FACTORS CONTRIBUTING TO JOBDISSATISFACTION AND ATTRITION IN THE FEDERAL WORKPLACE DENISE LOFTON, DOCTORAL LEARNERFeb. 7, 2012 Oral Defense Presentation
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Management in Organizational Leadership Dr. Alex Lazo, Dr. Betty Ahmed, Chair Member The CommitteeUniversity of Phoenix Dr. Gerald Nebeker, Denise Lofton, Member Learner
ABSTRACTThe purpose of the quantitative correlational study wasto examine the relative influence of individualdemographics (gender, age, tenure, supervisory status,location, and intent to leave) on job dissatisfaction (DV)with facets of employment (leadership and knowledgemanagement, result orientation and performance, talentmanagement, and job dissatisfaction index) in theInternal Revenue Service, and the Social SecurityAdministration (n = 2,203).
The Study Goals…The study used demographic profiling to look beyond thetypical effect of independent variables on dependentvariables, to create a picture of groups and organizationsby like categories, and characteristics.The study‟s outcome is significant to leadership as itconfirms the role of demographics in understanding thefactors contributing to job dissatisfaction.
BACKGROUNDCongress mandates that all Employees provide theirfederal agencies assess perceptions in two importantemployee perspectives and workplace categories: (1.)develop improvement plans to leadership and managementaddress key findings. practices that contribute toThe bi-annual survey conducted agency performance, and (2.)by the Office of Personnel employee satisfaction withManagement is the primary tool aspects of employment (OPM,for data collection. 2008).
Problem StatementThe general problem is The specific problem is federal agencies lack the knowledgedissatisfied employees withdraw, needed to:become disengaged, perceive link job dissatisfaction to attritionemployment to be less than adequately predict causationdesirable, and make the choice reduce loss of talentto leave (Bowling, Beehr &Lepisto, 2006; Ingersoll & Perda, OPM predicts the federal civilian2006; Walker, 2007). workforce will see 60 percent retirement eligibility by 2012 (OPM, 2009).
Purpose StatementThe purpose of the study was to The study looked at the change in dissatisfaction among employeeinvestigate the relationship groups, by demographicbetween job dissatisfaction with characteristics:various facets of employment Age, Gender,and individual demographic Tenure,characteristics for respondents Supervisory Status,in the Federal Human Capital Location, andSurvey in 2006 and 2008, in two Intent to LeaveExecutive Agencies.
Research Questions & HypothesesRQ1: What are the relative influences of therespondent demographic characteristics (age, tenure,gender, supervisory status, location, intent to leave),on respondent dissatisfaction with facets ofemployment (leadership & knowledge management,results orientation & performance, talentmanagement, and job satisfaction index)?
Research Questions & Hypotheses H1o: The respondent demographic characteristics do notinfluence respondent dissatisfaction with facets ofemploymentH1a: Tenure and location of the respondent exert the greatestinfluence on dissatisfaction with facets of employment(leadership & knowledge management, results orientation &performance, talent management, job satisfaction index)
Research Questions & HypothesesRQ2: What are the differences in the influence ofrespondent demographic characteristics ondissatisfaction with facets of employment, betweenSSA and IRS agencies?
Research Questions & Hypotheses H2o: For the IRS and SSA, there are no differences in theinfluences of respondent demographic characteristics ondissatisfaction with facets of employmentH2a: For the IRS and SSA, there are differences in theinfluences of respondent demographic characteristics ondissatisfaction with facets of employment
Research Questions & HypothesesRQ3: What are the differences in the influences ofrespondent demographic characteristics ondissatisfaction with facets of employment between2006 and 2008?
Research Questions & Hypotheses H3o: For 2006 and 2008, there are no differences in theinfluences of respondent demographic characteristics ondissatisfaction with facets of employment.H3a: For 2006 and 2008, there are differences in the influencesof respondent demographic characteristics on dissatisfactionwith facets of employment
Study Assumptions Study utilizes secondary analysis of existing data set and as such re-purposes data Original respondents are examined solely by responses and demographic characteristics (age, tenure, gender, supervisory status, location, intent to leave) The truthfulness of the responses is assumed reliable due to the privacy proffered and long-term acceptance of the survey in the federal community
Study Scope Study utilizes data set derived from Office of Personnel Management (OPM) Federal Human Capital Survey in the years 2006 and 2008 Data used for the comparisons and analysis is limited to respondents from two Presidential Management Council member agencies, namely, the Internal Revenue Service, and the Social Security Administration. The study organizations are representative of federal workforce large agencies, have similar missions, workforce composition, organizational structure, gender representation, customer base, and stakeholder alliances (BPTW, 2010).
Study Limitations Each participating agency sample is based on employee population at the time of the original survey, without regard to gender, age, or tenure. The study utilized the quantitative responses to the 206 and 2008 federal workforce survey without any subsequent qualitative aspects due to participant anonymity. The unique demographics of each agency extends the possibility that an agency has an overrepresentation of males, versus females, or young versus older workers, in the study population
Literature Review“There is a logical relation between our perceptual judgments of what isreal (in the naïve-realist sense) and our perceptual judgment about our ownexperiences” (Murphey, 1994, p. 51).The utility of job satisfaction measures seeks perception from a „real-world‟point of view and gives as much consideration to the consequences of jobdissatisfaction, as to the causes (Seashore & Tabor, 1975).
Key Literary Findings Federal agencies and Consideration of variables that their respective leaders may influence employee seek to understand perceptions, like age, gender, better the causes of and tenure, requires employee investigators to reevaluate disengagement and past assumptions about consider the trend an workers as a cohort, and important leader challenge (Harter & account for differences in Wagner, 2010) employee traits (Dychtwald, Erickson, & Morrison, 2006).
Key Literary Findings Job dissatisfaction also When aspects of employment affects worker attitude, once considered important to and the choice to remain the decision to join an or leave employment, organization are no longer even when the job or present, workers assess job benefits may differ search capabilities, and significantly (Berry, 2010; consider other options for MSPB, 2008; Starks, employment where they may 2007). exist (Dooley, 2007; Judge & Klinger, 2008).
Research MethodologyThe study utilizes a quantitative Given the goals of the study, themethod with correlational design: large population, and multiple independent variables, the Useful in determining predictors quantitative, correlational design, using hierarchical regression Appropriate to test research questions and study hypotheses techniques was appropriate and fit for a reexamination of the Federal Allows researchers to identify and Human Capital Survey in 2006 and isolate behaviors within and between study variables 2008.(Bryman, 2001; Creswell & Clark, 2007;Trochim and Donnelly, 2008)
Research MethodologyThe study utilizes secondary analysisto re-purpose the original OPM survey: The inability to identity original respondents and the lack of Reduces research time and cost access to original respondents Supports use of large data sets with supports use of a quantitative proven reliability methodology and secondary Provides a unique opportunity to data analysis (Gelman & Hill, continue study of specific phenomenon, 2007). expand on prior knowledge, and „see‟ the world differently(Bedeian, Ferris, & Kacmar, 1992;Neuman2003; Thomas & Heck, 2001)
Study Population Overview of Study Population and Sample FrameStudy populationconsists of all Study Agency/ Year Original Sample Size Respondentrespondents who Populationanswered each IRS 2006 1,147 1,147survey question in SSA 2006 1,317 1,317the High Impact IRS 2008 1,153 1,153Index and each SSA 2008 5,959* 1,140ademographic itemincluded in the a modified sample size calculation to equalize sample groupsstudy
Study Population Sample Population (By Year, and Agency) 2006 2008 SSA IRS SSA IRS 650 484 690 411 Studypopulation was comprised of: • 741 males • 1,431 females • Average age 50 – 59 (both agencies, both years) • 1,407 supervisors • 828 non-supervisors • Average tenure over 20 years (both agencies)
High Impact Index High-Impact Item Index, 2006, 2008The High Impact Category Item # 2006 Item # 2008Item Indexquestions Leadership & Knowledge Mgmt Q9, Q17, Q36, Q55, Q57 Q9, Q17, Q37, Q56, Q58comprised thedataset extracted Results Orientation & Performance Q24, Q57 Q24, Q57from the originalOffice of Talent Management Q2, Q18, Q59 Q2, Q18, Q60Personnel surveyarchive and re- Job Satisfaction Index Q5, Q6, Q54, Q58, Q61 Q5, Q6, Q55, Q59, Q62purposed for use Note: High-Impact Item Index for 2006 and 2008 includes the same questions, but the numbersin this study changed due to a new survey item in 2008 There were a total of (17) survey questions examined by demographic characteristic in the study. See Appendix C. for survey questions.
DATA COLLECTION The survey questions were grouped into four facets ofFive questions covering all employment:facets comprise the new Leadership and Knowledgeindex: ManagementQ5, Q6, Q54, Q58, Q61* Results Orientation and* Renumbered as Q. 62 in 2008 Performance Talent Management Job Dissatisfaction Index
DATA COLLECTION Each response was coded to allow for quantitative analysis and results interpretation: Response ScaleResponses coded as The scale was appropriate to1 = Dissatisfied each question asked, for2 = Very Dissatisfied0 = Neither, Satisfied, Very example…Satisfied Q55 – How satisfied are you with your involvement in decisions that affect your work?
DATA COLLECTION Each demographic characteristic was coded to allow for quantitative analysis and results interpretation: Response Scale The scale was appropriate toEach response option to the each question asked, forDemographic characteristics example…were grouped to facilitate X3: Tenure (in the agency, IRS, andinterpretation of results SSA) [under 1 year = 1; 1 to 5 years = 2; 6 to 10 years = 3; 11 to 20 years = 4; over 20 years = 5] X6: Intent to Leave was coded: No = 1; Yes, = 2.
DATA ANALYSIS In the study, all categorical responses were coded in numeric format to facilitate regression and interpretation of results. Where a, b, c, d, e, f, are coefficients, the regression equation is: Analysis Framework The Y = a +bx1 + cx2+ dx3+ ex4+ fx5 + fx6 (1)Data was examined by ResearchQuestion, Hypotheses, In Equation 1,Employment Facet and related x1 = age of the respondent,demographic characteristic , usinghierarchical regression analysis x2 = gender of the respondent, x3 = tenure (in the agency, IRS, and SSA), x4: = supervisory status, x5 = organization, x6 = intent to leave.
DATA ANALYSIS – STEPWISE PROCESS The change in R2 was determined to see if there was a significant change when a new variable is added to the model. If the change Regression Analysis in R2 was significant (indicating Step 1 – Gender & Age contribution to the model) the Step 2 – Tenure Step 3 – Supervisory Status and variable was retained in the next Location step. Step 4 – Intent to Leave The steps were repeated for each research question, to test hypothesesSee Appendix E for regression results for each facet of employment
DATA ANALYSIS – STEPWISE PROCESS The change in R2 was determined to see if there was a significant change when a new variable is Regression Analysis added to the model. If the change The hierarchical regression in R2 was significant (indicating analysis resulted in a total of (16) contribution to the model) the models: - 4 facets of employment variable was retained in the next - 2 study agencies step. - 2 study years The steps were repeated for each research question, to test hypothesesSee Appendix E for regression results for each facet of employment
DATA ANALYSIS – DESCRIPTIVE STATISTICS Descriptive Statistics was used to : Examine the significant variable for each facet of employment. For example: Descriptives Variable Levels with Highest Dissatisfaction Score for the Significant Variables The variable(s) with highest Demographic characteristic M SD n level of dissatisfaction, by Tenure 11-20 years 1.74 2.14 329 significant variable, was Non- Supervisor 1.70 2.25 813 determined for each facet of employment Location – Field 1.48 2.05 1778 Intent to leave 2.24 2.55 470 Note: Results are for the Leadership and Knowledge Management facet of employment.See Appendix F for descriptive statistics for all demographic variables, by facet of employment
Data Outcomes – RQ 1 Relative influence of IV, Full SampleThe coefficients for Leadership and Knowledge Managementeach demographic The coefficient for tenure was positive andcharacteristic was significant [ Beta .238, p < .01]determined to The coefficients for supervisor [ Beta -.525, p <assess the .01 and location [ Beta -.320, p < .01] wasdirection of the negative and significantinfluence and the The coefficient for intent to leave was positivesignificance. and significant [ Beta 1.071, p < .01]
Key Study Findings RQ 1 Employees indicating work in a As tenure increased, respondent Field location expressed more dissatisfaction with dissatisfaction with facets of facets of employment employment than did increased Headquarters employees Non-supervisors expressed more Employees expressing an dissatisfaction with intent to leave was more facets of employment dissatisfied than those than supervisors intending to remain
Data Outcomes – RQ 2 Relative Difference in influence of IV, Between IRS and SSAThe coefficients for Leadership and Knowledge Managementeach demographic Tenure was significant for SSA only. The coefficient forcharacteristic was tenure was positive and significant [ Beta .244, p < .01]determined to Supervisory status was significant for both agencies. Theassess the coefficients for supervisor IRS [ Beta -.484, p < .01] anddirection of the SSA [ Beta -.523, p < .01] were negative and significantinfluence and the Location was significant for IRS only. The coefficient forsignificance. location was negative [ Beta -.002, p < .01 ] The coefficient for intent to leave was positive and significant for both agencies: IRS [ Beta 1.123, p < .01], SSA [ Beta 1.104, p < .01]
Key Study Findings RQ 2 Tenure continued to influence Location was significant, and employee dissatisfaction with facets, negative for IRS only, in all when examined by Agency: facets of employment SSA employees expressed more Field employees expressed dissatisfaction as tenure more dissatisfaction with facets increased of employment than Headquarters IRS employees expressed less dissatisfaction as tenure increased
Key Study Findings RQ 2 Intent to Leave was significant, Supervisory status was significant for and negative for both agencies, SSA only. in all facets of employment Non-supervisors expressed more Employees expressing an intent to dissatisfaction with facets of leave demonstrated more employment than did supervisors dissatisfaction with facets of employment The Job Dissatisfaction Index facet of employment was affected by NOTE: Future research is needed to employees dissatisfaction for: determine if, and how often, the intent Tenure (SSA =more years of service, to leave was acted upon, and the more dissatisfaction; IRS more years of related demographics service, less dissatisfaction
Data Outcomes – RQ 3 Relative Difference in influence of IV, for 2006 and 2008The coefficients for Leadership and Knowledge Managementeach demographic Tenure was significant for both years. The coefficient forcharacteristic was tenure was positive 2006, [ Beta .265, p < .01]; 2008 [ Beta .243, p < .01]determined toassess the Supervisory status was significant for both agencies. Thedirection of the coefficients for supervisor IRS [ Beta -.484, p < .01] and SSA [ Beta -.523, p < .01] were negative and significantinfluence and thesignificance. Location was significant for IRS only. The coefficient for location was negative [ Beta -.002, p < .01] The coefficient for intent to leave was positive and significant for both agencies: IRS [ Beta 1.123, p < .01], SSA [ Beta 1.104, p < .01]
Key Study Findings RQ 3 Location was significant in Tenure continued to influence each facet of employment, but employee dissatisfaction with not in the same years: facets, when examined by Year: Leadership and Knowledge As SSA and IRS employees Management in 2008 only. tenure increased, the Results Orientation and expressed dissatisfaction Performance, 2006 and 2008 with leadership and Talent Management and Job knowledge management Dissatisfaction Index in 2006 only increased
Key Study Findings RQ 3 Intent to Leave was significant, Supervisory status was significant in and negative for both years, in each facet of employment, but not in all facets of employment each year: Employees expressing an intent Leadership and Knowledge to leave demonstrated more dissatisfaction with facets of Management in 2006 only. employment Results Orientation and Performance, Talent Management and Job NOTE: Future research is needed Dissatisfaction Index in 2006 and 2008 to determine if, and how often, the intent to leave was acted upon, and the related demographics ( significance at p< .01 level )
Significance of Study FindingsThe present study addresses the factorsthat may contribute to job dissatisfaction The purpose of the research study wasand intent to leave in the federal to examine the relative influence ofworkplace. demographic characteristics on respondent dissatisfaction with facets of The range of available responses was employment, in the 2006 and 2008 provided, instead of collapsing them by Federal Human Capital Survey, for the group, which allows the findings to be Internal Revenue Service and the Social more specific and informative Security Administration. Findings support previous research indicating age, in the presence of gender, is insignificant as a predictor of dissatisfaction (Cetin, 2006; Kacmar & Ferris, 1989)
Significance of Study FindingsThe role of the supervisor and how wellsupervisory performance is perceivedinfluences employee perception of The Judge study (2001) found adissatisfaction (Judge, Thoresen, Bono, & relationship between organizationalPatton, 2001) placement, individual performance, and perceptions of supervisor performance The present study indicates supervisory status as (employee ratings, communications, a negative and significant demographic policy, and practices). characteristic in the study agencies and study years Employees in non-supervisory (authoritative positions) express more dissatisfaction in every facet of employment Note: Judge et al study included 312 research samples, and over 54,000 respondents
Overview of Study Recommendations The federal workplace is a The level of significance of employee unique employer, with surveys increases when combined many internal and external with specific information related to stakeholders. With a experiences and individual projected 60% attrition, via achievement in the organization voluntary and normal (Joshi, 2010). retirement, engaging the workforce and increasing productivity is key to mission accomplishment Several recommendations are formed, (Berry, 2011) ) based on study analysis and results.
Study RecommendationsRecommendations for leadershipconsideration are offered for eachdemographic characteristic Chapter 5 provides specificincluded in the study: recommendations and supporting theoretical framework for each Gender demographic characteristic addressed. Age Tenure Supervisory Status Location Intent to Leave
Study RecommendationsWhile age and gender, whenpresent together, were not New studies indicate females morefound significant in the study, likely to act on thoughts of leaving when dissatisfied with career advancement,the presence of over 1000 particularly when they believe that the organization does not offer a chance tofemales in the population apply a broader set of skills (Cech,warrant future examination of Rubineau, Silbey, & Seron, 2011)..employee perception, bygender.
Study RecommendationsHigh unemployment generally means themarketplace is flooded with talent,though alignment between what isrequired and what is available may mean Studies examining the role ofthe number of unemployed will continue tenure in job dissatisfactionto rise (BLS, 2011). reflect greater significance in the presence of age (Kalleberg & Loscocco, 1983). Agencies may consider stratifying responses to annual surveys by age and tenure, and compare the results to efforts to recruit and retain high performing individual to assess the gap.
Study RecommendationsLocation of employee influencedemployee dissatisfaction withfacets of employment, for both Making critical decisions basedstudy agencies. on location may create new silos and support negative competition for scarce Leaders should consider re- resources (Rieger, 2011). examine policies established based on location, to ensure that when taken as a whole they still support goals of the organization.
Study RecommendationsIntent to Leave was a significant The reasons people leave jobs,demographic characteristic in thestudy agencies for each study year. careers, organizations, and industries vary with age and tenure, and often reflect the relationship and interactions with The findings for the influence of intent managers and supervisors to leave in each facet of employee (DeConinck & Johnson, 2009; supports further investigation to ascertain how long the employee Robinson, 2008). thought about leaving and whether or not the employee experienced a triggering event.
ConclusionThe Federal Human CapitalSurvey is a rich data source forthe federal community and for Investigating dissatisfaction is anorganizations who seek important construct in our efforts tocomparisons between the private understand employee perceptions,and public sector. affective mood and reasons for disillusion (ME, 2012). It has been a rewarding experience to conduct this investigation and add to the conversation about employee dissatisfaction.
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Questions and Answers THANK YOU, ALL FOR YOUR PARTICIPATION AND CONSIDERATION OF MY DISSERTATION AND DEFENSE.