 1.16, p =.316
(see Table 3 for contrast results). Similarly, a one-way ANOVA comparing application
intentions indicated that there were no signiﬁcant differences between companies, E (2,
193): .482, p =.618 (see Table 3 for contrast results). Finally, a one-way ANOVA
comparing familiarity means indicated that there were signiﬁcant differences in

familiarity ratings E (2, 200): 21.99, p <.01 such that Kodak’s familiarity ratings were

 

9 Individual AN OVAS were employed instead of an omnibus MAN OVA due to the
difficulty associated with justifying a linear composite of the dependent variables tested
(Tabachnick & Fidell, 1996). Additionally, Box’s M indicated that the covariances are
not equal across the dependent variables; thus violating a key MANOVA assumption
(T abachnick & Fidell, 1996).

57

higher than Proctor and Gamble’s, which in turn were higher than Philip Morris’;
however the means for Proctor and Gamble and Philip Morris were not signiﬁcantly
different from each other (see Table 3 for contrast results).

Hypothesis Tests

Hypothesis 1 stated that intentions to apply would increase as post-image
increased. To test this hypothesis a correlation was calculated between intentions to
apply and post-image. Across all the data there was a signiﬁcant moderate correlation of
r = .44 p < .01; correlations of r = .45 p < .01 were found for each company individually,
thus, supporting Hypothesis 1. This result is consistent with past research, which
suggests that image is related to applicant attraction and intentions to pursue further
contact with a ﬁrm (Belt & Paolillo, 1982; Gatewood et al., 1993; Highhouse et al., 1999;
Tom, 1971; Turban & Greening, 1996). However, this is the ﬁrst study to demonstrate
this effect across a range of organizational image.

Hypothesis 2 predicted that intentions to apply would be higher when applicants
were supplied with supplementary ﬁt information than when supplied with
complementary ﬁt information. To test this hypothesis an independent samples t-test was
conducted across all the data; (194) = -.03, p = .98 and within company (see Table 7).
The results indicate that there were no mean differences in application intentions across
type of ﬁt information; thus, Hypothesis 2 was not supported. This is not surprising
considering the manipulation check indicates that the type of information manipulation

failed.

58

Table 7

Indeppndent Samples t-tests Comparing Intentions to Apply Means for the
Supplement_apy and Complementary Fit Conditions

 

Supplementary Fit Complementary Fit

 

 

Company Mean SD Mean SD Mean t-value E
Difference

Overall 19.39 5.1 1 19.41 5.25 .02 -.031 .976

Kodak 20.15 4.37 19.19 5.35 .96 .800 .427

Proctor & 19.53 4.86 19.77 4.84 -.24 -. 195 .846

Gamble

Philip 18.50 5.98 19.31 5.65 -.813 -.567 .573

Morris

 

ﬁt; The N s with in company ranged from 30 to 34. The overall Ns ranged from 94 to
102.

Hypothesis 3 predicted that applicant quality would moderate the relationship
between the type of information provided and intentions to apply such that the type of
information provided would have less of a relationship to intentions to apply for qualiﬁed
applicants. As discussed in the methods section, applicant quality was a composite
variable consisting of standardized scores for GPA, ACT /SAT, and the sum of the 9 self-
report competency ratings collected at least 24 hours prior to the experiment; missing
data was addressed using mean replacement. To test this hypothesis a moderated
regression analysis was conducted. In step one, intentions to apply was regressed on type
of information; in step two intentions to apply was regressed on type of information and
applicant quality; the third step involved testing the interaction term. The results
indicated that there were no signiﬁcant main effects or interactions for the information
type/intentions to apply relationship (see Table 8). These non-signiﬁcant results were
obtained with and without mean replacement in the quality composite. In addition to the

quality composite, GPA, SAT/ACT, the competency composite, and each of the nine

59

competencies were tested individually as potential moderators. Similar to the quality
composite, no main effects or interactions were found. Thus, Hypothesis 3 was not
supported. This is ﬁnding is consistent with the failure of the ﬁt manipulation; that is,

there was no relationship to moderate.

 

 

Table 8
Moderated Reggession: Intentions to Apply Regressed on Fit and Quality
Step: Variable(s) R2 AR2 E p

1: Type of Fit Information .000 .000 .002 .978

2: Type of Fit Information .003 .003 -.002 .956
Quality V .055 .976

3: Type of Fit Information .004 .004 .011 .836
Quality .163 .883
Type of Fit * Quality .116 .469

 

Note. [3 is the standardized Beta. N = 198

Hypothesis 4 stated that intentions to apply would be positively related to
assessments of ﬁt. To test this hypothesis a correlation was calculated between intentions
to apply and ﬁt. Across all the data there was a signiﬁcant moderate correlation of r = .44
p < .01; thus, Hypothesis 4 was supported. Additionally, the correlations within company
were calculated r = .40 for Kodak p < .01, r = .48 for Proctor and Gamble p < .01 and r =
.50 for Phillip Morris p < .01. A Fisher’s Z transformation for comparing correlations
from independent samples indicates that these correlations are not signiﬁcantly different
from each other.

Hypothesis 5 suggested that post-image and the perceived ﬁt assessment would be
moderately correlated. To test this hypothesis a correlation was calculated between post-
image and ﬁt. Across all the data there was a signiﬁcant correlation of r = .54 p < .01,

which according to Cohen (1977) would be considered a high correlation; thus the

60

relationship between ﬁt and post-image was somewhat stronger than expected. The
correlations within company were also relatively high r = .61 p < .01 for Kodak, r = .69 p
< .01 for Proctor and Gamble and r = .37 p < .01 for Phillip Morris. A Fisher’s Z
transformation for comparing correlations from independent samples indicates that the
correlations between Kodak and Philip Mom's (z = +2.30 p < .05) and Proctor and
Gamble and Philip Morris (2 = +3.30 p < .05) are signiﬁcantly different from each other.
This pattern may suggest that the lower the organization’s image the harder it is for
potential applicants to admit or recognize ﬁt. This would be consistent with the cognitive
dissonance and self-preservation views previously discussed; however, it is also possible
that potential applicants simply feel they will not ﬁt in a low image organization.
Hypothesis 6 predicted that the type of ﬁt information provided would moderate
the pre/post image relationship such that the greatest changes in image perceptions would
be found when applicants are supplied with supplementary ﬁt information. To test this
hypothesis a moderated regression analysis was conducted. In step one, post-image was
regressed on pre-image; in step two post-image was regressed on pre-image and type of
information; the third step involved testing the interaction term. The results indicated
that there were no signiﬁcant main effects or interactions for the type of
information/image relationship (see Table 9); however, pre-image was obviously a
signiﬁcant predictor of post-image (see Table 9). Thus, Hypothesis 6 was not supported.
Once again, this is not surprising considering the manipulation check indicates that the ﬁt

manipulation failed.

61

Table 9

Moderated Regression: Post-Image Reggessed on Pre-Image and Typp of Information

 

 

Step: Variable(s) R2 ARZ p 13
1: Pre-Image .506 .506 .71 1 .000
2: Pre-Image .509 .003 .716 .000
Type of Fit Information -.059 .236
3: Pre-Image .513 .004 .916 .000
Type of Fit Information . .393 .280
Pre-Irnage * Type of Fit -.513 .210

 

Npte= B is the standardized Beta. N: 203

Hypothesis 7 predicted that familiarity would moderate the pre/post image
relationship such that the less familiar the applicant is with the organization the more
image would change from pre to post. To test this hypothesis a moderated regression
analysis was conducted. In step one, post-image was regressed on pre-image; in step two
post-image was regressed on pre-image and familiarity; the third step involved testing the
interaction term. The results indicated that there were signiﬁcant main effects for both
pre-image and familiarity (see Table 10). There was also a signiﬁcant interaction
between pre-image and familiarity in the predicted direction (see Table 10 & Figure 2).
That is, the less familiar the applicant was with the organization the more image
improved from pre to post. This effect appears to be particularly strong for organizations
with a more negative pre-image. Thus, Hypothesis 7 was supported.
Model Overview

The proposed model (see Figure 1) indicates that providing potential applicants
with additional information from recruiting materials would impact the pre-existing
image of the organization (see Figure 1 link A). Speciﬁcally, it was expected that the

positive recruiting information would lead to improved post-image perceptions. To

62

determine the impact the recruiting materials had on image perceptions, a dependent t-

test was conducted between pre and post-image perceptions. The results indicate a

 

 

Table 10
Moderated Regression: Post-Image Reggessed on Pre-Image and Familiarity
Step: Variable(s) R2 AR2 8 E

1: Pre-Image .506 .506 .71 1 .000

2: Pre-Image . .543 .037 .780 .000
Familiarity -.205 .000

3: Pre-Image .554 .011 .265 .001
Familiarity -1.09 .277
Pre-Irnage* Familiarity 1.17 .032

 

Note. B is the standardized Beta. N: 204

 

 

 

 

g. Familiarity

.5 High Familiarity
B _

a Low Familiarity

 

20 40 do so 100

Pre-Image

Figpre 2. Relationship between pre and post image as a function of familiarity. Note that
for graphing purposes, familiarity was dichotornized using a mean split.

63

signiﬁcant change in image perceptions such that for each company, image perceptions

improved signiﬁcantly after reviewing the recruiting materials (see Table 11).

Table 1 1

Epired Samples t-tests Comparing PrelPost Image Means

 

 

 

Pre-Image. Post_Image

Company Mean SD Mean SD Mean t- p
Difference value

Overall 59.82 8.38 68.51 10.05 -8.69 - 17.20 .000
Kodak 65.49 7.71 72.34 9.99 -6.85 -9.45 .000
Proctor & 58.94 5.67 67.87 8.34 -8.93 -8.88 .000
Gamble
Philip 55.09 8.05 65.37 10.55 -10.28 -12.35 .000
Morris

 

Note. The overall N = 202. The Ns by company ranged from 67-68.

The model also indicates that post-image mediates the pre-image/application
intentions relationship. To test this, ﬁrst a simple partial correlation was computed
between pre-image and application intentions controlling for post image. The results
indicate that controlling for post-image eliminates the pre-image/application intentions
relationship, that is the correlation drops from r = .38, p < .05 to r = .10, p = .15.
Additionally, Barron and Kenny’s (1986) 3-regression equation method for testing
mediation was employed. Speciﬁcally, post-image was regressed on pre-image (R2 =
.51; B = .85, p <.01), application intentions was regressed on pre-image (R2 = .15; B =
.24, p < .05) and application intentions was regressed on pre-image and post-image (R2 =
.21; B = .08 , p = .15 and B = .18 , p < .01 respectively). According to Barron and Kenny

(1986), mediation is demonstrated if the independent variable (IV) affects the mediator,

the IV affects the DV, and the mediator affects the DV and the IV has less affect in
equation 2 than equation 3. As is evident from the numbers presented above, this pattern
holds for the proposed relationship. That is, post-image mediates the pre—
image/application intentions relationship.

The remaining paths in Figure 1 were discussed in the hypothesis testing section.
Speciﬁcally, links f, d, and h were not signiﬁcant due to the failure of the information
type manipulation. Familiarity did moderate the pre/post-image relationship (see Link e),
ﬁt assessments and post-image were correlated (see Link g) and ﬁt assessments were
related to intentions to apply (see Link c).

Chapter 4
DISCUSSION

The current study was designed to investigate the possibility of manipulating the
type of information provided in a recruiting context to inﬂuence applicant behavior and
perceptions. More speciﬁcally, can the type of information provided (i.e., supplementary
or complementary ﬁt) inﬂuence applicant intentions to apply, organizational image, and
applicant quality and quantity? The results of this study provide general support for the
image and application intentions related hypotheses: (a) post-image is positively related
to intentions to apply, (b) post-image is related to ﬁt perceptions, (c) ﬁt perceptions are
positively related to intentions apply. However, the hypotheses related to type of
information provided were not supported. Finally, exploratory analyses of company
differences suggest that image is malleable. These ﬁndings and their implications are

discussed in the following sections.

65

Role of Image

Past research indicates that image is related to applicant attraction and intentions
to pursue further contact with a ﬁrm (Belt & Paolillo, 1982; Gatewood etal., 1993;
Highhouse et al., 1999; Tom, 1971; Turban & Greening, 1996). Speciﬁcally, the
literature indicates that applicants prefer organizations with a positive image over
organizations with a negative image (Belt & Paolillo, 1982; Gatewood et al., 1993;
Highhouse et al., 1999; Turban & Greening, 1996). The current study sought to extend
past research to include the full range of organizational image (i.e., positive, neutral, and
negative image). Consistent with previous research it was found that intentions to apply
increase as image increases. One caveat, however, remains; that is, does this study truly
represent the full range of image? Although this study has included a wider range of
image than previous work, it remains unclear if Philip Morris, the low image organization
in this current study, is really representative of negative image organizations.
Speciﬁcally, can the image perception improvements found in the current study be
expected in practice for an organization that is perceived very negatively? Another
interesting question along these lines, is with today’s technology and the global economy
allowing organizations to cast a broader recruiting net, are we likely to encounter
applicant pools that know enough about an organization to hold a very negative
perception of the organization? Using the current study as a guide, one has to consider
the possibility that the answer is no. Although the pilot study sample was small, 15
Fortune 500 organizations were considered and none of these organizations were

consistently perceived very negatively, even though there were respondents at both ends

66

of the image continuum. Future research should further explore these issues using larger
and more diverse samples.

The current study also extends our understanding of image by demonstrating that
organizational image can be changed and improved by providing applicants with positive
recruiting information. This ﬁnding is consistent with signaling theory (Bretz & Judge,
1994; Rynes, 1991; Spence, 1973) in that the recruiting materials acted as signals or
indicators that the organization was a good place to work; this information was integrated
into participants’ pre-existing image perceptions thus leading to improved image
perceptions. The change in image perceptions may also be explained by some of the
persuasion literature. Speciﬁcally, this literature indicates that similar information
obtained from multiple sources (Harkins & Petty, 1981) and information that matches
existing attitudes (Fabrigar, & Petty, 1999; Petty & Wegener, 1998) tends to be more
persuasive. Thus, if the information provided in the recruiting materials is consistent
with previous perceptions and information it is likely to enhance image perceptions.
Persuasion theories however, do not offer much insight regarding the image
improvements found for low image organizations.

From a research perspective, future studies should consider what types of
information have the largest impact on image perceptions and ultimately image
malleability (e.g., ﬁt information, company policies, employee testimonials, newspaper
articles and other ‘objective’ sources). This type of research may give us further insight
into image formation and techniques for changing attitudes and perceptions. In terms of
practice, organizations looking to improve their chances of attracting applicants may

want to provide potential applicants with easy access to recruiting style information in an

67

effort to improve image perceptions. Based on the current study, this may be especially
beneﬁcial for organizations that have a relatively low image and are not especially well
known; that is these organizations may be able to make the greater improvements in
image perceptions than highly familiar organizations with image problems.

Along the same lines, additional efforts should be made to understand the
malleability of image over time. That is, how does an organization’s image change or
evolve over time, and what can organizations do to repair a damaged image? This type
of research could be especially interesting if it was focused on familiar organizations that
have recently or at one time took a strong image hit due to very public negative incidents
such as the Exxon Valdez oil spill, Texaco’s racial discrimination problems, or
Microsoft’s anti-trust cases. Can these organizations take steps to more quickly recover
their positive pre-incident image or is time alone the only way to repair damage to a
familiar organization’s image? Based on the results of the current study, one might
predict that the more familiar applicants are with an organization, the more difﬁcult it
will be to change their perceptions. This prediction and the ﬁndings of the current study
are consistent with the extant literature and theory. That is, past studies suggest that
familiarity with an organization may inﬂuence image development, applicant attraction,
and recruiting efforts (Barber, 1998; Behling, Labovtiz & Gainer, 1968; Gatewood et al.,
1993). Speciﬁcally, applicants’ pre-existing image perceptions and degree of familiarity
with an organization may affect how much subsequent recruiting efforts inﬂuence
opinions of an organization (Gatewood et al., 1993). Thus, as found in the current study,
if a potential applicant is very familiar with and has a well developed image for company

X, the information presented in the recruiting materials may have less impact than it

68

would for someone less familiar with the organization. Furthermore, the human tendency
to pay more attention to familiar items than unfamiliar ones (Christie & Klien, 1995) is
likely to increase potential applicants’ awareness and memory for negative information
related to highly familiar organizations. Thus, making image repair a difﬁcult process for
familiar organizations.

Finally, the current study investigated the relationship between ﬁt and image
perceptions. The existing literature has failed to address this relationship even though
researchers frequently conduct studies in both areas and cite the same empirical pieces.
The current study found a strong but far from perfect correlation between the two
constructs across all the data, and the pattern of within company correlations suggests
that the relationship between ﬁt and image declines as image declines. Additionally, an
exploratory factor analysis suggests that ﬁt and image are two distinct factors. This
supports the expectation that although ﬁt and image will affect each other, they remain
separate constructs. As previously discussed, these ﬁndings are consistent with social
identity theory which suggests that our self—concepts are in-part shaped by the
organizations we identify with (Dutton, Dukerich & Harquail, 1994; Tajfel & Turner,
1985). As a result, if we determine that we are a good ﬁt with an organization, it
becomes more difﬁcult for us to view that organization in a negative light. However, this
is an individual cognitive process, thus, making it difﬁcult to predict the direction of
adjustments for ﬁt and image perceptions. Future research should attempt to further
disentangle these constructs to determine if the relationship is truly recursive or if there is
a causal direction to this relationship. Ideally, this research would be longitudinal in

nature and would consider both cognitive and affective theories.

69

Considering the role of image beyond the current study, several issues still need to
be addressed. Perhaps one of the most important issues is understanding the process for
completely unfamiliar or essentially imageless organizations. Research in this area is
critical for helping us better understand how organizational images are formed, what
types of information are most inﬂuential in image development, and helping us to further
disentangle the image/familiarity relationship. This type of research could be especially
beneﬁcial for small .com start-up companies and other lesser-known technology
companies, which are competing with much larger and more familiar technology ﬁrms
for a limited number of highly skilled employees.

Finally, the current study took the ﬁrst step in exploring the malleability of image;
however, a number of interesting questions remain. Speciﬁcally, are there gender,
personality, or other individual differences that may impact how much or how quickly
image perceptions can be changed? The correlation between gender and post-image
found in the current study suggests that female image perceptions may be more malleable
than male perceptions. Should this relationship be replicated in future research, it could
have far reaching implications for typically male dominated industries and organizations
(e. g., law enforcement, engineering) which are looking to diversify their workforce.
Additionally, one might expect personality variables such as openness to experience to
inﬂuence the image malleability and development process. That is, those who are
typically open to new ideas and experiences may be more willing to change their image
perceptions. Looking beyond individual differences, what are the other parameters that
limit or enhance an organization’s ability to change its image? From a practical

perspective this type of information could be very valuable for organizations which are

70

trying to attract or change perceptions of particular types or groups of applicants. While
from a research perspective, it can provide us with a greater understanding of applicant
behavior and decision processes.
Type of Information

The current study attempted to manipulate the type of information (i.e.,
supplementary vs. complementary ﬁt) subjects received with the expectation that the type
of information provided would differentially affect image perceptions and application
intentions. As previously discussed, the manipulation failed and hence all the related
hypotheses were not supported. One potential reason for this failure is applicants’
tendency to draw inferences from the information available to them. Based on previous
research it was expected that applicants would use other experiences or pieces of
information (e. g., beneﬁts, compensation, company policies) as indicators or signals of
company goals and values (Rynes et al., 1991) or supplementary ﬁt if they were not
explicitly provided with this information. The results of the current study however,
suggest that applicants also draw inferences from the available materials regarding skills
and characteristics or complementary ﬁt. Although this is an interesting research ﬁnding,
it does not necessarily change the practical implications previously discussed. That is,
assuming the disconnect outlined in the literature regarding the type of ﬁt organizations
emphasize (i.e., complementary ﬁt) vs. the type of ﬁt information applicants are seeking
(i.e., supplementary ﬁt) is accurate, organizations still need to clearly present
supplementary ﬁt information to ensure they are sending the desired message as opposed
to allowing potential applicants to extrapolate and read between the lines. From a

research perspective however, additional research is needed explore what types of

71

inferences are made by applicants. Understanding the inference process is likely to
become increasingly important as the intemet is quickly becoming a primary
informational source for many potential job applicants. This medium has the potential to
reduce the interactive component of recruiting process, thus, leaving more applicants to
infer ﬁt from written statements as opposed to early recruitment and selection
interactions.

Another reason the manipulation may have failed is that it was too weak for a
between subjects design. That is, if respondents had reviewed both versions of the
materials maybe the focus on the company’s goals and values (i.e., supplementary ﬁt)
versus the employees’ skills and characteristics (i.e., complementary ﬁt) would have been
more evident and as a result yielded the expected differences. Essentially in the absence
of a comparison, the subjects’ natural tendency to extrapolate the unknown from the
available information was too strong for the manipulation to overcome. Future research
should consider investigating the proposed relationships using a within subjects design.

On a broader level, we must consider the possibility that although supplementary
and complementary ﬁt can be deﬁned as conceptually distinct by researchers, this
distinction may not apply to applicants. That is, applicants may consider ﬁt a unitary
concept and as a result, ﬁt is either good or bad regardless of whether the ﬁt perception is
based on goals/values or skills/abilities. This possibility would be consistent with.the
factor analysis results for the current study’s ﬁt measure, whichhdemonstrated a single ﬁt
factor despite efforts to include questions with a supplementary vs. complementary focus.
From a research perspective, however, additional efforts should be made to further clarify

the conceptual distinction between ﬁt types. Since Kristoff’s (1996) seminal article on

72

ﬁt, the focus has primarily been on supplementary as opposed to complementary ﬁt. As a
result, we still know very little about the concept of complementary ﬁt, which could
become an increasingly important construct should the competency approach to selection
and training continue.

Although I believe additional research should be done to increase our
understanding of these two broad ﬁt classiﬁcations, one might also need to consider
revisiting the deﬁnitions and the classiﬁcations in an effort to further reﬁne and clarify
the distinctions between them. As previously discussed, Kristoff (1996) attempted to
organize multiple ﬁt perspectives into the two broad categories of supplementary and
complementary ﬁt to reduce the confusion associated with the concept of ﬁt (Rynes &
Gerhart, 1990). These broader deﬁnitions provide us with an organizing framework for
both the effects of PO ﬁt and the existing empirical literature; however, this is not to say
that there is no overlap between supplementary and complementary ﬁt. Furthermore, it is
possible that the complementary and supplementary labels drawn from Muchinsky and
Monahan ‘s (1987) work have been extended too far by Kristof’ s framework and more
research appropriate titles and deﬁnitions need to be established.

Finally, the results of the results of the current study do not allow one to
adequately address issues regarding applicant quality, information type, and increasing
self-selection. Future research should further explore these issues with an emphasis on
understanding what drives desirable self-selection or withdrawal from the application
process. Based on the current literature it is not unreasonable to believe that
supplementary ﬁt information could play a critical role in the self-selection process.

Speciﬁcally, organizations may not only need to provide this type of information but

73

make an effort to present this information in a very clear and accurate form. That is,
organizations may ﬁnd it beneﬁcial to be very honest as opposed to simply positive if
they really expect the supplementary ﬁt information they provide to differentiate the
organization and its applicant pool.

Limitations

Although this study provides interesting insights into the role and malleability of
organizational image, there are a number of limitations. One potential limitation is the
use of college students as opposed to real job applicants. (It is important to note however,
that the goal of this study was to consider the role of image early in the recruiting
process; thus, actual applicants may not be the best sample as they have already made the
choice to apply. Furthermore, college students will comprise a good portion of future
applicants to these organizations so it is important for us to understand what their image
perceptions are and whether they can be altered.

A related limitation involves the use of application intentions as opposed to actual
behavior. Critics of the recruiting literature argue that intentions are not equivalent to
actual behavior (Rynes, 1991). Although this may be a weakness of the current study,
efforts were made to tap actual behavior by including questions regarding the subjects’
interest in meeting with campus recruiters and receiving a complete recruiting packet. It
is expected that the inclusion of these behaviorally oriented questions would make the
intentions measure more reﬂective of actual behaviors.

Similarly, some may argue that the situation was too artiﬁcial and as a result
participants did not take the study seriously. This is does not appear especially likely

however based on the responses to the distracter questions included in the study. The

74

open-ended questions in particular, suggest that participants believed they were providing
feedback to the organization and took the experiment seriously. Additionally, several
participants in every experimental session inquired about when the recruiters for
company X would be coming to campus, and if company X was paying the school to do
this research or if the university did it for free. These types of responses and inquiries
strongly suggest that the cover story for the experiment was believable and as a result
participants were more likely to take the study seriously.

From a methodology perspective, failing to pilot the manipulation for the type of
information eliminated this study’s ability to address the bottom half of the model. This
is a limitation that future studies can avoid. Speciﬁcally, future research should provide
participants with a list including goals, values, norms, and competencies and ask them to
classify each item into one of the above categories. This will establish if these concepts
are distinguishable by lay persons. This study should be done both as a simple paper and
pencil study and with a verbal protocol analysis to help us understand the thoughts
guiding this classiﬁcation. It would also be interesting to conduct a verbal protocol
analysis using materials similar to those used in the current study to determine how
inferences about competencies were drawn from information regarding values and vice-
versa. The key to addressing the limitation encountered in this study is to understand the
thought processes that led to the manipulation failure.

Finally, it is possible that many of the relationships demonstrated by the study are
the result of general positive affect and/or method bias. Although this is possible, the
results do indicate differences in organizational image which are consistent with the pilot

test and many of the relationships tested do vary by organizational image. Additionally,

75

many of the results were as predicted. This suggests that although general affect and
method bias may have played a role, they do not account for all of the results
demonstrated by the study.
Conclusions

The present study has attempted to critique and extend the existing knowledge-
base with regard to organizational image and has taken the ﬁrst step towards exploring
the relationship between organizational image and PO ﬁt. As the competition for
employees continues to increase, a better understanding of organizational image, PO ﬁt,
and the impact of other types of information on the recruiting process will play a critical
role for both researchers and practitioners alike. Future research needs to take a closer
look at these issues and attempt to explicate these relationships beyond the initial steps

taken in the current study.

76

APPENDICES

77

APPENDIX A
Informed Consent
AN INVESTIGATION OF COMPANY PERCEPTIONS
Cover Sheet and written consent form for the pilot study

SUBJECT’S NAME:
DATE:

CLASS YOU WANT CREDIT FOR (OR NAME OF PROFESSOR):

 

 

 

INVESTIGATORS’ NAMES: Christine Scheu, Ann Marie Ryan

DESCRIPTION OF PROCEDURES: The purpose of this study is to investigate student
perceptions of various companies. You will be asked to provide your
opinions/perceptions of several Fortune 500 companies. You will also be asked to
provide some demographic information.

ESTIMATED TIME REQUIRED: 30 minutes
RISKS: There are no risks associated with this procedure.
BENEFITS: Where appropriate, students will receive course points/credit.

AN ONYMITY: To maintain anonymity, use only your experiment ID number (your ﬁrst
initial and the last 5 digits of your social security number) on all surveys and op-scan
sheets. DO NOT write your name or student ID number on any forms other than this
consent form. You will not be identiﬁed in any way by your responses.

If you have any additional questions or concerns please feel free to contact us at 355-
2171.

CONSENT:

You have been fully informed of the above described procedure and its possible risks and
beneﬁts. You understand that you will be able to review your responses at a later date
and be fully debriefed on them if you desire. You give permission for participation in
this study. You know that the investigator and his/her associates will be available to
answer any questions you may have. If at any time, you feel your questions has not been
adequately answered, you may speak with the Head of the Department (Gordon Wood,
355-9563), or the Committee on Research Involving Human Subjects (355-2180).

You understand that you may decline to answer any item and are free to withdraw this
consent and discontinue participation in this project at any time without penalty. You are
also aware that within one year of your participation a copy of this Informed Consent
form will be provided upon request.

 

Signature of participant

78

APPENDIX B

Measures

Familiarity (This measure is completed in the pilot and in the experiment before
reviewing the recruiting materials)

PWHQP‘PP’NT‘

I recall seeing advertisements for this organization

I know what types of products and services are produced by this organization
I have purchased products or services from this organization

I know people who have worked for this organization

I have worked for this organization

I have studied this organization in class or for a project

I have read articles about this organization

I have seen brochures or written materials produced by this organization

I have been to this organization’s web-site

10. I am familiar with this organization

Intentions to Apply (This measure is completed after reviewing the recruiting

materials)

1. I would consider applying to this company.

2. If offered a job from this company I would accept.

3. I have no interest in applying to this company. (R)

4. I would recommend this company to my friends.

5. I would like to receive a complete recruiting packet from Kodak.

If you said you would like to receive a complete recruiting packet from Kodak
please provide a mailing address:

I would be interested in meeting with a representative of Kodak should one visit MSU
to recruit applicants.

If you said you would be interested in meeting with a representative of Kodak
please provide your email address so a representative can contact you.

79

PrelPost Organizational Image (This measure is completed in the pilot and in the
experiment before and after reviewing the recruiting materials)

X cares about its customers.

X cares about its employees.

X treats its customers well.

X treats its employees well.

X is a reputable organization.

X is a prestigious organization.

X is a challenging place to work.

X has a negative reputation in the community. (R)

senses-9.0230:—

X is a progressive organization.

10. X is a competitive organization in its industry.
11. X provides quality goods and services.

12. X is a good organization to work for.

13. X is a responsible organization.

14. X has good commercials or advertisements.
15. I have heard good things about X.

16. I would be embarrassed to work at X. (R)

17. X cares about the community.

18. X is only interested in proﬁts. (R)

Fit Assessment (This measure is completed after reviewing the recruiting materials)
1. The values and ‘personality’ of this organization reﬂect my own values and
‘personality’.

My values match those of the current employees in the organization.

My skills and abilities reﬂect the skills and abilities the organization is looking for.
I would be a good match or ﬁt for this organization.

I have the qualities this organization is seeking.

QMPPP

I think people who work at this organization are similar to me.

80

9 Relevant Competencies (This measure is completed prior to attending the experiment
using 5—point likert type scale, which ranges from “not at all skilled” to “very skilled. ")

1.

Team Building — ability to get individuals to work together to achieve a common
goal.

2. Decisiveness — ability to make tough decisions without hesitation.

3. Customer Focus - capable of maintaining and improving customer satisfaction.

Personal Responsibility - capable of accepting responsibility for your own actions,
decisions.

Creative Thinking -- capable of thinking creatively and to and encouraging others to
do the same.

6. Resilience - capable of maintaining a positive attitude in response to failure.

7. Oral & Written Communication - ability to express yourself clearly, succinctly,

pleasantly and in a straightforward manner.

Self-Development - Motivated to seek out and engage in self-improvement
opportunities.

Technical Proficiency — typically know or can learn what is necessary to get the job
done.

Full List of Competencies Completed by Participants (This measure is completed
prior to attending the experiment using 5 -point likert type scale, which ranges from “not
at all skilled” to “very skilled. ”)

l.
2.

Decision Making — uses good judgement in resolving problems

Personal Responsibility — capable of accepting responsibility for your own actions,
decisions.

Rule Orientation —understands the importance of organizational rules and polices,
and willingly follows them

Resilience — capable of maintaining a positive attitude in response to failure.

5. Orderliness - capable of maintaining a high degree of organization in your physical

work environment

6. Seeking input - actively pursues other’s suggestions and contributions

Short-term Planning — capable of preparing the steps needed to complete tasks
before action is taken.

Technical Proﬁciency - typically know or can learn what is necessary to get the job
done.

Problem Awareness — can identify situations that may require action to promote
success or prevent failure

10. Listening Skills - actively attends to what others are saying

81

11. Oral & Written Communication - ability to express yourself clearly, succinctly,
pleasantly and in a straightforward manner.

12. Urgency - ability to respond quickly to pressing demands

l3. Self-Development — Motivated to seek out and engage in self-improvement
opportunities.

14. Assertiveness - capable of stating views conﬁdently, directly, and forcefully
15. Decisiveness — ability to make tough decisions without hesitation.
16. Goal Setting — can identify work objectives and the methods for achieving them

17. Public Presentation - capable of effectively and comfortably presenting material to
groups of people.

18. Creative Thinking -- capable of thinking creatively and to and encouraging others to
do the same.

19. Initiative — willing to take the preliminary steps to do what needs to be done without
direction

20. Adaptability - capable of adapting to new situations and immediate work demands

21. Team Building - ability to get individuals to work together to achieve a common
goal.

22. Stress Management - ability to effectively deal with feelings of job-related stresses
and their causes

23. Monitoring - actively compares current work progress to predetermined standards,
objectives, and deadlines

24. Customer Focus — capable of maintaining and improving customer satisfaction.

25. Task Focus -- capable of staying on task despite complexity and/or ambiguity

Demographics (This measure is completed in the pilot and in the experiment before
reviewing the recruiting materials)

1. Year in school.

a Freshman
b. Sophomore
c. Junior
(1. Senior
2. Age.
a. 1820
b. 21-22
c. 23-24
(1. 25-30
e. over 30

82

3. Gender.

a. Male
b. Female

Race.

African American

Asian American
Hispanic American
Middle Eastern American
Native American

White American

Other

98999-9?!” :p‘

5. Cumulative GPA

a. Less than 1.0

b. 1.0 — 1.5

c. 1.6 —2.0

d. 2.1 — 2.5

e. 2.6 - 3.0

f. 3.1 — 3.5

g. 3.5 - 4.0

h. If ﬁrst semester freshman provided high school GPA

6. Total SAT or ACT Score

 

Manipulation Check (This measure is completed after reviewing the recruiting
materials)

1. The materials included information regarding the type of characteristics, skills, and
abilities the company is looking for in new employees.
a. True
b. False

2. The materials included information regarding the company’s goals and values.
a. True
b. False

83

3. I did not receive any information about company goals or values.
a. True
b. False

4. I did M receive any information about the types of skills or characteristics new
employees should have.

a. True
b. False

Note: Pre-image questions will serve as the manipulation check for image groupings.
Distracter Questions (This measure is completed after reviewing the recruiting

materials)

1. I like the message conveyed by this draft.

2. I think the information provided in this draft would be perceived well by other
applicants.

. I think this information should be included in the company’s recruiting materials.

3
4. I think these materials are well written.
5. I do not believe the information provided is relevant to applicants.
6

. Please provide any additional comments you have about the materials you just
reviewed.

84

APPENDIX C
Debrieﬁng Form for the Pilot

Debrief’mg Statement

Recruiting job applicants and ultimately qualiﬁed employees is a critical aspect of any
organization’s stafﬁng process. If an organization is to succeed in today’s competitive
global market it must be able to attract and hire qualiﬁed employees. In an effort to
accomplish this, organizations spend thousands of dollars each year to acquire the “right”
employees (Martin & Raju, 1992). With so much money invested in attracting and hiring
the most qualiﬁed employees it is critical that we understand the factors that inﬂuence
why job seekers choose one organization over another. Research indicates that one factor
job seekers consider when deciding where to apply is an organization’s reputation. We
are preparing a study that will further investigate issues regarding company reputations
and how a company’s reputation affects their ability to attract employees. However,
before we begin the actual experiment we need to know how students feel about a variety
of organizations. The surveys you completed today will provide us with that information
and allow us to continue our research. Thank you for participating. If you have any
additional questions or concerns please feel free to contact Christine Scheu or Ann Marie

Ryan at 355-2171.

85

APPENDIX D
Informed Consent

AN INVESTIGATION OF STUDENTS’ PERCEPTIONS OF RECRUITING
MATERIALS

Cover Sheet and written consent form for the exppriment

 

SUBJECT’S NAME:
DATE:

CLASS YOU WANT CREDIT FOR (OR NAME OF PROFESSOR):

 

 

 

INVESTIGATORS’ NAMES: Christine Scheu, Ann Marie Ryan

DESCRIPTION OF PROCEDURES: The purpose of this study is to evaluate recruiting
materials. You will be asked to review some recruiting materials and provide your
opinions. You will also be asked to provide some demographic information.

ESTIMATED TIME REQUIRED: 30 minutes
RISKS: There are no risks associated with this procedure.
BENEFITS: Where appropriate, students will receive course points/credit.

AN ONYMITY: To maintain anonymity, use only your experiment ID number (your ﬁrst
initial and the last 5 digits of your social security number) on all surveys and op-scan
sheets. DO NOT write your name or student ID number on any forms other than this
consent form. You will not be identiﬁed in any way by your responses.

If you have any additional questions or concerns please feel free to contact us at 355-
2171.

CONSENT:

You have been fully informed of the above described procedure and its possible risks and
beneﬁts. You understand that you will be able to review your responses at a later date
and be fully debriefed on them if you desire. You give permission for participation in
this study. You know that the investigator and his/her associates will be available to
answer any questions you may have. If at any time, you feel your questions has not been
adequately answered, you may speak with the Head of the Department (Gordon Wood,
355-9563), or the Committee on Research Involving Human Subjects (355-2180).

You understand that you may decline to answer any item and are free to withdraw this
consent and discontinue participation in this project at any time without penalty. You are
also aware that within one year of your participation a copy of this Informed Consent
form will be provided upon request.

 

Signature of participant

86

APPENDD( E

Pre-screen Materials

This is the prescreen for the perceptions of recruiting materials experiment. It will only
take you a couple minutes and you will receive one credit for completing this and one for
the actual experiment for a total of two credits. You must complete both the pre-screen
and the experiment to receive credit. Below is a list of skills/abilities and their
deﬁnitions. Read each one and then rate how good you are at that skill/ability.
Remember we all have strengths and weaknesses so you should not be rating yourself as
very skilled or unskilled forevery question.

Competencies (This measure is completed prior to attending the experiment using 5 -
point likert type scale, which ranges from “not at all skilled” to “very skilled. ”)

1. Decision Making - uses good judgement in resolving problems

Personal Responsibility — capable of accepting responsibility for your own
actions, decisions.

Rule Orientation —understands the importance of organizational rules and
polices, and willingly follows them

4. Resilience - capable of maintaining a positive attitude in response to failure.

Orderliness — capable of maintaining a high degree of organization in your
physical work environment

6. Seeking input - actively pursues other’s suggestions and contributions

7. Short-term Planning - capable of preparing the steps needed to complete

10.
11.

12.
13.

14.
15.

tasks before action is taken.

Technical Proficiency - typically know or can learn what is necessary to get
the job done.

Problem Awareness - can identify situations that may require action to
promote success or prevent failure

Listening Skills - actively attends to what others are saying

Oral & Written Communication - ability to express yourself clearly,
succinctly, pleasantly and in a straightforward manner.

Urgency — ability to respond quickly to pressing demands

Self-Development - Motivated to seek out and engage in self-improvement
opportunities.

Assertiveness - capable of stating views conﬁdently, directly, and forcefully

Decisiveness — ability to make tough decisions without hesitation.

87

16. Goal Setting — can identify work objectives and the methods for achieving
them

17. Public Presentation - capable of effectively and comfortably presenting
material to groups of people.

18. Creative Thinking -- capable of thinking creatively and to and encouraging
others to do the same.

19. Initiative — willing to take the preliminary steps to do what needs to be done
without direction

20. Adaptability - capable of adapting to new situations and immediate work
demands

21. Team Building - ability to get individuals to work together to achieve a
common goal.

22. Stress Management — ability to effectively deal with feelings of job-related
stresses and their causes

23. Monitoring — actively compares current work progress to predetermined
standards, objectives, and deadlines

24. Customer Focus — capable of maintaining and improving customer
satisfaction.

25. Task Focus -- capable of staying on task despite complexity and/or ambiguity

88

Cover Story

(Provided after demographic information and pre-image measures were completed)

Company X is updating sections of its employee recruiting materials and would
like to see how students respond to the current draft. As you review the small recruiting
section Company X has provided, please remember that Company X is only concerned
with the content of the materials not the layout or the design. As you review the
materials, pretend you are looking for a job and assume that 1) Company X has a position
you would be interested in, 2) the position pays well relative to similar positions in other
companies, and 3) there are positions available in good locations. After reviewing the

material provided, please answer the remaining questions.

89

Experimental Materials Supplementary Fit

Who Are We & Where Are We Going?

X is a global Fortune 500 organization that provides products and services in over 100
countries. Our company has experienced tremendous growth and success during the past
decade and we are continually expanding our market and range of products and services.
As the new millennium approaches, we will continue to strive to be leaders in our
industry worldwide. But we realize that the only way to ensure our continued success is
to maintain a top-notch workforce. This goal clearly depends on our ability to ﬁnd
quality employees who share our organization’s core values.

Our Core Values:

Here at X our entire corporate philosophy is guided by our 9 core values:

1.

Concern for others — We consider it our responsibility to be compassionate,
supportive, and concerned about the welfare of our employees and their
families.

Achievement — We believe in continually improving our skills and abilities,
seizing opportunities, and achieving our objectives.

Honesty -- We believe in maintaining the highest ethical standards, taking
responsibility for our mistakes and being open and honest with each other, our
customers, and the community at large.

Fairness -- We strongly believe in being fair and impartial in all polices and
interactions, considering different points of view, and judging others on the
basis of their abilities.

Competitiveness -- We strive to be competitive in our industry and believe
that competition is healthy, leads to continual improvement, and higher
quality goods and services.

Quality — This is the cornerstone of our success. We strive to provide the
highest quality products and services available. And we are committed to
continually improving and surpassing the industry’s quality standards.

Innovation - We have never been shy about experimenting with new ideas
and technologies and we strongly encourage our employees to look for new
and creative way to solve to both organization and industry problems.

High Performance Expectations — We know our customers and our
employees have high expectations for this organization and we continually
strive to meet and exceed these expectations at all levels of the organization
and provide the resources and support necessary for optimal performance.

Social Responsibility - We are obligated to consider the impact of our
choices and actions on the community at large and to use that information to
act in a responsible manner.

90

Experimental Materials Complementary Fit

Who Are We & Where Are We Going?

X is a global Fortune 500 organization that provides products and services in over 100
countries. Our company has experienced tremendous growth and success during the past
decade and we are continually expanding our market and range of products and services.
As the new millennium approaches, we will continue to strive to be leaders in our
industry worldwide. But we realize that the only way to ensure our continued success is
to maintain a top-notch workforce. This goal clearly depends on our ability to ﬁnd
quality employees who possess the skills and characteristics central to success in our
organization. '

The Ideal Employee
Here at X the ideal employee is one who possesses 9 core competencies:

1. Team Building — Our organization consists of numerous cross-functional
teams so it is critical that our employees can identify and integrate various
organizational roles to achieve the spirit of collaboration and cooperation.

2. Decisiveness — We live and work in a fast paced environment so our
employees must be able to make tough decisions without hesitation.

3. Customer Focus — Our success depends on being responsive to our
customers. Thus, employees must be capable of maintaining and improving
customer satisfaction and understanding/anticipating the customers’ needs.

4. Personal Responsibility - Our employees enjoy a good deal of autonomy and
as result must accept responsibility for their own actions, decisions, and
directions to peers and subordinates.

5. Creative Thinking -- Creativity is critical if we are to remain on the cutting
edge. We expect our employees to think creatively and to foster creative
thinking within the organization and their work teams.

6. Resilience - Not every new idea succeeds thus employees must be capable of
maintaining a positive attitude in response to failure both for themselves and
their work groups.

7. Oral & Written Communication — We communicate with our customers and
each other on a daily basis; thus, it is critical that employees can express
themselves clearly, succinctly, pleasantly and in a straightforward manner
both verbally and in writing.

8. Self-Development — This is a rapidly changing industry and to be successful
we must stay up-to-date. We expect employees to seek out and engage in
self-improvement opportunities.

9. Technical Proﬁciency — Employees must possess the knowledge, skills, and
abilities to get the job done in a timely and effective manner.

91

APPENDD( F

Debrieﬁng form for the experiment

Research indicates that job seekers consider an organization’s reputation an
important factor when deciding where they will apply. We are trying to determine how
students perceive recruiting information and how this information affects students’
opinions of companies. In a time where it is increasingly difﬁcult to ﬁnd qualiﬁed
applicants and it is important for us to understand how recruiting information affects
people’s perceptions and opinions of organizations and if certain types of information can
change applicants’ opinions toward an organization.

Each participant in this study was asked to review one of two sets of recruiting
materials for a particular organization. The materials you reviewed were developed
solely for the purpose of this study and although they are similar to real recruiting
materials they are not actually associated with any particular organization. In order to
understand the role played by both a company’s reputation and speciﬁc types of
information, it was necessary for us to provided everyone with one of two types of
information (i.e., information about company goals and values vs. information about the
types of characteristics, skills, and abilities new employees should have) and simply vary
the name of the organization to see how this affects opinions and application behaviors.
We expect that companies can improve their reputations and attract more qualiﬁed
employees by including the type of information you reviewed today in their recruiting
materials. Additional details regarding the results of this study will be available upon
request in 4-6 months. Thank you for participating in our research. If you have any
additional questions or concerns please feel free to contact Christine Scheu or Ann Marie
Ryan at 355-2171.

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REFERENCES

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References

Ambady, N., & Rosenthal, R. (1993). Half a minute: Predicting teacher evaluations
from thin slices of nonverbal behavior and physical attractiveness. Journal of
Personality and Social Psychology. 64. 431-441.

Barber, A. E. (1998). Recruiting employees: Individual and organizational mrsmctives.
Thousand Oaks, CA: Sage Publications.

Barber, A. E., & Roehling, M. V. (1993). Job postings and the decision to interview:
A verbal protocol analysis . Journal of Applied Psychology, 78, 845-856.

Barnett, J. R., Vaughan, M. J ., & Moody, D. (1997). The importance of person-
organization value congruence for female students joining college sororities.
Journal of College Student Development, 38, 297-300.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic, and statistical
considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Behling, O., Labovitz, G., & Gainer, M. (1968). College recruiting: A theoretical basis.
Personnel Journal 47, 13-19.

Belt, J. A., & Paollilo, J. GP. (1982). The inﬂuence of corporate image and speciﬁcity
of candidate qualiﬁcations on response to recruitment advertisement. Journal of

Management, 8, 105-112.
Borkenau, P., & Lietiousness, A. (1992). Trait inferences: Sources of validity at zero

acquaintance. Journal of Personality and Social Psychology, 62, 645-657.
Boudreau, J. W., & Rynes, S. L. (1985). Role of recruitment in stafﬁng utility analysis.

Journal of Applied Psychology, 70, 354-366.

Boulding, W., & Kirrnani, A. (1993). A consumer-side examination of signaling theory:
Do consumers perceive warranties as signals of quality. Journpl of Consumer
Research 20, 111-123.

Bowen, D. E., Ledford, G. E., & Nathan, B. R. (1996). Hiring for the organization not he
job. In J. Billsbury (Ed) The Effective Manager. Sage Publications: London.

Breaugh, J. A. (1983). Realistic job previews: A critical appraisal and future directions.
Academy of Management Review, 8, 612-619.

Bretz, R. D., Ash, R. A., & Dreher, G. F. (1989). Do people make the place? An
examination of the attraction-selection-attrition hypothesis. Personnel
Psychology, 42, 561-581.

Bretz, R. D., & Judge, T. A. (1994). Person organization ﬁt and the theory of work
adjustment: Implications for satisfaction, tenure, and career success. Journal of
Vocational Behavior 43, 310-327.

Bretz, R. D., Rynes, S. L., & Gerhart, B. (1993). Recruiter perceptions of applicant ﬁt:
Implications for individual career preparation and job search behavior. Journal
of Vocational Behavior, 43, 310-327.

Cable, D. M., & Judge, T. A. (1994). Pay preferences and job search decisions: A
person-organization ﬁt perspective. Personnel Psychology. 47, 317-348.

Cable, D. M., & Judge, T. A. (1996). Person-organization ﬁt, job choice decisions, and

organizational entry. Organizational Behavior and Human Decision Processes,
ﬂ, 294-311.

 

 

 

94

Cable, D. M., & Judge, T. A. (1997). Interviewers’ perceptions of person-organization fit
and organization selection decisions. Journal of Applied Psychology, 82, 546-
561.

Carlson, K. D., & Connerley, M. L. (1999). Stafﬁng as nested decisions: An integrated
model and directions for future research. Paper presented at the 14th Annual
Conference for the Society for Industrial and Organizational Psychology, Atlanta,
Georgia.

Catelli, L., & Zogmaister, C. (2000). The role of familiarity in implicit memory effects:
The case of exemplar activation. Europpan Journal of Social Psychology, 30,
223-234.

Caudron, S. (1997). Hire for attitude: It’s who they are that counts. Workforce, 20-26.

Chan, D. (1996). Cognitive misﬁt of problem solving style at work: A facet of person-
organization ﬁt. Organizational Behavior and Human Decision Processes, 68,
194-207.

Chatman, J. (1991). Matching people and organizations: Selection and socialization in
public accounting ﬁrms. Administrative Science Quarterly, 36, 459-484.

Chatman, J. (1989). Improving interactional organizational research: A model of
person-organization ﬁt. Academy of Management Review, 14, 333-349.

Christie, J ., & Klien, R. (1995). Familiarity and attention: Does what we know affect
what we notice? Memog and Cognition, 23, 547-550.

Cohen, J. (1992). A power primer. Psychological Bulletin 112, 155-159.

Dube, L. & Schmitt, B. H. (1999). The effect of similarity and dissimilarity focus in
positioning strategy: The moderating role of consumer familiarity and product
category. Psychology and Marketing, 16, 211-224.

Dutton, J. E., Dukerich, J. M., & Harquail, C. V. (1994). Organizational Images and
member identiﬁcation. Administrative Science Quarterly. 39, 239-263.

Erdem, T. (1998). An empirical analysis of umbrella banding. Joumpl of Marketing
Research 35, 339-351.

Fabrigar, L. R., & Petty, R. E. (1999). The role of the affective and cognitive bases of
attitudes in susceptibility to affectivity and cognitively based persuasion.
Personality and Social Psychology Bulletin, 25, 363-381.

Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & MacCallum, E. J. (1999).
Evaluating the use of exploratory factor analysis in psychological research.

Psychological Methods, 4(3), 272-299.
Fombrun, C. & Shanley, M. (1990). What’s in a name? Reputation building and

corporate strategy. Academy of Management Journal, 33, 233-258.

Gatewood, R. D., Gowan, M.A. & Lautenschlager, G. J. (1993). Corporate image,
recruitment image, and initial job choice decisions. Academy of Management
Journal 36, 414-427.

Goltz, S. M., & Giannantonio, C. M. (1995). Recruiter friendliness and attraction to the
job: The mediating role of inferences about the organization. Journal of
Vocational Behavior 46, 109-118.

Harkins, S. G., & Petty, R. E. (1981). Effects of source magniﬁcation of cognitive effort
on attitudes: An inforrnation-processing view. Journal of Personality and Social

Psychology, 40, 401-413.

 

 

 

 

95

Herriot, P., & Rothwell, C. (1981). Organizational choice and decision theory: Effects
of employers’ literature and selection interview. Journal of Occupational
Psychology, 54, 17-31.

Highhouse, S., Zickar, M. J., Thorsteinson, T. J ., Stierwalt, S. L., & Slaughter, J. E.
(1999). Assessing company employment image: An example in the fast food
industry. Personnel Psychology, 52, 151-172.

Honeycutt, T. L., & Rosen, B. (1997). Family friendly human resource policies, salary
levels, and salient identity as predictors of organizational attraction. Journal of
Vocational Behpvior. 50. 271-290.

Johnson, W. B., & Packer, A. E. (1987). Workforce 2000: Work_and Workers for the
Twentv-ﬁrst Century. Hudson Institute: Indiana.

Judge, T. A., & Bretz, R. D. (1992). Effects of work values on job choice decisions.
Journal of Applied Psychology, 77, 261-271.

Kenny, D. A., Homer, C., Kasher, D. A., & Chu, L. (1992). Consensus zero
acquaintance: Replication, behavioral cues, and stability. Journal of Personality
and Social Psychology, 62, 88-97.

Keon, T. L., Latack, J. C., & Wanous, J. P. (1982). Image congruence and the treatment
of difference scores in organizational. Human Relations 35, 155-166.

Koch, J. (1990). Beyond nuts and bolts. Personnel Journal, 69, 70-77.

Kristoff, A. L. (1996). Person-organization fit: An integrative review of its
conceptualizations, measurement, and implications. Personnel Psychology, 49, 1-
49.

Laabs, J. J. (1991). Nurses get critical about recruitment ads. Personnel Journal 70, 63-
69.

Laabs, J. J. (1997). Rating jobs against new values. Workforce, 20-26.

Lawler, J. (1994). From job-based to competency-based organizations. Journal of
Organizational Behavior, 15, 3-15.

Martin, S. L., & Raju, N. S. (1992). Determining cutoff scores that optimize utility: A
recognition of recruiting costs. Journal of Applied Psychology, 77, 15-23.

Mason, N. A., & Belt, J. A. (1986). Effectiveness of speciﬁcity in recruitment
advertising. Jourgdﬁof Management, 12, 425-432.

McCormick, E. J ., DeNisi, A. S., & Shaw, J. B. (1979). Use of the position analysis
questionnaire for establishing the job component validity of tests. Journal of
Applied Psychology, 64, 51-56.

McCormick, E. J ., Jeanneret, P, R., & Mecham, R. C. (1972). A study of job
characteristics and job dimensions as based on the position analysis questionnaire
(PAQ). Journal of Applied Psychology, 56, 347-368.

McFadden, L. M., & Hubbard, K. L. ( 1998, December). Team concepts for emerging
organizational architectures. Information Outlook 2, 18-23.

Muchinsky, P. M., & Monahan, C. J. (1987). What is person-environment congruence?
Supplementary versus complementary models of ﬁt. J oumpl of Vocational
Behavior 31, 286-277.

Nassar, S. (1999, April 3), Jobless rate in the US hits 29 year low. New York Times, C,
l.

 

 

 

 

96

Nichols, M. T., & Sikes, J. (1995, December / 1996, January). Survival in transition of
implementing information science core competencies. American Society for
Information Science 22, 11-15.

Noe, R. A., Steffy, B. D., & Barber, A. E. (1988). An investigation of the factors
inﬂuencing employees’ willingness to accept mobility opportunities. Personnel
Psychology, 41, 559-565.

Petty, R. E., & Wegener, D. T. (1998). Matching versus mismatching attitude functions:
Implications for scrutiny of persuasive messages. Personjalitv and Social
Psychology Bulletin, 24, 227-240.

Ravlin, E. C., & Meglino, B. M. (1987). Effects of values on perception and decision
making: A study of alternative work values measures. Journal of Applied
Psychology, 72, 666-673.

Redman, T., & Matthews, B. P. (1992). Advertising for effective managerial recruitment.
Journal of General Management, 18, 29—44.

Rokeach, M. (1973). The Nature of Human V313. New York: Free Press.

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 (2nd ed, Vol 2, pp399-444). Palo Alto,
CA: Consulting Psychologists Press.

Rynes, S. L., Bretz, R. D., & Gerhart, B. (1991). The importance of recruitment in job
choice: A different way of looking. Personnel Psychology, 44, 487-521.

Rynes, S. L., & Gerhart, B. (1990). Interviewer assessments of applicant “ﬁt”: An
exploratory investigation. Personnel Psychology, 43, 13-35.

Rynes, S. L., & Lawler, J. (1983). A policy-capturing investigation of the role of
expectancies in decisions to pursue a job alternative. Journal of Applied
Psychology. 68. 620-631.

Rynes, S. L., Schwab, D. P., & Heneman, H. G. (1983). The role of pay and market
variability in job application decisions. Organizational Behavior and Human
Performance 31, 353-364.

Saks, A. M. (1994). A psychological process investigation for the effects of recruitment
source and organization information on job survival. Journal of Organizational
Behavior 15, 225-244.

Saks, A. M., & Ashford, 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.

Scheu, C. R., Ryan, A. M., & Nona, F. (1999). Company web sites as a recruiting
mechanism: What inﬂuences applicant impressions. Paper presented at the 14th
Annual Conference for the Society for Industrial and Organizational Psychology,
Atlanta, Georgia.

Schneider, B. (1987). The people make the place. Personnel Psychology, 40, 437—453.

Schwoerer, C., & Rosen, B. (1989). Effects of employment at will policies and
compensation policies on corporate image and job pursuit intentions. Journal of
Applied Psychology, 74, 653-656.

Shimoda, T. A. (1993). The effects of interesting and topic familiarity on text

comprehension, attention and reading speed. Journal of Experimental Education,
_6__1_, 93-103.

 

 

 

97

Spence, M. (1973). Job market signaling. Quarterly Journal of Economics. 87. 355-374.

Stroops, R. (1984). Reader survey supports market approach to recruitment. Personnel
Psychology, 93, 22-24.

Tabachnick, B. G., & Fidell, L. S. (1996). Using Multivariate Statistics. New York:
Harper Collins College Publishers.

Tajfel, H., & Turner, J. C. (1985). The social identity theory of group behavior. In S.
Worchel & W. G. Austin (Eds), Psychology of Interggoup Relations. Chicago:
Nelson-Hall.

Tett, R. (1999). [Organizational Competencies]. Unpublished raw data.

Thorson, E. & Lang, A. (1992). The effects of videographics and lecture familiarity on
adult cardiac orienting responses and memory. Communication Research 19,
346-369.

Thorsteinson, T. J ., Ryan, A. M., & McFarland, L. A. (1997). Effect of job
advertisement speciﬁcity and inferences about organizational characteristics on
applicant attraction. Paper presented at the 12th Annual Conference for the
Society for Industrial and Organizational Psychology, St. Louis, Missouri.

Tom, V. R. (1971). The role of personality and organizational images in the recruiting
process. Organizational Behavior and Human Performance, 6, 573-592.

Turban, D. B., & Greening, D. W. (1996). Corporate social performance and
organizational attractiveness to prospective employees. Academy of Management
Journal 40, 658-672.

Turban, D. B., & Keon, T. L. (1993). Organization attractiveness: An interactionist
perspective. Journal of Applied Psychology, 78, 184-193.

Vancouver, J. B., & Schmitt, N. W. (1991). An exploratory examination of person-
organization congruence. Personnel Psychology, 44, 333-352.

Werbel, J. D., & Landau, J. (1996). The effectiveness of different recruitment sources:
A mediating variable analysis. Journal of Applied Social Psychology, 26, 1337-
1350.

Wemerfelt, B. (1988). Umbrella banding as a signal of new product quality: An
example of signaling by posting a bond. Rand Journal of Economics 19, 458-
466.

Wilk, S. L., & Sackett, P. R. (1996). Longitudinal analysis of ability-job complexity and
job change. Personnel Psychology, 49, 937-967.

 

 

 

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