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Marktanalyse Deutsche Bahn

Deutsche BahnMobility, networks, logisticsPräsentation Marktanalyse WS 2013Betreunde Professor: Prof.Dr. Tobias SchützVorgelegt von: Fabio Cozzolino, Ziv Reichert, Juan Carlos Zarraga Teuril


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Executive Summary

• Employer Branding is a relatively new discipline which has sparked the interest of many researcher interested in identifying the components that make a successful employer brand.

• This study makes use of past research to build an employer attractiveness scale for German employers and specifically for Deutsche Bahn. The findings identified 4 constructs Economic Value, Social Value, Company Value and Development Value (Emvalue).

• Further analysis has been conducted in order to test the model and explore further solutions for DB.

• Deutsche Bahn revealed to be poorly competitive in the Social value and Company Value aspects.

• A step by step approach has been taken in order to provide an easy guide that will help the firm in applying a strategic approach to the Employer Brand Experience.

• A set of 5 specific recommendations based on digital innovation, measurements and evaluation, employer brand experience management has been developed.

• Further research ideas can help Deutsche Bahn in making full use of this study and develop a customised employer brand solution.

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Agenda

Background Research

Research Findings

Action Recommendations

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Agenda

Background Research

Research Findings


Sample Description

Method and Rationale

Introduction to the Project

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Project

-> Build a franework that will help DB in measuring employer attractivness -> Provide insights on main differences between female and male

candidates -> Provide recommendations on how to attract the target group.

Actions

• Leading passenger and logistic company

• Operates in 130 countries• 34.4 billions operating profit

(DeutscheBahn website, 2013)

Client Sponsor Low female presence within

employee population Difficulties in attracting young

graudate engineers Corporate brand negatively

associated to company service s(e.g. ICE)

Situation

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Background Research

Research Findings


Sample Description



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Method and rationale

Data collected from a questionnaire and handed out to 350 participants

Use of exploratory factor analysis and confirmatory factor analysis (through PLS) to build an employer attractivness (EA) scale.

Further investigations based on constructs

Method

Previous research shows interest in developing a significant way to assess EA.

This piece of research has support from a previous study conducted on EA in the Western Australia.

Focus on German engineering graduates and on German employers.

Rationale

EA scale for German Employers EA scale for German Employers based on young female engineers Further analysis and action recomendation based on findings

Output

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Background Research

Research Findings

Action Recomendations

Sample Description



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Total Sample BreakdownSex

Age

Studies

Semester

Institution

Region

Programme

231 Male Students119 Female Students

Relevant figures

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Age

Studies

Semester

Institution

Region

Programme

Mean Age: 24.21 years

Relevant figures

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Sex

Age

Studies

Semester

Institution

Region

Programme

Total Sample Breakdown

Relevant figures

Subject:Wirtschaftsingenieurwesen20.29%Maschinenbau15.43%

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Age

Studies

Semester

Institution

Region

Programme

Relevant figures

Semester: 3rd semester (69 students)

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Sex

Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Count:

Hocschule: 180 Universität: 170

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Sex

Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Region: Baden-Württemberg (85 students)

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Age

Studies

Semester

Institution

Region

Programme

Count:

Bachelor:237 Master: 113

Relevant figures

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Age

Studies

Semester

Institution

Region

Programme

Females Sample Breakdown

Relevant figures

Mean Age:23.75 years

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Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Count:Wirtschaftsineieurwesen: 26.05% (31 students)

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Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Semester: 3rd

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Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Count:

Universität: 69Hochschule:50

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Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Region:Baden-Württemberg

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Age

Studies

Semester

Institution

Region

Programme


Relevant figures

Count:

Bachelor:78 Master: 41

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Females vs. Males

Further Studies: 83 (35.8%) Master (31% no result)

Work Experience: 69 training , 141 Internship, 71 others and

33 no experienceExperience at DB, LT, SI: 10%

DB, 6.1% LT, 12.6% SIEmployer type: 127 (55%) Big companies and conglomeratesSalary Expectation (1st):38800€

on averageSalary Expectation (5): 56600€

on averageFuture: 69% plan to remain in Germany, 4,3% will leave, 26,

4% uncertain

Further Studies: 51 (42,98%) Master (34% no result)


18 no experienceExperience at DB, LT, SI: 9.9%

DB, 6.9% LT, 7.9% SIEmployer type: 57 (47.9%) Big companies and conglomeratesSalary Expectation (1st):40000€

on averageSalary Expectation (5): 57000€

on averageFuture: 67.2% plan to remain in

Germany, 1,7% will leave, 31.1% uncertain

Further Studies: 134 (38.3%) Master (32.3% no result)


51 no experienceExperience at DB, LT, SI: 10%

DB, 6.4% LT, 11% SIEmployer type: 184 (52.6%)

Big companies and conglomerates

Salary Expectation (1st):39380€ on average

Salary Expectation (5): 56810€ on average

Future: 68.6% plan to remain in Germany, 3.4% will leave, 28%

uncertain

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Background Research

Research Findlings


Scale Building and EMvalue

Research Hypothesis based on EMvalue

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Scale Building

THE Employer attractivness Scale (EMValue)

• Reliability measure and item purification (selection) through Cronbach‘ alpha (see Appendix I)

• Explorative Factor Analysis to compute the model

• Only Factors with Eigenvalue >=1 where chosen (see Appendix I)

• Confirmatory Factor analysis carried out through PLS-SEM

Technical Information

• Ambler and Barrow three Dimensions (1996)

• Berthon, Ewings and Hah five factors (2005)

• Aberdeen group (2009) Employer Branding inside and out.

Previous Research

Based on four factors:->Economic Value, Society Value, Company Value and Development Value.->It provides a base for comparison between the companies and could be applied to a German context

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Other Scales

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(Aberdeen, 2009)


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Results

• Economic Value (1)• Society Value (2)• Company Value (3)• Development Value (4)

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Factors

Factors components1. Work-life balance, salary offer, bonuses, fringe benefits, benefits range, work

environment2. Family influence, personal perspective(built upon society perspective), friends.3. General financial performance, product performance, rankings, prizes, CSR.4. Trainings opportunities, learning and talent development opportunities etc.


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Scores

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Deutsche Bahn Siemens Lufthansa Technik

EV =7.08 SV=6.63

CV=6.74 DV=7.21

SV=7.58SV=7.67 EV=7.53 EV=7.53

DV=8.13DV=8.12 CV=8.42 CV=8.39

EV= Economic ValueSV= Social ValueDO= Development ValueCP= Company Value

10

75

1010

7 755


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Testing the model

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Regression Analysis to confirm the influence on the willingness of the students in starting their

career at one of the firms

The model explained that the factors influence willingness to start their

career at one of the companies with a R2 of 0.8 in almost all the observations

(Appendix III)

-the society perspectives construct was the most influential factors in the

model.


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Further Testing (2) with PLS• The model was further tested (see Appendix

II) via the Smart-PLS software.

• Really positive results showed that the data actually fit the model previously explored through factor analysis (see Appendix II).

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“Step-by-Step” Recommendations based on Total Scores

- Two main weaknesses: Social Value, Company Value.- Integrated Brand Management and employer brand experience (Mosley, 2007)-Increase perceived brand innovation and performance. - Communication models and channels

-By following a strategic framework (Moroko, l and Uncles, M., 2008)-Differentiate career paths and integrate a specific communication means for engineering students. -Develop a personal Brand identity and investigate values experience by its own employees (Ritson, M., 2013)

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Challenges

What to improveHow to Improve?


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Integrated Brand Management

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(Mosley, 2007)


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Employer Brand Experience

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(Mosley, 2007)


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Strategic Actions

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Moroko and Uncles 4 cells

Strategic Issues


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Building a Scale for female students

FEMvalue

Economic ValueSocial Value

Company Value

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Step-by-step solutions based on female students scores

. Physical lack of female students interested in the subject- Culture communication problems

-Level of engagement with female population-Increase interest in the subject from first steps into education.

-Provide short term internships for female students (at high school level) in order to improve interest in the subject.-Start a female leaders mentoring scheme aimed at increase female workers at all levels in the organisation (Bonvissuto, K., 2001)

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Challenges

What to improveHow to Improve?


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Models Pros and Cons

Difficult to guarantee external validity despite

numbers of tests available

The model could overgeneralize real situation

and be to simplistic

Purely quantitative approach

Measurement errors might affect the results

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A ready to use and powerful tool for inexperienced HR

teams

Provide the base for further research and experimentation

It may provide a rare tool to examine the characteristics of successful/unsuccessful employer brands (Moroko, L., Uncles, M.,

2008)

An easy and concise way for comparison, self-evaluation and

problem recognition

- +


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Agenda

Background Research

Research Findings


Scale Building and EMValue

Research Hypothesis based on EMValue

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Further investigations

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H1: Product performance (e.g. attractiveness, innovation etc.) influence candidates choice when applying for a company

Results-A Regression analysis approach was applied to investigate the hypothesis. -The results were significant, showing a relationship between product and candidates choice when applying for a job position. Thus, supporting the findings of Emvalue scale.

Hypothesis


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• On average our investigation showed that the female students had poor knowledge of the culture, environment etc. at each respective firms.

• Surprisingly many other investigation showed that male and female students are similar in their preferences (e.g. Salary expectations and career making)(see Appendix IV)

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Further investigations


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Background Research

Research Findings


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Recommendations


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A digital Revolution – Best tool for improving

reputation (Valor, 2009)

The scale itself could be used as a measurement

tool and integrated in the whole brand

management experience

Implementing a specific and strategic approach to

employer branding for engineering students by

using a strategic framework and by integrating a specific

career profile (page)

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Take advantage of the lack of communication to female

graduates in the industry by inspiring future qualified women

early in their career.

Redesign product performance and implementing innovative

ideas by digitalizing and reinventing work environment.

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Further research ideas• Plan a larger sample of female students for a more

precise analysis • Evaluate values experience by DB employees on an

annual basis with an in-house specific questionnaire together with focus groups

• Repeat this study by using a combination of qualitative and quantitative data to improve performances

• Take into account more competitors in order to achieve a better view of the German Employers market

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Questions

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References/Literature• Ambler, T. & Barrow, S. (1996) The employer brand. Journal of Brand Management,

4(3), pp. 185–206.• Berthon, P, Ewing, M, & Hah, L 2005, 'Captivating company: dimensions of

attractiveness in employer branding', International Journal Of Advertising, 24, 2, pp. 151-172, Business Source Complete, EBSCOhost, viewed 6 January 2014.

• Bonvissuto, K 2001, 'Women's initiative sets new goals', Crain's Cleveland Business, 22, 9, p. 23, Regional Business News, EBSCOhost, viewed 7 January 2014.

• Churchill, G.A. Jr (1979) A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, XVI, pp. 64–73.

• Jones, B, Temperley, J, & Lima, A 2009, 'Corporate reputation in the era of Web 2.0: the case of Primark', Journal Of Marketing Management, 25, 9/10, pp. 927-939, Business Source Complete, EBSCOhost, viewed 6 January 2014.

• 'Lowdown' 2009, Prweek (U.S.), p. 10, Business Source Complete, EBSCOhost, viewed 6 January 2014.

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• Moroko, L, & Uncles, M 2008, 'Characteristics of successful employer brands', Journal Of Brand Management, 16, 3, pp. 160-175, Business Source Complete, EBSCOhost, viewed 6 January 2014.

• Mosley, RW 2007, 'Customer experience, organisational culture and the employer brand', Journal Of Brand Management, 15, 2, pp. 123-134, Business Source Complete, EBSCOhost, viewed 6 January 2014.

• Ritson, m 2013, 'Employer branding can do real harm so stop it', Marketing Week (01419285), p. 42, Business Source Complete, EBSCOhost, viewed 7 January 2014.

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References/Literature


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Appendix I ExploratoryFactor Analysis

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Measure of reliability used for item purification whole data set

Measure of reliability used for item purification female data set

Reliability test shows extremely positive results in accordance with Churchill ‘s criteria (1979)


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Appendix I Exploratory Factor Analysis

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Relevant data total dataset

Relevant data female dataset

Both KMO test and Bartlett’s Test show significant resultEspecially KMO with the .963 and .975 measures


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Appendix I Exploratory Factor Analysis

• Eigenvalue Criterion

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The first four factors were extracted.


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Appendix II Confirmatory factor analysis with PLS

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Both Internal Validity and reliability parameters are satisfied. Furthermore, less only 4 iterations where completed. Thus, confirming that the data fit the model.

AVE= suggested values >0.5

Composite reliability = suggested values > 0.817

Cronbachs Alpha= suggested value > 0.8


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Appendix II Confirmatory factor analysis with PLS

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All loadings from reflective items respect the > 0.7 recommended value

When performing confirmatory factory analysis on PLS, all the constructs must be connected to each other(Source: Smart-PLS forum)


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Appendix III – Further Testing

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Results Regression Analysis willingness to start a career at DB vs. Factors

All the variable were significant to the model as it is possible to observe from the Sig. column.


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Appendix IV- Further Investigation

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Both the analysis show homogenous variance and thus F-test was analysed.F-test shows that no significant difference has been observed. (Sig.>0.05)

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