Retail career attractiveness to college students: Connecting individual characteristics to the trade-off of job attributes

Journal of Retailing and Consumer Services 31 (2016) 345–354

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Retail career attractiveness to college students: Connecting individual characteristics to the trade-off of job attributes Hyunjoo Oh a,n, Barton Weitz b, Jeremy Lim a,b a Research Director, David F. Miller Center for Retailing Education and Research, 100 Stuzin Hall, Warrington College of Business Administration, University of Florida, Gainesville, FL 32611, USA b Emeritus JCPenney Eminent Scholar Chair and Professor of Marketing, Warrington College of Business Administration University of Florida, Gainesville, FL 32611, USA

art ic l e i nf o

a b s t r a c t

Article history: Received 18 April 2016 Accepted 19 April 2016

This study examines how U.S. business college students evaluate the attractiveness of potential job opportunities by making trade-offs among important job attributes. Using a conjoint approach, we examine the relative importance of industry type, starting salary, five-year salary, training, benefits, and work-life balance in job choice decisions. We also examine the effects of job applicants' career expectations and core competencies on their job choice determinants. An analysis of 162 business students' evaluations of 27 job profiles indicates that five-year-salary outweighs all other attributes. Their career expectations and core competencies have a substantial influence on their ensuing job choice. We suggest recruitment strategies to target recent college graduates with consideration of individuals' different career expectations and core competencies. & 2016 Elsevier Ltd. All rights reserved.

Keywords: Career expectation Conjoint approach Core competency Job choice determinants Recruitment Retailing career

1. Introduction The retail sector plays a vital role in the U.S. economy, supporting 1 in 4 American jobs. Each year the retail industry contributes over $2.6 trillion in total GDP impact to the American economy, and this number is only expected to grow (PWC, 2014). Because of this, it is critical that retailers revamp their recruiting tactics in order to beat competing industries in the fight to capture top talent. Recruitment has become one of the most important elements of strategy, as it influences all subsequent human resource practices, which further determines organizational performance (Breaugh and Starke, 2000; Rynes, 1991; Roberson et al., 2005). Also, since talented employees are often viewed as one of the most important factors of production needed by retailers to stay competitive in today's rapidly changing retail environments, many retail organizations have focused their recruiting efforts on college graduates (Reda, 2008). Indeed, the importance of recruiting “top talent” is underscored by numerous factors, such as the eminent retirement of the baby boomer generation, the increasing use of sophisticated technology in retailing, the competitive and quickly changing retail environment, and the placement of profit and loss responsibilities on frontline managers. It is for n

Corresponding author. E-mail addresses: [email protected]fl.edu (H. Oh), [email protected]fl.edu (B. Weitz), [email protected] (J. Lim). http://dx.doi.org/10.1016/j.jretconser.2016.04.012 0969-6989/& 2016 Elsevier Ltd. All rights reserved.

these reasons that the search for “top talent” is, and will remain, a high priority for retail organizations. Recruiting the best and the brightest college graduates has been a challenge for retailers due to negative stereotypes associated with the retailing profession (i.e. long work-hours, low compensation, monotonous work, and poor work-life balance), as documented in previous studies (Broadbridge, 2003b; Houlton and Thomas, 1990; Rhoads et al., 2002; Swinyard et al., 1991). Moreover, Broadbridge, (2003b) compared his results with similar research, conducted at early 80s (Swinyard, 1981) and 90s (Swinyard et al., 1991) and found that negative perception of a retail career prevailed and retail remained an unattractive career choice to college students during those 20 years. However, college graduates have recently begun to see renewed opportunities in retailing careers. A pool of talented graduates now want to pursue careers in retailing, in part inspired by the rapidly changing landscape of retailing, with emphasis shifting toward employee responsibility in areas such as financial management, leadership, and technological skills. It is expected that college students are even willing to start out by working in training track positions at retail stores (Broadbridge, 2003b). While such a change is a definite positive for retail recruitment, challenges brought about by competing industries still exist. Specifically, companies in other industries are simultaneously increasing their recruitment efforts, targeted toward those same talented graduates. Retailers should be wary of such competition because students are primarily concerned about their own career

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development with no boundaries on specific industries and job categories (Rousseau and Arthur, 1999). Hence, it is important to understand how these potential job candidates evaluate the attractiveness of jobs and make their decision across different industries. Due to its importance, retail career attractiveness and choice has attracted significant research attention in the past three decades (e.g., Hurst and Good, 2009; Broadbridge, 2003a, 2003b; Commins and Preston, 1997; Shim et al., 1999; Swinyard, 1981). However, most previous studies employed regression or structured equation modeling to model the static relationships between different determinants and college students’ retail career choice, while the dynamic trade-off of different determinants by college students in their career choice was completely neglected. Extending the existing literature methodologically, we employed a policy capturing methodology called conjoint analysis in marketing research. This method allows us to estimate psychological tradeoffs that job candidates make when evaluating several job attributes together and uncovers real or hidden drivers which may not be apparent to the respondent themselves. Furthermore, this study considered not only the trade-off of job attributes but also the influence of individual factors including career expectations and core competencies on college students' retail career choice. This study shed new light on college students' retail career choice by connecting job candidates' career expectations and competencies to the relative importance assessment of the various job attributes. Overall, we set out to investigate the following two research questions in this study: (1) what critical job attributes do business students use to determine job attractiveness when evaluating alternative job opportunities, and (2) how do college students’ career expectations and core competencies affect the relative importance of job attributes as they evaluate the attractiveness of a job? The answer to the above to research question will provide significant implications for retail managers. Several authors (e.g., Casey, 2006; Broadbridge et al., 2009.) have argued that retailers have not been successful in selling retail careers to the public. The negative perception of retail careers may be caused by poor communication between the retail industry and prospective job candidates (Broadbridge, 2003b). Thus, it is critical for retail recruiters to provide job information that is attractive to their targeted pool of candidates and communicate effectively with them. To build effective communication strategies, retailers must understand the important factors that influence the candidates' evaluation of job attractiveness and, ultimately, their job choice. This means recruiters have to understand not only which job attributes are particularly important for influencing job choice but also whether the effect of individual factors exist in job choice evaluation. In summary, this study helps retailers develop effective communication strategies that can heighten job candidates’ interest in learning more about the retailers’ career offerings and may thus increase the economic return to retailers’ recruiting efforts.

2. Literature review and theoretical framework Previous studies on retail career choice suggested that career choice or career attractiveness are determined by both job attributes and individual factors. For example, some previous studies focused on job attributes (e.g., Kim et al., 2009), some emphasized individual factors such as work expectation and personal values (e.g., Broadbridgea et al., 2003b), and the others evaluated the factors from both sides (e.g., Shim et al., 1999). In this study, we consider factors on both sides and propose that career expectation drives college students’ trade-off among different job attributes

based on their evaluation of their own core competencies. We will discuss each category of factors below. 2.1. The effects of individual factors Previous studies have widely examined individual factors that determine job candidates' career choice because different individuals have different needs and seek jobs that best fit these needs. Researchers have also pointed out that individual-organization fit influences not only job choice but also job performance and satisfaction (Cable and Judge, 1994; Cable and Edwards, 2004; O’Reilly et al., 1996). The importance of fit between the individual and his or her job implies that individual characteristics, such as values, capabilities, and goals, influence job choice. This further implies that career expectation and competency appear to influence the evaluation of job attractiveness. 2.1.1. Career expectation Career expectation, or work value, is the anticipation that job seekers have for their careers. Researchers have established that work value predicts job choices as individuals seek jobs that provide a fit between their work values and the characteristics of their job or organization (Cable and Judge, 1994; Elizur, 1984; Judge and Bretz, 1992; Knoop, 1994). The dimensions of work values suggested by researchers vary. For instance, Ros et al. (1999) proposed four basic dimensions as intrinsic, extrinsic, social, and prestige, whereas Cable and Edwards (2004) proposed eight dimensions as altruism, relationships with others, pay, prestige, security, authority, variety, and autonomy. In addition, Knight et al. (2006) proposed three other dimensions, such as: environment, opportunity, and success. Gush (1996) found that college graduates employed in retail stores expected the following characteristics: structured training and development programs, advancement opportunities, responsibility and variety in their job, clear career paths, and opportunities to fulfill their long-term career aspirations for success. Given this backdrop, we intend to identify the dimensions of career expectations that are relevant to college students’ job choices and to test the degree to which the different dimensions correspond to varying emphasis on the job attributes. 2.1.2. Core competencies Vroom noted that: “… people not only select their occupations…. they are selected for occupations…” (Vroom, 1964, p.56). His notion suggests that capabilities, skills, or competencies can influence job seekers’ evaluation of job attractiveness. Previous studies have shown that skills and abilities influence job performance and satisfaction (Fricko and Beehr, 1992). It is then reasonable to believe that one's self-assessment of core competencies plays an important role in regard to evaluating job attractiveness. The Society for Human Resource Management (SHRM) defines personal core competencies as competencies that employees must possess in order to successfully perform job functions that are essential to business operations. Whether the above reference is to task-based competence or general competence is debatable (Brown, 1994; Hart et al. 1999; Lievens et al., 2004; Woodruffe, 1991). Nonetheless, we adopt the general definition that describes managerial competence as personal traits, characteristics, or skills that are shown to influence job performance. Such a definition is also consistent with that of previous studies on retail and management careers (Hart et al., 1999; Preston and Smith, 1997). It is particularly important to understand how an individual's perceived general competence influences their evaluation of job choice alternatives since retailing requires general competencies, such as personal skills, energy, and drive that cannot be trained.

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2.2. The role of job attributes Researchers have pointed out that the attractiveness of a job listing itself plays a major role in soliciting responses and can subsequently affect the applicant's job choice (Breaugh and Starke, 2000; Turban et al., 1993). Accordingly, many studies have focused on identifying the relative preference for various job attributes, with job attribute preference defined as the extent to which people desire specific qualities and outcomes from their work (Konrad et al., 2000). For example, the job characteristic model proposed by Hackman and Oldham (1976) identified five core job dimensions (including skill variety, task identity, task significance, autonomy, and feedback) that determine the internal motivation or attractiveness of a job. Moreover, Kim et al. (2009) found that Generation Y employees' perception of job characteristics mediated the relationship between their perception of work environment and retail career intention. Job attributes that have been identified influencing job candidates' career choice include: pay, promotional opportunity, location, benefits, autonomy, security, type of work, organizational characteristics, and flexibility or work-life balance (Cable and Judge, 1994; Culpepper, 2006; Konrad et al., 2000; Feldman and Arnold, 1978; Judge and Bretz, 1992; Jurgenson, 1978; Ng and Burke, 2006; Rynes, 1991; Rynes et al., 1983; Schwab et al., 1987). Across these numerous studies, one common denominator is that pay and promotional opportunity are the two most important attributes that influence job choice. Other factors also identified in one of the above studies are type of industry, development opportunities, and prevalent organizational culture. Specifically, Cable and Graham (2000) demonstrated that the type of industry in which a firm operates, the opportunities that a firm provides for its employee development, and the organizational culture prevalent at the firm can influence its reputation, which can subsequently influence the applicant's job choice. On the other hand, students may also view their career as “having no boundaries between industries,” which has become an increasingly common view due not only to increased job mobility but also their changing opinions as to what constitutes a successful career (Rousseau and Arthur, 1999). Although their chosen major and its curriculum may result in some career restrictions (Berger, 1988; Kim et al., 2002), these restrictions are by no means set in stone. Talented students often receive offers from multiple organizations across different industries. As students are not restricted by a particular industry, they may trade-off between job attributes and their perception of a particular industry.

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been very accurate (Aiman-Smith et al., 2001; Philips et al., 2002; Rynes and Lawler, 1983; Slaughter et al., 2006). On the other hand, since people use non-compensatory strategies for complex decisions or decisions between conflicting choices that involve trade-offs, researchers then assume that job applicants are also likely to use the same strategies for job choice decisions. Using non-compensatory strategies, job applicants base their job choice decisions on one or two critical attributes or tradeoffs among different attributes (Baker, Ravichandran , and Randall, 1989; Spence and Keeping, 2010; Turban et al., 1993). Suppose there are two job offers: Job A is a management track position for a convenience store with high starting salary, low prestige, and fast career advancement and Job B is a position in a banking company with medium starting salary and high prestige but with slow career advancement. Judgments of relative attractiveness and the subsequent choice between these two jobs are then likely to be influenced by trade-offs that job applicants make on important attributes. To address the issue of how an individual chooses from different job opportunities that involve trade-offs, researchers have used the policy-capturing method (Aiman-Smith et al., 2001; Rynes et al., 1983; Sanchez and Levine, 1987; Slaughter et al., 2006). In this method, job seekers evaluate the attractiveness of job profiles that vary by attributes (e.g., starting salary, promotional opportunity, location, etc.). Then, the relative importance of each attribute in determining job attractiveness is statistically estimated through a regression analysis. The policy- capturing method is equivalent to conjoint analysis used in marketing research. Researchers claim that the policy capturing method allows for casual inferences on job choices without being vulnerable to biases, such as self-insight and social desirability (Cable and Graham, 2000; Cable and Judge, 1994; Schwab et al., 1987). In this study, we first use the policy-capturing method to identify the most important job choice determinants, considering the job attribute/industry trade-offs. As recruiting organizations differentiate themselves more succinctly by their comparative advantage, job seekers are more pressed to make trade-off decisions. We then regress college students’ career expectation and core competencies on the relative importance of each attribute resulted from the conjoint analysis. The associations between college students’ career expectation and competencies reflect how individuals’ internal motivators (including career expectation and core competencies) drive the trade-offs of different job attributes when they evaluate the attractiveness of different jobs.

2.3. Approaches to job choice determinants As described in the literature, researchers have used one of two approaches depending on what assumptions they make regarding the strategies that job seekers use (Highhouse and Hoffman, 2001). One of these approaches, adopted by many researchers, is based on Vroom's (1964) expectancy theory, which assumes that job seekers use a compensatory strategy to maximize the expected utility of their job choice (Shim et al., 1999; Wanous et al., 1983; Vann et al., 2000). In doing so, job seekers combine the desirability or importance of outcomes (e.g., high income, training, security, prestige) with the perceived expectancy of achieving the outcomes with their corresponding job in a multiplicative manner. Although the expectancy theory enables researchers to identify the important factors influencing overall job or career preference, researchers have criticized that the method of directly asking job seekers to rate each job attribute subjects them to its social desirability bias (Rynes, 1991; Schwab et al., 1987). In addition, since respondents have a tendency to rate all attributes as being important, predictions made with importance responses have not

3. Methodology 3.1. Sample Our sample consisted of business students at a large public university in the Southeastern United States. Subjects participated in an online survey on a voluntary basis with an opportunity to earn $25. A total of 186 business students responded to our email invitation, with 162 students subsequently completing the internet survey. As hoped for, students who participated in our study comprised mostly of juniors and seniors, who are more likely to have given serious consideration to their post-graduation career options. Nevertheless, freshmen and sophomores were not excluded and collectively comprised 7.1% of our sample. Of the 162 respondents, 64.6% were female; respondents' majors included: finance (27.8%), management (17.9%), marketing (25.3%), and all others (29.0%).

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3.2. Study design Adopting the policy capturing method, also called full profile conjoint analysis, we developed 27 job profiles. Each job profile is characterized by a unique combination of varying attribute levels for the six attributes. From respondents' overall evaluations of job profiles, we then used linear regression to estimate individuals’ utilities (part-worths) of the job attributes that enter their calculations in evaluating the attractiveness of overall job profiles. The utility estimates are determined by a set of attributes, the attribute levels, and the range of the levels shown in the job profiles (Ohler et al., 2000). Thus we selected attributes that satisfy the following conditions: (1) the attributes have to be inclusive (i.e. they contain all potentially important attributes relevant to the job choice context) so as to avoid biased estimates (Aiman-Smith et al.,

2002), (2) the attributes need to be able to differentiate the job choices, and (3) the number of attributes selected should produce a reasonable number of profiles so as not to induce fatigue (Slaughter et al., 2006). First, we selected key attributes based on our literature review and pre-tested them on two focus group interviews, which consisted of potential job seekers. The focus group method was adopted because it is particularly useful for exploring people’s knowledge and experience (Parker and Tritter, 2006). In addition to pay and promotional opportunity, our focus group participants emphasized the importance of these additional attributes: training in the early stages of career development, work-life balance, and benefits. Corresponding attribute levels were determined by interviews with career coordinators and recruiters. To control for the variation in benefits and work-life balance policies across

Table 1 Attributes/levels and job profiles. Attributes and levels Attributes Career field (X1)

L1 Sales

L2 Banking

L3 Retailing

Starting Salary (X2) Salary in 5 years (X3) Benefits (X4) Work-Life Balance (X5) Training (X6)

$30,000

$36,000

$42,000

$42,000

$65,000

$80,000

Below industry average Below industry average

Industry average

Among best in industry

Industry average

Among best in industry

Basic skill development

Basic skill development PLUS leadership development

Basic skill development PLUS leadership development PLUS support for MBA/Master

Job profile created with the orthogonal fractional factorial design Job profile

X1

L1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

L1 L1 L1 L1 L1 L1 L1 L1 L1 L2 L2 L2 L2 L2 L2 L2 L2 L2 L3 L3 L3 L3 L3 L3 L3 L3 L3

X2

L2

L3

X1Banking

X1Retail

L1

L1 L1 L1 L2 L2 L2 L3 L3 L3 L1 L1 L1 L2 L2 L2 L3 L3 L3 L1 L1 L1 L2 L2 L2 L3 L3 L3

X3

L2

L3

X2M

X2H

L1

L1 L1 L1 L2 L2 L2 L3 L3 L3 L2 L2 L2 L3 L3 L3 L1 L1 L1 L3 L3 L3 L1 L1 L1 L2 L2 L2

X4

L2

L3

X3M

X3H

L1

L1 L1 L1 L2 L2 L2 L3 L3 L3 L3 L3 L3 L1 L1 L1 L2 L2 L2 L2 L2 L2 L3 L3 L3 L1 L1 L1

X5

L2

L3

X4M

X4H

L1

L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3 L1 L2 L3

L2

L3

X5M

X5H

H. Oh et al. / Journal of Retailing and Consumer Services 31 (2016) 345–354

companies and industries, we used overall relative levels (i.e. below-industry-average, industry-average, and among-best-in-industry). We chose banking, sales, and retail as the industry types because they constitute the most common hiring industries of business college graduates. SYSTAT software was then used to generate an orthogonal fractional factorial design for the six attributes (industry type, starting salary, five-year salary, benefit, work-life balance, and training), each with 3 levels/types, resulting in a total of 27 job profiles. Table 1 shows the six attributes, with corresponding levels, used for generating the 27 job profiles. 3.3. Procedure and measures Prior to performing the job attractiveness evaluation, subjects were asked to choose the type of industry they preferred to work in and to rate the importance of their career expectations using a 5-point scale, ranging from “very unimportant” to “very important.” The measures of career expectations were developed in consultation with those developed and validated by Cable and Edwards (2004). Next, participants proceeded to evaluate the attractiveness of the 27 job profiles job on an 11-point scale, ranging from “not attractive at all” to “very attractive.” The order in which the 27 job profiles were presented was randomly determined for each participant. Participants then responded to questions designed to gauge their core competencies using a 7-point scale, ranging from “least characteristic of me” to “most characteristic of me.” These measures were developed based on scales used for assessing competencies required by retail and management sectors (Arnold et al., 1999; Commins and Preston, 1997; Hagan et al., 2006; Hart et al., 1999). Finally, demographic variables (age, gender, year, and major) were collected. 3.4. Analysis framework To investigate the research questions, we coded the attributes of profiles using binary indicator variables according to the following coding scheme and test series of regression models. Attribute One: Industry Career Field_Bank ¼1 if career field ¼“Banking” in the job profile description ¼ 0 otherwise Career Field_Retail ¼1 if career field ¼ “Retailing” in the job profile description ¼ 0 otherwise Attribute Two: Starting Salary Starting Salary Med ¼1 if starting salary ¼“36,000” in the job profile description ¼ 0 otherwise Starting Salary High ¼1 if starting salary ¼“42,000” in the job profile description ¼ 0 otherwise Attribute Three: Five-Year Salary 5 YR Salary Med ¼1 if five year salary¼ “65,000” in the job profile description ¼ 0 otherwise 5 YR Salary High ¼1 if five year salary¼“80,000” in the job profile description ¼ 0 otherwise Attribute Four: Benefits Benefits Med ¼1 if benefits ¼“industry average” in the job profile description ¼ 0 otherwise Benefits High ¼1 if benefits¼ “above industry average” in the job profile description ¼ 0 otherwise

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Attribute Five: Work-Life Balance WL Bal Med¼ 1 if work life balance ¼ “industry average” in the job profile description ¼0 otherwise WL Bal High¼ 1 if work life balance ¼“above industry average” in the job profile description ¼0 otherwise Attribute Six: Training Train Med ¼1 if training ¼“basic skill development PLUS leadership development” in the job profile description ¼0 otherwise Train High ¼1 if training ¼“basic skill development PLUS leadership development PLUS support for MBA/ Masters” in the job profile description ¼0 otherwise To investigate research question (1), we assessed the ability of these six job attributes to predict job seekers’ evaluation of job attractiveness using participants’ evaluations of the attractiveness of each job profile. The technique used for this task was a traditional full-profile conjoint analysis:

Job profile rating = β0 + Σ βij *Dij + ϵ where

β0 ¼ intercept βij ¼the part worth (utility) from attribute j at a level i ε ¼an error term We calculated the importance of each job attribute as the corresponding range of the part-worths (utilities), obtained from the prior analysis. Specifically, for ordinal attributes (i.e. starting salary, five-year salary, benefits, work-life balance and training) we assigned the estimated coefficient for the indicator variable, representing the highest attribute level as the range value since the range of an ordinal attribute is simply the utility attached to its highest level minus the utility attached to its lowest level, which coincidentally is the omitted level and thus has a coefficient value equaling zero. For the one non-ordinal variable (i.e. career-type), we computed the range by taking the difference between the utility assigned to the highest attribute level and that assigned to the lowest attribute level after having substituted zero as the coefficient for the “sales” attribute level (Sethuraman et al., 2005). Relative importance of the job attributes were then calculated as the importance of each attribute divided by the total importance of all six attributes and expressed as percentages. In all, this resulted in six relative importance variables that comprise our dependent variables (I1–I6) for the research question (2). To investigate research question (2), we first factor analyzed the career expectations and core competency responses using principal components with a varimax rotation. This process yielded 11 factors, which are displayed in Table 2 with their corresponding loading. With the factor scores as our independent variables, we proceeded with our regression analysis. Specifically, our model is given by:

Relative importance of attribute j = β0 + Σβjk *Fjk + ϵ where

β0 ¼ intercept Βjk ¼ the estimated coefficient of factor score k on the relative importance of attribute j ε ¼an error term

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Table 2 Factor analysis of constructs. Scale items

Factor loadings

α

Being sure I will always have a job Being certain my job will last Being certain of keeping my job

0.851 0.840 0.839

0.878

Career development

Training programs for professional growth Leadership development Existing role models for projected career paths Responsible for significant business activities

0.708 0.699 0.657 0.518

0.719

Social value

Making the world a better place Being of service to society Helping others Working closely with people

0.851 0.851 0.763 0.517

0.818

Intrinsic work

Doing a variety of things Doing exciting work Doing challenging work

0.734 0.691 0.580

0.701

Work conditions

Work-life balance Pleasant working conditions Flexible working hours Benefits

0.834 0.695 0.627 0.524

0.732

Extrinsic outcome

Future earnings potential Opportunities for promotion/advancement Starting salary Future career progression

0.761 0.701 0.635 0.560

0.745

Status

Obtaining status Gaining respect Being looked up to by others

0.778 0.630 0.612

0.729

Autonomy

Doing my work in my own way Determining the way my work is done Making my own decisions

0.856 0.721 0.619

0.751

People management skills

People orientation Team player Motivation Communication skill Energy level Achievement orientation Initiative

0.787 0.759 0.712 0.698 0.659 0.640 0.596

0.875

Problem-solving skills

Analytical reasoning Problem solving ability Intelligence Business knowledge

0.810 0.807 0.653 0.579

0.764

Planning/execution

Attend to details Planning and organization Prioritization Accountability

0.771 0.696 0.616 0.613

0.72

Factors Career expectations Security

Core compentencies

4. Results 4.1. Job choice and interest Almost half (48.8%) of all participants chose banking as their

preferred sector; for retailing and sales, the percentages are: 27.1% and 24.1%, respectively. This indicates that banking is the preferred industry for business students. Measures assessing career interest (using a five-point scale) also show the same pattern: banking (4.30), sales (3.83), and retailing (3.75).

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Table 3 Part-worth utility of job attributes. Attribute

Level

Coded independent variable

n

Relative importance

2.981n

Intercept Industry type

Sales Banking Retailing Starting salary $30,000 $36,000 $42,000 Five year salary $42,000 $65,000 $80,000 Benefits Below industry average Industry average Among best in industry Work-life balance below industry average Industry average Among best in industry Training Basic skill development Basic skill development PLUS leadership development Basic skill development PLUS leadership development PLUS support for MBA/Master

Estimated coefficients t-value

X1_banking X1_retailing

 0.358 0.014

 2.847n 18.86% 0.194 5.501n 0.914

X2_M X2_H

0.278 0.071

X3 _M X3 _H

1.843 2.927

19.706n 36.51% 23.276n

X4_M X4_H

0.212 1.088

3.120n 13.57% 16.900n

X5_M X5_H

0.961 1.229

14.915n 15.33% 14.539n

X6_M X6_H

0.177 1.191

3.173n 14.85% 14.434n

0.88%

Significant at po 0.005.

4.2. The relative importance of job attributes in career choice The relative importance of each job attribute determining job attractiveness evaluation was aggregated to examine research question 1 (What critical job attributes do business students use to determine job attractiveness when evaluating alternative job opportunities?). The effects of our independent variables on job attractiveness evaluation are summarized in Table 3. The t-test values corresponding to the standardized regression coefficients indicate that most variables are statistically significant at p o0.005, except for the indicator variables denoting the retailing career option (relative to the sales career option) and the highest starting salary (relative to the lowest starting salary). Fig. 1 illustrates utility estimates of each attribute level. Although banking was the industry of choice for most students in the absence of job specific attributes, it became the least preferred industry after taking the different attributes into account. The results also indicate that students value training more when such training comprises additional support for MBA/Masters programs as opposed to basic training with leadership development. While jobs with industry-average work-life balance enhance their appeal to business students, jobs with industry-average benefits do not. In fact, only jobs with above-industry average benefits are found to be significantly appealing to business students. The results of attributes' relative importance indicate that fiveyear salary is the most important attribute for students when evaluating job attractiveness (Table 3). In fact, the five-year salary accounts for 36.51% of total attribute importance, followed by the industry type, work-life balance, training and benefits attributes, which accounted for 18.86%, 15.33%, 14.85%, and 13.57%, respectively. The least important was starting salary, which accounted for a mere 0.88% of total attribute importance. The lack of importance placed on starting salary relative to a career advancement attribute (i.e. five-year salary) is noteworthy since it shows that students care more about growth prospects than starting salary. Additionally, we estimate the total value of a specific job profile by using the estimated utilities of attribute levels; we do so by adding the part-worth for each attribute level. For example, a sales job (0) with a $42,000 starting salary (0.071), followed by subsequent increases leading to a five-year salary of $65,000 (2.927), below average benefits (0), above average work-life balance

(1.229) and basic training plus leadership training (0.177) can be expected to receive a rating of 4.394. On the other hand, a retail job (0.014) with a starting salary of $30,000 (0), a five-year salary of $80,000 (2.927), above average benefits (1.088), average worklife balance (0.961), and basic training, leadership training, and educational support (1.191) can be expected to receive a rating of 6.181. The higher score for the retail job suggests that on average, students would prefer the retail job over the sales job even when the starting salary for the former is considerably lower. 4.3. The association between job candidates' characteristics and relative importance of job attributes To address research question 2 (How do college students' career expectations and core competencies affect the relative importance of job attributes as they evaluate the attractiveness of a job?), we conducted multiple regression analyses and examined the degree to which applicant characteristics predict their relative importance of job attributes. Table 4 provides the results from the regression of the six models where relative importance scores of the six job attributes were employed as criterion variables. Predictor variables are comprised of constructs that represent career expectations and core competencies. Constructs for career expectations include: career development, security, social value, work condition, intrinsic work, extrinsic outcome, autonomy, and expected career status. Constructs for core competencies include: people management skills, problem-solving skills, planning/ execution. The results indicate that the intrinsic work orientation (β ¼ .22, p o0.05) and people management skills (β ¼.21, p o 0.05) are apt predictors of the importance attached to the industry type attribute. Extrinsic outcome orientation (β ¼ .28, p o0.01) positively influences the importance attached to five-year salary whereas people management skills (β ¼  .24, p o0.05) negatively influences its importance. Expectations concerning development (β ¼.18, p o 0.05), work conditions (β ¼ .33, p o0.001) and occupational status (β ¼ .24, p o 0.01) are found to positively influence the importance of career training whereas planning and execution orientation is found to negatively influence its importance (β ¼  .20, po 0.05). Finally, higher expectations concerning work conditions (β ¼.37, p o0.001) and lower orientation toward

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I n d us t r y ty pe

Starting salary

3

3

2.5

2.5

2

2

1.5

1.5

1

1

0.5

0.5 0

0 Sales

Banking

$30,000

Retailing

$36,000

$42,000

-0.5

-0.5

Five-year salary

Benef its

3

3

2.5

2.5 2

2

1.5 1.5

1

1

0.5

0.5

0

0

-0.5 $42,000

$65,000

below industry

Industry average

average

$80,000

Among best in industry

-0.5

Training

Work-life balance

3

3

2.5

2.5

2

2

1.5

1.5

1

1

-0.5

-0.5

below industry average

Industry average

Among best in industry

Plus Education Support

0

0

Plus Leadership Development

0.5

Basic skill development

0.5

Fig. 1. Utilities of job attributes.

extrinsic outcomes (β ¼  .24, p o0.01) are associated with higher levels of importance attached to work-life balance.

5. Discussion Our research illustrates what future job candidates for management positions view as important in making job choice decisions. We identify their job choice determinants by investigating how they evaluate the attractiveness of different job profiles, created by varying six common job descriptors. An understanding of the attributes that influence applicant job choices is important for attracting applicants, influencing their job choice, (Roberson et al., 2005) and for giving insights into recruitment and selection strategies. First, our findings reveal that five-year rather than starting salary is of paramount concern to students. This finding demonstrates the general tendency of preferring outcomes that improve over time, such as increasing wage profiles. Also, it reflects the career development ambitions of business students. This finding is illuminating considering that five-year salary is usually unknown or not revealed during the recruitment process,

suggesting that retailers should emphasize five-year salary profiles, opportunities for advancement, and future career progression to attract talented workers. Another interesting finding is that the relative importance of industry type changes once we account for job specific attributes. Many studies have demonstrated that, among college students, retailing and sales careers result in negative perceptions and are not usually held in high regard (Amin et al., 1995; Swinyard, 1981; Swinyard et al., 1991; Rhoads et al., 2002). Consistent with these studies, the direct measures (i.e., career choice and interest) in our study reveal that banking is the preferred industry to retailing and sales when respondents are not provided with additional job information. However, a preference reversal (i.e. banking becomes the least preferred industry) occurs when information concerning job attributes is made available. This finding is particularly encouraging for retailers, since it suggests that they can counter the negative perceptions associated with a retailing career by offering career opportunities that are competitive with those of other industries. They can incorporate specific job attributes that are valued by business students, such as advancement opportunities and future earnings potential, to increase the appeal of their career offerings.

H. Oh et al. / Journal of Retailing and Consumer Services 31 (2016) 345–354

353

Table 4 The results of relative job attribute importance regressed on job applicants’ career expectations and core compentencies. Predictors

Criterion variables Standardized Beta Coefficient (β)

Constant E_Development E_Security E_Social value E_Work conditions E_Intrinsic works E_Extrinsic outcomes E_Autonomy E_Status C_People management C_Plan & execution C_Problem solving R2 Adjusted R2 F p

Industry Type

Starting Salary

Five year salary

Training

Benefits

Balance

 0.169 0.110  0.114  0.105 0.216n 0.160 0.069  0.060 0.214n 0.011  0.147

0.088  0.071  0.079  0.088 0.091 0.168 0.075  0.060 0.016 0.063  0.077

 0.003  0.032 0.033 0.009  0.148 0.280nn  0.088 0.009  0.237n 0.013 0.123

0.183n  0.065  0.046  0.332nnn 0.115  0.136  0.024 0.240nn 0.147  0.202n 0.112

 0.017  0.080  0.118 0.009  0.060 0.104 0.169  0.019 0.080 0.159  0.043

 0.045  0.049  0.004 0.367nnn  0.008  0.238nn 0.083  0.103 0.165  0.071 0.005

0.092 0.023 1.326 0.208

0.064  0.007 0.906 0.542

0.136 0.070 2.069 0.022

0.216 0.157 3.633 0.000

0.067  0.004 0.949 0.500

0.184 0.122 2.969 0.001

n

po 0.05. p o0.01. nnn p o 0.001. nn

Our findings also demonstrate the substantial influence of job candidates' characteristics (career expectations and core competencies) on their job choices. Specifically, for four job attributes (i.e. industry type, five-year salary, training, and work-life balance), we found that variations in individual expectations and orientation account for a significant difference in the importance attached to these job attributes. As expected, one's intrinsic work orientation influences the importance of industry type in job choice while extrinsic orientation influences the importance attached to five-year-salary. For the training attribute, we found that individuals with high expectations for career development also attach high importance to job training whereas those with high expectations for work conditions, such as work-life balance, pleasant work conditions, and flexible work hours deemphasized the importance attached to training when evaluating job attractiveness. It is also evident that individuals' core competencies affect the relative importance they attach to job attributes. Despite the use of a relatively homogeneous sample (business students) and rather simplistic measures of self-assessed core competencies, we were nonetheless able to reveal the effects of one's core competencies on job choice decisions. Our findings suggest that job candidates with people management skills are also the ones with a strong preference for a particular industry but are simultaneously less likely to value five-year-salary. In addition, job candidates with strong planning and execution skills attach lower relative importance to training since they can presumably learn on their own. Not surprisingly, we found that business students did not attach great importance to leadership development programs, since the benefit from such programs may not be sufficiently evident for someone applying to entry-level positions. In contrast, educational support was found to significantly increase the attractiveness of a job profile for most of our sample, except for students who value work-life balance. Presumably, educational support is valued mainly by motivated and hardworking business students who do not mind demanding jobs. The end assessment is that retailers should consider offering educational support mainly to hardworking and motivated candidates who are willing to sacrifice personal time for their careers.

Employers are now realizing that recent college graduates, from generation Y, have different work values, expectations, preferences, and goals than preceding generations (personal interview, September 2006). The findings of this study thus offer important insights into developing effective recruiting strategies specifically targeted to this group of potential employees.

6. Limitations and future research directions We acknowledge several limitations to our study. First, our findings lack generalizability because our sample is comprised of business students from one university. Consequently, future studies that use multiple distinct samples can contribute to the understanding of college students' job choices. In addition, it will be interesting to identify the determinants of retail career choice for different groups of students, such as female students and MBA students. A second limitation stems from the use of conjoint analysis, which requires each participant to evaluate the attractiveness of all 27 job profiles. Conjoint analysis enables us to investigate the important trade-offs that factor into the decision process but could have led to careless and inconsistent judgments. This may explain why a lower utility is attached to the highest starting salary ($42,000) than to a medium starting salary ($36,000). Alternatively, students may be hesitant to choose a retail job with the highest starting salary ($42,000) because of unfamiliarity with such a job combination or sheer skepticism. They also may have discounted the starting salary, having processed both the starting and five-year salary simultaneously. Since starting salary is often believed to be the primary factor in job choice, subsequent studies can focus on testing the importance of starting salary with and without the five-year salary in order to isolate the importance of starting salary.

7. Conclusion Retailers realize that their organizational performance relies largely on talented frontline employees and have thus been

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focusing on recruiting talented college graduates and subsequently developing them into future leaders for their organization. However, since retailers often compete with other industries for the most talented employees, it is important for retailers to understand how potential applicants evaluate job opportunities in retailing compared to those in other industries, controlling for job attributes. Our study demonstrates the trade-offs that job candidates make, revealing the importance of attributes associated with career advancement. In addition, we found various links between job applicant characteristics and the relative importance attached to the different job attributes. This leads us to suggest that retailers should tailor their recruitment strategies according to differences in career expectations and core competencies.

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