JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT
2020, VOL. 40, NOS. 1–2, 140–150
https://doi.org/10.1080/01608061.2020.1746476

The Impact of Authority Relations and Feedback Delivery
Method on Performance
Songhwa Chaea, Lauren M. Eagleb, Douglas A. Johnsonb, Kwangsu Moona,
Eunju Choib, and Shezeen OahaaChung-Aug University, Department of Psychology, Seoul, Korea; bWestern Michigan University,
Department of Psychology, Kalamazoo, Michigan, USA
ABSTRACTKEYWORDS

The proliferation of technology has been changing feedback
delivery methods in organizations. However, the effectivenessof feedback delivery methods can vary depending on social
dynamics (e.g., authority relations) in the organization. The current study was designed to examine the impact of authority
relations and feedback delivery methods on performance.
A total of 120 participants were recruited to work ona simulated cell-phone assembly task and were exposed to oneof the four feedback conditions: (a) authority figure with face-toface feedback, (b) authority figure with e-mail feedback, (c) nonauthority figure with face-to-face feedback, and (d) non-authority
figure with e-mail feedback. Results showed that while both
feedback delivery methods resulted in high performance withthe presence of an authority figure, only face-to-face feedback
resulted in high performance with a non-authority figure.
Practical considerations for effective feedback delivery methods
in relation to authority figures are also discussed.

Authority relations; feedback
delivery system; face-to-facefeedback; e-mail feedback

The modern workplace often places a heavy combination of competing
duties related to employee supervision and administration upon managers.
One result of these multiple demands is that administrative workload canoften interfere with opportunities to facilitate leadership practices (Wallo,
Ellstrom, & Kock, 2013), especially considering the long hours required of
the typical manager (U.S. Department of Labor, 2019). This could unintentionally contribute to a “neglectful” environment, one in which engaging in
administrative work takes precedence over monitoring employee performance. It may be that the only time performance monitoring trumps administrative tasks is when performance drops below a certain standard, in which
the manager may face repercussions from their own supervisor. When thishappens, managers will likely use aversive control because it influences
performance in the desired direction quickly so that they may return totheir other responsibilities in a timely fashion. The manager may berate the
CONTACT Douglas A. Johnson
behavioranalyst@gmail.com
University, Box 20415, Kalamazoo, MI 49019© 2020 Taylor & Francis

Department of Psychology, Western Michigan

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

141

employee or impose threats through a series of progressively worsening
discipline steps (Grote, 2006). Eventually, if the employee does not improve,
they may be terminated. These interactions may lead to employee turnover,as captured by the coined phrase “You don’t quit your job, you quit yourboss,” an adage that is supported by many research studies (Greenbaum,
Mawritz, & Piccolo, 2012; Mardanov, Heischmidt, & Henson, 2008; Palanski,
Avey, & Jiraporn, 2014). In cases where the employees do not exit thecompany, these contingencies motivate employees to perform just wellenough to avoid these aversive consequences and no more (Daniels, 2016).
For companies that try to avoid the pitfalls of an overly punitive system, there
is a need for an intervention that is not too time intensive or cost prohibitive.
Fortunately, feedback represents a potential solution to fit these constraints.
Feedback is a communicative variable that induces change by informing theemployee on how they are currently performing (Daniels & Bailey, 2014).
Feedback has been shown to be effective in enhancing employee performancessuch as productivity (Berger & Ludwig, 2007; Goomas, 2010), quality management (Tittelbach, Fields, & Alvero, 2008), customer-contact service (Brown,
Malott, Dillon, & Keeps, 1980; So, Lee, & Oah, 2013; Wiesman, 2006), and safety
behavior (Lee, Shon, & Oah, 2014; Moon & Oah, 2013) in various organizationalsettings. Feedback also provides the opportunity to embed social reinforcers into
feedback sessions, such as congratulating or thanking an employee. This not
only influences positive behaviors, but also attributes positive regard on behalf ofthe supervisor for recognizing the employee’s individual efforts and accomplishments. Such conditions make it more probable the supervisor themselves will
become a conditioned reinforcer, making their presence in the workplace moreenjoyable for the employees. The positive exchange of communication is likely
to improve morale and job satisfaction during these interactions (Anseel &Lievens, 2007; Sommer & Kulkarni, 2012). Finally, feedback can be delivered
quickly and at low cost. Due to such benefits, feedback may represent a plausible
solution for managers to use in order to optimize employee performance.
The most traditional method of feedback is face-to-face feedback, such as
having a one-on-one meeting or review. One reason face-to-face feedback
may be favored is that managers can add in impromptu evaluative statements
regarding the employee’s performance, which has been demonstrated asimportant in previous research (Johnson, 2013). Rule-governed behavior
may play a role as well (Malott, 1992), especially if employees describe
contingencies differently depending on the delivery method (e.g., “I betterpay attention to what he’s saying because it was important enough to tell mein person”). There is also a possibility that social reinforcement – through eye
contact, care, conversation, and other similar interactions between a feedback
provider and recipient – is better facilitated during a face-to-face interaction.
However, feedback does not necessarily have to be face-to-face to be effective.
As part of an effort to reduce errors in assembling orders in a warehouse,

142

S. CHAE ET AL.

a study by Berger and Ludwig (2007) used voice-assisted technology headsets
connected to worker’s waists to deliver feedback. This simple intervention
produced a reduction of errors that resulted in a sizable financial impact forthe company. The use of such voice-assisted headsets suggests that physicalpresence of the feedback giver may not be necessary to produce significant
changes in performance.
Modern-day advances in technology may also aid in closing the temporalgap between performance and feedback. Many organizations presently use
feedback consisting of weekly meetings, usually led by or in the presence ofa supervisor. Given that managers are already struggling to make time fora myriad of assigned duties, technological advances present the possibility for
improving performance without a significant investment of time. Moreover,the instantaneous properties of certain technology allow feedback to bedelivered more immediately and thus allows for the potential to exert evengreater control over the performance than the typical end-of-the-week meeting may. This raises the question about the degree to which the presence ofthe feedback provider will have a differential impact on performance, if at all.
Feedback is already being used in performance management interventions
in many different forms of delivery, modality, and content in efforts toimprove performance management. Feedback can vary widely in terms ofthe conditions under which it may be delivered, who is delivering it, how it
is being delivered, and when it is delivered (Johnson, Rocheleau, & Tilka,
2015; Palmer, Johnson, & Johnson, 2015). As such, social dynamics may
impact the effectiveness of feedback. Automation of feedback delivery may
represent an improvement for the expenditure of time, but such impersonal
and automatic feedback may not be as effective as feedback delivered
directly by a manager. Social contingencies, especially the social relations
between authority figures and subordinates, likely exert a powerful effect inmost organizations. Even for a new employee, it is quite possible thatcompliance with a new authority figure will still be quite powerful. Muchof this can be attributed to common learning histories in most cultures.
Most members of the prevailing culture learn that compliance with therequests of parents or other caregivers will result in approval and otherreinforcing outcomes, whereas noncompliance with the requests of parents
or other caregivers will result in disapproval and other punishing outcomes.
Similar learning outcomes likely occur with other powerful individuals in
the child’s life, such as teachers, doctors, and law enforcement officers, suchthat evocative effects extend to authority figures in general (Guerin, 1994).
Authority figures become a powerful stimulus class and the relevant control
continues to be maintained during adulthood thanks to managers, professors, and other figures with the necessary social status to readily confer
powerful consequences. Regarding the degree to which the contingencies
involving authority figures extends, it is unknown whether this generalizes

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

143

immediately to any new figure higher in organizational status or if somehistory of differential consequences with the authority figure is needed toexert control.
In summary, people quickly learn to emit behaviors that have been
specified by verbal stimuli from an authority figure. The evocative power ofsuch verbal stimuli may depend upon whether contextual variables establish
the requestor as sufficiently similar to past authority figures and the physicalproximity of such authority figures. The method of feedback delivery may
have a modulating effect on the stimulus control exerted by authority. As
such, the present study investigates the impact of different feedback delivery
methods. Furthermore, the study also examines the impact of feedback fromsomeone who was already established as an authority figure and someone
without such a prior history.
MethodParticipants and setting

Participants consisted of 120 undergraduate and graduate students froma university in South Korea. Participants were recruited through on- andoffline bulletin boards of the university. The study was conducted insidea university computer lab with 50 workspaces.
Experimental task and procedure

The experimental task involved a computer program designed to simulate
a production task that had been used in previous research (Choi, Johnson,
Moon, & Oah, 2018). Participants were required to assemble realistic components of virtual mobile phones. During assembly participants had two
opportunities to visually inspect their work through a quality control
check. Once the participant clicked the on-screen button labeled “Quality
Control,” the phone component would display as correct or faulty (if missing
an element or in nonstandard configuration). Participants then had theoption to compare their phone against a correct model for 1.25 seconds byclicking the “Model Stimulus” button on the screen. If the participant
detected an error, they could click over the faulty element to create a red
circle over it. The participant would then return to the assembly screen. Oncecompleted, the participant would click the “Next” button to submit theassembled phone and begin the next. Examples of the task during assemblyand quality control are represented in Figure 1.
The study consisted of four 30-minute sessions involving one baseline andthree experimental sessions. Prior to the sessions, participants attended anorientation involving informed consent and a demonstration of the

144

S. CHAE ET AL.

Figure 1. Example of virtual mobile phone assembly program.

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

145

experimental task. After the last session concluded, participants were compensated with ₩20,000 (~18 U.S. dollars at the time of rate conversion) anddebriefed on the entire experiment.
Independent and dependent variables

The independent variables in this study were 1) the nature of the relationshipwith the provider of feedback (established relationship with authority figure,no existing relationship with authority figure) and 2) the means throughwhich performance feedback was delivered to the participant (e-mail, face-toface). The participants were randomly assigned to one of the feedback
conditions. Half of the participants had a preexisting relation with theauthority figure and therefore random assignment could not be utilizedwith this variable. The dependent variables in this study were total number
correct and percentage correct during the assembly task.
Experience with the feedback provider as an authority figure
An established relationship with an authority figure was defined as prior or
current enrollment in an undergraduate course (based on recruitment survey) in which the experimenter served as the professor. Although no particular interactions were scripted or preplanned to establish such a historical
relationship, it was presumed that the professor belonged to the stimulus
class of “authority figure” because of the power of the professor to assign
content, set deadlines, and evaluate academic work as part of the coursework.
Means of feedback delivery
Face-to-face and e-mail feedback were delivered by the individual who had
been established as an authority figure for half of the participants. If assigned
to the face-to-face condition, the participant was directly handed written
feedback from the authority figure at the beginning of each experimental
session based upon the participant’s performance during the preceding session. The authority figure did not provide any other comments or non-verbal
communication such as facial expressions. If assigned to the e-mail condition, participants were prompted to check their e-mail containing the feedback, which was sent about five minutes prior to their arrival. The name of
the authority figure was clearly visible as the sender’s e-mail address. The
feedback consisted of the total number of phones assembled per model, thenumber of phones accurately assembled per model, and errors made. An
example of such feedback would be as follows: “Out of 52, 40 were accurately
assembled. In details, 11 out of 16 in Vega (accuracy 69%), 16 out of 18 in
Galaxy (89%), 13 out of 18 in iPhone (72%) were accurately assembled.
Particularly in Galaxy, 0 out of 18 had sequence error, and 2 out 18 had
quality control error. Thank you for participating in the work.”

146

S. CHAE ET AL.

Results and discussion
Figures 2 and 3 show the number and percentage of correctly completed
work tasks across experimental sessions. Results indicate that e-mail feedback
from a non-authority figure resulted in consistently lower performance thanother experimental conditions. There was consistent overlap in performancefor the remaining three feedback conditions. These differences were also seen
with the overall mean performances across sessions for authority/face-to-face(48.4; 59%), authority/e-mail (46.4; 60%), non-authority/face-to-face (45.3;59%), and non-authority/e-mail conditions (37.8; 45%).
Participants who received e-mail feedback from a non-authority figure had
lower levels of performance compared to other forms of feedback delivery.
This suggests that an established relation with an authority figure can maximize performance regardless of the method of feedback delivery, but thismay not hold true with non-authority figures trying to utilize feedback
through other means. This also supports the notion that not all forms ofcommunication will be equally effective for all types of feedback providers.
This may be due to the possibility that historically, additional interactions are
involved or at least perceived, within the context of face-to-face feedback.
Although follow-up interactions are possible via e-mail, it is unlikely thatthey can compare to the immediate and dynamic nature of an in-person
verbal exchange (this point may apply to both authority and non-authority

Figure 2. Number of correctly completed work tasks across sessions.

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

147

Figure 3. Percentage of correctly completed work tasks across sessions.

figures in actual work settings). This implies that although face-to-face may
be the more time-consuming method of feedback delivery, the changes
observed in employee performance may be worth the supervisor’s investment
if they do not already have an established history with the recipient offeedback. This study also suggests that other modalities of delivering feedback can be safely utilized if the individual does have an established history
with the supervisor, as suggested by the effectiveness of e-mail feedback froman authority figure. In short, it appears that either face-to-face feedback or an
established authority relation in general are important, but a combination ofboth may be unnecessary.
Several limitations should also be addressed. For example, it was assumed
that the professor would be seen as an authority figure by the participants,
but data were not collected to verify this. Future research could address this
via a simple Likert survey inquiring about the degree to which the participants perceived the professor as an authority figure. Furthermore, the natureof the authority relations may limit the generality of the findings in thata relation based on professor and student interactions may not perfectly
simulate a relation based on supervisor and employee interactions. Also,
there may be cross-cultural limitations if the typical evocative properties ofauthority figures within South Korean culture does not adequately capture
the evocative properties of authority figures in the cultures of the UnitedStates and elsewhere. In addition, preemptive data regarding participants’148

S. CHAE ET AL.

individual learning history with authority figures in general would have been
beneficial. This information would have helped with the analysis of thedifferences in performance between the non-authority versus authority relations in the two face-to-face feedback conditions. Knowledge of the performer’s past experiences with authority figures could have helped to predict
differential outcomes of feedback delivery.
The current study did not utilize a control condition of no feedback.
Although a rich literature exists demonstrating the effectiveness of feedback
over no feedback, the literature is not uniformly consistent (Alvero, Bucklin,& Austin, 2001; Balcazar, Hopkins, & Suarez, 1985). The current study did
find that face-to-face feedback and feedback from an authority figure (irrespective of modality) were effective, but this finding does not conclusively
show that such conditions would be superior to no feedback. Even if it isassumed that they would be superior, it would still be valuable to assess thedegree to which they are superior. As such, it is important that future studies
utilize an appropriate control condition.
In addition to addressing issues related to experimental control, other factors
could be studied as well in relation to authority figures, such as the inclusion ofphotos, simulated facial expressions, or video in communications. These additional stimuli that are present in face-to-face communication could potentiallyreduce the difference between face-to-face and less indirect communicationmeans. This research suggests that although face-to-face communication may
be replaced with technology, the effects it generates may not be replicated to thesame degree. Therefore, supervisor-to-employee interactions may be the more
pertinent of tasks the manager focuses on considering their current workload. If
this implication is correct perhaps other aspects of supervisory workload, suchas administrative duties, should be studied to see if substitution throughtechnological means yields results of equal merit.
Disclosure statement
No potential conflict of interest was reported by the authors.

References
Alvero, A. M., Bucklin, B. R., & Austin, J. (2001). An objective review of the effectiveness andessential characteristics of performance feedback in organizational settings (1985–1998).
Journal of Organizational Behavior Management, 21(1), 3–29. doi:10.1300/J075v21n01_02
Anseel, F., & Lievens, F. (2007). The long-term impact of the feedback environment on job
satisfaction: A field study in a Belgian context. Applied Psychology: An International
Review, 56(2), 254–266. doi:10.1111/j.1464-0597.2006.00253.x
Balcazar, F., Hopkins, B. L., & Suarez, Y. (1985). A critical, objective review of performance
feedback. Journal of Organizational Behavior Management, 7(3–4), 65–89. doi:10.1300/
J075v07n03_05

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

149

Berger, S. M., & Ludwig, T. D. (2007). Reducing warehouse employee errors using
voice-assisted technology that provided immediate feedback. Journal of Organizational
Behavior Management, 27(1), 1–31. doi:10.1300/J075v27n01_01
Brown, M. G., Malott, R. W., Dillon, M. J., & Keeps, E. J. (1980). Improving customer service
in a large department store through the use of training and feedback. Journal of
Organizational Behavior Management, 2(4), 251–265. doi:10.1300/J075v02n04_02
Choi, E., Johnson, D. A., Moon, K., & Oah, S. (2018). Effects of positive and negative
feedback sequence on work performance and emotional responses. Journal of
Organizational
Behavior
Management,
38(2–3),
97–115.
doi:10.1080/
01608061.2017.1423151
Daniels, A. C. (2016). Bringing out the best in people: How to apply the astonishing power of
positive reinforcement (3rd ed.). New York, NY: McGraw-Hill Education.
Daniels, A. C., & Bailey, J. S. (2014). Performance management: Changing behavior that drives
organizational effectiveness (5th ed.). Tucker, GA: Performance Management.
Goomas, D. T. (2010). Replacing voice input with technology that provided immediate visualand audio feedback to reduce employee errors. Journal of Organizational Behavior
Management, 30(1), 26–37. doi:10.1080/01608060903472478
Greenbaum, R. L., Mawritz, M. B., & Piccolo, R. F. (2012). When leaders fail to “walk thetalk”: Supervisor undermining and perceptions of leader hypocrisy. Journal ofManagement, 41(3), 929–956. doi:10.1177/0149206312442386
Grote, D. (2006). Discipline without punishment: The proven strategy that turns problem
employees into superior performers (2nd ed.). New York, NY: AMACOM.
Guerin, B. (1994). Analyzing social behavior: Behavior analysis and the social sciences. Reno,
NV: Context Press.
Johnson, D. A. (2013). A component analysis of the impact of evaluative and objective
feedback on performance. Journal of Organizational Behavior Management, 33(2),89–103. doi:10.1080/01608061.2013.785879
Johnson, D. A., Rocheleau, J. M., & Tilka, R. E. (2015). Considerations in feedback delivery:
The role of accuracy and type of evaluation. Journal of Organizational Behavior
Management, 35(3–4), 240–258. doi:10.1080/01608061.2015.1093055
Lee, K., Shon, D., & Oah, S. (2014). The relative effects of global and specific feedback onsafety behaviors. Journal of Organizational Behavior Management, 34(1), 16–28.
doi:10.1080/01608061.2013.878264
Malott, R. (1992). A theory of rule-governed behavior and organizational behavior
management. Journal of Organizational Behavior Management, 12(2), 45–65. doi:10.1300/
J075v12n02_03
Mardanov, I. T., Heischmidt, K., & Henson, A. (2008). Leader-member exchange and job
satisfaction bond and predicted employee turnover. Journal of Leadership & Organizational
Studies, 15(2), 159–175. doi:10.1177/154805180832098
Moon, K., & Oah, S. (2013). A comparison of the effects of feedback and prompts on safe
sitting posture: Utilizing an automated observation and feedback system. Journal of
Organizational
Behavior
Management,
33(2),
152–162.
doi:10.1080/
01608061.2013.785906
Palanski, M., Avey, J. B., & Jiraporn, N. (2014). The effects of ethical leadership and abusive
supervision on job search behaviors in the turnover process. Journal of Business Ethics, 121(1), 135–146. doi:10.1007/s10551-013-1690-6
Palmer, M. G., Johnson, C. M., & Johnson, D. A. (2015). Objective performance feedback: Is
numerical accuracy necessary? Journal of Organizational Behavior Management, 35(3–4),
206–239. doi:10.1080/01608061.2015.1093059

150

S. CHAE ET AL.

So, Y., Lee, K., & Oah, S. (2013). Relative effects of daily feedback and weekly feedback on
customer service behavior at a gas station. Journal of Organizational Behavior
Management, 33(2), 137–151. doi:10.1080/01608061.2013.785898
Sommer, K. L., & Kulkarni, M. (2012). Does constructive performance feedback improve
citizenship intentions and job satisfaction? The roles of perceived opportunities foradvancement, respect, and mood. Human Resource Development Quarterly, 23(2),177–201. doi:10.1002/hrdq.21132
Tittelbach, D., Fields, L., & Alvero, A. M. (2008). Effects of performance feedback on typing
speed and accuracy. Journal of Organizational Behavior Management, 27(4), 29–52.
doi:10.1300/J075v27n04_02
U.S. Department of Labor. (2019). Persons at work by occupation, sex, and usual full-or
part-time status [Data file]. Retrieved from https://www.bls.gov/cps/cpsaat23.htm
Wallo, A., Ellstrom, E., & Kock, H. (2013). Leadership as a balancing act between performance- and development-orientation: A study of managers’ and co-workers’ understanding of leadership in an industrial organization. Leadership & Organization Development
Journal, 34(3), 222–237. doi:10.1108/01437731311326666
Wiesman, D. W. (2006). The effects of performance feedback and social reinforcement on
up-selling at fast-food restaurants. Journal of Organizational Behavior Management, 26(4),1–18. doi:10.1300/J075v26n04_01