Can professionals “keep the tiller straight” in organizations? Resistance to reframing and decoy alternatives in workplace decision-making

Abstract

So far, little is known about the ability to contrast contextual bias as a protective factor in an ever-changing organizational environment. This study assessed whether professionals with different seniority can resist the reframing and the decoy effect under decision-making conditions and whether decision-making styles can predict the resistance to such covert influence tactics. To reach this aim, two groups of professionals divided into senior and junior professionals performed two novel tasks, a Resistance to Reframe Task (RRT) and a Resistance to Alternatives Task (RAT), which, by including ecological scenarios that represent typical decision situations that could arise in the company, can measure the resistance to such covert influence tactics. Decision-making styles were measured through the General Decision-Making Style (GDMS) and the Maximization Scale (MS). Results showed that all professionals were able to resist more to the reframing (at the RRT) than the decoy alternatives (RAT), without any difference between groups. In addition, higher GDMS-dependent subscale scores predict lower RRT scores, especially in the group of senior professionals. However, in the group of junior professionals, the GDMS-dependent subscale and MS high standards subscale predicted lower RAT scores. To conclude, this study showed that professionals know how to “keep the tiller straight” in organizations, especially when facing reframing conditions, rather than decoy alternatives; however, the predominance of dependent decision-making styles (for both senior and junior professionals) and the tendency to hold high standards in decisions (mainly for juniors) could undermine their resistance capacity and make them vulnerable to these covert influence tactics.

Full text

Frontiers in Psychology 01 frontiersin.org
Can professionals “keep the tiller
straight” in organizations?
Resistance to reframing and
decoy alternatives in workplace
decision-making
LauraAngioletti
1,2*, CarlottaAcconito
1,2, DavideCrivelli
1,2 and
MichelaBalconi
1,2
1 International research center for Cognitive Applied Neuroscience (IrcCAN), Catholic University of the
Sacred Heart, Milan, Italy, 2 Research Unit in Aective and Social Neuroscience, Department of
Psychology, Catholic University of the Sacred Heart, Milan, Italy
So far, little is known about the ability to contrast contextual bias as a protective
factor in an ever-changing organizational environment. This study assessed
whether professionals with dierent seniority can resist the reframing and the
decoy eect under decision-making conditions and whether decision-making
styles can predict the resistance to such covert influence tactics. To reach this
aim, two groups of professionals divided into senior and junior professionals
performed two novel tasks, a Resistance to Reframe Task (RRT) and a Resistance
to Alternatives Task (RAT), which, by including ecological scenarios that
represent typical decision situations that could arise in the company, can
measure the resistance to such covert influence tactics. Decision-making styles
were measured through the General Decision-Making Style (GDMS) and the
Maximization Scale (MS). Results showed that all professionals were able to resist
more to the reframing (at the RRT) than the decoy alternatives (RAT), without
any dierence between groups. In addition, higher GDMS-dependent subscale
scores predict lower RRT scores, especially in the group of senior professionals.
However, in the group of junior professionals, the GDMS-dependent subscale
and MS high standards subscale predicted lower RAT scores. To conclude,
this study showed that professionals know how to “keep the tiller straight” in
organizations, especially when facing reframing conditions, rather than decoy
alternatives; however, the predominance of dependent decision-making styles
(for both senior and junior professionals) and the tendency to hold high standards
in decisions (mainly for juniors) could undermine their resistance capacity and
make them vulnerable to these covert influence tactics.
KEYWORDS
reframe resistance, decoy eect, behavioral decision-making, organization,
professionals
1 Introduction
Current working conditions are characterized by a post-pandemic working modality
involving many changes in the organization of work (Chan et al., 2023). As a result,
employees—both senior professionals and novices—may experience a great deal of uncertainty
as they adapt to a new way of working. Organizations are becoming more aware that they must
OPEN ACCESS
EDITED BY
Christoph Schank,
University of Vechta, Germany
REVIEWED BY
Francesco Tommasi,
University of Verona, Italy
James Campbell Quick,
University of Texas at Arlington, UnitedStates
*CORRESPONDENCE
Laura Angioletti
laura.angioletti1@unicatt.it
RECEIVED 31 July 2023
ACCEPTED 12 February 2024
PUBLISHED 28 February 2024
CITATION
Angioletti L, Acconito C, Crivelli D and
Balconi M (2024) Can professionals “keep the
tiller straight” in organizations? Resistance to
reframing and decoy alternatives in
workplace decision-making.
Front. Psychol. 15:1270012.
doi: 10.3389/fpsyg.2024.1270012
COPYRIGHT
© 2024 Angioletti, Acconito, Crivelli and
Balconi. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
TYPE Brief Research Report
PUBLISHED 28 February 2024
DOI 10.3389/fpsyg.2024.1270012

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 02 frontiersin.org
invest in the wellbeing of employees, and, within this framework,
we have recently argued the importance of professionals’
neurocognitive health, giving particular attention to the assessment,
and strengthening of executive functions (EFs) in the workplace
(Balconi etal., 2020).
In this study, weseek to test whether, compared to professionals
already entered the world of work, junior professionals can resist
contextual bias, such as the reframing and the decoy eect under
decision-making conditions. Moreover, weaim to investigate whether
there is a decision-making style that predicts such resistance to
reframing and yielding in the decoy eect.
We did so by asking a sample of junior and senior professionals to
perform two novel tasks, a Resistance to Reframe Task (RRT) and a
Resistance to Alternatives Task (RAT), which, by including ecological
scenarios that represent typical decision situations that could arise in
the company, in which the professionals were asked to identify
themselves, can measure their resistance to such covert inuence
tactics. During the tasks, behavioral responses were collected to
compose specic behavioral indices of RRT and RAT.
Furthermore, the General Decision-Making Scale (GDMS; Scott
and Bruce, 1995) and the Maximization Scale (MS; Nenkov etal.,
2008) were applied to prole professionals’ decision-making styles and
explore potential associations between the ve dierent GDMS
decision-making styles (rational, intuitive, avoidant, dependent, and
spontaneous), the MS subscales (high standard, alternative search, and
decision diculty), and the ability to resist reframing and alternatives,
as an high-order executive control ability.
Indeed, EFs consist of a family of high-order cognitive functions
(including working memory, cognitive exibility, inhibitory control,
decision-making, and other functions) that are the basis for the
management of sustained attention, the control of impulsive reactions
control, support goal-attainment, and are especially relevant for
promoting a quick and exible adaptation to shiing environmental
demands (Miller and Cohen, 2001; Diamond, 2013). Among EFs,
decision-making plays a crucial role at all professionals’ levels (Del
Missier et al., 2010; Balconi, 2023; Rovelli and Allegretta, 2023),
especially under conditions of uncertainty, which can aect both
experienced and junior professionals. If on the one hand, the ability
to be exible in decisions and adapt to changes has been valued
(Laureiro-Martínez and Brusoni, 2018); on the other hand, it proves
useful for professionals to beable also to maintain one’s decision
independently from the context (to use an idiom, “to keep the tiller
straight” while navigating organizations), for instance, despite a
situation being subjected to covert inuence tactics that act on the
context, such as reframing strategy or decoy eect.
e strategy of reframing, in the therapeutic context, refers to a
type of interpretation that provides a new meaning or frame of
reference to perspectives in a constructive direction (i.e., positive
reframing) (Guterman, 1992; Bateson, 1995), by oen drawing
positive implications from adverse circumstances. On the contrary,
negative reframing provides helpful warnings about dicult situations
(Tracy etal., 2002). is concept has been exploited in communication
and political studies (Catellani and Bertolotti, 2017; Voelkel etal.,
2023), reaching up to beused in the organizational eld for enabling
professionals to see organizational issues through dierent lenses
(Winter etal., 1997; Bolman and Deal, 2017; Yilmaz etal., 2021).
Another context-dependent phenomenon is the decoy eect,
which happens when additional alternatives proposed to the
individual can change one’s previous choice (Huber et al., 1982).
Regarding the link between EFs and resistance to reframing and the
decoy eect, neuroscience studies demonstrated how additional
cognitive control is needed to inhibit the automatic process derived
from the decoy eect (Hu and Yu, 2014) and contrast the framing
eect (De Martino etal., 2006; Xu etal., 2013).
To the best of our knowledge, the inuence of reframing strategy
on professionals’ decision-making has never been tested before, as well
as the ability of professionals to resist such covert inuence tactics in
the workplace.
On the contrary, the bias derived from adding a decoy alternative
under decision-making conditions (i.e., the decoy eect) has been
studied in organizations in relation to hiring decisions (Slaughter
etal., 2011; Keck and Tang, 2020). Interestingly, concerning dierences
between junior and senior professionals, Slaughter et al. (2011)
examined the extent to which highly experienced executive Master of
Business Administration Students (executives with more than 10 years
of experience) and inexperienced undergraduate students (junior-
level college students) can use the decoy eect as a covert strategy for
inuencing the outcome of selection decisions. e decoy eect
happens in a situation when the inclusion of an inferior alternative (in
this case a candidate) in a set of options alters the preference
relationships between the current, superior options (i.e., change the
attraction toward other candidates) (Huber and Puto, 1983). Authors
showed that participants could similarly build an asymmetrical
dominance set of candidates that generated a decoy eect and that
students outperformed executives. e authors supposed that it is the
type of expertise, rather than the amount of experience and age, that
provides individuals with this skill.
Although the study by Slaughter etal. (2011) has the merit of
deepening decision-making skills in the professional context, it has
the limitation of using only the recruitment and selection scenarios
(typical of human resources professional gures) perhaps unfamiliar
to the participants. In addition, the authors did not nd any signicant
relation between demographical information, job dimensions with
selection decisions, or behavioral performance (Slaughter etal., 2011).
Yet, they neglected the link between behavioral performance and
individuals’ decision-making styles.
us, there appears to bean important gap in the literature, and
lling this gap can provide an important missing link from the
decision-making perspective (in terms of decision-making styles and
resistance to these covert inuences) to the organizational literature.
Decision-making styles can be conceived as learned habit-based
propensity to react in a specic way in a certain decision context (Scott
and Bruce, 1995). Considered as individual dierences in decision-
making proles, they were classically explored with validated
questionnaires such as the General Decision-Making Scale (GDMS;
Scott and Bruce, 1995), which proposes ve dierent independent
decision styles (rational, intuitive, avoidant, dependent, and
spontaneous), or the Maximization Scale (MS; Nenkov etal., 2008),
which include three main dimensions (the tendency to hold high
standards, to seek better alternatives and the diculty in deciding),
and they have previously examined also in relation to dierent
professions (Iannello, 2007).
Given these premises and considering the level of expertise and
seniority, wehypothesize higher RRT and RAT indices in senior than
junior professionals under decision-making conditions. In addition,
it is supposed that MS high standards and alternative search subscale
scores could bepredictors of lower RAT scores in junior professionals,
as the tendency to hold high standards for oneself and things in

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 03 frontiersin.org
general, and the tendency to always seek better options can generate
a greater tendency to yield (and thus resist less) to new alternatives,
especially for junior professionals that are entering the world of work.
Moreover, it is expected to nd a relation between GDMS subscale
scores and RRT and RAT scores. In particular, a GDMS-dependent
decision-making style could predict lower RRT and RAT scores for
both professional categories, as, regardless of seniority, this decision-
making style is characterized by constantly seeking suggestions and
advice from other people before deciding (unholm, 2004) and this
may generate a lower ability to resist external inuences deriving from
a reframed situation or the presentation of multiple alternatives.
2 Methods
2.1 Participants
A total of 61 professionals (40 females and 21 males; age
range = 22–60; Mage = 34.58 years; SD age = 11.44) par ticipated in the
study. Based on their age and expertise, the sample was divided into
two groups: e rst group consisted of a total of 32 junior
professionals (Mage = 34.21 years; SD age = 11.32) at the beginning of
their working experience, with a minimum expertise of 2 years and a
maximum of 3 years in the same role (apprenticeship); the second
group was composed of 29 senior professionals (Mage = 38.98 years;
SD age = 10.87) already placed on the labor market, who hold a
managerial role for at least 5 years. All participants were recruited
from dierent organizations in Northern Italy between October 2022
and April 2023. ey were all employed in managerial divisions and
the same job position for approximately 2 years at the time of the
experiment. is criterion was chosen to avoid potential biases
derived from situational factors, such as the potential increase of stress
due to a new job position or a greater workload while adjusting to new
tasks or obligations (Balconi et al., 2023a, 2023b). Moreover, to
increase the generalizability of the ndings, professionals were
recruited from various internal divisions (for example, human
resource management, training and professional learning, engineering
and maintenance management, service quality monitoring,
infrastructure management, and others) to increase the variety of the
sample in terms of professional specialization. In each of the two
groups, the internal divisions were equally distributed.
Exclusion criteria were levels of depression, previous psychiatric or
neurology disorders, and undergoing treatment with concomitant
psychoactive drug therapy that could alter cognitive or decision-making
abilities (Angioletti etal., 2023), as well as abnormal short- and long-
term memory or low global cognitive functioning. e study was
approved by the Ethics Committee of the Department of Psychology of
the Catholic University of the Sacred Heart, Milan, Italy. e study was
carried out under the Declaration of Helsinki Principles (2013). Written
informed consent was obtained from the participants, and they were
informed of their right to discontinue participation at any time.
2.2 Experimental procedure
Participants sat in a quiet room located on their company site, in
front of a computer place approximately 80 cm distant from them.
Aer signing the written informed consent, they received the
instruction for performing the two dierent tasks, RRT and RAT,
administered via a web-based survey and experiment-management
platform (Qualtrics XM platform; Qualtrics LLC, Provo, UT, USA).
e GDMS and the MS were administered at the conclusion of the
tasks to collect participants’ self-report data. e experiment lasted
approximately 15 min (Figure1).
2.2.1 Resistance to reframe task (RRT)
In the Resistance to Reframe Task (RRT), the participants were
presented with two dierent scenarios divided into two decisional
steps. In both decisional steps, they were asked to identify themselves
with the scene and choose the alternative that they thought was most
suitable in a set of multiple options.
In the rst decisional step, participants were presented with a
script regarding a critical work situation in which they were asked to
make a decision. For instance, in the rst scenario, they were presented
with the following script:
“You must participate together with all the executives of your
company in a particularly hard decision. Due to a funding cut, youmust
decide whether to close some plants and lay o some employees.
You have 4 factories and 6,000 employees in total. Let us introduce
youto some of the people who work in these establishments.”
Aer the presentation of the script, it was shown to them the
picture of the four companies and the four employees mentioned in
the script.
ey were asked to choose which of the four plants would they
choose to keep open (selecting one of the four options presented) and
to rate their condence in the choice on a Likert scale from 1 to 5,
where 1 corresponded to “not at all” and 5 to “entirely sure” (i.e.,
condence rating in the rst decisional step).
In the second decisional step, participants were then presented
with the reframed part of the task, in which they were told that “based
on the choice they have made, the other employees will lose their jobs”
and they were then asked once again to rate their condence in the
choice on a Likert scale from 1 to 5, where 1 corresponded to “not at
all” and 5 to “entirely sure” (i.e., condence rating in the second
decisional step, that was reframed).
Aer this rst scenario, a second dierent scenario was also
presented to the participants: e order of presentation was
randomized and counterbalanced between participants.
Response scores were calculated based on the dierence between
the condence rating in the rst decisional step and the condence
rating in the second decisional step (the reframed one), averaged
across scenarios. Such average dierence scoring was, then,
transcribed to a ve-point scale based on the following rules:
- AvgDi <1 ➔ RS = 5.
- 1 ≤ AvgDi <2 ➔ RS = 4.
- AvgDi = 2 ➔ RS = 3.
- 2 < AvgDi <3 ➔ RS = 2.
- AvgDi ≥3 ➔ RS = 1.
where AvgDi stands for average dierence scores as above
described, and RS stands for response scores. A higher score
corresponds to a higher ability to resist the reframe, while a lower
score to a lower ability to resist it.
Response scores were, then, transcribed oine in deciles to
compute the Resistance to the Reframe Task index (RRTi).

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 04 frontiersin.org
2.2.2 Resistance to the alternatives task (RAT)
In the Resistance to the Alternatives Task (RAT), participants were
presented with three dierent realistic decision-making scenarios
related to purchases of basic facilities for the company (printer, chairs,
and hard disks) and containing decoy alternatives. Participants were
asked to identify themselves in those decisional scenarios and then to
provide a behavioral response by choosing which of several proposed
options they thought was most suitable for them.
Each scenario presented two decisional steps: In the rst
decisional step, participants could choose between two alternative
options; in the second decisional step, a third superior alternative and
the superior option were added. Table1 reports the example of one
scenario and related alternatives for each decisional step.
e ecological validity of the decision scenarios with their
alternatives was taken into consideration during their creation and
was pursued with realistic situations and problems referred to the
organizational environment, with which professionals could easily
identify. Each scenario created was validated by a panel of independent
judges, who assessed its ecological validity as well as its realism and
clarity. In addition, to avoid an order eect, each scenario and
decisional step was presented in random order and counterbalanced
between participants.
To calculate the response scores, a score of 1 was assigned if the
choice matched the two decisional steps (i.e., the selection of the same
alternatives in the two decisional steps of each scenario), while a score
of 0 was assigned if a dierent choice was made (i.e., the selection of
dierent alternatives in the two decisional steps of each scenario).
e scores assigned to each scenario were then summed to obtain
a nal score of resistance to the alternatives. A higher score
corresponds to a higher ability to resist the alternatives, while a lower
score to a lower ability to resist them. Response scores were, then,
transcribed oine into deciles to compute the Resistance to the
Alternative Task index (RATi).
2.3 Self-report scales for measuring
decision-making style
e Italian version of the General Decision-Making Style (GDMS)
(Scott and Bruce, 1995; Gambetti etal., 2008) and the Maximization
Scale (MS) (Schwartz etal., 2002; Nenkov etal., 2008) were adopted
to collect self-report data on individuals’ decision-making styles.
GDMS is a validated tool for proling individuals according to
ve dierent decision-making styles (rational, intuitive, dependent,
avoidant, and spontaneous) and is composed of 25 items, for each of
which the participant is asked to indicate his/her level of agreement
on a 5-step Likert scale. An individual with a rational decision-making
style tends to make decisions based on careful consideration and
evaluation of dierent alternatives, because of a comprehensive and
exhaustive search for information, while a person with an intuitive
decision-making style is driven to make decisions based on intuitions
derived from the attention paid to global aspects. e dependent
decision-making style, on the other hand, is characterized by
constantly seeking suggestions and advice from other people before
deciding, while the avoidant style is dened by a tendency to avoid
making decisions. Finally, an individual with a spontaneous decision-
making style prefers to decide as quickly as possible.
e MS is a validated questionnaire consisting of 13 items
(Nenkov etal., 2008) that require individuals to express their degree
of agreement on a 7-step Likert scale that allows one to measure
decision makers’ tendencies (i) to hold high standards for themselves
and things in general (the high standard subscale), (ii) to seek better
options (the alternative search subscale), and (iii) to encounter
diculties in making a choice (the decision diculty subscale).
2.4 Data analysis
First, an exploratory repeated-measures ANOVA was applied to
the whole sample with Tas k (2: RRT, RAT) as a within-subject
independent factor and behavioral scores as dependent measures, to
obtain a preliminary view of general trends within the total sample. In
addition, to specically test group dierences, a further mixed
ANOVA including Group (2: junior, senior) as a between-subject
independent factor and Tas k (2: RRT, RAT) as a within-subject
independent factor was applied to the behavioral scores as
dependent measures.
Simple eects for signicant interactions were further checked via
pairwise comparisons, and Bonferroni correction was used to reduce
potential biases of multiple comparisons. Furthermore, the normality
of the data distribution was preliminarily assessed by checking
kurtosis and asymmetry indices. e size of statistically signicant
eects has been estimated by computing eta squared (η2) indices. e
threshold for statistical signicance was set at α = 0.05.
e relationship between RRTi, and RATi and the decision-
making styles has then been further explored via linear regressions:
First by analyzing the whole sample in order to get a preliminary
general glimpse of such relationship and, second, via subgroup
analysis. Specically, the GDMS subscale scores (rational, intuitive,
dependent, avoidant, and spontaneous) and the MS subscale scores
(choose between alternatives, research of options, and high standards)
have been used as predictors in separate multiple linear regression
stepwise models including RRTi and RATi as predicted dependent
measures. Scatterplots were drawn to check for the linearity of the
relationship between the predictor and dependent measures included
in the regression models. Assumptions concerning the
homoscedasticity, linearity, and normality of residuals were also
checked by examining the scatterplot of standardized predicted values
FIGURE1
Experimental flow.

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 05 frontiersin.org
versus standardized residuals as well as the P–P plot of standardized
residuals. e Durbin–Watson statistic was computed to determine
the autocorrelation of the residuals, and tolerance and variance
ination indices were calculated to check multicollinearity. e eect
size of the dependence relationship between the predictor and
dependent variables was estimated with the R-square. Following
Cohen’s (1988) rules, eect sizes are considered small when ≥0.02,
medium when ≥0.13, and large when ≥0.26. e threshold for
statistical signicance was set at α = 0.05.
3 Results
3.1 Total sample
From the rst ANOVA performed on the total sample, a
signicant main eect for the Tas k factor was found [F(1, 60) = 21,472
p ≤ 0.001, η2 = 0.264], for which higher behavioral scores were detected
for RRTi compared to RATi (Figure2).
e multiple linear regression model focusing on the relationship
between GDMS subscale scores as predictors and the RRTi score as
predicted variable highlighted the signicant role of GDMS dependent
scores as predictors [F(1, 59) = 5,232, p = 0.026], with a slope coecient
(β) equal to −0.29. e R
2
value was 0.083, qualiable as a small-to-
medium eect size. e Durbin–Watson value was 2.242.
No other multiple linear regression model highlighted signicant
eects in the total sample.
3.2 Subgroup comparison
e ANOVA performed by splitting the sample into the two
groups (senior and junior professionals) conrmed a signicant main
eect for the Tas k factor [F(1, 59) = 21,524, p ≤ 0.001, η
2
= 0.267], for
which higher behavioral scores were detected for RRTi compared to
RATi. No signicant eects nor signicant interaction eects were
found for the Group variable.
For the group of senior professionals, the multiple linear
regression model focusing on the relationship between the GDMS
subscale scores as predictors and the RRTi score as predicted variable
showed a signicant role of GDMS dependent scores as predictor [F(1,
27) = 4,840, p = 0.037], with a slope coecient (β) equal to −0.39. e
R
2
value was 0.15, qualiable as a medium eect size (Figure3A). e
Durbin–Watson value was 2.331.
No other multiple linear regression model highlighted signicant
eects in the senior professionals’ subgroup.
FIGURE2
Bar graph shows the significant dierences between RRTi and RATi
observed in the total sample. Bars indicate the ±1 Standard Error (SE).
The star (*) marks the significant dierence.
TABLE1 Example of the printer scenario and its two decisional steps with the relative alternatives of choice.
RAT
First decisional step Second decisional step
Printer scenario
Your company needs to buy six new oce printers.
You contact your supplier who oers youtwo alternatives:
Express printers: single function printer, performs monochromatic
printing operations in A4 format. Compact, fast, and reliable.
Maximum savings on toner.
Price €490 each
- Business printers: multifunction printer, performs color
printing, copying, and scanning operations. An HD prints in A4
format. Intelligent and safe technology, with high-
quality resolution.
Price €820 each
Your company needs to buy 6 new oce printers. Youcontact your supplier
who oers you2 alternatives:
Express printers: single function printer, performs monochromatic printing
operations in A4 format. Compact, fast, and reliable. Maximum savings on
toner.
Price €490 each
- Business printers: multifunction printer, performs color printing, copying,
and scanning operations. HD prints in A4 format. Intelligent and safe
technology, with high-quality resolution.
Price €820 each
- Advanced Printers: multifunction printer, performs color printing,
copying, scanning, and faxing. Professional prints on dierent formats
and dimensions in very high denition. New-generation technology and
innovative design.
Price €1,250 each
Alternatives of choice
What do youchoose?
1. Express printers (€ 490)
2. Business Printers (€ 820)
What do youchoose?
1. Express printers (€ 490)
2. Business Printers (€ 820)
3. Advance Printers (€ 1,250)

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 06 frontiersin.org
For the group of junior professionals, the multiple linear
regression model focusing on the relationship between the GDMS
subscale scores as predictors and the RATi score as predicted variable
showed the signicant role between predictor and dependent variable
[F(1, 31) = 4,954, p = 0.034], with a slope coecient (β) for GDMS
dependent subscale equal to −0.38. e R2 value was 0.14, qualiable
as a medium eect size (Figure 3B). e Durbin–Watson value
was 1.815.
Additionally, the multiple linear regression model focusing on the
relationship between the MS subscale scores as predictors and RATi
as predicted variable showed the signicant role of MS high standards
scores [F(1, 31) = 4,487, p = 0.043], with a slope coecient (β) equal to
−0.36. e R
2
value was 0.13, qualiable as a medium eect size
(Figure3C). e Durbin–Watson value was 1.813.
No other multiple linear regression model highlighted signicant
eects in the junior professionals’ subgroup.
4 Discussion
is study explored the ability of professionals to resist reframing
and decoy alternatives in decision-making conditions, focusing
specically on the dierences between professionals already entered
the world of work and junior professionals. Two novel behavioral tasks
were proposed to participants for exploring their resistance to
reframing—the Resistance to Reframe Task (RRT)—and decoy
alternatives—the Resistance to the Alternatives Task (RAT)—in
organizational settings. Furthermore, the relationship between
individual dierences in decision-making styles (measured through
the GDMS and MS scales) and resistance to reframing and alternatives
was investigated.
e results derived from two distinct analyses will bediscussed
below, i.e., from a rst analysis carried out on the overall sample and
then from a more in-depth analysis applied to the two subgroups of
professionals. e latter was carried out to highlight potential
dierences attributable to job seniority.
First, the whole professionals showed to beable to resist more to
the reframing (RRT) than the decoy alternatives (RAT) task, without
any dierence between groups. us, on one hand, professionals
demonstrated to beable to run counter a reframed condition and
display a “rational,” description-invariant behavior (De Martino etal.,
2006); on the other hand, they all showed a lower ability to resist
multiple alternatives presented in such a way as to evoke the decoy
eect. Moreover, dierently from what was hypothesized no
FIGURE3
(A–C) Scatterplots and regression line estimates for statistically significant regression models including (A) GDMS-dependent style as the predictor
variable and RRTi as the dependent variable in senior professional, (B) GDMS-dependent style as the predictor variable and RATi as the dependent
variable in junior professional, (C) MS high standards as the predictor variable and RATi as the dependent variable in a junior professional. Straight lines
represent global linear trends.

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 07 frontiersin.org
dierences related to seniority were found. is result is partially in
line with Slaughter etal. (2011) previously demonstrated that the
ability to exploit the decoy eect did not depend on seniority, but they
supposed it depended rather on the type of expertise. is evidence
adds to this line of research that seniority did not impact resistance to
reframing and the decoy eect. However, some dierences in terms of
seniority emerge if professionals’ decision-making style is taken
into consideration.
In fact, by including in this framework the individual style that
each person adopts in making a decision, it was observed how higher
scores at the GDMS-dependent subscale predict lower RRT scores.
anks to the second-level subgroup analysis, it emerged that such an
eect was attributable mainly to the group of senior professionals and
not to junior ones. is means, that with advancing age, having a
predominance of dependent decision-making style, that is
characterized by constantly seeking suggestions and advice from other
people before deciding (Scott and Bruce, 1995; unholm, 2004;
Gambetti etal., 2008), might reduce the resistance to the reframe and
can lead to making decisions more dependent on the context (and
therefore on the frame) or dependent on comparisons with other
people (typical of this decision-making style).
Interestingly, some peculiarities related to decision-making style
and resistance to alternatives were found also in the group of junior
professionals. Indeed, two main decision-making proles were
demonstrated to predict lower RAT scores in the group of junior
professionals: One connoted by high MS high standards scores, and
one connoted by high GDMS dependent scores. is result
demonstrated that, even in the group of junior professionals, it is
always a context-dependent decisional prole (comparing with others
to receive advice on how to decide or considering others as a
comparison standard to beovercome) that makes the resistance to
multiple decoy alternatives more complex.
e reason why in junior professionals, a context-dependent
decision-making prole predicts lower RAT scores, and in seniors, the
same prole predicts lower RRT scores (together with a generally lower
ability to resist RAT, rather than RRT, regardless of the decision-making
style, as demonstrated by the ANOVA) must beinvestigated also taking
into consideration the role of EFs, examining whether a reduction in
cognitive control toward these biases also occurs in this specic case.
Another recent study (Tommasi etal., 2023) explored the
presence of bias in professionals and demonstrated that
entrepreneurs exhibit higher levels of under/overconfidence (i.e.,
self-confidence in taking decisions) than managers and
specifically showed a marked presence of this bias among
entrepreneurs at younger ages. Therefore, both higher levels of
expertise and seniority in terms of age require thorough
investigation in the context of resistance to decision biases.
To conclude, this study suggests that professionals know how
to “keep the tiller straight” in organizations, especially when
facing reframing conditions, rather than decoy alternatives;
however, the predominance of dependent decision-making styles
(both for senior and junior professionals), and the tendency to
hold high standards in decisions (mainly for juniors) could
undermine their resistance capacity and make them vulnerable
to these covert influence tactics.
Although our current study is one of the rst studies investigating
the construct of resistance to decision bias in professional contexts,
and their relationship to decision-making styles, it is not without
caveats. Among all limitations, the presence of only behavioral data
would benet from the integration of neurophysiological data to
explore professionals’ EFs and increase the validity and generalizability
of current results.
Data availability statement
e raw data supporting the conclusions of this article will
bemade available by the authors, without undue reservation.
Ethics statement
e studies involving humans were approved by Department of
Psychology of the Catholic University of the Sacred Heart, Milan, Italy.
e studies were conducted in accordance with the local legislation
and institutional requirements. e participants provided their written
informed consent to participate in this study.
Author contributions
LA: Validation, Visualization, Writing – original dra, Writing –
review & editing. CA: Data curation, Formal analysis, Investigation,
Writing – review & editing. DC: Data curation, Formal analysis,
Methodology, Writing – review & editing. MB: Conceptualization,
Methodology, Project administration, Resources, Supervision,
Validation, Writing – review & editing.
Funding
e author(s) declare nancial support was received for the
research, authorship, and/or publication of this article. is research
did not receive any specic grant from funding agencies in the public,
commercial, or not-for-prot sectors. Funded by the European Union
– Next Generation EU (PRIN 2022 call, Ministry of University and
Research - Project n° 202284WCP9). e views and opinions
expressed are only those of the authors and do not necessarily reect
those of the European Union or the European Commission. Neither
the European Union nor the European Commission can be held
responsible for them.
Acknowledgments
e authors kindly thank all the professionals for their availability
in participating in the study.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.

Angioletti et al. 10.3389/fpsyg.2024.1270012
Frontiers in Psychology 08 frontiersin.org
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