JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT
2022, VOL. 42, NO. 3, 203–209
https://doi.org/10.1080/01608061.2022.2029797

Revisiting the Past and Selecting for the Future: AnIntroduction to Handbook of Organizational Performance:
Foundations and Advances
Douglas A. Johnson

aand C. Merle JohnsonbaWestern Michigan University, Department of Psychology, Kalamazoo, Michigan, USA; bCentral Michigan
University, Department of Psychology, Mount Pleasant, Michigan, USAABSTRACTKEYWORDS

Both business and behavior can be understood through the lensof variation and selection, with adaptive approaches prosperingand other approaches perishing. The Handbook of
Organizational Performance: Foundations and Advances series
seeks to lay out the groundwork and direction for our field toprosper, as understood by many expert contributors in the fieldof organizational behavior management. Other worthwhile
directions beyond the series are also noted, all guided by thenotion that a science of behavior is not only possible, but alsoa critical missing component from the typical understanding of
how to best operate a business so that it survives.

Organizational behavior
management; selectionism;
behavior analysis

Behavior analysis, and by extension organizational behavior management(OBM), has been guided by a selectionist paradigm since the conceptualbasis for B. F. Skinner’s science of behavior was first developed (Palmer &Donahoe, 1992; Skinner, 1945). Behavior is a product of selection contin­
gencies operating at three levels (Skinner, 1981, 1987, 1990): biological(natural selection of species), psychological (contingencies of reinforcement
responsible for behavior of individuals), and anthropological (evolution ofcontingencies that maintain social environments). C. M. Johnson et al.
(2001) proposed an analogous paradigm for organizational performance,suggesting three levels of variation and selection: economics (natural selec­tion of organizations that survive competition in the marketplace), behavior
analysis (contingencies of reinforcement for individual and group behavior
within and between organizational settings), and social environments (orga­
nizational culture, verbal behavior, laws, workplace rules, policies and orga­
nizational practices). Two decades later there appears little reason to dismiss
this evolutionary model of organizational performance. Organizations, beha­viors, and social practices change over time. The adaptive ones flourish or atleast maintain; those that do not evolve in changing environments undergo
CONTACT Douglas A. Johnson
University, Kalamazoo, MI 49008© 2022 Taylor & Francis

behavioranalyst@gmail.com

Department of Psychology, Western Michigan

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extinction. Although the scale of behavior is clearly vast and the units ofanalysis change across disciplines, variation and selection remains a constantshaping process across the levels. OBM often has needed to straddle thefence between multiple levels, looking at both individual/performer andcollective/organizational levels (or contingencies and metacontingencies if
one prefers).
This current series is an evolution of the Handbook of Organizational
Performance: Behavior Analysis and Management (C. M. Johnson et al.,2001), which itself was a descendant of the two original OBM handbooks
published in 1982 (Frederiksen, 1982; O’Brien et al., 1982). After 40 years ofprogress, OBM has grown large enough to permit tremendous variability. In
fact, this was one of the greatest challenges as the editors sought to apply theirown selection pressures to the contributions and topics (i.e., deciding what toinclude from the many possibilities, constrained by practical limitations).
Despite the extensive contributions of many authors, many topics will regret­tably have to be left untouched. Such a range that is incorporated in thehandbook would likely be pleasing to Skinner and other pioneers in behavior
analysis, who always saw our science as broad and far-reaching; not a science
to be applied to just a handful of demographics or concerns (Skinner, 1953).
We are honored by the contributors willing to share their hard-earned exper­
tise and the input of the editors, associate editors, editorial review board
members, and guest reviewers of the Journal of Organizational Behavior
Management (JOBM).
To capture the aims of our many contributors and to ensure a continuity
across series, we settled on the title of Handbook of Organizational
Performance: Foundations and Advances. The subtitle is intended to empha­
size the need to look both forward and backward. Foundations tell us where weoriginated and provide direction as we continue forward. In fact, it is tradi­tional for OBM handbook introductions to summarize how the field came tobe (Houmanfar et al., 2021; C. M. Johnson et al., 2001; Wine & Pritchard,2018). Such an approach orients readers and honors the architects. We will not
dwell on such points here for fear of stealing the thunder from contributions tothe series, except to note that several will lay the groundwork with theircoverage of the history of OBM pioneers, our methodology, our terminology(and thus our concepts and principles), and various motivational and diag­nostic tools. Of course, our foundations include the wealth of literature builtup over 40+ years, informing topics such as training, goal setting, feedback,safety, health, etc.
Advances tell us about the new territory we have recently entered andterritory into which we should be venturing. Looking forward is always
fraught with difficulties, as legions of past amateur futurists can surely attest.
Beyond the many suggestions mentioned by our contributors, there remaina few threads that have stuck out to us as worth pulling.

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One area of tremendous growth potential is providing support for otherbehavior analysts as they forge new organizational ventures. The most obvious
candidate is behavior analysts providing professional services related toAutism Spectrum Disorder. As these services have expanded, organizations
have emerged with all the employee-related needs of any other organization.
Most of the behavior analysts managing such organizations lack formal train­
ing in OBM (or perhaps have attended only a workshop or two). As such,collaborations with the human service industry would be wise, or else they will
surely reinvent the OBM wheel without us and our base of empirical findings.
It would help broaden the scope and mission of our field if we could findways to contribute to the broader culture besides traditional management
initiatives. How might OBM support union concerns? How can we contributeto diversity of the workforce or the development of professional skills ofemployees? How can we prevent layoffs or support former employees transi­
tioning between jobs?
While on the topic of unemployment, the nature of work demands willundoubtedly change and therefore we may not be able to rely on the depen­
dent measures of years gone by. For example, increasing automation will
eliminate many jobs and types of work, but can rise to new jobs and emphases(Asimov, 1991; D. A. Johnson & Akpapuna, 2018). There will likely be
a greater need for behavior analysts to understand creativity and innovation(Bradley & Johnson, in press). Quoting Jack Welch, former chief executive
officer of General Electric, in his annual report, Andersen (2020) described
how organizations change or die and new forms of work develop.
“When the rate of change inside an institution becomes slower than the rate of changeoutside, the end is in sight. The only question is when. Learning to love change is an
unnatural act in any century-old institution” (Andersen, 2020, pp. 342-343).

OBM professionals will need to continually refine their verbal skills to become
more proficient in marketing and outreach. No doubt this will require us tobetter understand our audiences, not just our products and services, no matter
how proud we may be of the processes we have developed. We need tounderstand and exhibit persuasive behaviors at the performer level, organiza­
tional level, and the broad cultural level.
When mapping out our plans for moving forward, it is probably wise tomark our progress by three questions: Where are we going? How shall we getthere? How will we know we have arrived? (Brethower & Smalley, 1998;
Mager, 1997). This introduction and the collection of articles point out several
possible directions. The foundations of our field will undoubtedly provide themeans for how we will get there. But how will we know we have arrived? As
Dale Brethower mentioned in his contribution (who unfortunately passed
away several months after the completion of the manuscript), we can “let thedata be the guide!” (Brethower et al., in press). However, not just data alone,

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Low

Frequency

Highbut a thoughtful and critical appraisal of the data. To illustrate how data may
impact decision making differentially, let us consider the landmark study by
Tversky and Kahneman (Kahneman won the Nobel Prize in 2002 for his workin economics. Tversky passed away; the Nobel Committee does not presentawards posthumously).
Tversky and Kahneman (1974) were teaching flight instructors in Israel tominimize criticisms in favor of rewards supported by empirical evidence. The
flight instructors disagreed and noted that when they praised trainees for goodlandings, trainees typically performed worse the next time. When the instruc­tors harshly criticized poor landings, their trainees usually performed betterthe next opportunity. Thus, the flight instructors concluded that praise wasdetrimental to learning and verbal punishment was beneficial. Tversky andKahneman suddenly realized that the statistical principle of regression to themean was responsible for the flight instructors’ erroneous conclusion. That is,events that are outliers from typical performance are more likely to return toaverage performance the next time (see, Figure 1). For example, poor or
exceptionally great athletic performances are likely to return to a typicalperformance for that individual or team the next game. Similarly, exception­
ally hot or cold days are likely to return to average highs or lows for that season
the next day. Thus, climate change is gradual, many people fail to detect it(Easterling et al., 2000). When learning and behavior change are incremental
and relatively slow, extreme outcomes are likely to return to near average
performance for that individual. Regardless of whether the flight instructor
yelled at the trainee or put a poor landing on extinction, the next time thePoor

Average

Performance

Figure 1. Regression to the mean for performance.

Excellent

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207

trainee was likely to improve. Conversely, if flight instructors praised greatlandings, trainees were likely to execute worse in comparison the next timeand return to just above or near their average performance. Hence, criticizing
flight instructors was being reinforced and the delivery of praise for outstand­ing performance by trainees was not reinforced by the statistical principle ofregression to the mean due to the slow improvements on this complex task.
Couple this regression to the mean with the immediate, yet short-term, change
in employee behavior and it becomes obvious why aversive control is pre­valent. Even though experts have long since warned about the perils ofexcessive aversive techniques (Azrin & Holz, 1966; Sidman, 1989) and thetrends of data overall supported the use of praise, the data based upon theimmediate and direct experiences of the instructors supported the use ofcriticism.
Variation and selection strike again – we are swimming upstream when weadvocate the use of reinforcement over punishment to those who are not wellversed in behavior analysis research unless shaping new behavior is rapid andaverage performance is improving dramatically. Extinction, correcting, anddifferential reinforcement for alternative behaviors are more humane andeffective for long-term behavior change when motivating employees to workin organizational settings (Daniels & Bailey, 2014). Reinforcement contingen­cies improve and sustain performance over time, but most managers andsupervisors do not systematically collect data on the behavior of their sub­ordinates. There might be well-developed outcome measures or results of staff
performance, but these are frequently tied to the bottom line in a loose mannerat best. We need to understand these various streams of data and plan
accordingly. To advance the field, we need to push beyond the normal rangeof variability into new territory. The world of business is a world flooded withnumerical measures. Net cash from operations, optimal size for inventory,
present value of a growing perpetuity, internal rate of return, acceptable
tolerance levels for machinery, and other precisely calculated quantifications
are routinely developed. However, traditional business metrics are largely
restricted to processes and products. Metrics involving people are rarely
used outside the confines of paychecks, attendance, delivery dates, and infre­
quent subjective performance appraisals. When it comes to actual day-to-day
workplace behavior, the level of precision approaches zero. Instead, vague
theories of behavior lurk, outflowing with constructs such as emotional intel­
ligence, drive, vision, motivation 3.0, personality, self-knowledge, level 5
leadership, and many, many more (the list is exhausting and ever-growing).
As such, products and processes are planned, with the hope that annoying
human variation does not get in the way and that our exhortations and threats
may somehow push the right secret internal button within our employees. As
one of the first author’s business professors once put, when responding toa question of how we might prevent injuries and deaths when employees hide208

D. A. JOHNSON AND C. M. JOHNSON

unsafe performance, “Well, that’s human behavior and there’s nothing you
can do about that. People will just do things wrong sometimes and you can’t
stop them.” We respectfully disagree with such a fatalistic assumption. The
science of behavior shows us how to understand human behavior with thesame degree of precision as the other facets of business. This series is a solid
start detailing how to achieve this objective. Of course, there remains much todo in the world of work. Join us as we traverse this expedition, varying
directions and selecting many prosperous paths.

Disclosure statement
No potential conflict of interest was reported by the author(s).

ORCID
Douglas A. Johnson

http://orcid.org/0000-0002-7802-3566

References
Andersen, K. (2020). Evil geniuses. Random House.
Asimov, I. (1991). Robot visions. Roc.
Azrin, N. H., & Holz, W. C. (1966). Punishment. In W. K. Honig (Ed.), Operant behavior: Areasof research and application (pp. 380–447). Appleton-Century-Crofts.
Bradley, J. L., & Johnson, D. A. (in press). Creating creativity: A behavior analytic approach.
The Psychological Record. https://doi.org/10.1007/s40732-021-00480-z
Brethower, D., & Smalley, K. (1998). Performance-based instruction: Linking training to busi­
ness results. Jossey-Bass/Pfeiffer.
Brethower, D. M., Dickinson, A. M., Johnson, D. A., & Johnson, C. M. (in press). A history oforganizational behavior management. Journal of Organizational Behavior Management.
https://doi.org/10.1080/01608061.2021.1924340
Daniels, A. C., & Bailey, J. S. (2014). Performance management: Changing behavior that drives
organizational effectiveness (5th ed.). Performance Management Publications.
Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A., Karl, T. R., & Mearns, L. O.
(2000). Climate extremes: Observations, modeling, and impacts. Science, 289(5487),
2068–2074. https://doi.org/10.1126/science.289.5487.2068
Frederiksen, L. W. (Ed.). (1982). Handbook of organizational behavior management. John
Wiley & Sons.
Houmanfar, R. A., Fryling, M., & Alavosius, M. P. (Eds.). (2021). Applied behavior science inorganizations: Consilience of historical and emerging trends in organizational behavior
management. Routledge.
Johnson, C. M., Redmon, W. K., & Mawhinney, T. C. (Eds.). (2001). Handbook of organiza­
tional performance: Behavior analysis and management. Haworth.
Johnson, D. A., & Akpapuna, M. (2018). A pragmatic approach for building motivation topromote employee creativity and organizational innovation. In B. Wine & J. K. Pritchard(Eds.), Essentials of Organizational Behavior Management (pp. 242–273). Hedgehog
Publishers.

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

209

Mager, R. (1997). How to turn learners on . . . without turning them off. Center for EffectivePerformance.
O’Brien, R. M., Dickinson, A. M., & Rosow, M. P. (Eds.). (1982). Industrial behavior modifica­
tion: A management handbook. Pergamon Press, Inc.
Palmer, D. C., & Donahoe, J. W. (1992). Essentialism and selectionism in cognitive science andbehavior analysis. American Psychologist, 47(11), 1344–1358. https://doi.org/10.1037//0003066x.47.11.1344
Sidman, M. (1989). Coercion and its fallout.
Skinner, B. F. (1945). The operational analysis of psychological terms. Psychological Review, 52(5), 270–277. https://doi.org/10.1037/h0062535
Skinner, B. F. (1953). Science and human behavior. Macmillan.
Skinner, B. F. (1981). Selection by consequences. Science, 213(4507), 501–504. https://doi.org/10.1126/science.7244649
Skinner, B. F. (1987). Upon further reflection. Prentice-Hall.
Skinner, B. F. (1990). Can psychology be a science of mind? American Psychologist, 45(11),1206–1210. https://doi.org/10.1037/0003-066X.45.11.1206
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases.
Science, 185(4157), 1124–1135. https://doi.org/10.1126/science.185.4157.1124
Wine, B., & Pritchard, J. K. (Eds.). (2018). Organizational behavior management: The essentials.
Hedgehog Publishers.