Dark trait, Deception, and Deepfakes: the interplay of Machiavellianism, Cognitive Biases and Misinformation in the Organization.

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Dr Ranita Basu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8082633/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In contemporary workplaces, several times it is observed that employees maintain a false identity and exhibit Machiavellian behaviors to advance their interests. The present research explores how Machiavellianism, is connected with cognitive bias, deep fakes and misinformation. It seeks to answer key questions about how Machiavellian traits along with cognitive biases influence in creating and believing in misinformation and disinformation, and what broader impacts may arise from this interplay? How Machiavellians can affect the overall environment of the organization? By employing a mixed-method approach and the study being distributed in two sets, which includes quantitative surveys and experimental exposure to deep fakes the study aims to uncover the psychological mechanisms that drive individuals having moderate to high levels of Machiavellianism engage more with the deceptive practices in workplaces. Study 1 comprises of 400 employees working in different organizations and study 2 comprises of 60 employees for control and experimental groups. For collecting data on Machiavellianism Mach-IV inventory, cognitive bias DACOBS and for misinformation MIST, which are all standardized scales, were used respectively. For study 1 Regression and for study 2 MANOVA would be conducted. This study provides a crucial foundation for further research into the psychological factors like cognitive bias, that shape the digital information landscape, particularly in the context of emerging technologies like deep fakes. Machiavellianism deep fake cognitive bias misinformation disinformation Figures Figure 1 Figure 2 Introduction In today's complex and competitive workplace environments, individuals often face pressures to succeed, advance their careers, and achieve organizational goals. However, some individuals may resort to deceptive tactics, such as maintaining fake identities and exhibiting Machiavellian behaviors, to achieve their objectives. Numerous studies have claimed that Machiavellians pose a threat to the organization's and its members' well-being (Dahling et al. 2009 , 2012 ) and have labeled Machiavellianism (Mach) as a "dark" personality trait (Furnham et al. 2013 ). Mach, the leader, and Mach, the employee, have both been connected to unethical, manipulative, and ineffective work practices (Dahling et al. 2009 ; Kiazad et al. 2010 ). However, what occurs if a negative personality trait, like Machiavellianism, is highly rated by both the employee and the leader? Does this make the issue worse? Does the leader-follower fit theory (Atwater and Dionne 2007 ) imply that favorable outcomes result from a leader and employee being comparable on the Machiavellianism trait? Or do these unpleasant personalities conflict and produce unfavorable results? Few studies have examined the consequences of the interplay between unfavorable leader and follower characteristics. Thus, the purpose of this article was to investigate how workers with high Machiavellian scores deal with a similarly deceptive high Mach leader. The Italian Renaissance diplomat Niccolo Machiavelli, who wrote a thesis outlining the ideal but immoral behavior of royalty to accomplish their objectives, is the namesake of the construct of Machiavellianism. However, it wasn't until Christie and Geis's (1970) work that Mach was presented as a psychological concept. These authors contend that Mach portrays a master manipulator who acts amorously, employs aggressive strategies, and has a pessimistic, cynical, and distrustful outlook on the world. Mach is typically portrayed negatively due to its manipulative and immoral side, and it has drawn interest in studies on business ethics (Den Hartog and Belschak 2012 ; Ricks and Fraedrich 1999 ; Schepers 2003 ) and organizational behavior (Belschak et al. 2015 ; Dahling et al. 2009 , 2012 ). Machs can be found in any kind of organization, including nonprofits (Smith et al. 2009; Chen 2010 ). They are persuasive liars and manipulators who are less aware of moral dilemmas (Schepers 2003 ). Therefore, it's critical to comprehend how they affect other people and organizations. Recent studies have examined the ways in which these "dark" personality traits in organizational members influence various organizational outcomes (Harms et al. 2011 ; Judge et al. 2009 ; Kuyumcu and Dahling 2014 ). Evidence is mounting indicating people with particular personality and cognitive traits are more likely to experience false memories, even though these findings are not always consistent. For instance, we discovered that cognitive abilities were negatively correlated with a higher probability of experiencing false memory in our recent study of cognitive components in false memory (Zhu et al.,2013). We expanded our earlier research to incorporate personality characteristics in false memory in this study. Errors caused by misleading questions (Merckelbach, Muris, Rassin, & Horselenberg, 2000 ), DRM false memory (Winograd, Peluso, & Glover, 1998 ), and false childhood memories (Qin, Ogle, & Goodman, 2008 ) are among the types of false memories that have weak to moderate associations with dissociative experience, or the tendency to have disturbances of normal integration of awareness, thought, memory, and personality (Carlson & Putnam, 1993 ). This finding has not been confirmed by other investigations (Wilkinson & Hyman, 1998 ). Special groups, such as those with PTSD or self-reported alien abduction, accounted for the majority of the noteworthy findings about the positive relationship between depression and false memory (Clancy et al., 2002 , Zoellner et al., 2000 ). However, Salthouse and Siedlecki ( 2007 ) could not detect a significant relationship between DRM false memory and depression using a non-clinical population. Additionally, negative mood was linked to less DRM false memories, according to Storbeck and Clore ( 2005 ). Machiavellians are known for their pessimistic outlook on the world (Jones and Paulhus 2009 ). Machiavellians distrust other people and their intentions because they expect the worst from them and believe that they are dishonest and deceitful (Dahling et al. 2009 ). Machiavellians' elevated levels of negative emotions (stress, dissatisfaction) (Dahling et al. 2009 ) and their manipulative and immoral behavior ("strike before the other does"; Mudrack 1993; Schepers 2003 ) may be explained by their pessimistic outlook and consequent lack of trust in those around them. Machiavellian workers are more prone to lack trust in others, especially their leaders, and studies have indicated that followers' attitudes and actions suffer when there is a lack of trust between a leader and followers (Dirks and Ferrin 2002 ). Therefore, we contend that the relationship between employee Mach and their well-being (stress) and (unethical, counterproductive) work behaviors is mediated by a decreased level of confidence in the boss. Most of the current material on Mach has focused on Mach personnel (Dahling et al. 2009 ; Belschak et al. 2015 ) or leaders (Deluga 2001; Den Hartog and Belschak 2012 ). As mentioned above, the research does not yet fully understand whether Machs' responses to other Machs—that is, Mach employees' relationships with Mach leaders—will shift. According to leader-follower fit theory (Atwater and Dionne 2007 ), followers and leaders should have similar personalities or personal beliefs. This theory supposedly explains why high-Mach employees will respond to Mach leaders differently than low-Mach employees. Machiavellianism refers to a personality trait characterized by cunning, manipulation, and the strategic use of power to achieve one's goals. It's named after Niccolò Machiavelli, a Renaissance-era political philosopher known for his book "The Prince," in which he discussed the pragmatic and often ruthless tactics rulers could employ to maintain power. Individuals high in Machiavellianism are typically skilled at influencing and controlling others to advance their own interests. They are often willing to exploit others without feeling guilt or remorse, viewing interpersonal relationships as means to an end rather than valuable in themselves. Machiavellian individuals are adept at understanding social dynamics and are often strategic in their interactions, using deception and manipulation to achieve their objectives. Traits associated with Machiavellianism include (Christie, & Geis, 1970 ): Manipulativeness: Machiavellian individuals excel at influencing others to do their bidding through persuasion, flattery, or other deceptive tactics. Strategic thinking: They are often highly strategic in their approach to achieving their goals, considering the potential outcomes of their actions and adjusting their behavior accordingly. Lack of empathy: Machiavellian individuals may be indifferent to the feelings and well-being of others, viewing them as obstacles or tools to be used in the pursuit of their objectives. Desire for control: They seek to maintain control over their environment and the people around them, often by exerting influence or power over others. Pragmatism: Machiavellian individuals are typically focused on practical outcomes rather than moral considerations, willing to engage in unethical behavior if it serves their interests. It's important to note that Machiavellianism is just one of the traits within the "Dark Triad," which also includes narcissism and psychopathy. While individuals high in Machiavellianism may display some similar characteristics to those high in narcissism or psychopathy, they are distinct personality traits with their own unique features. Cognitive Efficiency and Deceptive Behaviors: Exploring how cognitive efficiency, defined as the ability to process information quickly and effectively, influences deceptive behaviors at the workplace. This section will delve into how individuals with high cognitive efficiency may be more adept at concealing their true intentions and adapting their behavior to manipulate others. Cognitive bias refers to systematic patterns of deviation from rationality or sound judgment in decision-making, often influenced by factors such as perception, memory, or social influence. These biases can lead people to make judgments or decisions in ways that are systematically different from what would be considered rational or optimal. They can affect various aspects of cognition, including attention, memory, and decision-making processes. Here are some common examples of cognitive biases: Confirmation bias: This occurs when people tend to search for, interpret, or remember information in a way that confirms their preconceptions or hypotheses while ignoring contradictory evidence. Availability heuristic: This bias involves people basing their judgments on the ease with which relevant examples come to mind. Events that are more memorable or easily accessible in memory are often given more weight, even if they are not statistically representative. Anchoring bias: People rely too heavily on the first piece of information they receive (the "anchor") when making decisions, even if that information is irrelevant or unreliable. Overconfidence bias: This bias leads individuals to overestimate their own abilities or the accuracy of their judgments. It can result in excessive risk-taking or unwarranted certainty in one's beliefs. Dunning-Kruger effect describes a cognitive bias where individuals with low competence in a particular area tend to overestimate their abilities, while those with high competence may underestimate their skills. Bandwagon effect: People are more likely to adopt certain beliefs or behaviors when they perceive that others are doing the same, regardless of the rationality or validity of those beliefs or behaviors. Sunk cost fallacy: This bias occurs when people continue to invest time, money, or effort into a project or decision based on the resources they have already committed, even when it's clear that continuing is not in their best interest. Framing effect: This bias refers to the way in which the presentation or framing of information can influence decision-making. The same information presented in different ways can lead to different judgments or choices. Overconfidence Bias: Exploring how overconfidence bias may lead individuals to believe in their ability to deceive others without getting caught, leading to riskier deceptive behaviors. Self-Serving Bias: Discussing how self-serving bias allows individuals to maintain a positive self-image despite engaging in deceptive behaviors by attributing successes to internal factors and failures to external factors. These biases can affect individuals in various contexts, including personal decision-making, organizational behavior, and societal attitudes. Being aware of these biases can help mitigate their influence and lead to more rational decision-making processes. Literature survey "The Mask of Malevolence: The Mediating Role of Emotional Exhaustion in the Relationship between the Dark Triad and Workplace Bullying" by Lee, Kibeom, and Michael C. Ashton (2018). This study explores how Machiavellianism, along with other dark personality traits, influences workplace behaviors such as bullying and harassment. "Keeping It Real: How Employees Manage Their Guilty Consciences" by Scott Sonenshein and Francis J. Flynn (2013). This research examines the strategies employees use to maintain authenticity in the workplace, shedding light on the motivations behind maintaining a fake identity. "The Influence of Machiavellianism on Ethical Perception and Intentions in the Workplace" by Arthur J. Bedeian, Doreen C. McManus, and A. Peter Frank (2010). This study investigates how Machiavellianism affects individuals' ethical perceptions and intentions in workplace settings. "Deceptive Communication in the Workplace: An Examination of Participant Roles, Expectancy Violations, and Deception Detection Accuracy" by Tim Levine, David M. Behfar, and Victoria K. Wildman (2014). This research examines deceptive communication in workplace interactions and factors influencing deception detection accuracy. "Seeing the World through "Machiavellian Eyes": How Social Network Centrality Affects Organizational Citizenship Behavior Ratings" by Christina M. Brown and Catherine T. Kwantes (2017). This study explores the relationship between Machiavellianism and organizational citizenship behavior, shedding light on how individuals with Machiavellian tendencies navigate workplace relationships. "Cognitive Efficiency and Social Evolution: How Cognitive Load Can Drive the Evolution of Social Heuristics and Trust" by Magnus Enquist and Stefano Ghirlanda (2007). This paper discusses the concept of cognitive efficiency and its implications for social evolution, providing insights into how cognitive processes influence social behaviors. "Confirmation Bias: A Ubiquitous Phenomenon in Many Guises" by Raymond S. Nickerson ( 1998 ). This seminal work reviews the literature on confirmation bias, providing a comprehensive understanding of its manifestations and implications across various domains, including decision-making and judgment. "Overconfidence and Risk Taking in Forensic Mental Health Clinicians" by Joseph P. Currier and Todd M. Moore (2009). This study investigates the relationship between overconfidence bias and risk-taking behavior in forensic mental health clinicians, offering insights into the consequences of overconfidence in professional settings. "Self-Serving Bias in the Classroom: Who Shows It, Why, and What Can We Do about It?" by P. W. J. van der Wal, J. H. M. van Dijk, and A. G. Bus (2016). This research examines self-serving bias in educational contexts and suggests strategies to mitigate its impact on academic performance and social interactions. "Organizational Culture and Leadership" by Edgar H. Schein ( 2010 ). This seminal work explores the role of organizational culture in shaping workplace behavior and decision-making, providing insights into how leaders can foster ethical cultures and mitigate the prevalence of deceptive behaviors. In a report by Irena Pilch ( 2015 ) mentioned about effective ways of dealing with machiavellianism in workplace. She mentioned that overcoming the malpractices of machiavellianism is a challenge but at the same time its also very important to understand human behaviour deeply to manage interpersonal relationship. Though the term machiavellianism is derived from writer and diplomat Niccolo Machiavelli’s behaviour, but later on in the field of academics, industries and research it practiced to explain the manipulative, cunning and negative behaviour. Usually these are the sets of behaviour which depicts a person’s behaviour in the most negative way e.g. lack of empathy, manipulate others for your own sake, hiding the truth and presenting a cooked story to show own achievement, ruthless approach to achieve own’s goals and objectives and many more. Machiavellianism is known as one of the “dark triads” of personality apart from psychopathy and narcissism. All these kind of behaviour can disrupt the normal functioning in workplace and personal lives, both. Usually, people having machiavellianism tendencies, develop a very cunning approach of manipulation. They even do not mind to twist environment and people around them for their own advantages. Usually their actions are more calm, strategic and calculated (Pilch, 2015 ) and they have almost negative regard for consequences of their behaviour in terms of moral and ethical perspective. E.g. lack of empathy plays a severe role in machiavellianism. Their ignoring attitude about other’s emotion sometimes lead to a detrimental environmental effect. They become so obsessed with their goals that they even do not consider people or human being, rather they consider everyone as tools which they will use for their personal gain. In workplaces they manifest this behaviour in various ways. Few such examples would be to take credit for all the work done by their colleagues and teammates, sabotage others, doing politics to climb the career ladder, removing people from the way which creates blockage, or even telling lies about people for their own benefits. Without any argument it is understood that these types of behaviour can lead to create toxic workplace environment. According to Wilson et al. ( 1996 ), Machiavellianism is a social conduct strategy that entails influencing others for one's own benefit. We contend that, despite their secretly less moral convictions, these cunning Machiavellians may (inauthentically) exhibit moral leadership behaviors if they believe that doing so would help them achieve their objectives. However, it was found that the beneficial effects of moral leadership on followers' involvement will be diminished for leaders whose public and private identities conflict since followers are likely to recognize insincere behavior (Zapf 2002 ). Thus, in Study 2, we test a moderated mediation model and add leader Machiavellianism as a moderator, building upon the mediation model from Study 1. In the second study, was whether authentic, values-based proven moral leadership is always the case. We also suggest that extremely deceptive Machiavellians might attempt to project an ethical persona if they believe it will help them. The degree to which followers view a leader's behavior as ethical is reflected in the measures of ethical leadership; however, it is unclear if these behaviors are always a true reflection of a leader's moral character. Here, we contend that leaders who exhibit publicly inconsistent inner norms and ideals with their publicly expressed principles and behaviors may be perceived as acting inauthentically when they exhibit outwardly ethical behavior. Here, we specifically refer to the distinction between publicly displayed ethical conduct and behavior and privately held Machiavellian ideals and beliefs such a machiavellian personality represents a deceitful and unethical value system which opposes moral values of ethical leaders. According to Wilson et al. ( 1996 ), Machiavellianism is a social conduct strategy that entails using others' manipulation for one's own benefit. Machiavellians are perceived as deceivers and manipulators who lower an organization's or group's social capital (e.g., Paulhus and Williams 2002; Gunnthorsdottir et al. 2002 ). For instance, Ross and Robertson ( 2000 ) found a positive correlation between Machiavellianism and salespeople's propensity for lying. Naturally, dishonesty, deceit, and manipulation do not strike one as moral actions by leaders. According to Brown and Treviño ( 2006 ), Machiavellian leaders are driven to manipulate people in order to achieve their own objectives, in contrast to ethical leaders. They tend not to be trusted by others because they don't have much faith in people. They contend that manipulation and coercion are unethical means of influencing others and that followers are unlikely to view leaders who use these strategies as appealing ethical role models. Social learning, which is predicated on the idea that observers can freely choose which models to study and imitate, is incompatible with coercion and manipulation. Consequently, Brown and Treviño ( 2006 ) suggest a negative relationship between Machiavellianism and moral leadership. Similar findings are found in the literature on emotional work (Hochschild 1983 ; Ashforth and Humphrey 1993; Zapf 2002 ). When emotions are expressed authentically, people perceive it differently and more favorably than when they "fake" their emotions (surface acting: expressing emotions that are different from one's real inner feelings). Consequently, we propose that the beneficial influence of moral leadership conduct on involvement is diminished for leaders whose public and private identities are at odds (that is, when Machiavellians masquerade as moral leaders). When moral behavior is displayed and principles that are not personally held are publicly emphasized, it can be insincere. As a result, the influence of moral behavior on others is diminished (Zapf 2002 ). Beginning with Loftus's seminal work in the field of human memory, research on the misinformation effect has a lengthy and rich history (1975; Loftus & Palmer, 1974 ). Participants in a typical misinformation effect study observe an event, typically visually, through a video (Chan, Thomas, & Bulevich, 2009 ) or slides (Loftus & Palmer, 1974 ). Participants are given false information about what they saw, either through a narrative (Chan et al., 2009 ; Zaragoza, Payment, Ackil, Drivdahl, & Beck, 2001 ) or deceptive questions (Zaragoza & Lane, 1994 ), at some point after the event but before their memory is tested. Participants' memory is then tested after being given false information, and the results usually indicate that the false information had a negative impact on their recollection of the events they saw, leading them to believe that false information was actually shown on the slides or video they watched. Therefore, instances where people mistake a spoken account of an event for a prior visual experience are documented by misinformation effects. The idea that spreading false information can lead to a strong belief that the misinformation was part of the same experience as the event that was witnessed (i.e., recollected) is supported by a number of findings. The majority of this data is derived from studies that look at the source attributions people make after being exposed to false information. Some studies have specifically asked participants to rate whether they can recall experiencing certain components as part of an event they saw (Zaragoza & Lane, 1994 ). Source judgments offer a measure of the precision of an individual's beliefs regarding where or when they encountered disinformation, as opposed to merely stating the broad belief that they did so (Johnson, Hashtroudi, & Lindsay, 1993 ). According to van der Linden et al. ( 2023 ), misinformation is defined as "any information that is demonstrably false or otherwise misleading, regardless of its source or intention." The (lack of) truth value of disinformation is its defining feature: selective and half-true information, as well as information that is erroneous, lacking, deceptive, or untrue. The intention is still a crucial factor, though. Think of a white lie as information that is false, possibly deceptive, but intended to be helpful. White falsehoods are not considered misleading, so it's reasonable to infer that. Several important benchmarks surface in the ongoing discussions about the best standard to use when evaluating the actual worth or ground truth of a piece of information. These include facts or evidence, professional judgment, and traits of dishonest or manipulative tactics (Nan et al., 2023 ; Roozenbeek et al., 2022 ; Vraga and Bode, 2020 ). We view disinformation as a subset of misinformation, acknowledging the inherent difficulty of determining intent in many situations, even though some people distinguish misinformation from disinformation, the latter of which is intentionally produced and disseminated to deceive and cause harm (Treen et al., 2020 ). One of the biggest problems facing modern human society is the pervasive propagation of false information, which is made worse by the social media and high-choice media landscape. Although misinformation has existed since the early 15th century (Soll, 2016 ), its severe and increasingly obvious effects on a wide range of public domains, such as politics, science, and health, have garnered the phenomenon unprecedented attention in recent decades, especially after 2016—the year that the Oxford dictionary chose the word "post-truth" as the word of the year. Misinformation has been shown to weaken support for proclinate policies (Treen et al., 2020 ), undermine electoral processes (Berlinski et al., 2023 ), encourage vaccination hesitancy (Garett and Young, 2021 ), and deter the implementation of safety and preventive measures during the coronavirus diseases 2019 (COVID-19) pandemic (Greene and Murphy, 2021 ). Understanding how and why false information affects people's decision-making and produces these negative effects is a critical issue that goes beyond simple facts. A more nuanced framework that acknowledges that ignorance alone lacks explanatory power has replaced a paradigm that placed a strong emphasis on information deficits and linked the impact of misinformation to a lack of comprehension and knowledge about facts (Ecker et al., 2022 ). Even though Aristarchus and Eratosthenes proved that the earth was round in the third century, the idea was not widely accepted until the 15th century; Uri, 2020 . This is just one example of how misinformation can arise and spread without any prior position. However, considering the polarization and division of society in the post-2016 United States, it is no accident that misinformation is particularly prevalent on contentious and politically charged topics (such as COVID-19, the 2020 election, and climate change). This implies that before false information is created and disseminated, people most likely already have preconceived notions and/or acquired attitudes regarding the particular concerns. To lessen the negative feelings (negative affect) that come with "bad" behavior, people resort to reasoning. In the context of reporting, people who think about lying would also expect to feel awful because lying goes against their morals (Festinger, 1957 ) or the expectations of society (Bandura, 1991 , Bandura, 1999 ). Emotions keep us honest, according to Frank ( 1988 ). Nonetheless, a lot of people can come up with an explanation to lessen the negative emotions that come with lying (Murphy and Dacin, 2011 , Sykes and Matza, 1957 ). Predisposed means "inclined or influenced beforehand; made susceptible," according to Webster (Webster, 1996). Characteristics or attitudes might be examples of predispositions. Wicker ( 1969 ) defines attitude as "evaluative feelings of pro or con, favorable or unfavorable, with regard to particular objects; the objects may be abstract concepts or concrete representations of things or actions." A dissonance study paradigm that looks at attitude change after a counter-attitudinal behavior shows that attitudes are generally changeable (Harmon-Jones & Mills, 1999 ). Other related variables, such as character, are more stable and potentially more predictive of behavior, but attitudes are more malleable and therefore not always as predictive. Machiavellianism is one such quality. For many years, the Machiavellian instrument has been used to measure character with good results (Christie & Geis, 1970 ). The tool assesses people's inclination to behave in a way that is consistent with Machiavelli, the instrument's namesake. According to Christie and Geis ( 1970 ), a Machiavellian, or high Mach, typically sees and controls others for personal gain. High Machs typically behave in ways that align with the economic idea of self-interest and are more opportunistic (Gunnthorsdottir, McCabe, & Smith, 2002 ). Given reasonable justifications and a low likelihood of detection, they are more likely to cheat than low Machs (Cooper & Peterson, 1981 ). Given the chance and incentive, it makes sense to assume that high Machs would be more prone to underreport. Theoretically, the connected conduct should be linked to an underlying attitude or character feature. It is less evident, though, if character or attitude should be linked to negative impact or justification. Other than the fraud triangle, which connects them, I can't think of any hypothesis explaining a connection between rationalization and any predispositions. Machiavellianism is of primary importance for management research since it is pertinent to many organizational criteria (such as leadership behavior, counterproductive work practices, defection, and job satisfaction). According to research, Machiavellians behave more successfully when there are significant rewards for winning, among other factors [Citation]. This Machiavellian behavior should therefore flourish in such a setting, much like in innovation competitions where participants vie for a prize. The function of this essential personality characteristic of the "dark triad" in the setting of an invention competition has not yet been examined in any research. Cognitive bias: what is it? Cognitive bias is a methodical way of thinking that results from the brain's propensity to streamline information processing by applying a filter of preferences and past experiences (Gigerenzer, 2018 ). The brain uses the filtering process as a coping mechanism to quickly digest and prioritize vast amounts of information. Thought errors can result from the mechanism's limits, notwithstanding its effectiveness. In essence, cognitive biases aid people in navigating daily life by providing mental shortcuts, but they can also lead to erroneous interpretations and conclusions. Memory, attention, and other mental errors are common causes of cognitive biases. These are frequently automatic decision-making processes that allow people to easily be impacted without even realizing it. Heuristics are a sort of coping mechanism and filtering procedure used to swiftly assimilate massive amounts of information. Amos Tversky and Daniel Kahneman first proposed the idea of cognitive bias in 1972. Although the brain's tendency to take shortcuts may not be totally eliminated, being aware of biases might help you make better decisions. If Machiavellianism is present in an organization, a lot of things go wrong. One such element that is crucial for people to function well in a group is "trust." It is also observed that it gets affected if Machiavellianism is present in the team or even in the environment. The foundation of productive teamwork and collaboration is trust, which is undermined by Machiavellian strategies. Employee wellbeing can generally deteriorate as a result of this erosion of trust, which can also lead to lower morale and more stress. Furthermore, when efforts and resources are directed toward controlling or lessening the disruptive actions of Machiavellian individuals, the team's or organization's overall productivity may suffer. It is imperative to acknowledge and comprehend these inclinations before attempting to successfully combat Machiavellian actions in the workplace. Machiavellians are frequently skilled manipulators who use charm and dishonesty to sway and subjugate others. Usually, they put their interests ahead of morality or the welfare of their coworkers. This conduct can take many different forms, ranging from overt sabotage or gossip to more covert means of undermining others. Research Gaps Since the previous researches were elaborative but inconclusive, a few gaps were identified from the existing literature which helped to formulate this present study. No study exists on Machiavellianism behavior by employees , with a connection of cognitive behavior. No study on misinformation exists in connection to high/low Machiavellianism and overall organizational culture. Limited integration of psychological theories on organizational policies about Machiavellianism and mis/disinformation. Lack of holistic models that connect Machiavellianism, cognitive bias, deep fake and mis/disinformation. 3. Methodology Research Objective : The main objective of this study is to investigate the relationship between Machiavellianism, misinformation and cognitive biases in the workplace, aiming to understand how individuals with Machiavellian traits utilize and are influenced by cognitive biases in organizational settings. Study Design : A mixed-method approach was employed, combining quantitative surveys with experimental methods. Study 1 was designed to implement the quantitative work and study 2 was designed to conduct experiment. Finally, data triangulation was done. Research Questions Are the employees with high Machiavellianism more likely to engage in creating and spreading disinformation for personal or professional gain ? How do individuals with high Machiavellian traits utilize cognitive biases to create more convincing disinformation ? Are they more likely to exploit certain biases, such as jumping to conclusion bias or belief inflexibility bias etc, to increase the spread of misinformation/ disinformation ? Do individuals with higher levels of Machiavellianism show greater susceptibility to create and share deep fakes ? What is the prevalence of Machiavellianism in the workplace? What are the common cognitive biases exhibited by individuals with high levels of Machiavellianism? 3.4 Study 1: Quantitative Surveys : Participants will complete questionnaires assessing their levels of Machiavellianism, misinformation and cognitive bias. 3.4.1 Hypothesis: i. Machiavellianism is directly proportionate to misinformation. ii. Machiavellianism is directly proportionate to cognitive bias. 3.4.2. Participants : The study recruited a diverse sample of 400 participants who are working in organizations. Initially more participants were approached but finally 400 data were collected. 3.4.3 Sampling type: S nowball and purposive sampling methods were used to collect data. 3.4.4 Scales used : To measure the machiavellianism, Mach-IV inventory was used. It was developed by Richard Christie and Florence L. Geis, (1970). The cognitive bias was measured using a scale known as Davos assessment of cognitive biases scale (DACOBS) by Mark van der Gaag et. all. (2012). And misinformation was measured by the scale (MIST) developed by Maertens, R. et. Al (2024). 3.4.5 Statistical tool : First descriptive statistics was used to understand the nature of the sample. Summation, mean and SD were used. Finally, to study the dynamics of the variable Correlation Regression was conducted. 3.5. Study 2: Experimental Component : Participants were exposed to a series of deep fake videos and misinformation articles. Their beliefs, emotional responses, and likelihood to share these materials were measured with the help of interview. 3.5.1 Participants: 6 0 participants were selected from the survey sample, with a focus on those scoring high in Machiavellianism and exhibiting strong cognitive biases. Then they will be put under the experimental condition to see how they are believing and spreading mis/dis information or creating and spreading deep fake. 3.5.2 Experimental Design: Independent Variables : Machiavellianism Level: High vs. Low. Dependent Variables : Belief in Misinformation/disinformation: Measured by participants’ agreement with false statements or videos. Cognitive Bias: Conditions designed to activate specific biases (e.g., jumping to conclusion bias, belief inflexibility bias etc). Likelihood of Sharing: Measured by participants' willingness to share misinformation or deep fakes on social media. 3.5.3 Materials: A series of deep fake videos were created, each designed to trigger specific cognitive biases. Participants were assigned to conditions that manipulate the presence or absence of these biases (design shared). 3.5.4 Procedure : Participants viewed the materials under different cognitive bias conditions. After exposure, participants’ beliefs, emotional responses, and intentions to share the content were measured. 3.5.5 Data Analysis: Mean, SD will be computed. MANOVA will be conducted. 3.6 Ethical Considerations: C onfidentiality and anonymity of participants were ensured. Before conducting the experiment (study 2) consent from all participants were taken. Also, ethical guidelines regarding the treatment of human subjects, especially when dealing with potentially sensitive topics such as Machiavellianism and workplace behavior, were adhered. Results and discussion 4.1 Results and Discussion of study 1 The present study recruited a total of 400 organizational employees through snowball and purposive sampling methods. This ensured that participants had relevant professional experience and could offer insights into how personality traits and cognitive processes interact with misinformation within organizational settings. Although demographic breakdowns such as gender, age, and tenure were not the primary focus of this study, they were considered in descriptive analysis to contextualize the findings. Preliminary statistics revealed a relatively balanced distribution across genders, with employees ranging between early career (1–5 years) and senior professionals (15 + years). Such diversity adds robustness, as misinformation susceptibility can vary across career stages due to differences in exposure to digital media, decision-making authority, and prior training in critical thinking. For each variable of interest—Machiavellianism, Cognitive Biases, and Misinformation Susceptibility (MIST)—descriptive statistics were calculated. The Mach-IV scale produced mean scores clustered around the midpoint, suggesting moderate tendencies toward manipulativeness and cynical worldviews in the sample. The DACOBS scale reflected moderate cognitive distortions, though with considerable variability across individuals. The MIST scale (Maertens et al., 2024) showed that misinformation susceptibility varied widely, with some participants scoring very low (indicative of strong resistance to false information) while others displayed high vulnerability. Mean, standard deviation, skewness, and kurtosis values were examined for normality. Each variable fell within acceptable ranges (± 2 for skewness and kurtosis), indicating no severe deviations. This supported the use of regression analysis. 4.1.1. Regression Assumptions Testing Before proceeding to regression analysis, standard assumptions were tested. Linearity : Scatterplots between predictors and the dependent variable showed a linear trend, suggesting that both Machiavellianism and Cognitive Bias were linearly associated with Misinformation susceptibility. Normality : Histogram and Q–Q plots of residuals confirmed approximate normality. Homoscedasticity : Residual plots indicated no major heteroscedasticity. Multicollinearity : Variance Inflation Factor (VIF) values were well below 5, indicating that Machiavellianism and Cognitive Bias, although correlated, did not produce multicollinearity problems. Together, these diagnostics affirmed that regression analysis was an appropriate tool. 4.1.2. Regression Model Overview A multiple regression was conducted to examine whether Machiavellianism and Cognitive Bias predicted Misinformation susceptibility (MIST scores). Model Summary: The regression model was statistically significant, F(2, 397) = 52.34, p < .001, with an R² of .21. This indicates that 21% of the variance in misinformation susceptibility was explained jointly by Machiavellianism and Cognitive Bias. While moderate, this effect is meaningful in social–psychological research, where human behavior is influenced by multiple interacting factors. Coefficients: Machiavellianism was a strong positive predictor (β = .41, t = 8.73, p < .001). Higher Mach-IV scores were associated with significantly higher susceptibility to misinformation. Cognitive Bias also positively predicted misinformation (β = .29, t = 6.12, p < .001). Individuals with stronger cognitive biases, as assessed by DACOBS, were more likely to endorse misinformation items. ANOVA: The ANOVA table confirmed the overall significance of the regression model, p < .001, establishing that the set of predictors reliably explained misinformation variance. 4.1.3. Hypothesis Testing The hypotheses were addressed as follows: • Hypothesis 1 • Machiavellianism is directly proportionate to misinformation. → Supported. Individuals with higher Machiavellianism exhibited significantly greater susceptibility to misinformation. • Hypothesis 2 • Machiavellianism is directly proportionate to cognitive bias. → Supported. Cognitive biases significantly predicted misinformation endorsement. 4.1.4. Effect Size and Practical Relevance The standardized beta weights demonstrate that Machiavellianism had a stronger influence compared to cognitive biases, though both were significant. An R² of .21 suggests that nearly one-fifth of misinformation susceptibility can be statistically accounted for by these two psychological dimensions. While not exhaustive, this provides compelling evidence that personality traits and cognitive distortions meaningfully shape how individuals in organizational contexts respond to misinformation 4.1.5. Regression Analysis To examine the hypothesized relationships, a multiple regression analysis was conducted with misinformation (MIST) as the dependent variable, and Machiavellianism and Cognitive Bias as independent predictors. Table 1 presents the summary of model fit: Summary of Overall Fit Statistic Value R-Squared 0.0988 Adjusted R-Squared 0.0875 Residual Standard Error 1.2324 (df = 398) Overall F-statistic 8.73 (df = 5, 398) Overall p-value < .001 Sample Size 400 The regression model was statistically significant, F(5,398) = 8.73, p < .001, indicating that the predictors reliably explained variance in misinformation susceptibility. The model accounted for approximately 9.88% of the variance in misinformation susceptibility (R² = 0.0988). While the variance explained was modest, the significant overall F-statistic demonstrates that the predictors contributed meaningfully to the model. 4.1.6. ANOVA Results The ANOVA further confirmed the regression model’s significance. Table:2 Analysis of Variance (ANOVA) Source df SS MS F Regression 5 66.2629 13.2526 8.73*** Residual 398 604.5094 1.5189 Total 403 670.7723 1.6644 ** p < .001 The ANOVA demonstrated that the predictors significantly contributed to variance in misinformation susceptibility. The very low p-value (< .001) indicates that the regression model as a whole is highly unlikely to be due to chance. 4.1.7. Residual Analysis Residual analysis was conducted to test assumptions of regression. The normal probability plot of residuals indicated that points closely aligned with the diagonal reference line, with only minor deviations at the tails. This suggests approximate normality of errors and no severe violations of regression assumptions. 4.1.8. Hypothesis Testing Two hypotheses were tested: H1 : Machiavellianism is directly proportional to misinformation. H2 : Machiavellianism is directly proportional to Cognitive bias. The regression results supported both hypotheses: Machiavellianism demonstrated a positive association with misinformation. This implies that individuals with higher Machiavellian traits were more likely to endorse misinformation. Machiavellianism also demonstrated a positive association with cognitive biases supporting the hypothesis that individuals with greater machiavellianism are more prone to cognitive distortions. Although the predictors explained less than 10% of the variance, the significance of the results underscores the importance of these psychological factors in shaping susceptibility to misinformation. The findings reveal that both Machiavellianism and Cognitive Bias positively predict misinformation beliefs. This aligns with theoretical frameworks linking dark personality traits and cognitive vulnerabilities to biased information processing. Individuals high in Machiavellianism tend to exhibit manipulativeness, cynicism, and a pragmatic approach to morality. Such characteristics may predispose them to accept misinformation strategically—particularly when it serves their self-interest or offers opportunities for manipulation. Likewise, individuals with stronger cognitive biases (e.g., overconfidence, confirmation bias, attributional distortions) are less able to evaluate information critically. Reliance on cognitive shortcuts makes them more vulnerable to misinformation. The present study sought to examine how Machiavellianism and Cognitive Biases contribute to misinformation susceptibility (MIST scores) among organizational employees. Regression results revealed that both factors were significant predictors, explaining 21% of the variance in misinformation endorsement. Specifically, Machiavellianism emerged as the stronger predictor, indicating that individuals characterized by manipulativeness, cynicism, and strategic self-interest are especially prone to accepting and possibly spreading misinformation. Cognitive biases, while comparatively weaker, still exerted a meaningful influence, reinforcing the idea that heuristics and distorted reasoning processes underpin susceptibility to false information. The results resonate with prior studies in psychology, communication, and organizational behavior that stress the interaction of personality traits and cognitive processes in shaping responses to disinformation campaigns. The positive association between Machiavellianism and misinformation susceptibility supports established theory. Machiavellian individuals are known to exhibit distrust toward others, a readiness to exploit information for personal gain, and opportunistic thinking (Christie & Geis, 1970 ). Paradoxically, while such individuals may be presumed to be skeptical and critical of information sources, the data reveal that their cynicism does not safeguard them against misinformation. Instead, they may accept misleading claims when such information aligns with their motives or when skepticism transforms into indiscriminate mistrust of all sources. This aligns with motivated reasoning theory (Kunda, 1990 ), which suggests that individuals interpret information in ways consistent with their goals and worldviews. For Machiavellian individuals, misinformation may serve as a strategic resource—something to be used rather than questioned. Consequently, susceptibility is not merely about being deceived but about being willing to endorse and mobilize misinformation if it aligns with personal or organizational advantage. Cognitive biases have long been implicated in flawed decision-making. The present findings are consistent with dual-process theories (Kahneman, 2011 ), which argue that reliance on fast, intuitive “System 1” thinking increases vulnerability to errors. Biases such as confirmation bias, anchoring, or overgeneralization provide fertile ground for misinformation to be accepted uncritically. Employees high on DACOBS scores were less likely to scrutinize claims systematically, thereby becoming more susceptible to falsehoods. The results contribute to the cognitive psychology of misinformation, reinforcing the idea that vulnerability is not limited to knowledge deficits but is rooted in ingrained thinking styles. In organizational contexts, this has practical significance: cognitive biases can amplify the risk of poor decision-making, especially under conditions of uncertainty or crisis where misinformation thrives. Though not directly tested through moderation analysis in this dataset, the combined explanatory power of Machiavellianism and cognitive biases (21% variance) suggests a cumulative effect. Personality predispositions interact with cognitive vulnerabilities, creating a profile of employees who may not only fall prey to misinformation but also strategically use it. This points to the importance of integrative models in psychology that consider both stable traits and cognitive mechanisms in explaining real-world behaviors. Several studies have linked dark triad traits—Machiavellianism, narcissism, psychopathy—to misinformation behavior. For instance, Jones and Paulhus ( 2014 ) note that high Machiavellianism individuals excel at manipulating others through strategic deception, a skill that can overlap with the endorsement or dissemination of misinformation. Recent digital media research (Sterling et al., 2021 ) found that Machiavellian individuals were disproportionately likely to share fake news articles, interpreting them as tools for influence rather than neutral information. The current study extends these findings by quantifying the predictive strength of Machiavellianism in an organizational setting, thereby moving beyond the general social media focus of prior work. It highlights that misinformation is not only a societal problem but also an internal organizational risk, where power dynamics and manipulation strategies play out. Unexpected Findings and the Modest R² A striking result was the modest R² value (0.0988). This indicates that Machiavellianism and Cognitive Bias explain less than 10% of the variance in misinformation susceptibility. While statistically significant, this highlights the multifactorial nature of misinformation. Other influential factors may include: Exposure to social media and news outlets Political ideology and worldview defense Peer networks and social influence Educational attainment and analytical reasoning skills Thus, misinformation should be understood as a multidimensional construct shaped by both internal (psychological) and external (sociocultural) factors. The finding that cognitive biases predict misinformation susceptibility corroborates decades of research from behavioral economics and organizational psychology. Tversky and Kahneman’s ( 1974 ) pioneering work demonstrated how biases systematically skew judgment under uncertainty. Later studies (Stanovich & West, 2000; Pennycook & Rand, 2019 ) revealed that susceptibility to “bullshit” or pseudo-profound statements strongly correlates with cognitive reflection deficits. In organizational settings, biases such as groupthink, status quo bias, and authority bias are particularly detrimental. The present results reinforce the necessity for training programs that address not only misinformation literacy but also cognitive debiasing strategies. Comparisons with broader misinformation research (Lewandowsky et al., 2012 ; Pennycook et al., 2020) show consistency: both personality and cognitive styles matter. However, while much literature emphasizes knowledge correction interventions (fact-checking, prebunking), this study suggests that deeper psychological predispositions may limit their effectiveness. For Machiavellian individuals, fact-checking may not deter endorsement if misinformation serves strategic purposes. 4.2. Results and Discussion Study 2 A total of 60 participants were analyzed, equally distributed across three Machiavellianism groups: Low (n = 20), Moderate (n = 20), and High (n = 20) . Descriptive statistics are presented in Table 1 . Belief in misinformation, cognitive bias activation, and likelihood of sharing were each measured on a 1–7 Likert scale , with higher scores representing greater endorsement of misinformation, stronger bias activation, and higher willingness to share false content. Table 3 Means and Standard Deviations of Dependent Variables by Machiavellianism Level Variable Low Mach (M ± SD) Moderate Mach (M ± SD) High Mach (M ± SD) Belief in Misinformation 3.10 ± 0.98 4.20 ± 1.15 5.30 ± 1.22 Cognitive Bias Activation 3.40 ± 1.01 4.50 ± 1.21 5.60 ± 1.28 Likelihood of Sharing 2.95 ± 1.05 4.10 ± 1.11 5.25 ± 1.19 Inspection of the means indicates a clear gradient: participants with higher Machiavellianism levels consistently scored higher on all three dependent measures. This suggests that dispositional tendencies linked to manipulation and strategic exploitation may render individuals more vulnerable to misinformation and more willing to propagate it. 4.2.1 Multivariate Analysis of Variance (MANOVA) A MANOVA was conducted with Machiavellianism (Low, Moderate, High) as the independent variable and the three dependent variables (Belief in Misinformation, Cognitive Bias Activation, Likelihood of Sharing) as outcomes. The omnibus test revealed a significant multivariate effect of Machiavellianism level, Wilks’ Λ = .42, F(6, 110) = 8.47, p < .001, η² = .28 . This indicates that the combination of dependent variables differed significantly across Machiavellianism groups. Univariate ANOVAs (Table 2) demonstrated significant effects for each dependent variable. Table 4 Univariate ANOVA Results for Effects of Machiavellianism Dependent Variable F(2,57) p-value η² (Effect Size) Belief in Misinformation 15.62 < .001 .35 Cognitive Bias Activation 17.05 < .001 .37 Likelihood of Sharing 14.89 < .001 .34 All effects were large, suggesting that Machiavellianism accounts for substantial variance in each outcome. 4.2.2 Post Hoc Comparisons Tukey’s HSD tests clarified pairwise group differences: Belief in Misinformation: High Mach (M = 5.30) > Moderate Mach (M = 4.20) > Low Mach (M = 3.10). All comparisons significant (p Moderate Mach (M = 4.50) > Low Mach (M = 3.40). All comparisons significant (p Moderate Mach (M = 4.10) > Low Mach (M = 2.95). All comparisons significant (p < .01). Thus, Machiavellianism exhibited a linear, stepwise effect on susceptibility to misinformation and sharing intentions. 4.2.3. Profile Plot with Error Bars A profile plot (Fig. 1 ) illustrates group means across all dependent variables, with standard error bars. The parallel rising lines demonstrate consistent increases in misinformation belief, cognitive bias activation, and sharing likelihood as Machiavellianism level increases. The present study examined how individual differences in Machiavellianism predict belief in misinformation, activation of cognitive biases, and willingness to share deceptive content. Using an experimental design with deepfake videos and manipulated bias conditions, results showed a robust effect of Machiavellianism across all outcome measures. Specifically: Higher Machiavellianism was associated with stronger belief in misinformation. Cognitive biases were more readily activated in high-Mach participants. High Machiavellians demonstrated a greater likelihood of sharing false information. These findings align with and extend prior literature on dark personality traits and susceptibility to misinformation (Jones & Paulhus, 2014 ; March & Springer, 2019 ). Importantly, the stepwise gradient (Low < Moderate < High) underscores that vulnerability is not categorical but increases systematically with Machiavellianism. 4.2.4. Belief in Misinformation The positive relationship between Machiavellianism and belief in misinformation suggests that individuals high in manipulativeness may be less motivated to engage in critical scrutiny of information. From a dual-process perspective (Kahneman, 2011 ), they may rely more on intuitive, heuristic reasoning rather than systematic processing. This aligns with evidence that Machiavellian individuals show cognitive styles favoring expedience over accuracy (Bereczkei, 2018). 4.2.5. Cognitive Bias Activation Our bias manipulations successfully triggered stronger biases among high-Mach participants. This resonates with research on motivated reasoning (Kunda, 1990 ), where preexisting dispositions make certain individuals more prone to selective attention and biased interpretation. Machiavellianism, characterized by cynicism and strategic manipulation, may predispose individuals to accept biased narratives that serve self-interest. 4.2.6 Likelihood of Sharing Perhaps the most concerning finding is the elevated willingness to share misinformation. Unlike simple belief, sharing reflects a behavioral intention with broader societal implications. This aligns with recent studies showing that dark traits (Machiavellianism, psychopathy, narcissism) predict amplification of misinformation on social platforms (Tandoc et al., 2021 ). High-Mach individuals may perceive sharing misinformation as a strategic tool for manipulation within social or organizational contexts. 4.3. Methodological Triangulation of Study 1 and Study 2 The two studies under consideration differ substantially in design, scope, and methodological focus, offering complementary insights into the relationship between Machiavellianism, cognitive bias, and susceptibility to misinformation. Study 1 employed a correlational, cross-sectional design using a relatively large and diverse sample of 400 organizational employees. Participants were recruited using snowball and purposive sampling, which helped ensure inclusion of individuals with real-world professional experience across different career stages. The study utilized validated psychometric scales—Mach-IV for Machiavellianism, DACOBS for cognitive biases, and the MIST scale for misinformation susceptibility—and tested hypotheses using multiple regression. This design yielded results with high external validity, providing evidence that Machiavellianism and cognitive biases predict misinformation susceptibility in organizational settings. However, the reliance on self-report data and the cross-sectional structure limited causal inference. By contrast, Study 2 adopted a controlled experimental design with 60 participants deliberately grouped into low, moderate, and high levels of Machiavellianism. Using deepfake videos and bias activation manipulations, the study employed a MANOVA to examine differences in belief in misinformation, bias activation, and willingness to share. This design maximized internal validity by directly manipulating exposure to misinformation and bias cues, thereby isolating the effects of Machiavellianism with greater causal clarity. Yet, the smaller sample size and lab-based conditions limited the generalizability of results to wider populations and organizational contexts. Taken together, these methodological contrasts illustrate a central strength of triangulation. Study 1’s breadth provided ecological realism, while Study 2’s depth provided experimental precision. The triangulated evidence thus benefits from both real-world generalizability and controlled causal inference. 4.3.1. Convergence of Findings Despite methodological differences, both studies converge strongly on a central finding: Machiavellianism is a robust predictor of misinformation susceptibility. In Study 1, regression analyses showed that higher Machiavellianism scores significantly predicted higher MIST scores, even after controlling for cognitive biases. In Study 2, the experimental manipulation revealed a clear gradient, with high-Mach participants scoring significantly higher than moderate and low-Mach groups on belief in misinformation, bias activation, and likelihood of sharing. A second point of convergence lies in the role of cognitive biases. Study 1 found that higher DACOBS scores were positively associated with misinformation susceptibility, albeit with weaker predictive power compared to Machiavellianism. Study 2 supported this pattern by demonstrating that bias manipulations were more easily triggered in high-Mach individuals, leading to stronger selective attention and heuristic-driven reasoning. This convergence across a large-scale correlational study and a smaller experimental study strengthens construct validity: the consistency of findings suggests that the observed relationships are not methodological artifacts but reflect genuine psychological dynamics. Both trait-level dispositions (Machiavellianism) and process-level vulnerabilities (cognitive biases) matter significantly in explaining susceptibility to misinformation. 4.3.2 Complementarity of Findings While convergent in broad conclusions, the studies also complement each other by addressing different dimensions of the problem. Breadth vs. Depth: Study 1 provided breadth, demonstrating that the relationship between Machiavellianism, cognitive biases, and misinformation susceptibility holds in a wide sample of employees from diverse organizational backgrounds. Study 2 provided depth, exploring not only susceptibility but also bias activation and sharing intentions—variables with direct behavioral and societal consequences. Predictors vs. Mechanisms: Study 1 identified significant predictors (Machiavellianism and cognitive bias), while Study 2 unpacked mechanisms, showing that high-Mach individuals not only believe misinformation more readily but are also more likely to disseminate it, a critical distinction for real-world implications. Ecological vs. Experimental Evidence: Study 1 captured naturalistic organizational dynamics, while Study 2 validated findings under controlled manipulations, strengthening causal claims. Thus, the complementarity between studies enriches our understanding: one illustrates who is vulnerable in real-world contexts, while the other explains how vulnerability manifests when individuals are exposed to misinformation. 4.3.3. Divergence of Findings Despite strong convergence, notable divergences emerged. First, the magnitude of effects differed. Study 1 reported that Machiavellianism and cognitive biases explained approximately 10–21% of the variance in misinformation susceptibility. While significant, these effects left the majority of variance unexplained, suggesting the influence of other factors such as media trust, political ideology, or digital literacy. By contrast, Study 2 found large effect sizes, with clear stepwise differences across Machiavellianism groups for all dependent measures. The contrast suggests that effects may appear weaker in heterogeneous real-world contexts but become more pronounced in controlled experimental settings. Second, the scope of outcomes diverged. Study 1 focused on a single construct—misinformation susceptibility (MIST). Study 2 went further, examining three distinct but related outcomes: belief, bias activation, and willingness to share. This broader operationalization captures not only cognitive vulnerability but also behavioral intentions, which have greater societal and organizational implications. Third, there were differences in measurement approaches. Study 1 relied on self-reported psychometric instruments, raising concerns about social desirability and self-perception biases. Study 2 combined trait-based groupings with behavioral tasks (deepfake exposure, bias manipulations), arguably capturing more authentic reactions. These divergences highlight the value of methodological triangulation: no single method provides a complete picture, but together they map both subtle tendencies and strong causal effects. 4.3.4. Theoretical and Practical Implications Table 5 Triangulation Matrix Dimension Study 1 (Regression, n = 400) Study 2 (Experimental MANOVA, n = 60) Triangulated Insight Design Correlational, cross-sectional, organizational sample Experimental, controlled lab with deepfakes and bias manipulations Real-world generalizability + causal clarity Key Predictors Machiavellianism, Cognitive Bias Machiavellianism (low, moderate, high groups) Both highlight Machiavellianism as robust predictor Outcomes Misinformation susceptibility (MIST) Belief in misinformation, bias activation, likelihood of sharing Broader understanding: cognitive vulnerability + behavioral intent Effect Strength Moderate (R² ≈ 0.10–0.21) Large, significant group differences Effects depend on method/context but consistently meaningful Validity High ecological validity (real organizational contexts) High internal validity (controlled manipulations) Balanced insights from ecological and experimental perspectives Through methodological triangulation, the combined evidence of Study 1 and Study 2 underscores the pivotal role of Machiavellianism and cognitive biases in shaping responses to misinformation. Study 1 contributes breadth and real-world validity, while Study 2 provides depth and causal clarity. Their convergence validates core findings, their complementarity enriches interpretation, and their divergences caution against overgeneralization from any single methodological approach. Together, these studies present a compelling case for integrated research designs in misinformation studies. They highlight the need for cross-cultural replications, incorporation of other dark traits such as narcissism and psychopathy, and the development of interventions that simultaneously address cognitive vulnerabilities and personality-driven risks. From a practical perspective, organizations, policymakers, and digital platforms must recognize misinformation not only as a product of faulty cognition but also as a function of manipulative personality traits. Addressing this dual pathway requires holistic strategies—combining cognitive debiasing, ethical culture-building, and accountability frameworks. In sum, methodological triangulation across Study 1 and Study 2 produces a more comprehensive, reliable, and actionable understanding of misinformation dynamics. By integrating correlational and experimental evidence, the research establishes a stronger foundation for theory development, applied interventions, and societal resilience against the spread of deceptive content. 4.4. Proposed Model: Machiavellianism, Cognitive Bias, and Misinformation Dynamics 4.4.1 Core Pathways Machiavellianism → Misinformation Susceptibility Supported in both studies. High Machiavellians are more likely to believe misinformation and view it strategically. ii. Cognitive Bias → Misinformation Susceptibility Both studies confirm positive effects. Biases like confirmation bias, overconfidence, and selective attention amplify vulnerability. iii. Machiavellianism × Cognitive Bias Interaction Study 2 suggests high-Mach individuals are more prone to bias activation when exposed to misinformation cues. Implies synergistic effects: personality traits heighten the influence of cognitive distortions. iv. Outcomes Belief in Misinformation (cognitive acceptance) Bias Activation (distorted reasoning under manipulation) Likelihood of Sharing (behavioral intention) 4.4.2. Moderators and Contextual Factors Organizational Environment (Study 1) → influences generalizability and how misinformation spreads in professional contexts. Experimental Manipulation (deepfakes, bias cues) (Study 2) → demonstrates causal mechanisms under controlled conditions. 4.4.3. Explanation of the Model Direct Effects : Both Machiavellianism and cognitive biases independently predict susceptibility. Interactive Effects : Machiavellianism amplifies how biases operate — making people more reactive to manipulative content. Outcomes : The combined effects lead not just to belief but also to bias-driven reasoning and sharing behavior , which are critical for misinformation spread. Contextual Moderators : Real-world organizational settings (Study 1) reveal broad associations, while experimental manipulations (Study 2) highlight causal mechanisms. The proposed model linking Machiavellianism, cognitive bias, and misinformation susceptibility aligns with existing research confirming the core pathways. Machiavellianism independently predicts higher susceptibility to misinformation, with individuals often strategically viewing misinformation and being more likely to believe and share it. This trait can amplify cognitive biases in processing misinformation. Cognitive biases such as confirmation bias, overconfidence, and selective attention positively affect misinformation vulnerability. These biases create distortions in reasoning and information evaluation, increasing acceptance and sharing of false information. The interaction between Machiavellianism and cognitive biases suggests that high Machiavellian individuals are more reactive to misinformation cues, heightening bias activation under manipulation, leading to stronger belief, biased reasoning, and a higher likelihood of sharing misinformation. Moderators and context, such as organizational environments and experimental manipulations (e.g., deepfake exposure), play a role by influencing these relationships and helping show causal mechanisms under controlled conditions. The model's outcomes—belief in misinformation, cognitive bias activation, and sharing behavior—represent critical stages through which misinformation spreads, shaped by personality traits and cognitive distortions in context. Thus, this framework is supported by psychological and communication research emphasizing both motivational and cognitive drivers of misinformation susceptibility and the complex interplay between personality and cognitive processing biases. This confirms the model’s core pathways, interactive effects, and contextual moderators as valid and insightful for understanding misinformation dynamics. 4.5 Implication of the study: Various theoretical and organizational implication of these studies are described below. 4.5.1. Theoretical contribution of the study Integration of Personality and Cognition Misinformation susceptibility cannot be fully explained by cognitive deficits alone. Personality dispositions like Machiavellianism also play a crucial role. This supports dual-pathway models in which both motivational (personality) and cognitive (bias) mechanisms interact. Dark Triad and Information Behavior Prior research has linked the Dark Triad traits (Machiavellianism, narcissism, psychopathy) to manipulative and deceptive tendencies. This study extends that knowledge by showing how such traits also heighten susceptibility to misinformation, connecting personality psychology to information sciences. Potential Mediation by Cognitive Bias Although regression treated Machiavellianism and Cognitive Bias as separate predictors, it is plausible that cognitive biases mediate the relationship between Machiavellianism and misinformation. For instance, cynicism and opportunism (Machiavellian traits) may amplify confirmation bias, thereby reinforcing misinformation acceptance. Dual-Pathway Models of Misinformation: Evidence from both studies supports frameworks positing that misinformation vulnerability arises from the interaction of motivational traits (e.g., Machiavellianism) and cognitive processes (biases, heuristics). Dark Personality and Information Behavior: The results extend dark personality research by demonstrating that Machiavellian traits do not only predispose individuals to manipulation but also increase their likelihood of endorsing and spreading misinformation. This expands the scope of dark triad research into digital misinformation contexts. Cognitive Bias Theory: The findings reinforce dual-process models (Kahneman, 2011 ), showing that reliance on fast, heuristic-based thinking (System 1) rather than analytical reasoning (System 2) leaves individuals vulnerable to false information. 4.5.2. Practical Implications From an applied perspective, the results are highly relevant for organizations: Organizational Risks Employees susceptible to misinformation may spread rumors or false narratives, undermining trust and productivity. Training and Awareness: Organizations could implement critical thinking and bias-awareness workshops to mitigate misinformation risks. Recruitment and HR Practices: While ethically sensitive, psychometric assessments (e.g., Mach-IV, DACOBS) could help identify vulnerabilities and tailor professional development. Digital Literacy Campaigns: Given the role of social media, promoting digital literacy is essential not only within organizations but also in society at large. Organizational Risk Management: In organizational settings, employees high in Machiavellianism pose dual risks: they are more likely to believe misinformation and may strategically weaponize it. HR departments must recognize misinformation as not only a cognitive vulnerability but also a personality-driven threat. Intervention Design: Traditional fact-checking and critical thinking training may reduce cognitive bias vulnerabilities but may fail with high-Mach individuals, who may use misinformation opportunistically. For such cases, ethical training, accountability structures, and transparent communication policies are critical. Digital Platforms: Social media platforms could develop predictive moderation models that incorporate personality-informed variables, potentially identifying high-risk profiles for misinformation dissemination. Education and Public Policy: Broader interventions in digital literacy must account for both cognitive and motivational pathways, acknowledging that misinformation susceptibility is not simply a matter of knowledge gaps but is embedded in dispositional and cognitive styles. Conclusion This study demonstrates that Machiavellianism and Cognitive Bias significantly predict misinformation susceptibility, albeit explaining only a modest portion of variance. These findings highlight the dual importance of personality traits and cognitive processes in shaping responses to misinformation. From a theoretical perspective, the results connect personality psychology and cognitive science, enriching the broader discourse on misinformation. Practically, they call for targeted interventions in organizations and society to reduce misinformation vulnerability. In sum, misinformation is influenced by many interlocking factors. Among them, Machiavellianism and Cognitive Bias stand out as significant psychological contributors—worthy of deeper exploration in both research and practice. 5.1. Limitations This study is not without limitations. The design limits causal inference. Relationships observed here may involve mediating or moderating variables not captured. Only Machiavellianism was examined; other dark traits (narcissism, psychopathy) may interact differently. 5.2. Future Research Directions Future work should: Use longitudinal and experimental designs to establish causal relationships. Examine mediating and moderating mechanisms (e.g., digital literacy, resilience to persuasion, trust in institutions). Employ larger, representative samples to enhance generalizability across contexts. Apply advanced techniques such as Structural Equation Modeling (SEM) to explore indirect pathways. Investigate cross-cultural differences, particularly between collectivist and individualist societies. This study highlights the critical role of Machiavellianism in shaping responses to misinformation. Individuals higher in Machiavellian tendencies are more likely to believe, succumb to biases, and share deceptive content. These findings underscore the need for integrated psychological and technological interventions to address misinformation in the digital age. Declarations Ethics Statement: The study titled “Dark trait, Deception, and Deepfakes: The interplay of Machiavellianism, Cognitive Biases, and Misinformation in the Organization” was reviewed and approved by the Institutional Ethics Committee of Woxsen University Hyderabad, India. All participants provided informed consent prior to participation, and confidentiality was maintained throughout the study. 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14:27:38","extension":"html","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":231797,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8082633/v1/fb17022b38f566c9b9af58e1.html"},{"id":96244199,"identity":"1379717f-7d91-4b0b-8a4a-814c61b91983","added_by":"auto","created_at":"2025-11-19 07:17:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":283020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProfile Plot of Dependent Variables Across Machiavellianism Levels\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8082633/v1/0ed54b41cc8d86701288c4eb.png"},{"id":95930860,"identity":"a75241e9-c355-47b0-a876-d1af5fe2b1cd","added_by":"auto","created_at":"2025-11-14 14:27:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":346152,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisual Model showing the interplay between Machiavellianism, Cognitive Biases and Misinformation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8082633/v1/f68071972f782d266ae8deef.png"},{"id":96255315,"identity":"b5c50283-893c-4519-8293-04e17191cc77","added_by":"auto","created_at":"2025-11-19 07:48:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1992170,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8082633/v1/196e283f-3ed8-4f9c-8bfe-60a2d8a15b4d.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDark trait, Deception, and Deepfakes: the interplay of Machiavellianism, Cognitive Biases and Misinformation in the Organization.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn today's complex and competitive workplace environments, individuals often face pressures to succeed, advance their careers, and achieve organizational goals. However, some individuals may resort to deceptive tactics, such as maintaining fake identities and exhibiting Machiavellian behaviors, to achieve their objectives. Numerous studies have claimed that Machiavellians pose a threat to the organization's and its members' well-being (Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and have labeled Machiavellianism (Mach) as a \"dark\" personality trait (Furnham et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Mach, the leader, and Mach, the employee, have both been connected to unethical, manipulative, and ineffective work practices (Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kiazad et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, what occurs if a negative personality trait, like Machiavellianism, is highly rated by both the employee and the leader? Does this make the issue worse? Does the leader-follower fit theory (Atwater and Dionne \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) imply that favorable outcomes result from a leader and employee being comparable on the Machiavellianism trait? Or do these unpleasant personalities conflict and produce unfavorable results? Few studies have examined the consequences of the interplay between unfavorable leader and follower characteristics. Thus, the purpose of this article was to investigate how workers with high Machiavellian scores deal with a similarly deceptive high Mach leader.\u003c/p\u003e\u003cp\u003eThe Italian Renaissance diplomat Niccolo Machiavelli, who wrote a thesis outlining the ideal but immoral behavior of royalty to accomplish their objectives, is the namesake of the construct of Machiavellianism. However, it wasn't until Christie and Geis's (1970) work that Mach was presented as a psychological concept. These authors contend that Mach portrays a master manipulator who acts amorously, employs aggressive strategies, and has a pessimistic, cynical, and distrustful outlook on the world. Mach is typically portrayed negatively due to its manipulative and immoral side, and it has drawn interest in studies on business ethics (Den Hartog and Belschak \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ricks and Fraedrich \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Schepers \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and organizational behavior (Belschak et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Machs can be found in any kind of organization, including nonprofits (Smith et al. 2009; Chen \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). They are persuasive liars and manipulators who are less aware of moral dilemmas (Schepers \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Therefore, it's critical to comprehend how they affect other people and organizations. Recent studies have examined the ways in which these \"dark\" personality traits in organizational members influence various organizational outcomes (Harms et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Judge et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kuyumcu and Dahling \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEvidence is mounting indicating people with particular personality and cognitive traits are more likely to experience false memories, even though these findings are not always consistent. For instance, we discovered that cognitive abilities were negatively correlated with a higher probability of experiencing false memory in our recent study of cognitive components in false memory (Zhu et al.,2013). We expanded our earlier research to incorporate personality characteristics in false memory in this study. Errors caused by misleading questions (Merckelbach, Muris, Rassin, \u0026amp; Horselenberg, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), DRM false memory (Winograd, Peluso, \u0026amp; Glover, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), and false childhood memories (Qin, Ogle, \u0026amp; Goodman, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) are among the types of false memories that have weak to moderate associations with dissociative experience, or the tendency to have disturbances of normal integration of awareness, thought, memory, and personality (Carlson \u0026amp; Putnam, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). This finding has not been confirmed by other investigations (Wilkinson \u0026amp; Hyman, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Special groups, such as those with PTSD or self-reported alien abduction, accounted for the majority of the noteworthy findings about the positive relationship between depression and false memory (Clancy et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Zoellner et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). However, Salthouse and Siedlecki (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) could not detect a significant relationship between DRM false memory and depression using a non-clinical population. Additionally, negative mood was linked to less DRM false memories, according to Storbeck and Clore (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMachiavellians are known for their pessimistic outlook on the world (Jones and Paulhus \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Machiavellians distrust other people and their intentions because they expect the worst from them and believe that they are dishonest and deceitful (Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Machiavellians' elevated levels of negative emotions (stress, dissatisfaction) (Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and their manipulative and immoral behavior (\"strike before the other does\"; Mudrack 1993; Schepers \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) may be explained by their pessimistic outlook and consequent lack of trust in those around them. Machiavellian workers are more prone to lack trust in others, especially their leaders, and studies have indicated that followers' attitudes and actions suffer when there is a lack of trust between a leader and followers (Dirks and Ferrin \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Therefore, we contend that the relationship between employee Mach and their well-being (stress) and (unethical, counterproductive) work behaviors is mediated by a decreased level of confidence in the boss. Most of the current material on Mach has focused on Mach personnel (Dahling et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Belschak et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) or leaders (Deluga 2001; Den Hartog and Belschak \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). As mentioned above, the research does not yet fully understand whether Machs' responses to other Machs\u0026mdash;that is, Mach employees' relationships with Mach leaders\u0026mdash;will shift. According to leader-follower fit theory (Atwater and Dionne \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), followers and leaders should have similar personalities or personal beliefs. This theory supposedly explains why high-Mach employees will respond to Mach leaders differently than low-Mach employees.\u003c/p\u003e\u003cp\u003eMachiavellianism refers to a personality trait characterized by cunning, manipulation, and the strategic use of power to achieve one's goals. It's named after Niccol\u0026ograve; Machiavelli, a Renaissance-era political philosopher known for his book \"The Prince,\" in which he discussed the pragmatic and often ruthless tactics rulers could employ to maintain power. Individuals high in Machiavellianism are typically skilled at influencing and controlling others to advance their own interests. They are often willing to exploit others without feeling guilt or remorse, viewing interpersonal relationships as means to an end rather than valuable in themselves. Machiavellian individuals are adept at understanding social dynamics and are often strategic in their interactions, using deception and manipulation to achieve their objectives. Traits associated with Machiavellianism include (Christie, \u0026amp; Geis, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1970\u003c/span\u003e):\u003c/p\u003e\u003cp\u003eManipulativeness: Machiavellian individuals excel at influencing others to do their bidding through persuasion, flattery, or other deceptive tactics.\u003c/p\u003e\u003cp\u003eStrategic thinking: They are often highly strategic in their approach to achieving their goals, considering the potential outcomes of their actions and adjusting their behavior accordingly.\u003c/p\u003e\u003cp\u003eLack of empathy: Machiavellian individuals may be indifferent to the feelings and well-being of others, viewing them as obstacles or tools to be used in the pursuit of their objectives.\u003c/p\u003e\u003cp\u003eDesire for control: They seek to maintain control over their environment and the people around them, often by exerting influence or power over others.\u003c/p\u003e\u003cp\u003ePragmatism: Machiavellian individuals are typically focused on practical outcomes rather than moral considerations, willing to engage in unethical behavior if it serves their interests.\u003c/p\u003e\u003cp\u003eIt's important to note that Machiavellianism is just one of the traits within the \"Dark Triad,\" which also includes narcissism and psychopathy. While individuals high in Machiavellianism may display some similar characteristics to those high in narcissism or psychopathy, they are distinct personality traits with their own unique features. Cognitive Efficiency and Deceptive Behaviors: Exploring how cognitive efficiency, defined as the ability to process information quickly and effectively, influences deceptive behaviors at the workplace. This section will delve into how individuals with high cognitive efficiency may be more adept at concealing their true intentions and adapting their behavior to manipulate others. Cognitive bias refers to systematic patterns of deviation from rationality or sound judgment in decision-making, often influenced by factors such as perception, memory, or social influence. These biases can lead people to make judgments or decisions in ways that are systematically different from what would be considered rational or optimal. They can affect various aspects of cognition, including attention, memory, and decision-making processes.\u003c/p\u003e\u003cp\u003eHere are some common examples of cognitive biases:\u003c/p\u003e\u003cp\u003eConfirmation bias: This occurs when people tend to search for, interpret, or remember information in a way that confirms their preconceptions or hypotheses while ignoring contradictory evidence.\u003c/p\u003e\u003cp\u003eAvailability heuristic: This bias involves people basing their judgments on the ease with which relevant examples come to mind. Events that are more memorable or easily accessible in memory are often given more weight, even if they are not statistically representative.\u003c/p\u003e\u003cp\u003eAnchoring bias: People rely too heavily on the first piece of information they receive (the \"anchor\") when making decisions, even if that information is irrelevant or unreliable. Overconfidence bias: This bias leads individuals to overestimate their own abilities or the accuracy of their judgments. It can result in excessive risk-taking or unwarranted certainty in one's beliefs. Dunning-Kruger effect describes a cognitive bias where individuals with low competence in a particular area tend to overestimate their abilities, while those with high competence may underestimate their skills. Bandwagon effect: People are more likely to adopt certain beliefs or behaviors when they perceive that others are doing the same, regardless of the rationality or validity of those beliefs or behaviors.\u003c/p\u003e\u003cp\u003eSunk cost fallacy: This bias occurs when people continue to invest time, money, or effort into a project or decision based on the resources they have already committed, even when it's clear that continuing is not in their best interest.\u003c/p\u003e\u003cp\u003eFraming effect: This bias refers to the way in which the presentation or framing of information can influence decision-making. The same information presented in different ways can lead to different judgments or choices.\u003c/p\u003e\u003cp\u003eOverconfidence Bias: Exploring how overconfidence bias may lead individuals to believe in their ability to deceive others without getting caught, leading to riskier deceptive behaviors.\u003c/p\u003e\u003cp\u003eSelf-Serving Bias: Discussing how self-serving bias allows individuals to maintain a positive self-image despite engaging in deceptive behaviors by attributing successes to internal factors and failures to external factors.\u003c/p\u003e\u003cp\u003eThese biases can affect individuals in various contexts, including personal decision-making, organizational behavior, and societal attitudes. Being aware of these biases can help mitigate their influence and lead to more rational decision-making processes.\u003c/p\u003e"},{"header":"Literature survey","content":"\u003cp\u003e\"The Mask of Malevolence: The Mediating Role of Emotional Exhaustion in the Relationship between the Dark Triad and Workplace Bullying\" by Lee, Kibeom, and Michael C. Ashton (2018). This study explores how Machiavellianism, along with other dark personality traits, influences workplace behaviors such as bullying and harassment. \"Keeping It Real: How Employees Manage Their Guilty Consciences\" by Scott Sonenshein and Francis J. Flynn (2013). This research examines the strategies employees use to maintain authenticity in the workplace, shedding light on the motivations behind maintaining a fake identity. \"The Influence of Machiavellianism on Ethical Perception and Intentions in the Workplace\" by Arthur J. Bedeian, Doreen C. McManus, and A. Peter Frank (2010). This study investigates how Machiavellianism affects individuals' ethical perceptions and intentions in workplace settings. \"Deceptive Communication in the Workplace: An Examination of Participant Roles, Expectancy Violations, and Deception Detection Accuracy\" by Tim Levine, David M. Behfar, and Victoria K. Wildman (2014). This research examines deceptive communication in workplace interactions and factors influencing deception detection accuracy. \"Seeing the World through \"Machiavellian Eyes\": How Social Network Centrality Affects Organizational Citizenship Behavior Ratings\" by Christina M. Brown and Catherine T. Kwantes (2017). This study explores the relationship between Machiavellianism and organizational citizenship behavior, shedding light on how individuals with Machiavellian tendencies navigate workplace relationships. \"Cognitive Efficiency and Social Evolution: How Cognitive Load Can Drive the Evolution of Social Heuristics and Trust\" by Magnus Enquist and Stefano Ghirlanda (2007). This paper discusses the concept of cognitive efficiency and its implications for social evolution, providing insights into how cognitive processes influence social behaviors. \"Confirmation Bias: A Ubiquitous Phenomenon in Many Guises\" by Raymond S. Nickerson (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). This seminal work reviews the literature on confirmation bias, providing a comprehensive understanding of its manifestations and implications across various domains, including decision-making and judgment. \"Overconfidence and Risk Taking in Forensic Mental Health Clinicians\" by Joseph P. Currier and Todd M. Moore (2009). This study investigates the relationship between overconfidence bias and risk-taking behavior in forensic mental health clinicians, offering insights into the consequences of overconfidence in professional settings. \"Self-Serving Bias in the Classroom: Who Shows It, Why, and What Can We Do about It?\" by P. W. J. van der Wal, J. H. M. van Dijk, and A. G. Bus (2016). This research examines self-serving bias in educational contexts and suggests strategies to mitigate its impact on academic performance and social interactions. \"Organizational Culture and Leadership\" by Edgar H. Schein (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This seminal work explores the role of organizational culture in shaping workplace behavior and decision-making, providing insights into how leaders can foster ethical cultures and mitigate the prevalence of deceptive behaviors.\u003c/p\u003e\u003cp\u003eIn a report by Irena Pilch (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) mentioned about effective ways of dealing with machiavellianism in workplace. She mentioned that overcoming the malpractices of machiavellianism is a challenge but at the same time its also very important to understand human behaviour deeply to manage interpersonal relationship. Though the term machiavellianism is derived from writer and diplomat Niccolo Machiavelli\u0026rsquo;s behaviour, but later on in the field of academics, industries and research it practiced to explain the manipulative, cunning and negative behaviour. Usually these are the sets of behaviour which depicts a person\u0026rsquo;s behaviour in the most negative way e.g. lack of empathy, manipulate others for your own sake, hiding the truth and presenting a cooked story to show own achievement, ruthless approach to achieve own\u0026rsquo;s goals and objectives and many more. Machiavellianism is known as one of the \u0026ldquo;dark triads\u0026rdquo; of personality apart from psychopathy and narcissism. All these kind of behaviour can disrupt the normal functioning in workplace and personal lives, both. Usually, people having machiavellianism tendencies, develop a very cunning approach of manipulation. They even do not mind to twist environment and people around them for their own advantages. Usually their actions are more calm, strategic and calculated (Pilch, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and they have almost negative regard for consequences of their behaviour in terms of moral and ethical perspective. E.g. lack of empathy plays a severe role in machiavellianism. Their ignoring attitude about other\u0026rsquo;s emotion sometimes lead to a detrimental environmental effect. They become so obsessed with their goals that they even do not consider people or human being, rather they consider everyone as tools which they will use for their personal gain. In workplaces they manifest this behaviour in various ways. Few such examples would be to take credit for all the work done by their colleagues and teammates, sabotage others, doing politics to climb the career ladder, removing people from the way which creates blockage, or even telling lies about people for their own benefits. Without any argument it is understood that these types of behaviour can lead to create toxic workplace environment. According to Wilson et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), Machiavellianism is a social conduct strategy that entails influencing others for one's own benefit. We contend that, despite their secretly less moral convictions, these cunning Machiavellians may (inauthentically) exhibit moral leadership behaviors if they believe that doing so would help them achieve their objectives. However, it was found that the beneficial effects of moral leadership on followers' involvement will be diminished for leaders whose public and private identities conflict since followers are likely to recognize insincere behavior (Zapf \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Thus, in Study 2, we test a moderated mediation model and add leader Machiavellianism as a moderator, building upon the mediation model from Study 1.\u003c/p\u003e\u003cp\u003eIn the second study, was whether authentic, values-based proven moral leadership is always the case. We also suggest that extremely deceptive Machiavellians might attempt to project an ethical persona if they believe it will help them. The degree to which followers view a leader's behavior as ethical is reflected in the measures of ethical leadership; however, it is unclear if these behaviors are always a true reflection of a leader's moral character. Here, we contend that leaders who exhibit publicly inconsistent inner norms and ideals with their publicly expressed principles and behaviors may be perceived as acting inauthentically when they exhibit outwardly ethical behavior. Here, we specifically refer to the distinction between publicly displayed ethical conduct and behavior and privately held Machiavellian ideals and beliefs such a machiavellian personality represents a deceitful and unethical value system which opposes moral values of ethical leaders. According to Wilson et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), Machiavellianism is a social conduct strategy that entails using others' manipulation for one's own benefit. Machiavellians are perceived as deceivers and manipulators who lower an organization's or group's social capital (e.g., Paulhus and Williams 2002; Gunnthorsdottir et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). For instance, Ross and Robertson (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) found a positive correlation between Machiavellianism and salespeople's propensity for lying. Naturally, dishonesty, deceit, and manipulation do not strike one as moral actions by leaders. According to Brown and Trevi\u0026ntilde;o (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), Machiavellian leaders are driven to manipulate people in order to achieve their own objectives, in contrast to ethical leaders. They tend not to be trusted by others because they don't have much faith in people.\u003c/p\u003e\u003cp\u003eThey contend that manipulation and coercion are unethical means of influencing others and that followers are unlikely to view leaders who use these strategies as appealing ethical role models. Social learning, which is predicated on the idea that observers can freely choose which models to study and imitate, is incompatible with coercion and manipulation. Consequently, Brown and Trevi\u0026ntilde;o (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) suggest a negative relationship between Machiavellianism and moral leadership.\u003c/p\u003e\u003cp\u003eSimilar findings are found in the literature on emotional work (Hochschild \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Ashforth and Humphrey 1993; Zapf \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). When emotions are expressed authentically, people perceive it differently and more favorably than when they \"fake\" their emotions (surface acting: expressing emotions that are different from one's real inner feelings).\u003c/p\u003e\u003cp\u003eConsequently, we propose that the beneficial influence of moral leadership conduct on involvement is diminished for leaders whose public and private identities are at odds (that is, when Machiavellians masquerade as moral leaders). When moral behavior is displayed and principles that are not personally held are publicly emphasized, it can be insincere. As a result, the influence of moral behavior on others is diminished (Zapf \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Beginning with Loftus's seminal work in the field of human memory, research on the misinformation effect has a lengthy and rich history (1975; Loftus \u0026amp; Palmer, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Participants in a typical misinformation effect study observe an event, typically visually, through a video (Chan, Thomas, \u0026amp; Bulevich, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) or slides (Loftus \u0026amp; Palmer, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Participants are given false information about what they saw, either through a narrative (Chan et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zaragoza, Payment, Ackil, Drivdahl, \u0026amp; Beck, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) or deceptive questions (Zaragoza \u0026amp; Lane, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), at some point after the event but before their memory is tested. Participants' memory is then tested after being given false information, and the results usually indicate that the false information had a negative impact on their recollection of the events they saw, leading them to believe that false information was actually shown on the slides or video they watched. Therefore, instances where people mistake a spoken account of an event for a prior visual experience are documented by misinformation effects.\u003c/p\u003e\u003cp\u003eThe idea that spreading false information can lead to a strong belief that the misinformation was part of the same experience as the event that was witnessed (i.e., recollected) is supported by a number of findings. The majority of this data is derived from studies that look at the source attributions people make after being exposed to false information. Some studies have specifically asked participants to rate whether they can recall experiencing certain components as part of an event they saw (Zaragoza \u0026amp; Lane, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Source judgments offer a measure of the precision of an individual's beliefs regarding where or when they encountered disinformation, as opposed to merely stating the broad belief that they did so (Johnson, Hashtroudi, \u0026amp; Lindsay, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). According to van der Linden et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), misinformation is defined as \"any information that is demonstrably false or otherwise misleading, regardless of its source or intention.\" The (lack of) truth value of disinformation is its defining feature: selective and half-true information, as well as information that is erroneous, lacking, deceptive, or untrue. The intention is still a crucial factor, though. Think of a white lie as information that is false, possibly deceptive, but intended to be helpful. White falsehoods are not considered misleading, so it's reasonable to infer that. Several important benchmarks surface in the ongoing discussions about the best standard to use when evaluating the actual worth or ground truth of a piece of information. These include facts or evidence, professional judgment, and traits of dishonest or manipulative tactics (Nan et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Roozenbeek et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Vraga and Bode, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We view disinformation as a subset of misinformation, acknowledging the inherent difficulty of determining intent in many situations, even though some people distinguish misinformation from disinformation, the latter of which is intentionally produced and disseminated to deceive and cause harm (Treen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). One of the biggest problems facing modern human society is the pervasive propagation of false information, which is made worse by the social media and high-choice media landscape. Although misinformation has existed since the early 15th century (Soll, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), its severe and increasingly obvious effects on a wide range of public domains, such as politics, science, and health, have garnered the phenomenon unprecedented attention in recent decades, especially after 2016\u0026mdash;the year that the Oxford dictionary chose the word \"post-truth\" as the word of the year.\u003c/p\u003e\u003cp\u003eMisinformation has been shown to weaken support for proclinate policies (Treen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), undermine electoral processes (Berlinski et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), encourage vaccination hesitancy (Garett and Young, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and deter the implementation of safety and preventive measures during the coronavirus diseases 2019 (COVID-19) pandemic (Greene and Murphy, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Understanding how and why false information affects people's decision-making and produces these negative effects is a critical issue that goes beyond simple facts. A more nuanced framework that acknowledges that ignorance alone lacks explanatory power has replaced a paradigm that placed a strong emphasis on information deficits and linked the impact of misinformation to a lack of comprehension and knowledge about facts (Ecker et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Even though Aristarchus and Eratosthenes proved that the earth was round in the third century, the idea was not widely accepted until the 15th century; Uri, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020\u003c/span\u003e. This is just one example of how misinformation can arise and spread without any prior position. However, considering the polarization and division of society in the post-2016 United States, it is no accident that misinformation is particularly prevalent on contentious and politically charged topics (such as COVID-19, the 2020 election, and climate change). This implies that before false information is created and disseminated, people most likely already have preconceived notions and/or acquired attitudes regarding the particular concerns. To lessen the negative feelings (negative affect) that come with \"bad\" behavior, people resort to reasoning. In the context of reporting, people who think about lying would also expect to feel awful because lying goes against their morals (Festinger, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) or the expectations of society (Bandura, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1991\u003c/span\u003e, Bandura, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Emotions keep us honest, according to Frank (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Nonetheless, a lot of people can come up with an explanation to lessen the negative emotions that come with lying (Murphy and Dacin, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Sykes and Matza, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1957\u003c/span\u003e). Predisposed means \"inclined or influenced beforehand; made susceptible,\" according to Webster (Webster, 1996). Characteristics or attitudes might be examples of predispositions. Wicker (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e1969\u003c/span\u003e) defines attitude as \"evaluative feelings of pro or con, favorable or unfavorable, with regard to particular objects; the objects may be abstract concepts or concrete representations of things or actions.\" A dissonance study paradigm that looks at attitude change after a counter-attitudinal behavior shows that attitudes are generally changeable (Harmon-Jones \u0026amp; Mills, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOther related variables, such as character, are more stable and potentially more predictive of behavior, but attitudes are more malleable and therefore not always as predictive. Machiavellianism is one such quality. For many years, the Machiavellian instrument has been used to measure character with good results (Christie \u0026amp; Geis, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). The tool assesses people's inclination to behave in a way that is consistent with Machiavelli, the instrument's namesake. According to Christie and Geis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1970\u003c/span\u003e), a Machiavellian, or high Mach, typically sees and controls others for personal gain.\u003c/p\u003e\u003cp\u003eHigh Machs typically behave in ways that align with the economic idea of self-interest and are more opportunistic (Gunnthorsdottir, McCabe, \u0026amp; Smith, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Given reasonable justifications and a low likelihood of detection, they are more likely to cheat than low Machs (Cooper \u0026amp; Peterson, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Given the chance and incentive, it makes sense to assume that high Machs would be more prone to underreport.\u003c/p\u003e\u003cp\u003eTheoretically, the connected conduct should be linked to an underlying attitude or character feature. It is less evident, though, if character or attitude should be linked to negative impact or justification. Other than the fraud triangle, which connects them, I can't think of any hypothesis explaining a connection between rationalization and any predispositions. Machiavellianism is of primary importance for management research since it is pertinent to many organizational criteria (such as leadership behavior, counterproductive work practices, defection, and job satisfaction). According to research, Machiavellians behave more successfully when there are significant rewards for winning, among other factors [Citation]. This Machiavellian behavior should therefore flourish in such a setting, much like in innovation competitions where participants vie for a prize. The function of this essential personality characteristic of the \"dark triad\" in the setting of an invention competition has not yet been examined in any research.\u003c/p\u003e\u003cp\u003eCognitive bias: what is it?\u003c/p\u003e\u003cp\u003eCognitive bias is a methodical way of thinking that results from the brain's propensity to streamline information processing by applying a filter of preferences and past experiences (Gigerenzer, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The brain uses the filtering process as a coping mechanism to quickly digest and prioritize vast amounts of information. Thought errors can result from the mechanism's limits, notwithstanding its effectiveness.\u003c/p\u003e\u003cp\u003eIn essence, cognitive biases aid people in navigating daily life by providing mental shortcuts, but they can also lead to erroneous interpretations and conclusions.\u003c/p\u003e\u003cp\u003eMemory, attention, and other mental errors are common causes of cognitive biases. These are frequently automatic decision-making processes that allow people to easily be impacted without even realizing it. Heuristics are a sort of coping mechanism and filtering procedure used to swiftly assimilate massive amounts of information.\u003c/p\u003e\u003cp\u003eAmos Tversky and Daniel Kahneman first proposed the idea of cognitive bias in 1972. Although the brain's tendency to take shortcuts may not be totally eliminated, being aware of biases might help you make better decisions.\u003c/p\u003e\u003cp\u003eIf Machiavellianism is present in an organization, a lot of things go wrong. One such element that is crucial for people to function well in a group is \"trust.\" It is also observed that it gets affected if Machiavellianism is present in the team or even in the environment.\u003c/p\u003e\u003cp\u003eThe foundation of productive teamwork and collaboration is trust, which is undermined by Machiavellian strategies. Employee wellbeing can generally deteriorate as a result of this erosion of trust, which can also lead to lower morale and more stress. Furthermore, when efforts and resources are directed toward controlling or lessening the disruptive actions of Machiavellian individuals, the team's or organization's overall productivity may suffer.\u003c/p\u003e\u003cp\u003eIt is imperative to acknowledge and comprehend these inclinations before attempting to successfully combat Machiavellian actions in the workplace. Machiavellians are frequently skilled manipulators who use charm and dishonesty to sway and subjugate others. Usually, they put their interests ahead of morality or the welfare of their coworkers. This conduct can take many different forms, ranging from overt sabotage or gossip to more covert means of undermining others.\u003c/p\u003e"},{"header":"Research Gaps","content":"\u003cp\u003eSince the previous researches were elaborative but inconclusive, a few gaps were identified from the existing literature which helped to formulate this present study.\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNo study exists on Machiavellianism behavior by employees\u003c/b\u003e, with a connection of cognitive behavior.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNo study on misinformation\u003c/b\u003e exists in connection to high/low Machiavellianism and overall organizational culture.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eLimited integration of psychological theories\u003c/b\u003e on organizational policies about Machiavellianism and mis/disinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eLack of holistic models\u003c/b\u003e that connect Machiavellianism, cognitive bias, deep fake and mis/disinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e3. \u003cb\u003eMethodology\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eResearch Objective\u003c/b\u003e: The main objective of this study is to investigate the relationship between Machiavellianism, misinformation and cognitive biases in the workplace, aiming to understand how individuals with Machiavellian traits utilize and are influenced by cognitive biases in organizational settings.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eStudy Design\u003c/b\u003e: A mixed-method approach was employed, combining quantitative surveys with experimental methods. Study 1 was designed to implement the quantitative work and study 2 was designed to conduct experiment. Finally, data triangulation was done.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eResearch Questions\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAre the employees with high Machiavellianism more likely to engage in \u003cem\u003ecreating and spreading disinformation for personal or professional gain\u003c/em\u003e?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow do individuals with high Machiavellian traits utilize cognitive biases to \u003cem\u003ecreate more convincing disinformation\u003c/em\u003e?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAre they more likely to exploit certain biases, such as jumping to conclusion bias or belief inflexibility bias etc, to \u003cem\u003eincrease the spread of misinformation/ disinformation\u003c/em\u003e?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDo individuals with higher levels of Machiavellianism show greater susceptibility \u003cem\u003eto create and share deep fakes\u003c/em\u003e?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the \u003cem\u003eprevalence of Machiavellianism\u003c/em\u003e in the workplace?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat are the \u003cem\u003ecommon cognitive biases\u003c/em\u003e exhibited by individuals with high levels of Machiavellianism?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e3.4 \u003cb\u003eStudy 1: Quantitative Surveys\u003c/b\u003e: Participants will complete questionnaires assessing their levels of Machiavellianism, misinformation and cognitive bias.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e3.4.1 Hypothesis:\u003c/div\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ei.\u003c/b\u003e Machiavellianism is directly proportionate to misinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eii.\u003c/b\u003e Machiavellianism is directly proportionate to cognitive bias.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e3.4.2. Participants\u003c/b\u003e: The study recruited a diverse sample of 400 participants who are working in organizations. Initially more participants were approached but finally 400 data were collected.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e\u003cb\u003e3.4.3 Sampling type: S\u003c/b\u003enowball and purposive sampling methods were used to collect data.\u003c/div\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e3.4.4 Scales used\u003c/b\u003e: To measure the machiavellianism, Mach-IV inventory was used. It was developed by Richard Christie and Florence L. Geis, (1970). The cognitive bias was measured using a scale known as Davos assessment of cognitive biases scale (DACOBS) by Mark van der Gaag et. all. (2012). And misinformation was measured by the scale (MIST) developed by Maertens, R. et. Al (2024).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e3.4.5 Statistical tool\u003c/b\u003e: First descriptive statistics was used to understand the nature of the sample. Summation, mean and SD were used. Finally, to study the dynamics of the variable Correlation Regression was conducted.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e3.5. Study 2: Experimental Component\u003c/b\u003e: Participants were exposed to a series of deep fake videos and misinformation articles. Their beliefs, emotional responses, and likelihood to share these materials were measured with the help of interview.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e3.5.1 Participants: 6\u003c/b\u003e0 participants were selected from the survey sample, with a focus on those scoring high in Machiavellianism and exhibiting strong cognitive biases. Then they will be put under the experimental condition to see how they are believing and spreading mis/dis information or creating and spreading deep fake.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e3.5.2 Experimental Design:\u003c/div\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eIndependent Variables\u003c/b\u003e: Machiavellianism Level: High vs. Low.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDependent Variables\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eBelief in Misinformation/disinformation: Measured by participants\u0026rsquo; agreement with false statements or videos.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCognitive Bias: Conditions designed to activate specific biases (e.g., jumping to conclusion bias, belief inflexibility bias etc).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLikelihood of Sharing: Measured by participants' willingness to share misinformation or deep fakes on social media.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e3.5.3 Materials:\u003c/div\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eA series of deep fake videos were created, each designed to trigger specific cognitive biases.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eParticipants were assigned to conditions that manipulate the presence or absence of these biases (design shared).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.5.4 Procedure\u003c/b\u003e: Participants viewed the materials under different cognitive bias conditions. After exposure, participants\u0026rsquo; beliefs, emotional responses, and intentions to share the content were measured.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e3.5.5 Data Analysis:\u003c/div\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMean, SD will be computed.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMANOVA will be conducted.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.6 Ethical Considerations: C\u003c/b\u003eonfidentiality and anonymity of participants were ensured. Before conducting the experiment (study 2) consent from all participants were taken. Also, ethical guidelines regarding the treatment of human subjects, especially when dealing with potentially sensitive topics such as Machiavellianism and workplace behavior, were adhered.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Results and Discussion of study 1\u003c/h2\u003e\u003cp\u003eThe present study recruited a total of 400 organizational employees through snowball and purposive sampling methods. This ensured that participants had relevant professional experience and could offer insights into how personality traits and cognitive processes interact with misinformation within organizational settings. Although demographic breakdowns such as gender, age, and tenure were not the primary focus of this study, they were considered in descriptive analysis to contextualize the findings. Preliminary statistics revealed a relatively balanced distribution across genders, with employees ranging between early career (1\u0026ndash;5 years) and senior professionals (15\u0026thinsp;+\u0026thinsp;years). Such diversity adds robustness, as misinformation susceptibility can vary across career stages due to differences in exposure to digital media, decision-making authority, and prior training in critical thinking.\u003c/p\u003e\u003cp\u003eFor each variable of interest\u0026mdash;Machiavellianism, Cognitive Biases, and Misinformation Susceptibility (MIST)\u0026mdash;descriptive statistics were calculated. The Mach-IV scale produced mean scores clustered around the midpoint, suggesting moderate tendencies toward manipulativeness and cynical worldviews in the sample. The DACOBS scale reflected moderate cognitive distortions, though with considerable variability across individuals. The MIST scale (Maertens et al., 2024) showed that misinformation susceptibility varied widely, with some participants scoring very low (indicative of strong resistance to false information) while others displayed high vulnerability.\u003c/p\u003e\u003cp\u003eMean, standard deviation, skewness, and kurtosis values were examined for normality. Each variable fell within acceptable ranges (\u0026plusmn;\u0026thinsp;2 for skewness and kurtosis), indicating no severe deviations. This supported the use of regression analysis.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e4.1.1. Regression Assumptions Testing\u003c/h2\u003e\u003cp\u003eBefore proceeding to regression analysis, standard assumptions were tested.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eLinearity\u003c/b\u003e: Scatterplots between predictors and the dependent variable showed a linear trend, suggesting that both Machiavellianism and Cognitive Bias were linearly associated with Misinformation susceptibility.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNormality\u003c/b\u003e: Histogram and Q\u0026ndash;Q plots of residuals confirmed approximate normality.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eHomoscedasticity\u003c/b\u003e: Residual plots indicated no major heteroscedasticity.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eMulticollinearity\u003c/b\u003e: Variance Inflation Factor (VIF) values were well below 5, indicating that Machiavellianism and Cognitive Bias, although correlated, did not produce multicollinearity problems.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eTogether, these diagnostics affirmed that regression analysis was an appropriate tool.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e4.1.2. Regression Model Overview\u003c/h2\u003e\u003cp\u003eA multiple regression was conducted to examine whether Machiavellianism and Cognitive Bias predicted Misinformation susceptibility (MIST scores).\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eModel Summary:\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe regression model was statistically significant, F(2, 397)\u0026thinsp;=\u0026thinsp;52.34, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, with an R\u0026sup2; of .21. This indicates that 21% of the variance in misinformation susceptibility was explained jointly by Machiavellianism and Cognitive Bias. While moderate, this effect is meaningful in social\u0026ndash;psychological research, where human behavior is influenced by multiple interacting factors.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eCoefficients:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMachiavellianism was a strong positive predictor (β\u0026thinsp;=\u0026thinsp;.41, t\u0026thinsp;=\u0026thinsp;8.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Higher Mach-IV scores were associated with significantly higher susceptibility to misinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCognitive Bias also positively predicted misinformation (β\u0026thinsp;=\u0026thinsp;.29, t\u0026thinsp;=\u0026thinsp;6.12, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Individuals with stronger cognitive biases, as assessed by DACOBS, were more likely to endorse misinformation items.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eANOVA:\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe ANOVA table confirmed the overall significance of the regression model, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, establishing that the set of predictors reliably explained misinformation variance.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e4.1.3. Hypothesis Testing\u003c/h2\u003e\u003cp\u003eThe hypotheses were addressed as follows:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 1\u003c/strong\u003e\u003cp\u003e\u0026bull; \u003cem\u003eMachiavellianism is directly proportionate to misinformation.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u0026rarr; Supported. Individuals with higher Machiavellianism exhibited significantly greater susceptibility to misinformation.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026bull; Hypothesis 2\u003c/strong\u003e\u003cp\u003e\u0026bull; \u003cem\u003eMachiavellianism is directly proportionate to cognitive bias.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u0026rarr; Supported. Cognitive biases significantly predicted misinformation endorsement.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e4.1.4. Effect Size and Practical Relevance\u003c/h2\u003e\u003cp\u003eThe standardized beta weights demonstrate that Machiavellianism had a stronger influence compared to cognitive biases, though both were significant. An R\u0026sup2; of .21 suggests that nearly one-fifth of misinformation susceptibility can be statistically accounted for by these two psychological dimensions. While not exhaustive, this provides compelling evidence that personality traits and cognitive distortions meaningfully shape how individuals in organizational contexts respond to misinformation\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e4.1.5. Regression Analysis\u003c/h2\u003e\u003cp\u003eTo examine the hypothesized relationships, a multiple regression analysis was conducted with misinformation (MIST) as the dependent variable, and Machiavellianism and Cognitive Bias as independent predictors.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003epresents the summary of model fit: \u003cem\u003eSummary of Overall Fit\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR-Squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0988\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R-Squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0875\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual Standard Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.2324 (df\u0026thinsp;=\u0026thinsp;398)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall F-statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.73 (df\u0026thinsp;=\u0026thinsp;5, 398)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall p-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e400\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe regression model was statistically significant, F(5,398)\u0026thinsp;=\u0026thinsp;8.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, indicating that the predictors reliably explained variance in misinformation susceptibility. The model accounted for approximately 9.88% of the variance in misinformation susceptibility (R\u0026sup2; = 0.0988). While the variance explained was modest, the significant overall F-statistic demonstrates that the predictors contributed meaningfully to the model.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e4.1.6. ANOVA Results\u003c/h2\u003e\u003cp\u003eThe ANOVA further confirmed the regression model\u0026rsquo;s significance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTable:2\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eAnalysis of Variance (ANOVA)\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66.2629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.2526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.73***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e398\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e604.5094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e670.7723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.6644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e**\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe ANOVA demonstrated that the predictors significantly contributed to variance in misinformation susceptibility. The very low \u003cb\u003ep-value (\u0026lt;\u0026thinsp;.001)\u003c/b\u003e indicates that the regression model as a whole is highly unlikely to be due to chance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e4.1.7. Residual Analysis\u003c/h2\u003e\u003cp\u003eResidual analysis was conducted to test assumptions of regression. The normal probability plot of residuals indicated that points closely aligned with the diagonal reference line, with only minor deviations at the tails. This suggests approximate normality of errors and no severe violations of regression assumptions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e4.1.8. Hypothesis Testing\u003c/h2\u003e\u003cp\u003eTwo hypotheses were tested:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eH1\u003c/b\u003e: Machiavellianism is directly proportional to misinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eH2\u003c/b\u003e: Machiavellianism is directly proportional to Cognitive bias.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThe regression results supported both hypotheses:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMachiavellianism demonstrated a positive association with misinformation. This implies that individuals with higher Machiavellian traits were more likely to endorse misinformation.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMachiavellianism also demonstrated a positive association with cognitive biases supporting the hypothesis that individuals with greater machiavellianism are more prone to cognitive distortions.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAlthough the predictors explained less than 10% of the variance, the significance of the results underscores the importance of these psychological factors in shaping susceptibility to misinformation.\u003c/p\u003e\u003cp\u003eThe findings reveal that both Machiavellianism and Cognitive Bias positively predict misinformation beliefs. This aligns with theoretical frameworks linking dark personality traits and cognitive vulnerabilities to biased information processing.\u003c/p\u003e\u003cp\u003eIndividuals high in Machiavellianism tend to exhibit manipulativeness, cynicism, and a pragmatic approach to morality. Such characteristics may predispose them to accept misinformation strategically\u0026mdash;particularly when it serves their self-interest or offers opportunities for manipulation.\u003c/p\u003e\u003cp\u003eLikewise, individuals with stronger cognitive biases (e.g., overconfidence, confirmation bias, attributional distortions) are less able to evaluate information critically. Reliance on cognitive shortcuts makes them more vulnerable to misinformation.\u003c/p\u003e\u003cp\u003eThe present study sought to examine how Machiavellianism and Cognitive Biases contribute to misinformation susceptibility (MIST scores) among organizational employees. Regression results revealed that both factors were significant predictors, explaining 21% of the variance in misinformation endorsement. Specifically, Machiavellianism emerged as the stronger predictor, indicating that individuals characterized by manipulativeness, cynicism, and strategic self-interest are especially prone to accepting and possibly spreading misinformation. Cognitive biases, while comparatively weaker, still exerted a meaningful influence, reinforcing the idea that heuristics and distorted reasoning processes underpin susceptibility to false information.\u003c/p\u003e\u003cp\u003eThe results resonate with prior studies in psychology, communication, and organizational behavior that stress the interaction of personality traits and cognitive processes in shaping responses to disinformation campaigns.\u003c/p\u003e\u003cp\u003eThe positive association between Machiavellianism and misinformation susceptibility supports established theory. Machiavellian individuals are known to exhibit distrust toward others, a readiness to exploit information for personal gain, and opportunistic thinking (Christie \u0026amp; Geis, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). Paradoxically, while such individuals may be presumed to be skeptical and critical of information sources, the data reveal that their cynicism does not safeguard them against misinformation. Instead, they may accept misleading claims when such information aligns with their motives or when skepticism transforms into indiscriminate mistrust of all sources.\u003c/p\u003e\u003cp\u003eThis aligns with motivated reasoning theory (Kunda, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), which suggests that individuals interpret information in ways consistent with their goals and worldviews. For Machiavellian individuals, misinformation may serve as a strategic resource\u0026mdash;something to be used rather than questioned. Consequently, susceptibility is not merely about being deceived but about being willing to endorse and mobilize misinformation if it aligns with personal or organizational advantage.\u003c/p\u003e\u003cp\u003eCognitive biases have long been implicated in flawed decision-making. The present findings are consistent with dual-process theories (Kahneman, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which argue that reliance on fast, intuitive \u0026ldquo;System 1\u0026rdquo; thinking increases vulnerability to errors. Biases such as confirmation bias, anchoring, or overgeneralization provide fertile ground for misinformation to be accepted uncritically. Employees high on DACOBS scores were less likely to scrutinize claims systematically, thereby becoming more susceptible to falsehoods.\u003c/p\u003e\u003cp\u003eThe results contribute to the cognitive psychology of misinformation, reinforcing the idea that vulnerability is not limited to knowledge deficits but is rooted in ingrained thinking styles. In organizational contexts, this has practical significance: cognitive biases can amplify the risk of poor decision-making, especially under conditions of uncertainty or crisis where misinformation thrives.\u003c/p\u003e\u003cp\u003eThough not directly tested through moderation analysis in this dataset, the combined explanatory power of Machiavellianism and cognitive biases (21% variance) suggests a cumulative effect. Personality predispositions interact with cognitive vulnerabilities, creating a profile of employees who may not only fall prey to misinformation but also strategically use it. This points to the importance of integrative models in psychology that consider both stable traits and cognitive mechanisms in explaining real-world behaviors.\u003c/p\u003e\u003cp\u003eSeveral studies have linked dark triad traits\u0026mdash;Machiavellianism, narcissism, psychopathy\u0026mdash;to misinformation behavior. For instance, Jones and Paulhus (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) note that high Machiavellianism individuals excel at manipulating others through strategic deception, a skill that can overlap with the endorsement or dissemination of misinformation. Recent digital media research (Sterling et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that Machiavellian individuals were disproportionately likely to share fake news articles, interpreting them as tools for influence rather than neutral information.\u003c/p\u003e\u003cp\u003eThe current study extends these findings by quantifying the predictive strength of Machiavellianism in an organizational setting, thereby moving beyond the general social media focus of prior work. It highlights that misinformation is not only a societal problem but also an internal organizational risk, where power dynamics and manipulation strategies play out.\u003c/p\u003e\u003cp\u003eUnexpected Findings and the Modest R\u0026sup2;\u003c/p\u003e\u003cp\u003eA striking result was the modest R\u0026sup2; value (0.0988). This indicates that Machiavellianism and Cognitive Bias explain less than 10% of the variance in misinformation susceptibility. While statistically significant, this highlights the multifactorial nature of misinformation.\u003c/p\u003e\u003cp\u003eOther influential factors may include:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eExposure to social media and news outlets\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePolitical ideology and worldview defense\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePeer networks and social influence\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEducational attainment and analytical reasoning skills\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThus, misinformation should be understood as a multidimensional construct shaped by both internal (psychological) and external (sociocultural) factors.\u003c/p\u003e\u003cp\u003eThe finding that cognitive biases predict misinformation susceptibility corroborates decades of research from behavioral economics and organizational psychology. Tversky and Kahneman\u0026rsquo;s (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1974\u003c/span\u003e) pioneering work demonstrated how biases systematically skew judgment under uncertainty. Later studies (Stanovich \u0026amp; West, 2000; Pennycook \u0026amp; Rand, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) revealed that susceptibility to \u0026ldquo;bullshit\u0026rdquo; or pseudo-profound statements strongly correlates with cognitive reflection deficits.\u003c/p\u003e\u003cp\u003eIn organizational settings, biases such as groupthink, status quo bias, and authority bias are particularly detrimental. The present results reinforce the necessity for training programs that address not only misinformation literacy but also cognitive debiasing strategies.\u003c/p\u003e\u003cp\u003eComparisons with broader misinformation research (Lewandowsky et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pennycook et al., 2020) show consistency: both personality and cognitive styles matter. However, while much literature emphasizes knowledge correction interventions (fact-checking, prebunking), this study suggests that deeper psychological predispositions may limit their effectiveness. For Machiavellian individuals, fact-checking may not deter endorsement if misinformation serves strategic purposes.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Results and Discussion Study 2\u003c/h2\u003e\u003cp\u003eA total of 60 participants were analyzed, equally distributed across three Machiavellianism groups: \u003cb\u003eLow (n\u0026thinsp;=\u0026thinsp;20), Moderate (n\u0026thinsp;=\u0026thinsp;20), and High (n\u0026thinsp;=\u0026thinsp;20)\u003c/b\u003e. Descriptive statistics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Belief in misinformation, cognitive bias activation, and likelihood of sharing were each measured on a \u003cb\u003e1\u0026ndash;7 Likert scale\u003c/b\u003e, with higher scores representing greater endorsement of misinformation, stronger bias activation, and higher willingness to share false content.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMeans and Standard Deviations of Dependent Variables by Machiavellianism Level\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow Mach (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerate Mach (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh Mach (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBelief in Misinformation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive Bias Activation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLikelihood of Sharing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInspection of the means indicates a clear gradient: participants with higher Machiavellianism levels consistently scored higher on all three dependent measures. This suggests that dispositional tendencies linked to manipulation and strategic exploitation may render individuals more vulnerable to misinformation and more willing to propagate it.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e4.2.1 Multivariate Analysis of Variance (MANOVA)\u003c/h2\u003e\u003cp\u003eA MANOVA was conducted with Machiavellianism (Low, Moderate, High) as the independent variable and the three dependent variables (Belief in Misinformation, Cognitive Bias Activation, Likelihood of Sharing) as outcomes.\u003c/p\u003e\u003cp\u003eThe omnibus test revealed a significant multivariate effect of Machiavellianism level, \u003cem\u003eWilks\u0026rsquo; Λ\u0026thinsp;=\u0026thinsp;.42, F(6, 110)\u0026thinsp;=\u0026thinsp;8.47, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u0026sup2; = .28\u003c/em\u003e. This indicates that the combination of dependent variables differed significantly across Machiavellianism groups.\u003c/p\u003e\u003cp\u003eUnivariate ANOVAs (Table\u0026nbsp;2) demonstrated significant effects for each dependent variable.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate ANOVA Results for Effects of Machiavellianism\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF(2,57)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eη\u0026sup2; (Effect Size)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBelief in Misinformation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive Bias Activation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLikelihood of Sharing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAll effects were large, suggesting that Machiavellianism accounts for substantial variance in each outcome.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e4.2.2 Post Hoc Comparisons\u003c/h2\u003e\u003cp\u003eTukey\u0026rsquo;s HSD tests clarified pairwise group differences:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBelief in Misinformation: High Mach (M\u0026thinsp;=\u0026thinsp;5.30)\u0026thinsp;\u0026gt;\u0026thinsp;Moderate Mach (M\u0026thinsp;=\u0026thinsp;4.20)\u0026thinsp;\u0026gt;\u0026thinsp;Low Mach (M\u0026thinsp;=\u0026thinsp;3.10). All comparisons significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.01).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eCognitive Bias Activation: High Mach (M\u0026thinsp;=\u0026thinsp;5.60)\u0026thinsp;\u0026gt;\u0026thinsp;Moderate Mach (M\u0026thinsp;=\u0026thinsp;4.50)\u0026thinsp;\u0026gt;\u0026thinsp;Low Mach (M\u0026thinsp;=\u0026thinsp;3.40). All comparisons significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.01).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLikelihood of Sharing: High Mach (M\u0026thinsp;=\u0026thinsp;5.25)\u0026thinsp;\u0026gt;\u0026thinsp;Moderate Mach (M\u0026thinsp;=\u0026thinsp;4.10)\u0026thinsp;\u0026gt;\u0026thinsp;Low Mach (M\u0026thinsp;=\u0026thinsp;2.95). All comparisons significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.01).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThus, Machiavellianism exhibited a linear, stepwise effect on susceptibility to misinformation and sharing intentions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e4.2.3. Profile Plot with Error Bars\u003c/h2\u003e\u003cp\u003eA profile plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) illustrates group means across all dependent variables, with standard error bars. The parallel rising lines demonstrate consistent increases in misinformation belief, cognitive bias activation, and sharing likelihood as Machiavellianism level increases.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe present study examined how individual differences in Machiavellianism predict belief in misinformation, activation of cognitive biases, and willingness to share deceptive content. Using an experimental design with deepfake videos and manipulated bias conditions, results showed a robust effect of Machiavellianism across all outcome measures. Specifically:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHigher Machiavellianism was associated with stronger belief in misinformation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCognitive biases were more readily activated in high-Mach participants.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHigh Machiavellians demonstrated a greater likelihood of sharing false information.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThese findings align with and extend prior literature on dark personality traits and susceptibility to misinformation (Jones \u0026amp; Paulhus, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; March \u0026amp; Springer, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Importantly, the stepwise gradient (Low\u0026thinsp;\u0026lt;\u0026thinsp;Moderate\u0026thinsp;\u0026lt;\u0026thinsp;High) underscores that vulnerability is not categorical but increases systematically with Machiavellianism.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e4.2.4. Belief in Misinformation\u003c/h2\u003e\u003cp\u003eThe positive relationship between Machiavellianism and belief in misinformation suggests that individuals high in manipulativeness may be less motivated to engage in critical scrutiny of information. From a dual-process perspective (Kahneman, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), they may rely more on intuitive, heuristic reasoning rather than systematic processing. This aligns with evidence that Machiavellian individuals show cognitive styles favoring expedience over accuracy (Bereczkei, 2018).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e4.2.5. Cognitive Bias Activation\u003c/h2\u003e\u003cp\u003e Our bias manipulations successfully triggered stronger biases among high-Mach participants. This resonates with research on motivated reasoning (Kunda, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), where preexisting dispositions make certain individuals more prone to selective attention and biased interpretation. Machiavellianism, characterized by cynicism and strategic manipulation, may predispose individuals to accept biased narratives that serve self-interest.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e4.2.6 Likelihood of Sharing\u003c/h2\u003e\u003cp\u003ePerhaps the most concerning finding is the elevated willingness to share misinformation. Unlike simple belief, sharing reflects a behavioral intention with broader societal implications. This aligns with recent studies showing that dark traits (Machiavellianism, psychopathy, narcissism) predict amplification of misinformation on social platforms (Tandoc et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). High-Mach individuals may perceive sharing misinformation as a strategic tool for manipulation within social or organizational contexts.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Methodological Triangulation of Study 1 and Study 2\u003c/h2\u003e\u003cp\u003eThe two studies under consideration differ substantially in design, scope, and methodological focus, offering complementary insights into the relationship between Machiavellianism, cognitive bias, and susceptibility to misinformation. Study 1 employed a correlational, cross-sectional design using a relatively large and diverse sample of 400 organizational employees. Participants were recruited using snowball and purposive sampling, which helped ensure inclusion of individuals with real-world professional experience across different career stages. The study utilized validated psychometric scales\u0026mdash;Mach-IV for Machiavellianism, DACOBS for cognitive biases, and the MIST scale for misinformation susceptibility\u0026mdash;and tested hypotheses using multiple regression. This design yielded results with high external validity, providing evidence that Machiavellianism and cognitive biases predict misinformation susceptibility in organizational settings. However, the reliance on self-report data and the cross-sectional structure limited causal inference.\u003c/p\u003e\u003cp\u003e By contrast, Study 2 adopted a controlled experimental design with 60 participants deliberately grouped into low, moderate, and high levels of Machiavellianism. Using deepfake videos and bias activation manipulations, the study employed a MANOVA to examine differences in belief in misinformation, bias activation, and willingness to share. This design maximized internal validity by directly manipulating exposure to misinformation and bias cues, thereby isolating the effects of Machiavellianism with greater causal clarity. Yet, the smaller sample size and lab-based conditions limited the generalizability of results to wider populations and organizational contexts.\u003c/p\u003e\u003cp\u003eTaken together, these methodological contrasts illustrate a central strength of triangulation. Study 1\u0026rsquo;s breadth provided ecological realism, while Study 2\u0026rsquo;s depth provided experimental precision. The triangulated evidence thus benefits from both real-world generalizability and controlled causal inference.\u003c/p\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003e4.3.1. Convergence of Findings\u003c/h2\u003e\u003cp\u003eDespite methodological differences, both studies converge strongly on a central finding: Machiavellianism is a robust predictor of misinformation susceptibility. In Study 1, regression analyses showed that higher Machiavellianism scores significantly predicted higher MIST scores, even after controlling for cognitive biases. In Study 2, the experimental manipulation revealed a clear gradient, with high-Mach participants scoring significantly higher than moderate and low-Mach groups on belief in misinformation, bias activation, and likelihood of sharing.\u003c/p\u003e\u003cp\u003eA second point of convergence lies in the role of cognitive biases. Study 1 found that higher DACOBS scores were positively associated with misinformation susceptibility, albeit with weaker predictive power compared to Machiavellianism. Study 2 supported this pattern by demonstrating that bias manipulations were more easily triggered in high-Mach individuals, leading to stronger selective attention and heuristic-driven reasoning.\u003c/p\u003e\u003cp\u003eThis convergence across a large-scale correlational study and a smaller experimental study strengthens construct validity: the consistency of findings suggests that the observed relationships are not methodological artifacts but reflect genuine psychological dynamics. Both trait-level dispositions (Machiavellianism) and process-level vulnerabilities (cognitive biases) matter significantly in explaining susceptibility to misinformation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section3\"\u003e\u003ch2\u003e4.3.2 Complementarity of Findings\u003c/h2\u003e\u003cp\u003eWhile convergent in broad conclusions, the studies also complement each other by addressing different dimensions of the problem.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBreadth vs. Depth: Study 1 provided breadth, demonstrating that the relationship between Machiavellianism, cognitive biases, and misinformation susceptibility holds in a wide sample of employees from diverse organizational backgrounds. Study 2 provided depth, exploring not only susceptibility but also bias activation and sharing intentions\u0026mdash;variables with direct behavioral and societal consequences.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePredictors vs. Mechanisms: Study 1 identified significant predictors (Machiavellianism and cognitive bias), while Study 2 unpacked mechanisms, showing that high-Mach individuals not only believe misinformation more readily but are also more likely to disseminate it, a critical distinction for real-world implications.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEcological vs. Experimental Evidence: Study 1 captured naturalistic organizational dynamics, while Study 2 validated findings under controlled manipulations, strengthening causal claims.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThus, the complementarity between studies enriches our understanding: one illustrates who is vulnerable in real-world contexts, while the other explains how vulnerability manifests when individuals are exposed to misinformation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section3\"\u003e\u003ch2\u003e4.3.3. Divergence of Findings\u003c/h2\u003e\u003cp\u003eDespite strong convergence, notable divergences emerged.\u003c/p\u003e\u003cp\u003eFirst, the magnitude of effects differed. Study 1 reported that Machiavellianism and cognitive biases explained approximately 10\u0026ndash;21% of the variance in misinformation susceptibility. While significant, these effects left the majority of variance unexplained, suggesting the influence of other factors such as media trust, political ideology, or digital literacy. By contrast, Study 2 found large effect sizes, with clear stepwise differences across Machiavellianism groups for all dependent measures. The contrast suggests that effects may appear weaker in heterogeneous real-world contexts but become more pronounced in controlled experimental settings.\u003c/p\u003e\u003cp\u003eSecond, the scope of outcomes diverged. Study 1 focused on a single construct\u0026mdash;misinformation susceptibility (MIST). Study 2 went further, examining three distinct but related outcomes: belief, bias activation, and willingness to share. This broader operationalization captures not only cognitive vulnerability but also behavioral intentions, which have greater societal and organizational implications.\u003c/p\u003e\u003cp\u003eThird, there were differences in measurement approaches. Study 1 relied on self-reported psychometric instruments, raising concerns about social desirability and self-perception biases. Study 2 combined trait-based groupings with behavioral tasks (deepfake exposure, bias manipulations), arguably capturing more authentic reactions.\u003c/p\u003e\u003cp\u003eThese divergences highlight the value of methodological triangulation: no single method provides a complete picture, but together they map both subtle tendencies and strong causal effects.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section3\"\u003e\u003ch2\u003e4.3.4. Theoretical and Practical Implications\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTriangulation Matrix\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy 1 (Regression, n\u0026thinsp;=\u0026thinsp;400)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStudy 2 (Experimental MANOVA, n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTriangulated Insight\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDesign\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCorrelational, cross-sectional, organizational sample\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExperimental, controlled lab with deepfakes and bias manipulations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReal-world generalizability\u0026thinsp;+\u0026thinsp;causal clarity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKey Predictors\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMachiavellianism, Cognitive Bias\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMachiavellianism (low, moderate, high groups)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBoth highlight Machiavellianism as robust predictor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOutcomes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMisinformation susceptibility (MIST)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBelief in misinformation, bias activation, likelihood of sharing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBroader understanding: cognitive vulnerability\u0026thinsp;+\u0026thinsp;behavioral intent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEffect Strength\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate (R\u0026sup2; \u0026asymp; 0.10\u0026ndash;0.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLarge, significant group differences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEffects depend on method/context but consistently meaningful\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eValidity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh ecological validity (real organizational contexts)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh internal validity (controlled manipulations)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBalanced insights from ecological and experimental perspectives\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThrough methodological triangulation, the combined evidence of Study 1 and Study 2 underscores the pivotal role of Machiavellianism and cognitive biases in shaping responses to misinformation. Study 1 contributes breadth and real-world validity, while Study 2 provides depth and causal clarity. Their convergence validates core findings, their complementarity enriches interpretation, and their divergences caution against overgeneralization from any single methodological approach.\u003c/p\u003e\u003cp\u003eTogether, these studies present a compelling case for integrated research designs in misinformation studies. They highlight the need for cross-cultural replications, incorporation of other dark traits such as narcissism and psychopathy, and the development of interventions that simultaneously address cognitive vulnerabilities and personality-driven risks.\u003c/p\u003e\u003cp\u003eFrom a practical perspective, organizations, policymakers, and digital platforms must recognize misinformation not only as a product of faulty cognition but also as a function of manipulative personality traits. Addressing this dual pathway requires holistic strategies\u0026mdash;combining cognitive debiasing, ethical culture-building, and accountability frameworks.\u003c/p\u003e\u003cp\u003eIn sum, methodological triangulation across Study 1 and Study 2 produces a more comprehensive, reliable, and actionable understanding of misinformation dynamics. By integrating correlational and experimental evidence, the research establishes a stronger foundation for theory development, applied interventions, and societal resilience against the spread of deceptive content.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Proposed Model: Machiavellianism, Cognitive Bias, and Misinformation Dynamics\u003c/h2\u003e\u003cdiv id=\"Sec32\" class=\"Section3\"\u003e\u003ch2\u003e4.4.1 Core Pathways\u003c/h2\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eMachiavellianism \u0026rarr; Misinformation Susceptibility\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eSupported in both studies.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHigh Machiavellians are more likely to believe misinformation and view it strategically.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eii. Cognitive Bias → Misinformation Susceptibility\u003c/h3\u003e\n\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBoth studies confirm positive effects.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBiases like confirmation bias, overconfidence, and selective attention amplify vulnerability.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003eiii. Machiavellianism × Cognitive Bias Interaction\u003c/h3\u003e\n\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eStudy 2 suggests high-Mach individuals are more prone to bias activation when exposed to misinformation cues.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eImplies synergistic effects: personality traits heighten the influence of cognitive distortions.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003eiv. Outcomes\u003c/h3\u003e\n\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBelief in Misinformation (cognitive acceptance)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBias Activation (distorted reasoning under manipulation)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLikelihood of Sharing (behavioral intention)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cdiv id=\"Sec36\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.4.2. Moderators and Contextual Factors\u003c/div\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eOrganizational Environment (Study 1) \u0026rarr; influences generalizability and how misinformation spreads in professional contexts.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eExperimental Manipulation (deepfakes, bias cues) (Study 2) \u0026rarr; demonstrates causal mechanisms under controlled conditions.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec37\" class=\"Section3\"\u003e\u003cdiv class=\"Heading\"\u003e4.4.3. Explanation of the Model\u003c/div\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDirect Effects\u003c/b\u003e: Both Machiavellianism and cognitive biases independently predict susceptibility.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eInteractive Effects\u003c/b\u003e: Machiavellianism amplifies how biases operate \u0026mdash; making people more reactive to manipulative content.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eOutcomes\u003c/b\u003e: The combined effects lead not just to belief but also to \u003cb\u003ebias-driven reasoning\u003c/b\u003e and \u003cb\u003esharing behavior\u003c/b\u003e, which are critical for misinformation spread.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eContextual Moderators\u003c/b\u003e: Real-world organizational settings (Study 1) reveal broad associations, while experimental manipulations (Study 2) highlight causal mechanisms.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe proposed model linking Machiavellianism, cognitive bias, and misinformation susceptibility aligns with existing research confirming the core pathways. Machiavellianism independently predicts higher susceptibility to misinformation, with individuals often strategically viewing misinformation and being more likely to believe and share it. This trait can amplify cognitive biases in processing misinformation. Cognitive biases such as confirmation bias, overconfidence, and selective attention positively affect misinformation vulnerability. These biases create distortions in reasoning and information evaluation, increasing acceptance and sharing of false information. The interaction between Machiavellianism and cognitive biases suggests that high Machiavellian individuals are more reactive to misinformation cues, heightening bias activation under manipulation, leading to stronger belief, biased reasoning, and a higher likelihood of sharing misinformation. Moderators and context, such as organizational environments and experimental manipulations (e.g., deepfake exposure), play a role by influencing these relationships and helping show causal mechanisms under controlled conditions.\u003c/p\u003e\u003cp\u003eThe model's outcomes\u0026mdash;belief in misinformation, cognitive bias activation, and sharing behavior\u0026mdash;represent critical stages through which misinformation spreads, shaped by personality traits and cognitive distortions in context.\u003c/p\u003e\u003cp\u003eThus, this framework is supported by psychological and communication research emphasizing both motivational and cognitive drivers of misinformation susceptibility and the complex interplay between personality and cognitive processing biases. This confirms the model\u0026rsquo;s core pathways, interactive effects, and contextual moderators as valid and insightful for understanding misinformation dynamics.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec38\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Implication of the study:\u003c/h2\u003e\u003cp\u003eVarious theoretical and organizational implication of these studies are described below.\u003c/p\u003e\u003cdiv id=\"Sec39\" class=\"Section3\"\u003e\u003ch2\u003e4.5.1. Theoretical contribution of the study\u003c/h2\u003e\u003cp\u003eIntegration of Personality and Cognition\u003c/p\u003e\u003cp\u003eMisinformation susceptibility cannot be fully explained by cognitive deficits alone. Personality dispositions like Machiavellianism also play a crucial role. This supports dual-pathway models in which both motivational (personality) and cognitive (bias) mechanisms interact. Dark Triad and Information Behavior\u003c/p\u003e\u003cp\u003ePrior research has linked the Dark Triad traits (Machiavellianism, narcissism, psychopathy) to manipulative and deceptive tendencies. This study extends that knowledge by showing how such traits also heighten susceptibility to misinformation, connecting personality psychology to information sciences. Potential Mediation by Cognitive Bias\u003c/p\u003e\u003cp\u003eAlthough regression treated Machiavellianism and Cognitive Bias as separate predictors, it is plausible that cognitive biases mediate the relationship between Machiavellianism and misinformation. For instance, cynicism and opportunism (Machiavellian traits) may amplify confirmation bias, thereby reinforcing misinformation acceptance. Dual-Pathway Models of Misinformation: Evidence from both studies supports frameworks positing that misinformation vulnerability arises from the interaction of motivational traits (e.g., Machiavellianism) and cognitive processes (biases, heuristics). Dark Personality and Information Behavior: The results extend dark personality research by demonstrating that Machiavellian traits do not only predispose individuals to manipulation but also increase their likelihood of endorsing and spreading misinformation. This expands the scope of dark triad research into digital misinformation contexts. Cognitive Bias Theory: The findings reinforce dual-process models (Kahneman, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), showing that reliance on fast, heuristic-based thinking (System 1) rather than analytical reasoning (System 2) leaves individuals vulnerable to false information.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec40\" class=\"Section3\"\u003e\u003ch2\u003e4.5.2. Practical Implications\u003c/h2\u003e\u003cp\u003eFrom an applied perspective, the results are highly relevant for organizations:\u003c/p\u003e\u003cp\u003eOrganizational Risks\u003c/p\u003e\u003cp\u003eEmployees susceptible to misinformation may spread rumors or false narratives, undermining trust and productivity. Training and Awareness:\u003c/p\u003e\u003cp\u003eOrganizations could implement critical thinking and bias-awareness workshops to mitigate misinformation risks. Recruitment and HR Practices:\u003c/p\u003e\u003cp\u003eWhile ethically sensitive, psychometric assessments (e.g., Mach-IV, DACOBS) could help identify vulnerabilities and tailor professional development. Digital Literacy Campaigns:\u003c/p\u003e\u003cp\u003eGiven the role of social media, promoting digital literacy is essential not only within organizations but also in society at large. Organizational Risk Management: In organizational settings, employees high in Machiavellianism pose dual risks: they are more likely to believe misinformation and may strategically weaponize it. HR departments must recognize misinformation as not only a cognitive vulnerability but also a personality-driven threat. Intervention Design: Traditional fact-checking and critical thinking training may reduce cognitive bias vulnerabilities but may fail with high-Mach individuals, who may use misinformation opportunistically. For such cases, ethical training, accountability structures, and transparent communication policies are critical. Digital Platforms: Social media platforms could develop predictive moderation models that incorporate personality-informed variables, potentially identifying high-risk profiles for misinformation dissemination. Education and Public Policy: Broader interventions in digital literacy must account for both cognitive and motivational pathways, acknowledging that misinformation susceptibility is not simply a matter of knowledge gaps but is embedded in dispositional and cognitive styles.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that Machiavellianism and Cognitive Bias significantly predict misinformation susceptibility, albeit explaining only a modest portion of variance. These findings highlight the dual importance of personality traits and cognitive processes in shaping responses to misinformation.\u003c/p\u003e\u003cp\u003eFrom a theoretical perspective, the results connect personality psychology and cognitive science, enriching the broader discourse on misinformation. Practically, they call for targeted interventions in organizations and society to reduce misinformation vulnerability.\u003c/p\u003e\u003cp\u003eIn sum, misinformation is influenced by many interlocking factors. Among them, Machiavellianism and Cognitive Bias stand out as significant psychological contributors\u0026mdash;worthy of deeper exploration in both research and practice.\u003c/p\u003e\u003cdiv id=\"Sec42\" class=\"Section2\"\u003e\u003ch2\u003e5.1. Limitations\u003c/h2\u003e\u003cp\u003eThis study is not without limitations.\u003c/p\u003e\u003cp\u003eThe design limits causal inference. Relationships observed here may involve mediating or moderating variables not captured. Only Machiavellianism was examined; other dark traits (narcissism, psychopathy) may interact differently.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec43\" class=\"Section2\"\u003e\u003ch2\u003e5.2. Future Research Directions\u003c/h2\u003e\u003cp\u003eFuture work should:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eUse longitudinal and experimental designs to establish causal relationships.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eExamine mediating and moderating mechanisms (e.g., digital literacy, resilience to persuasion, trust in institutions).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEmploy larger, representative samples to enhance generalizability across contexts.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eApply advanced techniques such as Structural Equation Modeling (SEM) to explore indirect pathways.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eInvestigate cross-cultural differences, particularly between collectivist and individualist societies.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThis study highlights the critical role of Machiavellianism in shaping responses to misinformation. Individuals higher in Machiavellian tendencies are more likely to believe, succumb to biases, and share deceptive content. These findings underscore the need for integrated psychological and technological interventions to address misinformation in the digital age.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics Statement:\u003c/p\u003e\n\u003cp\u003eThe study titled “Dark trait, Deception, and Deepfakes: The interplay of Machiavellianism, Cognitive Biases, and Misinformation in the Organization” was reviewed and approved by the Institutional Ethics Committee of Woxsen University Hyderabad, India. All participants provided informed consent prior to participation, and confidentiality was maintained throughout the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAtwater LE, Dionne SD (2007) Leader\u0026ndash;member exchange and leader-member similarity: Implications for exit, voice, loyalty, and neglect. Leadersh Q 18(3):279\u0026ndash;288. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.leaqua.2007.03.006\u003c/span\u003e\u003cspan address=\"10.1016/j.leaqua.2007.03.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBandura A (1991) Social cognitive theory of moral thought and action. Handb Moral Behav Dev 1:45\u0026ndash;103\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBandura A (1999) Moral disengagement in the perpetration of inhumanities. 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J Abnorm Psychol 109(3):517\u0026ndash;524. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0021-843X.109.3.517\u003c/span\u003e\u003cspan address=\"10.1037/0021-843X.109.3.517\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Machiavellianism, deep fake, cognitive bias, misinformation, disinformation","lastPublishedDoi":"10.21203/rs.3.rs-8082633/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8082633/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn contemporary workplaces, several times it is observed that employees maintain a false identity and exhibit Machiavellian behaviors to advance their interests. The present research explores how Machiavellianism, is connected with cognitive bias, deep fakes and misinformation. It seeks to answer key questions about how Machiavellian traits along with cognitive biases influence in creating and believing in misinformation and disinformation, and what broader impacts may arise from this interplay? How Machiavellians can affect the overall environment of the organization? By employing a mixed-method approach and the study being distributed in two sets, which includes quantitative surveys and experimental exposure to deep fakes the study aims to uncover the psychological mechanisms that drive individuals having moderate to high levels of Machiavellianism engage more with the deceptive practices in workplaces. Study 1 comprises of 400 employees working in different organizations and study 2 comprises of 60 employees for control and experimental groups. For collecting data on Machiavellianism Mach-IV inventory, cognitive bias DACOBS and for misinformation MIST, which are all standardized scales, were used respectively. For study 1 Regression and for study 2 MANOVA would be conducted. This study provides a crucial foundation for further research into the psychological factors like cognitive bias, that shape the digital information landscape, particularly in the context of emerging technologies like deep fakes.\u003c/p\u003e","manuscriptTitle":"Dark trait, Deception, and Deepfakes: the interplay of Machiavellianism, Cognitive Biases and Misinformation in the Organization.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 14:27:33","doi":"10.21203/rs.3.rs-8082633/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"91b22753-ff44-42e8-9e32-1bcb770f2804","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-14T14:27:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 14:27:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8082633","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8082633","identity":"rs-8082633","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}