Industrial Psychology

Abstract

Industrial psychology is the scientific study of human behavior at work: how people are selected, trained, motivated, and led, and how work itself can be designed to be both productive and humane. Also called industrial and organizational (I-O) psychology, it applies the methods of the behavioral sciences to the practical problems of organizations, from choosing valid predictors of performance to reducing burnout. This article treats it as a branch of applied psychology and follows its core problems: personnel selection, work motivation and job design, job satisfaction, leadership, and occupational well-being. It shows how each rests on measurement and on cumulative meta-analytic evidence rather than intuition, and where the field is heading as technology and remote work reshape the job. Three interactive demonstrations let the reader manipulate selection validity, job design, and the balance of job demands and resources.

Keywords: industrial psychology, industrial and organizational psychology, personnel selection

Industrial psychology is the application of psychological science to the world of work, the branch of applied psychology that studies how human beings behave in organizations and how organizations can be arranged to make the best of human capacities. Its questions are practical ones that every employer and every worker faces: who should be hired for a job, how work should be structured so that people will do it well and willingly, what makes an employee satisfied or exhausted, and how a group of people can be led toward a common purpose. What makes the field a science rather than a collection of management maxims is its insistence on measurement and evidence. Where folk wisdom asserts that a firm handshake reveals a good hire or that pay is all that motivates, industrial psychology tests such claims against data, and it has accumulated a large body of quantitative findings, many of them syntheses of hundreds of individual studies, that frequently overturn the intuition. The discipline dates its founding to Hugo Munsterberg's demonstration that the methods of the psychological laboratory could be turned to the selection and efficiency of workers (Munsterberg, 1913).

What Industrial Psychology Is

Industrial psychology is the scientific study of people at work and the application of that science to the problems of employment and organization. It occupies the ground where two things meet: the rigor of psychological measurement, with its tests, scales, and controlled comparisons, and the messy practical business of staffing and running an enterprise. The modern name for the field, industrial and organizational psychology, marks a historical widening of that ground. The industrial side is the older tradition, concerned with the individual worker as the unit of analysis: measuring aptitudes, selecting the right person for the job, training skills, and appraising performance. The organizational side, which grew up alongside and after the human relations movement of the 1930s, takes the social system of the workplace as its subject: motivation, attitudes, leadership, teams, fairness, and the culture of the organization. That movement traces to the Hawthorne studies, a program of research carried out at the Western Electric Hawthorne Works between 1924 and 1932, in which investigators found that worker productivity seemed to respond to the social conditions surrounding the experiment, the attention paid to the workers and the group dynamics among them, rather than only to the physical variables such as illumination that were being manipulated. The studies were long read as proof that social factors dominate physical ones, though a later reanalysis of the original illumination experiments found the classic effect to be weaker and more equivocal than the legend held (Levitt & List, 2011); their lasting importance is less any single result than the reorientation they prompted, toward the worker as a social being embedded in a group rather than an isolated unit of production. The two sides are complementary halves of one applied science, and a practitioner moves between them constantly, because a valid selection test is of little use in a job so badly designed that good people will not stay. What unites the field is a commitment to basing recommendations on evidence rather than on the confident intuitions that surround the subject of work, where almost everyone believes they already understand what motivates people and what makes a good employee. Industrial psychology exists in part to show, repeatedly and with data, that those beliefs are often wrong.

Types of Industrial Psychology

Industrial Psychology is also a formal descriptor in the National Library of Medicine's Medical Subject Headings, which files it under Applied Psychology within the behavioral disciplines at tree position F02.784.692. Beneath the descriptor MeSH hangs the set of narrower headings listed in Table 1. Two cautions apply. The list is an indexing classification built to organize the biomedical literature, not a theory that carves the field at its joints, and its members are neither mutually exclusive nor jointly exhaustive: job satisfaction, absenteeism, and presenteeism are causally intertwined rather than separate compartments, and the field's central concerns of selection, leadership, and motivation cut across these headings rather than matching them. Only subtypes that are themselves live articles on this site are linked, and at present none of these descriptors has its own page.

Personnel Selection

The oldest and most developed problem in industrial psychology is personnel selection: given many applicants and few positions, how should an organization decide whom to hire so as to maximize later job performance? The problem is one of prediction under uncertainty, and its central quantity is the validity coefficient, the correlation between a predictor measured before hiring, such as a test score or interview rating, and a criterion of performance measured afterward. A predictor with zero validity is worthless however plausible it seems; a predictor with high validity earns its place however counterintuitive. The field's signature achievement is the accumulation, through meta-analysis, of validity estimates for essentially every selection method in use. The classic synthesis of eighty-five years of such research concluded that general mental ability is among the most valid single predictors of performance across the range of jobs, that its validity rises with job complexity, and that the most useful additions to an ability test are a structured interview and an integrity test, while methods organizations often prize, such as unstructured interviews, years of experience, and graphology, add little or nothing (Schmidt & Hunter, 1998). Personality also predicts, though more modestly and selectively: of the Big Five traits, conscientiousness forecasts performance across virtually all jobs, because the disposition to be organized, dependable, and achievement-striving is an asset in any role (Barrick & Mount, 1991). These estimates are not merely academic. Because the value of good selection scales with the number of people hired and the spread of their performance, even a modest gain in validity is worth a great deal to a large employer, which is why the field expresses selection quality in the economic language of utility. Figure 1 arranges the major selection methods by their approximate validity, and the ordering is the field's standing rebuke to intuition: the methods organizations trust most, the unstructured interview and years of experience, sit near the bottom, while the abstract test of general mental ability sits at the top. The demonstration below then lets the reader vary a predictor's validity and the selectivity of hiring and watch how the expected performance of the people actually hired responds.

A valid predictor pays off more the more selective the hiring: tightening the selection ratio raises λ, and the mean performance of the hired group is the validity multiplied by that intensity. With zero validity the bar stays at the pool average no matter how selective you are.

The validity numbers themselves have recently been reopened. A careful re-examination of the corrections that meta-analysts routinely apply, especially the correction for range restriction that inflates observed validities back to an applicant-pool value, argued that the standard procedure systematically overcorrects, so that the true operational validity of cognitive ability and several other predictors is lower than the textbook figures long implied, and the ranking of methods shifts accordingly (Sackett et al., 2022). The episode is a good advertisement for the field's self-correcting habits: the same meta-analytic machinery that produced the received estimates was turned on its own assumptions, and the profession revised its numbers rather than defend them.

Work Motivation and Job Design

Selecting able people is only half the task; the other half is arranging conditions under which they will exert effort. Industrial psychology approaches motivation less as a matter of exhorting workers than of designing jobs and goals so that motivation follows. An early and influential form of this idea was Frederick Herzberg's two-factor theory, which held that the factors producing job satisfaction are distinct from those producing dissatisfaction: hygiene factors such as pay, supervision, and working conditions can, when adequate, only prevent dissatisfaction, whereas genuine motivation flows from the content of the work itself, from achievement, recognition, and responsibility. The theory's evidence was contested almost from the start, and a well-known review judged its empirical support weak and partly an artifact of the method used to gather it (House & Wigdor, 1967); yet its practical injunction, to motivate by enriching the work rather than by improving its surroundings, proved durable and set the agenda for the more rigorous design research that followed. The most influential of those later design theories holds that the motivating power of a job arises from its structure. Work that draws on a variety of skills, that lets a person complete a whole and identifiable piece of work, that matters to others, that grants autonomy over how the work is done, and that provides direct feedback on results tends to produce internal motivation, satisfaction, and high-quality performance, because it engages the worker's own sense of responsibility and accomplishment rather than relying wholly on external reward (Hackman & Oldham, 1976). This is the job-enrichment tradition, and its practical lesson is that a badly designed job cannot be rescued by incentives alone. Alongside job design runs the other great motivational principle, goal setting. A large program of research established that specific and difficult goals produce higher performance than vague exhortations to do one's best or than easy goals, provided the person is committed to the goal and has the ability and feedback needed to pursue it; the goal focuses attention, mobilizes effort, encourages persistence, and prompts the search for task strategies (Locke & Latham, 2002). The two principles are complementary: goal setting supplies the direction and intensity of effort, job design supplies the conditions under which effort is willingly given. The demonstration below builds the job-design theory into a calculator, letting the reader adjust the five core characteristics of a job and see how they combine, multiplicatively, into a single index of motivating potential.

The three meaning dimensions are averaged, then autonomy and feedback multiply the result. Set feedback to 1 and watch a rich job collapse; restoring a missing multiplier is usually the cheapest large gain in motivating potential.

Job Satisfaction and Organizational Attitudes

If motivation concerns what people do at work, job satisfaction concerns how they feel about it: the evaluative attitude, positive or negative, that a person holds toward the job as a whole and toward its particular facets, such as pay, supervision, coworkers, and the work itself. Satisfaction is one of the most heavily measured constructs in the field, and its relationships are better understood than folk belief supposes. The intuitive idea that a happy worker is a productive worker turns out to be true but weak: across many studies the correlation between job satisfaction and job performance is real and positive but modest, strong enough to matter in the aggregate yet far from the tight coupling managers often assume (Judge et al., 2001). Satisfaction relates far more strongly to withdrawal than to output: dissatisfied employees are markedly more likely to be absent and, above all, to quit, so that attitudes forecast turnover better than they forecast productivity. A closely related organizational attitude is the perception of fairness. Employees form judgments about whether outcomes are distributed justly, whether the procedures that produce them are fair, and whether they are treated with dignity, and these justice perceptions predict satisfaction, commitment, trust, and citizenship behavior across a wide range of settings (Colquitt et al., 2001). The practical upshot is that how decisions are made and explained, and not only what they award, shapes the attitudes on which retention and cooperation depend.

Leadership

Few topics attract more folk theorizing than leadership, and few have been more thoroughly measured by industrial psychology. Modern research distinguishes styles of leadership by what the leader actually does. Transactional leadership operates through exchange, clarifying what is expected and rewarding or correcting performance against those expectations. Transformational leadership works through inspiration and individual attention, articulating a compelling vision, stimulating followers intellectually, and attending to their development, so that they transcend narrow self-interest for a collective goal. A meta-analytic comparison of the two found that transformational leadership, and the contingent-reward component of transactional leadership, are both positively related to a range of outcomes including follower satisfaction, motivation, and rated leader effectiveness, with transformational leadership showing broad and consistent validity (Judge & Piccolo, 2004). The finding matters because leadership development is a large industry built more often on charisma and anecdote than on evidence; the meta-analytic approach asks instead which describable, trainable behaviors actually track effectiveness. As with selection, the field's contribution is to replace the confident personal theory of leadership that everyone carries with a measured account of what predicts what, and by how much.

Occupational Well-Being and Burnout

The organizational side of the field has increasingly concerned itself not only with performance but with the health of the worker, and its central construct here is burnout: a syndrome of chronic occupational stress marked by emotional exhaustion, cynicism or depersonalization toward the job, and a reduced sense of personal accomplishment. Burnout is not simply fatigue or ordinary dissatisfaction; it is a distinct condition that develops when the demands of work chronically outstrip the resources available to meet them, and it predicts absenteeism, turnover, and impaired performance as well as personal suffering (Maslach et al., 2001). The dominant framework for understanding it, the job demands-resources model, generalizes the insight: every job can be described by its demands, the aspects that cost effort and deplete energy, and its resources, the aspects that help achieve goals, reduce demands, or foster growth. Demands drive a health-impairment process that ends in strain and burnout, while resources drive a motivational process that ends in engagement, and the two processes interact, so that ample resources buffer the toll of high demands (Bakker & Demerouti, 2017). The model is attractive because it is general enough to apply to any occupation yet specific enough to guide intervention: reduce the demands that can be reduced, and build the resources, such as autonomy, support, and feedback, that convert a demanding job from a source of strain into a source of engagement. The demonstration below lets the reader move demands and resources independently and watch the two processes, strain and engagement, respond.

Two processes run at once. Demands drive strain toward burnout, while resources drive engagement; adding resources both raises engagement and buffers the strain that the same demands would otherwise produce.

Worked Example

The claim that job design has a multiplicative structure can be made exact with the index the job-characteristics theory proposes, the Motivating Potential Score, which combines the five core job dimensions into a single number (Hackman & Oldham, 1976). Each dimension is rated on a scale from 1 to 7. Three of them, skill variety, task identity, and task significance, together determine how meaningful the work feels, and they enter as an average; the remaining two, autonomy and feedback, enter as multipliers, on the theory that experienced meaningfulness, experienced responsibility, and knowledge of results are all necessary, so that a near-zero value on any one nearly cancels the motivating potential of the whole. The formula is MPS equals the average of skill variety, task identity, and task significance, multiplied by autonomy, multiplied by feedback. Consider an assembly job rated skill variety 6, task identity 4, task significance 6, autonomy 5, and feedback 3. The meaningfulness average is (6 plus 4 plus 6) divided by 3, which is 16 divided by 3, or 5.33. The score is then 5.33 multiplied by 5 multiplied by 3, which is 80.0, out of a maximum possible 343 (that is, 7 times 7 times 7). Now suppose a redesign leaves the work identical but adds a real-time performance dashboard, raising feedback from 3 to 6 while everything else stays fixed. The meaningfulness average is unchanged at 5.33, and the new score is 5.33 multiplied by 5 multiplied by 6, or 160.0. Doubling one multiplier has doubled the motivating potential of the job, from 80 to 160, even though four of the five characteristics were untouched. The multiplicative form is the theory's substantive claim: because autonomy and feedback multiply rather than add, an otherwise rich job with almost no autonomy or almost no feedback has little motivating potential, and the cheapest large gains often come from restoring a missing multiplier rather than from enriching an already-present one.

Discussion

Industrial psychology occupies an unusual position among the applied sciences of behavior, because its subject, work, is one about which nearly everyone holds strong prior beliefs. Almost every manager has a theory of what motivates people, what makes a good hire, and what leadership requires, and these theories are held with a confidence that the evidence frequently does not support. The enduring contribution of the field has been to subject those beliefs to measurement and cumulative test, and to report the results whether or not they flatter intuition: that structured procedures beat holistic judgment in selection, that the design of a job motivates more reliably than exhortation, that satisfaction predicts quitting better than producing, that fair process matters as much as favorable outcome, and that burnout is a describable syndrome with identifiable drivers rather than a personal failing. These findings share a methodological signature. They are usually meta-analytic, pooling many modest studies into a stable estimate, and they are expressed as validities and effect sizes rather than as slogans, which lets the field state not only that something works but how well. That quantitative discipline is also the field's answer to the perennial competition it faces from management fashion, the succession of confidently marketed programs that promise transformation and rarely report an effect size. The open questions are substantial and increasingly urgent. The validities on which selection practice rests are themselves under revision as the field re-examines its statistical corrections (Sackett et al., 2022). The nature of work is changing faster than the theories built to describe stable jobs, and the field must decide how much of its accumulated knowledge, gathered largely from twentieth-century organizations, still holds when the job itself is being redefined.

Current Directions

The most active front is the collision between the field's stable knowledge and a rapidly changing world of work. Technology is the first driver: automation, algorithmic management, and artificial intelligence are reshaping which tasks humans do, how performance is monitored, and even how hiring decisions are made, raising questions about the validity and fairness of machine-scored selection that the field is only beginning to answer (Cascio & Montealegre, 2016). The COVID-19 pandemic supplied a second, abrupt driver, forcing a natural experiment in remote and hybrid work, in the management of isolated and distributed teams, and in the boundary between work and home, and prompting a broad agenda for how the discipline should study large-scale disruptions to work (Rudolph et al., 2021). A third direction is methodological and internal: the reappraisal of meta-analytic validity estimates has set off a wider reckoning with how the field corrects, pools, and reports its cumulative evidence, a debate whose resolution will reset the numbers that selection practice quotes (Sackett et al., 2022). Running through all three is a sustained turn toward employee well-being as an outcome in its own right rather than a means to productivity, with the job demands-resources framework increasingly used to design interventions and to justify job redesign on health as well as performance grounds (Bakker & Demerouti, 2017). The field that Munsterberg founded to make workers more efficient now spends much of its effort making work more sustainable, and the two aims are less opposed than a century of debate assumed.

Common Misconceptions

Industrial psychology is just human resources or common-sense management.

It is an empirical science that develops and validates the methods human resources may later apply, and its findings routinely contradict common sense: unstructured interviews and years of experience, both widely trusted, are weak predictors of performance, whereas structured procedures and general mental ability are strong ones (Schmidt & Hunter, 1998).

A satisfied worker is automatically a productive worker.

The satisfaction-performance correlation is real but modest; satisfaction predicts absenteeism and turnover far more strongly than it predicts output. Improving morale is worthwhile, but chiefly for retention and citizenship rather than as a reliable lever on productivity (Judge et al., 2001).

Money is the only thing that motivates people at work.

Pay matters, but the design of the work itself is a powerful and often cheaper motivator. Jobs with variety, autonomy, and feedback generate internal motivation that incentives alone cannot buy, and specific difficult goals raise performance independently of pay (Hackman & Oldham, 1976).

Burnout is simply a sign that someone cannot cope.

Burnout is a syndrome produced by the chronic mismatch between job demands and resources, not a personal weakness. Because its drivers lie largely in the design and conditions of work, it responds to organizational change more reliably than to telling individuals to be more resilient (Maslach et al., 2001).

Glossary

Absenteeism.

Habitual or intentional absence from work, treated in the field as a behavioral index of withdrawal linked to dissatisfaction and ill health.

Burnout.

A syndrome of chronic occupational stress marked by emotional exhaustion, cynicism toward the job, and a reduced sense of accomplishment.

Conscientiousness.

The Big Five personality trait of being organized, dependable, and achievement-striving; the most general dispositional predictor of job performance.

Criterion.

The outcome a selection procedure is meant to predict, typically a measure of job performance gathered after hiring.

Goal setting.

The motivational practice of assigning specific, difficult goals, which raise performance by directing attention, mobilizing effort, and prompting strategy search.

Hawthorne studies.

A program of research at the Western Electric Hawthorne Works (1924-1932) that drew the field's attention to the social determinants of worker behavior and helped found the human relations movement.

Job demands-resources model.

A framework in which job demands drive a strain process toward burnout while job resources drive a motivational process toward engagement.

Job satisfaction.

The evaluative attitude a person holds toward their job as a whole and toward its facets such as pay, supervision, and the work itself.

Motivating Potential Score.

A single index of a job's motivating power, formed by averaging skill variety, task identity, and task significance and multiplying by autonomy and feedback.

Organizational justice.

Employees' perceptions of fairness in the outcomes they receive, the procedures that produce them, and the interpersonal treatment they are given.

Personnel selection.

The process of choosing among job applicants using predictors validated against later job performance so as to maximize the quality of hires.

Range restriction.

The narrowing of a predictor's variance when only selected applicants are studied, which lowers observed validity and is the target of a statistical correction now under debate.

Selection ratio.

The proportion of applicants an organization hires; the more selective the ratio, the greater the payoff a valid predictor can deliver.

Transformational leadership.

A leadership style that inspires followers through vision, intellectual stimulation, and individual attention, associated with broad positive outcomes.

Two-factor theory.

Herzberg's proposal that job satisfaction and dissatisfaction arise from distinct sets of factors, the motivators intrinsic to the work and the hygiene factors surrounding it; the origin of the job-enrichment approach.

Utility.

The economic value of a selection procedure, which grows with its validity, the number of people hired, and the spread of performance among them.

Validity coefficient.

The correlation between a predictor measured before hiring and a criterion of performance measured afterward; the core measure of a selection method's worth.

Work motivation.

The set of forces that determine the direction, intensity, and persistence of effort at work, engineered through job design and goal setting as much as through incentives.

Key Researchers

J. Richard Hackman (1940-2013). Organizational psychologist at Yale and later Harvard University; with Greg Oldham he developed the job characteristics model and the Motivating Potential Score, showing how the structure of work shapes motivation. Faculty Page - Wikipedia

Frederick Herzberg (1923-2000). Psychologist at the University of Utah; his two-factor theory distinguished the hygiene factors that prevent dissatisfaction from the motivators that produce satisfaction, and helped launch the job-enrichment movement. Wikipedia

Gary P. Latham. Organizational psychologist at the University of Toronto; with Edwin Locke he built and tested goal-setting theory, one of the most strongly supported theories of work motivation. Faculty Page - ORCID

Edwin A. Locke. Foundational motivation researcher, emeritus at the University of Maryland; his work with Gary Latham established that specific, difficult goals raise performance and specified the conditions under which they do. Faculty Page - Google Scholar - Wikipedia

Christina Maslach. Social psychologist at the University of California, Berkeley; she defined and measured job burnout, creating the Maslach Burnout Inventory and the modern research program on occupational exhaustion. Faculty Page - ORCID - Google Scholar - Wikipedia

Elton Mayo (1880-1949). Australian-born industrial researcher at Harvard Business School; his role in the Hawthorne studies helped found the human relations movement and turned the field's attention to the social conditions of work. Wikipedia

Hugo Munsterberg (1863-1916). German-American psychologist at Harvard University; his 1913 book applied the psychological laboratory to selection, training, and efficiency, and is regarded as the founding text of industrial psychology. Faculty Page - Wikipedia

Frank L. Schmidt (1944-2021). Industrial psychologist at the University of Iowa; with John Hunter he developed psychometric meta-analysis and produced the definitive syntheses of the validity of personnel selection methods. Wikipedia

Frequently Asked Questions

What is industrial psychology? Industrial psychology is the scientific study of human behavior at work and the application of that science to the problems of employment and organization, including selection, training, motivation, job design, leadership, and well-being. It is now usually called industrial and organizational psychology to reflect both its individual-worker and its social-system concerns (Munsterberg, 1913).

What is the difference between industrial and organizational psychology? The industrial side is the older tradition, focused on the individual worker: measuring aptitudes, selecting and training people, and appraising performance. The organizational side, which grew from the human relations movement onward, studies the social system of the workplace, including motivation, attitudes, leadership, fairness, and teams. The two are complementary halves of one applied field.

How do organizations decide whom to hire? Scientifically minded organizations use predictors whose validity, the correlation with later job performance, has been established by research. Meta-analysis shows that general mental ability, structured interviews, and integrity tests are among the strongest predictors, while unstructured interviews and years of experience are comparatively weak (Schmidt & Hunter, 1998).

What actually motivates people at work? Motivation is driven both by the design of the job and by the goals set. Work with variety, autonomy, and feedback fosters internal motivation (Hackman & Oldham, 1976), and specific difficult goals raise performance when the person is committed and has the ability and feedback to pursue them (Locke & Latham, 2002).

Does job satisfaction improve performance? Only modestly. The correlation between satisfaction and performance is real but weak, whereas satisfaction predicts absenteeism and turnover much more strongly, so its main practical value lies in retaining employees rather than in raising their output (Judge et al., 2001).

What is employee burnout? Burnout is a syndrome of chronic work stress characterized by emotional exhaustion, cynicism toward the job, and reduced personal accomplishment. It arises when job demands chronically exceed resources, and it predicts absenteeism, turnover, and impaired performance (Maslach et al., 2001).

What kind of leadership is most effective? Meta-analytic evidence supports transformational leadership, which inspires followers through vision, intellectual stimulation, and individual attention, along with the contingent-reward component of transactional leadership; both relate positively to follower satisfaction, motivation, and rated effectiveness (Judge & Piccolo, 2004).

Is industrial psychology just management consulting? No. It is an empirical science whose distinctive contribution is measurement and cumulative evidence, expressed as validities and effect sizes. This lets it test the confident intuitions that surround work and, unlike management fashion, state not only that a practice works but how well (Colquitt et al., 2001).

References

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Barrick, M. R., & Mount, M. K. (1991). The Big Five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44(1), 1-26. https://doi.org/10.1111/j.1744-6570.1991.tb00688.x

Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3, 349-375. https://doi.org/10.1146/annurev-orgpsych-041015-062352

Colquitt, J. A., Conlon, D. E., Wesson, M. J., Porter, C. O. L. H., & Ng, K. Y. (2001). Justice at the millennium: A meta-analytic review of 25 years of organizational justice research. Journal of Applied Psychology, 86(3), 425-445. https://doi.org/10.1037/0021-9010.86.3.425

Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279. https://doi.org/10.1016/0030-5073(76)90016-7

House, R. J., & Wigdor, L. A. (1967). Herzberg's dual-factor theory of job satisfaction and motivation: A review of the evidence and a criticism. Personnel Psychology, 20(4), 369-390. https://doi.org/10.1111/j.1744-6570.1967.tb02440.x

Judge, T. A., Thoresen, C. J., Bono, J. E., & Patton, G. K. (2001). The job satisfaction-job performance relationship: A qualitative and quantitative review. Psychological Bulletin, 127(3), 376-407. https://doi.org/10.1037/0033-2909.127.3.376

Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional leadership: A meta-analytic test of their relative validity. Journal of Applied Psychology, 89(5), 755-768. https://doi.org/10.1037/0021-9010.89.5.755

Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3(1), 224-238. https://doi.org/10.1257/app.3.1.224

Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705-717. https://doi.org/10.1037/0003-066X.57.9.705

Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. https://doi.org/10.1146/annurev.psych.52.1.397

Munsterberg, H. (1913). Psychology and industrial efficiency. Houghton Mifflin.

Rudolph, C. W., Allan, B., Clark, M., Hertel, G., Hirschi, A., Kunze, F., Shockley, K., Shoss, M., Sonnentag, S., & Zacher, H. (2021). Pandemics: Implications for research and practice in industrial and organizational psychology. Industrial and Organizational Psychology, 14(1-2), 1-35. https://doi.org/10.1017/iop.2020.48

Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection: Addressing systematic overcorrection for restriction of range. Journal of Applied Psychology, 107(11), 2040-2068. https://doi.org/10.1037/apl0000994

Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262-274. https://doi.org/10.1037/0033-2909.124.2.262