Industrial and Organizational Psychology Research Paper

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When you seek your next job, you will likely encounter the work of industrial and organizational (I-O) psychologists. Somehow, you will find a job opening, perhaps from an on-campus recruiter, an online job service, a Web site, or a newspaper ad. You will apply for a specific position. You may complete an application, answer questions about your personality and attitudes, and take tests designed to assess your abilities. Your potential employer may interview you. If members of the organization perceive that you will be able to perform the job well, you may be offered a job along with a compensation package designed to convince you to accept the offer. If you accept that offer, you may participate in programs designed to socialize you in the workplace and train you to do your job. Once you are on the job, myriad individual, interpersonal, group, and environmental processes will influence your attitudes, performance, and other behaviors. Your organization may have programs designed to improve these processes, specifically leadership, motivation, and communication. Your work performance may be evaluated.

All of these things involve I-O psychology. Every step, every event, and every process described in the previous paragraph has been the focus of study by I-O psychologists. Of course, I-O psychology is not limited to these areas, but these examples illustrate how I-O psychology may impact you in the very near future.

I-O psychology can be defined as the scientific study of behavior and psychological processes in the workplace and the application of the acquired knowledge. I-O psychologists may investigate phenomena occurring outside the workplace, including work-family conflict, work-related legislation (e.g., changes in the minimum wage), or changing workforce demographics. I-O psychologists do not address psychological or substance use problems that may be experienced by employees. Employees experiencing these difficulties are generally referred to employee assistance programs (i.e., employer programs aimed at helping employees address problems that may adversely affect their work or well-being).

The field of I-O psychology (alternatively called work psychology or occupational psychology in some parts of the world) comprises two major divisions: industrial psychology and organizational psychology. Though it is tempting to view these areas as distinct, separating them is unwise, as they overlap considerably; most I-O psychologists are trained in both areas. Industrial psychology, sometimes called personnel psychology, developed first and includes topics that are often seen as a part of human resource management (e.g., recruitment, selection, performance evaluation, and training). Organizational psychology developed as an outgrowth of industrial psychology and includes topics that also are often studied in social psychology: personality, organizational behavior, and communication.

I-O psychology is one of 54 divisions of the American Psychological Association (APA), the largest professional organization for psychologists. I-O psychologists comprise about 6 percent of the total membership of APA (for reference, clinical and counseling psychologists account for more than 50 percent of the APA membership). The largest professional organization for I-O psychologists is the Society for Industrial-Organizational Psychology (SIOP; Division 14 of APA), with approximately 3,500 professionals and 1,900 students. In addition, many I-O psychologists belong to the Society of Consulting Psychology (Division 13 of APA).

The scientist-practitioner model guides the training of I-O psychologists. This model asserts that mastery of theory and research (the science) and its skilled application (the practice) are essential and interdependent components in the preparation of I-O psychologists. The scientist must have considerable knowledge of the issues and practices of the work world. Similarly, the practitioner must have great familiarity with the research process and should be at least a sophisticated consumer of the published research. SIOP has incorporated the scientist-practitioner model into its guidelines for the education and training of I-O psychologists. These guidelines specify areas of competence to be developed at the master’s and doctoral levels. The areas of competence are generally topic-specific (e.g., individual assessment, work motivation), and they integrate science and practice. The SIOP Web site (www.siop.org) provides information for more than 95 doctoral programs and more than 100 master’s programs in I-O psychology or related areas (e.g., human resources or organizational behavior). Most of these adhere to the scientist-practitioner model. In reality, very few I-O psychologists are trained exclusively as researchers or practitioners.

Given their training, it is not surprising that I-O psychologists work in a variety of settings. According to a 2003 survey by SIOP, more I-O psychologists identified academia as their primary work setting (33 percent of respondents) than any other area. Other prominent work settings included private and nonprofit organizations (31 percent) and consulting organizations (27 percent). The survey results revealed a median annual primary income of more than $87,000 for doctoral-level respondents and $65,000 for master’s-level respondents. At the doctoral level, men reported greater income than did women ($95,000 and $80,150, respectively), but men and women were paid similarly at the master’s level ($64, 000 and $65,000, respectively). I-O psychologists working in private, nonprofit, and consulting organizations generally reported greater primary income than did those working in academic settings, but academics frequently supplement their primary income with consulting work outside of the academic setting. The job outlook for I-O psychologists is rated as average by the U.S. Bureau of Labor Statistics, with expected growth of 10 to 20 percent by 2014 (Occupational Information Network, n.d.)

A doctoral degree is not required to work in I-O psychology. Some positions are limited to people holding a doctorate (e.g., college professor, some consulting positions), but good jobs in human resources (HR) and related fields are available for individuals with master’s and bachelor’s degrees. The master’s degree often allows for a higher career ceiling than the baccalaureate, but an undergraduate major in I-O psychology with a solid foundation of business coursework provides a competitive degree for entry-level jobs in human resources. The Bureau of Labor Statistics rated growth in most HR-related occupations as above average, with expected growth of 21 to 35 percent by 2014 (see Occupational Information Network, n.d., for an example).

A Brief History Of I-O Psychology

I-O psychology enjoys a distinguished history, albeit one that is shorter than many other disciplines within psychology. Katzell and Austin (1992) have written what is probably the most authoritative history of I-O psychology, and much of what follows in this section of the chapter borrows from their work.

I-O psychology has a prehistory that comprises discrete and unscientific attempts to understand the workplace and the lives of workers. Though efforts were not coordinated in any fashion and little cumulative knowledge resulted, these early works addressed many of the topics studied by modern I-O psychology. The earliest of these attempts include Jethro’s advice to his son-in-law Moses on delegation of authority (circa 1500 BCE; Exodus 18, New American Bible), Sun Tzu’s discussion of the virtues of the leader in The Art of War (circa 500 BCE; trans. 2001), and Aristotle’s development of concepts such as specialization of labor and decentralization in Politics (350 BCE; trans. 1967). Many similar efforts would follow over the next 2,000 years, and more recent examples include Adam Smith’s (1776/1937) rationale for the modern factory system and division of labor, Robert Owen’s (1813-1816) argument for better working and living conditions for employees in a series of essays titled “A New View of Society,” and Charles Babbage’s (1832/1963) description of the advantages of a profit-sharing program in his treatise “On the Economy of Machinery and Manufactures.”

Systematic, scientific efforts to examine the workplace and its employees did not start until the early 1900s. At that time, a convergence of factors favored the application of psychology to business and industry. Among these factors were the increasing industrialization of America and the emergence of “scientific management.” Frederick Taylor, best known for his work at Bethlehem Steel, developed time-and-motion studies of work to identify the most efficient labor processes. His goal was to demonstrate that a science of management based on laws and rules was superior to so-called “ordinary” management. Though he has been criticized for creating a system that would extract maximum effort from workers for minimum compensation (a criticism leveled against much early I-O psychology), Taylor was also interested in the well-being of employees. In the first sentence of The Principles of Scientific Management, Taylor (1911/1998) wrote, “The principal object of management should be to secure the maximum prosperity for the employer, coupled with the maximum prosperity for each employee” (p. 1). In a similar vein, Frank and Lillian Gilbreth (1916/1973), contemporaries of Taylor who strove to identify the “one best way” to do work, wrote, “The aim of life is happiness, no matter how we differ as to what happiness means. Fatigue elimination, starting as it does from a desire to conserve human life and to eliminate enormous waste, must increase ‘Happiness Minutes,’ no matter what else it does, or it has failed in its fundamental aim” (pp. 149-150).

At about the same time as the scientific management movement, several experimentally trained psychologists were examining applied issues that would provide a foundation for the emerging field of industrial psychology (also then called “economic psychology” or “business psychology”). For example, Walter Dill Scott published works on the psychology of advertising (1903), work efficiency (1911), and selection (1917), and Hugo Munsterberg (1913) published his classic Psychology and Industrial Efficiency.

World War I was a notable force in the development and acceptance of industrial psychology. The war served to heighten interest in scientific management in general, but it also stimulated two related and more specific efforts to use the scientific methodology of psychology to aid America’s war effort. Robert Yerkes and his colleagues developed a system to psychologically evaluate army recruits utilizing the Army Alpha and Army Beta exams. Similarly, the Committee on Classification of Personnel, led by Scott, created a complete personnel system for the army. The work of these two groups showed that selection testing was feasible, and they provided credibility to the new discipline.

The birth of organizational psychology can be traced to a series of well-known studies conducted at a Western Electric plant in the late 1920s and 1930s. These studies (referred to as the “Hawthorne Studies” after their location in Hawthorne, Illinois) started as an attempt to identify optimal working conditions in a manufacturing plant (e.g., the ideal level of illumination). The researchers found that manipulation of work conditions did not lead to predictable results. For instance, a reduction in light intensity for an experimental group led to higher (not lower) productivity versus a control group. Interviews with workers in the studies indicated that interpersonal relationships and employee attitudes were important for worker productivity. No longer could managers simply focus on the technical aspects of work; leadership, motivation, and worker attitudes now demanded the attention of business and psychology.

In addition to the interest in organizational psychology generated by the Hawthorne studies, two other forces emerged in the 1930s. First was the large-scale measurement of employee attitudes by several major employers (e.g., Procter & Gamble, Kimberly-Clark). Advances in measurement techniques (e.g., by L. L. Thurstone and Rensis Likert) clearly facilitated this work, but so did an emerging interest in the well-being of the employees.

The second force was Kurt Lewin’s immigration to the United States. Though his contributions are astonishingly broad, Lewin’s move from Nazi Germany resulted in significant advances in three major areas of I-O psychology: the empirical study of leadership, group dynamics, and “action research” (i.e., the collection of empirical data to identify, evaluate, implement, and improve solutions to applied problems).

In the time before World War II, I-O psychology became particularly well established in its continued work on selection and training, the “industrial core of the field,” according to Katzell and Austin (1992). There was an expansion in the number of universities offering the doctorate in I-O psychology, and the number of I-O psychologists in the United States was probably about 100, double the number in the late 1920s.

World War II stimulated further growth of I-O psychology, as the military once again called on the expertise of Yerkes, Scott, and others. In addition to selection, performance appraisal, and training (traditional “I” topics that formed the backbone of the World War I work), I-O psychologists were also involved in the war effort by studying team development and attitude change (“O” topics). After the war, many of the advances that I-O psychology contributed to the military were applied to the private sector. Katzell and Austin (1992) wrote, “I-O psychology was now equally concerned with fitting people to their work and fitting work to people, at the level of the organization and work group as well as the job” (p. 811). Leadership, group work, attitudes, organizational communication, and decision making emerged as major foci for research as demand for I-O psychologists grew in academics, the military, and the private sector (including consulting organizations).

The start of the modern era of I-O psychology started in 1973 when Division 14 of the APA was renamed the Division of Industrial and Organization Psychology (formerly the Division of Industrial Psychology; it has been known as “SIOP” since 1982). This change formally incorporated the “O” side of the field that had been developing for several decades. The contemporary era of I-O psychology has witnessed an increase in (a) the breadth of its scholarship, (b) its application in a wide variety of organizations, and (c) its propagation through graduate and undergraduate education. The broad scope of I-O psychology in the 21st century will be examined in the remainder of this research-paper.

Industrial Psychology

Along with its introduction to I-O psychology, the opening section of this research-paper offered the suggestion that it is generally unwise to try to separate “I” from “O” psychology. Despite that advice, this section describes topics that are typically considered part of the “I” side for heuristic purposes. Similarly, a description of “O” psychology follows this section. The four topics covered here (job analysis, predictors and selection, criterion measurement and performance appraisal, and training) are not an exhaustive listing of the content of industrial psychology (recruitment and compensation, for example, are omitted), but they do represent a significant part of the discipline.

Job Analysis

Job analysis is essential to most work in industrial psychology, including all of the other topics covered in this section. To choose the right person for the job, or to assess an individual’s performance, or to train a worker, one must first have a thorough understanding of the job. Job analysis is a process for defining jobs. Usually, the job is broken into units such as elements and tasks. An element is the most basic unit into which a job may be separated; an element of a cashier’s job may be opening the cash register. For example, task is a work activity that is performed for some specific purpose and comprises multiple elements. One of a cashier’s tasks is to receive a customer’s payment at checkout.

There are two general approaches used to perform job analyses. Job-oriented approaches focus on the tasks that make up a job. One such technique is the functional job analysis (FJA; Fine & Cronshaw, 1999). This approach emphasizes tasks that are performed and how they are performed. Task statements relevant to the job are generated (e.g., “issues receipt to customer”) and clustered according to the extent to which they require working with things, data, and people. Job incumbents or subject-matter experts (SMEs; individuals who are familiar with the job, such as supervisors or I-O psychologists) rate each statement to develop a unique quantitative profile for the job.

In contrast to the job-oriented focus on tasks, worker-oriented approaches focus on the human characteristics that may be associated with successful job performance. The most frequently used worker-oriented approach is the position analysis questionnaire (PAQ; McCormick, Jeanneret, & Mecham, 1972). The PAQ is a standardized questionnaire of almost 200 items comprising five dimensions (information input, mental processes, work output, interpersonal activities, and work context). The items reflect the knowledge, skills, abilities, and other personal attributes (KSAOs) that are required to do the job well. Job incumbents or SMEs rate each item to produce a profile for the job. Since the PAQ creates a KSAO profile for each job, and because it is so widely used, the profile for any job can be compared to hundreds of jobs in the PAQ database.

The U.S. Department of Labor’s Occupational Information Network, or O*NET (http://online.onetcenter. org/), represents a hybrid approach that combines both approaches to job analysis. O*NET is a continuously updated computer-based resource for job information, providing exhaustive information for more than 800 different jobs. Each job is rated on approximately 450 dimensions reflecting job characteristics (e.g., tasks, tools, and technology) and worker KSAOs. O*NET also provides information about wages and employment trends.

Predictors and Selection

Once members of an organization have performed a job analysis, they will attempt to select people who best match the job they have classified. In a perfect world, the organization would have information about how each applicant would perform on the job (i.e., criterion data) prior to hiring. Unfortunately, that information is rarely available. Instead, the organization must rely on predictors of eventual job performance. Organizations generally use quantitative tests as predictors. As with most tests, reliability and validity are important concerns; here, criterion-related validity is a principal concern. Because they do not have criterion data on their applicants, I-O psychologists take great care to demonstrate that the predictors are related to the criteria. The correlation between a predictor and a criterion variable is called the validity coefficient (r).

A broad variety of predictor tests are available for employee selection. Although no elegant taxonomy of these tests exists, they can be classified into broad categories: cognitive ability tests, integrity or honesty tests, interviews, personality tests, psychomotor tests, biographical data, assessment centers, and work samples (Levy, 2006). The tests in the first five categories are probably familiar to most students of psychology, but the latter three may require some description. Biographical data include both the “application blank” that almost all organizations require and biodata (often obtained from “biographical information blanks”). Whereas an application blank contains information like education and work history, a biographical information blank is typically much longer and addresses a broad range of issues, including interests, preferences, and experiences. For instance, the question “To what extent have you traveled outside of the United States?” may be used to indicate the range of experience the applicant has had with people of different backgrounds.

Assessment centers use multiple assessors to evaluate several job candidates simultaneously on a series of standardized exercises, perhaps over a period of several days. Exercises are designed to simulate actual job activities and are used frequently to identify managerial talent. One of the most commonly used exercises is the in-basket test. Candidates pretend they are starting a new job where several items (e.g., memos, schedules, messages, plans) have been placed in their in-baskets. Candidates work with these items (e.g., drafting a response to an e-mail, setting the item aside for later) and assessors score their actions.

Work samples differ from the previous tests in that they utilize actual job behaviors rather than predictors of these behaviors. For example, a forklift operator might be asked to transfer loaded pallets from warehouse floor to truck trailer. A trained observer would watch the candidate’s performance and score it for accuracy, speed, and other performance elements.

In all cases, I-O psychologists take care to assess the criterion-related validity of the predictor tests they use. Predictors must be carefully tested for individual jobs through validation studies, but Schmidt and Hunter (1998) have reported meta-analytic validity data for various predictors based upon research published over 85 years. They concluded that general cognitive ability is the best predictor, based on its validity coefficient (r = 0.51) and its low cost to assess. Work samples also have a high validity coefficient (r = 0.54), but they are more expensive and can only be used for candidates with previous experience and skills. Interviews can be good predictors, with the validity of structured interviews (r = 0.51) exceeding that of unstructured interviews (r = 0.38). Integrity tests (r = 0.41), assessment centers (r = 0.37), biodata (r = 0.35), and some personality tests (e.g., conscientiousness, r = 0.31) have also been found to have good validities (Schmidt & Hunter, 1998). Because even the best predictor, general cognitive ability, explains only about a quarter of the variance (i.e., r2 = 0.26) in performance, I-O psychologists generally use a battery of predictors to select a candidate. When several predictors are used in combination, a much greater proportion of the variance in the criterion may be explained (as long as the predictors are not too highly correlated).

In addition to the selection tools, numerous laws and court decisions guide the selection process. U.S. legislation prevents employment discrimination based upon race, color, religion, sex, or national origin (Title VII of the Civil Rights Act of 1964), age (Age Discrimination in Employment Act of 1967, amended 1968), and mental and physical disabilities (Americans With Disabilities Act of 1990). Other issues like affirmative action, sexual harassment, and reasonable accommodations for disabled workers also influence employee selection, but are beyond the scope of this research-paper.

Criterion Measurement and Performance Appraisal

The previous section described employee selection based upon predictors of performance criteria; this section describes the measurement of performance criteria and their use in the evaluation of employees. I-O psychologists use the term criteria to refer to dependent variables that serve as measures of employee performance. In addition to serving as indicators of employee success, criteria may also be used to assess training needs, as a basis for decisions such as pro-motions or terminations, and for feedback to employees.

Though performance may seem simple enough to conceptualize for some jobs (e.g., How many widgets does an assembler construct?), criterion measurement is quite difficult for most positions (e.g., What are the performance criteria for a professor?). For most jobs, multiple criteria exist, and different criteria may be appropriate for different purposes. If a professor’s duties include teaching, research, and service, then certainly no single criterion will work for each of these three areas. Further, the criteria may change over time. For instance, a worker will be expected to engage in different activities after a promotion from cashier to shift manager.

I-O psychologists use a variety of different rating formats in measuring performance. For objective criteria, counting is often sufficient (e.g., number of absences, accidents, widgets produced, sales per hour in dollars). More often, however, subjective measures of performance are employed. Usually this approach involves some form of graphical rating scale (e.g., “Rate the employee’s work quality on the following scale: 1 = Poor, 2 = Fair, 3 = Adequate, 4 = Good, 5 = Excellent”). Subjective measures may be focused on behaviors that the employee performs. Behaviorally anchored rating scales (or BARS; Smith & Kendall, 1963) are similar to the graphical rating scale above except that they utilize behavioral descriptions at the anchor points rather than the more ambiguous labels. For example, instead of “Poor” on the scale above, the anchor might read “The employee produces widgets of varying quality, including those that violate established error tolerances.”

Though no measurement is free of error, the frequent use of subjective criterion measures makes the issue of error especially pertinent. Many systematic errors and biases have been identified in performance appraisal, including the halo effect (previous knowledge in one area influences judgments about other areas), leniency (an ongoing relationship or familiarity with an employee results in positively biased ratings), and the error of central tendency (avoidance of extreme ratings). Rater training and an increased reliance on behavioral indicators can be used to reduce the effects of these and other errors. Getting multiple ratings of an employee’s performance may also reduce error associated with a single source of information. A process called 360-degree feedback uses performance ratings from peers, supervisors, and subordinates on multiple performance dimensions to develop a more complete and unbiased assessment of employee performance.

Performance appraisal, like selection, involves a variety of legal issues (e.g., age, race, and sex discrimination). Guidelines for optimal performance appraisal include starting with a job analysis, providing written communication of performance standards to employees, assessing separate elements of performance individually, using multiple trained raters, allowing employees an appeal process, and keeping exhaustive documentation (see Austin, Villanova, & Hindman, 1995).

Training

Skill building, adaptation to changing conditions, and improvement of employees’ quality of work life are all reasons to conduct training. Before engaging in training, training needs are assessed. Assessment should be done at multiple levels (Goldstein & Ford, 2002). First, organizational support for training is established. Second, the needs of the organization are examined to see how they will influence training. Third, the focus of the training is defined and the methods, participants, and training protocol are developed. Fourth, KSAOs are specified for the job that is the focus of training. Fifth, employees who need training are identified. The last two steps may be unnecessary if a job analysis has been done and if a performance appraisal system with good criteria is in place.

The needs assessment should provide a basic plan for the training program and can be used to derive specific training objectives. Training objectives aid in the selection of instructional approaches and facilitate the ultimate evaluation of the training program. The major concern is transfer of training—that is, whether training influences work behavior. Training has no value to the organization unless it is brought back to the job. Instructional design, trainee factors, and other factors influence transfer (Goldstein & Ford, 2002).

Instructional design is the arrangement of the training activities. The trainer sets out a plan of instruction consistent with the training objectives, incorporating what is known about learning and cognition. For instance, research demonstrates that performance feedback throughout training is essential (Ilgen, Fisher, & Taylor, 1979) and that the use of advanced organizers (i.e., information such as text and figures presented to trainees before training) is beneficial (Mayer, 1989).

The trainer can choose from a variety of training programs, including traditional choices (classroom lecture, discussion, case studies, and role playing), self-directed approaches (readings, workbooks, and programmed instruction), training simulations (including virtual reality training), and technology-based choices (distance learning, interactive media, and Web-based instruction). The point is to select a training program that matches the training objectives and maximizes transfer of training.

Trainee factors must also be considered in developing training, particularly trainability and motivation to learn (Goldstein & Ford, 2002). Trainability is the extent to which the trainee already has some of the required KSAOs, along with the ability to develop these abilities. Many I-O psychologists advocate testing for trainability to optimize training transfer. Trainee motivation to learn must also be considered. Even though an employee may possess the KSAOs to benefit from training, the employee may not want or see the need for training. Goldstein and Ford described the unsurprising finding that trainees who are open to training benefit most. They also noted that self-efficacy (the employee’s confidence in performing some specific task), an internal locus of control (the belief that important outcomes are under the employee’s own control as opposed to outside forces), and commitment to career are all positively related to trainee motivation.

The trainer also contributes to transfer of training. Although a very diverse group of people serves as trainers in organizations, some trainer characteristics have been shown to contribute to better training outcomes. Much of the research on transfer of training attempts to generalize from academic instruction, but it is reasonable to believe that being well organized, using examples, setting difficult but attainable goals, showing enthusiasm, and encouraging participation are no less important in the training environment than in the academic classroom.

The final element of training is evaluation. Although most organizational training is evaluated, too often evaluation focuses on participant reactions to training. Less frequent is an evaluation approach based on training objectives established prior to training. Though this type of evaluation requires greater methodological savvy, management understanding, and expense (at least in the short term), it is the only way to ascertain training success. Evaluation may use a summative or formative approach. Summative evaluation focuses on whether the training objectives were achieved (e.g., if cashiers can effectively use the cash registers and software). Formative evaluation (used with summative evaluation) examines training strategies and tactics to see how they might be improved in future training efforts.

Organizational Psychology

The following model can be used to organize the “O” side of I-O psychology: Organizational Outcomes = / (Individual Processes x Interpersonal and Group Processes x Environmental Processes). In this model, the I-O psychologist tries to explain, predict, or control organizational outcomes, including productive behaviors (job performance, organizational citizenship behavior), counterproductive behaviors (turnover, absenteeism), and attitudes (job satisfaction, organizational commitment). These outcomes are a function of psychological processes at the individual, interpersonal, group, and environmental levels. Individual processes may include motivation, personality, mood, learning, and social perception. Interpersonal and group processes may include leadership, power, politics, and communication. Environmental processes may occur within the organization or outside the organization, though I-O psychologists examine internal factors such as organizational culture and change with much greater frequency than they do external factors, such as market demands or labor demographics.

Though the factors noted above do not exhaust the range of variables that contribute to the model, even these are too numerous for a chapter of this length. Thus the following section will examine only some of the most popular topics in organizational psychology.

Organizational Outcomes

Productive Organizational Behavior

One major category of productive behavior is job performance. This research-paper has already described the prediction and measurement of performance criteria, but the efforts to maximize worker performance have not been addressed. Much of this work is based on motivation and leadership (topics covered below) or on the research used to derive predictors for selection. For instance, general cognitive ability and conscientiousness predict performance. However, the effect of each of these variables is mediated by job knowledge (Schmidt & Hunter, 1998). Thus, smart people and highly conscientious people know their jobs very well, and their increased knowledge facilitates performance.

Another major category of productive behavior is organizational citizenship behavior (OCB), behavior that is not a part of a worker’s job description or formal reward system. These “extra-role” behaviors are not required, yet they do facilitate organizational performance. Several different types of OCB have been described, including altruism (i.e., providing assistance to a specific person) and generalized compliance to organizational policies, such as exemplary attendance and respect for property. Organ and Ryan (1995) demonstrated that the strongest predictors of these OCBs were leader supportiveness, employee job satisfaction, organizational fairness, and employee conscientiousness.

Counterproductive Behaviors

Not all organizational outcomes are desirable; I-O psychologists attempt to minimize counterproductive behaviors like theft, deviations in production, lateness, absenteeism, and turnover. A meta-analysis of 40 studies (Lau, Au, & Ho, 2003) identified age as a predictor of theft and lateness. Age and job satisfaction predicted negative production deviations. Absenteeism was predicted by an absenteeism norm and shortened workweeks. Another meta-analysis (Salgado, 2002) found that each of the Big Five personality factors (emotional stability, conscientiousness, agreeableness, extroversion, and openness) was a predictor of turnover.

Employee Attitudes

Job satisfaction (JS) is an employee’s attitude toward his or her job. Like all attitudes, there are affective, cognitive, and behavioral components to the attitude, but with JS, most attention has been given to the affective component. JS is probably the most frequently studied variable in I-O psychology research. Some of the research in this area focuses on general JS, whereas other research examines facet satisfaction (e.g., satisfaction with pay, coworkers, and supervision). The dominant view of JS is that it is determined by the extent to which the job provides employees with things that are important to them. However, an emerging view suggests that JS may be determined, in part, by dispositional factors (Ilies & Judge, 2003); some people may be satisfied or dissatisfied regardless of the job or its characteristics.

JS has its strongest correlations with other attitudes (e.g., for organizational commitment, r = 0.53; Mathieu & Zajac, 1990). It has weaker correlations with important outcome variables like turnover (r = -0.09; Carsten & Spector, 1987) and absenteeism (r = -0.09; Hackett & Guion, 1985). Perhaps most interesting is the I-O psychologists’ inability to find the “holy grail” (Landy, 1985, p. 410) of I-O psychology: a strong positive relationship between JS and performance. The “happy worker is a better worker” hypothesis has been popular among academics, workers, and management, but it has defied empirical verification for decades. The low correlation (r = 0.17) reported by Laffaldano and Muchinsky (1985) in their well-known meta-analysis of 74 studies is a representative finding. Recently, more sophisticated analyses have provided reason for optimism. For instance, when JS and performance are aggregated across all members of an organization, JS is more strongly related to performance (mean r = 0.26; Ostroff, 1992). Even more compelling results are obtained when researchers assess the consistency between the affective and cognitive components of JS (Schleicher, Watt, & Greguras, 2004). For individuals with high affective-cognitive consistency (e.g., employees know that their supervisor is poorly qualified and they dislike the supervisor), the JS-performance relationship is stronger (mean r = 0.55) than with low consistency (e.g., employees like their unqualified manager; mean r = -0.07). High consistency indicates that the attitude is important, resulting in a stronger JS-performance link.

Organizational commitment (OC) is another important work attitude, representing the dedication of an employee to the organization and the employee’s likelihood of continued membership. OC has three bases: affective (based on the employee’s acceptance of the organization’s goals and values), continuance (based on investment in the organization and the costs incurred by leaving), and normative (based upon a perceived obligation to stay). A review of the OC studies (Mathieu & Zajac, 1990) demonstrated that most researchers have focused on affective OC, where it has been identified as a strong predictor of turnover (r = -0.28) and intention to leave (r = -0.46), but it is unrelated to measures of performance.

Individual Process: Motivation

Why do people work? The simple answer is that they are motivated to do so. Thus, the more complicated answer must address motivation. Early approaches treated motivation as an economic issue: Pay motivates workers. Later approaches, inspired by the Hawthorne studies, took interpersonal factors into account. Current approaches to motivation may be classed into four categories: need-based theories, job-based theories, cognitive process theories, and behavioral theories (Jex, 2002).

Need-based theories attempt to identify the content of motivation. This approach is consistent with the view that JS is based on the extent to which the job provides the worker with desired things. The best-known needs-based approach to motivation is Maslow’s (1943) familiar need hierarchy. However, this theory was not originally developed to address work motivation; because it lacks empirical support, the theory’s primary value is in its inspiration of other theories. As a group, the needs theories provide a rich menu of “things” that workers may find satisfying and motivating.

Job-based approaches focus on the job as a source of motivation. The first of these approaches was Herzberg’s (1968) motivation-hygiene theory. It proposes that work is characterized by “hygiene” factors (job context elements like pay, benefits, and interpersonal relationships) and “motivation” factors (job content elements like recognition, challenge, and autonomy). Hygiene factors ensure that workers are not dissatisfied, but these factors do not lead to motivation. Motivation factors, along with the foundational hygiene factors, are the necessary conditions for motivation. Though Herzberg’s theory suffers from a lack of empirical support, it focused attention on the job itself as a source of motivation.

A more successful job-based approach is job characteristics theory (JCT; Hackman & Oldham, 1976). JCT posits that core job dimensions elicit psychological states that lead to employee and work outcomes. More specifically, if an employee holds a job that is high on a cluster of job dimensions comprising skill variety (the number of different skills the job requires), task identity (the extent to which the job results in the production of a complete work product), and task significance (the extent to which the job influences others), then the employee should experience the job as meaningful. According to JCT, the psychological state of experienced meaningfulness should result in more positive work outcomes, including increased job satisfaction, intrinsic motivation, and performance, and decreased absenteeism and turnover. Similarly, an employee whose job allows autonomy (the job dimension) should feel responsibility (the psychological state), resulting in positive outcomes. Finally, more feedback leads to greater knowledge of work results, producing positive outcomes.

Although JCT proposes strong positive correlations among the variables, these relationships are moderated by “growth-need strength” (i.e., the degree to which an employee desires personal growth and development). For high-growth-need-strength employees, the relationships in the model should be quite strong; low-growth-need-strength employees may show no relationships among these variables at all. Another moderating variable is the employee’s KSAO level. Imagine an employee who is required to perform duties without proper training. It is unlikely that this employee will experience meaningful-ness, as JCT predicts. Rather, this employee is more likely to experience frustration or anger. Though JCT has its detractors, it has received empirical support (see Parker & Wall, 1998), and it is one of the most widely used models in organizational psychology.

Cognitive process theories address the thought processes that are involved in employee motivation (Jex, 2002). Though there are numerous theories that fit this category, I will describe three of the most prominent approaches: equity theory, expectancy theory, and goal setting.

According to equity theory (Adams, 1965), a worker uses an internal calculus to produce a ratio of personal outcomes (e.g., pay, benefits, recognition) to inputs (e.g., time, knowledge, education), as well as a similar ratio for some other worker. The worker compares the two ratios and when they are roughly equal, the worker is satisfied. When the ratios are unequal, the resulting state of tension motivates the worker to engage in efforts to produce equity. Alteration of worker inputs, selection of a different comparison worker, and cognitive reevaluation of the inputs and outcomes are among the possible strategies. Though equity theory received strong support in laboratory and field studies in the 25 years following its introduction, it has generated little recent interest, possibly due to the greater utility of other approaches to motivation.

Vroom’s (1964) valence-instrumentality-expectancy model proposes that the employee makes a series of conscious decisions to maximize desirable outcomes. The first decision, called expectancy, refers to perceptions of the likelihood that a behavior will result in a particular outcome (e.g., If a salesperson learns a new product line, will the effort produce greater sales?). The second decision, instrumentality, refers to perceptions of the likelihood that the first outcome will lead to second-level outcomes (e.g., If the salesperson increases sales, will a promotion to sales manager result?). The third decision, valence, reflects the employee’s affective valuation of the second-level outcome (e.g., Does the salesperson desire the promotion?). The worker will be motivated to act only if all three decisions are positive. Recent appraisals of Vroom’s model have been supportive (Donovan, 2002), and the approach is useful in predicting organizational behavior.

Goal-setting theory’s straightforward tenet is that performance goals determine how well employees perform tasks (Locke & Latham, 1990). In particular, specific and difficult goals facilitate task performance. The amount of performance feedback, task complexity, and possession of the requisite KSAOs have been shown to moderate the relationship between goal and performance. Though goal-setting theory is rather simple, it is one of the best-accepted and well-supported approaches to motivation. It continues to generate research and has widespread applications in the workplace.

Behavioral approaches to motivation are based on the principles of operant conditioning, and because of the treatment that learning processes receive in Part VI of this handbook, they will not be covered here. Note, though, that the types and schedules of reinforcement and punishment work in organizations as they do in other settings. Behavioral principles are usually easily implemented in organizations, and the research is generally supportive of organizational behavior modification (or OBM, as the behavioral approach is known in many organizations). It should also be noted that a frequent criticism is that OBM works best for relatively simple behaviors.

In general, the research on work motivation leaves something to be desired (with the exceptions of goal setting and OBM). Though work motivation is better understood today than four decades ago, a clear understanding has yet to emerge. Research continues, but commentators have noted a trend toward increasing fragmentation in the motivation literature (Ambrose & Kulik, 1999), which may hinder future attempts at integration of this important area of organizational psychology.

Interpersonal Process: Leadership

The search for primary components of leadership is probably as old as civilization, and it is among the most written-about topics within organizational psychology. Three traditional approaches shape our current understanding of leadership, though none of them is currently dominant. Instead, a number of “alternative” approaches receive the bulk of the attention.

Historically, a “great man” approach to leadership was assumed. The old maxim “Great leaders are born, not made” expresses this view. I-O psychologists sought to identify individuals who would emerge as leaders by examining employee personality traits. Though the approach had some promise, early failures and the rise of behavioral theories in psychology contributed to a long period of relative dormancy. Recent research has revitalized the trait approach. For instance, traits such as high energy, stress tolerance, integrity, emotional maturity, and self-confidence can be used to predict managerial effectiveness (Yukl & Van Fleet, 1992).

The leadership style approach, focusing on leader behaviors, offered an alternative to traits. Among the most successful of these approaches are the Ohio State studies (e.g., Fleishman & Harris, 1962) that represent leadership style on two dimensions: initiating structure (i.e., task-oriented behaviors) and consideration (i.e., people-oriented behaviors). A leader was characterized as “high” or “low” on each dimension, resulting in four combinations: the leader high on both dimensions was said to be best. Though popular, the leadership style approach failed to receive empirical support, and it was criticized for its failure to consider situational characteristics that may moderate the relationship between leader behaviors and success.

The third view of leadership, the contingency approach, includes many popular theories, each emphasizing different situational characteristics. Hersey and Blanchard’s (1972) situational leadership theory is almost identical to the Ohio State approach except that the suggested leader style is not always high-task, high-relationship. Instead, the leader should attend to follower readiness (the ability and willingness of subordinates to be autonomous). When workers have little readiness, a “telling” (high-task, low-relationship) leadership style is appropriate. Increasing levels of readiness can result in “selling” (high-task, high-relationship), “participating” (low-task, high-relationship), or “delegating” (low-task, low-relationship) leadership styles. Another of these approaches, Fiedler’s (1967) “least-preferred-coworker” theory, stresses the importance of the leader-subordinate relationship, task structure, and leader position power. The most and least favorable situations indicate a task-oriented leader style, with moderately favorable situations indicating a relationship-oriented approach.

None of the contingency approaches enjoys strong empirical support. The failure of these approaches has led researchers to call for other approaches to the study of leadership. Some of these suggestions focus on more limited power and influence techniques or rewards and punishment as alternatives to the more global leadership domain. Other suggestions advocate examination of charismatic and transformational leadership. Both of these leadership approaches emphasize leader attempts to create emotional arousal among employees to produce change. Still other suggestions urge the expansion of the leadership construct beyond national and cultural boundaries as technology and globalization change organizational life. These new approaches to leadership are garnering considerable attention in the research literature, and will doubtlessly continue to do so.

Environmental Process: Organizational Culture

There are dozens of definitions of organizational culture. The theme that unites most of these definitions is that attitudinal and behavioral norms are shared among organizational members. One straightforward definition that captures the theme is that culture is how we do things (Deal & Kennedy, 1982). Here is a more comprehensive offering: Culture is “(a) a pattern of basic assumptions, (b) invented, discovered, or developed by a given group, (c) as it learns to cope with its problems…, (d) that has worked well enough to be considered valid, and (e) is to be taught to new members as the (f) correct way to perceive, think, and feel” (Schein, 1990, p. 111).

Schein (1990) posited that culture manifests itself on three levels: artifacts, values, and assumptions. Artifacts are tangible manifestations of culture, like symbols, language, and stories. For example, imagine a company whose “star” logo represents excellence to its employees. Artifacts represent underlying values of the organization. At the imaginary company, excellence is highly valued and permeates all its activities. The assumptions are even more foundational and, for Schein, they are deep-seated, taken for granted, and rarely addressed. Employees of the imaginary company assume that excellence provides the organization with a competitive advantage and a path to profitability.

Several issues make research on organizational culture difficult. First, though Schein’s (1990) approach has been influential, there are also other models of culture. For instance, there are approaches based on differences in national cultures. Second, though an organization may have a shared culture, subcultures exist. Different units (e.g., departments, geographical locations, hierarchical levels, professions) within the organization may have slightly different artifacts and values. Third, and perhaps most difficult, is the distinction between culture and climate. The consensus among I-O psychologists is that though these two constructs overlap, they are distinguishable. The essential difference is that culture reflects the more deeply held values and assumptions, and climate reflects the more consciously perceived elements of the internal environment that are under the organization’s control. Unfortunately, these two constructs are not always clearly differentiated in the empirical literature, and their measurement (e.g., discriminant validity) can be particularly troubling.

The most important issue, however, is whether culture has measurable effects. Regarding organizational performance, the most consistent finding is that there does not seem to be one “right” culture. Successful organizations have widely varied cultures (even those in the same industry). In what is probably the best study of the issue, Kotter and Heskett (1992) found that organizations with “adaptive” cultures (e.g., valuing people and change) outperformed those with “unadaptive” cultures (e.g., valuing order and risk reduction) on a number of financial indices. However, numerous authors have suggested that the performance effects of culture may be mediated by other (yet unidentified) important variables. Culture should also have measurable effects on a number of other important organizational outcomes. For instance, authors have suggested all of the following as reasonable outcomes of organizational culture: recruitment, retention/turnover, job satisfaction, employee health, and well-being. Though research has investigated all of these outcomes, there are far too many inconsistencies in the results to offer any strong conclusions.

Summary

I-O psychology is well established within psychology, and it is working to raise its profile elsewhere. Educational institutions are preparing people for work in I-O psychology through thoughtfully designed training programs, and graduates are finding good employment in education, business, and government. Researchers are engaged in the production of new knowledge, and practitioners are engaged in its application for the betterment of organizations and their members. In short, I-O psychology is healthy and viable at the start of the 21st century.

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