Cost management constitutes a fundamental pillar of modern corporate governance. One of the primary causes of cost stickiness stems from the managerial dilemma that arises when faced with declining sales volume or revenue: whether to maintain existing costs or adjust them. This deliberation often results in costs failing to decrease proportionally with falling sales, thereby reflecting a form of managerial decision-making inertia in cost control.

In cost management, managers confronting demand declines must evaluate the trade-off between maintaining idle capacity and reallocating resources post-recovery. This analysis informs decisions regarding asset retention or divestment. Costs are classified as variable or fixed based on behavioral characteristics. Fixed costs exhibit lower adjustability, prompting firms to prioritize the regulation of variable costs during periods of short-term volatility to maintain operational flexibility. Extended downturns, however, compel fixed cost reductions to alleviate persistent losses. The asymmetric adjustment between fixed and variable costs induces cost stickiness. Elevated stickiness amplifies managerial inclinations toward resource accumulation over optimization, fostering operational redundancies.

Agency theory suggests that information asymmetry in principal-agent relationships incentivizes managers to prioritize their interests over organizational goals, resulting in inefficient resource allocation that compromises stakeholder welfare. Twardawski and Kind (2023) highlights M&A activities as strategic arenas where executives exploit informational advantages for personal benefit. The strategic imbalance between corporate expansion and contraction strategies stems fundamentally from transaction cost economics and self-interested executive decision-making.

Based on the foregoing theoretical rationale, the following hypothesis is proposed:

H1: Cost stickiness is negatively associated with corporate merger performance.

Academic investigations into the determinants of cost stickiness highlight managerial optimism as a critical behavioral driver. During sales declines, executives assess the costs of idle resource disposal, preferring to retain existing resources when anticipating transient downturns to avoid adjustment expenditures. This resource retention behavior becomes amplified under conditions of optimistic performance expectations.

Existing research indicates that overconfidence represents a prevalent psychological characteristic in human decision-making (Weinstein, 1980), particularly pronounced among corporate executives relative to the general population (Cooper and Kaplan, 1998). This cognitive bias manifests through two principal mechanisms affecting managerial conduct: self-perception distortion and excessive optimism. The former involves executives’ erroneous conviction in their ability to singularly reverse organizational decline, perpetuating existing resource commitments despite deteriorating conditions. This cognitive fallacy leads to unrealistic assessments of market recovery likelihoods, resulting in sustained investment levels during economic contractions that exacerbate cost rigidity. The latter manifestation leads overconfident managers to overestimate the accuracy of demand projections while maintaining current resource configurations, thereby compounding cost stickiness effects.

Hayward and Hambrick (1997) link managerial overconfidence to excessive M&A premiums. Overconfident executives overvalue targets’ potential, pay unwarranted premiums, and underestimate integration challenges. This results in financial losses, operational inefficiencies, and failed synergies due to unrealistic assumptions about cost control and post-merger outcomes.

Based on the above theoretical analysis, the following hypothesis is proposed:

H2: Managerial overconfidence intensifies the negative relationship between cost stickiness and corporate merger performance.

Female managers generally demonstrate greater prudence and risk aversion compared to their male counterparts (Faccio et al., 2016; Gong et al., 2022). They exhibit heightened ethical responsibility and empathy in professional contexts (Ibrahim and Angelidis, 1994), typically avoiding high-risk ventures and speculative investments in corporate decisions. Their enhanced foresight enables proactive resource reallocation to anticipate revenue declines, effectively reducing the formation of cost stickiness through superior risk management.

The intrinsic attributes of female executives systematically curb cost stickiness through three primary disciplinary mechanisms. First, their risk-averse nature discourages speculative investments (Gong et al., 2022; Faccio et al., 2016) and organizational overexpansion (Peng and Wei, 2007). Second, ethical governance rooted in altruistic principles (Martin et al., 2009; Ibrahim and Angelidis, 1994) prioritizes sustainable growth over short-term speculation. Third, they exhibit heightened accounting conservatism (Peng and Wei, 2007) and maintain restrained resource allocation practices, resisting optimistic projections even when possessing forward-looking information. These behavioral paradigms collectively enhance decision-making rationality, reducing value erosion and asymmetric cost adjustments.

Gender disparities in executive decision-making demonstrate distinct behavioral tendencies. Male decision-makers exhibit a pronounced susceptibility to cognitive biases during investment strategizing, often resulting in inefficient resource allocation due to psychological predispositions. Their risk mitigation strategies typically favor high-volatility investments for alpha generation, potentially compromising organizational value through excessive risk exposure. Female executives, conversely, exhibit systemic ethical superiority: Krishnan and Parsons (2008) empirically demonstrate 23% fewer profit-motivated violations among female-led teams, correlating with enhanced moral governance. This ethical discipline corresponds with an 18% reduction in agency costs and superior regulatory compliance, particularly evident in a decrease in power-abuse incidents. Operational methodologies further diverge, with male-centric teams demonstrating a 34% greater short-term orientation, which amplifies post-acquisition integration expenses through tactical concessions (p 0.05).

Female managerial representation affects firm outcomes through variations in risk preference and dynamics of team diversity. Minimal representation (tokenism) sustains male hegemony without substantive decision-making authority. At moderate levels, gender-based strategic polarization emerges: conflicting risk postures between majority male aggressiveness and minority female caution create organizational dissonance and opportunity costs. Critical mass dominance (female majority) enables collaborative leadership models that favor procedural innovation and evolutionary change through inclusive governance structures. According to Critical Mass Theory, when a minority group within an organization reaches a threshold proportion, it exerts material influence on organizational decision-making. Specifically, once the proportion of female executives exceeds this critical threshold, corporate leadership shifts toward a more democratic style, with the degree of democratization increasing in tandem with the representation of female executives. Beyond this inflection point, female executives authentically participate in strategic deliberations, and their perspectives gain substantive recognition and adoption.

Based on the above theoretical foundation, the following hypothesis is proposed:

H3: The proportion of female managers exerts a U-shaped moderating effect on the relationship between cost stickiness and corporate merger performance.

Aged executives leverage accumulated expertise and social acumen to develop cognitive frameworks and decision-making heuristics that produce differentiated strategic outcomes. In contrast, younger managers emphasize self-expression and organizational validation through individual capability displays, often resulting in underutilization of public information and overreliance on private data sources.

Zhang et al. (2013) identified that senior managers, despite their experiential advantages, demonstrate age-related constraints including reduced physiological vitality, cognitive rigidity, outdated expertise, and delayed responsiveness. Occupying career stages marked by professional and financial stability, these individuals frequently exhibit conservative inclinations favoring risk mitigation and organizational inertia. However, their accumulated operational wisdom and sophisticated comprehension of institutional mechanisms enable methodical strategic evaluations. The researchers characterize such decision-making paradigms as systematically deliberative and systematically integrative during the strategy development process.

Conversely, younger leadership teams tend to demonstrate a higher entrepreneurial orientation and risk appetite, which may boost returns during growth periods but heighten vulnerability during contractions. Delayed cost adjustments during revenue declines exacerbate cost stickiness by leading to resource misallocation. In contrast, seasoned executives leverage accumulated experience and adaptive responsiveness to enhance risk management. Their organizational memory and reputation awareness facilitate contextually informed solutions aligned with strategic priorities.

Intergenerational managerial disparities manifest in experiential capital, cognitive patterns, and risk calculus. Senior executives exhibit institutionally anchored decision-making, characterized by structured analysis and compliance with governance, albeit with diminished cognitive agility and resistance to innovation. Junior counterparts demonstrate intuitive problem-solving with elevated risk propensity and creative initiative, yet are constrained by experiential deficits and occasional impulsivity. This generational polarity generates complementary competencies while introducing operational tensions in organizational ecosystems.

Avolio et al. (1990) found that while increasing age initially enhances performance through heightened motivation, further age advancement correlates negatively with performance due to declining ability levels, stricter evaluations, and reduced momentum. Consequently, studies posit an inverted U-shaped relationship between age and performance. This curvilinear pattern is empirically supported by both graphical evidence and the statistically significant negative coefficient of the age-squared term in regression models. Empirical studies suggest that organizational performance peaks when top executives are aged 33–48, an interval demonstrating optimal adaptability to market dynamics. Beyond this threshold, advancing age is correlated with a diminished risk tolerance and innovation capabilities, thereby fostering conservative decision-making patterns. Such stability-focused approaches generally yield incremental but sustained organizational improvements.

In light of the foregoing discussion, the following hypothesis is proposed:

H4: The average age of managers exerts an inverted U-shaped moderating effect on the relationship between cost stickiness and corporate merger performance.

Following the methodology of Kravet et al. (2018), this study measures corporate merger performance using the growth rate of Return on Equity (ROE). The calculation is defined as:

MA = (ROE_t – ROE_t–1)/ROE_t–1

Where ROE_t denotes the ROE in the year of the merger, and ROE_t–1 represents the ROE from the year prior. A higher value indicates better post-merger performance.

While the Anderson Banker and Janakiraman (ABJ) model is widely utilized in cost stickiness research, it lacks the capacity to quantify the degree of stickiness. To address this limitation, Weiss (2010) proposed an enhanced model framework enabling quantification. This study first computes the specific value of cost stickiness and subsequently incorporates it as the core independent variable in the analytical Model, thereby enhancing empirical reliability. The formula is as follows:

(1)$$STICK{Y}_{i,t}=log(\frac{\mathrm{\Delta }Cost}{\mathrm{\Delta }Sale}){}_{i,\omega 1}-log(\frac{\mathrm{\Delta }Cost}{\mathrm{\Delta }Sale}){}_{i,\omega 2}$$

Here, $\omega$1 and $\omega$2 represent the quarters nearest to the fiscal year-end in which firm i’s revenue increases and decreases, respectively. $\mathrm{\Delta }$Sale and $\mathrm{\Delta }$Cost indicate the changes in operating revenue and total cost, respectively, for firm i in quarter $\omega$_j (j = 1, 2) of year t. Total cost is the sum of operating costs, selling expenses, and administrative expenses. The computed cost stickiness represents firm i’s cost stickiness in year t. A positive STICKY value suggests that cost increases following revenue growth outweigh cost reductions during revenue decline, evidencing the presence of cost stickiness.

Following Weiss’s negative-value methodology, this study reverses the signs of calculated values to align the variation direction with the intensity of cost stickiness, thereby enhancing the clarity of regression interpretation. Robustness checks employ alternative cost stickiness metrics to verify findings.

Drawing on Tang et al. (2023), this study introduces three managerial characteristics as moderating variables:

(1) Managerial overconfidence = Total compensation of the top three executives/Total compensation of all executives; Cross-validation was conducted using managerial tone manipulation, denoted as ABTONE.

(2) Proportion of Female Executives = Number of female executives/Total number of executives.

(3) Average Age of Executives = Total age of all executives/Number of executives.

Drawing on the methodology of Bradley et al. (2011), absorbed slack is measured by the ratio of Selling, General, and Administrative expenses (SG&A) to operating revenue. A higher value of this ratio indicates a greater degree of absorbed slack within the firm, reflecting the presence of more idle resources that are difficult to reconfigure or identify within the organization.

The earnings management level is commonly used in the literature to gauge accounting information quality. Following Dechow et al. (1995), this study employs the Modified Jones Model to measure accounting information quality. The specific methodology is as follows:

(2)$$\frac{T{A}_t}{A_{t-1}}={\beta }_0\frac{1}{A_{t-1}}+{\beta }_1\frac{\mathrm{\Delta }RE{V}_t-\mathrm{\Delta }RE{C}_t}{A_{t-1}}+{\beta }_2\frac{PP{E}_t}{A_{t-1}}+{\epsilon }_t$$

t denotes the current year of the sample, while t–1 refers to the preceding year. Total accruals, year-end total assets, changes in operating revenue, changes in accounts receivable, and net fixed assets at year-end are represented by TA_t, A_t–1, $\mathrm{\Delta }$REV_t, $\mathrm{\Delta }$REC_t, and PPE_t, respectively. The manipulable portion of accruals is denoted by $|$E_t$|$, and its absolute value is expressed as absDA. A greater absDA indicates a stronger degree of earnings manipulation, reflecting a lower quality of corporate accounting information.

Following the frameworks of Liu et al. (2021), Bai et al. (2025), and Gu (2023), the specific list of controlled variables is presented in Table 1. Detailed definitions and measurement methods for all variables are presented in Table 1.

Table 2 summarizes descriptive statistics for model variables. Merger performance (MA) exhibits notable variation, with values ranging from 7.341 to –23.814, reflecting substantial heterogeneity in outcomes across sampled firms. While some achieved post-merger profitability gains, others experienced significant declines in profitability. The negative mean value (–0.604) indicates that overall, merger outcomes are suboptimal, suggesting that anticipated synergies have not been achieved. A standard deviation of 3.472 further confirms pronounced performance volatility, underscoring the complex dynamics influencing merger success in the sample.

The cost stickiness (STICKY) exhibits substantial variation (range: –7.92 to 10.288), indicating potential anomalous cost management practices among certain firms. The mean leverage ratio (LEV) of 0.433 suggests that while corporate debt levels remain generally manageable, opportunities exist for optimizing financial structures.

The average fixed asset ratio (Fixed) stands at 20.4%, indicating a significant allocation of capital to fixed assets. Total asset turnover (TA) averages 0.624 (range: 0.084–2.586), revealing notable disparities in asset utilization efficiency across firms, which necessitate enhanced asset management strategies. Core revenue growth (Growth) demonstrates substantial variation (–0.522–2.359), further underscoring heterogeneous business expansion patterns within the sample cohort.

Table 3 displays correlation analysis outcomes, revealing a significant negative relationship between cost stickiness and merger performance at the 1% level. Control variables demonstrate differentiated associations: Acquirer size (Size), asset turnover (TA), and core business growth (Growth) show positive correlations with merger performance (1% significance). Conversely, leverage ratio (LEV) and debt ratio (Debt) exhibit negative correlations at the 1% level, while fixed asset ratio (Fixed) presents a weaker negative correlation (5% significance).

This study employs a fixed-effects model that controls for both firm-level and year-specific effects. Table 4 reports the results of Model 1. Column (1) presents the regression of cost stickiness on merger performance. The coefficient of cost stickiness (STICKY) is –0.414 and is statistically significant at the 1% level. This suggests that cost stickiness has a significant impact on merger performance. When cost stickiness intensifies, managers tend to allocate resources inefficiently and escalate investments, resulting in redundant capacity. As market demand fluctuates, the disjunction between resource allocation and production becomes more pronounced, directly undermining capital efficiency. This deterioration in synergy ultimately erodes firm value. For each one-unit increase in cost stickiness, M&A performance decreases by an average of 0.414 units.

Column (2) of Table 4 reports the regression results for cost stickiness, managerial overconfidence, and merger performance. The coefficient of cost stickiness is –0.235 and remains significant at the 1% level. The interaction term between cost stickiness and managerial overconfidence is –0.273, statistically significant at the 5% level, thereby confirming that overconfident managers exacerbate the negative impact of cost stickiness on merger outcomes. Column (3) of Table 4 presents the relationship between cost stickiness, managerial tone manipulation, and M&A performance. The coefficient on cost stickiness is –0.454, statistically significant at the 1% level. The interaction term coefficient is –0.801, significantly negative at the 1% level, indicating that managerial tone manipulation exacerbates the negative relationship between cost stickiness and M&A performance. This further validates that managerial overconfidence intensifies this negative association.

Column (4) examines the moderating effect of the proportion of female executives. The coefficient of the interaction term between cost stickiness and the female executive ratio is –0.365, which is significant at the 10% level, while the squared interaction term is 1.765, which is also significant at the 10% level. The coefficients are both significant and exhibit opposite signs, confirming a U-shaped moderating effect. The turning point is calculated as –$\beta$₄/2$\beta$₅ = 0.103. To mitigate multicollinearity, all moderating variables were mean-centered. The adjusted turning point is 0.296 when added to the uncentered mean value. This suggests that when the proportion of female executives is below 29.6%, an increase in female representation intensifies the negative relationship between cost stickiness and merger performance; when the proportion exceeds 29.6%, greater female representation alleviates the adverse effect. The effect is weakest at approximately 30% female composition, where the benefits of team diversity are maximized.

Column (5) of Table 4 explores the role of average managerial age. The coefficient for the interaction term between cost stickiness and average age is 0.024, while the squared interaction term is –0.002; both are statistically significant. The opposite signs and the negative quadratic coefficient indicate an inverted U-shaped moderating effect: the initially positive influence of managerial age gradually reverses with further aging. The turning point is calculated as 6. After accounting for centering, the actual threshold becomes 55.31 years (mean plus turning point). Thus, when the average age is below 55.31, an increase in age weakens the negative relationship between cost stickiness and merger performance; when it exceeds 55.31, the adverse impact is exacerbated.

To mitigate potential endogeneity in the explanatory variable, this study employs an instrumental variable (IV) approach using the industry-year average cost stickiness (mean_sticky) as the IV, following Binhua and Boyuan (2024), within a two-stage least squares (2SLS) framework. Dual rationales justify this selection: First, industry-level cost stickiness exhibits exogenous relevance as it does not directly affect firm-specific merger outcomes. Second, its derivation from aggregated firm-level data ensures a substantial correlation with the endogenous variable, effectively addressing concerns about weak instruments.

The Kleibergen-Paap rk LM statistic is 194.035 (p = 0.000), confirming that the Model passes the under-identification test. The first-stage regression coefficient of the instrument on the endogenous variable is highly significant at the 1% level (F = 752.17, p = 0.000), and the Cragg-Donald Wald F-statistic far exceeds the conventional threshold for weak instrument diagnosis, affirming the adequacy of instrument relevance.

Column (1) of Table 5 reports the first-stage regression, where the coefficient of the industry-year average cost stickiness is significantly negative, indicating its positive association with firm-level cost stickiness. Column (2) presents the second-stage results, where cost stickiness remains significantly negatively related to merger performance, confirming that the main findings are robust to endogeneity concerns.

To explore the causal relationship between cost stickiness and merger performance, the ideal comparison would involve evaluating the same firm’s performance under both the presence and absence of cost stickiness—an inherently unobservable counterfactual. To address this limitation and control for selection bias, propensity score matching is employed to approximate a quasi-experimental setting. Firms with cost stickiness levels above the industry-year median are classified as the treatment group, while the control group comprises firms closely matched on key covariates drawn from the baseline regression. Radius matching is performed based on these covariates.

As shown in Column (3) of Table 5, the regression results confirm that cost stickiness remains significantly negatively associated with merger performance, lending further support to the robustness of the primary findings.

To assess whether the Model suffers from spurious correlation or false causal inference, a placebo test is conducted by randomly generating a pseudo-treatment variable, STICKY_fake. If the coefficient of STICKY_fake were to remain significant, it would suggest that the observed relationship may be driven by confounding factors or model misspecification. Conversely, an insignificant coefficient would further validate the authenticity of the findings.

Column (4) of Table 5 reports that STICKY_fake is statistically insignificant, indicating no association with merger performance. Given the large sample size, the likelihood of coincidental significance is minimal, and thus, a single iteration suffices to confirm robustness; repeated placebo simulations are deemed unnecessary.

As a further robustness check, cost stickiness is redefined as a binary variable, STICKY_new, based on the sample median. Firms with cost stickiness above the median are assigned a value of 1 (high stickiness), and those below a value of 0 (low stickiness). The Model is re-estimated using the baseline regression approach.

Column (5) of Table 5 presents the results. Although the regression coefficient differs slightly from the baseline model, it remains significantly negative at the 1% level (coefficient: –0.592), reaffirming the inverse relationship between cost stickiness and merger performance. Specifically, higher cost stickiness continues to predict poorer merger outcomes.

Given that when ROE_t–1 is close to zero or negative, it may have a significant impact on MA and introduce potential biases, this study first calculates the proportion of values close to zero or negative and finds that only 8% of the values fall into this category. Drawing on the approach of Freeman and Tse (1992), this study removes the abnormal values and conducts a regression on the sample. The results are consistent with those of the main regression, indicating the robustness of the findings.

Drawing on the approach of Barber and Lyon (1996), this study employs the industry-adjusted return on equity to measure merger and acquisition performance. This is done to mitigate the potential impact of the denominator on the measurement results of merger and acquisition performance when ROE_t–1 is close to zero or negative. The results are consistent with those of the main regression, indicating robustness.

Under cost stickiness conditions, managers tend to retain existing operations or inefficient capacity during downturns, leading to a disconnect between cost changes and operational scale. Organizational slack manifests as two distinct forms based on resource utilization: absorbed slack, which is operationally embedded and resistant to reallocation, and unabsorbed slack, characterized by idle resources with high redeployment flexibility.

Absorbed slack, marked by low liquidity, requires significant temporal and financial investments for reconfiguration, often resulting in resource wastage, managerial inefficiencies, and internal discord. These factors divert strategic focus and exacerbate post-merger integration challenges, ultimately eroding synergistic benefits and undermining merger performance. Conversely, unabsorbed slack demonstrates operational agility, enabling rapid redeployment to facilitate resource alignment and enhance post-merger operational efficacy.

Accordingly, absorbed slack is posited as a mediating variable in the relationship between cost stickiness and merger performance. Following the methodology proposed by Preacher (2015), this study constructs Eqns. 7,8,9 to examine whether absorbed slack mediates the effect of cost stickiness on merger performance.

(7)$$M{A}_{i,t}={\beta }_0+{\beta }_{1}STICK{Y}_{i,t}+{\beta }_{k}Controls+YEAR$$ $$+ FIRM+\epsilon$$

(8)$$abslac{k}_{i,t}={\beta }_0+{\beta }_{1}STICK{Y}_{i,t}+{\beta }_{k}Controls+$$ $$YEAR+FIRM+\epsilon$$

(9)$$M{A}_{i,t}={\beta }_0+{\beta }_{1}STICK{Y}_{i,t}+{\beta }_{2}Abslac{k}_{i,t}+$$ $${\beta }_{k}Controls+YEAR+FIRM+\epsilon$$

To examine the mediating role of absorbed slack in the relationship between cost stickiness and merger performance, this study conducts tests based on Models (7) through (9). The results presented in Table 6 are as follows: Column (1) reports a coefficient of –0.414 for cost stickiness, significant at the 1% level, reaffirming its suppressive effect on merger performance and lending support to Hypothesis 1. Column (2) demonstrates that cost stickiness has a significantly positive effect on absorbed slack. In Column (3), after introducing absorbed slack into the Model, the coefficient of cost stickiness decreases slightly from –0.414 to –0.405, while the coefficient for absorbed slack is –0.027. The Sobel test confirms a partial mediating effect, indicating that cost stickiness impairs merger performance in part by increasing the level of absorbed slack.

Cost stickiness refers to the asymmetric cost behavior exhibited by firms, where expenses increase with rising activity levels but exhibit downward rigidity during periods of operational contraction. Cost stickiness signals adverse operational conditions to external stakeholders. To sustain going-concern viability, management may engage in earnings manipulation, thereby eroding the credibility of financial data. In mergers and acquisitions, firms with elevated cost stickiness exhibit a greater propensity to camouflage operational distress through artificial earnings adjustments. Such enterprises typically employ accounting engineering techniques to manipulate profits, disseminating favorable signals to market investors to alleviate financing constraints. These earnings management activities impair the relevance and reliability of financial information. High-quality accounting information facilitates efficient M&A transactions and reduces information asymmetry costs, enabling investors to accurately assess deal value while mitigating post-merger integration frictions, ultimately enhancing synergy realization. Conversely, manipulated accounting data is inherently of low quality and subject to future reversals, thereby depressing M&A performance.

Following the methodology of Preacher (2015), this study constructs Eqns. 10 and 11 to examine whether accounting information quality serves as a mediating variable in the relationship between cost stickiness and merger performance.

(10)$$AbsD{A}_{i,t}={\beta }_0+{\beta }_{1}STICK{Y}_{i,t}+{\beta }_{2}Siz{e}_{i,t}+$$ $${\beta }_{3}LE{V}_{i,t}+{\beta }_{4}Fixe{d}_{i,t}+{\beta }_{5}T{A}_{i,t}+$$ $${\beta }_{6}SO{E}_{i,t}+{\beta }_{7}growt{h}_{i,t}+{\beta }_{8}deb{t}_{i,t}+$$ $${\beta }_{9}C{I}_{i,t}+YEAR+FIRM+\epsilon$$

(11)$$M{A}_{i,t}={\beta }_0+{\beta }_{1}STICK{Y}_{i,t}+{\beta }_{2}AbsD{A}_{i,t}+$$ $${\beta }_{3}Siz{e}_{i,t}+{\beta }_{4}LE{V}_{i,t}+{\beta }_{5}Fixe{d}_{i,t}+$$ $${\beta }_{6}T{A}_{i,t}+{\beta }_{7}SO{E}_{i,t}+{\beta }_{8}growt{h}_{i,t}+$$ $${\beta }_{9}deb{t}_{i,t}+{\beta }_{10}C{I}_{i,t}+YEAR+FIRM+\epsilon$$

To test the mediating effect of accounting information quality, Models (10) and (11) are employed for empirical validation. The results presented in Table 6 are as follows: Column (1) reports a coefficient of –0.414 for cost stickiness (p 0.01), confirming its significant suppressive effect on merger performance and supporting Hypothesis 1. Column (4), where accounting information quality is the dependent variable, shows a cost stickiness coefficient of 0.302 (p 0.01), indicating a positive association between the two.

In Column (5), after incorporating the mediating variable, accounting information quality demonstrates a significant transmission effect in the pathway from cost stickiness to merger performance. Specifically, the coefficient for cost stickiness declines from –0.414 in Column (1) to –0.385 in Column (5), while the coefficient for accounting information quality is 0.302 in Column (4) and –0.095 in Column (5), both significant at the 1% level. Together with the results of the Sobel test, these findings confirm that accounting information quality partially mediates the relationship between cost stickiness and merger performance. In essence, cost stickiness impairs merger outcomes by undermining the credibility and quality of financial reporting.

As an external governance mechanism rooted in industry dynamics, market competition shapes corporate behavior through two critical pathways. First, competitive intensity increases operational transparency as firms disclose critical information to sustain market positions, facilitating shareholder oversight and reducing agency costs through enhanced monitoring. Second, competitive pressures drive organizations to systematically eliminate inefficiencies and prevent post-M&A resource redundancy, thereby aligning managerial priorities with shareholder interests through strengthened accountability frameworks.

Second, intense market competition compels firms to prioritize operational efficiency. Survival pressures incentivize managers to optimize processes, accelerate innovation, and enhance performance—actions that collectively activate managerial initiative while strengthening governance capacities. Concurrently, market discipline drives improved resource allocation and managerial effectiveness, establishing a self-reinforcing cycle of governance enhancement.

In highly competitive industries, managerial complacency becomes unsustainable as executives employ strategic vigilance and professional rigor to safeguard profitability and career capital against reputational risks. Within this paradigm, mergers are primarily driven by strategic imperatives rather than operational synergies, with accumulated strategic benefits potentially mitigating the effects of cost rigidity.

In summary, the analysis suggests that within highly competitive industries, managerial prudence in decision-making mitigates the emergence of cost stickiness, while strategically motivated mergers offset its detrimental effects. These dual mechanisms synergistically alleviate the negative influence of cost stickiness on merger performance through complementary pathways.

This study utilizes the Herfindahl-Hirschman Index (HHI) to measure industry competition intensity, with elevated HHI values reflecting heightened competitive pressures. As shown in Table 7, the analysis reveals a significantly negative coefficient (–0.527, p 0.01) for cost stickiness and a positive interaction coefficient (0.249, p 0.01) with HHI. These results demonstrate that increased market concentration substantially mitigates the adverse impact of cost stickiness on merger performance.

Superior ESG performance mitigates cost stickiness by optimizing cost adjustment efficiency and alleviating agency conflicts. The inherent asymmetry in adjustment costs—lower for upward adjustments versus higher for downward adjustments—underpins cost stickiness. Robust ESG frameworks foster stakeholder trust, reducing environmental uncertainty and lowering communication and transaction costs. Simultaneously, enhanced ESG credentials attract investments, diminishing resource friction during strategic adaptations and curbing cost stickiness.

A robust ESG system constrains such managerial discretion through sound governance structures, while its disclosure mechanisms increase operational transparency, enabling stakeholders to exercise effective oversight. These dual mechanisms enhance firms’ responsiveness to cost control.

Throughout the merger process, information asymmetry among transacting parties poses a persistent barrier to effective resource integration. This asymmetry spans all stages of the M&A lifecycle—from pre-merger planning and deal execution to post-merger integration.

The disclosure of ESG data mitigates information asymmetry. Companies demonstrating robust ESG performance align with stakeholder expectations through social responsibility initiatives, strengthening organizational cohesion and operational efficiency (Li et al., 2021). Sustained ESG commitment cultivates competitive advantages and positively influences merger outcomes. High-quality ESG practices facilitate cross-functional collaboration, enhance risk identification through transparency, and optimize decision-making processes, thereby improving the effectiveness of post-merger integration. These efforts signal corporate dedication to sustainable development and operational resilience, which supports long-term value creation. Mergers serve as strategic mechanisms for driving corporate growth and fostering long-term development.

Following the methodology of Xie and Lyu (2022), this study utilizes the Huazheng ESG scoring system, which assigns firms a score on a 100-point scale and categorizes them into nine tiers, ranging from AAA to C, alongside four risk categories: Low Risk, Watchlist, Warning, and Severe Warning. Higher scores denote stronger ESG performance.

Regression results in Table 7 show that the coefficient for cost stickiness is –0.662, significant at the 1% level, while the interaction term is 0.274, significant at the 10% level. These findings indicate that ESG performance effectively moderates the adverse relationship between cost stickiness and merger performance.

A robust internal control system enhances financial reporting accuracy while advancing operational efficiency and strategic objectives. Capital review mechanisms utilizing cost-benefit analysis facilitate proactive project assessment, systematically eliminating inefficient investments. These protocols prevent resource misallocation, deter managerial short-termism, and enhance the precision of allocation. Comprehensive control activities sustain financial integrity through full-cycle monitoring, effectively reducing budgetary variances.

A standardized information-transmission framework enhances managerial decision-making by delivering comprehensive data, thereby improving capital oversight accuracy and alleviating cost stickiness through optimized internal controls. During mergers, this system operates through three mechanisms: (1) mitigating information asymmetry, (2) resolving principal-agent conflicts, and (3) restructuring governance architecture. The framework’s strategic filtering capability eliminates extraneous information during decision formulation, enabling data-driven solution optimization through professional analytics. Empirical evidence confirms a positive correlation between the framework and enhanced merger performance.

This study employs the DIB internal control scoring system to evaluate internal control quality, where higher scores indicate superior internal governance. According to Table 7, the coefficient for cost stickiness is –0.600, significant at the 1% level, while the interaction term is 0.106, significant at the 5% level. These results suggest that internal control has a significant moderating effect on the adverse relationship between cost stickiness and merger performance.

A sound governance structure reduces internal information asymmetry, constrains self-serving managerial behavior, and curbs excess operating costs stemming from inadequate oversight. Ownership concentration stands as a pivotal element of corporate governance.

Large shareholders exhibit stronger incentives than minority holders to exercise vigilant oversight, mitigating agency costs and improving performance. Concentrated ownership enhances objective alignment and coordination efficiency among stakeholders while curbing free-riding tendencies. The consolidation of capital empowers major stakeholders with heightened monitoring capacity and strategic influence, enabling more effective restraint of managerial discretion. This governance mechanism ensures decision-making rationality by anchoring strategic choices in operational realities through enhanced oversight authority.

The oversight mechanism aligns strategic planning with organizational objectives, enhances managerial accountability, and optimizes performance. Agency theory highlights the inherent misalignments between the owner’s and manager’s goals. Shareholders bear fixed monitoring costs, with major shareholders demonstrating a proportional willingness to bear costs relative to their equity stakes to ensure returns. Conversely, dispersed ownership reduces the incentives for minority shareholders to incur additional monitoring expenditures.

This study measures ownership concentration using the shareholding ratio of the largest shareholder. The higher values indicate greater concentration. Table 7 reveals that the coefficient for cost stickiness is –0.743, which is significant at the 1% level. The interaction term is also significant at the 1% level, with a value of 0.010. These findings confirm that ownership concentration moderates and mitigates the negative impact of cost stickiness on merger performance.

Mergers and acquisitions are classified as related or unrelated based on the degree of industry alignment between the acquiring and target firms. As hypothesized (H1), cost stickiness negatively correlates with merger performance. However, related and unrelated mergers demonstrate differential synergy potential and integration complexity. Specifically, related M&A enables intra-industry consolidation that promotes scale economies, reduces redundancy and adjustment costs, facilitates the transfer of managerial expertise, and standardizes operational processes - thereby enhancing cost flexibility through optimized resource allocation mechanisms.

In contrast, unrelated mergers often span across the supply chain or even across industries, facing challenges such as technological incompatibility, asset specificity, and heightened managerial complexity, all of which can lead to resource dispersion and increased agency costs.

Column (1) of Table 8 presents the regression results for unrelated mergers, showing a cost stickiness coefficient of –0.421, which is significantly negative at the 1% level of significance. Column (2) presents the results for related mergers, where the coefficient is –0.278 and is statistically insignificant. These findings suggest that the negative impact of cost stickiness on merger performance is particularly pronounced in unrelated mergers and acquisitions (M&A) contexts. A Fisher test confirms that the negative effect of cost stickiness on merger performance is significantly more severe in unrelated mergers.

M&A activities can be categorized as either cross-border or domestic. Cross-border transactions inherently involve foreign exchange settlements, where fluctuations in exchange rates increase transaction costs. While hedging instruments reduce currency risk exposure, they require sustained capital allocation and escalate adjustment expenditures. Insufficient realization of post-merger synergies may exacerbate cash flow constraints, thereby intensifying the negative impacts of cost rigidity.

Cross-border transactions face regulatory challenges (e.g., antitrust reviews, tax compliance) that incur substantial compliance costs and political sensitivities. Host government interventions may trigger delays or cancellations, amplifying operational uncertainties and financial risks. Furthermore, cultural differences impede post-merger integration through clashes in managerial philosophy and divergent decision-making frameworks, prolonging organizational alignment, compromising market entry schedules, and ultimately reducing the effectiveness of the merger.

In contrast, domestic mergers benefit from central bank liquidity support, which alleviates short-term funding pressures and reduces cost rigidity. Familiarity with the domestic supply chain and regulatory environment further facilitates post-merger integration. Compared to cross-border transactions, domestic mergers are less encumbered by institutional and cultural frictions, making cost structure adjustments more feasible.

Column (3) of Table 8 reports the results for cross-border mergers, showing a cost stickiness coefficient of –0.436, significantly negative at the 1% level. Column (4) displays results for domestic mergers, with a coefficient of –0.405, which is also significant at the 1% level. A Fisher test confirms that the negative effect of cost stickiness on merger performance is significantly more severe in cross-border mergers.

M&A transactions are classified by payment method into cash and non-cash (stock/mixed). Cash transactions impose immediate liquidity constraints, prompting cost optimization via operational streamlining, unit closures, and asset divestitures to mitigate cost stickiness. Cash payments simultaneously signal financial stability, stabilizing stock valuations and reinforcing investor confidence. Additionally, cash transactions strengthen post-merger managerial control, facilitating accelerated cost optimization and reducing organizational inertia during integration.

In contrast, non-cash payments dilute ownership structures, weakening managerial commitment to long-term cost efficiency in the face of short-term performance imperatives. Stock transactions depend critically on mutual valuation consensus; underperforming post-merger synergies risk triggering goodwill impairment due to overvaluation, which can subsequently diminish profitability. Such transactions also require heightened stakeholder alignment, which can prolong decision hierarchies and erode integration control, ultimately degrading the efficacy of mergers.

Column (5) of Table 8 reports results for firms using non-cash payment methods, with a cost stickiness coefficient of –0.452, significantly negative at the 1% level. Column (6) presents results for cash-based transactions, where the coefficient is –0.329, also significant at the 1% level. A Fisher test confirms that the negative impact of cost stickiness on merger performance is more pronounced among firms utilizing non-cash payments.