The Impact of Digital Transformation Job Autonomy on Lawyers’ Support for Law Firms’ Digital Initiatives: The Mediating Role of Cognitive Adjustment and the Moderating Effect of Leaders’ Empathy

Abstract

Digital transformation has reshaped knowledge creation patterns, business models, and practices within the legal industry. However, many organizations have struggled to realize the anticipated benefits of digital transformation due to individual adaptation barriers. Drawing on the Job Demands–Resources model, this study employs both regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) to investigate the mechanisms and the boundary conditions through which digital transformation job autonomy affects lawyers’ supportive behaviors toward digital change in law firms. The regression analysis of multi-wave survey data from 423 lawyers demonstrates that digital transformation job autonomy not only has a direct positive effect on lawyers’ digital transformation-supportive behaviors, but also indirectly promotes such behaviors through lawyers’ cognitive adjustment in the workplace. Furthermore, leader empathy enhances the relationship between digital transformation job autonomy and supportive behaviors. The fsQCA results identify multiple pathways leading to high and low levels of digital transformation-supportive behaviors among lawyers. These findings contribute to a deeper understanding of how organizations foster individual support for digital transformation.

1. Introduction

In recent years, digital transformation has emerged as a critical strategic imperative for organizations across industries. Defined as the process through which organizations leverage digital technologies to reshape business processes, production models, and organizational structures in response to market uncertainty (Zhao et al., 2024), digital transformation has not only revolutionized the traditional business models and customer experiences (Gebauer et al., 2021), but has also profoundly impacted professional service sectors such as the legal industry (Chen et al., 2024; Rodgers et al., 2023). Law firms are increasingly applying algorithms, data-driven artificial intelligence, and machine learning tools to support various aspects of the legal practice, including technology-assisted review, due diligence, and contract analysis, as well as billing and resource utilization (Armour et al., 2022). However, research shows that 87.5% of digital transformation initiatives fail, primarily due to cultural barriers and employees’ inadequate adaptation (Wade & Shan, 2020). The success of organizational digital transformation depends not only on critical management capabilities, but also on individuals’ active participation and support (Gfrerer et al., 2021; Meske & Junglas, 2021; Poláková-Kersten et al., 2023; Selimović et al., 2021). Negative individual responses may manifest as technology avoidance, collaboration resistance, or skepticism toward change (Klein et al., 2024; Pei et al., 2025), which may delay transformation progress, or even lead to project failure (Holopainen et al., 2023; Valtonen & Holopainen, 2025). Therefore, it is important to explore how to stimulate individuals’ digital transformation-supportive behaviors, such as actively learning about digital tools, assisting colleagues to adapt, and advocating for digital practices. The existing studies point out that organizational training, education, and support (Chawla et al., 2025; Bozkus, 2023), as well as shaping the organizational culture and guiding individuals to participate in the change process (Peschl & Schüth, 2022; Singh & Hess, 2017), can enhance individuals’ acceptance of digital transformation. Höyng and Lau (2023) found that employees who are encouraged to act more autonomously perceive digital work tools as more useful and easier to use, thereby increasing their adoption intention. According to the Job Demands–Resources (JD-R) model (Schaufeli & Bakker, 2004; Bakker & Demerouti, 2017), digital transformation job autonomy serves as a key work-related resource that empowers individuals with decision-making flexibility in digital tasks (e.g., autonomy in choosing tools and adapting workflows). This autonomy not only alleviates the stress induced by technological changes, but also stimulates intrinsic motivation. When individuals have the autonomy to experiment with new systems, they are more proactive in exploring technology features rather than passively waiting for instructions (Höyng & Lau, 2023). This sense of control effectively reduces uncertainty-induced anxiety, encouraging individuals to view digital challenges as opportunities for growth rather than threats. Therefore, this study aims to explore the mechanisms and boundary conditions through which digital transformation job autonomy influences individuals’ digital transformation-supportive behaviors.

In the context of law firm digital transformation, job autonomy provides lawyers with greater flexibility to explore and master digital tools at their own learning pace (Huu, 2023). This autonomy enhances lawyers’ sense of control and work engagement (Bakker & Demerouti, 2017), prompting them to better understand the evolving role dynamics within teams, adapt to new cross-departmental and cross-platform collaborative mechanisms, and facilitate team cognitive adjustment. In addition, lawyers with a higher degree of autonomy are more likely to participate in the decision-making process related to digital transformation, thereby strengthening their identification with the goals and strategic values of organizational change (Bošković, 2021; Meske & Junglas, 2021). This promotes their transition from passive executors to active advocates who proactively acquire digital skills and disseminate digital concepts. Therefore, we propose that digital transformation job autonomy indirectly promotes lawyers’ supportive behaviors during the transformation process by facilitating their cognitive adjustment in the workplace.

Notably, in the process of digital transformation, lawyers may face challenges, such as the steep learning curve of new technologies and intensive information updates. Without appropriate psychological support and emotional regulation, autonomy may transform into a burden, resulting in responsibility overload and adaptation barriers (Shakina et al., 2021). Therefore, we introduce leader empathy as a critical moderating variable and examine its role in the relationship between digital transformation job autonomy and lawyers’ supportive behaviors. Specifically, leaders with high levels of empathy are able to communicate with lawyers, identify their emotional fluctuations and adaptation difficulties during digital transformation, and provide feedback and guidance in a caring manner. This alleviates lawyers’ frustration and uncertainty, as well as enhances their psychological readiness and confidence to embrace change (Muss et al., 2025). Moreover, highly empathetic leaders are more inclined to create an organizational climate that tolerates trial and error and encourages exploration (Yue et al., 2021), which makes lawyers dare to use their autonomy to carry out innovative attempts and adjust their behavioral strategies. Thus, under the combined effect of job autonomy and leader empathy, lawyers will be more active in cognitive adjustment in the workplace, which, in turn, encourages digital transformation-supportive behaviors.

Our study makes several theoretical contributions. First, we systematically elucidate the impact pathway of job autonomy on lawyers’ supportive behaviors in digital transformation contexts, enriching and expanding the application boundaries of the JD-R model. While previous research has predominantly focused on the effects of job resources in traditional contexts (Clausen et al., 2022; Spagnoli & Molinaro, 2020), we emphasize that job autonomy, as a structural resource in digital transformation contexts, can help individuals to meet the high job demands brought by digital technologies, which, in turn, leads to positive outcomes in terms of individuals’ support for digital transformation. Second, by introducing cognitive adjustment in the workplace as a mediating variable, our study reveals the psychological mechanisms by which job autonomy influences lawyers’ supportive behavior. We demonstrate that job autonomy not only directly leads to positive outcomes, but also indirectly promotes lawyers’ supportive behaviors by improving lawyers’ cognitive adjustment in terms of task structure, teamwork, and organizational culture. Thus, our study validates the buffering assumption about job resources in the JD-R model, and further enriches the understanding of how job resources bring about behavioral changes in individuals by influencing their psychological mechanisms. Third, our study further clarifies the moderating role of leader empathy in the relationship between digital transformation job autonomy and lawyers’ digital transformation-supportive behaviors. It has been found that under the high-pressure environment of digital transformation, even if lawyers possess a high degree of job autonomy, they may experience confusion and helplessness due to technological complexity or information asymmetry, thus inhibiting their cognitive adjustment and behavioral response (Klein et al., 2024; Shakina et al., 2021). In such cases, empathy prompts leaders to listen patiently and give positive feedback to lawyers, which enhances lawyers’ psychological safety and sense of organizational belonging (Muss et al., 2025; Yue et al., 2021), thereby increasing their confidence and motivation to engage in cognitive adjustment, and ultimately leading them to exhibit more supportive behaviors. Consequently, our research emphasizes the vital role of leader empathy in individuals’ psychological adjustment and behavioral transformation, contributing to the literature on how leadership styles influence employees’ attitudes and behaviors.

2. Theory and Hypotheses Development

2.1. Job Demands–Resources Model

The Job Demands–Resources (JD-R) model categorizes work conditions into job demands and job resources (Schaufeli & Bakker, 2004; Bakker & Demerouti, 2017). Job demands refer to the physical, psychological, or organizational factors that require sustained effort and are often associated with stress, fatigue, and burnout (Bakker et al., 2007). In contrast, job resources encompass the psychological, social, or organizational factors that reduce the negative impact of job demands, while fostering motivation, engagement, and personal growth (Bakker & Demerouti, 2017). The JD-R model posits two key pathways: the health impairment process and the motivational process. Excessive job demands may lead to emotional exhaustion and burnout, whereas sufficient job resources promote work engagement and enhance performance. Furthermore, the buffering hypothesis suggests that when high job demands are matched with adequate resources, they may produce positive outcomes (Halbesleben, 2010). Additionally, the model also incorporates personal resources, which interact with job resources to influence how employees cope with stress and perform under pressure (Bakker et al., 2023).

2.2. Digital Transformation Job Autonomy and Digital Transformation-Supportive Behavior

Digital transformation job autonomy is the extent of independence and discretion permitted while performing professional tasks during digital transformation (Galanti et al., 2021; Morgeson & Humphrey, 2006). Lawyers having greater job autonomy during law firm digital transformation means they can freely choose the digital tools, methods, and processes used to complete tasks. According to the JD-R model, job autonomy mitigates the uncertainty brought by technological change, reducing lawyers’ anxiety about unfamiliar technologies or process modifications, thereby enhancing their sense of control and confidence (Huu, 2023). Therefore, lawyers are more likely to maintain a positive work attitude and adopt supportive behaviors, such as proactively learning digital technologies and engaging in the use of digital systems (Bakker et al., 2007). Digital transformation-supportive behavior refers to individuals’ proactive actions to participate in, drive, and contribute to organization-initiated digital transformation (Kim et al., 2011). Lawyers empowered with job autonomy can participate in decision-making processes, which enhances their understanding and acceptance of digital transformation strategies, thereby increasing their willingness to engage in transformation initiatives, such as promoting digital tools and guiding colleagues through change. Moreover, autonomy is often accompanied by a higher sense of responsibility (Wu et al., 2023). As lawyers are responsible not only for execution outcomes, but also have a say in process selection, their role identification and commitment are strengthened. This motivates them to demonstrate greater responsibility and initiative during transformation (Wu et al., 2023), exemplified by proposing improvement suggestions or helping coworkers to adapt to new systems. Thus, we propose the following hypothesis:

Hypothesis 1. 

Digital transformation job autonomy is positively related to lawyers’ digital transformation-supportive behavior.

2.3. The Mediating Role of Cognitive Adjustment in the Workplace Linking Digital Transformation Job Autonomy and Supportive Behavior

In the context of law firm digital transformation, job autonomy, as a critical job resource in the JD-R model, also facilitates individuals’ cognitive adjustment to changing work content and contexts, ultimately translating into supportive behaviors toward organizational change. Cognitive adjustment in the workplace refers to the proactive efforts of individuals to acquire the necessary knowledge and skills at the psychological level to cope with changing job requirements and achieve career goals (Montani et al., 2020).

On the one hand, digital transformation job autonomy promotes lawyers’ cognitive adjustment in the workplace. Job autonomy serves as a key job resource for lawyers, encouraging them to invest greater effort and engagement in their work (Clausen et al., 2022; Galanti et al., 2021). When faced with changes in digital tools and systems, lawyers with autonomy are more likely to engage in proactive exploration and experimentation (Bakker & Demerouti, 2017). Such exploratory behaviors drive them to continuously update their understanding of digital system operations, process optimization, and other aspects. They also gain clearer insights into team members’ role distribution and the strategic significance of organizational digital transformation. Furthermore, job autonomy provides lawyers with room for trial and error, lowering the psychological cost of cognitive adjustment during digital transformation (Meng et al., 2019). Thus, we argue the following:

Hypothesis 2. 

Digital transformation job autonomy is positively related to lawyers’ cognitive adjustment in the workplace.

On the other hand, the cognitive adjustments carried out by lawyers promote their digital transformation-supportive behaviors. Cognitive adjustment in the workplace consists of three dimensions: task adjustment, group adjustment, and organizational adjustment (Malo et al., 2016). Task adjustment refers to individuals’ comprehension and adaptation to the knowledge and skills required for different aspects of their work tasks (Malo et al., 2016). With greater job autonomy, lawyers can flexibly select tools and processes, gaining deeper insights into task objectives and operational details. This motivates them to proactively identify new knowledge demands in digitalized tasks (e.g., data processing, case analyzing, and automated platform operations) and actively engage in digital platform utilization and process optimization (Bošković, 2021; Meske & Junglas, 2021). Second, group adjustment entails individuals’ cognitive adaptation to evolving team dynamics, role distributions, and collaborative mechanisms (Malo et al., 2016). Job autonomy facilitates individuals’ psychological well-being and reduces emotional exhaustion (Gardner, 2020; Spagnoli & Molinaro, 2020), thus enhancing cross-functional communication and enabling individuals to efficiently accomplish digital tasks. As a result, they proactively assess team members’ digital competencies and refine role allocations. When individuals are cognitively adapted to new collaboration frameworks (e.g., remote coordination and digital tool integration), they exhibit greater willingness to assist others, share experiences, and carry out digital transformation-supportive behaviors. Third, organizational adjustment involves employees’ reinterpretation of formal/informal norms, power structures, and cultural values (Malo et al., 2016). When lawyers have a high level of digital transformation job autonomy, they are required to make decisions independently and therefore must understand the organization’s policies, structural changes, and values regarding digitalization. Upon recognizing the significance of their law firm’s digital transformation, lawyers with job autonomy demonstrate a greater willingness to take responsibility for solving digital technology problems and align their behaviors with organizational expectations (Cai et al., 2020). This alignment manifests through supportive behaviors, such as advocating for digital concepts and optimizing digital systems, reflecting both cognitive consistency and behavioral endorsement of the transformation (Meske & Junglas, 2021). Therefore, we propose the following:

Hypothesis 3. 

Digital transformation job autonomy indirectly influences lawyers’ digital transformation-supportive behavior through cognitive adjustment in the workplace.

2.4. The Moderating Role of Leader Empathy

Although digital transformation job autonomy is generally regarded as a positive job resource that motivates individuals’ supportive behaviors, the lack of adequate psychological support may turn autonomy into a source of responsibility pressure for individuals, potentially leading to negative outcomes (Dettmers & Bredehöft, 2020; E. Zhou, 2020). Drawing from the JD-R model, leader empathy, the ability of leaders to accurately recognize, perceive, and experience the emotions of others (Cornelis et al., 2013), serves not only as a critical contextual factor, but also as a job resource for employees. It may shape how employees perceive, interpret, and utilize job autonomy, thereby moderating the positive effect of digital transformation job autonomy on employees’ supportive behaviors.

Empathy is an important concept central to emotionally intelligent behavior, defined as “the ability to comprehend another’s feelings and to re-experience them oneself” (Salovey & Mayer, 1990, pp. 194–195). While job autonomy encourages lawyers to proactively explore digital tools, the complexity of technologies may lead to high job demands, potentially reducing lawyers’ self-efficacy (Shakina et al., 2021). Leaders with a high level of empathy can recognize lawyers’ frustration, avoid critical feedback, and instead provide encouragement and personalized support (Kock et al., 2019). This supportive intervention not only preserves lawyers’ job autonomy in decision making, but also increases their confidence and sense of security in using autonomy, making them more willing to try new approaches and actively participate in transformation tasks.

Second, leaders with high-level empathy are more capable of fostering trust and emotional connections that make lawyers feel valued and important within the organization (Steenkamp & Dhanesh, 2023). This positive emotional experience increases lawyers’ identification with organizational goals, motivating them to use their granted job autonomy to support organizational transformation.

Third, highly empathetic leaders can enhance the positive impact of job autonomy on digital transformation-supportive behaviors by preventing lawyers from interpreting autonomy as taking risks alone through timely guidance and encouragement (Yue et al., 2023). Therefore, we propose the following:

Hypothesis 4. 

Leader empathy strengthens the relationship between digital transformation job autonomy and lawyers’ digital transformation-supportive behavior.

Leader empathy also enhances the positive effects of digital transformation job autonomy on lawyers’ cognitive adjustment in the workplace. On the one hand, digital collaboration models disrupt the traditional communication mechanisms, requiring lawyers to reorient themselves to new team roles and working methods (Shakina et al., 2021). Empathetic leaders actively listen to lawyers’ discomfort in team collaboration (e.g., communication barriers and role ambiguity), helping them to understand new collaborative logic and reducing team cognitive conflicts (Lloyd et al., 2017; Ni et al., 2023). Additionally, by fostering an inclusive and supportive collaborative environment, leaders enhance lawyers’ psychological safety (Yue et al., 2021), enabling them to utilize autonomy more effectively and adapt more willingly to new team structures through cognitive adjustments.

On the other hand, digital transformation often entails reshaping strategic directions and cultural principles, which may trigger resistance due to lawyers’ cognitive uncertainty. Empathetic leaders explain the organization’s new direction and cultural values in an emotionally resonant manner, alleviating negative emotions during autonomous exploration (Muss et al., 2025). When lawyers feel respected and understood, they are more likely to internalize organizational values and achieve cognitive alignment at the organizational level (Lloyd et al., 2017). Therefore, we propose the following:

Hypothesis 5. 

Leader empathy strengthens the relationship between digital transformation job autonomy and lawyers’ cognitive adjustment in the workplace.

Furthermore, we propose a moderated mediation model, in which leader empathy moderates the indirect effect of job autonomy on lawyers’ digital transformation-supportive behaviors. Specifically, when lawyers perceive high levels of job autonomy and their leaders demonstrate strong empathetic capabilities—including the ability to accurately perceive lawyers’ emotional states, understand their challenges and pressures in technology adaptation, and provide timely emotional support and constructive feedback—this combination significantly enhances lawyers’ psychological safety and perceptions of emotional value (Huu, 2023; Yue et al., 2021). Leader empathy not only helps to alleviate the uncertainty and anxiety induced by digital transformation, but also activates lawyers’ initiative and adaptability, leading to more effective cognitive adjustments in the workplace. Consequently, lawyers develop a deeper understanding of and greater adaptation to new collaboration mechanisms and team role allocations in the digital context, while also recognizing and aligning with the organization’s value orientation, institutional logic, and cultural norms during transformation (Malo et al., 2016; Q. Zhou et al., 2024). Ultimately, this psychological and cognitive adjustment promotes lawyers’ supportive behaviors during the digital transformation process, such as taking the initiative to learn about new technologies and assisting others in adapting to the transformation. Thus, we argue the following:

Hypothesis 6. 

Leader empathy strengthens the indirect effect of digital transformation job autonomy on digital transformation-supportive behavior through cognitive adjustment in the workplace.

In summary, this study develops a moderated mediation model (see Figure 1) to explore how digital transformation job autonomy affects lawyers’ digital transformation-supportive behavior.

3. Method

3.1. Samples and Procedures

This study utilized a multi-wave online survey, developed and disseminated through one of China’s largest legal industry associations. The respondents were rigorously screened according to the following criteria: (1) be currently practicing lawyers with valid licenses, and (2) work in law firms that had either implemented or were actively undergoing digital transformation initiatives. To effectively reduce potential common method bias (Podsakoff et al., 2024), the questionnaire was administered at three separate time points (i.e., Time 1, Time 2, and Time 3), with a three-month interval between waves. Before the survey distribution, the participants were assured of (1) the complete anonymity of responses through encrypted data collection protocols, (2) that all participation was entirely voluntary and any participant could withdraw at any time, and (3) the exclusive use of data for academic research purposes under confidentiality agreements. Written informed consent was obtained from the participants.

The three-wave survey design was implemented through the lawyer association’s internal communication network. To ensure high-quality responses and maintain participant engagement throughout the longitudinal study, immediate compensation via the survey platform’s reward system upon questionnaire completion was offered. Additionally, the survey interface included attention check questions and consistency validations to further enhance data reliability.

In the initial phase, survey invitations were sent to all registered lawyers, resulting in 748 valid responses from voluntary participants. The Time 1 questionnaire assessed lawyers’ perceptions of digital transformation job autonomy, together with their demographic variables (gender, age, education level, professional rank, and work experience). Three months later, the Time 2 survey was administered to the same respondents, evaluating their cognitive adjustment in the workplace and perceived level of direct leader’s empathy. At Time 3, the participants were invited to report their supportive behavior towards digital transformation in their law firms. Through rigorous data cleaning procedures, including the validation of reverse-coded items and the elimination of careless responses (e.g., straight lining or inconsistent answers), we obtained 423 matched valid responses across the three time points, yielding a valid response rate of 56.55%. The t-test revealed no significant differences between the sample and the participants who discontinued the survey, suggesting that the attrition was likely to be random rather than systematic. This methodological approach ensured both temporal separation of predictor and outcome measurements and high-quality paired data for analyzing the hypothesized relationships.

Regarding gender distribution, 42.8% of the respondents identified as male. The age breakdown indicated that 40.2% of the participants were between 21 and 30 years old, while the majority (52.2%) were aged from 31 to 40. In terms of educational attainment, most participants held master’s degrees (68.3%), with 12.1% possessed doctoral qualifications. The professional hierarchy of the sample included 35.0% assistant lawyers, 35.9% third-grade lawyers, and 22.2% second-grade lawyers. The average work experience duration among the participants was 6.11 years (standard deviation [SD] = 4.18).

3.2. Measurements

We followed the standard translation and back-translation procedures outlined by Brislin (1986) to develop the Chinese items. All measures utilized a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

3.2.1. Digital Transformation Job Autonomy

At Time 1, the lawyers were invited to rate their perceived job autonomy during digital transformation. Following established approaches for contextualizing (e.g., Meske & Junglas, 2021; Q. Zhou & Shi, 2025; Q. Zhou et al., 2024), we adapted a three-item scale from Deci et al. (2001) and Spreitzer (1995), and contextualized it to reflect autonomy in digitally transformed work settings. A sample item included “There are many opportunities for me to decide for myself how I use the digitally transformed workplace” (α = 0.84).

3.2.2. Cognitive Adjustment in the Workplace

At Time 2, we used Malo et al.’s (2016) 18-item scale, which contained three dimensions. The dimension of “Task adjustment” had four items, such as “During digital transformation, I master the tasks required for my work” (α = 0.70). “Group adjustment” dimension contained 8 items, e.g., “During digital transformation, I know how decisions in my law firm are taken” (α = 0.84). “Organizational adjustment” dimension had six items, e.g., “During digital transformation, I know who to turn to when I cannot find answers to my questions” (α = 0.85). Cognitive adjustment in the workplace was regarded as a unidimensional variable (α = 0.89).

3.2.3. Leader Empathy

At Time 2, the lawyers rated their direct leader’s level of empathy using Dietz and Kleinlogel’s (2014) scale, which was later validated by Tian and Robertson (2019). A sample item included “My direct leader often has tender, concerned feelings for people less fortunate than him/her” (α = 0.95).

3.2.4. Digital Transformation-Supportive Behavior

At Time 3, the lawyers were invited to rate their digital transformation-supportive behavior using measurements adapted from Meske and Junglas (2021). A sample item included “During last three months, I intend to provide proactive feedback regarding the digital transformation in the law firm” (α = 0.85).

3.2.5. Control Variables

The previous studies have shown that individuals’ demographic information can influence their attitudes and behaviors toward digital transformation (Q. Zhou & Shi, 2025; Q. Zhou et al., 2024). Consequently, we controlled for these demographic variables to mitigate their potential impact on the results of the data analysis. All the findings remained consistent regardless of the inclusion of these controls.

4. Results

4.1. Preliminary Analyses

Table 1. Means, standard deviations, and correlation coefficients between variables.

Variables	Mean	SD	1	2	3	4	5	6	7	8	9
1. Gender	1.57	0.50	--
2. Age	1.70	0.68	−0.08	--
3. Educational background	3.85	0.76	0.04	−0.20 ***	--
4. Professional rank	2.01	0.92	−0.13 **	0.14 **	0.09	--
5. Tenure	6.12	4.18	−0.12 *	0.63 ***	−0.26 ***	0.13 **	--
6. Digital transformation job autonomy	5.48	0.92	−0.04	0.01	0.00	0.31 ***	0.06	0.84
7. Cognitive adjustment in the workplace	5.74	0.56	−0.02	0.09	0.12 *	0.21 ***	0.09	0.50 ***	0.89
8. Leader empathy	5.24	1.05	0.00	0.05	0.01	0.13 **	0.03	0.44 ***	0.62 ***	0.95
9. Digital transformation-supportive behavior	5.15	0.98	0.07	−0.04	0.10 *	0.13 **	0.03	0.35 ***	0.51 ***	0.60 ***	0.85

Notes: N = 423. 1 = Male; 2 = Female. Age groups are categorized as follows: 21–30 years = 1, 31–40 years = 2, 41–50 years = 3, 51–60 years = 4, and above 60 years = 5. Educational background is classified as: 1 = Junior high school; 2 = Associate degree; 3 = Bachelor’s degree; 4 = Master’s degree; 5 = Doctoral degree. Professional rank is defined as follows: 1 = Assistant lawyer; 2 = Second-grade lawyer; 3 = Third-grade lawyer; 4 = Fourth-grade lawyer. Tenure is measured in years. * p < 0.05, ** p < 0.01, *** p < 0.001 (two-tailed tests).

presents the descriptive statistics (means and SDs) and correlation coefficients for all the focal variables. As indicated in Table 1, the observed relationships between the variables are consistent with the theoretical expectations. Specifically, the lawyers’ digital transformation job autonomy shows significant positive correlations with both cognitive adjustment in the workplace (r = 0.50, p < 0.001) and supportive behavior (r = 0.35, p < 0.001). These correlations provide preliminary support for our hypothesized relationships.

This study conducted the confirmatory factor analysis (CFA) of the four focal variables. Due to the ratio of sample size to the estimated number of items affecting the model fit (Little et al., 2013; Williams et al., 2009), we parceled cognitive adjustment in the workplace into three factors due to its three dimensions. The results demonstrated that the hypothesized four-factor model exhibited a superior fit to the observed data (χ²(146) = 366.69, p < 0.000; RMSEA = 0.06, CFI = 0.96, TLI = 0.95, SRMR = 0.05) and outperformed all the alternative models, including a three-factor model combing digital transformation job autonomy and supportive behavior (χ²(149) = 790.78, p < 0.000; RMSEA = 0.10, CFI = 0.86, TLI = 0.87, SRMR = 0.08); another three-factor model combing cognitive adjustment in the workplace and supportive behavior (χ²(149) = 611.94, p < 0.000; RMSEA = 0.09, CFI = 0.92, TLI = 0.91, SRMR = 0.06); and a two-factor model combing digital transformation job autonomy, cognitive adjustment in the workplace, and supportive behavior (χ²(151) = 939.64, p < 0.000; RMSEA = 0.11, CFI = 0.86, TLI = 0.84, SRMR = 0.07). The findings provide evidence for the discriminant validity among the four variables.

Given that the survey data were collected from the same respondents, a common method bias may be present (Podsakoff et al., 2024). To evaluate its potential impact on our findings, we conducted two tests using Mplus 7.4 (Muthén & Muthén, 2012). First, Harman’s single-factor test indicated a significantly poorer model fit for a single-factor model (χ²(152) = 1242.38, p < 0.000; RMSEA = 0.13, CFI = 0.81, TLI = 0.78, SRMR = 0.09) compared to that of our hypothesized four-factor model. In addition, the exploratory factor analysis that constrained all the items to load on a single common factor revealed that the first factor accounted for only 37.72% of the total variance—below the 50% threshold—suggesting that most variability remained unexplained by this artificial construct. Second, the results of the common latent factor test showed that after adding a common method factor to the four-factor model, the fit indices (χ²(145) = 409.70, p < 0.000; RMSEA = 0.07, CFI = 0.95, TLI = 0.94, SRMR = 0.08) did not significantly improve compared to the fit of the four-factor model. Therefore, both tests confirm that common method bias does not significantly impact our data, thereby justifying further analysis.

4.2. Hypotheses Test

To examine our hypothesized relationships, we performed path analysis using Mplus (Muthén & Muthén, 2012). Following Edwards and Lambert’s (2007) analytical procedures, we employed bootstrapping with 5000 resamples to generate bias-corrected 95% confidence intervals [CI] for all the parameter estimates. We controlled for the covariates, including the lawyers’ gender, age, educational level, professional rank, and tenure, to isolate the effects of the primary variables of interest.

We first conducted path analysis without a moderator (i.e., leader empathy) to test the main effects and mediation effects in Hypotheses 1–3.

4.2.1. Test of Main Effects

The results in

Table 2. Path analysis without leader empathy.

Variables	Cognitive Adjustment in the Workplace				Digital Transformation-Supportive Behavior
	β	SE	LLCI	ULCI	β	SE	LLCI	ULCI
Constant	3.47 ***	0.22	[3.04,	3.90]	−0.36	0.48	[−1.31,	0.58]
Control variables
Gender	0.01	0.05	[−0.09,	0.10]	0.16 *	0.08	[0.00,	0.33]
Age	0.08	0.04	[0.00,	0.17]	−0.16 *	0.08	[−0.31,	−0.01]
Educational background	0.11 **	0.03	[0.04,	0.17]	0.06	0.06	[−0.06,	0.17]
Professional rank	0.02	0.03	[−0.04,	0.07]	0.01	0.05	[−0.08,	0.10]
Tenure	0.00	0.01	[−0.01,	0.02]	0.02	0.01	[−0.01,	0.04]
Independent variable
Digital transformation job autonomy	0.30 ***	0.03	[0.25,	0.35]	0.13 *	0.05	[0.03,	0.24]
Mediator
Cognitive adjustment in the workplace					0.78 ***	0.09	[0.61,	0.94]

Notes: N = 423. Unstandardized coefficient values are reported. SE = standard error. LLCI = Lower Limit of Confidence Interval; ULCI = Upper Limit of Confidence Interval. * p < 0.05, ** p < 0.01, *** p < 0.001.

indicate that the association between digital transformation job autonomy and digital transformation-supportive behavior is positive and significant (β = 0.13, Standard Errors [SE] = 0.05, p < 0.05, 95% CI = [0.03, 0.24]), supporting Hypothesis 1. The association between digital transformation job autonomy and cognitive adjustment in the workplace is positive and significant (β = 0.30, SE = 0.03, p < 0.001, 95% CI = [0.25, 0.35]), supporting Hypothesis 2.

4.2.2. Test of Mediation Effects

Hypothesis 3 proposes that digital transformation job autonomy indirectly influences digital transformation-supportive behavior through cognitive adjustment in the workplace. Following Edwards and Lambert’s (2007) approaches, the results with 5000 resamples of bootstrapping analysis reveal a significant positive indirect effect (indirect effect = 0.23, SE = 0.04, 95% CI = [0.16, 0.32], excluding zero). Therefore, Hypothesis 3 is supported.

4.2.3. Test of Moderation Effects

To examine the hypothesized moderation and moderated mediation effects (Hypotheses 4 and 5), we conducted additional path analyses incorporating leader empathy as the moderating variable. Consistent with the established procedures for testing interaction effects (Cohen et al., 2003), both digital transformation job autonomy and leader empathy were centered prior to analysis. The results of these analyses, including the bias-corrected CI derived from 5000 bootstrap resamples, are presented in

Table 3. Path analysis with leader empathy.

Variables	Cognitive Adjustment in the Workplace				Digital Transformation-Supportive Behavior
	β	SE	LLCI	ULCI	β	SE	LLCI	ULCI
Constant	5.19 ***	0.15	[4.90,	5.47]	2.90 ***	0.54	[1.83,	3.96]
Control variables
Gender	0.00	0.04	[−0.08,	0.08]	0.15 *	0.07	[0.00,	0.30]
Age	0.05	0.04	[−0.03,	0.12]	−0.18 **	0.07	[−0.32,	−0.04]
Educational background	0.10 **	0.03	[0.04,	0.15]	0.09	0.05	[−0.01,	0.19]
Professional rank	0.02	0.02	[−0.02,	0.07]	0.03	0.04	[−0.05,	0.12]
Tenure	0.01	0.01	[−0.01,	0.02]	0.02	0.01	[0.00,	0.04]
Independent variable
Digital transformation job autonomy	0.18 ***	0.03	[0.13,	0.23]	0.09	0.05	[−0.01,	0.19]
Mediator
Cognitive adjustment in the workplace					0.30 ***	0.09	[0.12,	0.48]
Moderator
Leader empathy	0.27 ***	0.02	[0.23,	0.31]	0.45 ***	0.05	[0.36,	0.54]
Interaction term
Digital transformation level job autonomy × Leader empathy	0.05 *	0.02	[0.01,	0.08]	0.10 **	0.04	[0.03,	0.17]

Notes: N = 423. Unstandardized coefficient values are reported. SE = standard error. LLCI = Lower Limit of Confidence Interval; ULCI = Upper Limit of Confidence Interval. * p < 0.05, ** p < 0.01, *** p < 0.001.

.

The results summarized in Table 3 showed that when regressing all the control variables, centered digital transformation job autonomy, centered leader empathy, and their interaction term on digital transformation-supportive behavior, the interaction term was positively related to digital transformation-supportive behavior (β = 0.10, SE = 0.04, p < 0.01, 95% CI = [0.03, 0.17]). In order to interpret the results, we followed Aiken et al.’s (1991) procedures to illustrate the interactions (see Figure 2) and conducted simple slopes analysis. The results indicated that the effect of digital transformation job autonomy on digital transformation-supportive behavior was stronger when the leaders were highly empathetic (one SD above the mean, simple slope = 0.19, SE = 0.07, p < 0.01, 95% CI = [0.05, 0.33]). In contrast, the effect of digital transformation job autonomy on digital transformation-supportive behavior became non-significant when leader empathy was low (one SD below the mean, simple slope = -0.02, SE = 0.05, p > 0.05, 95% CI = [−0.12, 0.09]). Thus, Hypothesis 4 is supported.

Similarly, when regressing all the control variables, centered digital transformation job autonomy, centered leader empathy, and their interaction term on cognitive adjustment in the workplace, the interaction term is positively related to cognitive adjustment in the workplace (β = 0.05, SE = 0.02, p < 0.05, 95% CI = [0.01, 0.08]). Figure 3 illustrates these interactions. The simple slopes analysis indicated that the effect of digital transformation job autonomy on cognitive adjustment in the workplace was stronger when the leaders were highly empathetic (one SD above the mean, simple slope = 0.23, SE = 0.04, p < 0.001, 95% CI = [0.16, 0.30]). In contrast, the effect of digital transformation job autonomy on cognitive adjustment in the workplace was still positive, but much weaker when the leaders were not very empathetic (one SD below the mean, simple slope = 0.13, SE = 0.03, p < 0.001, 95% CI = [0.08, 0.19]). Thus, Hypothesis 5 is supported.

4.2.4. Test of Moderated Mediation Effects

Following Edwards and Lambert’s (2007) approaches, the results with 5000 resamples from bootstrapping analysis revealed that when the leaders were highly empathetic, the indirect effect was positive and significant (indirect effect = 0.07, SE = 0.03, 95% CI = [0.02, 0.13]). In contrast, when the leaders were low in empathy, the indirect effect was still positive and significant, but much weaker (indirect effect = 0.04, SE = 0.02, 95% CI = [0.01, 0.08]). The index of moderated mediation was also significant (index = 0.01, SE = 0.01, 95% CI = [0.01, 0.03]). Therefore, Hypothesis 6 is supported.

It must be noted that, through regression analysis, all the hypotheses have been verified. However, the regression model is more inclined to identify the single strongest factor, while ignoring potential alternative pathways. To further analyze the complex relationships among the variables and identify multiple possible pathways and conditional combinations that may affect lawyers’ digital transformation-supportive behavior, this study introduces the method of fuzzy-set qualitative comparative analysis (fsQCA). On the one hand, this approach comparatively verifies the mechanisms through which factors such as digital transformation job autonomy, cognitive adjustment in the workplace, and leader empathy collectively influence lawyers’ digital transformation-supportive behavior, thereby enhancing the robustness of the research conclusions. On the other hand, it delves deeper into the subtle differences hidden within the sample data and uncovers new pathways beneath the overall average trends, identifying the combinations of factors that have distinct effects on specific groups. This provides richer and multi-layered explanations for this research.

4.3. Fuzzy-Set Qualitative Comparative Analysis

Given the inadequacy of the regression analysis methods in revealing the effects of interactions between antecedent variables on the outcome variables, this study further used fsQCA to analyze the combined effects of multivariate influences on digital transformation-supportive behavior. Specifically, considering that the effects of digital transformation job autonomy, cognitive adjustment in the workplace, and leader empathy on lawyers’ digital transformation-supportive behavior were verified in theoretical and empirical analyses, this study aims to explore how these three variables, namely, digital transformation job autonomy, cognitive adjustment in the workplace, and leader empathy, combine to contribute to lawyers’ digital transformation-supportive behaviors.

4.3.1. Calibration

This study selected digital transformation job autonomy, cognitive adjustment in the workplace, and leader empathy as conditional variables and digital transformation-supportive behavior as the outcome variable. To ensure the accuracy of these variables in data analysis, this study used the direct method to calibrate the variables to fuzzy sets by using the 95th percentile, 50th percentile, and 5th percentile as the thresholds for full membership, crossover point, and full non-membership (Ragin, 2009). In addition, the calibration value of 0.5 was adjusted to 0.501 to avoid case omission (Fiss, 2011).

4.3.2. Analysis of Necessary Conditions

After the calibration of the variables, the necessary condition analysis of each single variable was conducted. According to Ragin (2006), the antecedent variable is considered a necessary condition for the outcome variable when its consistency value exceeds 0.90. As shown in

Table 4. Analysis of necessary conditions.

Variables	High-Level Digital Transformation-Supportive Behavior		Non-High-Level Digital Transformation-Supportive Behavior
	Consistency	Coverage	Consistency	Coverage
Digital transformation job autonomy	0.742	0.773	0.627	0.567
~ Digital transformation job autonomy	0.584	0.643	0.749	0.716
Cognitive adjustment in the workplace	0.777	0.792	0.599	0.530
~ Cognitive adjustment in the workplace	0.539	0.608	0.766	0.749
Leader empathy	0.809	0.822	0.595	0.525
~ Leader empathy	0.532	0.602	0.798	0.784

, none of the antecedent variables achieved a consistency value above 0.90 in explaining either high- or non-high-level digital transformation-supportive behavior, indicating that none of them constitutes a necessary condition. Therefore, it was necessary to conduct the configurational analysis of the antecedent variables in this study.

4.3.3. Analysis of Sufficient Conditions

This study utilized fsQCA 3.0 software, setting the case frequency threshold to 1 and the raw consistency threshold to 0.80. The software analysis generated three types of solutions: complex, intermediate, and parsimonious. Following Fiss (2011), we integrated the intermediate and parsimonious solutions to identify the core and auxiliary conditions for each configuration. As shown in

Table 5. Analysis of sufficient conditions.

Variables	High-Level Digital Transformation-Supportive Behavior		Non-High-Level Digital Transformation-Supportive Behavior
	H1	H2	NH1
Digital transformation job autonomy	●		⊗
Cognitive adjustment in the workplace		●	⊗
Leader empathy	●	●	⊗
Consistency	0.893	0.878	0.847
Raw coverage	0.676	0.704	0.574
Unique coverage	0.058	0.086	0.574
Overall solution coverage	0.762		0.574
Overall solution consistency	0.861		0.847

Notes: ● signifies that the core condition exists; ⊗ signifies that the core condition does not exist; the blanks show that the condition can either be present or absent.

, configurations H1 and H2 explain the lawyers’ high-level digital transformation-supportive behavior. These configurations exhibit an overall solution consistency of 0.861, exceeding the minimum requirement of 0.75. The solution coverage reaches 76.2%, indicating that these configurations account for 76.2% of cases with high-level digital transformation-supportive behavior, demonstrating strong explanatory power.

Specifically, configuration H1 is characterized by digital transformation job autonomy and leader empathy as core conditions, indicating that digital transformation job autonomy can stimulate lawyers’ intrinsic motivation, prompting them to proactively explore the features of digital technologies and engage in organizational digital transformation decision making (Bošković, 2021). Simultaneously, the presence of a lot of empathy in leaders can effectively mitigate lawyers’ uncertainty in the face of digital technologies (Muss et al., 2025), encouraging them to proactively pursue innovative attempts and demonstrate support for law firm digital transformation. Thus, the coexistence of high-level digital transformation job autonomy and a high level of leader empathy fosters high-level digital transformation-supportive behavior, effectively supporting Hypothesis 1 and Hypothesis 4 of this study.

Configuration H2, with cognitive adjustment in the workplace and leader empathy as the core conditions, highlights the critical role these factors play in generating high-level digital transformation-supportive behavior. This configuration suggests that during law firm digital transformation, the presence of leaders with a lot of empathy as well as a high level of cognitive adjustment in the workplace will effectively enhance lawyers’ digital transformation-supportive behavior. Meanwhile, both configurations H1 and H2 emphasize the positive influence of leader empathy on digital transformation-supportive behavior, which aligns with extant research on the impact of leaders on employees during digital transformation (Weber et al., 2022).

Furthermore, leveraging the causal asymmetry feature of fsQCA, this study analyzes the antecedent configuration NH1, leading to non-high-level digital transformation-supportive behavior. The overall consistency of this configuration is 84.7%, and the overall coverage is 54.7%. Specifically, configuration NH1 includes digital transformation job autonomy, cognitive adjustment in the workplace, and leader empathy as core conditions, which indicates that in the context of digital transformation, a lack of job autonomy makes it difficult for lawyers to effectively explore and master digital technologies, while the lack of cognitive adjustment and the lack of leader empathy further weaken the lawyers’ support for digital transformation. The combined effect of these three factors ultimately leads to non-high-level digital transformation-supportive behavior among lawyers, which indirectly validates Hypothesis 3 and Hypothesis 6 of this study.

4.3.4. Robustness Analysis

This study conducted robustness analysis on the antecedent configurations of both high-level and non-high-level digital transformation-supportive behaviors by varying the consistency and frequency thresholds (Skaaning, 2011). First, when the case frequency threshold was increased from one to two, the adjustment did not alter the configurations for either high-level or non-high-level digital transformation-supportive behaviors. Second, when the consistency threshold was adjusted from 0.8 to 0.9, the resulting configurations remained consistent with the original solutions, with no changes observed in the consistency and coverage values of each configuration. Therefore, the findings demonstrate strong robustness.

5. Discussion

Based on the JD-R model, we constructed and validated a moderated mediation model that reveals how digital transformation job autonomy promotes lawyers’ supportive behaviors toward law firm digital transformation. Through regression analysis and fsQCA, we found that digital transformation job autonomy has a significant positive impact on lawyers’ digital transformation-supportive behavior. The prior studies have shown that digital transformation often involves the restructuring of work processes, the upgrading of skill requirements, and intensified performance monitoring, which may trigger anxiety and stress among individuals (Y. Yang et al., 2025; Pei et al., 2025). However, our findings suggest that job autonomy provides lawyers with greater decision making discretion and execution space, enabling them to adapt to changes at their own pace. This reduces the psychological burden associated with being forced to accept change (Bakker et al., 2023) and enhances both their willingness and behavioral support for transformation.

In addition, many employees are likely to worry that digitalization may lead to job displacement by technologies (Cheng et al., 2023), especially in professional fields such as law (Rodgers et al., 2023). Our study shows that digital transformation job autonomy enhances lawyers’ cognitive adjustment in the workplace. When lawyers are granted higher levels of autonomy, they are more likely to proactively acquire new skills, engage in process optimization, and perceive digital tools as a means to enhance their competitiveness rather than as a threat (Schneider & Sting, 2020). This shift helps to rebuild individuals’ confidence in their future career prospects and reduces concerns about unemployment.

Furthermore, leader empathy plays a significant moderating role in this mechanism. When individuals feel understood and emotionally supported by their leaders, the positive effects of job autonomy are further amplified. Although digitization improves efficiency, it may also weaken the emotional connections among colleagues and cause interpersonal detachment (X. Yang et al., 2024). When individuals are granted with too much decision-making authority and independence, they may experience increased responsibility pressure, psychological overload, or even role overload, which can lead to stress, anxiety, and burnout (Dettmers & Bredehöft, 2020). Our findings highlight that when a high level of job autonomy is paired with leader empathy, the potential negative consequences of autonomy can be effectively mitigated. Leaders with a lot of empathy can identify and respond to employees’ emotional needs, offering more human-centered support. Thus, they help to maintain trust, a sense of belongingness, and team cohesion in highly technological environments (Başer et al., 2025). Such emotional support not only enhances psychological safety, but also reinforces employees’ support for digital transformation. Therefore, our study enriches the understanding of how to promote lawyers’ positive responses to digital transformation. It also highlights the critical roles of digital transformation job autonomy and leader empathy in mitigating the potential negative consequences associated with digital transformation.

5.1. Theoretical Implications

First, our study reveals the positive impact of digital transformation job autonomy on lawyers’ digital transformation-supportive behaviors, expanding research on how to enhance individuals’ support for digital transformation. The previous studies have shown that employees often exhibit negative reactions, such as skepticism, resistance, and anxiety, during digital transformation (Holopainen et al., 2023; Valtonen & Holopainen, 2025). While organizational support and training have been identified as the key facilitators of employee adaptation to change (Chawla et al., 2025; Bozkus, 2023), our study shifts the focus to job autonomy as a critical enabler of proactive engagement with digital transformation. Although job autonomy has been extensively studied in general organizational settings (e.g., Spreitzer, 1995; E. Zhou, 2020), our research captures its distinctive characteristics and significance within the dynamic and complex environment of digital transformation. Grounded in the JD-R model, our study examines the mechanism through which job autonomy as a work resource promotes supportive behaviors and reveals the multiple pathways that lead to high-level individual digital transformation-supportive behaviors through fsQCA, providing theoretical insights for understanding the drivers of individuals’ support for digital transformation.

Second, our study identifies the mediating role of cognitive adjustment in the workplace in the relationship between digital transformation job autonomy and supportive behaviors, expanding the understanding of the motivational process of the JD-R model. While the JD-R model posits that job resources alleviate stress from job demands and enhance work engagement (Bakker & Demerouti, 2017; Halbesleben, 2010), our study further demonstrates that digital transformation job autonomy, as a key job resource, not only directly promotes positive individual behaviors, but also facilitates individuals’ cognitive adaptation to changes in task structures, team collaboration, and organizational culture. Unlike the previously explored mechanisms, such as motivation and engagement, cognitive adjustment focuses specifically on the internal psychological processes involved in how employees interpret and accept digital transformation. It reflects the ways in which individuals reframe their understanding of work practices, organizational goals, and interpersonal dynamics in response to technological shifts. Thus, cognitive adjustment in the workplace serves as a more direct and nuanced indicator of how employees transition from passive compliance to active support for organizational change. By identifying this mechanism, our study reveals a novel psychological pathway through which job autonomy influences employee behavior during digital transformation. Therefore, we contribute to the JD-R literature by extending its motivational process to include cognitive adjustment as an essential component of resource-driven behavioral outcomes.

Third, by introducing leader empathy as a moderator, our research uncovers the boundary conditions under which digital transformation job autonomy promotes supportive behaviors through cognitive adjustment. Our findings advance the current understanding by showing that the effects of job autonomy are not uniform across contexts. Although job autonomy provides lawyers with greater flexibility to address digital transformation challenges, inadequate psychological support may turn it into a burden, leading to responsibility overload and adaptation difficulties (Shakina et al., 2021). Our study proposes that leader empathy enhances lawyers’ psychological safety and mitigates the pressure associated with job autonomy, thereby strengthening the positive effect of job autonomy on cognitive adjustment and ultimately fostering digital transformation-supportive behaviors. This interaction between autonomy and leader empathy highlights the sensitivity to the socio-emotional environment of job autonomy’s functioning. Thus, this study offers a more comprehensive theoretical framework for understanding the positive effects of job autonomy, contributing to research on how leader empathy shapes lawyers’ attitudes and behaviors in law firm digital transformation contexts.

5.2. Practical Implications

The findings of our study provide several practical recommendations for law firms to more effectively stimulate lawyers’ supportive behaviors during digital transformation. First, law firms can enhance lawyers’ job autonomy by changing their work design during digital transformation. Our study demonstrates the positive impact of digital transformation job autonomy on lawyers’ digital transformation-supportive behaviors. By integrating originally fragmented and repetitive tasks into complete work modules, law firms can give lawyers a greater degree of responsibility and enhance their control over the overall workflow. In addition, provided that information security and system compatibility requirements are met, law firms may allow for lawyers to select their preferred digital tools, workflow paths, and platform interfaces based on individual habits, thereby increasing flexibility to adapt to collaborative model changes induced by digital tools. When the supportive behaviors of lawyers become widespread across the law firms, they may cumulatively contribute to the successful implementation of digital strategies at the organizational level (Poláková-Kersten et al., 2023; Selimović et al., 2021; Q. Zhou & Shi, 2025).

Second, law firms should actively facilitate lawyers’ cognitive adjustment in the workplace. Our study reveals that lawyers’ cognitive adjustment regarding tasks, groups, and organization can reduce their resistance and anxiety toward digital technologies, making them more willing to share application experiences and optimize digital systems. Therefore, law firms should help lawyers to understand how digitization transforms work content, collaboration patterns, and organizational systems, guiding them toward positive cognitive restructuring. Initiatives such as digital skills training programs and cross-departmental simulation exercises can enhance individuals’ digital competence and organizational cognition, consequently strengthening their supportive behaviors.

Third, we suggest that law firms should emphasize the development of empathetic leadership among managers. Our empirical research shows that leader empathy motivates managers to provide feedback and guidance that alleviates lawyers’ frustration and uncertainty, and enhances their confidence in adapting to change. Thus, when selecting leaders, law firms should assess their ability to understand lawyers’ difficulties and provide emotional support and positive feedback, as these qualities significantly influence lawyers’ performance in the workplace. Additionally, law firms may enhance leaders’ empathy and supportive behaviors through leadership training and situational simulations, creating a more psychologically safe work environment for lawyers.

5.3. Limitations and Directions for Future Research

While our study has made progress at both the theoretical and practical levels, several limitations remain to be addressed in future research. First, although we used a multi-wave design to collect the questionnaire data for empirical testing, which revealed the correlational mechanisms among variables, it cannot fully establish causal relationships. Therefore, future research can adopt experimental methods to track the psychological and behavioral changes in individuals across different digital transformation stages, thereby further validating the causal relationship between digital transformation job autonomy and individuals’ digital transformation-supportive behaviors. Moreover, we acknowledge that longitudinal survey designs are inherently subject to limitations, such as participant attrition and recall bias. Thus, studies employing longitudinal designs should consider strategies to improve retention rates, such as offering stronger incentives, shortening the survey length, and implementing systematic reminder systems.

Second, although procedural and statistical controls were applied to mitigate common method bias, the exclusive use of self-reported data may still introduce a social desirability bias. The participants might have provided responses that align with perceived expectations rather than their true attitudes. Future research should adopt multi-source data such as supervisor or peer ratings to enhance measurement validity and reduce the reliance on self-reports.

Third, our study found that cognitive adjustment in the workplace plays a mediating role in the relationship between digital transformation job autonomy and lawyers’ digital transformation-supportive behaviors. However, job autonomy has the potential to further act on individuals’ behavioral responses through other mechanisms, such as psychological safety, organizational identification, and emotional exhaustion. Therefore, in order to develop a more comprehensive theoretical model, future research can continue to explore the underlying mechanisms through which job autonomy influences individual behaviors in digital transformation contexts.

Fourth, our study mainly focused on the cognitive and behavioral responses at the individual level within the legal industry and considered the influence of leader empathy on lawyers’ cognitive adjustment and digital transformation-supportive behaviors. However, we acknowledge that factors such as organizational culture, firm size, team climate, and industry-specific characteristics may also shape employees’ perceptions of job autonomy and their adaptation strategies. For instance, law firms with a more hierarchical or risk-averse culture may constrain the positive effects of job autonomy, whereas organizations with a learning-oriented or innovation-supportive culture may amplify these effects. Similarly, differences in the level of digitization and the complexity of work tasks across industries and firms may moderate how individuals perceive and respond to job autonomy during digital transformation. Future research could explore the applicability of our model in other professional and industrial contexts. Additionally, incorporating variables such as organizational culture, team dynamics, and individual differences could provide a more comprehensive understanding of the antecedents of digital transformation-supportive behaviors.

6. Conclusions

In the process of digital transformation, lawyers are not only stakeholders in the organization, but also active participants in digital strategy formulation and the key drivers of transformation initiatives. Their support for digital transformation is critical for the successful implementation of digital transformation in the organization (Q. Zhou & Shi, 2025). Drawing on the JD-R model, we proposed and tested a moderated mediation model to explain the positive effect of digital transformation job autonomy on lawyers’ digital transformation-supportive behaviors. Specifically, digital transformation job autonomy not only directly promotes lawyers’ digital transformation-supportive behavior, but also indirectly enhances it by facilitating cognitive adjustment in the workplace. In addition, leader empathy plays an important moderating role in these relationships. When leaders demonstrate high levels of empathy, the direct effects of digital transformation job autonomy on lawyers’ digital transformation-supportive behavior and cognitive adjustment in the workplace are amplified, as well as the indirect effect of digital transformation job autonomy on lawyers’ digital transformation-supportive behaviors through cognitive adjustment. Our theoretical model is supported by the results of the regression analysis and fsQCA of the data from 423 lawyers working in law firms that had either implemented or were actively undergoing digital transformation initiatives.