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The Role of  Gender in Transformational Information 
Technology Leadership: 

Extending the Glass-Cliff  Theory 
 

 
Ugur Yeliz Eseryel 

East Carolina University 
 

Christopher Furner 
East Carolina University 

 
Deniz Eseryel 

North Carolina State University 
 

Ayşın Paşamehmetoğlu 
Özyeğin Üniversitesi, Istanbul, TR 

 
Brenda Killingsworth 
East Carolina University 

 
April Reed 

East Carolina University 
 

Anna Johnson 
East Carolina University 

 
Asligul Erkan-Barlow 
East Carolina University 

 

http://journals.sfu.ca/abr 
     2024, Volume 14, pages 20-39 

http://journals.sfu.ca/abr


21 

 

The glass cliff phenomenon refers to a tendency to appoint women to leadership positions when 
organizational performance is declining, often resulting in lower levels of female leader success. This 
phenomenon is well documented in management literature, however, the social and psychological 
mechanisms that lead to these appointments are still poorly understood and have not been 
investigated in the Information Technology (IT) field. Therefore, this study fills a gap in the 
literature by developing a model of predicted IT leadership success and predicted transformational 
IT leadership. Results of a scenario-based experiment indicate that expectations tend to be higher 
for female candidates. Additionally, when members of a leader hiring team score higher in terms of 
sexism, they tend to rate transformational information technology (IT) leadership of female leaders 
higher. This may explain the glass cliff phenomenon since transformational IT leaders are believed 
to be better suited to turning around poor-performing teams. Implications of gender for IT 
researchers, hiring teams, and leader evaluation boards are discussed.  
 
Keywords: Transformational IT leadership, leader gender, IT leadership success, organizational 
performance, women in IT 
 

Introduction 
Individuals’ career advancement and leadership opportunities are visibly and significantly 

influenced by their gender (for a comprehensive review, see Lindqvist et al., 2021). Management 
literature suggests that among the individuals whose assigned gender at birth corresponds to their 
self-defined gender identity (i.e., cisgender individuals), women were more disadvantaged than men, 
even when their capabilities are similar (Khushk et al., 2023; Koburtay et al., 2019; Lindqvist et al., 
2021; Shen & Joseph, 2021). This article investigates the current situation that cisgender women face 
as a minority group compared to cisgender men within the context of leadership in the Information 
Technology (IT) field. Even though the glass ceiling is more permeable than in the past, female 
leaders are still held to different standards and expectations than their male counterparts (Rudman et 
al., 2012). Several years ago, psychologists identified a newer form of discrimination called glass cliff 
(Ryan et al., 2007). Glass cliff suggests that females are preferred for leadership positions in high-
risk, precarious situations. Coincidentally, when companies are geared toward success, male leaders 
are more likely to be chosen for leadership positions. While the glass ceiling has become more 
permeable over the last few years, female leaders are still held to different standards and 
expectations than male leaders. Glass cliff has adverse outcomes for both the women who are 
Information Technology (IT) leaders, in general, and those who were put into high-risk positions. 
Female IS leaders taking on risky leadership positions are more likely to fail due to the increased 
riskiness of the endeavor. Consequently, their reputations and leadership careers may be impacted 
negatively and irrevocably (Ryan et al., 2007). Furthermore, such leadership failures may be 
generalized and impact the employment of women overall by creating a negative stereotype of 
female IT leaders. Therefore, it is crucial to understand and overcome the glass cliff phenomenon 
within the IT profession. This phenomenon is particularly salient, since it may manifest due to the 
perceivers' sexist attitudes (Acar & Sumer, 2018). For simplicity, hereafter, the discussion of the IT 
profession includes the information systems field.  

Sexist attitudes are likely to exist in the historically male-dominated IT profession which also 
tends to have a masculine organizational culture (Kirton & Robertson, 2018). Lawler and Molluzzo 
(2016) conducted a study of Information Systems students at their university and found that female 
students, in particular, were aware of sexism in their field, which also led to bullying. Their research 
showed that Information Systems and Computer Science students are “essentially knowledgeable of 



22 

 

bullying as a concern in [the] industry” (Lawler & Molluzzo, 2016, p. 137). Not only can sexism 
affect female leaders, but it can also affect work quality in that it can “constrain the morale and the 
performance of professionals” (Lawler & Molluzzo, 2016, p. 137). The researchers concluded there 
was enough concern to suggest that programs prepare students for this eventuality before entering 
the profession. Other studies identified a need to understand and reduce the gender gap in the 
profession through approaches like understanding barriers, i.e., the lack of access to technology 
education in high school (Reid et al., 2010).  

Empirical studies of the glass cliff phenomenon have demonstrated contradictory results 
(Ryan et al., 2016). In responding to criticism regarding the glass cliff phenomenon, the authors who 
coined the term suggest that the phenomenon is nuanced and context-dependent (Ryan et al., 2016, 
p. 449). However, a literature review identified a gap in this research area and highlighted the need to 
understand the different contexts in which it occurs (Ryan et al., 2016). In this study, we investigate 
the psychological and social drivers of the glass cliff phenomenon and its impact on the IT 
profession. This study also employs a conceptualization of transformational leadership that was 
developed for the IT field, which is characterized by a culture of innovation and constant change. 
Specifically, this study investigates the influence of a leader's gender on perceptions of the degree of 
transformational IT leadership associated with the leader, and how the sexism of the perceiver 
influences this relationship. We also investigate whether a leader's gender influences predicted 
success of the organization that they lead.  Therefore, we pose the following research question: 

 
RQ. How does a leader’s gender influence perceptions of transformational IT leadership and 

predicted organizational success? 
 
This study seeks to contribute to the glass-cliff paradigm by (1) testing this phenomenon 

within the Information Systems field and (2) examining the impact of the glass-cliff phenomenon on 
perceptions of transformational IT leadership. The findings augment the understanding of the 
mechanisms that drive the glass cliff phenomenon and should carry implications for leader selection 
teams seeking to avoid bias in their hiring decisions. This study also contributes to the Information 
Systems literature by introducing the impact of the glass-cliff phenomenon. It also enhances studies 
on gender-related issues in IS research that promote women's participation both in the IS field and 
especially in IS leadership.  The practical contribution of this study includes eliciting factors that 
increase bias in IT-related hiring decisions. This would allow executives and hiring staff to increase 
their awareness and take action to eliminate such bias.  

Findings that performance expectations tend to be higher for female candidates are 
consistent with the glass cliff paradigm. Further, the finding that when members of a leader hiring 
team score higher in terms of sexism, they tend to rate female candidates higher in terms of 
transformational IT leadership represents a potential explanation of the glass cliff phenomenon, 
since transformational IT leaders are expected to be more effective at turning around poor-
performing teams, and members of the hiring committee who score higher in sexism (and thus have 
stereotypical expectations regarding characteristics of female leaders) may assume that women will 
exhibit a transformational style of leadership (characterized by nurturing, open communication, and 
team building rather than inter-team competition). In addition to the implications for the glass cliff 
phenomenon and female leadership in the IT field, these findings have implications for hiring teams, 
related to the identification of implicit biases and gender-based expectations of leadership 
candidates. These implications may have a substantial influence on leadership candidate selection, 
team performance, and the career prospects for female leader candidates.  



23 

 

In the following section, we review relevant research on the glass cliff phenomenon, 
transformational leadership, organizational performance, organizational culture, and gender in the IT 
field, including the gender gap, masculine organizational culture, and sexism. A model of predicted 
transformational IT leadership and organizational performance is developed and tested using a 
simulation-based experiment. Results are discussed, highlighting one unexpected finding, 
implications, and areas for further exploration. The paper concludes by summarizing remarks. 

 
Literature Review 

To answer our research question, the relevant literature on transformational leadership, the 
glass cliff phenomenon, and gender in the information systems field are reviewed.   

 
The Glass Cliff Phenomenon  

Borrowing the glass metaphor from the ‘glass ceiling’ term, Ryan and Haslam (2005) coined 
the term glass cliff to describe an observed tendency for women to be chosen for leadership 
positions during times of low performance, turbulence, crisis, or impending failure. Earlier scenario-
based experiments confirmed this tendency (e.g. Mulcahy & Linehan, 2014).  

Many factors are at play in the glass-cliff phenomenon. Some key drivers are selection bias 
based on stereotypes about women and a faulty understanding of the characteristics associated with 
successful emergence from crisis (Ryan et al., 2016). For instance, women tend to be perceived as 
communal, while men tend to be viewed as agentic (Ryan et al., 2016). Further, the common and 
biased beliefs about "good leadership" tend to track with stereotypes associated with masculinity 
(i.e., competence, independence, competitiveness), yet when performance is declining, this 
association no longer applies, and preference is for stereotypically feminine characteristics of 
nurturing, empathy, and compassion (Ryan et al., 2016), and tactfulness and a desire to avoid 
controversy (Morgenroth et al., 2020).   

 
Evolving Leadership Theories in the IT Field 

The information systems discipline is characterized by multiple unique factors that make 
traditional leadership theories less effective at explaining outcomes than in other fields (Eseryel, 
2014). In addition, the dynamic nature of this field suggests that the leadership factors that influence 
organizational outcomes are changing, and thus require frequent attention from researchers. For 
example, researchers found different ways of decision-making, knowledge creation and 
management, politeness behaviors among members, and unique participation behaviors in certain 
IT-enabled organizations. 

Further, many theories do not explore the characteristics of leaders that influence 
transformation in the technology industry, which is characterized by several distinct traits (Pittenger 
et al., 2022). These characteristics include a focus on innovation, a dynamic business environment, 
and unique supply chain characteristics (i.e., short distribution channels, and high production costs 
but negligible distribution costs) (Altinkemer & Guan, 2003). Several IT-based theories are 
developed such as the IT self-leadership (Eseryel, 2020), action-based transformational leadership 
theory (Eseryel & Eseryel, 2013), e-leadership (Avolio et al., 2000), functional & visionary leadership 
theory (Eseryel et al., 2021), and transformational IT leadership theory.  

In this study, we use transformational IT leadership (Eseryel, 2020; Eseryel & Biernath, 
2024) theory because it fits very well for organizations with a specific leader who tries to make an 
outstanding impact in the organization to transform it in a major way. Transformational IT 



24 

 

leadership refers to the ability of a leader to foster a culture of innovative thinking where the 
followers use IT to improve their work processes and outcomes. 

 
The Gender Gap and the Transformational IT Leadership 

Women remain underrepresented in tech leadership positions (Atomico, 2021). The 
percentage of women studying IT has steadily dropped since reaching 37% in 1984 
(ComputerScience.org, 2022) and is now only 18.7% (NSF, 2019). McCain (2022) reported that 
women comprise only 19% of senior vice president positions and 15% of CEO positions in the tech 
industry.  

Many factors that influence the low representation of women in tech have not changed over 
the years - the education pipeline, recruitment, hiring, pay equity, promotion, and retention of 
women are still prevalent concerns in the tech industry today (Deloitte, 2021). Lamar and Shaikh 
(2020) note that the top three barriers reported by women that prevent them from moving into 
leadership positions in the tech industry are gender bias (21%), followed by work/life integration 
(16%), and lack of sponsorship (14%). Extant research identifies the need to understand and reduce 
the gender gap in the Information Systems field through approaches such as understanding barriers 
(Reid et al., 2010).  

One well-documented result of the IT gender gap is a culture of sexism (Harmon & Walden, 
2020). As male IT professionals work with other males, they can develop experience-based norms 
and expectations of what constitutes a good coworker, as these norms develop socially. The social 
construction of these norms is driven by interactions among mostly males. These norms may reflect 
masculine characteristics, and over time, a masculine, or in some cases, even sexist organizational 
culture may emerge.  

Business literature commonly views culture as "a pattern of shared basic assumptions learned 
by a group and to be taught to new members as the correct way to perceive and think as it solved its 
problems of external adaptation and internal integration well enough to be considered valid" 
(Schein, 2010, p. 18). Occupational culture is defined as a unique culture related to a field, which is 
formed as a corollary of specific tasks and expertise (Jacks, 2012). For instance, IT professionals 
support technology services, including hardware and software, and bring expertise in system analysis 
and design, programming, database administration, project management, and technical support 
(Jacks & Palvia, 2014). The IT occupational culture includes technical jargon, ideation, and unique 
values (Jacks & Palvia, 2014). As such, the IT field has an occupational culture that is different from 
other business aspects (Annabi & Lebovitz, 2018), which may lead to some adverse organizational 
outcomes (Jacks et al., 2018).  

In addition to sexism, male-dominated fields tend to be characterized by a culture of 
masculinity (Blondé et al., 2022). While a culture of masculinity can imply gender-differentiated 
roles, masculinity refers to a sense of competitiveness, individual accomplishment, and propensity to 
succeed in risky endeavors. Individuals who score highly in masculinity tend to seek opportunities to 
set themselves apart from others (Furner & George, 2012), often by taking on challenging tasks and 
highlighting their accomplishments relative to their peers. Individuals who report lower masculinity, 
on the other hand, tend to be more nurturing, supportive, and communal (Hofstede, 2011).  

While a majority of gender in transformational leadership studies find that female leaders are 
perceived as being more transformational, Hypothesis 1 predicts that in a technologically intensive 
environment, a culture of masculinity will dominate, where leaders value individual achievement and 
measurable performance over relationship building and collaboration, and this will lead subordinates 
to strive to outperform each other, resulting in a competitive race to stand out. In this setting, it is 



25 

 

predicted that subjects will view male leaders as more masculine, fostering a sense of competition 
that will push employees to go beyond transactional expectations, and as such, male IT leader 
candidates will be perceived as more transformational.  

 
H1: Within the IT field, male leader candidates will be perceived as higher in terms of 

transformational IT leadership. 
 

 
Sexism and Perceptions of Transformational IT Leadership 

The IT field, similar to some other male-dominated fields, is characterized by a culture of 
sexism (Matwyshyn, 2003). Occupational terminology is rampant with sexist terms such as 
motherboard, grandfather, father backups, and Alexis – a female servant. IT occupational culture-
related barriers that obstruct women include male-dominated environments, gender discrimination, 
and companies not supporting women for leadership positions (Kirton & Robertson, 2018). While 
women are less likely to be promoted, when they are promoted, it is at a minor step up the career 
ladder and often in a career path that moves them further from the core business functions (Alegria, 
2019). Women continue to be underrepresented in tech leadership positions (Atomico, 2021). 
Similarly, benevolent sexism leads to a lack of promotion of women to jobs in which they are 
underrepresented (Hideg & Ferris, 2016). Therefore, we posit that sexism moderates the relationship 
between the leader's gender and the transformation of IT leadership perception as such: 

Sexism may affect female leaders and their work quality because it can "constrain the morale 
and the performance of professionals" (Lawler & Molluzzo, 2016, p. 137). Sexist attitudes may be 
why the glass cliff phenomenon exists (Acar & Sumer, 2018). Glass Cliff refers to female executives 
being more likely to be appointed in high-risk situations when a firm's performance is declining 
(Ryan & Haslam, 2007). The already downward trajectory increases the likelihood of failure, which, 
in return, may negatively and permanently impact women's reputations and leadership careers (Ryan 
et al., 2007). 

Since sexism refers to prejudice based on stereotypes, we anticipate that subjects who score 
higher in terms of sexism will harbor more stereotypical expectations regarding female leaders, 
specifically that they are nurturing, collaborative, supportive, and collegial rather than competitive. 
We expect that this biased view of females will lead those who score highly on the sexism scale to 
view female IT leader candidates as more transformative and that this will supersede the effects of 
masculinity described in hypothesis 1. In summary, we predict that a culture of masculinity will lead 
IT professionals to view male candidates as more transformative because they can foster a 
competitive work environment (H1). However, if the IT professional scores highly in terms of 
sexism, their expectations of female leaders will supersede their beliefs regarding the relationship 
between a competitive environment and transformational IT leadership, and they will rate female 
candidates as more transformational (H2).  

 
H2: Sexist responders will rate female candidates higher in terms of transformational IT 

leadership. 
 
Organizational Performance & Predicted IT Leadership Success 

A variety of individual organizational and environmental factors influence leadership success, 
and definitions of success vary depending on situational factors. For many leaders, success is 
determined by the financial performance of the organization.  



26 

 

For example, Chen et al. (2019) explored CEO transformational leadership on firm 
performance and examined a potential difference in the moderating role of environmental 
uncertainty on the relationship between transformational leadership and firm performance. They 
contend that high technology uncertainty and sophisticated information technology information are 
considered different types of environmental uncertainty, which may explain a negative influence on 
the relationship between transformational leadership and firm performance. They hypothesized that 
"technology uncertainty negatively moderates the positive effect of CTL on exploratory innovation" 
(Chen et al., 2019, p. 88). Although the impact of technology innovation and uncertainty were 
evident, this hypothesis was not supported. However, demand and technology uncertainty had a 
partial mediating role in the relationship between CTL and firm performance. 

The relationship between leadership style and organizational performance has been studied 
extensively. Relevant to this study, glass cliff researchers suggest that leadership success is 
determined in part by organizational performance trajectory, which refers to the relative change in 
the entity's performance at a given point in time. Corporate performance trajectory is higher when 
growth has been improving until the time of measurement and lower when growth has been 
declining. For example, Yang et al. (2021) examined a sample of U.S. college football coaches. They 
found that when leaders take over high-performing organizations, if there is a decline, then the rate 
of performance decline is lower, suggesting a positive relationship between performance trajectory 
and leader success.  

D'Aventi (1989) notes that managing declining firms is challenging because organizations are 
systems that tend to get caught in positive or negative reinforcing cycles. Hence, identifying the cycle 
drivers and correcting the negative drivers is complicated by social, cultural, and political factors and 
by the fact that the drivers are only sometimes visible to leadership. Moreover, according to 
D'Aventi (1989), the mechanism that drives these negative cycles also applies to positive ones. 
Chaganti et al. (2005, p. 133) echo this sentiment and add that an incumbent CEO must not only 
manage the performance trajectory of the firm but must also "address repeated transitions between 
performance cycles of decline, stagnation, and growth." 

Consistent with the findings of several studies within the glass cliff literature and the findings 
of Yang et al. (2021), D'Aventi (1989), and Chaganti et al. (2005), we anticipate that when a firm is in 
a state of growth, expectations of leadership success for incumbent leaders will be higher than it 
would if the firm was in a state of decline.   

 
H3: A positive organizational performance trajectory will increase predicted IT leadership 

success. 
 
According to Jas and Skelcher (2005, p. 195), "[the] improvement of organizational 

performance is a major theme in contemporary debates about the governance and management of 
public organizations." The turnaround paradigm represents a substantial body of literature that 
examines the factors that influence the efforts to improve performance when organizational 
performance is declining. For example, Jas and Skelcher (2005) argue that in the absence of 
leadership capability and cognition, organizations fail to self-initiate turnaround and are at higher 
risk of failure. As a result, organizations in a state of performance decline will often replace 
leadership (Bodolica & Spraggon, 2021) to instigate substantial change that results in turnaround.  

While research on leadership during periods of declining organizational performance is 
extensive, research on the influence of gender on leadership success is relatively limited, particularly 
within the context of the IT workforce. Within the glass cliff paradigm, the role of gender 



27 

 

expectations of leaders is well studied. However, few glass cliff studies measure performance 
expectations, and fewer are still conducted in an IT-intensive setting.  

According to Morgenroth et al. (2020), a common approach to the design of glass cliff 
studies is to develop a quasi-experiment in which subjects are presented with two leader candidates, 
one male, and one female, and are presented with two firms, one that is described as doing well, and 
another that is depicted as being in crisis. Findings generally indicate that female candidates are 
preferred when the organization is in crisis (Morgenroth et al., 2020), with many researchers 
explaining this finding by suggesting that stereotypically feminine personality characteristics of 
compassion, collaboration, and communication are desirable when a substantial degree of 
organizational change associated with turnaround is needed.  

While the focus of glass cliff literature is on the tendency to appoint female leaders to 
organizations in crisis, no literature was found during the conduct of this study that explores leader 
gender preferences when the organization is in a state of high and improving performance. Previous 
literature on the effect of leadership characteristics on firm performance, which were not conducted 
in IT work contexts, suggests that critical leadership characteristics include charisma (Awamleh & 
Gardner, 1999), conscientiousness (Colbert et al., 2014), strategic vision (Zaccaro & Banks, 2001), 
experience, emotional intelligence, and intelligence (Cavazotte et al., 2012). 

Revisiting the literature on the gender gap in the IT field, which was outlined while 
describing hypothesis 1, it was argued that the IT field was characterized by a masculine culture 
driven by achievement and a focus on individual accomplishment. Suppose this masculine culture 
also characterizes those firms that are experiencing improving performance. In that case, it stands to 
reason that evaluators will expect that a leader who embodies these masculine characteristics would 
be best suited to continue the trajectory of performance improvement and would thus prefer a male 
leader candidate. In addition, the positive effect of prior leader experience on organizational 
performance has been demonstrated in multiple studies (Desai et al., 2016). Since the IT industry is 
male-dominant, likely, the number of available experienced male leaders is simply higher, leading to 
a tendency to select male leader candidates.  

 
H4: Male information technology leaders will be perceived to have higher levels of IT 

leadership success when organizational performance is increasing. 
 
Figure 1 - Research Model 

 



28 

 

 
Method 

To evaluate the research model, a scenario-based experiment was conducted in which 
subjects were asked to assume the role of a hiring professional tasked with considering applicants 
for a leadership position. The experiment is described in the following subsection.   

 
Research Design 

First, a scenario-based experiment with a 2x2 factorial design (candidate sex and 
organizational performance trajectory) was developed. Scenario-based experiments allow researchers 
to examine the effects of specific manipulated factors on individual judgment and cognition while 
controlling for factors that are not modeled (Rungtusanatham et al., 2011). Next, a hiring scenario 
was developed in which subjects are asked to assume the role of a hiring professional considering 
applicants for a Director of Information Technology (IT) role. The subjects are provided with a job 
description, a one-paragraph Financial Times article about the company that indicates either 
declining performance or growth, and a short, half-page resume for one candidate. After reading this 
material, subjects were asked to predict the candidate's performance impact and to indicate their 
potential for transformational IT leadership. Each subject evaluated one candidate, consistent with 
the protocol employed by (Furner & Grubb, 2020). Subjects were also asked a series of questions 
related to sexism and demographic questions. 

   
Measures 

Both organizational performance trajectory and candidate sex were manipulated during the 
experiment. Specifically, organizational performance trajectory (TRAJECTORY) was manipulated 
using a 1-paragraph Financial Times article along with a line graph, which indicated either declining 
(coded as 1) or increasing (coded as 2) stock performance. Candidate sex (C_GENDER) was 
manipulated using resumes that included a small photo of the candidate (male is coded as 1; female 
is coded as 2) along with culturally traditional names that matched the sex of the candidate's photo. 
Manipulation checks for TRAJECTORY and C_GENDER were also conducted. Sexism (SEXISM) 
was assessed using Glick and Fiske's (1997) 22-item Ambivalent Sexism Inventory, where both 
dimensions, hostile sexism and benevolent sexism, were included. Predicted success (SUCCESS) was 
measured using three questions developed for this study. More precisely, a 5-point Likert-type scale 
was used where 1 was "very poor," and 5 was "very good" to measure participants' responses. The 
questions asked were:  

(1) What do you think will be the success of this company after [candidate's name] works in 
this position for five years? 

(2) To what extent will [candidate's name] be able to influence the company to change in 
positive ways within five years? 

(3) To what extent is the success or failure of this company dependent on [candidate's 
name]? 

Transformational IT leadership (TRANSFORM_LEAD) was measured using Eseryel and Biernath’s 
(2024) 22-item scale.  
 
Subjects 

Data were collected from undergraduate student subjects at two universities, one in Turkey 
and one in the Netherlands. These students had an average of 5.8 months of professional work 
experience. Students from these two countries were chosen because they differ on Hofstede's (2011) 



29 

 

masculinity dimension and, as such, are expected to provide sufficient variance on the sexism 
variable.  Participation was voluntary. Each survey was presented to the participants in their native 
language and included candidate profiles that provided typical names and experiences from their 
country. Five hundred sixty-two responses were collected, with 281 from Turkey and 281 from the 
Netherlands. Cases were excluded if subjects did not answer any of the analyzed questions, yielding 
a final usable sample of 441 subjects.   

 
Analysis and Results 

 The data were analyzed with IBM’s Statistical Package for the Social Sciences (SPSS) version 
26. Before testing the main effects, a manipulation check was run to ensure that subjects correctly 
identified the firm's performance trajectory (TRAJECTORY) and the candidate's sex 
(C_GENDER). The bivariate correlation between TRAJECTORY and the corresponding 
manipulation check is 0.96 and was significant. Additionally, the bivariate correlation between 
C_GENDER and the corresponding manipulation check was 1.00 and significant. Finally, we 
conducted an exploratory factor analysis (EFA) using principal components analysis with varimax 
rotation on the items for SEXISM, SUCCESS, AND TRANSFORM_LEAD. Factor loadings 
ranged from 0.69 to 0.91 for SEXISM, from 0.48 to 0.79 for SUCCESS, and from 0.49 to 0.88 for 
TRANSFORM_LEAD, indicating discriminant validity. Cronbach alphas were 0.926 for SEXISM, 
0.805 for SUCCESS, and 0.943 for TRANSFORM_LEAD. Means, standard deviations (Std. Dev.), 
and bivariate correlations (r) are presented in Table 1.   

Hypotheses 1 and 2 can be tested using regression analysis. Hypotheses 3 and 4 can be 
tested using a second regression analysis. A regression analysis was conducted to test hypotheses 1 
and 2, with predicted success as the dependent variable and organizational performance trajectory 
and an interaction term of candidate sex multiplied by organizational performance trajectory as 
independent variables. The regression equation was significant (F(2,441) = 6.07 p=-0.003; adj. R2 = 
0.027).   
 
Table 1 - Means, Standard Deviations, and Bivariate Correlations  
 
Variables  Mean  Std. Dev.  r(1)  r(2)  r(3)  
TRAJECTORY (1) 1.52  0.50  1.00 0.05  -0.01  
C_GENDER (2)  1.52  0.50  0.05  1.00  0.03  
SEXISM (3)  4.05  1.20  -0.01  0.03  1.00  
SUCCESS 5.45  0.94        
TRANSFORM_LEAD  5.30  0.75        
*** = p < 0.001; ** = p < 0.050; and * = p < 0.100  
TRAJECTORY is an indicator variable; it is equal to 1 when a participant received a declining 
performance scenario and 2 if given an increasing performance scenario. 
C_GENDER is an indicator variable; it is equal to 1 for male participants and equal to 2 for 
female participants. 
SEXISM – is a factored variable based on Glick and Fiske's (1997) 22-item Ambivalent Sexism 
Inventory.  
SUCCESS - is a factored variable using three items created for this study. 
TRANSFORM_LEAD – is a factored variable adapted from Podsakoff, MacKenzie, and 
Bommer's (1996) 22-item Transformational Leadership Behavioral Scale for use in an IT context. 

  



30 

 

A regression analysis was conducted to test hypothesis 3, with perceived transformational IT 
leadership as the dependent variable and sexism and an interaction term of Candidate Sex X sexism 
as independent variables. The regression equation was significant (F(2,439)= 10.11, p < 0.001; adj. 
R2 = 0.040). Regression results are presented in Table 2.   

 
Table 2 - Results of Regression Analysis  
 

Dependent Var Hypothesis Independent 
Var Beta SE T Supported 

TRANSFORM_ 
LEAD 

H1  GENDER  -0.21  0.10  -2.03* Yes 

H2  SEXISM X 
C_GENDER 0.08  0.02  4.23** Yes 

SUCCESS 
H3  TRAJECTORY 0.29  0.09  3.21** Yes 

H4  TRAJECTORY X 
C_GENDER 0.13  0.40  3.21** No 

** = p < 0.001; * = p < 0.050   
TRAJECTORY is an indicator variable; it is equal to 1 when a participant received a declining 
performance scenario and 2 if given an increasing performance scenario.   

C_GENDER is an indicator variable; it is equal to 1 for male participants and equal to 2 for 
female participants.   

SEXISM – is a factored variable based on Glick and Fiske's (1997) 22-item Ambivalent Sexism 
Inventory.    

SUCCESS - is a factored variable using three items created for this study.   
TRANSFORM_LEAD – is a factored variable adapted from Podsakoff, MacKenzie, and 
Bommer's (1996) 22-item Transformational Leadership Behavioral Scale for use in an IT context.  

 
Hypothesis 1 predicted that within the IT field, male leader candidates would be rated higher 

in transformational IT leadership. This hypothesis was supported. Hypothesis 2 predicted that the 
influence of candidate sex on perceived transformational IT leadership would be different for 
respondents who score higher on sexism and that they would rate female candidates as higher in 
transformational IT leadership. This hypothesis was supported. Findings indicate that when the 
respondent scores higher in terms of sexism, they tend to rate female candidates higher in terms of 
transformational IT leadership. Hypothesis 3 predicted that when organizational performance 
trajectory was positive, predictions of leadership success would increase. This hypothesis was 
supported. Finally, Hypothesis 4 predicted that when organizational performance trajectory was 
positive, male leader candidates would be rated higher in terms of leadership success. This 
hypothesis was not supported. While a positive relationship was identified, female leader candidates 
were rated higher in terms of leadership success.    

 
Discussion 

The objective of this study was to evaluate the effect of leadership candidate characteristics, 
including sex, on predictions of transformational IT leadership and candidate success within the 
context of the glass cliff paradigm. This study carries implications for researchers as well as IT 
professionals, particularly those involved in decisions affecting the appointment of leaders. Findings 
are discussed along with research implications, followed by practical implications, limitations, and 
opportunities for future research.  

 



31 

 

Theoretical Contributions  
Findings supported a relationship between candidate gender and perceptions of 

transformational leadership, in which male candidates are rated higher in terms of IT 
transformational leadership (H1). This finding differs from the consensus within the glass cliff 
paradigm, in which female leaders tend to be viewed as more capable of inspiring subordinates to go 
beyond their transactional obligations. This finding is attributed to differences in the culture in the 
IT field, which is male-dominated and tends to be masculine, thus favoring male candidates. Further 
findings supported an interaction between decision-maker sexism and the relationship between 
candidate gender and organizational performance trajectory on predicted success, in which female 
candidates were rated as more transformational when the respondent scored higher in terms of 
sexism (H2). This finding is consistent with the cultural literature on masculinity, in which 
individuals characterized by higher levels of masculinity not only espouse gender-based roles but 
also view women as more nurturing and social. In contrast, they view men as more focused on 
individual accomplishment Hofstede, 2011). For the glass cliff paradigm, this implies the 
phenomenon in which female leaders tend to be appointed to leadership opportunities in which the 
odds of success are lower. It occurs partly because the people making the assignment may believe 
that a transformational leader would be better suited to turn around the poor-performing team. If 
they are sexist, they may believe that female leaders will be more successful at facilitating the 
transformation. While the r-squared for this regression was relatively low, the dependent variable, 
perceptions of transformational IT leadership are complex and nuanced, and as such a vast number 
of factors, including subject-level psychological factors, organizational cultural derived perceptions 
of leadership expectations, and many others influence this outcome. As our understanding of the 
factors that drive perceptions of transformational IT leadership evolves, our ability to develop 
models that explain the factor should improve as well. In the meantime, our findings that gender 
and the interaction between gender and sexism are important to our understanding of leadership in 
IT, given the traditional male-dominated nature of the field. While low, these r-squared values are 
not inconsistent with those found in other studies that have had a substantial impact on emerging 
paradigms (e.g., De Bondt & Thaler, 1985; Fan & Wong, 2002). 

This study predicted that organizational performance trajectory would be positively 
associated with predicted success (H3), and evidence supports this relationship. Consequently, the 
findings are consistent with the premise of the glass cliff paradigm that the underlying factors that 
influence organizational outcomes tend to persist, which is also consistent with Yang et al. (2021), 
and D'Aventi (1989). 

Findings did not support a moderated relationship between candidate gender and the 
relationship between organizational performance and perceived leadership success in which male 
candidates are rated higher in terms of perceived leadership success when organizational 
performance was higher. Rather, an interaction effect was observed in which female candidates were 
rated higher on perceived leadership success when organizational performance was higher. This 
unexpected finding might be explained by nuance in organizational leadership theory. When 
organizational performance is strong, transformational leadership may not be as effective as 
transactional leadership since maintaining the rate of performance growth is preferable to 
transforming or changing performance growth. This may not be the case in every industry. As 
Loderer et al. (2016) point out, maintaining performance growth in the IT industry is difficult 
because of frequent disruptions in the business environment, resulting in a situation where 
transformational leaders tend to outperform transactional leaders over the long term. Within the IT 
industry, female candidates may be rated as more apt to be successful leaders when the organization 



32 

 

is experiencing success because they are viewed as less assertive and thus less likely to support 
substantial change to operations, which may alter the organization's performance trajectory. This 
unexpected finding suggests that this relationship is quite nuanced and that exploration of this 
relationship could augment the leadership paradigm. While the r-squared for this model was 
relatively low, the outcome and predictions of leadership success are complex and dependent on a 
variety of both psychological and organizational factors. Consistent with the research objectives, the 
model is relatively simple and focused, and as a result, one would only expect to explain a limited 
proportion of the variance in this outcome. The variance explained in this model is not inconsistent 
with that reported by other studies that examined a relatively small factor that influenced a 
substantially complex outcome (Malmendier & Tate, 2005). 

 
Practical Implications  

From a theoretical perspective, hypothesis 4 represents a potential explanation for the 
phenomenon underlying the tendency to appoint female candidates to leadership positions when the 
organization is in a state of performance decline. This finding also carries significant implications for 
hiring and appointment teams tasked with selecting leaders. Members of these teams should reflect 
on their personal biases regarding both men and women. This includes what they may believe are 
positive biases, such as women being more transformational leaders than men, before considering 
candidates. The implications of continuing the trend of appointing women to leadership positions of 
low-performing organizations have already been articulated and include substance reputation and 
career roadblocks, as well as a perpetuation of gender stereotypes regarding leadership. 

Hypothesis 3 found that when sexism is not considered, leader gender does not significantly 
influence perceptions of transformational leadership. This implies that hiring/appointment teams 
can make decisions without gender bias if the members are not sexist. Although controversial, it may 
be prudent for organizations to consider asking hiring/appointment teams to screen for signs of 
sexism, perhaps employing a questionnaire to help identify and address biases before making 
decisions. However, there are challenges to this recommendation, including socially desirable 
reporting bias and time issues, as well as a potential loss of trust among the hiring team members. 

Hypothesis 2 found that expectations of success were higher when the candidate was female. 
Expectation confirmation theory suggests that when expectations are higher, leaders may be 
evaluated using higher standards than when expectations are low. Therefore, boards of trustees and 
others who assess leaders should be aware of expectation/confirmation bias when evaluating 
leaders, particularly female leaders.   

 
Limitations and Future Research 

The findings of this study advance the glass cliff paradigm; however, they are limited by the 
study design and sample characteristics. The most substantial determination is that the role of 
sexism in perceptions of transformational leadership depends on the conceptualization of sexism, 
which is limited by the study design in two ways. First, data were collected in Turkey and the 
Netherlands. These two countries were selected specifically because they are on opposite ends of the 
masculinity spectrum (see Hofstede, 2011). By choosing these two countries, we expected an 
acceptable variance on the sexism scale to facilitate analysis. However, this sample is limited, and 
other cultural or country-specific factors could come into play. For this reason, future studies could 
consider the same relationships but employ a sample from other countries, perhaps from countries 
that score in the middle on the masculinity dimension. This study measured sexism at the individual 



33 

 

level, mitigating this concern. However, more reflective samples tend to yield more generalizable 
results, and therefore, replication studies would be recommended as future research. 

Second, the sample consisted of students. While students are prone to sexism, and our 
results indicated variation on the sexism scale, there is reason to believe that students are more 
progressive than the population at large, which may have affected our results. Further, even if the 
subjects were sexist, the topic of this study does lend itself to socially desirable reporting, potentially 
conflating the measurement of the sexism variable. Finally, beyond the measure of sexism, students 
are unlikely to have been involved in appointing leaders and may not fully understand organizational 
performance trajectory, although we did get adequate variation on this variable. As a result, future 
studies could seek to confirm or disprove these findings by sampling different populations, ideally 
those involved in leader appointment decisions.  

Despite the limitations of the sample, common to many studies, our findings raise several 
new questions regarding the glass cliff phenomenon. First, if perceptions of transformational IT 
leadership combined with attitudes about women as being more transformational influence 
appointment decisions when performance is declining, what other leadership style perceptions might 
be tied to gender and come into play during leadership appointment decisions? The literature on 
leadership styles is vast. Researchers may consider which leadership style topologies may be 
influenced by gender bias and model these relationships. 

From the human resources point of view, the social and psychological characteristics of 
hiring/appointment team members are complex.  Hiring decisions are also likely influenced by 
various organization-specific, industry-specific, and environmental factors. By studying these factors, 
researchers may be able to augment our understanding of this phenomenon and hopefully mitigate 
its harmful effects on the careers of female IT professionals.  

Finally, future research in the IT field should test our findings for cisgender women for 
other genders that constitute a minority. We suggest operationalizing gender as consisting of various 
aspects including (a) physiological/bodily aspects; (b) gender identity or self-defined gender; (c) legal 
gender; and (d) social gender in terms of norm-related behaviors and gender expressions following 
(Lindqvist et al., 2021, p. 333). Future research that enhances our understanding of the biases faced 
by all genders is needed to create gender equality for all. Understanding biases against various 
genders and creating means to eliminate gender gaps are likely to improve organizational 
performance and increase employee satisfaction. 

 
Conclusion 

CEO replacement is common during periods of changes in organizational performance 
trajectory (Downes, 2019). The glass cliff phenomenon, in which female candidates tend to be 
appointed to teams in which performance is declining, is well documented. However, the 
psychological mechanisms of the members of the hiring/appointment teams that lead to this 
phenomenon are not. It stands to reason that these mechanisms are complex and entail many 
factors, and our findings suggest that those mechanisms may be industry-dependent. They likely vary 
substantially from team to team and depend on other organizational industry-level factors. In this 
study, we provide evidence to support one potential explanation: Hiring/Appointment team 
members believe that transformational IT leaders will be more effective at turning around poorly 
performing teams or organizations and that if members are sexist, they may perceive female leaders 
as more transformational than male leaders. While there is still much to learn about the drivers of 
this phenomenon, this study should constitute an essential step in understanding this phenomenon 



34 

 

and, through understanding, empower the mitigation of the damage that the glass cliff phenomenon 
has on the careers of female IT professionals.  

 
References 

Acar, F. P., & Sumer, H. C. (2018). Another test of gender differences in assignments to precarious 
leadership positions: Examining the moderating role of ambivalent sexism. Applied Psychology: 
An International Review, 67(3), 498-522. https://doi.org/10.1111/apps.12142  

Akerlof, G. A. (1978). The market for “lemons”: Quality uncertainty and the market mechanism. In 
P. Diamond & M. Rothschild (Eds.), Uncertainty in Economics (pp. 235-251). Academic Press. 
https://doi.org/10.1016/B978-0-12-214850-7.50022-X  

Altinkemer, K., & Guan, J. (2003). Analyzing Protection Strategies for Online Software Distribution. 
J. Electron. Commer. Res., 4(1), 34-48.  

Annabi, H., & Lebovitz, S. (2018). Improving the retention of women in the IT workforce: An 
investigation of gender diversity interventions in the USA. Information Systems Journal, 28(6), 
1049-1081. https://doi.org/10.1111/isj.12182  

Atomico. (2021). The 9th annual state of European tech 21. https://stateofeuropeantech.com/ 
Avolio, B. J., Kahai, S., & Dodge, G. (2000). E-leadership: implications for theory, research and 

practice. The Leadership Quarterly, 11(6), 615-668.  
Awamleh, R., & Gardner, W. L. (1999). Perceptions of leader charisma and effectiveness: The 

effects of vision content, delivery, and organizational performance. The Leadership Quarterly, 
10(3), 345-373. https://doi.org/10.1016/S1048-9843(99)00022-3  

Blondé, J., Gianettoni, L., Gross, D., & Guilley, E. (2022). Hegemonic masculinity, sexism, 
homophobia, and perceived discrimination in traditionally male-dominated fields of study: A 
study in Swiss vocational upper-secondary schools. International Journal for Educational and 
Vocational Guidance, 1-22. https://doi.org/10.1007/s10775-022-09559-7  

Bodolica, V., & Spraggon, M. (2021). Leadership in times of organizational decline: a literature 
review of antecedents, consequences and moderators. International Journal of Organizational 
Analysis, 29(2), 415-435. https://doi.org/10.1108/IJOA-04-2020-2123  

Bonner, N. A. (2010). Predicting leadership success in agile environments: An inquiring systems 
approach. Academy of Information and Management Sciences Journal, 13(2), 83-103.  

Bruckmüller, S., & Branscombe, N. R. (2010). The glass cliff: When and why women are selected as 
leaders in crisis contexts. British Journal of Social Psychology, 49(3), 433-451. 
https://doi.org/10.1348/014466609X466594  

Cavazotte, F., Moreno, V., & Hickmann, M. (2012). Effects of leader intelligence, personality and 
emotional intelligence on transformational leadership and managerial performance. The 
Leadership Quarterly, 23(3), 443-455. https://doi.org/10.1016/j.leaqua.2011.10.003  

Chaganti, R., Damanpour, F., & Mankelwicz, J. (2005). CEO power cycles and corporate 
performance cycles: An examination of the relationship between changes in power and 
changes in performance. In M. A. Rahim & R. T. Golembiewski (Eds.), Current Topics in 
Management (1 ed., Vol. 10, pp. 133-160). Routledge/Taylor and Francis Group. 
https://doi.org/10.4324/9780203794043-8  

Chen, J.-X., Sharma, P., Zhan, W., & Liu, L. (2019). Demystifying the impact of CEO 
transformational leadership on firm performance: Interactive roles of exploratory innovation 
and environmental uncertainty. Journal of Business Research, 96, 85-96. 
https://doi.org/10.1016/j.jbusres.2018.10.061  

https://doi.org/10.1111/apps.12142
https://doi.org/10.1016/B978-0-12-214850-7.50022-X
https://doi.org/10.1111/isj.12182
https://stateofeuropeantech.com/
https://doi.org/10.1016/S1048-9843(99)00022-3
https://doi.org/10.1007/s10775-022-09559-7
https://doi.org/10.1108/IJOA-04-2020-2123
https://doi.org/10.1348/014466609X466594
https://doi.org/10.1016/j.leaqua.2011.10.003
https://doi.org/10.4324/9780203794043-8
https://doi.org/10.1016/j.jbusres.2018.10.061


35 

 

Colbert, A. E., Barrick, M. R., & Bradley, B. H. (2014). Personality and leadership composition in 
top management teams: Implications for organizational effectiveness. Personnel Psychology, 
67(2), 351-387. https://doi.org/10.1111/peps.12036  

ComputerScience.org. (2022, September 9). Women in computer science. 
https://www.computerscience.org/resources/women-in-computer-science/ 

Connell, R. (2013). Gender and power: Society, the person and sexual politics. John Wiley and Sons.  
Crowston, K., Howison, J., Masango, C., & Eseryel, U. Y. (2007). The balancing act: The role of 

face-to-face meetings in technology-supported self-organizing distributed teams. Transactions 
on Professional Communication, 50(3), 185-203. https://doi.org/10.1109/TPC.2007.902654  

Crowston, K., Li, Q., Wei, K., Eseryel, U. Y., & Howison, J. (2007). Self-organization of teams in 
free/libre open source software development. Information and Software Technology, 49(6), 564-
575. https://doi.org/10.1016/j.infsof.2007.02.004  

D'Aventi, R. A. (1989). The aftermath of organizational decline: A longitudinal study of the strategic 
and managerial characteristics of declining firms. The Academy of Management Journal, 32(3), 
577-605. https://doi.org/10.2307/256435  

De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact? The Journal of finance, 40(3), 
793-805. https://doi.org/10.1111/j.1540-6261.1985.tb05004.x  

Deloitte. (2021). TMT Preditions 2022 (Deloitte Insights, Issue. Deloitte. 
https://www2.deloitte.com/content/dam/insights/articles/GLOB164581_TMT-
Predictions-2022/DI_TMT-predictions-2022.pdf 

Desai, M. N., Lockett, A., & Paton, D. (2016). The effects of leader succession and prior leader 
experience on postsuccession organizational performance. Human Resource Management, 55(6), 
967-984. https://doi.org/10.1002/hrm.21700  

Downes, M. (2019). Connecting Governance to CEO Replacement and Organizational Recovery. 
Advances in Business Research, 9(1), 64-77.  

Eden, D. (1992). Leadership and expectations: Pygmalion effects and other self-fulfilling prophecies 
in organizations. The Leadership Quarterly, 3(4), 271-305. https://doi.org/10.1016/1048-
9843(92)90018-B  

Eseryel, U. Y. (2014). IT-enabled knowledge creation for open innovation. Journal of the Association for 
Information Systems, 15(11), 805-834. https://doi.org/10.17705/1jais.00378  

Eseryel, U. Y. (2020). Enabling IT self-leadership in online education. Interdisciplinary Journal of e-Skills 
and Lifelong Learning, 16(123-142). 
https://doi.org/10.28945/4684https://doi.org/https://doi.org/10.28945/4684  

Eseryel, U. Y., & Biernath, P. (2024). The influence of transformational IT leadership on the IT 
leadership of followers. Journal of Leadership and Management, 10(1), 11-29. https://bit.ly/titl-itl  

Eseryel, U. Y., Crowston, K., & Heckman, R. (2021). Functional and Visionary Leadership in Self-
Managing Virtual Teams. Group & Organization Management, 46(2), 424-460. 
https://doi.org/10.1177/1059601120955034  

Eseryel, U. Y., & Eseryel, D. (2013). Action-embedded transformational leadership in self-managing 
global information technology teams. The Journal of Strategic Information Systems, 22(2), 103-120. 
https://doi.org/10.1016/j.jsis.2013.02.001  

Eseryel, U. Y., Wei, K., & Crowston, K. (2020). Decision-making processes in community-based 
free/libre open source software development teams with internal governance: An extension 
to decision-making theory. Communications of the Association for Information Systems, 46, 484-510, 
Article 20. https://doi.org/10.17705/1CAIS.04620  

https://doi.org/10.1111/peps.12036
https://www.computerscience.org/resources/women-in-computer-science/
https://doi.org/10.1109/TPC.2007.902654
https://doi.org/10.1016/j.infsof.2007.02.004
https://doi.org/10.2307/256435
https://doi.org/10.1111/j.1540-6261.1985.tb05004.x
https://www2.deloitte.com/content/dam/insights/articles/GLOB164581_TMT-Predictions-2022/DI_TMT-predictions-2022.pdf
https://www2.deloitte.com/content/dam/insights/articles/GLOB164581_TMT-Predictions-2022/DI_TMT-predictions-2022.pdf
https://doi.org/10.1002/hrm.21700
https://doi.org/10.1016/1048-9843(92)90018-B
https://doi.org/10.1016/1048-9843(92)90018-B
https://doi.org/10.17705/1jais.00378
https://doi.org/10.28945/4684
https://doi.org/https:/doi.org/10.28945/4684
https://bit.ly/titl-itl
https://doi.org/10.1177/1059601120955034
https://doi.org/10.1016/j.jsis.2013.02.001
https://doi.org/10.17705/1CAIS.04620


36 

 

Fan, J. P., & Wong, T. J. (2002). Corporate ownership structure and the informativeness of 
accounting earnings in East Asia. Journal of accounting and economics, 33(3), 401-425. 
https://doi.org/10.1016/S0165-4101(02)00047-2  

Fiedler, F. E. (1992). Time-based measures of leadership experience and organizational performance: 
A review of research and a preliminary model. The Leadership Quarterly, 3(1), 5-23. 
https://doi.org/10.1016/1048-9843(92)90003-X  

Furner, C. P., & George, J. F. (2012). Cultural determinants of media choice for deception. Computers 
in Human Behavior, 28(4), 1427-1438. https://doi.org/10.1016/j.chb.2012.03.005  

Furner, C. P., & Grubb, L. Galyani Moghaddam, G. (2010). Information technology and gender gap: 
Toward a global view. The electronic library, 28(5), 722-733. 
https://doi.org/10.1108/02640471011081997The influence of observable interview 
behaviors on the willingness to accept a job offer. Amity Journal of Management, 8(2), 29-39. 
https://www.amity.edu/gwalior/ajm/pdf/ajm_v8n2.pdf  

Glick, P., & Fiske, S. T. (1997). Hostile and benevolent sexism: Measuring ambivalent sexist 
attitudes toward women. Psychology of Women Quarterly, 21(1), 119–135. 
https://doi.org/10.1111/j.1471-6402.1997.tb00104.x  

Greer, L. L., Homan, A. C., De Hoogh, A. H. B., & Den Hartog, D. N. (2012). Tainted visions: The 
effect of visionary leader behaviors and leader categorization tendencies on the financial 
performance of ethnically diverse teams. Journal of Applied Psychology, 97(1), 203-213. 
https://doi.org/10.1037/a0025583  

Harmon, K. A., & Walden, E. A. (2020). Comparing three theories of the gender gap in information 
technology careers: The role of salience differences. Journal of the Association for Information 
Systems, 22(4), 1099-1145. https://doi.org/10.17705/1jais.00690  

Hickman, L., & Akdere, M. (2017). Development of effective IT leadership behaviors: A review. 
Twelfth Midwest Association for Information Systems Conference, Springfield, Illinois. 

Hideg, I., & Ferris, D. L. (2016). The compassionate sexist? How benevolent sexism promotes and 
undermines gender equality in the workplace. Journal of Personality and Social Psychology, 111(5), 
706–727. https://doi.org/10.1037/pspi0000072  

Hofstede, G. (1984). Culture's consequences : International differences in work- related values (Vol. 5). Sage 
Publications, Inc.  

Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online readings in 
psychology and culture, 2(1), 2-26, Article 8. https://doi.org/10.9707/2307-0919.1014  

Jacks, T. (2012). An examination of occupational culture: Interpretation, measurement, and impact (Publication 
Number 3525769) [Doctor of Philosophy, The University of North Carolina at 
Greensboro ProQuest Dissertations Publishing].  

Jacks, T., & Palvia, P. (2014). Measuring value dimensions of IT occupational culture: An 
exploratory analysis. Information Technology and Management, 15(1), 19–35. 
https://doi.org/10.1007/s10799-013-0170-0  

Jacks, T., Palvia, P., Iyer, L., Sarala, R., & Daynes, S. (2018). An ideology of IT occupational culture: 
The ASPIRE values. Advances in Information Systems, 49(1), 93-117. 
https://doi.org/10.1145/3184444.3184451  

Jas, P., & Skelcher, C. (2005). Performance decline and turnaround in public organizations: A 
theoretical and empirical analysis. British Journal of Management, 16(3), 195-210. 
https://doi.org/10.1111/j.1467-8551.2005.00458.x  

https://doi.org/10.1016/S0165-4101(02)00047-2
https://doi.org/10.1016/1048-9843(92)90003-X
https://doi.org/10.1016/j.chb.2012.03.005
https://doi.org/10.1108/02640471011081997
https://www.amity.edu/gwalior/ajm/pdf/ajm_v8n2.pdf
https://doi.org/10.1111/j.1471-6402.1997.tb00104.x
https://doi.org/10.1037/a0025583
https://doi.org/10.17705/1jais.00690
https://doi.org/10.1037/pspi0000072
https://doi.org/10.9707/2307-0919.1014
https://doi.org/10.1007/s10799-013-0170-0
https://doi.org/10.1145/3184444.3184451
https://doi.org/10.1111/j.1467-8551.2005.00458.x


37 

 

Khushk, A., Zengtian, Z., & Hui, Y. (2023). Role of female leadership in corporate innovation: A 
systematic literature review. Gender in Management, 38(3), 287-304. 
https://doi.org/10.1108/GM-01-2022-0028  

Kirton, G., & Robertson, M. (2018). Sustaining and advancing IT careers: Women's experiences 131 
in a UK-based IT company. The Journal of Strategic Information Systems, 27(2), 157–169. 
https://doi.org/10.1016/j.jsis.2018.01.001  

Koburtay, T., Syed, J., & Haloub, R. (2019). Congruity between the female gender role and the 
leader role: A literature review. European Business Review, 31(6), 831-848. 
https://doi.org/10.1108/EBR-05-2018-0095  

Kulich, C., Lorenzi-Cioldi, F., Iacoviello, V., Faniko, K., & Ryan, M. K. (2015). Signaling change 
during a crisis: Refining conditions for the glass cliff. Journal of Experimental Social Psychology, 
61(November), 96-103. https://doi.org/10.1016/j.jesp.2015.07.002  

Lamar, K., & Shaikh, A. (2020, March 5, 2021). Cultivating diversity, equity, and inclusion: How 
CIOs recruit and retain experienced women in tech. Deloitte Insights. 
https://www2.deloitte.com/xe/en/insights/topics/value-of-diversity-and-
inclusion/diversity-and-inclusion-in-tech/recruit-and-retain-experienced-women-in-
technology.html  

Lawler, J., & Molluzzo, J. C. (2016). A perception study of computer science and information 
systems students on bullying prevalence in the information systems profession. Contemporary 
Issues in Education Research, 9(3), 137-144. https://doi.org/10.19030/cier.v9i3.9709  

Lindqvist, A., Gustafsson Senden, M., & Renstrom, E. A. (2021). What is gender anyway: A review 
of the options for operationalizing gender. Psychology and Sexuality, 12(4), 332-344. 
https://doi.org/10.1080/19419899.2020.1729844  

Loderer, C., Stulz, R., & Waelchli, U. (2016). Firm rigidities and the decline in growth opportunities. 
Management Science, 63(9), 3000-3020. https://doi.org/10.1287/mnsc.2016.2478  

Malmendier, U., & Tate, G. (2005). CEO Overconfidence and Corporate Investment. The Journal of 
finance, 60(6), 2661-2700. https://doi.org/10.1111/j.1540-6261.2005.00813.x  

Matwyshyn, A. M. (2003). Silicon ceilings: Information technology equity, the digital divide and the 
gender gap among information technology professionals. Northwestern Journal of Technology and 
Intellectual Property, 2(1), 35-75. 
https://scholarlycommons.law.northwestern.edu/njtip/vol2/iss1/2  

McCain, A. (2022, October 21, 2022). 40 telling women in technology statistics [2023]: Computer science gender 
Rratio. Zippia. https://www.zippia.com/advice/women-in-technology-statistics 

Morgenroth, T., Kirby, T. A., Ryan, M. K., & Sudkämper, A. (2020). The who, when, and why of the 
glass cliff phenomenon: A meta-analysis of appointments to precarious leadership positions. 
Psychological Bulletin, 146(9), 797-829. https://doi.org/10.1037/bul0000234  

Mulcahy, M., & Linehan, C. (2014). Females and precarious board positions: Further evidence of the 
glass cliff. British Journal of Management, 25(3), 425–438. https://doi.org/10.1111/1467-
8551.12046  

Pittenger, L. M., Berente, N., & Gaskin, J. (2022). Transformational it leaders and digital innovation: 
the moderating effect of formal it governance. ACM SIGMIS Database: The DATABASE for 
Advances in Information Systems, 53(1), 106-133.  

Reid, E. M., O'Neill, O. A., & Blair‐Loy, M. (2018). Masculinity in male‐dominated occupations: 
How teams, time, and tasks shape masculinity contests. Journal of Social Issues, 74(3), 579-606. 
https://doi.org/10.1111/josi.12285  

https://doi.org/10.1108/GM-01-2022-0028
https://doi.org/10.1016/j.jsis.2018.01.001
https://doi.org/10.1108/EBR-05-2018-0095
https://doi.org/10.1016/j.jesp.2015.07.002
https://www2.deloitte.com/xe/en/insights/topics/value-of-diversity-and-inclusion/diversity-and-inclusion-in-tech/recruit-and-retain-experienced-women-in-technology.html
https://www2.deloitte.com/xe/en/insights/topics/value-of-diversity-and-inclusion/diversity-and-inclusion-in-tech/recruit-and-retain-experienced-women-in-technology.html
https://www2.deloitte.com/xe/en/insights/topics/value-of-diversity-and-inclusion/diversity-and-inclusion-in-tech/recruit-and-retain-experienced-women-in-technology.html
https://doi.org/10.19030/cier.v9i3.9709
https://doi.org/10.1080/19419899.2020.1729844
https://doi.org/10.1287/mnsc.2016.2478
https://doi.org/10.1111/j.1540-6261.2005.00813.x
https://scholarlycommons.law.northwestern.edu/njtip/vol2/iss1/2
https://www.zippia.com/advice/women-in-technology-statistics
https://doi.org/10.1037/bul0000234
https://doi.org/10.1111/1467-8551.12046
https://doi.org/10.1111/1467-8551.12046
https://doi.org/10.1111/josi.12285


38 

 

Reid, M. F., Allen, M. W., Armstrong, D. J., & Riemenschneider, C. K. (2010). Perspectives on 
challenges facing women in IS: The cognitive gender gap. European Journal of Information 
Systems, 19(5), 526-539. https://doi.org/10.1057/ejis.2010.30  

Riemenschneider, C. K., Armstrong, D. J., Allen, M. W., & Reid, M. F. (2006). Barriers facing 
women in the IT workforce. The DATA BASE for Advances in Information Systems, 37(4), 58–
78. https://doi.org/10.1145/1185335.1185345  

Rudman, L. A., Moss-Racusin, C. A., Phelan, J. E., & Nauts, S. (2012). Status incongruity and 
backlash effects: Defending the gender hierarchy motivates prejudice against female leaders. 
Journal of Experimental Social Psychology, 48(1), 165-179. 
https://doi.org/10.1016/j.jesp.2011.10.008  

Ryan, M. K., & Haslam, S. A. (2005). The glass cliff: Evidence that women are over-represented in 
precarious leadership positions. British Journal of Management, 16(2), 81–90. 
https://doi.org/10.1111/j.1467-8551.2005.00433.x  

Ryan, M. K., & Haslam, S. A. (2007). The glass cliff: Exploring the dynamics surrounding the 
appointment of women to precarious leadership positions. The Academy of Management Review, 
32(2), 549–572. https://doi.org/10.5465/AMR.2007.24351856  

Ryan, M. K., Haslam, S. A., Morgenroth, T., Rink, F., Stoker, J., & Peters, K. (2016). Getting on top 
of the glass cliff: Reviewing a decade of evidence, explanations, and impact. The Leadership 
Quarterly, 27(3), 446–455. https://doi.org/10.1016/j.leaqua.2015.10.008  

Ryan, M. K., Haslam, S. A., & Postmes, T. (2007). Reactions to the glass cliff: Gender differences in 
the explanations for the precariousness of women's leadership positions. Journal of 
Organizational Change Management, 20(2), 182-197. 
https://doi.org/10.1108/09534810710724748  

Schein, E. (2010).Sawyer, K., & Valerio, A. M. (2018). Making the case for male champions for 
gender inclusiveness at work. Organizational Dynamics, 47(1), 1-7. 
https://doi.org/10.1016/j.orgdyn.2017.06.002  

Schein, E. (2010). Organizational Culture and Leadership (4 ed.). Jossey-Bass/John Wiley and Sons, Inc.  
Schweizer, L., & Nienhaus, A. (2017). Corporate distress and turnaround: Integrating the literature 

and directing future research. Business Research, 10(1), 3-47. https://doi.org/10.1007/s40685-
016-0041-8  

Shen, W., & Joseph, D. L. (2021). Gender and leadership: A criterion-focused review and research 
agenda. Human Resource Management Review, 31(2). 
https://doi.org/10.1016/j.hrmr.2020.100765  

Smith, L. M. (2013). Working hard with gender: Gendered labour for women in male dominated 
occupations of manual trades and information technology (IT). Equality, Diversity and 
Inclusion, 32(6), 592-603. https://doi.org/10.1108/EDI-12-2012-0116  

Trahms, C. A., Ndofor, H. A., & Sirmon, D. G. (2013). Organizational decline and turnaround: A 
review and agenda for future research. Journal of Management, 39(5), 1277-1307. 
https://doi.org/10.1177/0149206312471390  

Trauth, E. M. (2002). Odd girl out: An individual differences perspective on women in the IT 
profession. Information Technology and People, 15(2), 98–118. 
https://doi.org/10.1108/09593840210430552  

Trauth, E. M. (2013). The role of theory in gender and information systems research. Information and 
Organization, 23(4), 277-293. https://doi.org/10.1016/j.infoandorg.2013.08.003  

https://doi.org/10.1057/ejis.2010.30
https://doi.org/10.1145/1185335.1185345
https://doi.org/10.1016/j.jesp.2011.10.008
https://doi.org/10.1111/j.1467-8551.2005.00433.x
https://doi.org/10.5465/AMR.2007.24351856
https://doi.org/10.1016/j.leaqua.2015.10.008
https://doi.org/10.1108/09534810710724748
https://doi.org/10.1016/j.orgdyn.2017.06.002
https://doi.org/10.1007/s40685-016-0041-8
https://doi.org/10.1007/s40685-016-0041-8
https://doi.org/10.1016/j.hrmr.2020.100765
https://doi.org/10.1108/EDI-12-2012-0116
https://doi.org/10.1177/0149206312471390
https://doi.org/10.1108/09593840210430552
https://doi.org/10.1016/j.infoandorg.2013.08.003


39 

 

Wei, K., Crowston, K., & Eseryel, U. Y. (2021). Participation in  community-based free/libre open 
source software development tasks: The impact of task characteristics. Internet Research, 31(4), 
1177-1202. https://doi.org/10.1108/INTR-03-2020-0112  

Wei, K., Crowston, K., Eseryel, U. Y., & Heckman, R. (2017). Roles and politeness behavior in 
community-based free/libre open source software development tasks. Information and 
Management, 54(5), 573-582. https://doi.org/10.1016/j.im.2016.11.006  

Woodfield, R. (2002). Woman and information systems development: Not just a pretty (inter)-face? 
Information Technology and People, 15(2), 119–138. 
https://doi.org/10.1108/09593840210430561  

Yang, B., Eckardt, R., Jin, F., & Tsai, C. (2021, July 26, 2021). Organizational influence across CEO 
life cycle: The moderating roles of prior performance and status. 81st Annual Meeting of the 
Academy of Management, Virtual. 

Zaccaro, S. J., & Banks, D. J. (2001). Leadership, Vision, and Organizational Effectiveness. In S. J. 
Zaccaro & R. J. Klimoski (Eds.), The nature of organizational leadership: Understanding the 
performance imperatives confronting today's leaders (pp. 181-218). Jossey-Bass: A Wiley Company.  

 

https://doi.org/10.1108/INTR-03-2020-0112
https://doi.org/10.1016/j.im.2016.11.006
https://doi.org/10.1108/09593840210430561

	Introduction
	Literature Review
	The Glass Cliff Phenomenon
	Evolving Leadership Theories in the IT Field
	The Gender Gap and the Transformational IT Leadership

	Method
	Research Design
	Measures
	Subjects

	Analysis and Results
	Discussion
	Theoretical Contributions
	Practical Implications
	Limitations and Future Research

	Conclusion

