From greenwashing to green transformation: evidence from mergers and acquisitions Open Access

The benefits that firms derive from a focus on Environmental, Social and Governance (ESG) factors include increased reputation (Boone and Uysal, 2020), lower cost of capital (Fatemi et al., 2015) and stronger stakeholder commitment (Arouri et al., 2019; Deng et al., 2013). To attract the financial benefits associated with improved ESG practices, firms face pressure from external stakeholders through channels such as social media campaigns (Du, 2015; Lyon and Montgomery, 2013) to address substandard ESG activities. Firms with poor ESG performance or that operate in ESG-sensitive industries are particularly exposed to such pressure. These firms are highly visible to the public and attract greater scrutiny from a variety of different stakeholders (Bowen, 2000; Marquis et al., 2016).

While some firms make genuine efforts and progress to become more environmentally friendly, or greener, others engage in an activity known as “greenwashing” to mask poor environmental impacts. For example, a firm may make public statements to convey an image of strong environmental credentials but make no material changes to its underlying operations (Delmas and Burbano, 2011; Garrow and Valentine, 2012) or engage in actions that contradict their stated environmental objectives. Greenwashing may be especially severe amongst firms in ESG-sensitive sectors such as the chemical, oil and gas and mining industries.

One approach to respond to stakeholder pressure to address a firm's poor ESG practices is to acquire a firm with higher ESG metrics (Li et al., 2020b). Acquirers that engage in mergers and acquisitions (M&As) with “green” target firms can access the target's ESG practices, leading to improved ESG practices (Pfeffer and Salancik, 1978). Such deals help the acquiring firm enhance its own sustainability practices while simultaneously satisfying stakeholders' ESG demands. A second motivation to acquire a firm with a higher ESG score is to maintain the illusion that the acquirer is “green.” These acquisitions are not intended to integrate the target's ESG practices. The purpose of such deals is to convey an apparent signal of a green transformation to the market (Bryant et al., 2020; Li et al., 2020b).

An example of using M&A to transform a business is the acquisition of Burt's Bees by The Clorox Company (Clorox) in 2007 (Story, 2008). With increased pressure from customers for green products, bleach manufacturer Clorox paid close to $1 billion to acquire Burt's Bees, a green manufacturer of beeswax-related products. Clorox claimed that it was expecting to learn the environmental practices of Burt's Bees in an effort to make its own products eco-friendlier. Clorox's history of greenwashing prior to the deal caused skepticism, partially on account of vague reporting on its environmental programs (Conley, 2012; Story, 2008). However, following the merger, Clorox introduced a new range of cleaning products made from 99% natural ingredients, known as Green Works, leading to a substantial increase in its ESG rating.

In addition to media attention, greenwashing has also attracted a substantial body of academic research. Most greenwashing studies focus on environmental aspects (Du, 2015; Marquis et al., 2016; Testa et al., 2018; Walker and Wan, 2012). However, Lyon and Maxwell (2011) and Yu et al. (2020) contend that social and governance are also subject to greenwashing. Controversy is not restricted to environmentally motivated M&A deals. For example, in 2006, L'Oréal of France, a firm associated with animal testing of its cosmetics products, acquired Body Shop International, which is committed to no animal testing of its products ^[1]. In 2021, tobacco manufacturer Phillip Morris International Inc acquired Vectura Group plc, a British health care company ^[2]. These controversial deals highlight the emergence of social components in a broader greenwashing scope. Therefore, we examine all three ESG components to explore greenwashing in M&A deals.

Our measure of greenwashing is motivated by Seele and Gatti (2017). They suggest that greenwashing occurs when an external party, such as the media, accuses a company of acting in a manner that contradicts the information it publicly communicates to its external stakeholders. Identifying and measuring, greenwashing is possible through the controversy that arises from an allegation of ESG-wrongdoing. Consequently, we use the ESG controversies (ESGC) score from the Refinitiv ESG Database as a proxy for greenwashing. In contrast to ESG ratings that are based on a firm's stated ESG principles, the ESGC score also incorporates actions that are contrary to its publicly disclosed ESG commitments.

In this paper, we investigate whether M&A deals are used as a channel to improve ESG practices or used for further greenwashing. First, we examine whether greenwashing firms purchase targets with higher ESG ratings. Second, we investigate how the market reacts to such deal announcements. Third, we study the relationship between the pre-merger relative ESG performance of targets and acquirers' level of greenwashing post-merger. Examining both the short-term market reaction and the extent of greenwashing of the merged entity helps us answer the question of whether greenwashing acquirers legitimately transform their ESG practices or simply engage in further greenwashing through M&A deals.

While the short-term market reaction suggests these deals are greenwashing-motivated, over the longer one-year period following the deal, we document evidence of a legitimate green transformation. Firms with higher levels of greenwashing acquire targets with ESGC scores that are significantly larger than the acquirer's scores. Furthermore, acquirers' cumulative abnormal returns around the deal announcement dates are significantly more negative for firms with higher greenwashing scores. This result indicates that the market reacts negatively to the deal, and the negative response is more pronounced when the target firm has a higher ESGC rating. However, this initial skepticism over the stockholder value created through the transaction abates one year after the deal announcement. We find that the acquisition of a target with a higher relative ESGC score results in a significant reduction in the acquirers' greenwashing score following the deal. In further analysis, we rule out alternative explanations for our results. The negative announcement-period return cannot be explained by the acquirer overpaying for the target, and the propensity score matching method demonstrates that greenwashing firms exhibit significantly lower returns than their non-greenwashing counterparts, further supporting our hypotheses.

We make several important contributions. First, we find that acquirers with higher levels of greenwashing acquire targets with higher relative ESGC scores. We also provide evidence that these deals lead to lower greenwashing following the merger, confirming a green transformation. Our findings are consistent with both the resource dependence theory and the organizational learning theory (Pfeffer and Salancik, 1978), which suggests acquirers integrate a target's ESG practices. A decrease in the level of greenwashing by an acquirer after a merger enriches the benefits of green deals studied in previous literature. Li et al. (2020b) show that acquiring a highly sustainable target helps an acquirer improve its legitimacy, which is measured by greater access to resources, lower financial constraints and reduced tax liability. Green deals also boost acquirers' business model innovation and sustainability (Li et al., 2020a).

Second, we shed light on how the market perceives deals that involve greenwashing acquirers and higher-rated ESG targets in the context of M&A's. Our finding of a negative market reaction to the deal is consistent with the attribution theory (Parguel et al., 2011). Seele and Gatti (2017) contend that there is information asymmetry between acquirers and the market. Without information regarding the intention of acquirers, the market extrapolates acquirers' greenwashing history and responds negatively to the deal announcement. Our result complements Du (2015), who finds a negative market reaction when a firm is accused of greenwashing, with a more negative response for firms with higher ESGC scores. Previous studies find that the ESG ratings of acquirers and target firms have a positive impact on deal performance, including deal announcement returns, long-term buy-and-hold abnormal returns (Deng et al., 2013) and accounting-based return measures (Tampakoudis and Anagnostopoulou, 2020). In contrast to using ESG ratings, we use ESGC scores to better proxy for greenwashing activity and find a negative relationship between target firms' ESGC score and deal announcement returns.

Firms with responsible ESG practices that engage in environmentally transformative initiatives convey a signal of their genuine sustainability concerns to stakeholders (Torelli et al., 2019). However, while firms may publicly claim to maintain responsible ESG credentials, they may engage in actions that are contrary to those claims in a practice known as greenwashing. Due to its multifaceted nature, there is no universally agreed definition of greenwashing. One definition relates greenwashing to selective disclosure. Delmas and Burbano (2011) and Marquis et al. (2016) define greenwashing as the act of misleading consumers regarding a firm's questionable environmental activities through positive communication.

Walker and Wan (2012) and Siano et al. (2017) contend that greenwashing occurs when a firm engages in “green talk.” This language is merely a symbolic action designed to satisfy stakeholders' demands to address sustainability issues. In other words, firms fail to fulfil their commitments on environmental concerns in order to alleviate external public pressure on sustainability (Guo et al., 2018). Seele and Gatti (2017) suggest that greenwashing should combine the two elements of falsity and accusation of misleading information. Without a third party accusing a firm of actions contrary to its stated ESG commitments, the greenwashing remains undetected. Following their approach, we define greenwashing as a firm's misleading behavior, which is alleged and publicly reported by external monitors such as the media or environmental organizations.

Li et al. (2020b) refer to green M&As as the acquisition of a green target, which has energy-saving or emission-reduction technologies, by an acquiring firm that is a heavy polluter. The purpose of these deals is to transform an acquirer's operations by obtaining access to the target's green resources and improving green practice (Lu, 2021). Therefore, a green deal may be characterized by a deal where a firm acquires a target with a higher level of “green” credentials. Nguyen et al. (2025) report evidence consistent with this description.

There are two views on the acquisition of a higher ESG-rated target by a greenwashing entity. On the one hand, the acquirer may not actually adopt the target's ESG practices but instead uses the M&A deal to mislead the market regarding its intentions. Wang et al. (2024) present evidence that firms conduct green M&As with targets located in areas with weaker environmental regulations for pollution transfer reasons. On the other hand, a greenwashing acquirer could legitimately transform its business for sustainability reasons by learning and adopting the target's ESG policies (Pfeffer and Salancik, 1978). Sun et al. (2025) find that firms with substandard sustainability practices are more likely to acquire green targets, driven by negative investor sentiment and intense media scrutiny. Such green deals help acquirers enhance green innovation, increase investment in environmental protection and disclosure (Lu et al., 2023) and reduce carbon emissions (Yi et al., 2024).

Both views suggest that acquirers with higher levels of greenwashing acquire targets with higher relative ESGC ratings. This type of transaction allows the acquirer to either further mask its greenwashing or represent a genuine strategy to “go green.” Therefore, we propose the following hypothesis:

Previous literature finds that greenwashing firms experience lower financial performance and a negative market reaction to M&As. For instance, Walker and Wan (2012) show that greenwashing firms have negative accounting return on assets. Greenwashing activities bear associated costs, such as higher perceived risks and environmental penalties and fines (Bansal and Clelland, 2004). In addition to accounting-based performance, greenwashing is negatively related to market-based measures of financial performance (e.g. TobinQ, Market-to-Book value) (Testa et al., 2018). Furthermore, misleading communication regarding environmental performance negatively impacts a firm's intangible asset value (Konar and Cohen, 2001). Greenwashing firms exhibit lower cumulative abnormal returns (CARs) around greenwashing actions (Du, 2015). The negative market reactions are more pronounced when the levels of reputation and legitimacy attained from misleading communication are higher (Torelli et al., 2019). In terms of M&A deals between firms with disparate ESG ratings, Aktas et al. (2011) find that acquisitions where the target has better sustainability performance are linked with higher cumulative abnormal returns, and Tampakoudis and Anagnostopoulou (2020) report that acquirers demonstrate improvements in ESG performance and market value after acquiring a target with a higher ESG rating.

We build on the argument of Seele and Gatti (2017) and theorize that because external stakeholders lack relevant information to infer the legitimacy of green acquisition by a greenwashing firm, investors infer that the firm's existing history of greenwashing will continue following the merger. To reflect skepticism of the deal's financial benefits, there is a negative market reaction to the deal's announcement. Formally, we propose the following hypothesis:

Our third hypothesis is motivated by the resource dependence theory (Pfeffer and Salancik, 1978) and the organizational learning hypothesis (Aktas et al., 2011) that posit an acquirer could decrease their level of greenwashing after a merger when acquiring targets with higher relative ESG ratings. By acquiring, learning and integrating a target's ESG practices, an acquirer not only improves their own sustainability practices but also reduces their greenwashing activities. Therefore, we propose that:

We obtain data on all international M&A deals from Thomson Securities Data Company (SDC) Platinum Mergers and Acquisitions Database and apply similar criteria to existing studies (Aktas et al., 2011; Alexandridis et al., 2013). Completed deals are announced between January 1, 2006 and December 31, 2020. Both acquirer and target are listed non-financial companies. That is, we exclude firms with Standard Industrial Classification (SIC) codes from 6,000 to 6,999. All deal values are at least US$1 million. We exclude spin-offs, recapitalizations, self-tenders, repurchases, minority stake purchases, acquisitions of remaining interest, exchange offers and privatizations. The acquirer must own less than 50% of the target firm's shares before the deal announcement and at least 50% after completing the deal. These criteria lead to an initial sample of 3,863 observations. Filtering firms with available ESGC scores and accounting data yields a final sample of 489 transactions.  Appendix 1 presents the sample description.

Various greenwashing measures are proposed in the literature. The peer-relative greenwashing measure of Yu et al. (2020) combines Bloomberg's ESG disclosure scores and ASSET4's ESG scores. This method addresses the issue of ESG rating disagreement due to a lack of a common framework for scoring ESG performance (Brandon et al., 2021; Jacobs and Levy, 2022), but the calculation of their score suffers from several methodological problems (Lubloy et al., 2025). Following the selective disclosure approach, Marquis et al. (2016) use the Trucost database to measure greenwashing. Trucost Plc (2008) states that it collects a firm's self-reported ESG data to examine the environmental impact of 464 business activities. However, it does not account for any accusations of a firm's ESG wrongdoing. Finally, Walker and Wan (2012) assess greenwashing via the substantive and symbolic actions published on a firm's website with a scoring ranging from 1 to 7. This approach is subjective and therefore difficult to replicate. Several studies use MSCI ESG scores to measure a firm's sustainability practice (Bae et al., 2019; Bryant et al., 2020; Giese et al., 2019). However, a limitation of the MSCI ESG score is that it reflects a firm's stated ESG commitments and does not capture firms whose actions are inconsistent with their claims leading to ESG scores that do not accurately measure the firm's activities.

Due to these limitations associated with extant greenwashing measures, we recognize the definition by Seele and Gatti (2017) and measure the level of greenwashing using the ESG controversies score provided by Refinitiv's ESG Database. The ESG controversies score quantifies a company's stated commitments against its actions by monitoring global media sources. The ESG controversies score assesses information related to 23 ESG controversies topics. A firm with zero controversies surrounding its operations is assigned a score of 100. The minimum score of zero is assigned to firms that are associated with extreme controversies. Refinitiv benchmarks the controversies scores within each industry to make the scores comparable across different firms. The scores also account for the bias due to larger firms attracting more media attention than smaller firms (Delmas and Burbano, 2011; Du, 2015; Lyon and Montgomery, 2013). Seele and Gatti (2017) highlight that, without market accusation, such behaviors of the firm are considered potential greenwashing. The controversies score is a signal that proxies for the significance and materiality of the impact of negative scandals on a firm's actual ESG performance. We then calculate the inverse of the controversies score to proxy an acquirer's level of greenwashing (AGW). The higher the inverse controversies score, the higher the level of greenwashing.

We define a target's relative ESGC score (TRESG) as the ratio of a target's ESGC score to that of a corresponding acquirer at the end of the year prior to the deal announcement as follows:

We proxy an acquirer's level of greenwashing prior to the deal announcement (⁠$AGWPREorAGWt−1$⁠) by the inverse of the ESG controversies score in the year prior to the deal announcement. We also define the change in an acquirer's level of greenwashing pre- and post-merger (AGWCHANGE) as:

Following Brown and Warner (1985), we use the market-adjusted model to calculate the cumulative abnormal return (CAR) to measure the market reaction to the M&A deal announcement. We examine a short event window to avoid debate regarding the appropriate risk adjustment method associated with longer event window analyses (Fuller et al., 2002). The abnormal return (AR) is defined as the difference between the return on a firm's stock and the market:

where $ARi,t$ is the abnormal return of firm i on day t; $Ri,t$ is the return of firm i on day t; $Rm,t$ is the corresponding country market index return on day t.

We calculate the cumulative abnormal return (CAR) as follows:

where [m;n] is the event period from m days before to n days after the deal announcement date. We examine three-day and five-day windows around the announcement date. Stock returns and the corresponding country market index returns are obtained from Refinitiv and Bloomberg, respectively. We also employ the market model to measure CARs as a robustness test ^[3].

Our choice of firm-specific variables is motivated by the M&A literature. We gather data on market capitalization (MKCAP), total assets (ASSETS), market-to-book ratio (MTB), leverage (LEV) and Return-on-Equity (ROE) of both acquirers and target firms. Deal characteristics include deal size (DSIZE), deal diversification (DDIV), cross-border deals (DCROSS), deals with multiple bidders (DMUL), cash-offer deals (DCASH) and stock-offer deals (DSTOCK). We exclude the deal attitude as the sample includes all friendly deals. We collect data on board size (BSIZE), percentage of institutional ownership (INSTOWN) and percentage of independent directors on the Board (IDIR) based on the Ghitti et al. (2020) and Yu et al. (2020). All variables are measured at the end of the fiscal year prior to the deal announcement date. Data are obtained from Refinitiv, and definitions are provided in  Appendix 2.

Table 1 presents sample descriptive statistics. The acquirers' level of greenwashing (AGWPRE) has an average of 0.026 with a standard deviation of 0.063. This relatively low average indicates that the acquirers are involved in a relatively high level of greenwashing before the deal, due to the way ESG controversy scores are defined. Acquirers' average change in greenwashing (AGWCHANGE) is 38.9%. The mean of the target firm's relative ESGC scores (TRESG) is 0.84. Acquirers' cumulative abnormal returns are 1.5% across both the three and five-day window centered on the deal announcement date (ACAR[−1; +1] and ACAR[−2; +2]).

All acquisitions are friendly transactions. Deal-related statistics show that approximately 30% (DDIV = 0.323) of the deals involve an acquirer and target firm from different two-digit SIC industries. Only 34.2% of deals (DCROSS) are undertaken across borders with only 7% of deals (DMUL) involving more than one bidder, indicating these transactions involve relatively low levels of deal competition. In terms of payment method 6.1% of deals are cash (DCASH) and less than 1% are stock-only (DSTOCK), with the remaining deals financed using a combination of cash and stock.

Acquirers are larger in terms of market capitalization (AMKCAP) and total assets (AASSETS), on average, compared to target firms (TMKCAP and TASSETS, respectively). Acquiring firms' profitability (AROE = 17.3%) is higher than that of the target firms (TROE = 4.3%). In addition, institutional investors own 80.9% (AINST) of the acquiring firm, and 73.9% of their boards include independent directors.

We estimate the following model to explore the relationship between an acquirer's level of greenwashing and a target's relative ESGC score:

where $i$ is a deal; t is the year of deal announcement; $∑ControlsAcquirer,t−1$ is a set of control variables related to acquirers' characteristics; and $∑ControlsTarget,t−1$ is a set of control variables related to targets' characteristics ^[4]. Control variables related to acquirers and targets are lagged by one year prior to the deal announcement. $γ$ is the year fixed effect; δ represents acquirer and target industry fixed effects; and ε is the error term.

We include year fixed effects to remove time-varying unobserved heterogeneity. We account for acquirer and target industry fixed effects to eliminate other invariant unobserved heterogeneity across industries. We argue that acquirers' levels of greenwashing tend to be correlated within a country due to the impact of the corruption level in that country Ioannou and Serafeim (2012). Therefore, we cluster the standard errors in Equation (1) at the acquirer country level to account for this potential correlation.

Column (1) of Table 2 reveals the coefficient of AGWPRE is 1.227 and statistically significant, confirming that acquirers with higher levels of greenwashing purchase targets with a higher relative ESGC score. A one standard deviation increase in the acquirer's greenwashing score is associated with a higher relative ESGC score of 0.063 × 1.227 = 0.08% points. The positive relationship between an acquirer's measure of greenwashing and the target's ESGC score is consistent with Hypothesis 1.

We acknowledge that AGWPRE is potentially endogenous, as several factors may drive its variation. For example, corporate culture (Walker and Wan, 2012), Twitter presence (Lyon and Montgomery, 2013) and regulatory pressure (Bowen, 2000; Walker and Wan, 2012) impact a firm's level of greenwashing. We address the endogeneity concern by employing an instrumental variable and using Two-Stage Least Squares (2SLS) to estimate Equation (1). We employ a country's absence of corruption index (CORRUPT) as an instrumental variable for AGWPRE (Ioannou and Serafeim, 2012; Yu et al., 2020). Ioannou and Serafeim (2012) state that firms in a country with a high level of corruption are more likely to engage in unethical practices to reduce their costs, increase market share and retain their competitiveness. The rewards for ethical behavior in such countries are low, as the government is less likely to provide financial incentives for firms to be socially responsible. Following Yu et al. (2020), we proxy a country's absence of corruption using Transparency International's Corruption Perception Index. The index ranges from zero (a highly corrupt country) to 100 (a country with zero corruption).

Confirming that our instrumental variable is relevant, the first-stage regression results reported in Column (2) of Table 2 indicate the coefficient of CORRUPT is −0.006, and highly significant. The result supports the findings of Ioannou and Serafeim (2012) and Yu et al. (2020) that firms located in a country with a low level of corruption are less likely to engage in greenwashing. The second-stage regression estimates in Column (3) reveal a coefficient on AGWPRE of 2.589 that is approximately twice the magnitude of the coefficient estimated using OLS in Column (1). Thus, after addressing endogeneity, the level of greenwashing remains positively related to the target's ESGC score.

The finding regarding the behavior of a greenwashing acquirer is consistent with the two views explaining the behavior in a green deal. Acquiring a target with a higher ESGC rating conveys a misleading signal to the market regarding its green transformation (Berrone et al., 2015; Delmas and Burbano, 2011; Lyon and Montgomery, 2013). In contrast, transforming ESG performance could also be a motive for a greenwashing acquirer (Li et al., 2020a) through the acquisition of a target with superior sustainability policies.

Table 3 presents the acquirer's abnormal return around the deal announcement, for the full sample and subsamples of acquirers based on the level of greenwashing. The mean three-day return, ACAR[−1; +1], is 1.5% for the full sample. Partitioning the sample by the level of greenwashing reveals that acquirers with lower greenwashing scores exhibit announcement-period returns of 8.2% compared to a return of −10.1% for firms with higher values of AGWPRE, with the difference of −18.3% being statistically significant. The negative reaction to the announcement of deals by high greenwashing acquirers compared to acquirers with low greenwashing levels lends prima facie support to the hypothesis that the market is skeptical of the merit of mergers announced by firms associated with levels of greenwashing.

We build on the univariate results in the previous section and further explore the relationship between greenwashing scores and abnormal returns in a multivariate setting by estimating the following baseline regression model:

Consistent with the M&A literature, we control for a set of variables related to deal characteristics (⁠$∑ControlsDeal$⁠) in addition to acquirer and target characteristics in Equation (2) and present the estimation results in Table 4.

We find that the acquirer's three-day return, centered on the deal announcement date, is lower when its level of greenwashing is higher. Column (1) in Table 4 reports the influence of AGWPRE on ACAR[−1; +1]. The relationship between AGWPRE and ACAR[−1; +1] is significantly negative −0.108. In terms of the economic magnitude, an acquirer with a one standard deviation higher level of greenwashing exhibits abnormal returns that are approximately 0.7% points lower. This negative relationship remains using the 2SLS approach reported in Column (3). The coefficient of AGWPRE is −0.284 and remains strongly significant.

The effect of AGWPRE on ACAR[−2; +2] exhibits a similar effect as for the shorter three-day event window. As reported in Column (4) in Table 4, the coefficient of AGWPRE is −0.071 and is significant at the 10% level. The 2SLS estimate in Column (5) is consistent with the OLS estimate ^[5]. Therefore, these results support Hypothesis 2.

Our evidence that the market reacts negatively to the deal announcement is consistent with the attribution theory of Parguel et al. (2011). Information asymmetry between a firm and investors makes it difficult to assess if any green claims are misleading (Seele and Gatti, 2017). Therefore, market participants incorporate the acquirer's greenwashing behavior to assess the value of a deal. The market reaction we observe is consistent with Du (2015), who finds that the market responds negatively to a firm's greenwashing practice when the firm is publicly accused of greenwashing.

We further investigate how the impact of AGWPRE on abnormal returns varies in accordance with the target's relative ESGC score. We create a dummy variable, HighTRESG, to indicate the level of TRESG. If a target's relative ESGC score is equal or higher than the median value of the entire sample, we classify it as “High” and record “1” and “0” otherwise. We calculate the interaction between AGWPRE and HighTRESG to explore the moderating effect of HighTRESG on the relationship between the two variables.

We find that the impact of an acquirer's level of greenwashing on the market's reaction to the deal is more pronounced when acquiring a target with a high ESGC score. Column (1) in Table 5 reports that the coefficient of AGWPR × HighTRESG is −0.156, and significant. As reported in Column (2), the coefficient is smaller in magnitude but remains highly significant when the CAR window length is extended from three days to five days.

Overpaying for a target firm may explain the market's negative reaction to a deal (Baker et al., 2012). Baker et al. (2012) find that the offer prices are significantly influenced by the most recent 52-week high of the targets. Using the target's 52-week high as an instrumental variable for the offer premium, they show that the market perceives that a higher difference between a target's pre-takeover stock price and its 52-week-high reflects a higher potential for overpayment, with the market exhibiting a negative reaction to the deal announcement.

Therefore, we follow the methodology of Baker et al. (2012) and measure the overpayment potential and investigate whether it explains the market's negative response that we observe. The offer premium (OFFERPREM) is defined as the percentage difference from the target's stock price 30 days prior to the deal announcement. The 52-week high of a target is its highest price over a 335-day period ending 30 days prior to the announcement date. The 52-week high is then expressed as a percentage difference from the respective target's market price 30 days prior to the deal announcement (T52WKHI).

Column (1) in Table 6 presents the regressions of OFFERPREM on T52WKHI. Consistent with Baker et al. (2012), the coefficient of T52WKHI is positive and significant, suggesting that acquirers use the targets' 52-week highs as a reference point to determine the offer price. Columns (2) and (3) demonstrate how the overpayment potential influences the abnormal return across a three-day and five-day window around the deal announcement date, and Columns (4) and (5) report the results using the market model to measure abnormal returns. The coefficients of T52WKHI across four regressions are negative but insignificant. Therefore, we discount the possibility that the market's negative response is explained by the overpayment potential.

To confirm that the perception of further greenwashing toward such deals drives the market's negative reaction, we apply the propensity score matching (PSM) method. We define a categorical variable TREATMENT indicating two groups of deals: treatment (recorded as 1) and control (recorded as 0). The treatment (control) group includes deals with acquirers having (not having) ESG scores and ESG controversies scores available pre-merger, respectively. We then estimate the propensity scores using a logistic regression model, where TREATMENT is regressed on the set of control variables mentioned above. We match each treated deal with one control deal based on the similarity of their propensity scores, using nearest-neighbor matching with a caliper of 0.05 to ensure quality matches. This step yields 300 matched pairs of deals. Table 7 shows that ACAR around the announcement dates of the treated group is statistically significantly lower than that of the control group. This analysis confirms that, all else being equal, the market's negative response is driven by the acquirer's level of greenwashing prior to the merger instead of other variables.

We examine the variation in greenwashing around M&A deals by estimating the following model:

The legal origin of a particular country may influence a firm's ESG performance in that country (Kim et al., 2017), so we cluster the standard errors in Equation (3) at the target country level.

OLS estimates show that acquiring a higher ESGC target reduces an acquirer's greenwashing level post-merger. Column (1) in Table 8 reports that TRESG has a negative and significant impact on AGWCHANGE with a coefficient of −0.346. When acquiring a target with one standard deviation higher in a relative ESGC score, an acquirer lowers its level of greenwashing by 0.346% points. These results support Hypothesis 3.

The measurement error of TRESG in Equation (3.3) is a potential source of endogeneity. Several factors determine a firm's ESG scores, such as the ESG scores in previous years (Bae et al., 2019), religion rank of a firm's location of its headquarters (Deng et al., 2013), and the state where its headquarters is located (Rubin, 2008). We address such a potential issue by using an instrumental variable for TRESG and the 2SLS to estimate Equation (3.3).

Following Kim et al. (2017), we account for the legal origins (LEGAL) of the countries in which the targets are located as an instrumental variable for TRESG. Most countries follow one of two primary legal systems: civil law or common law. Compared to common law, civil law is characterized by a more concentrated ownership structure, which has a high level of managerial shareholding. It motivates managers to focus on long-term investments and performance. The civil law system focuses on maximizing stakeholder value, while the common law regime emphasizes shareholders' wealth and the protection of investor rights (Porta et al., 1998). For this reason, civil-law-based firms tend to have a greater focus on socially responsible investment than those located in common-law-countries, thereby leading to higher ESG ratings (Kim et al., 2017). Therefore, LEGAL theoretically satisfies the relevance condition of a good instrumental variable. There is no reason to believe that the targets' legal origins have a direct impact on the acquirers' ESG ratings rather than an indirect effect via the targets' ESG performance thereby satisfying the exclusion restriction. LEGAL assumes a value of one if the target firm is in a civil law country and zero in a common law country ^[6].

Our results are reinforced by the 2SLS estimate reported in Columns (2) and (3) of Table 8. Column (2) shows the first-stage regression with LEGAL as an instrumental variable for TRESG. The legal origin of a target firm's country has a positive and significant relationship with its relative ESGC rating, with a significant coefficient of 0.7. This result is consistent with Kim et al. (2017), who report that civil-law-based firms tend to have higher ESG scores than those located in common-law-countries. The large F-value indicates our instrumental variable, LEGAL, is sufficiently relevant. The second stage estimation results in Column (3) support the negative effect of TRESG on AGWCHANGE, with a significant coefficient of −0.052.

This finding is in line with the view that greenwashing acquirers embark on ESG transformations (Li et al., 2020a, b). After successfully integrating a target's ESG practices, a greenwashing acquirer improves its ESG performance and reduces greenwashing activities. Accused by external stakeholders, greenwashing behaviors bear costs to a greenwashing firm, such as lower signal reliability, legitimacy and firm financial performance. Therefore, green M&A deals could enable greenwashing firms the opportunity to sustain their businesses, despite the inherent costs of high ESG standards and the fact that ESG-related benefits take time to realize.

Overall, acquiring a green target helps a greenwashing acquirer transform its ESG practices, but the market initially distrusts the company's intention of going green. These findings confirm the green transformation of a greenwashing acquirer with a decrease in its level of greenwashing following the merger. This finding is consistent with Nguyen et al. (2025), who find that acquiring a target with higher relative ESGC ratings enhances an acquirer's post-merger ESG performance. It confirms the green transformation of a greenwashing acquirer when involved in a deal with a firm with superior ESG practices, even if the market is initially skeptical due to the acquirer's existing greenwashing.

We find that greenwashing acquirers genuinely transform their sustainability practices by acquiring firms with better ESG practices. After eliminating the hypothesis that the acquirer is overpaying for the target, the negative return around the deal announcement suggests that the market perceives the M&A transaction as being motivated as a means for the acquirer to further greenwash to mask poor environmental practices. However, acquirers exhibit a reduction in greenwashing following the deal, thereby suggesting that the acquirer incorporates the target's environmental credentials and transforms its own operations.

There are several practical implications of these results. First, acquiring a higher ESG-rated firm is a strategic solution for firms to reduce greenwashing and transform ESG practice. Regulators could refer to this finding to guide firms that engage in greenwashing to improve their sustainability practices. Second, when transforming ESG practices through green M&A deals, the managers of acquiring firms should focus on communicating deal motives and the up-to-date integration process to the market. The market uses the acquirer's past greenwashing behavior to interpret the signal, so evidence is necessary to overcome their reputation for greenwashing. Clear, detailed and informative communication, particularly around the planned adoption of ESG practices, may help to compensate for the firm's tarnished reputation and may lessen the market's negative response around the deal announcement date. Third, understanding how the market reacts to such deals provides investors with a reference for making investment decisions related to these deals.

Further research could explore which factors drive the ESG-related integration process of an acquirer and impact the acquirer's overall ESG practices. These factors could provide a comprehensive framework regarding the details required to implement a green acquisition as an ESG transformation channel.