I’ll have what I had before, but with a cherry on top: leveraging status quo bias when introducing organizational change

The adage above encapsulates the enduring struggle of organizational change, especially amidst today’s volatile business landscape where adaptation is paramount for survival (Alnoor et al., 2020; Godefroid et al., 2023; Kotter et al., 2021; Mulholland, 2023). When considering a business’s ability to adapt, we need to also consider employee resistance – often displayed through inaction, dismissal, or even outright defiance, and a formidable obstacle to change effort success (Cameron and Green, 2020; Guidetti et al., 2018).

Current research on organizational change management underscores a persistent relationship between change initiatives and employee resistance, where cognitive factors like status quo bias play a significant role. Traditional models, such as Kotter’s eight-step change model, assume that employee resistance stems initially and largely from a lack of urgency or vision (1995), leading change practitioners to approach resistance by framing the current state as unfavorable (Appelbaum et al., 2012). However, studies indicate that such framing can clash with an inherent preference for stability, as evidenced by cognitive theories like status quo bias (Samuelson and Zeckhauser, 1988), which suggest individuals are inclined to resist disruptions to the familiar. Behavioral economics and decision-making research (Jost et al., 2004) further highlight that this preference for the status quo may be more than just a passive reluctance but an active cognitive mechanism that influences decision-making.

The failure rate of change initiatives, estimated to be as high as 90% (Burnes, 2011; King et al., 2018a), underscores the persistent challenge of overcoming resistance. While existing literature extensively documents the prevalence of employee resistance to change (Khaw et al., 2023), it often overlooks the underlying cognitive mechanisms, particularly the role of biases such as status quo bias – the inherent human tendency to favor the current state of affairs (Samuelson and Zeckhauser, 1988). In fact, a review of current literature into the relationship between effective change management and employee resistance to change, specifically in relation to status quo bias, suggests that we have a deep-seated tendency to defend the status quo, although there is little empirical research to support this notion (Jost et al., 2004).

Importantly, Samuelson and Zeckhauser’s (1988) introduction of status quo bias and Jost et al.’s (2004) system justification theory have laid foundational theoretical groundwork for understanding the cognitive mechanisms underlying resistance to organizational change, yet these insights have been largely overlooked in mainstream change management literature, such as Kotter’s (1995, 1996, 2007) model. Our study not only bridges this gap but also expands the application of these theories beyond their traditional contexts, illustrating their relevance across a broader range of organizational change management scenarios. Martin (2017) stresses that companies can proactively influence recipient response to communications by utilizing choice architecture – deliberately nudging sensemaking in a desired direction. His contribution appears unique in broadening the scope of organizational change management research to include behavioral economics application away from solely technology system implementation efforts. Building on this, our study aims to further explore and potentially advance this integration, applying it to a wider range of organizational change scenarios and collecting much-needed empirical data as urged by Beaudry et al. (2020), Kim and Kankanhalli (2009), Klein et al. (2022), Polites and Karahanna (2012), and Shirish and Batuekueno (2021).

Application opportunity therefore exists, but also an important contradiction that needs to be addressed – that is, our tendency is to purportedly favor the current state (Samuelson and Zeckhauser, 1988), and the fact that organizational change management is commonly defined as the deliberate process of transitioning an organization from its current state to a desired future state (Stouten et al., 2018), often necessitating alterations to existing employee work practices / alterations to the status quo (Kotter et al., 2021; Malek and Yazdanifard, 2012).

This research seeks to address this void by directly examining how status quo bias interacts with employee resistance to change. By providing actionable insights, we aim to equip change practitioners with innovative communication strategies that can proactively mitigate employee resistance and significantly improve the success rate of change initiatives. This study has the potential to not only advance our theoretical understanding of employee change resistance but also to revolutionize change management practices, leading to more effective and less disruptive organizational change efforts.

Many popular change management models, notably Kotter’s eight-step change model, advocate for creating a sense of urgency by vilifying the status quo (Appelbaum et al., 2012; Kotter, 1995, 1996, 2007). This approach, representative of the “received view” that has become a type of paradigmatic orthodoxy in change management, clashes with the deep-seated human preference for stability and familiarity, as evidenced by status quo bias and system justification theory – where our first instinct is to defend (Jost et al., 2004).

Given that change communications are considered a central mechanism for influencing employee response and is decisive in terms of shaping change management effort success, adhering to the received view and vilifying the status quo instead of leveraging it appears particularly problematic. Therefore, such strategies may inadvertently trigger resistance, exacerbating the very problem they aim to solve.

With the seemingly widespread use of change management models failing to stem the tide of organizational change failure (Schouten et al., 2022), it is imperative to explore new avenues for understanding and addressing employee resistance. Looking outside of change management theoretical orthodoxy to a discipline like behavioral economics, which offers rich insights into human decision-making and cognitive biases, may provide a fruitful way to break this impasse.

This research proposes a paradigm shift in organizational change management grounded in behavioral economics. Instead of fighting against status quo bias, we explore whether it could be used as a lever. Testing an argument presented in a recent conceptual paper by members of this research team (McLaren et al., 2023), we gather data to assess how framing change management initiatives in a way that emphasizes continuity, minimizes perceived losses, and fosters approach motivation, may impact employee acceptance.

Through an experimental study, we empirically investigate the influence of status quo bias on employee resistance to organizational change. By providing evidence-based recommendations, we aim to equip change practitioners with innovative communication strategies that proactively address employee resistance and have the potential to significantly improve the success rate of organizational change initiatives.

Adaptation is essential for organizational survival in today’s dynamic landscape (DuFrene and Lehman, 2014). However, most organizations are inherently designed for stability rather than rapid adaptation (Kotter et al., 2021; Malek and Yazdanifard, 2012). Despite the prevalence of change management models developed to address this challenge, few are grounded in rigorous scientific evidence (Stouten et al., 2018). John Kotter, often hailed as a “master of change management”, has profoundly shaped the field with his influential eight-step change model (Kotter et al., 2021). His best-selling books, translated into 26 languages, have not only underpinned his multi-million dollar company but also inspired popular frameworks like the Prosci model. Jeff Hiatt (2006), the founder of Prosci, credits Kotter’s contribution as a source of inspiration, and today Prosci is purportedly used by 80% of Fortune 500 companies (McAllister, 2024). Kotter’s legacy is undeniable; he stands as a central figure in organizational change management as it exists today. However, Kotter’s model suffers from significant limitations, including a lack of empirical grounding and failure to cite supporting evidence (Appelbaum et al., 2012). This absence of scholarly rigor has led some to categorize Kotter’s work, and similar models lacking validation, as “pop management” (Cummings et al. (2016). This has created a critical research gap: this widespread acceptance and implementation of such models without adequate scientific scrutiny underscores the urgency and relevance of further investigation, empirical testing, and advancement within the field of organizational change management.

A primary focus of change management models is to reduce employee resistance, which is frequently cited as a key reason for organizational change effort failure (Grønvad et al., 2023; Stouten et al., 2018). Rivard and Lapointe’s (2012) review of 89 published case studies further underscores this point by emphasizing the critical importance of overcoming employee change resistance to achieve change initiative success. Resistance can manifest in several ways, including failing to follow prescribed procedures, refusing to listen or help, neglecting to address known problems, and displaying adversarial or condescending attitudes (McKay et al., 2012). Yet, despite extensive documentation of these manifestations, the deeper cognitive processes underlying resistance (like status quo bias) remain largely underexplored.

To effectively mitigate resistance, it is essential to understand its origins. Behavioral economics, the study of human decision-making and factors that influence choice, offers valuable insights into this issue (Angner, 2020). Regardless of potential benefit, change often evokes feelings of insecurity, uncertainty, and anxiety (DuFrene and Lehman, 2014). These feelings, stemming from ambiguity and perceived risk, can present as resistance (Cameron and Green, 2020; Guidetti et al., 2018). Piderit (2000) argues that resistance is multidimensional, often encompassing both support and opposition simultaneously – a complexity that status quo bias further intensifies. Yet, while behavioral economics highlights the impact of cognitive biases such as status quo bias, current change management models, including Kotter’s, largely overlook these insights. Jost et al. (2004) further supports the notion that individuals have a deep-seated tendency to defend the status quo, which is often overlooked in organizational change management strategies. Given the pivotal role that employee resistance plays in the success or failure of change initiatives, exploring how cognitive biases like status quo bias can be leveraged rather than combated is not only theoretically significant but also highly relevant for practitioners facing the realities of organizational change. As employee reactions are largely dependent on how change is presented (Khaw et al., 2023), carefully crafted and strategically deployed communications should be of paramount consideration for change practitioners.

Change communications play a pivotal role in shaping recipient sensemaking (Schulz-Knappe et al., 2019; Shulga, 2021), influencing perceptions and guiding behavior (Endrejat et al. (2021). However, the interaction between communication strategies and cognitive biases, particularly status quo bias, appears largely underexplored in the literature. This represents a significant research opportunity, as effective communication is a crucial change mechanism, empowering change practitioners to facilitate successful organizational transformations (Malek and Yazdanifard, 2012; Simoes and Esposito, 2014). Hodgkinson and Healey (2018) highlight how psychological inertia can hinder the development of dynamic capabilities within organizations, with inertia being a factor that is closely related to status quo bias.

Harikkala-Laihinen (2022) conducted a qualitative study with employees (N = 1,763, response rate ≈ 65%) from two large European companies that had merged a few years prior. Grounded in affective events theory (where emotions and moods are linked to job performance and satisfaction), the findings demonstrated that strategically designed and delivered communications influenced employee interpretations of the change. Specifically, clear communication fostered reduced inertia by enhancing understanding, dispelling rumors, alleviating concerns, and improving motivation and commitment, ultimately contributing to a positive change climate. In essence, these communications facilitated led employee sensemaking.

Effective communication is intrinsically linked to the success or failure of change initiatives (DuFrene and Lehman, 2014). Consequently, organizational leaders and change practitioners should adopt a proactive approach, preemptively shaping the change narrative rather than merely reacting to it (Khaw et al., 2023). This implies that employee sensemaking can be strategically influenced through thoughtfully constructed and disseminated communications. Such communications can therefore mitigate uncertainty and ambiguity, thereby fostering a smoother change process and reducing potential resistance. However, common change management advice like “communicate effectively” provides little practical value (Elving, 2005; Johansson and Heide, 2008). Beaudry et al. (2020) reinforce this view further when they comment that existing communications research in this space can be considered largely high-level and at “face value” only. Furthermore, Prosci’s (Creasey, 2024) warning that organizational leaders and change practitioners need to repeat a change message five to seven times to get it to stick, means little if that message is not actually shaping recipient sensemaking in a way that is beneficial to the change effort. Given the reported high failure rates of organizational change efforts, understanding and leveraging cognitive biases like status quo bias in communication strategies is not only timely but also essential for improving the outcomes of change initiatives.

Kim and Kankanhalli (2009) advised that despite the well-documented and stressed importance of managing employee resistance, few studies have suggested theoretical explanations. This study aims to provide theoretical insights by empirically investigating if status quo bias can be strategically leveraged in change communications to enhance acceptance and reduce resistance, as well as potentially providing some understanding into what “communicate effectively” might actually mean.

A compelling vision – a vivid picture that taps into hearts and minds, can inspire change by mobilizing individuals towards a shared goal (Kotter et al., 2021). Such a vision should be a clear and emotionally resonant narrative, aligning employees with a future desired future (Appelbaum et al., 2012). Since his seminal work in 1995, Kotter has consistently emphasized the importance of creating a strong vision, a concept embedded in four of the eight steps in his change model. Moreover, Kotter advocates for establishing the current state (the status quo) as more precarious than the uncertainty of the desired future state (Maguire and Albright, 2005; Stankey et al., 2003). He underscores the necessity of a compelling vision to disrupt the status quo, highlighting the need to challenge and dismantle it, even through the use of a “burning platform” analogy (Appelbaum et al., 2012). Kotter (2008) asserts that such urgency can catalyze action, even among those content with the status quo. He further suggests that organizational leaders and change practitioners should be empowered to disrupt the status quo through bold, even risky, actions (Appelbaum et al., 2012). This perspective is echoed by, Fernandez and Rainey (2006) who advocate for highlighting dissatisfaction with the current state to facilitate change. Hiatt (2006) reinforces this notion, stressing the importance of emphasizing the risks of not changing, even suggesting the need to “shock” employees into recognizing the necessity of change.

However, this prevailing (burning platform) view in organizational change management lacks, as discussed, theoretical backing and is challenged by empirical insights from behavioral economics and decision-making research. Standard economic theory proposes that all decision-making rests on highest utility of return calculations, but that kind of rational thinking is not always the case because a lack of information, emotive reaction, or time pressures etc. can get in the way (Prentice and Koehler, 2003). Psychologically, losses are felt more acutely than gains, which in turn exerts a powerful influence on decision-making (Geiger, 2017). Individuals exhibit a preference for the status quo because it is reliable, and experienced (Thaler and Sunstein, 2009). Positioning the current state as dangerous is a combative and futile strategy as the inherent loss within that approach will elevate employee anxiety and stress given the inescapable nature of status quo bias (McLaren et al., 2023).

Geng (2016) credits Samuelson and Zeckhauser as having coined the term “status quo bias”, explaining it as the powerful tendency of decision-makers to favor the current state of affairs. Status quo bias, described by Mulholland (2023) as “mighty,” reflects the inherent human preference for the familiar and predictable. Human decision-making operates in two ways (dual process): on an automatic intuitive system that is fast and subconscious, and a more considered deliberate system that is slow and with reflection (Monteiro et al., 2020). Automatic processing, often driven by heuristics or mental shortcuts (Mlodinow, 2012), serves as our default mode, prioritizing efficiency over deliberation (Martin (2017). Consequently, first impressions (like what is expressed when launching a change effort) exert a disproportionate influence on our choices and are difficult to alter (Knight, 2016). As Heath and Heath (2013) advise, when it comes to the psychology of decision-making, we predominately “run on autopilot” – that is, automatic processing.

On behavioral economics and decision-making research, Polites and Karahanna’s (2012) conducted a two-part study that involved a survey and simulation exercise with students (N = 334). The findings revealed that habit, perceived switching costs, and sunk cost commitments resulted in demonstratable inertia – a preference for maintaining the status quo. Notably, Polites and Karahanna found that individuals consistently favored the status quo, even over “promised” superior alternatives. This is an important point to consider when crafting a change vision (led employee sensemaking), and repeating a change message. A preference exists for the known and reliable over the uncertain and not yet realized future benefits. As their article title aptly captures, individuals can be “Shackled to the status quo …” (Polites and Karahanna, 2012, p. 21) even when changing may be advantageous. A compelling vision that is meant to tap into hearts and minds by disrupting the status quo, could actually tap into fear and inaction.

Despite these insights, mainstream change management frameworks continue to prioritize approaches that seek to dismantle the status quo without fully addressing the cognitive mechanisms that make it appealing to employees. The literature, including foundational work on system justification and status quo bias (Jost et al., 2004; Samuelson and Zeckhauser, 1988), offers theoretical underpinnings that suggest resistance might be less about opposition to change and more about an ingrained cognitive preference for the familiar. However, an explicit research gap remains: existing studies largely overlook how change management can benefit from aligning with these biases rather than opposing them. This study addresses this gap by empirically testing whether framing change as aligned with the status quo may mitigate resistance and improve acceptance, an approach scarcely explored in empirical research.

In essence, moving away from the status quo incurs loss. The preference for stability is rational – humans crave stability; the expectation of stability is fundamental to our sense of security (Eidelman and Crandall, 2012). Stakeholders subjectively assess the costs of transition, highlighting the crucial role of perception in organizational change acceptance (Khaw et al., 2023). This underscores the importance of strategic communications to guide and influence employees through organization change.

The prevailing organizational change management logic, as illustrated by Kotter’s model, suggests that portraying the status quo negatively is crucial for fostering employee engagement in the change process. However, this approach contradicts decades of decision-making research demonstrating a strong human preference for the status quo (Evans and Evans, 2019). Given the widespread application of Kotter’s model and its influence on organizational change management practices, exploring alternative approaches that align with how people naturally think and make decisions is critically important. This discrepancy highlights a significant research gap: if employees are inherently inclined to maintain the current state, would it not be more effective to leverage this tendency rather than actively combat it? This study bridges the gap by applying behavioral economics insights to organizational change management, specifically examining whether framing change as a continuity of the status quo can reduce resistance. By shifting from traditional disruption-focused narratives to alignment-based communications, this research offers both theoretical advancements and practical implications for managing change in ways that resonate with employees’ cognitive preferences.

Despite this apparent disconnect, little research has explored the intersection of organizational change management and behavioral economics, particularly concerning the role of cognitive biases in change communications. Martin (2017) made a significant stride in this area, highlighting how framing change initiatives can drastically improve adoption rates and noting the potential barriers posed by cognitive biases, including status quo bias. However, a gap remains in empirically examining how behavioral economics insights, particularly regarding status quo bias, can inform and enhance change management practices. Oreg (2018) found that resistance to change is significantly influenced by personality traits, which can interact with cognitive biases like status quo bias, creating additional layers of resistance.

As Fernandez and Rainey (2006) observed nearly 2 decades ago, organizational change management is often ineffective; a premise that seems to still persist according to Burnes (2011) and King et al. (2018). Could this ineffectiveness be attributed, at least in part, to a failure to account for the inherent human preference for the status quo? This research is particularly relevant because it aims to address these longstanding inefficiencies by investigating an approach to change communications that could lead to higher rates of change acceptance. This empirical study seeks to address this by answering the following Research Question (RQ):

To address this RQ, an experiment was conducted to test the following hypothesis (H):

The vignettes, carefully crafted to mirror real-world decision-making scenarios, systematically explored the influence of status quo bias within common organizational change contexts (for example – process changes, office layouts, relocations). Our design, particularly the use of closed-ended responses, aligns with established research methodologies for capturing cognitive biases (Aguinis and Bradley, 2014; Tversky and Kahneman, 1981).

Vignette 1 (V1)

Vignette 2 (V2)

Vignette 3-A (V3-A)

Vignette 3-B (V3-B)

Vignette 3-C (V3-C)

Vignette 3-D (V3-D)

To capture participants’ fast, intuitive response, a 90-s time limit was applied to each question. This aimed to tap into subconscious decision-making, as described by Knight (2016), Mlodinow (2012), and Monteiro et al. (2020). The time limit, determined through pre-testing, ensured participants could not deliberate extensively (as per normal heuristic practice when digesting a piece of information), preventing a switch to slower, conscious reasoning. If unanswered within 90-s, the survey progressed automatically.

A content validity analysis was conducted to assess the vignettes’ appropriateness and identify necessary amendments. Nine experts, adhering to recommendations by Yassir et al. (2017), Almanasreh et al. (2019), and Polit et al. (2007), were recruited based on their postgraduate qualifications in relevant fields and experience with survey design and/or assessment. These experts, external to the researchers’ direct working environment, voluntarily participated without compensation. Their demographic details are summarized in Table 1.

Experts were first provided with a definition of status quo bias and the three abovementioned vignettes (V1, V2, V3-A to V3-D) with accompanying response options. They were asked to evaluate if the questions accurately measured status quo bias (relevance) and if participants would be aware of the bias being tested (sensitivity). An optional free text box was provided for additional suggestions on improving the questions.

Content validity was evaluated using a Content Validity Index (CVI) which includes Item-level CVI (I-CVI) and Scale-level CVI average (S-CVI/Ave). Probability of chance occurrence between experts (Pc) was calculated, and a modified kappa statistic (k*) applied to enhance analysis by accounting for chance agreement among experts. This approach provides a more robust assessment than the minimum recommendation. The k* scores were interpreted using Polit et al.’s (2007) thresholds: 0.40 to 0.59 (Fair), 0.60 to 0.74 (Good), and 0.75 to 1.0 (Excellent).

The k* score, encompassing both CVI and Pc, was used to determine whether individual survey items should be retained, revised, or rejected, following the recommendations of Almanasreh et al. (2019).

Experts evaluated each question’s relevance (allocating 1 if it tested status quo bias, or 0 if it did not) and sensitivity (allocating 1 if participants would not realize that status quo bias was being tested or if they may realize but it still would not affect their response, or 0 if awareness would compromise the test). All experts completed the evaluation, and all three received Excellent scores on both criteria, indicating their appropriateness for use in the study. The consistent expert agreement and successful test/retest performance suggest preliminary evidence of reliability.

Following content validation, the three vignettes were incorporated into a survey to answer the RQ.

Eligibility criteria for participation included being 18 years or older, having held a full-time position for at least six months, and having direct experience as a recipient of organizational change (therefore excluding Chief Executive Officers or owner-operators).

Participants primarily represented three countries – Australia, the United Kingdom, and the United States (with “Other” contributions from Singapore N = 3, Germany N = 1, Japan N = 1, New Zealand N = 1, Thailand N = 1, and country not provided N = 2), represented a broad age range, worked in companies sized small and large, held varied levels of seniority with their organizational, and were largely tertiary qualified. Table 2 summarizes basic survey participant information.

This study adhered to the principles outlined in the researcher’s National Statement on Ethical Conduct in Human Research (2018). Prior to participant recruitment, the survey protocol received ethical approval from the host institution’s Human Research Ethics Committee (HREC) – granted 2 November 2020, with HREC reference identification number H19REA313.

The survey was deployed online for a period of three months – from start November 2021 to end January 2022. Participant recruitment employed a combined approach of direct invitation and snowball sampling. The survey link was initially disseminated to select contacts within the research team’s professional network, who were asked to forward the link (with research names deidentified) exclusively to individuals fulfilling the predetermined eligibility criteria. Upon completing the survey, participants were subsequently encouraged to share the link with other potentially eligible individuals, thereby facilitating an organic expansion of the participant pool. This multi-tiered distribution strategy ensured an arm’s length recruitment process, mitigating potential biases arising from direct researcher solicitation.

A binomial test was chosen as the primary analytic method due to the binary nature of the data (forced choice between two alternatives: one representing more the status quo, and the other, change – a more varied future state) (Abdi, 2007; Cohen, 1988; Rea and Parker, 2016). This test allowed us to assess whether participants demonstrated a significant preference for either option, with a null hypothesis of no preference (equal probability of choosing either option).

In alignment with the theoretical assumption of the pervasiveness of status quo bias and the hypothesis challenging conventional organizational change management assumptions, selecting the status quo option (option 1) was coded as a “success” in the binomial test, while choosing the alternative (change) option was coded as a “failure”. Only complete responses – from those who progressed to the end of the survey (up to N = 222), were included in the analysis. Statistical significance was evaluated at the alpha level (α) of 0.05, and a 95% confidence interval (CI) was calculated to estimate the true proportion of individuals preferring the status quo option, with the probability of random chance shown through the presented p value (p) (Lee, 2016).

A CI containing 0.50 would indicate that the observed preference could be attributed to random chance, suggesting no significant preference for either option. Conversely, a CI falling entirely below 0.50 would indicate a significant preference for the change option, aligning with Kotter’s (1995) theory. A CI entirely above 0.50 would signal a significant preference for the status quo, demonstrating a status quo bias.

To quantify the strength of this preference, Cohen’s h, a measure of effect size for comparing proportions, was calculated (Cohen, 1988). Cohen’s h values between 0.00 and 0.20 represent a negligible effect, 0.20 to 0.50 a small effect, 0.50 to 0.80 a medium effect, and values above 0.80 a large effect. Values exceeding 1.20 can be interpreted as a very large effect.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 217 trials, with 157 observed selections of the status quo option (72.4%). The binomial test revealed a significantly higher proportion of status quo selections than the null hypothesis of 0.50 (N = 217, p < 0.001). The 95% CI for the probability of selecting the status quo option ranged from 0.67 to 1.00, with an estimated probability of 0.72. Cohen’s h = 0.46, indicating a medium effect size.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 219 trials, with 97 observed selections of the status quo option (44.3%). The binomial test revealed a proportion of status quo selections that was not significantly different from the null hypothesis of 0.50 (N = 219, p = 0.105). The 95% CI for the probability of selecting the status quo option ranged from 0.38 to 0.51, with an estimated probability of 0.44. Cohen’s h = −0.11, indicating a negligible effect size.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 219 trials, with 108 observed selections of the status quo option (49.3%). The binomial test did not reveal a significant difference in the proportion of status quo selections compared to the null hypothesis of 0.50 (N = 219, p = 0.610). The 95% CI for the probability of selecting the status quo option ranged from 0.44 to 1.00, with an estimated probability of 0.49. Cohen’s h = −0.01, indicating a negligible effect.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 220 trials, with 123 observed selections of the status quo option (55.9%). The binomial test revealed a significantly higher proportion of status quo selections than the null hypothesis of 0.50 (N = 220, p = 0.046). The 95% CI for the probability of selecting the status quo option ranged from 0.50 to 1.00, with an estimated probability of 0.56. Cohen’s h = 0.12, indicating a small effect size.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 219 trials, with 212 observed selections of the status quo option (96.8%). The binomial test revealed a significantly higher proportion of status quo selections than the null hypothesis of 0.50 (N = 219, p < 0.001). The 95% CI for the probability of selecting the status quo option ranged from 0.94 to 1.00, with an estimated probability of 0.97. Cohen’s h = 1.21, indicating a very large effect size.

An exact binomial test was conducted to determine if the proportion of individuals choosing the status quo option was significantly different from 0.50. The analysis included 222 trials, with 171 observed selections of the status quo option (77%). The binomial test revealed a significantly higher proportion of status quo selections than the null hypothesis of 0.50 (N = 222, p < 0.001). The 95% CI for the probability of selecting the status quo option ranged from 0.72 to 1.00, with an estimated probability of 0.77. Cohen’s h = 0.57, indicating a medium to large effect size.

This study questions aspects of the traditional organizational change management approach, such as the tendency to vilify the status quo, and offers an alternative strategy grounded in behavioral economics. By empirically testing how leveraging status quo bias can mitigate resistance, we address a key research gap and provide practical tools for change practitioners. This research offers a deeper understanding of the cognitive factors driving employee resistance and equips organizational leaders and change practitioners with increased understanding to better prepare and navigate change efforts more effectively.

Our hypothesis predicted that, contrary to Kotter’s model, individuals presented with a binary choice between change and the status quo would still exhibit a preference for maintaining the status quo due to the influence of status quo bias. The results largely supported this hypothesis, with most conditions showing a significant preference for the status quo. Although a few conditions did not reach statistical significance, the overall pattern of results indicates a robust presence of status quo bias, reinforcing the idea that even positively framed changes struggle to overcome this inherent preference.

Given the partial support for the hypothesis when analyzing individual scenarios, a post-hoc analysis was conducted to assess the overall evidence for a preference for change across all scenarios combined. The binomial exact test revealed a significant preference for the status quo option (868 out of 1,316 participants, p < 0.001). The estimated probability of choosing the status quo was 0.66, 95% CI [0.63, 0.69]. Cohen’s h was 0.33, indicating a moderate effect size. Therefore, while subtle differences existed between scenarios, the overall pattern of results strongly supports the status quo bias as a dominant, though not exclusive, factor influencing participant choice.

Participants presented with V1 overwhelmingly favored the status quo (72.4%), contradicting traditional change management logic that emphasizes the power of a compelling vision to drive change adoption. This finding highlights a strong preference for the familiar, even when faced with a well-articulated alternative. The moderate effect size (Cohen’s h = 0.46) further emphasizes the strength of this preference.

In contrast to expectations, participants showed no significant preference between the status quo and the proposed change in V2. This challenges established change management practices and suggests a degree of hesitation or ambivalence towards change, even when presented favorably.

The varied responses to V3 highlight the complex interplay between status quo bias and change acceptance. While V3-A showed no significant preference, V3-B, V3-C, and V3-D collectively demonstrate a clear trend favoring the status quo, ranging from a small effect in V3-B to a very large effect in V3-C. These findings suggest that a compelling vision alone may not always be sufficient to overcome status quo bias, as championed by Kotter (1995), and highlights the influence of contextual factors on decision-making during organizational change. These findings emphasize the need to tailor organizational change management strategies to the specific context and individual preferences, as illustrated in Figure 1.

To date, research into organizational change management and behavioral economics have run primarily on parallel streams, rarely converging, and when doing so, usually focused on user resistance factors as they apply to new software system implementation (Beaudry et al., 2020; Kim and Kankanhalli, 2009; Klein et al., 2022; Polites and Karahanna, 2012; Shirish and Batuekueno, 2021). However, the integration of behavioral economics insights, particularly those related to cognitive biases like status quo bias, offers a promising avenue to enhance the effectiveness of change management strategies.

Godefroid et al. (2023) stated that individuals prefer to avoid the new – a position that is supported by the data we collected. This finding aligns with behavioral economics research, particularly the work of Geiger (2017), which highlights loss aversion as a key factor driving the preference for the familiar and predictable. Rather than simply observing and reporting that employee resistance exists, this research effort (through presenting mandatory and contradictory fixed response options) sought to uncover reasons as to what may trigger employee resistance, why that may be the case, and what to say or not say in change communications. Choosing one option over another gives an immediate point of difference that can be used for comparison. Our research, particularly in V1, appears consistent with Polites and Karahanna’s (2012) findings on perceived switching costs and inertia, and expands on previous work by Beaudry and Pinsonneault (2005), Klein et al. (2022), and Shirish and Batuekueno (2021) regarding the role of uncertainty and perceived loss in organizational change resistance. Specifically, we demonstrate that framing change as “very closely mirroring” the status quo is more effective in garnering acceptance than emphasizing significant differences. This finding implies that minimizing perceived transition costs and highlighting continuity may help mitigate resistance. Similarly, with V3 – that using wording like “is almost identical”, “very similar”, and “as you do at the moment” is better received than “is totally different”, “completely different”, and not per the “current arrangement”. This finding underscores the importance of leveraging status quo bias, as described by Samuelson and Zeckhauser (1988), in designing change communications. Risk is reduced when the familiar is promoted. Martin (2017) stresses that companies can proactively design choice architecture to influence recipient response; the aforementioned provides an example of exactly that, in practice. Our findings also extend Martin’s (2017) work by illustrating how cognitive biases can be strategically harnessed rather than merely avoided. Flipping Martin’s (2017) advice that cognitive bias can be a barrier to change effort success, this study explores not how to avoid that barrier, but how a change practitioner can potentially use cognitive bias to their advantage. Careful semantic analysis and commentary delves further than simple face value statements, specifically acting on Beaudry et al. (2020) earlier referenced critique and advice.

Another related contradiction was discovered as part of this research effort. It takes time, effort, and reflection to truly calculate and confirm highest utility of return (Godefroid et al., 2023). However, if the majority of the decisions that humans make are automatic (Pereira, 2019), then appealing to anything other than a cognitive bias is somewhat redundant. This notion is further supported by Monteiro et al. (2020), who emphasize that automatic processing, driven by heuristics or mental shortcuts, dominates our decision-making processes. This is perhaps another reason why the status quo is so powerful, as promoted by Godefroid et al. (2023), and as evidenced in the results outlined above – that is, painting and selling a compelling vision, as Kotter et al. (2021) espouses, is the painting and selling of an end game outcome. That end game outcome requires considered, slow, and reflective thought; a place where we rarely go. End game outcome is not immediate, not in the now, and not how we function day-to-day if dual process decision-making is to be believed, remembering that automatic processing can only come first (Monteiro et al., 2020).

Notably, and unexpectedly, the results (illuminated particularly by responses to V3-C and V3-D) provide an intriguing insight; it can be surmised that employees would prefer what they already have over something new (regardless of how bright and shiny that “new” is), however, add a small feature that provides a “reason to change”, and employee support is super-charged. This finding is consistent with the theory of loss aversion (Geiger, 2017) and suggests a practical application for Polites and Karahanna’s (2012) insights on perceived switching costs and inertia. This finding is also supported by, and provides a potential reason for, the negligible statistical results associated with V2 – that is, the change option was so insignificant that it may not have provided a strong reason to change nor align strongly with the status quo. An accidental “hedging of your bets bias” – sitting in the middle, as explained by Grant and Xie (2007), may have indiscriminately prevailed. So, while the status quo reigns, there is a caveat. This has implications for Geiger (2017), Godefroid et al. (2023), Martin (2017), and anyone else expanding knowledge in the field of status quo bias, as it highlights the importance of carefully considering how cognitive biases are leveraged in organizational change management.

This study provides organizational leaders and change practitioners with actionable strategies that challenge the conventional burning platform approach, advocating for a strategy grounded in leveraging the inherent human preference for familiarity. These insights are directly applicable to the practice of managing organizational change.

Organizational change communications should focus on continuity and incremental improvement rather than emphasizing stark differences. By framing changes as enhancements or evolutions rather than radical overhauls, practitioners can reduce employee, shock, anxiety, and resistance. For instance, emphasizing that a new system “very closely mirrors” the existing one can make the change feel less threatening, fostering smoother acceptance.

The power of familiarity should be central in organizational change communications strategy. Language that underscores what remains consistent or aligns new practices with established processes can significantly reduce the perceived disruption of change. Our research showed that phrases like “almost identical” or “as you do at the moment” were effective in garnering support, suggesting that such framing could reduce employee resistance.

The findings also support adopting incremental change strategies. By implementing changes in stages and incorporating familiar elements into each phase, organizations can reduce perceived risk and create a sense of control among employees. This approach not only minimizes resistance but also allows for ongoing adjustments based on feedback, further enhancing the effectiveness of the change process.

This research challenges the effectiveness of traditional change management models that rely primarily on creating urgency or fear through dramatic transformation. Organizations should reconsider these models in light of behavioral economics insights, particularly those related to cognitive biases like status quo bias. By understanding and leveraging these biases, change practitioners can design strategies that align better with human decision-making processes, leading to higher success rates in change initiatives.

The societal impact of applying these principles lies in creating a workplace culture that respects human cognitive tendencies, thus reducing the psychological burden on employees and fostering a more supportive and inclusive work environment. In contexts where change can lead to significant employee stress, reducing resistance by framing change as a continuation rather than a disruption could have substantial positive effects on job satisfaction and mental health.

To maximize the effectiveness of change strategies, it is crucial to train change leaders and those controlling corporate communications in the principles of behavioral economics. This training should focus on understanding cognitive biases and how they influence decision-making and resistance to change. Equipped with this, communication strategies and change plans can be crafted that resonate with employees, reducing resistance and enhancing the overall success of organizational change efforts.

The insights from this study are broadly applicable across various organizational contexts. Whether dealing with technological upgrades, physical relocation and/or updates, structural reorganizations or cultural shifts, the principles of leveraging familiarity and incrementalism can be adapted to fit the unique needs and challenges of different organizations.

By incorporating these practical implications into their change management practices, organizations can create a more supportive and less disruptive environment for change, ultimately leading to more sustainable and successful change efforts.

While our vignettes aimed to represent realistic workplace change scenarios, their limited number inherently restricts the generalizability of our findings. Future research should explore a broader range of change situations, encompassing diverse organizational contexts and cultures, to understand how the strength of status quo bias may vary across industries and cultural settings. Longitudinal studies could also assess the long-term impact of leveraging status quo bias in change initiatives, tracking employee attitudes and organizational outcomes over time.

While the forced-choice response format facilitated data collection and analysis, it precluded open-ended input from participants, potentially limiting the discovery of nuanced perspectives and motivations. Future studies could incorporate qualitative methods, such as interviews, to complement quantitative findings and provide a richer understanding of decision-making processes during change.

Furthermore, although our results largely confirm a preference for the status quo, a notable overall minority (34%) did opt for change. This suggests the influence of factors beyond a compelling vision, such as personality traits, change specifics, and individual novelty-seeking tendencies. Future research should investigate the interplay of these factors with status quo bias, potentially leading to more personalized change management strategies.

The promising finding that even small benefits can significantly increase change acceptance warrants further exploration. Defining the boundary conditions of this “small reason” effect and developing practical guidelines for its implementation could empower change practitioners to strategically leverage this insight.

Future research could also investigate the role of change leadership styles in leveraging behavioral economics principles and the potential for customizing change communications based on individual differences in susceptibility to status quo bias.

Finally, conducting a comparative analysis of traditional and behaviorally-informed change models, exploring the impact of cognitive bias awareness on resistance, and investigating other cognitive biases in change contexts would enrich our understanding of this complex phenomenon. Addressing the ethical implications of leveraging cognitive biases in change management is also crucial for responsible and sustainable practice.

By delving deeper into these areas, future research can build upon our findings and contribute to a more comprehensive understanding of how to navigate the intricacies of organizational change, ultimately leading to more successful and less disruptive change efforts.

This study questions the effectiveness of the traditional burning platform approach in organizational change management and proposes an alternative strategy grounded in leveraging the status quo. Our findings indicate that framing change as a continuum rather than a departure from the current state could reduce resistance as vilifying the familiar can inadvertently heighten opposition. The widespread adoption of such approaches, particularly those based on Kotter’s model, calls for further evaluation of the effectiveness of current organizational change management practices – which may accidentally be aiding the “making of enemies” as forewarned by Wilson. If Prosci does indeed have a significant footprint in most Fortune 500 companies, promoting an approach based on Kotter’s teachings, then some of their suggested focus may be misdirected.

In practical terms, our findings offer actionable insights for organizational leaders and change practitioners, presenting behaviorally-informed strategies that can be applied across diverse organizational contexts to foster smoother transitions and greater adaptability. This perspective shifts the focus from a vision-driven strategy to one that integrates human cognitive tendencies, potentially leading to more sustainable and less disruptive change. From a societal perspective, leveraging cognitive biases in this way may promote broader acceptance of change initiatives within communities. Aligning change management strategies with cognitive tendencies can reduce the psychological toll on employees, fostering a more resilient and adaptable workforce, and thereby contributing positively to societal mental health and overall well-being.

This research offers a potential solution to the persistent problem of organizational change effort failure. It also shows how highlighting a small reason to justify the change – I’ll have what I had before, but with a cherry on top, can perhaps leverage the power of status quo bias even further. This approach aligns with insights from behavioral economics and challenges the notion that a compelling vision alone can overcome resistance.

The Open Access (OA) Article Publication Charge (APC) for this paper was paid in full by the Council of Australian University Librarians (CAUL) - Australian consortium agreement - with the University of Southern Queensland and Emerald Publishing Limited.