M (MELANIE) SUNDAHL 1983148
University of Groningen Faculty of Economics and Business
Master Thesis 22/6/2015 Sabangplein 6a 9715CX Groningen +31 613890392 m.sundahl@student.rug.nl S1983148
INTRODUCTION ... 1
THEORY ... 3
The Relationship between Word-of-Mouth and Job Choice ... 3
The Influence of Perceived Pressure to conform on the relation between Word-of-Mouth and Job Choice ... 6
METHODOLOGY ... 9
Sample ... 9
Attributes and level selection ... 9
Choice design ... 11
Perceived pressure to conform ... 11
RESULTS ... 12
Sample ... 12
Main effects ... 12
Model fit ... 12
Estimates ... 15
Tie strength and Credibility ... 16
Moderating effect : perceived pressure to conform as moderator ... 18
Factor analysis ... 18
Model fit ... 19
Estimates ... 19
CONCLUSION ... 22
DISCUSSION... 23
Theoretical and Managerial Implications ... 23
Limitations and Future Directions... 25
REFERENCES ... 27
INTRODUCTION
Baby boomers are reaching the retirement age which leads to demographic shifts with organizational implications (Thompson & Aspinwell, 2009). College-educated workers need to fill in the labor gap of the baby boomers (Bernstein, 2002; Graham, 1997). Because the labor pool is reduced recruitment is a top priority (Cascio, 2003). There is a need to better understand how to attract new college graduates (Thompson et al. 2009). Therefore, over the last forty years employee recruitment research has increased substantially (Breaugh & Starke, 2000). Literature about job search and job choice have investigated how job seekers identify employment options, how they apply for them and how they determine to accept or decline a job offer (Highhouse & Hoffman, 2001). Most of these studies have studied the features of job offers that influence job seekers final choice (Bonnacio, Gauvin & Reeve, 2014). These studies portray job choice as a relatively rational and goal-directed behavior (Rynes, Bretz & Gerhart, 1991). However, recent research informs that job choice decisions may also be based on social influence and social comparisons (Kulkarni & Nithyanad, 2012). Informal word-of-mouth from strong and credible ties such as family and friends influence perceptions of the attractiveness of an organization and job choice decisions (Van Hoye & Lievens, 2007, 2009; Van Hoye and Saks, 2010). Higgins (2001) states that job seekers perceive the worth of the job choice decision higher when many similar others attest it, and because there are strong norms about choosing particular employers in certain social contexts.
word-of-mouth and their impact on job choice, they do not discuss differences between categories of word-of-mouth sources or differences within specific word-of-mouth channels (Van Hoye & Lievens, 2007; Zottoli & Wanous, 2000). Therefore, this study will contribute to research by studying different word-of-mouth channels and their effect on job choice. An organization cannot directly influence word-of-mouth, however they can influence it indirectly by for instance building relationships with the key influential and opinion leaders (Van Hoye & Lievens, 2007). For this the organization needs to understand the different influences of the channels. This study will also contribute by adding the normative influence part of social influence as a moderator. More precise this study will add perceived pressure to conform as a moderator. Because according to the theory of planned behavior in addition to people’s personal attitude toward job choice, the perceived pressure to conform in that behavior is an important determinant (Kulkarni & Nithyanand, 2012; Jaidi, Van Hooft & Arends, 2011).
In the present study we engage the following research questions: Are job choices influenced by word-of-mouth? Do different channels of word-of-mouth have different effects on job choice? If so, which word-of-mouth channel have the strongest effect on job choice? Does the perceived pressure to conform have any effect on the relation between different word-of-mouth channels and the job choice?
Job choice will be defined as a process that can be characterized as a series of decisions made by an applicant, starting with the evaluation of information obtained from various sources, following employment pursuance decisions with specific organizations (Gatewood, Gowan & Lautenschlager, 1993). Job choice thus includes choosing an organization to work for (Killduf, 1990). Job choice occurs in a context where attributes of each job alternative can be compared to one another (Hsee, Rottenstreich & Stutzer, 2012). This is because job choice is made in a context with a salient alternative. This means that we can either accept a job offering or stay in the status quo occupation (Comerford & Ubel, 2013). Initial decisions can be important in setting the job choice path and accepting a job offering (Boswell, Roehling, Lepine & Moynihan, 2003). Thus, understanding job choices of students early in the process is important for understanding their choices.
THEORY
The Relationship between Word-of-Mouth and Job Choice
In certain situations comprehensive data about organizations is missing to make job choice decisions (Irving, Coleman & Cooper, 1997). An example of a certain situation is when a company has just established and less information is known about the company. In these situations, applicants give rational thinking away to social influences and social comparisons (Higgins, 2001). Social influence can be divided in two sub terms. The first one is normative influence, which can be defined as conformance to the positive expectations of another (Deutsch & Gerard, 1955). The second one is informational influence, which can be defined as the acceptance of information obtained from other as evidence about reality (Deutsh & Gerard, 1955). Informational social influence can be seen as word-of-mouth communication from different ties (Van Hoye & Lievens, 2007, 2009). When applicants give rational thinking away to social influences they therefore act based on normative and informational influences regarding organizational attractiveness (Killduff, 1990; Kilduff, 1992; Deutsh & Gerard, 1955; Van Hoye & Lievens, 2007).
The different channels through which people receive information influence the initial attraction to an organization (Rynes & Cable, 2003; Zottoli & Wanous, 2000; Van Hoye & Lievens, 2009). Different channels of WOM can have different effects, because of the strength of the tie (Keeling, McGoldrick & Sadhu, 2013). Granovetter (1973) defines the tie strength between the recipient and the word-of-mouth source as: ‘a combination of the amount of time, the emotional intensity, the intimacy, and the reciprocal services which characterize the tie’. This means that when the tie strength is high this encourages the trust building and the job seeker will accept the information sooner (Keeling et al., 2013). Because information from strong ties is considered more useful and credible and therefore more influential than from a weak tie (Keeling et al., 2013). Source credibility is the main reason for the recipient to believe the message that is send (Fisher et al., 1979). Source credibility is build out of trust and expertise of the source (Fisher et al., 1979; Kawakami & Parry, 2013). So the higher the trust, expertise and liking of the source the higher the source credibility (Fisher et al., 1979; Kawakami & Parry, 2013). Previous study’s supports the fact that tie strength and source credibility are linked with effective knowledge transfer (Lenvin & Cross, 2004; Brown & Reingen, 1987). Therefore this study bases the WOM channels on the level of tie strength and the level of source credibility. More specific high tie strength is combined with high source credibility, this will result in word-of-mouth of family and friends. Low tie strength will be compared with high credibility which will result in word-of-mouth of an employee of a company. Whereas, high tie strength is also combined with low credibility which result in word-of-mouth of friends on Facebook. Lastly, low tie strength will be combined with low credibility which will result in word-of-mouth of an online review.
motivation of the speaker is to be helpful and accurate and more likely to be context specific (Keeling et al., 2013). Therefore assumed is that the source credibility of family and friends are high and this leads to the following hypothesis:
H1: Positive PWOM of family and friends have a positive influence on job choice
Word-of-mouth from employees are also seen as PWOM. Staff word-of-mouth means that staff or former employees communicate information and opinions about the organization (Keeling, McGoldrick & Sadhu, 2013). Employees are seen as a high expertise source and trustworthy, because of their experiences with the company and they do not have the motivation to convince them to work for the company (Keeling et al., 2013).Therefore assumed is that the source credibility is high. Assumed is that the tie strength is low, because the employees are not familiar to the job seeker. Compared to family and friends we assume that there will still exist a positive relationship, however weaker than for family and friends, because of the lower tie strength. This leads to the following hypothesis:
H2: Positive PWOM of employees have a positive influence on job choice, but lower than the impact of PWOM of family and friends have on job choice.
H3: Positive EWOM of friends on Facebook will have a positive influence on job choice, but lower than the impact of PWOM of family and friends have on job choice
Online reviews are also a form of electronic word of mouth, which are becoming increasingly popular worldwide (Filieri, 2014). People are reading reviews before making decisions (Filieri, 2014). However the readers of the review are assumed not to be familiar and therefore the tie strength is rather low. Because the writer is unknown the reader cannot say something about the credibility, therefore the source credibility is also rather low. Nga, Carson and Moore, (2013) found that a positive review does still have a positive impact on the readers reaction. Therefore this research does assume a positive relationship, however weaker then when the tie strength and source credibility were high and weaken than WOM of family and friends. This leads to the following hypothesis:
H4: Positive EWOM of online reviews will have a positive influence on job choice, but lower than the impact of PWOM of family and friends have on job choice.
Concluding from above assumed is that a high tie strength and a high credibility have a stronger effect than if one of both of these factors are low. There the fifth hypothesis is:
H5a: A high tie strength will have a stronger impact on job choice than if tie strength is low.
H5b: A high credibility level will have a stronger impact on job choice than if the credibility level is low.
The Influence of Perceived Pressure to conform on the relation between Word-of-Mouth and Job Choice
too much but to conform to those norms, values and cultural practices that are central to the WOM source (van Kerckem, van de Putte & Stevens, 2014). According to the social comparison theory of Festinger (1954), when people compare themselves with others people learn more about themselves. The theory suggest that people compare themselves with similar others and people are most influenced by social comparison when there is no objective basis of comparison (Festinger, 1954). Expected can be that students who compare themselves highly with people from a particular social system, the greater the identification with that group (Higgins, 2001). When a student has a high identification with a group this will lead to an organizational decision consistent with the prevailing norm (Higgins, 2001). Social commitment is a source of internalization (Higgins, 2001). When an individual changes his behavior, because this change is consistent with his values or because he believes it is moral (Kelman & Hamilton, 1989). Social commitment can be defined as the extent to which an individual feels committed to a decision he has made in the past (Higgins, 2011). People have a basic desire to be consistent in their decisions and therefore commit to these decisions (Cialdini, 1984).
Normative pressure to conform have been found to affect attitudes and behaviors more strongly (Neigbors, Dillard, Lewis, Bergstrom & Neil, 2006). Subjective norms or perceived social pressures are particularly strong predictors of job search behavior (Kulkarni et al., 2012). Concluded can be that when there is a high pressure to conform, the positive word of mouth is more likely to lead to a positive job choice. As mentioned before assumed is that a high tie strength and a high credibility have a stronger impact on job choice. Assumed is that when the tie strength and credibility are high that conformity has a stronger impact to conform. Therefore the sixth hypothesis are:
Figure 1: Conceptual model PWOM of employees vs PWOM of friends and family EWOM on Facebook vs PWOM of friends and family EWOM by online reviews vs PWOM of friends and family
Job Choice PWOM of Friends &
Family vs PWOM of Employees
PWOM of Friends & family vs EWOM on Facebook
METHODOLOGY
This study is interested in analyzing the preferences of students when choosing a job. Preference measurement shows what these students like and prefer and also reveals the underlying motives for the actions they took (Eggers & Sattler, 2011). The results can generate sustainable insights in the predicted behavior of students when choosing a job (Eggers & Sattler, 2011). Preference measurement uses a combination of attribute levels, an attribute bundle (Eggers & Sattler, 2011). A utility function translates the results of the preference measurement into the perceived preferences (Montgomery & Ramus, 2011). By using these results managers can use these to see which attribute has a big impact on the job choice. One of the most popular methods for doing preference measurement is the conjoint method (Guillot-Soulez & Soulez, 2014). Conjoint analysis is a method for analyzing a situation where a person has to deal with several options that differ in attribute levels (Guillot-Soulez & Soulez, 2014). Therefore in this research is chosen for the conjoint method. More precisely the choice-based conjoint (CBC) is chosen, because choices are an integral part of student’s everyday life and is therefore effective (Eggers & Sattler, 2011). With CBC a respondent repeatedly chooses their most preferred product from a set of alternatives (Eggers & Sattler, 2011). First the sample of the conjoint analysis will be discussed, second the determinant attributes and the levels of these attributes, third the conjoint analysis will be discussed and fourth the measure of perceived pressure to conform will be discussed.
Sample
The current study was conducted in the Netherlands. The study specially focused on students, because of the labor gap as mentioned in the introduction. However the online questionnaire is focused on students. The online questionnaire could not be controlled so that a none student cannot fill in the questionnaire. Out of the 226 respondents 60.4% is male and 39.6% is female. The average age of the respondents in total is 22.77 {SD=2.781}. Out of the 226 respondents 82.3% is student, 2.7% is just graduated, 14.6% is working and 4% is none of these options.
Attributes and level selection
added the attributes of salary, location, opportunities for promotion and job security as control variables. Table 1 shows the different attributes and their levels. Baum & Kabst, (2013) combined these attributes and more in his study. Baum & Kabst., (2013) concluded that all of these attributes were relevant. For these specific attributes was chosen, because they were assumed to be more relevant for students.
Salary is based on three levels: €36,000 a year, €43,000 a year and €50,000 a year. These levels concerns the payment for graduates, the lower, median and higher quartile.
Location is based on three levels: Groningen, Amsterdam and Utrecht. These levels were based on city’s attractiveness and geographical dispersion (Baum & Kabst, 2013).
Opportunities for promotion is based on two levels: promotion in 2 years and promotion in 5years. It is hard to delineate several categories, but to make it more specific 2 years and 5 years were chosen (Baum & Kabst, 2013).
Job security is based on two levels: ‘to a great extent’ and ‘to a minor degree’, because no job is absolutely safe or unsafe (Baum & Kabst, 2013). With job security is meant the probability of being laid of (Baum & Kabst, 2013). To make is more specific with a great extent chosen is for a three year contract and for a minor degree an one year contract is chosen as level. Attributes Levels Salary €36,000 a year €43,000 a year €50,000 a year Location Groningen Amsterdam Utrecht
Opportunities for promotion Promotion in 2 years
Promotion in 5 years
Job security Three year contract
One year contract
Choice design
The next step is concerned with the construction of a set of profiles. Although a full factorial design is always efficient, in this case it is not possible. A full factorial design would mean 48 choice sets, because there would be 144 different choice based on the attribute levels 4x3x3x2x2. When using more than 12 choice sets respondents need to be motivated (Eggers & Sattler, 2011). Therefore, a fractional factorial design was chosen with 12 choice sets, which means that each respondent answered a subset of stimuli. Dominated choice sets were excluded, because these do not give extra information. The no-choice option was also excluded, because the purpose of this study is not to measure price sensitivity. The Best-Worst conjoint was used, because this increases the information per choice set. This study also accounted for minimal overlap of choices. The conjoint based choice design was collected through the software of my.preferencelab. An example of a choice set is given in figure 2. The conjoint analysis is conducted by the use of LatenGold and SPSS. Next the conjoint model is validated by making use of the r2adjusted, the hitrate and the likelihood ratio test.
Figure 2. Choice set Perceived pressure to conform
RESULTS
Sample
After the data was collected, it was exported to SPSS to check the data for outliers and inconsistencies. Respondents needed to answer the questions, before they could move on to the next question. Therefore, no missing values were found. Respondents who did not finish the survey, were deleted from the dataset, because they were not useful for analyzing the relative choices.
Main effects
First an analysis of fit is discussed to test if the attributes should be nominal or numeric. To determine if the estimated model has a good fit, the estimated model is compared to the null model. Second, the main relationship utilities are discussed.
Model fit
Model with best choice
Part-worth Linear Salary as linear
LL -2219.563 -2251.9785 -2228.0663
Parameters 9 5 8
R2 0.2550 0.2441 0.2522
R2 adjusted 0.2520 0.2425 0.2495
Chi-square (Wald=1519.747), p<0.05 (Wald=1454.916), p<0.05 (Wald=1502.74), p<0.05
Hit rate 0.6412 0.6331 0.6416
Prediction error 0.3588 0.3669 0.3584
Table 2 Model fit with the best choice
Second the worst option models were analyzed by making use of the rejection dummy and compared to the null model as mentioned before. As can be seen in table 3, the same result can be concluded. The Part-worth model was chosen, because of its higher r2 adjusted, high significant chi-square, relative high hit rate and lower error rate. The chi-square between the linear model and the part-worth model was found significant (Wald=227.1416, p<0.05), the chi-square between the linear model and salary as linear was also significant (Wald=18.2868, p<0.05), and the chi-square between the part-worth model and the salary as linear model was also significant (Wald=34.5112, p<0.05). This means that the different models are significantly different from each other.
Model with best choice
Part-worth Linear Salary as linear
LL -2282.7843 -2290.8965 -2300.0399
Parameters 9 5 8
R2 0.2338 0.2311 0.2280
R2 adjusted 0.2308 0.2281 0.2250
Chi-square (Wald=1393.304), p<0.05 (Wald=1377.08), p<0.05 (Wald=1358.79), p<0.05
Hit rate 0.6268 0.6243 0.6250
Prediction error 0.3732 0.3757 0.3750
Table 3 Model fit with the worst choice
Moderator rejection Wald p-value Rejection dummy x WOM of
family and friends
0.0674 0.80
Rejection dummy x WOM of employee
0.1490 0.70
Rejection dummy x WOM of friends on Facebook
0.8105 0.37
Table 4 Worst choice moderating effects
The data of the best and worst choice together have a different null model than the best and worst choice separated, due to the doubled number of respondents. LL(0) is 452*12*ln(1.3)=-5958,8731. As can be seen in table 5, the r2 adjusted and the hit rate for the Part-Worth model were the highest. The chi-square for the salary as linear model was the highest. However the part-worth model was chosen as best model, because of the highest r2adjusted and hit rate. The chi-square between the linear model and the part-worth model was significant (Wald=143.962, p<0.05), the chi-square between the linear model and salary as linear was also significant (Wald=92.9144, p<0.05), and the chi-square between the part-worth model and the salary as linear model was also significant (Wald=51.0476, p<0.05). Which means that every model differs from each other.
Model with best choice
Part-worth Linear Salary as linear
LL -4514.4361 -4586.4171 -4539.9599
Parameters 9 5 8
R2 0.2424 0.2303 0.2381
R2 adjusted 0.2409 0.2288 0.2366
Chi-square (Wald=2888.874), p<0.05 (Wald=2744.912), p<0.05 (Wald=2937.83), p<0.05
Hit rate 0.6321 0.6205 0.6318
Prediction error 0.3679 0.3795 0.3682
Table 5 Model fit with best and worst choice combined
Estimates
Attributes β pvalue Probability Importance
WOM 3.2E-30 15.24%
Family and Friends 0.3040 32.5%
Employee 0.2621 31.17% Facebook -0.1800 20.03% Review -0.3861 16.30% salary 2.1E-142 36.74% € 36.000,00 -0.8883 11.17% € 43.000,00 0.1329 31.02% € 50.000,00 0.7554 57.81% location 4.1E-25 11.47% Groningen 0.3266 44.93% Amsterdam -0.1931 26.72% Utrecht -0.1335 28.36% promotion 1.7E-58 17.64% promotion in 5 years -0.3993 31.03% promotion in 2 years 0.3993 68.97% Security 6.9E-66 18.91%
A one year contract -0.4281 29.81%
A three year contract 0.4281 70.19%
Table 6 Part-worth model
Tie strength and Credibility
Credibility Mean Tie strength Mean Family and Friends 3.15 Family and Friends 3.16 Employee 2.65 Employee 2.29 Facebook 1.74 Facebook 1.8 Review 1.62 Review 1.04
Table 7 Credibility and tie strength
Attributes β pvalue WOM
Family and Friends -0.1954 0.0039
Employee -0.1359 Facebook -0.3184 Review 0.6498 salary 36000 -0.8946 5.10E-143 43000 0.1337 50000 0,7609 location Groningen 0.3298 2.20E-25 Amsterdam -0.1939 Utrecht -0.1358 promotion
promotion in 5 years -0.3999 2.30E-58
promotion in 2 years 0.3999
security
A one year contract -0.4279 1.80E-65
A three year contract 0.4279
Moderating effects
WOM of family and friends x Tie strength and credibility 0.0799 0.008 WOM of friends on Facebook x Tie strength and credibility 0.0401 0.12
WOM of review x Tie strength and credibility -0.12
WOM of employee of the company x Tie strength 0.0276 0.55
WOM of employee of the company x credibility 0.1274 0.0041
Table 8. Moderating effect of tie strength and credibility Moderating effect : perceived pressure to conform as moderator
Before the analysis of utility values is discussed, the model fit test is done to compare the moderating model to the part-worth best choice model and a factor analysis is discussed. Factor analysis
case the Cronbach’s alpha is 0.764 which is bigger than the base line and therefore the five variables were combined in one variable called pressure to conform.
Model fit
In table 9 the values of the part-worth best choice and the moderating model fit can be found. The r2 of the moderating model is slightly higher than for the part-worth model. This is due to the moderating model having more parameters. However the r2 adjusted of the moderating model is also slightly higher, which adjust for the amount of parameters. So the moderating has higher values on r2 and for the r2adjusted, but also for the hit-rate. To test if the models are significantly different from each other a chi-square was tested. The chi-square between the part-worth model and the moderating model was not signficiant (Wald=0.6866, p>0.05). So the part-worth model and the moderating model do not differ. The moderated model is used to answer hypothesis 6, however it can be concluded that the part-worth model is better in explaining variance since it is more parsimonious.
Part-worth best choice Moderating model
LL -2219.563 -2216.13
Parameters 9 12
R2 0.2550 0.2562
R2 adjusted 0.2520 0.2522
Chi-square (Wald=1519.747), p<0.05 (Wald=1526.608), p<0.05
Hit rate 0.6412 0.6423
Prediction error 0.3588 0.3577
Table 9. Model fit between part-worth and the moderating model
Estimates
Attributes β pvalue Probability Importance
WOM 0.013 9.36%
Family and Friends 0.3576 0.3456
Employee -0.0136 0.2384 Facebook 0.0381 0.2511 Review -0.3821 0.1649 salary 8.40E-143 39.05% € 36.000,00 -0.8922 0.1111 € 43.000,00 0.1336 0.3099 € 50.000,00 0.7586 0.5790 location 2.90E-25 12.33% Groningen 0.3282 0.4499 Amsterdam -0.1931 0.2671 Utrecht -0.1351 0.2830 promotion 1.50E-58 18.94% promotion in 5 years -0.4003 0.3099 promotion in 2 years 0.4003 0.6901 Security 4.40E-66
A one year contract -0.4293 0.2976
A three year contract 0.4293 0.7024
Moderator
Pressure x WOM Family and Friends -0.0253 0.67
Pressure x WOM Employee 0.1329 0.019
Pressure x WOM Facebook friends -0.1052 0.079
Presssure x Reviews -0.0024
CONCLUSION
DISCUSSION
Theoretical and Managerial Implications
Previous research has largely neglected the fact that job seekers can be influenced by social influences (Van Hoye & Lievens, 2007). More precisely research have not discussed differences between the channels of word-of-mouth and their influence on job choice. This study contributes to theory by research about the different channels of word-of-mouth and their different influence on job choice. Moreover, pressure to conform has been added as a moderator to furthermore explain the relationship between different word-of-mouth channels and job choice. The labor pool is being reduced, due to baby boomers reaching their retirement age (Cascio, 2003). Therefore, it is relevant to know how to attract new college graduates (Thompson et al., 2009).
This study found that positive PWOM of family and friends has a positive influence on job choice compared to the other WOM levels. Van Hoye and Lievens, 2005 also found that positive WOM would have positive influence on job attractiveness. That is because of the high tie strength and credibility of the WOM channel (Van Hoye and Lievens, 2007). Secondly this study found that positive PWOM of employees have a positive influence on job choice compared to the average level of WOM. Keeling et al., 2013 is indirectly supporting this finding, because employees of a company are seen as highly credible. And source credibility is seen as a main reason for recipients to believe the message from the WOM channel (Fisher et al., 1979). For this finding the findings of Van Hoye and Lievens, 2005 are also concerning; that positive WOM would have a positive influence on job attractiveness.
This study did not find any support for positive EWOM of friends on Facebook having a positive influence on job choice, but did find a significant effect of EWOM of friends on Facebook on job choice. There is found that EWOM of friends on Facebook do have an impact on job choice, but lower than for WOM of family and friends. This study found a negative influence of positive EWOM of friends on Facebook on job choice compared to WOM of family and friends. Overall it could not be said if it has a positive or negative impact on job choice, because the WOM levels are interval scaled instead on an absolute level. The negative relationship compared to PWOM can be due to respondents receiving the channel of friends of Facebook as low on credibility and low on tie strength. This can also be due to the respondents being students, but another group could define this channel as a higher tie strength as predicted.
levels are interval scaled, which means the negative influence is not on an absolute level. This study did found that EWOM of online reviews do have an significant impact on job choice, but lower than for WOM of family and friends. This can also be due to the low credibility and low tie strength, that respondents are not accepting the message send by the WOM channel. This finding is contradictory to the study of Carson and Moore, 2013, who found that positive reviews do have a positive impact on the readers’ reaction.
This study found that a high tie strength and a high credibility have a stronger impact on job choice than if one or both of these factors are low. This is line with the studies of Van Hoye and Lievens, 2007, 2009; Ilgen and Hoyer, 1979; Fisher et al., 1979 and Kawakami & Parry, 2013). The higher the tie strength the more familiar the WOM channel the bigger the positive impact on job choice (Van Hoye and Lievens, 2007, 2009; Ilgen and Hoyer, 1979). How more credible the source is received the sooner the message of the WOM channel is accepted and the bigger the positive impact on the job choice is (Fisher et al., 1979; Kawakami et al., 2013).
Lastly, this study found partial support for pressure to conform to influence the relationship between PWOM and job choice positively. This is partial, pressure to conform was only positively influencing the relationship between WOM of employees and job choice and not for WOM of family and friends on job choice. This can be due to students comparing themselves more to employees of the company then with the friends and family (Festinger, 1954; Higgins, 2001). Or due to students receiving the employees of the company as more credible than their family and therefore feel more pressure to conform. This study also found no support for pressure to conform having influence on the relationship between EWOM and job choice. This can be due to the low credibility and low tie strength of the WOM source and therefore respondents are not comparing themselves with the WOM source and don’t feel the pressure to conform. It can be concluded that pressure to conform not necessarily have to increase the relationship between WOM and job choice if the tie strength and credibility are high. But perhaps has more to do with students comparing themselves with certain WOM sources.
are most likely to accept the message from family and friends and second from employees of the company. Therefore, the organization should try to build relationships with the family and friends of these students to attract them to the company. First, organizations should build their recruitment activities around family and friends. So communicate the company and their offers to students on college grounds and stimulate them to tell their friends about the company and their offers. Or organizing family fairs or open house events to attract family of the employee (Van Hoye and Lievens, 2009). This last option will have a double word-of-mouth influence, namely the word-of-mouth of a family member, but also the word-of-mouth of an employee. Second, the organization should build a good relationship with their employees, so that they will have a positive word-of-mouth to other parties. For an employee to be able to tell something about the company and their vacancies, they need to have information. Third, organizations can use the pressure to conform to even strengthen the influence of word-of-mouth of an employee of the company on job choice. The company can do this by communicating their culture, like their norms and values. If an employee of the company tells a positive message to the students, they will feel more pressure to conform and so they will sooner accept the job offer.
Limitations and Future Directions
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