Choice-based conjoint analysis: The impact of
the employer brands on job choice
By
Yuan ZHAO
Choice-based conjoint analysis: The impact of the
employer brands on job choice
By: Yuan ZHAO 16-06-2016 MSc Marketing, Intelligence Master Thesis University of Groningen Faculty of Economics and Business
Department of Marketing 9700 AV, Groningen
Supervisors:
First: F. Eggers Second: J.E.M. van Nierop
Management Summary
As companies are looking for new method to attract high quality employees and seeking for a better brand performance, the concept, employee-based brand equity is introduced. Employee-based brand equity allows a brand to realize and maximize its performance from the perspective of employees. However, most research related employee-based brand equity only focus on the importance of employees, and how to satisfy employees. There is little research about what elements are influencing employees. Also, few researches discuss how different attributes within a brand have an effect on attracting potential employees. This report researched the preference of job seekers using an online survey by utilizing a choice-based conjoint analysis. For this research, we receive 233 valid responses.
The attributes that were investigated to influence job seekers’ preference are: Brand Name, Industry, Location, Salary, Brand Awareness, Brand Reputation and Brand Sustainability. Five models are built to test different effects of listed attributes. In the basic model where Brand Awareness, Brand Reputation and Brand Sustainability are excluded, brand effect are test. Only two brands have a significant effect on potential employees, Shell and Nuon. Industry and Location have an effect on job seekers but depends on the specific Industry or Location. Moreover, Salary has a significant and positive effect on potential employees. In the final model, brand awareness has little effect on job seekers when compared with brand reputation and brand sustainability. Hence, brand should pay more effort on establishing brand reputation rather than only improving their brand awareness.
Keywords: Employee-based Brand Equity, Choice-based Conjoint Analysis, Job
Preface
During my education on the bachelor’s degree, I became interested in the field of Marketing. After my internship at a market analysis company in China, the interest becomes stronger. In the September of 2017, I stared my Master Marketing Intelligence at the University of Groningen and now, I am at the end of the Master Marketing. This report was written as a master thesis to conclude my study for the whole year. The topic was decided based mostly on my personal interest in employer branding field. It is interesting to figure out what and how a brand is influence and attracting potential employees and high-quality job seekers. This is my first time to write a thesis fully in English which could be a big challenge for me, but I learned more about myself and my majors. Also, the ability I got from writing this thesis helped me have better plan in the future. Overall, I am glad to work with my team and share the result of my thesis. I would like to thank several people for helping me through the process.
First of all, I would like to thank Felix Eggers for helping with my thesis and providing me with feedbacks throughout the last few months. Moreover, I would like to thank my thesis group for helping me out when I need technical support and collecting data. Also, I would like to thank all people who took their time to fill in the survey. I could not have been able to finish this thesis without all of them.
Kind regards, Yuan ZHAO
Table of Content
Management Summary………3
Preface………...4
1 Introduction………...6
2 Literature Review………..……9
2.1 Customer-based brand equity vs. Employee-based brand equity………….…....9
2.1.1 Customer-based brand equity………..………….……..….…9
2.1.2 Employee-based brand equity………...….………10
2.2 Conceptual Framework for assessing work preference…………....………12
3 Research Design and Methodology………15
3.1 Methods and Measurement……….…………15
3.1.1 Experiment Design………..……….….………16
3.1.2 the Utility, Logit & MNL model……….……16
3.1.3 Choice Set Design………..…18
3.2 Attribute and Levels………..…….….…19
3.3 Measures……….………....22
3.4 Data Collection……….………..23
4 Result………24
4.1 Data Preparation and Sample……….…….24
4.2 Data Overview………..…..24
4.3 Findings………...…25
4.3.1 Brand Effects………..……...…25
4.3.2 Model Fit……….……….….25
4.3.3 Industry, Location and Salary Effect……….…………...26
4.3.4 Effects of Awareness, Reputation and Sustainability….…………..……..27
4.3.5 Final Model……….………..…….29
4.3.6 Main Findings………..……….…….30
4.3.7 Attributes Importance………..………..32
5 Discussion……….33
5.1 The Preferred Brand, Industry and Location………..33
5.2 Managerial Implication………..34
5.3 Future Research and Limitation……….36
1 Introduction
With increasing competitiveness in today’s marketplace, the development and efficient usage of brands become the most important management task for marketers and human resource managers alike (Wilden et al., 2006). In the employment context, brand equity affects potential employees whether they would like to apply for a position. Competition between firms to hire qualified staff has become increasingly important as the result of demographic changes, for example, aging of population: the population of people older than 60 years increases at a rate of about 3 percent per year, which growth faster than any other younger group (United Nations, 2017). In this case, the lack of supply in suitable workforce urges firms to find out a way to solve this problem, otherwise, the firm financial performance will be affected negatively (Wilden et al., 2006).
In fact, it has been discussed in marketing literature that the real competitive
advantage that a firm realizes in nowadays marketplace is through internal intangible resources, that is, brands and employees (Vargo and Lusch, 2004). A brand is
described in Kotler’s (1997) work as “essentially a seller’s promise to consistently deliver a specific set of features, benefits and services to the buyers” in order to differentiate from competitors. In most marketing literature, the brand is most commonly defined from the perspective of consumers not from other stakeholders’ perspective such as employees that are also affected by brand message and, in turn, influence the brand performance. Brand management has been considered as a significant priority for both management and academics for the reason that brand value is concerned as one of the most important intangible assets of a firm (Keller and Lehmann 2006). Through organizations’ ability to find out a source of a product, assign its responsibilities to production sector, provide high quality products, reduce customer search and switch cost and offer consumer a symbolic attachment (Keller 1998), brands are considered to provide both economical and symbolical advantages for customers. Moreover, the organizations’ capability comes basically from
employees. To maximize financial benefits, attracting, training and satisfying high quality employee or job seekers can be relatively important, in other words,
2005), it is discussed by Dell et al. (2001) that “The employer brand establishes the identity of the firm as an employer. It encompasses the firm’s values, systems,
policies, and behaviors toward the objective of attracting, motivating and retaining the firm’s current and potential employees”. The equity associated with the brand is affected by the extent to which the brand contributes to retaining and attracting employees. As increasing considerable research attention has been paid to employee recruitment and organization choice in recent years (Highhouse et al., 2003), brand equity research from an employee perspective is needed with regard to different aspect of brand equity, such as brand awareness, brand reputation and brand sustainability. Specially, this paper focuses not only on the brand effect on job seekers, but also other effects within the firm equity. Brand awareness has a strong effect on consumers (Dell et al., 2001) which might also influence job seekers.
Similarly, brand reputation which indicates more about the brand values by customers will also have an impact on job seeker. Furthermore, brand sustainability which gives potential employee a sense that the brand has a promising future could influence employees’ performance. Besides brand effects, this paper will give more details about how brand awareness, brand reputation and brand sustainability influence potential employee’s choice.
This paper contributes to theory and practice in following three aspects. First, for the conceptualization of employee-based brand equity, this paper compares several measures regarding brand equity. Customer-based brand equity (CBBC) is a special brand equity from the perspective of consumers and could be regarded as “the
differential effect that brand knowledge has on consumer response to the marketing of that brand” (Keller, 1998). The view proposed within the brand equity literature that customer-based brand equity is the prime metric of financial performance (Lassar et al. 1995) is believed to be narrow. Employees are the same important as customers for a company based on the concept of “employee-based brand equity” – which is defined as differential effect that brand knowledge has on employee response to the
choice on the view-of-point of employees. Hence, measuring and predicting job choice preference of job seekers and employees is necessary. Such an investment contributes to employee-based brand equity, which in turn benefits customer-based brand equity. Measuring and predicting the job preference accurately, therefore, provides a more comprehensive approach to brand equity.
Second, for empirical research model, choice-based conjoint analysis (CBC) is well used to analyze customer’s preference of products. In CBC, consumers choose their most preferred product from a set of alternatives repeatedly (Eggers and Sattler 2014). There has been a vast amount of research that adapt CBC to market, but there is little research that use CBC to analyze the preferences of employees on job choices, especially when it comes to isolate the effect of some specific attributes which might have a dominant impact on the preference of job seekers when searching for a
position. When measuring the brand effects of employer, there are other confounding elements included, such as the location of the employer or the industry, which are often strongly correlated with the brand. This paper aims at isolating those effect from measuring and predicting job choice. In order to measure the brand effect, we need to separate the brand effect from other attributes. In this paper, two conjoint analysis experiments are applied, one with brand name and another without brands but only with industry and location.
Third, this paper provides a better insight of job seekers to company managers, helping firm managers have a better understanding of what employee want. For example, when brand reputation is considered, brand awareness has little influence on job seekers, which means that brand managers should focus more on brand reputation rather than brand awareness. Moreover, sustainability is also an important attribute which impacts potential employees’ choice. In the case, managers could create more suitable positions for employees, making the most use of human resources and financial resources. The practitioner literature suggests a “value chain” where
view of how to associate the firm with employees to generate greater profits
The remainder of this paper is structured as follows. Firstly, the theoretical framework introduce why employee-based brand equity is important when improving firm
performance. This framework explains why it is feasible to use CBC to measure and predict job choices based on previous studies. In the following chapter, there will be a brief summary of brand effects. More emphasis about how brand awareness, brand reputation and brand sustainability influence job seeker’s choice are stress. In the end of the paper, some managerial implication and future research area are discussed.
2 Literature Review
2.1 Customer-based brand equity vs. Employee-based brand equity 2.1.1 Customer-based brand equity
affective commitment is mediated by loyalty.
While many marketing literatures focuses on customer-based brand equity which provides firm a direct insight of its targeted group or segment, Wilden et al. (2010) suggested that customers are only connected to the brand by employees, and relatively little literature has examined the role of brand to attract employees.
2.1.2 Employee-based brand equity
Applying the same logit as customer-based brand equity to employee-based brand equity, it could be assumed that both brand awareness and brand reputation have significant effect on employee’s job choice. The more an employee is aware of a brand, the more s/he is likely to work for the brand. However, employee is different from customer in following three aspects. First, customer consumes products where employee provides services. Investment in customer resource management (CRM) has a directly impact on financial output, where investment in improving employee satisfaction has no direct consequence of finance. Second, rather than paying money, employee is paid. In this case, it is easy to measure the willingness-to-pay of consumer, whereas it is hard to predict the willingness-to-sacrifice salary of employee.
customer satisfaction and customer loyalty. Consistent with the previous theories, investment in firm’s brand is considered to be a useful and efficient marketing strategy among competitors (Kim, Kim and An 2003; Pappu, Quester and Cooksey 2005). The job market has a characteristic of information asymmetries, but brands can serve to overcome these information asymmetries and provide some references for it. Without taking part in a job and experiencing work conditions directly beforehand, a potential job seeker could hardly fully assess the situation of an expected employer with certainty. It is the same when the situation comes to employers (Spence, 1974). While employment contracts and long-term implications is important for both employers and employees (Wilden et al., 2010), both of them are forced to find ways to diminish the effect of information asymmetries and balance out the problem of adverse selection. From the potential employee’s perspective, information asymmetry comes from the underlying characteristics of the prospective firm, for example, work environment, career development (Martain, 2005). It is beneficial for a potential employee to figure out as much as they could about a prospective firm because of the existence of information asymmetric risks to both parties. And from the employer’s perspective, it is in the best interests of an employer to deliver their competences, resources and capabilities to the employment market. Potential employees’ understanding of a prospective employer is influenced by the capabilities and characteristics internalized in the firm’s brand. A prospective employer will play a misleading role when the potential employees have insufficient, inconsistent, or incorrect information about the prospective firm and its brands, which make potential employees have a high perceived risk associated with working in the firm or organization, and consequently, job seekers would consider an alternative employer for which they have less perceived risk (Tavassoli et al., 2014).
and retaining the firm’s current and potential employees”, stressing that employer’s brand have an impact on both existing employer and potential employer. This suggests that a firm or employer can reduce uncertainties and risks by delivering more details of an occupation to job seekers. The extent to which an attribute consisted in an occupation account for retaining and attracting employees is associated with employee-based brand equity. In terms of employee context, brand equity could be considered as “the impact of brand reputation on potential and existing employees in conjunction with the firm” (Backhaus et al, 2004).
2.2 Conceptual framework for assessing work preference
Based on employee-based brand equity, we present a framework in which a work occupation consists of various underlying attributes, and in turn, these attributes have different influences on the preference of employees. As shown in figure 1, factors that affect job choice preference can be divided into two parts, employer and salary. There are three underlying dimensions within employer factors, namely, brand, industry, and location. In conjoint analysis experiment, these three factors are considered as different attribute.
Figure 1 Structure and Hypotheses
familiar than those they are less aware of. However, there are little research about how brand awareness influences employee’s job seeking behavior. Applying the same logic as consumer behavior, we can assume that potential employee is more likely to be attracted by a position provided by a well-known brand (H1 a).
H1 a Brand awareness has a significant and positive effect on job choice
Brand reputation associations are central building elements in customer-based brand equity frameworks (Aaker, 1991; Keller, 1993; Park and Srinivasan, 1994). Different measures of customer-based brand equity have been proposed in the literature. Kamakura and Russell (1993) indicated that brand reputation can be served as intangible components of firm assert which can have a positive and significant impact on consumers’ behavior. In consideration of the relationship between employee and the firm, the emphasis is placed on the how brand reputation influence employee’s behavior. For example, customers tend to buy a product from a famous brand which have a good reputation not only because of the high quality but also because of the added-value delivered by the brand’s name. Similarly, it could be assumed that potential employees are more likely and more willing to work in a reputed company or brand.
H1 b Brand reputation has a significant and positive effect on job choice
both privately and publicly (Tavassoli et al., 2014). For example, Gucci can influence both consumer’s perception and the attitudes toward the consumer from others. People tend to seek jobs at firms that will give them guarantee about a security job in the future. According to Jain and Bhatt (2015), being associated with a company that has a high brand value gives employees a sense of satisfaction which constitutes several factors. Firstly, it gives them an assurance of the sustainability of the company which means they are assured of a long-term employment. Secondly, it involves a sense of achievement of having secured a job with a prestigious company that has high brand recognition among consumers. Also, as postulated by Baker et al. (2014), employees of such companies, especially those in the front line sales and service find it easy to deal with customers and achieve their sales targets due to an easy to recognize brand, which means they can achieve higher incentives, promotions, bonuses, and other benefits due to efficient performance, Additionally, working with a recognized brand entails working with colleagues who are highly experienced and qualified as only such persons are hired by top brands, which means finding good mentors and other people who can help them with their career.
H1 c Brand sustainability has a significant and positive effect on job choice
and, jobs with higher salary will be more attractive than those with lower salary.
H2 Different industries have different effects on potential employees’ choice. H3 Different location have different effects on job seeker’s preference. H4 Salary has a significant and positive effect on employee’s job choice.
3 Research Design and Methodology
This section discusses the framework designed to conduct the research. This includes the explanation of the choice of analysis for the research, data collection method and procedure to measure the data.
3.1 Methods and measurement
As discussed earlier, the competitiveness among the employers to allure the brightest of the limited skilled human resource is growing. Brand worth is one vital aspect attracting employees to a particular company but, that is not all (Seijts and Crim, 2006; Erickson and Gratton, 2007). Multiple attributes impact of the decisions of the job seekers about their preferred company to join. In light of above-stated facts, it is becoming necessary for managers and the human resource department of firms to understand which attribute with what degree influences the decision of job seekers. In order to understand the same, the conjoint analysis technique is suitable for the current research.
Both ranking and rate-based deal with attributes which are to be ranked or rated by respondents. The difficulties lie in the vagueness and restricted vision to infer relevant insights because of the differentiations between rank levels, for example, 5 and 6 are difficult to be interpreted. On the other hand, the choice-based conjoint analysis model is an advanced technique widely used in research field to understand how people make decisions when they pick one product or service among various available alternatives. The technique helps researchers to identify the underlying rules that people have in making trade-offs. The respondents unlike those in rating based and rank based approaches, are not asked to cover the complete set of choices and rank them. Instead of such mechanism which can result in a tiresome experience for the respondents, choice-based conjoint asks participants only to choose the most preferred option out of the shown sets of combinations. This technique also provides the option to include a void of null choice, making the survey more realistic to approach. Also, the model works suitably if the significant attributes are less in number (Gustafsson, Herrmann and Huber, 2013).
3.1.1 Experiment Design
Since, the given research aims basically to understand the choices made by the job seekers and resigning behind it. Hence, the concept of choice-based conjoint analysis technique is suitable here to decode job seekers’ decisions making behavior. Also, the choice-based conjoint analysis method works well with the limited number of attributes considered significant in understanding the objective of the experiment.
The experiment design of the research is based on the random utility theory. The theory is built on the hypothesis stating that every decision maker or an individual is rational in his or her approach of making decision and hence, picks that particular choice from a given set of available options, which ensures maximised relative utility (Cascetta, 2009).
3.1.2 the Utility, Logit & MNL model
the options with the highest net benefit. In order to measure the utility, the random utility theory would be adopted, and the essence of this model is still the rational decision making by consumers. As is indicated by Hariharan et al (2018), there are previous researches which believe that the preferences of the customers and therefore the customers’ utility functions can be expressed as a function of attributes of innovation. According to Heinberg et al (2018), this is agreed upon by many other scholars and it assumes that the utility generated for different attributes are latent constructs which are demonstrated by a systematic component and the error term. The error term would incorporate all the aspects that affect the model and they are not accounted for by the systematic components. Therefore, this model can be demonstrated as:
𝑈 = 𝑉 + 𝜀
In this case U is utility and V is the systematic term. The V is the choice based conjoint vector and it associates the preference estimate with the attributes of different products and services.
Furthermore, the summation of the preference estimates of different attributes is determined. In this case the model is demonstrated here:
𝑈' = ( 𝛽* * *+,
𝑋*' + 𝜀'
In this case X is the attribute of products and services. Beta is the preference estimate for the respective attribute.
Model 3: Model 1 + extend with Brand Reputation Model 4: Model 1 + extend with Brand Sustainability
Model 5: Model 1 + extend with Awareness, Reputation, brand Sustainability
The preferences of the customers would be estimated using the multinomial logit model (MNL). In this model, the preferences of customers are translated into probabilities. MNL also assumes that the error is independent. The probability that an alternative choice (a) is chosen from J different options is demonstrated in the equation below:
𝑝(𝑎|𝐽) = exp (𝑈*') ∑''+,exp (𝑈*')
3.1.3 Choice Set Design
Figure 2 Experiment Design 1 - Choice Set Example
Figure 3 Experiment Design 2 - Choice Set Example
3.2 Attributes and Levels
of level across all attributes must be even. An uneven distribution of level to attributes gives rise to the Number of level effect which needs to be controlled while using Choice-based Conjoint Analysis technique. For better results, each attribute so defined needs to be distinctly chosen avoiding any overlapping. To keep the possible standard error to be as low as possible, the number of levels are suggested to be low (Wiley, Raghavarao and Chitturi, 2010; Eggers and Sattler, 2011; Gustafsson, Herrmann and Huber, 2013).
Keeping the above-mentioned aspects, the attributes and levels are designed so for the current research. Brand, Industry, Location are major related aspects about a brand of the company distributed across three level making matrix. These attributes selected are considered as the most vital one in understanding the impact of the brand on a job seeker. This will include not just the brand awareness as an attribute but, also other related brand aspects like the connection and association that a person extends towards the values and sustainability of a brand.
In order to first identify how any brand can impact the choice of a job seeker while making the decision about joining any particular company, it is important to understand the aspects related to a brand which play vital roles in extending the impact of the brand name over the decision-making and behaviour. In this regard, for a comparative study of the effect of the brand name on decision making of a job seeker, attributes like the industry association, and other dominant factors like location and salary are included along with aspects of brand worth.
Below is the discussion regarding the choice of attributes for the current context of work and its relevance with respect to it.
Brand Awareness
considered a brand of great worth and status. (Wilden, Gudergan, and Lings, 2010). The survey questions so designed aim at understanding these important aspects from the perception of the respondents. The purpose is to analyze how the personal association with the brand, perception regarding the reputation and sustainability of the company impact the decisions of job seekers. With regard to other attributes, industries and regions, three brands for each industry are proposed. Furthermore, those 11 brands and a virtual brand (12 brands in total) are balanced in four regions. The fake brand is set as a control variable that could give a clear comparison with other brands regarding brand awareness. Below are the details of the brands considered in the research.
Table 1 Items of Choice-based Conjoint Analysis
Brand Industry Location
ASN Bank Banking and Financial Services
The Hague
ING Amsterdam
Rabobank Utrecht
Douwe Egberts Consumer Goods Utrecht
Heineken Amsterdam Unilever Rotterdam Electrolight (control) Electronics Utrecht KPN The Hague TomTom Amsterdam
Eneco Energy Rotterdam
NUON Amsterdam
Royal Dutch Shell The Hague
Industry
combined with the attributes, Location, is adapted to isolate the effect of brand on job seekers. As mentioned above, brand awareness would have a significant effect on job preferences which might result in a bias outcome or parameter of other attributes, making it difficult to analyze the underlying effect of different attributes.
Location
Just like industries, cities are also perceived in regard to the type of lifestyle they would be offering. The structure of cities and expected market condition impact the degree of the acceptance of a job by a job seeker. The size of the city, close vicinity of it and the region it belongs are some aspects related to a selection of city being most dominant ones (Sato, 2004). For the research Location considered are of four different cities with in the Netherlands, Amsterdam, Rotterdam, Utrecht and the Hague.
Salary
Income and incentives are the things which highly drive people and important factor regarding job satisfaction. It is an inseparable and sometimes the most important aspect of consideration in making a decision while job seeking process (Parvin and Kabir, 2011; Sharma and Bajpai, 2011). For the research the salary brackets are considered in four steps facilitating in the range of + 15%, +7.5% to -7.5%, -15% as compared to the expected salary.
3.3 Measures
Table 2 Hypothesis and Survey Question
Attribute Hypothesis Survey question
Awareness H1a: brand awareness
Brand awareness has a significant and positive effect on job choice
Please select all brands that you are familiar with, for example, you have previously seen or heard of them. Reputation H1b: brand reputation
Brand reputation has a significant and positive effect on job choice
Which of the following brands would you describe as having a good reputation?
Sustainability H1c: brand sustainability
Brand sustainability has a significant and positive effect on job choice
As shown in the table, in order to measure the specific effects of brand awareness, brand reputation, and brand sustainability. Three extra survey questions are mentioned in the follow-up questionnaire, as shown in figure 4. The question for awareness is “Please select all brands that you are familiar with, for example, you have previously seen or heard of them”, the question for reputation is “Which of the following brands would you describe as having a good reputation?”, and the question for sustainability is that “Which of the following brands would you describe as having a promising future?” All the 12 brands are listed below these three question, and respondents could select as much as they want as assumed that they answer the questions earnestly. The result will be marked as “1” when the brand is selected by participants. Otherwise, “0” is recorded in the spreadsheet.
Figure 4 Example of Survey Question
3.4 Data collection
given set of choices available for each type of question. There are 6 choice sets for experiment 1 where brand name is not included, and there are 9 choice sets for experiment 2 which includes brand names. For both experiments, each choice set has 4 alternatives, and 3 alternatives are job related and one none-option alternative. Participants could select none-option choice when they dislike none of the three alternatives in one choice set. The questions were framed relating it to the brand value, its perceived impression and other associated aspects. Data from the sample across various profession ranging from different demographics were collected.
4 Result
4.1 Data Preparation and Sample
According to Hazee et al (2017), it is important to realize that the sample size is very important for the statistical analysis because the sample size has to be sufficient to make sure that the results are statistically significant. If the sample size is too small, it is difficult for the study to yield results that are significant. This is especially the case for conjoint analysis. Specifically, according to Hazee et al (2017), the sample size has to be at least 50 in order to generate good insights about the preferences of the customers. If the sample size is lower than 50, the consequences can be negative. Therefore, the optimal case should have more than 150 people in the sample. In this case, there are 241 respondents in the study and this means that the results of the study would be significant. After the cleaning of the data, there are still 233 respondents that are included in the analysis.
4.2 Data Overview
also be deleted. Therefore, the cleaning would normalize the data and would eliminate data which are obvious wrong. After cleaning up, the figure for salary indicates that the mean salary is 39508 euro per year, the min salary is 8000, and the max salary is 130,000 euro per year. After the cleaning, it is found out that the average age of participant is 27.65. The min age of participants is 18, and the max age of participants is 70. According to the result, female is marked as 0 where male is marked as 1, and the Gender variable has a mean of 0.5193, which means that 51.93% of participants are male and 48.07% of them are female. Respondents are balanced between men and women.
4.3 Findings 4.3.1 Brand effect
With regard to brand effect, some changes have been made to model 1, as shown below. Full dataset: 1) Applying model 1 by using the full dataset; 2) Variables are brands, industry, location and salary.
𝑈 = 𝛽89:;<𝐵 + 𝛽>;<?@A9B𝐼 + 𝛽DEF:A*E;𝐿 + 𝛽H:I:9B𝑆 + 𝜀
Conjoint part 1: 1) Applying model 1 by using data from choice-based conjoint analysis part 1; 2) Variables are industry, location and salary.
𝑈 = 𝛽>;<?@A9B𝐼 + 𝛽DEF:A*E;𝐿 + 𝛽H:I:9B𝑆 + 𝜀
Conjoint part 2: 1) Applying model 1 by using data from choice-based conjoint analysis part 2; 2) Variables are only brands and salary.
𝑈 = 𝛽89:;<𝐵 + 𝛽H:I:9B𝑆 + 𝜀
Conjoint part 2 without brand: 1) Applying model 1 by using data from choice-based conjoint analysis part 2; 2) Variables are industry, location and salary.
𝑈 = 𝛽>;<?@A9B𝐼 + 𝛽DEF:A*E;𝐿 + 𝛽H:I:9B𝑆 + 𝜀
Table 3 Model Fit
LL R2 Radj2
Full Dataset -4214.7 0.7669 0.7659
Conjoint part 1 -1785.2 0.7667 0.7686
Conjoint part 2 -2418.5 0.7660 0.7647
Conjoint part 2 without brand -2427.7 0.7651 0.7643 Based on the results list above, there is little differences on parameters when different datasets are used. Also, Chisq is performed, showing that all the four methods are significant better than null model. For the reason that model 1 that uses full dataset has a higher R2 and has a wide range of variables, model 1 with full dataset are applied in
the following test.
4.3.3 Industry, Location and Salary Effects
Table 4 Result of Model 1
4.3.4 Effects of awareness, reputation and sustainability
Full dataset Conjoint Part 1 Conjoint Part 2
Variables are added individually in different models, and interaction effects are not considered. Moreover, the following table shows the frequency that a certain brand was connected to one of the four variables. According to survey questions, the result will be marked as 1 when participant choose the brand, otherwise, 0. While ING, Unilever, Heineken and Shell have higher awareness than other brands, EL receives only 6.01% brand awareness which is in line with the expectation that EL is a fake brand and it should have the lowest brand awareness.
Table 5 Demographic Results of Other Factors
Brand Awareness Reputation Sustainability
Rabobank 73.39% 33.05% 30.90% ING 79.04% 36.05% 42.06% ABN 53.22% 21.03% 22.75% Unilever 86.27% 52.79% 57.08% DE 65.24% 39.91% 30.04% Heineken 81.55% 54.94% 51.07% KPN 70.82% 28.33% 30.47% TomTom 66.09% 29.18% 18.45% EL 6.01% 4.72% 12.45% Eneco 58.37% 15.88% 22.75% Nuon 56.22% 12.02% 18.88% Shell 87.98% 25.32% 32.19%
As mentioned in previous chapter, four models based on model 1 are extended with above factors separately. According to the results of other four models, it is found that the effect of awareness is significant and positive (0.40). Therefore, the result supports the hypothesis H1a in the literature review that brand awareness can increase brands’ attraction to potential employees. As is indicated by Lieven et al (2016), the results are understandable because the brand awareness is known to significantly affect decision making. During the process of data collection and comparison, higher awareness allows job seekers to generate more detailed information for the specific company so that the job seekers are more likely to be in favor of the brands.
the reputation is believed to be a very important factor affecting the market. All job seekers are willing to be identified with companies that have good reputation. If the reputation is bad, it is usually difficult for companies to find the right candidates. Therefore, most of the companies are focusing on enhancing their reputation.
Similarly, the result of sustainability also indicates a significant and positive coefficient (0.52), which means that the attraction of brand to potential employees would be stronger when the brand has a more promising future. As is indicated by Wilke et al (1999), the sustainability demonstrates the future prospect of the company and it is obvious that employees are willing to work for companies that have bright future.
4.3.5 Final model
In order to get a better insight of data and have a model that can explain the underlying needs of job seekers, an aggregated model is built, in the model, every variable list above is included, namely, brand name, industry, location, In this case different factors are incorporated into the model and the result of model show that the effect of awareness become insignificant and sustainability becomes less significant while reputation still have a highly significant result when combine every attribute in one model. The alternative explanation for this result would be that some attributes are taking variance of other attributes when being analyzed separately. Then a correlation check is performed. The result is shown in the table below.
Table 6 Correlation Results
Awareness Reputation Sustainability
Awareness 1.000 0.538 0.526
Reputation 0.538 1.000 0.576
Sustainability 0.526 0.576 1.000
this case, reputation will have a significant parameter in the outcome of the aggregated model. Furthermore, reputation would explain some variances that other variables could not explain.
4.3.6 Main Findings
Table 7 Result of Final Model
More and more talents are willing to work for companies that have good reputation. In the final model, all the brand parameters except Nuon and shell have insignificant effect on job choice. In the meantime, parameters of industry have a significant effect on job
preference, indicating that company will waste time and money if they focus only on improving themselves. It is a better to make the industry attractive. As is indicated by Rozsnyai (2016), this is possibly explained by the fact that when job seekers consider which company they want to work in, they normally start from the industry and therefore the attractiveness of the industry directly affects the future decision making about the individual companies. The attractive industry brings more opportunities for individual companies. On the other hand, if the industry is not attractive it is still hard for good companies in the industry to attract talents.
4.3.7 Attributes Importance
The following table indicates the importance of different variables contained in the research.
Table 8 Attribute Importance
Attributes Coefficient Difference Importance
Brand Max: 0.297 0.619 8.4% Min: -0.322 Industry Max: 0.360 0.708 9.6% Min: -0.348 Location Max: 0.151 0.309 4.2% Min: -0.158 Salary 4.965 4.965 67.4% Awareness 0.124 (insig.) - 0 Reputation 0.498 0.498 6.8% Sustainability 0.257 0.257 3.6%
5 Discussion
5.1 The Preferred Brand, Industry and Location
It is found out that the study successfully supports the hypothesis and the location and industry are more important than brand alone. As is indicated by Louviere et al (1983), the brand value is usually believed to be critical because the brand value affects the decision making by affecting the information collection and comparison. Therefore, the job seekers tend to work for employers with better brand name. However, the study identifies that the industry and location are more important factors. According to Kim et al (2016), most of the students determine their future lines of work before they enter college and they would choose their majors at college. This means that whether the industry is attractive or not is more important than the attractiveness of the individual brand. The individual brands are only chosen after the employees believe the specific industries are attractive as they make the decision before for the industry. Furthermore, it is also important to realize that the location is a very important factor. As is indicated by Jeansson (2017), most of the job seekers prefer areas that are close to where they live, and the convenience is a very important consideration. The convenient location allows workers to save significant amount of time on the road and therefore the convenient locations are selected.
incremental improvement (Hess, 2014), which means that electronics industry has a low degree of technological turbulence.
The table below shows the hypotheses and results of this paper:
Table 9 Supported Hypotheses
Does brand affect job seekers? Depends on brands
H2: Does industry affect job seekers? Depends on industries H3: Does location affect job seekers? Depends on Locations
H4: Does salary affect job seekers? Yes
H1 a: Does brand awareness affect job seekers? No H1 b: Does brand reputation affect job seekers? Yes H1 c: Does brand sustainability affect job seekers? Yes
5.2 Managerial Implication
There are many important implications that are generated from the study:
Firstly, for the brands which have high brand value and they are active in the market, it is important that they further enhance the brand value in order to attract candidates. According to Henard et al (2010), it is important to realize that most of the companies are not able to easily shift industries so that it is still critical for them to gain competitive advantages against other competitors in the industry. Better brand allows them to focus on the employees that would choose the specific industry and they can have more talented workers. This means that if companies allocate more resources to construct better brands it is easier for them to attract employees in the future and they are able to enhance their human capital.
reducing the negative impacts that are generated because of the poor reputation, most of the talented employees are not willing to join the organizations.
Thirdly, for the brands that are not significant and do not have good brand value and if the industries are highly attractive, they should focus less on brand value but on the overall attractiveness of the industry overall. This is supported by the data from the study that the attractiveness of the industry is more important than the brands. If the attractiveness of the whole industry is enhanced, the recruitment process for individual companies will become more efficient. The attractiveness of industry affects the areas of study that people have initially. Therefore, if the industry is not attractive, most of the people would join other industries and ultimately, they would not choose the companies in this unattractive industry even if the brand value is high. This indicates the fact that the attractiveness of the industry can be more important than that of the company.
Fourthly, for companies in industries that are not attractive, it is critical for them to improve their attractiveness to workers based on other factors such as salaries and location. It is found out in the study that the salaries are instrumental for the motivation of employees and it is more likely for talented people to want to work for higher compensation. Furthermore, the location is also important as it affects the willingness of the employees to work hard as well. For companies that cannot relocate, and the locations are not attractive, it would be important for the companies to increase the compensation to employees, such as enhancing salaries or perk levels in order to attract employees. The better financial rewards would stimulate the employees to select the employers because in this case it would allow the employees to have higher motivation at work. The financial rewards would attract employees to join and it will pay off when the human capital is enhanced.
employees would believe that they have a bright future in the organization, so that they would be more willing to work in the organization.
5.3 Future Research and Limitation
This paper aims to isolate the brand effect from industry and location to figure out the preference of job seekers when hunting for a job. While the hypotheses list above are supported, there are still some limitation existing.
Firstly, the study focuses on the brands that are located in Netherland and the answers are provided by people from multiple different countries, so that the awareness of these brands would be affected. It is possible that there are certain brands which are not commonly known by foreign people. Fortunately, this impact is limited because the awareness is high based on the study.
Secondly, another limitation is that the study focuses on factors such as awareness, reputation, and sustainability but it does not focus on other factors such as age, sex, and other benefits which can affect the preferences for jobs. As is indicated by Aggarwal et al (2007), it is found out that the features of employees and their backgrounds normally affect the preferences of jobs. Employees are not only affected by the factors of employers but also the features of themselves. In the future the study could focus on these factors involved.
References
Aaker D.A. (1991). Managing Brand Equity. New York: Free Press.
Aggarwal P., McGill A.L. (2007). Is that car smiling at me? Schema congruity as a basis for evaluating anthropomorphized products. Journal of consumer research, 34(4), 468-479.
Ambler T., Bhattacharya C.B., Edell J., Keller K.L., Lemon K.N. and Mittal V. (2002). Relating brand and customer perspectives on marketing management. Journal of
Service Research, Vol. 5 No.1, pp. 13-25.
Atilagan E., Aksoy S. and Akinci S. (2005). Determinants of the brand equity: a verification approach in the beverage industry in Turkey. Marketing Intelligence &
Planning, Vol. 23 Nos 2/3, pp. 237-48.
Backhaus K. & Tikoo S. (2004). Conceptualizing and researching employer branding. Career Development International, 9(4/5), 501–517.
Baker T. L., Rapp A., Meyer T. & Mullins R. (2014). The role of brand communications on front line service employee beliefs, behaviors, and performance. Journal of the Academy of Marketing Science, 42(6), 642-657.
Boswell W.R., Roehling M.V., LePine M.A. and Moynihan L.M. (2003). Individual job-choice decisions and the impact of job attributes and recruitment practices: A longitudinal field study. Human resource management, 42(1),.23-37.
Cable D.M. and Graham M.E. (2000). The determinants of job seekers' reputation perceptions. Journal of Organizational Behavior, 929-947.
Cascetta E. (2009). Random utility theory. In Transportation systems analysis. Springer, Boston, MA. 89-167.
Datta H., Kusum L., Ailawadi and Harald J. van Heerde. (2017). How well does consumer-based brand equity align with sales-based brand equity and marketing mix response? Journal of Marketing, 2017, Vol.81(3), pp.1-2
Dawar N. and Parker P. (1994). Marketing universals: Consumers’ use of brand name, price, physical appearance, and retail reputation as signals of product quality. Journal of Marketing, 58(4), 81–95.
Eggers F., and Sattler H. (2011). Preference Measurement with Conjoint Analysis: Overview of State- of-the-art Approaches and Recent Developments. GfK Marketing
Intelligence Review, 3(1), 36–47.
Eggers F., Sattler H., Teichert T. and Volckner F. (2018). Conjoint analysis and discrete choice experiments.
Erickson T. J. and Gratton L. (2007). What it means to work here. Harvard Business
Review, 85(3), 104.
Eyssel F. and Kuchenbrandt D. (2012). Social categorization of social robots: Anthropomorphism as a function of robot group membership. The British Journal of Social Psychology, 51(4), 724-31.
Noseleit F. (2018). Renewable energy innovations and sustainability transition: how relevant are spatial spillovers? Journal of Regional Science. 2018;58(1):259–275. Gustafsson A., Herrmann A., and Huber F. (Eds.). (2013). Conjoint measurement:
Methods and applications. Springer Science & Business Media.
Hariharan V.G., Desai K.K., Talukdar D. and Inman J.J. (2018). Shopper marketing moderators of the brand equity – behavioral loyalty relationship, Journal of Business Research, April 2018, Vol.85, pp.91-104.
Hazee S., Vaerenbergh Y.V. and Armirotto V. (2017). Co-creating service recovery after service failure: The role of brand equity, Journal of Business Research, May 2017, Vol.74, pp.101-109.
Heinberg M., Ozkaya H.E. and Taube M. (2018). Do corporate image and reputation drive brand equity in India and China? - Similarities and differences, Journal of Business Research, May 2018, Vol.86, pp.259-268.
Henard D. and Dacin P.A. (2010). Reputation for product innovation: Its impact on consumers. Journal of Product Innovation Management, 27, 321-335.
Putting the service profit chain to work. Harvard Business Review.
Highhouse S., Lievens F., Sinar EF. (2003). Measuring attraction to organizations. Educational and Psychological Measurement.
Homburg C., Klarmann M. and Schmitt J. (2010). Brand awareness in business markets: When is it related to firm performance? International Journal of Research in
Marketing, 27(3),.201-212.
Jain N. & Bhatt P. (2015). Employment preferences of job applicants: unfolding employer branding determinants. Journal of Management Development, 34(6), 634-652.
Jeansson J. (2017). SMEs’ online channel expansion: Value creating activities. Electronic Markets: The International Journal on Networked Business,27(1), 49-66. Keller K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57, 1–22.
Keller K.L. (1998). Strategic Brand Management – Building, Measuring and Managing Brand Equity, Prentice-Hall, Upper Saddle River, NJ.
Keller K.L. & Lehmann D.R. (2006). Brands and branding: Research findings and future priorities. Marketing Science, 20(1), 27-36.
Kotler P. (1997). Marketing Management. Prentice Hall, Upper Saddle River.
Kim H.B., Kim W.G. and An J.A. (2003). The effect of consumer-based brand equity on firms’ financial performance. The Journal of Consumer Marketing, Vol. 20 Nos 4/5, pp. 335-51.
Kim S., Chen R.P and Zhang K. (2016). Anthropomorphized Helpers Undermine Autonomy and Enjoyment in Computer Games. Journal of Consumer Research, 43(2), 282-302.
Lassar W., Mittal B. and Sharma A. (1995). Measuring customer-based brand equity.
The Journal of Consumer Marketing, Vol. 12 No. 4, p. 11.
Louviere J. and Woodworth G. (1983). Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data. Journal of Marketing Research, 20, 350 – 367.
Macdonald E.K. and Sharp B.M. (2000). Brand awareness effects on consumer decision making for a common, repeat purchase product: A replication. Journal of
business research, 48(1), pp.5-15.
Martin G., Beaumont P., Doig R. & Pate J. (2005). Branding: A new performance discourse for HR? European Management Journal, 23(1), 76–88.
Maxham J. G., Netemeyer R.G. and Lichtenstein D.R. (2008). The retail value chain: Linking employee perceptions to employee performance, customer evaluations, and store performance. Marketing Science, 27(2), 147.
Pappu R., Quester P.G. & Cooksey R.W. (2005). Consumer-based brand equity: Improving the measurement–empirical evidence. The Journal of Product and Brand
Management, 14 (2/3), 143–154.
Parvin M.M. and Kabir M.N. (2011). Factors affecting employee job satisfaction of pharmaceutical sector. Australian Journal of business and management research, 1(9), 113.
Perrey J., Freundt T. and Spillecke D. (2015). Power brands: measuring, making, and managing brand success. John Wiley & Sons.
Qiu C. and Leszczyc P.P. (2016), Send-for-review decisions, brand equity, and pricing, European Journal of Marketing, 08 February 2016, Vol.50(1/2), pp.145-165.
Sapsford R. & Jupp V. (Eds.). (2006). Data collection and analysis. Sage.
Sato Y. (2004). City structure, search, and workers' job acceptance behavior. Journal of
Urban Economics, 55(2), pp.350-370.
Rozsnyai O. (2016). Willingness to pay for innovations an emerging European innovation adoption behavior. European Journal of Innovation Management, 19(4) 568 – 588.
Sharma J.P. and Bajpai N. (2011). Salary satisfaction as an antecedent of job satisfaction: Development of a regression model to determine the linearity between salary satisfaction and job satisfaction in a public and a private organization. European
Journal of Social Sciences, 18(3), 450-461.
Simon C.J. and Sullivan M.W. (1993). The measurement and determinants of brand equity: a financial approach. Marketing Science, 12(1): 28–52.
Singh D. (2013). The brand personality component of brand goodwill: some antecedents and consequences. Brand equity & advertising: Advertising's role in building strong brands, 83-96.
Spence M. (1974). Market signaling: Informational transfer in hiring and related screening processes. Cambridge, MA: Harvard University Press.
Tavassoli N. T., Sorescu A. & Chandy R. (2014). Employee-Based Brand Equity: Why Firms with Strong Brands Pay Their Executives Less. Journal of Marketing
Research, 51(6), 676-690.
Turner J. and Haslam S.A. (2001). Social identity, organizations and leadership. In M. Turner (Ed.), Groups at work: Theory and research (25–65). London: Erlbaum.
United Nations (2017). World Population Prospects. 2017 Revision.
Vargo S.L. and Lusch R.F. (2004). Evolving to a new dominant logic for marketing.
Journal of Marketing, Vol. 68 No. 1, p. 1.
Wang H., Sengupta S. (2016). Stakeholder relationships, brand equity, firm performance: A resource-based perspective, Journal of Business Research, December 2016, Vol.69(12), pp.5561-5568.
Wilden R., Gudergan S. and Lings I. (2006). Employee-based Brand Equity.
University of Technology, Sydney.
Wilden R., Gudergan S. and Lings I. (2010). Employer Branding: Strategic
Implications for Staff Recruitment. Journal of Marketing Management, 26(1-2), pp. 56–73.
competition, and brand equity. Business Horizons, 42(6), 9-18.
Choice-based Conjoint analysis:
The impact of the employer brands on job
choice
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