Journal of Work and Organizational Psychology Developing Biodata for Public Manager Selection Purposes: A Comparison between Fuzzy Logic and Traditional Methods

Biodata have been widely used in personnel selection for a long time, mainly due to their predictive validity in different contexts, low faking, and positive applicant reactions. At the same time, some disadvantages need to be highlighted, with discriminatory content representing a major concern. In order to shed light on these issues, the objectives of the present research are twofold: firstly, we aim to develop biodata items for personnel selection for the provision of managerial positions in Public Administration and, secondly, we aim to test the fuzzy logic method as a valid approach for the development of biodata scales, with a view to choosing the best biodata items in terms of job performance, fairness, and privacy, according with manager and applicant perspectives. Participants assessed 26 items according to traditional and fuzzy rules, resulting in 8 highly effective items. Then, both approaches were compared: fuzzy logic turned out to have similar results as the traditional approach. Finnally, future developments in research an practical implications in the field are suggested.

[1]  J. Breaugh,et al.  The Value of Biodata for Selecting Employees: Comparable Results for Job Incumbent and Job Applicant Samples? , 2014 .

[2]  N. Schmitt,et al.  Impact of elaboration on socially desirable responding and the validity of biodata measures. , 2003, The Journal of applied psychology.

[3]  Ute R. Hülsheger,et al.  Applicant Reactions in Selection: Comprehensive Meta-Analysis into Reaction Generalization Versus Situational Specificity , 2010 .

[4]  Steven F. Cronshaw,et al.  Broadening International Perspectives on the Legal Environment for Personnel Selection , 2008, Industrial and Organizational Psychology.

[5]  E. Ertugrul Karsak,et al.  A fuzzy MCDM approach for personnel selection , 2010, Expert Syst. Appl..

[6]  Chuen-Chien Lee,et al.  Fuzzy logic in control systems: fuzzy logic controller. II , 1990, IEEE Trans. Syst. Man Cybern..

[7]  Beryl Hesketh,et al.  Construct‐oriented Biodata: Capturing Change‐related and Contextually Relevant Future Performance , 1999 .

[8]  Christopher D. Nye,et al.  Using Biodata and Situational Judgment Inventories across Cultural Groups , 2017 .

[9]  Robert E. Ployhart,et al.  Applicants’ Perceptions of Selection Procedures and Decisions: A Critical Review and Agenda for the Future , 2000 .

[10]  James A. Breaugh,et al.  The use of biodata for employee selection: Past research and future directions , 2009 .

[11]  P. F. Wernimont,et al.  Signs, samples, and criteria. , 1968, The Journal of applied psychology.

[12]  Antonio L. García-Izquierdo,et al.  “Why Can’t I Become a Manager?”—A Systematic Review of Gender Stereotypes and Organizational Discrimination , 2019, International journal of environmental research and public health.

[13]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[14]  P. Alonso,et al.  Procedimientos de selección de personal en pequeñas y medianas empresas españolas , 2015 .

[15]  Sydney R. Siver,et al.  Applying Theory to the Black Box: A Model for Empirically Scoring Biodata , 2020, International Journal of Selection and Assessment.

[16]  G. Táuriz,et al.  Valoraciones de Méritos (Training and Experience) en la Administración Pública y la Empresa: Fiabilidad, Validez y Discriminación de Género Merit Ratings (Training and Experience) in the Public Administration and Industry: Reliability, Validity and Gender Differences , 2009 .

[17]  G. Stokes,et al.  Specification of Scales in Biodata Form Development: Rational vs. Empirical and Global vs. Specific , 1999 .

[18]  John P. Hausknecht,et al.  Applicant Reactions to Selection Procedures: An Updated Model and Meta-Analysis , 2004 .

[19]  Antonio L. García-Izquierdo,et al.  e-Recruitment, gender discrimination, and organizational results of listed companies on the Spanish Stock Exchange , 2015 .

[20]  Antonio Padovano,et al.  Modeling workers’ behavior: A human factors taxonomy and a fuzzy analysis in the case of industrial accidents , 2019, International Journal of Industrial Ergonomics.

[21]  M. Dean Examination of ethnic group differential responding on a biodata instrument , 2013 .

[22]  Jesús F. Salgado,et al.  Evaluación del Desempeño en la Administración Pública del Principado de Asturias: Análisis de las Propiedades Psicométricas Performance Appraisal in the Public Administration of the Principality of Asturias: An Analysis of Psychometric Properties , 2011 .

[23]  Chuen-Chien Lee FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[24]  Imtiaz Ahmed,et al.  Employee performance evaluation: a fuzzy approach , 2013 .

[25]  Thomas Bliesener Methodological moderators in validating biographical data in personnel selection1 , 1996 .

[26]  Alan Jessop,et al.  Minimally biased weight determination in personnel selection , 2004, Eur. J. Oper. Res..

[27]  Robert Pryor,et al.  An Application of a Computerized Fuzzy Graphic Rating Scale to the Psychological Measurement of Individual Differences , 1988, Int. J. Man Mach. Stud..

[28]  Ann Marie Ryan,et al.  The Unrealized Potential of Technology in Selection Assessment , 2019, Revista de Psicología del Trabajo y de las Organizaciones.

[29]  L. A. Witt,et al.  Incremental Validity of Empirically Keyed Biodata Scales over GMA and the Five Factor Personality Constructs , 2000 .

[30]  Stephanie M. Merritt,et al.  Differential Item Functioning in Biodata: Opportunity Access as an Explanation of Gender- and Race-Related DIF , 2010 .

[31]  Saadettin Erhan Kesen,et al.  A fuzzy AHP approach to personnel selection problem , 2009, Appl. Soft Comput..

[32]  Tim Hesketh,et al.  Use of fuzzy variables in developing new scales from the Strong Interest Inventory , 1995 .

[33]  Michael S. Cole,et al.  Using Recruiter Assessments of Applicants' Resume Content to Predict Applicant Mental Ability and Big Five Personality Dimensions , 2003 .

[34]  Michael Matthews,et al.  Using Biodata to Predict Turnover, Organizational Commitment, and Job Performance in Healthcare , 2009 .

[35]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[36]  Antonio L. García-Izquierdo,et al.  Applying Information Theory to Small Groups Assessment: Emotions and Well-being at Work , 2010, The Spanish journal of psychology.

[37]  Robert E. Ployhart,et al.  THE DIVERSITY–VALIDITY DILEMMA: STRATEGIES FOR REDUCING RACIOETHNIC AND SEX SUBGROUP DIFFERENCES AND ADVERSE IMPACT IN SELECTION , 2008 .

[38]  Adrian Furnham,et al.  HR Professionals' Beliefs About, and Knowledge of, Assessment Techniques and Psychometric Tests , 2008 .

[39]  L. Zadeh A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges , 1972 .

[40]  J. West,et al.  Biodata: Meeting Clients’ Needs for a Better Way of Recruiting Entry‐level Staff , 1999 .

[41]  Frank L. Schmidt,et al.  Biographical Data in Employment Selection: Can Validities Be Made Generalizable? , 1990 .

[42]  Antonio L. García-Izquierdo,et al.  Discriminación, igualdad de oportunidades en el empleo y selección de personal en España Discrimination, equal employmet opportunities and personnel selection in Spain , 2007 .

[43]  Michael Matthews,et al.  Using Biodata as a Predictor of Errors, Tardiness, Policy Violations, Overall Job Performance, and Turnover Among Nurses , 2012 .

[44]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[45]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[46]  Antonio L. García-Izquierdo,et al.  LinkedIn “Big Four”: Job Performance Validation in the ICT Sector , 2019, Revista de Psicología del Trabajo y de las Organizaciones.

[47]  Jesús F. Salgado,et al.  Evaluación del Desempeño en la Administración Pública del Principado de Asturias: Análisis de las Propiedades Psicométricas , 2011 .

[48]  R. Reilly,et al.  VALIDITY AND FAIRNESS OF SOME ALTERNATIVE EMPLOYEE SELECTION PROCEDURES , 1982 .

[49]  Svitlana Grygoruk,et al.  An approach to construct fuzzy preference relationships for managerial decision making , 2017 .

[50]  J. Goguen L-fuzzy sets , 1967 .

[51]  Murray R. Barrick,et al.  Reducing voluntary, avoidable turnover through selection. , 2005, The Journal of applied psychology.

[52]  Jeffrey M. Cucina,et al.  Scoring Biodata: Is it Rational to Be Quasi‐Rational? , 2013 .

[53]  N. Schmitt,et al.  Developing a biodata measure and situational judgment inventory as predictors of college student performance. , 2004, The Journal of applied psychology.

[54]  Edmundas Kazimieras Zavadskas,et al.  Robustness of MULTIMOORA: A Method for Multi-Objective Optimization , 2012, Informatica.

[55]  R. Klimoski,et al.  Is it rational to be empirical? A test of methods for scoring biographical data. , 1982 .

[56]  Lynn A. McFarland,et al.  The Validity of Verifiable and Non-Verifiable Biodata Items: An Examination Across Applicants and Incumbents , 2006 .

[57]  Fred A. Mael,et al.  RAINFOREST EMPIRICISM AND QUASI‘-RATIONALITY: TWO APPROACHES TO OBJECTIVE BIODATA , 1993 .

[58]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[59]  Filipa Pires da Silva,et al.  University or polytechnic? A fuzzy-set approach of prospective students' choice and its implications for higher education institutions' managers , 2017, Journal of Business Research.

[60]  M. J. Guedes,et al.  Top managers' characteristics as causal explanations for self-reported performance , 2019, Journal of Business Research.

[61]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[62]  J. Hunter,et al.  Validity and Utility of Alternative Predictors of Job Performance , 1984 .

[63]  Lotfi A. Zadeh,et al.  Is there a need for fuzzy logic? , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[64]  Lotfi A. Zadeh,et al.  Fuzzy Algorithms , 1968, Inf. Control..

[65]  Dennis Doverspike,et al.  The Validity of “Mini” Simulations for Mexican Retail Salespeople , 2002 .

[66]  N. Schmitt,et al.  Combining Cognitive and Noncognitive Predictors and Impact on Selected Individual Demographics: An Illustration , 2019, International Journal of Selection and Assessment.

[67]  M. Dean,et al.  An Examination of Biodata Theory-Based Constructs in a Field Context , 2005 .

[68]  Jeffrey M. Cucina,et al.  UNLOCKING THE KEY TO BIODATA SCORING: A COMPARISON OF EMPIRICAL, RATIONAL, AND HYBRID APPROACHES AT DIFFERENT SAMPLE SIZES , 2012 .

[69]  Garnett S. Stokes Introduction to Special Issue: The Next One Hundred Years of Biodata , 1999 .

[70]  Newell K. Eaton,et al.  Criterion-related validities of personality constructs and the effect of response distortion on those validities , 1990 .

[71]  Antonio L. García-Izquierdo,et al.  La formación en competencias como estrategia para mejorar la dirección pública , 2019 .