Quantitative data analysis

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Reference no: EM132253831

Use the Case Study to answer all the questions. QUANTITATIVE DATA ANALYSIS: HYPOTHESIS TESTING PERCEPTIONS OF ORGANIZATIONAL ATTRACTIVENESS INTRODUCTION When Song Mei Hui moved from being Vice President for Human Resources at Pierce & Pierce in Shanghai to her international assignment in New York, she was struck by the difference in perception of Pierce & Pierce as an employer in China and the United States. Pierce & Pierce in China stands for an attractive and popular place to work, as opposed to its image as an employer in the United States, which was one of an unattractive, traditional, and uninspiring place of work. This difference in perception was bothering Song Mei Hui, because a strong and appealing ‘employer brand’ has the capacity to attract (and retain) talent as denoted by the number of university graduates aspiring to work for companies such as SAS, Google, Cisco, and the Boston Consulting Group. According to Song Mei Hui, the drivers of employer attractiveness have evolved into a complex and challenging set in this day and age. Even though she believes that the success of the organization itself is at the cornerstone of being an attractive employer (and Pierce & Pierce is flourishing indeed), she feels that a wide variety of factors contribute to being successful in attracting and retaining talent. “For many employees, being a part of a profitable, thriving corporation is a reward on its own,” she says. “However, this is obviously not enough. Opportunities for empowerment, a feeling of achievement, a substantial compensation package, and a culture of grooming and development also play a major role in the decision-making process of today’s young professionals. Job candidates are looking for a career, and not just for a job.” Song Mei Hui has hired a graduate student in management, Timothy Brice, to develop and test a model of employer attraction. The results of Timothy’s study should help Pierce & Pierce to become more popular as an employer in the United States and hence to attract and retain talented young professionals. Timothy has conducted a literature review and in-depth interviews with graduate students and young professionals who have just started their careers in order to establish the drivers of employer attractiveness. Based on the results of the literature review and the qualitative study, he has developed the following model. CONCEPTUAL MODEL AND HYPOTHESES Figure 1: A conceptual model of employer attraction EMPLOYER BRAND IMAGE From this model, Timothy has derived the following hypotheses. The effect of Brand Image on Employer attraction Employer brand image can be defined as the potential applicants’ perceptions of instrumental and symbolic attributes of an organization (cf. Backhaus and Tikoo, 2004; Lievens and Highhouse, 2003; Lievens, 2007; Martin, Beaumont, Doig and Pate, 2005). The instrumental dimension includes tangible attributes related to the job and/or the organization such as ‘job opportunities’, whereas the symbolic dimension includes (the perception of) intangible attributes of an employer (as if it were a person) such as ‘sincerity’ and ‘being exciting’. Both instrumental and symbolic attributes have been found to affect applicant attraction to an employer (Backhaus and Tikoo, 2004; Cable and Turban, 2001; Turban and Greening, 1997). Therefore, the following hypotheses are proposed: H1a: The more positive the perception of instrumental attributes of an employer, the stronger applicant attraction to the organization. H1b: The more positive the perception of symbolic attributes of an employer, the stronger applicant attraction to the organization. Feelings of significant others. If significant others in someone‘s surrounding (e.g., family and friends) tell this person that a company is a much better employer than other employers, someone’s level of attraction to Instrumental attributes: - Workplace atmosphere - Job opportunities - Industry characteristics Employer attraction Symbolic attributes: - Excitement - Sincerity - Prestige Subjective norms that particular organization will grow. It is generally recognized that potential applicants often consult other people (e.g., family, friends, and/or acquaintances) about jobs and organizations (e.g., Van Hoye and Lievens, 2007)”. What’s more, Turban (2001) found that university personnel’s beliefs about organizations affect students’ attraction to that organization. Kilduff (1990) also found that in the early stages of job search, college students are heavily influenced by the beliefs of their friends and classmates. These findings all point at the relevance of social influences to potential applicants in influencing the level of employer attraction. Hence, the following hypothesis is proposed: H2: The more positive significant others are about an organization, the stronger applicant attraction to the organization. To test these hypotheses, Timothy has undertaken a quantitative field study. He has collected data using a questionnaire measuring the variables in his model and a couple of respondent characteristics such as age, gender, and level of education with closed-ended questions. The results of this study are provided next. RESULTS Table 1 provides the means and standard deviations of the variables of interest to this study and the results of a multiple regression analysis that was conducted to test the hypotheses of this study. Table 1 Summary statistics and results of the regression analysis Adjusted R2 df F M SD B SE t p Regression .365 7, 89 7.30 4 - - - - - .000 a Constant - - 2.21 3 .522 4.23 8 .000 Instrumental attributes Workplace atmosphere 4.32 .75 .088 .152 .577 .565 Job opportunities 4.73 .75 .390 .136 2.86 8 .005 Industry characteristics 4.24 .74 .275 .186 1.47 3 .144 Symbolic attributes Excitement 3.78 .91 .071 .149 .474 .637 Sincerity 5.13 .80 .109 .137 .794 .429 Prestige 4.05 .81 .146 .115 1.26 8 .208 Subjective norm 4.98 1.13 .317 .100 3.16 9 .002 Employer attraction 3.71 1.23 - - - - Note. df = degrees of freedom; F = F-statistic; M = Mean; SD = Standard deviation; B = Unstandardized beta coefficient; SE = standard error; t = t-statistic; p = significance level; Scale 1-7 a. Predictors: (Constant), Workplace atmosphere, Job opportunities, Industry characteristics, Excitement, Sincerity, Prestige, Subjective norm. b. Dependent Variable: Employer Attraction. N= 197 (88 men and 109 women). QUESTIONS 4. Provide the equation of Timothy’s model. 5. Interpret the results of the regression analysis. Discuss: a. the model fit; b. the significance of the model; c. the constant; d. the statistical validity of the beta coefficients; e. the face validity of the results. 6. A common problem encountered in regression analysis is multicollinearity. a. What is multicollinearity and how does it affect the estimates of the regression coefficients? b. Describe two ways to test for multicollinearity. Which one do you prefer? c. Suppose that multicollinearity is a problem in this study. What can Timothy do about it? d. Do you expect that multicollinearity is a problem in this study? Explain. 7. Timothy suggests that Pierce & Pierce should create more exciting jobs to attract more employees since the mean of the independent variable “excitement” is relatively low. Do you agree? 8. What managerial conclusions can you draw based on the results of the regression analysis? 9. Song Mei Hui believes that the gender of potential employees may affect the original relationship between prestige and employer attraction. She asks Timothy to test this idea. a. How can Timothy test this idea? b. Provide a new equation of the model: include Song’s ideas about the moderating effect of gender on the relationship between prestige and employer attraction. 10. Discuss the following statement: “Regression analysis does not address the issue of causality.

Reference no: EM132253831

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