Despite growing research on blockchain value, little is known about the role of CEOs in shaping these outcomes. This study examines whether CEO external directorships influence market reactions to blockchain investment announcements and how adoption strategy and application type condition this relationship through interaction effect.
We conduct an event study of 200 blockchain-related announcements by 138 U.S. public firms and use regression analyses to assess the effects of CEO external directorships, adoption strategy and application type.
CEO external directorships positively affect market responses to blockchain investments, with stronger effects for collaborative initiatives and financial applications. The results highlight the contingent value of CEO external social capital in complex IT investment decisions.
CEO external board ties can be a strategic asset in navigating regulatory, collaborative and technological complexities in blockchain projects. Boards and investors may consider executive network capital when evaluating leadership and strategic IT decisions.
This study offers one of the first pieces of empirical evidence on how CEO external directorships influence market reactions to blockchain investments. More importantly, it extends social capital, signaling and governance theories by showing that in blockchain investment contexts – characterized by heightened inter-organizational coordination, regulatory scrutiny and interpretive uncertainty – CEO external directorships function as context-activated social capital, whose value depends on adoption strategy and application type rather than being universally beneficial.
1. Introduction
Blockchain technology is rapidly emerging as a transformative force in business operations and decision-making. Beyond virtual currencies like Bitcoin, it now functions as enterprise information infrastructure enabling secure, transparent and decentralized data management across organizational boundaries, with growing applications in finance, supply chain and interorganizational collaboration. As global blockchain spending is projected to reach USD 1,950.3 billion by 2034, driven largely by smart-contract adoption in enterprise settings (Custom Market Insights, 2025), firms face heightened uncertainty, regulatory ambiguity and technical complexity – particularly in financial domains – making effective strategic decision-making essential.
Existing studies highlight blockchain's potential to enhance operational efficiency (e.g. Pan et al., 2020; Sharma et al., 2023) and improve market value (e.g. Cheng et al., 2019; Klöckner et al., 2022). However, no research has examined how CEO external social capital shapes market reactions to blockchain investment announcements – a notable gap given the interorganizational and legitimacy-intensive nature of blockchain initiatives. Social capital theory conceptualizes external board ties as channels for information, legitimacy and resources (Geletkanycz et al., 2001). CEOs who hold external directorships may therefore be better equipped to navigate blockchain's collaborative demands and regulatory complexities.
Research on CEO external directorships in finance and management has produced mixed findings, with some studies showing benefits through enhanced knowledge flows (Chang and Wu, 2021), and others highlighting downsides such as distraction, collusion and bias (e.g. Gedajlovic et al., 2013). In IT research, most social capital studies focus on internal ties (e.g. CIO–TMT relationships), and little is known about how external CEO networks influence IT investment outcomes (Randolph et al., 2020). Furthermore, while social capital theory explains the general value of executives' external ties, it does not account for how such ties operate under the interorganizational, legitimacy-intensive and regulatory demands of blockchain investments. This study addresses this gap by investigating whether and when CEO external directorships affect investor reactions to blockchain investment announcements. We pose two research questions:
Q1: Do CEO external directorships influence market value following blockchain investment announcements?
Q2: How do adoption strategy (collaborative vs. individual) and application type (financial vs. nonfinancial) condition this relationship through interaction effect?
Grounded in social capital theory, signaling theory, and a contingency perspective, we argue that CEO external directorships enhance market responses to blockchain investment announcements and that this moderating effect is further amplified in contexts requiring interorganizational coordination or regulatory navigation. Firms often form collaborations to create synergistic efficiency for blockchain solutions (Pan et al., 2020). The finance sector is known for its heavy regulation (McLaughlin et al., 2017), and implementing blockchain in this domain requires additional external legal information and advice. CEOs with external directorships can leverage broader information channels, legitimacy signals and expert access to support these more complex initiatives (Randolph et al., 2020). We assess these relationships using abnormal stock returns, a forward-looking and widely adopted indicator of investor expectations in IT investment research (e.g. Teo et al., 2016). Accordingly, the scope of this study is limited to blockchain investment announcements by U.S. public firms during 2020–2022, bounding generalizability to similar institutional settings. The findings capture short-term investor expectations at the time of announcement and should not be generalized to long-term performance outcomes or non-U.S. contexts.
Unlike prior research that examines internal executive networks or generic IT investment announcements, this study focuses on CEO external board-level ties and their contingent effects on market reactions to blockchain investment announcements. This study makes three distinct contributions. First, it addresses the lack of evidence on how CEO external directorships shape market reactions to blockchain investment announcements. Second, it identifies adoption strategy and application type as interaction-based boundary conditions that shape the value of CEO external directorships, responding to calls for a contingency-based understanding of blockchain value creation. Third, it advances social capital theory by showing that the value of CEO external ties is context-activated rather than universal, emerging most strongly when blockchain initiatives intensify coordination and regulatory uncertainty, thereby extending existing theories of signaling and governance under heightened uncertainty.
2. Theoretical background
2.1 Blockchain and its organizational implications
Blockchain is a distributed ledger technology designed to record and validate transactions without a central authority. Its key characteristics – immutability, transparency and smart contracts – enable more secure and efficient interorganizational processes (Kim and Shin, 2019). Despite its potential, blockchain remains in early stages (Li et al., 2023), with firms facing high costs, scalability limitations, technical complexity and evolving regulation (Li et al., 2023). Adoption rates remain relatively low (AlShamsi et al., 2022), and many initiatives continue to operate in pilot phases (Li et al., 2023).
Although blockchain research is expanding, much of it remains conceptual or case-based, with limited quantitative evidence (Karakas et al., 2021). Existing studies show that blockchain can improve operating performance (Pan et al., 2020; Hasan et al., 2020) and market value (e.g. Cheng et al., 2019; Klöckner et al., 2022). More recent studies highlight governance and signaling mechanisms in blockchain initiatives (e.g. Ezzi et al., 2023; Filatotchev et al., 2025). Outcomes are shown to vary across project characteristics and use cases.
However, the role of CEOs, a key factor in successful blockchain investment (Hastig and Sodhi, 2020) – remains underexplored. We focus on CEO external directorships because blockchain initiatives require boundary-spanning resources – such as inter-organizational information, legitimacy and coordination. Unlike other CEO attributes (e.g. tenure, age), external directorships capture externally oriented social capital that is particularly relevant in blockchain's multi-party, legitimacy-intensive environment.
Blockchain differs from traditional enterprise IT because its value often depends on multi-firm coordination, shared governance and compliance with evolving regulatory frameworks. These demands heighten the importance of CEO external ties, which provide access to cross-firm information, alliance partners and regulatory insight – resources less critical for more mature or internally oriented technologies.
2.2 CEO external directorships and firm performance
Research has long debated whether CEO external directorships strengthen or weaken firm performance. From a resource-based perspective and social capital perspective, external board ties represent valuable and unique intangible resources offering firms substantial advantages (Barney, 1991; Peng et al., 2013). Well-connected executives can access diverse intelligence (Edvinsson and Malone, 1997) and enhance innovation quality (Chang and Wu, 2021; Faleye et al., 2014).
Conversely, agency theory warns that external board roles may create distractions, increase agency costs or facilitate collusion and biased decision-making (e.g. Gedajlovic et al., 2013; Xue et al., 2018; Khan and Mauldin, 2021). This ongoing debate highlights the need to investigate CEO external directorships in contexts – such as blockchain – where external knowledge, legitimacy and cross-firm coordination are especially critical.
2.3 IT, top management and organizational performance
Extensive work links IT investments to firm performance, with outcomes shaped by various contextual factors – such as country, industry and firm-specific characteristics (e.g. Lui et al., 2023). A consistent theme is the crucial role of top management support in achieving IT success. Research shows that individual top executives (e.g. the CIO and CEO) (Banker et al., 2022) and ties among top executives, including CIO-TMT relationships, improve organizational performance upon IT adoption (Bendig et al., 2023).
A newer stream emphasizes the role of social networks in IT value creation. Internal social capital – such as ties between CIOs, TMTs and business units – positively influences IT investment performance by facilitating knowledge combination and exchange (e.g. Karahanna and Preston, 2013; Wagner et al., 2014; Nugroho et al., 2020). Yet, external social capital held by CEOs remains underexplored.
2.4 Research gap
Prior studies provide mixed evidence on the performance effects of CEO external directorships. Embeddedness-based research highlights benefits such as information exchange, legitimacy and learning (Geletkanycz et al., 2001), while agency-based work emphasizes distraction and increased agency costs (e.g. Gedajlovic et al., 2013; Xue et al., 2018; Khan and Mauldin, 2021).
We extend this debate into the blockchain context, where uncertainty, regulatory scrutiny and interfirm collaboration amplify both the potential benefits and challenges of external ties. While IT research has examined internal governance factors, little is known about how CEO external directorships shape market responses to blockchain investment announcements. Blockchain investments amplify uncertainty, coordination complexity and legitimacy concerns, increasing investors' reliance on observable executive signals. In this setting, CEO external directorships function as context-activated social capital, simultaneously providing access to external information (social capital), conveying credibility and oversight capability (signaling), and mitigating governance concerns associated with novel IT investments. These mechanisms operate jointly to shape investor expectation formation rather than independently. These conditions distinguish blockchain investments from prior IT contexts and necessitate a refinement of executive social capital and signaling theories to account for context-activated effects.
Prior work suggests that executive external ties can provide information, legitimacy and coordination benefits (Geletkanycz and Boyd, 2011). However, existing applications of social capital theory do not explain how these mechanisms operate under blockchain's uniquely inter-organizational, legitimacy-intensive and regulatory conditions. Recent blockchain studies (e.g. Bai et al., 2024; Klöckner et al., 2022; Rogalski and Schiereck, 2025) further highlight that outcomes vary across project characteristics and use cases, reinforcing the need for a contingency-based understanding of blockchain value creation. Recent syntheses of blockchain research also highlight growing research on blockchain in accounting/auditing and cybersecurity (Al-Shattarat et al., 2025; Hassanein et al., 2025; Hassanein and Tharwat, 2024; Tharwat et al., 2025), noting positive market implications from efficiency and transparency but limited attention to executive governance factors – setting baseline expectations for positive announcement reactions moderated by CEO ties.
In summary, despite growing attention to blockchain's strategic value, the role of CEO external directorships in shaping market responses remains unexplored. We address this gap by theorizing how and when external ties influence blockchain investment outcomes. We frame agency theory as a competing baseline mechanism, which predicts negative market reactions due to CEO busyness, weakened monitoring or potential conflicts of interest associated with external directorships (Gedajlovic et al., 2013). In contrast, social capital mechanism and signaling theory predict positive reactions through enhanced information access, legitimacy and coordination capacity (Geletkanycz et al., 2001; Zhang and Wiersema, 2009). We integrate contingency theory as the reconciling framework, explaining when and why social capital and signaling mechanisms dominate agency concerns – namely, in blockchain contexts characterized by heightened uncertainty, regulatory scrutiny and interorganizational coordination demands. Under these conditions, investors prioritize external resources and observable credibility signals over potential managerial distractions from agency costs, particularly when initiatives involve collaboration or regulatory scrutiny. We elaborate on these mechanisms in Section 3 as the basis for our hypotheses.
3. Hypothesis
3.1 The moderating effect of CEO external directorship on the blockchain-performance link
CEO external directorships positively influence investor reactions to blockchain announcements through three mechanisms central to social capital theory: information access, legitimacy and coordination capacity.
First, information access: external ties provide CEOs with diverse strategic, industry and regulatory knowledge that helps them evaluate blockchain's complex architecture, anticipate compliance challenges and adopt emerging best practices (Cheng et al., 2021; Karahanna and Preston, 2013; Nugroho et al., 2020). This is particularly valuable in the blockchain context, where technological choices and regulatory expectations are rapidly evolving.
Second, legitimacy: serving on outside boards enhances a CEO's status and credibility (D'Aveni, 1990; Galaskiewicz, 1985), signaling managerial competence to external stakeholders (Podolny, 1994). CEOs with multiple directorships are viewed as more reputable and capable leaders (e.g. Zhang and Wiersema, 2009), which can reduce investors' perceived risk around high-uncertainty blockchain initiatives and increase confidence in the firm's execution capability (Podolny, 1994).
Third, coordination capacity: blockchain initiatives often require multi-party collaboration, shared governance and partner alignment. External directorships broaden CEO relational networks, facilitating trust-building, access to potential partners and smoother interorganizational coordination – capabilities especially relevant for consortium-based or cross-firm blockchain applications.
Together, these mechanisms reduce perceived execution and regulatory risk, leading investors to revise upward their expectations of firm value. While agency theory predicts negative effects due to CEO busyness and weakened monitoring (e.g. Gedajlovic et al., 2013), blockchain's heightened uncertainty and interorganizational demands cause investors to privilege social capital and signaling benefits (Geletkanycz et al., 2001; Teo et al., 2016). Formalizing the above arguments, we hypothesize:
CEO external directorships are positively associated with market value following blockchain investment announcements.
3.2 Adoption strategy
Consistent with the contingency perspective, the benefits of CEO external directorships should be more pronounced under collaborative blockchain adoption strategies. Collaborative initiatives require shared standards, partner alignment and interfirm trust – conditions under which external social capital becomes especially valuable. Social capital theory suggests that external ties enhance coordination capacity and information flow across organizational boundaries, helping firms manage uncertainty and collective decision-making.
Firms may adopt blockchain individually or collaboratively. Collaboration involves cooperative agreement between two or more entities working together on a blockchain investment (Shipilov and Stern, 2016). Such strategies are common because blockchain value is maximized through interoperability, shared protocols and network effects (Carson et al., 2018). Collaborative approaches also enable firms to pool resources, co-create standards and achieve synergistic efficiencies in uncertain technological environments (Pan et al., 2020).
These characteristics make CEO external directorships particularly relevant in collaborative settings. External ties help CEOs nurture trust-based relationships, secure partner commitment and mobilize resources essential for cross-firm collaboration (Nawinna and Venable, 2019; Uzzi, 1996). They also provide access to dynamic capabilities and specialized knowledge that support coordination among diverse stakeholders (Randolph et al., 2020). Collaborative adoption strategies heighten coordination demands across firms, amplifying the perceived value of CEO external directorships as channels for alliance formation and trust-building, thereby strengthening the positive translation of these ties into investor expectations.
CEO external directorships lead to more positive market reactions for collaborative blockchain investments than for individual blockchain investments.
3.3 Types of applications
The influence of CEO external directorships is also likely to vary by application type. Financial blockchain applications face substantially higher regulatory scrutiny, compliance obligations and legitimacy demands than nonfinancial applications (Kakavand et al., 2017; McLaughlin et al., 2017). These conditions heighten the importance of the mechanisms outlined earlier, particularly information access and legitimacy.
Financial applications such as payments, asset management and trade finance require deeper engagement with regulators, legal advisors and financial intermediaries, whereas nonfinancial applications (e.g. supply chain management, loyalty reward systems, voting and healthcare services) involve fewer regulatory constraints (Zheng et al., 2018). Because regulatory complexity increases uncertainty for investors, managerial credibility becomes especially important when evaluating financial blockchain investments.
CEO external directorships can help address these challenges by providing timely regulatory insights, early awareness of policy changes and access to legal expertise (Boso et al., 2013; Cornwell et al., 2017). These ties also enhance the CEO's legitimacy and facilitate coordination with external stakeholders, signaling that the firm is well-positioned to navigate compliance-heavy financial environments. As a result, investors are likely to perceive well-connected CEOs as more capable of implementing blockchain solutions in highly regulated financial contexts.
Accordingly, investors should respond more positively to financial blockchain announcements when CEOs hold extensive external directorships, as heightened regulatory scrutiny and legitimacy concerns lead investors to rely more heavily on CEO external directorships as observable signals of oversight capability and regulatory navigation competence, resulting in stronger positive market reactions.
CEO external directorships lead to more positive market reactions for financial blockchain investments than for nonfinancial applications.
Figure 1 shows the research model and the three hypotheses investigated.
The figure presents a conceptual framework examining how C E O external directorships shape stock market reactions to blockchain investment announcements. The primary focus of the model is the moderating role of C E O external directorships (H 1), which influence how investors respond to blockchain investment announcements. In addition, the model highlights two interaction effects that further condition this relationship. Adoption strategy (collaborative vs. individual) interacts with C E O external directorships (H 2), such that the influence of C E O external ties on market reactions is stronger in collaborative blockchain initiatives. Application type (financial vs. nonfinancial) also interacts with C E O external directorships (H 3), with stronger effects expected in financial applications due to greater regulatory complexity and legitimacy demands. While the framework includes a direct relationship between blockchain investment announcements and stock returns, this direct effect is not the central focus of the study. Instead, the model emphasizes that the value of C E O external directorships is contingent on project characteristics, highlighting their role as context-dependent drivers of investor responses.Research framework
The figure presents a conceptual framework examining how C E O external directorships shape stock market reactions to blockchain investment announcements. The primary focus of the model is the moderating role of C E O external directorships (H 1), which influence how investors respond to blockchain investment announcements. In addition, the model highlights two interaction effects that further condition this relationship. Adoption strategy (collaborative vs. individual) interacts with C E O external directorships (H 2), such that the influence of C E O external ties on market reactions is stronger in collaborative blockchain initiatives. Application type (financial vs. nonfinancial) also interacts with C E O external directorships (H 3), with stronger effects expected in financial applications due to greater regulatory complexity and legitimacy demands. While the framework includes a direct relationship between blockchain investment announcements and stock returns, this direct effect is not the central focus of the study. Instead, the model emphasizes that the value of C E O external directorships is contingent on project characteristics, highlighting their role as context-dependent drivers of investor responses.Research framework
4. Research method
4.1 Sample selection
We conducted a comprehensive search of the Factiva (Dow Jones Newswires) database for announcements containing the keyword “blockchain” from 2020 to 2022. The 2020–2022 period was selected as it captures the post-COVID surge in blockchain adoption for resilient supply chains and digital finance, aligning with social capital theory's emphasis on networks mitigating uncertainty in disruptive contexts (e.g. Bai et al., 2024). This era saw heightened regulatory ambiguity (e.g. SEC guidelines on crypto), amplifying the value of CEO external ties for legitimacy signaling (Podolny, 1994; Filatotchev et al., 2025). Each announcement was manually reviewed to determine whether it constituted a blockchain investment announcement, defined as a disclosure in which a firm initiates, implements or scales a blockchain-related project, platform or partnership with a clear intent to deploy or integrate blockchain technology.
To ensure data validity, we followed a systematic screening protocol. One author first applied predefined inclusion and exclusion criteria. Ambiguous or borderline cases were independently reviewed by all co-authors until consensus was reached. To further ensure coding reliability, two authors also independently coded a subset of announcements, the resulting Cohen's kappa values ranged from 0.82 to 0.88 for key categories (strategy and application), indicating strong agreement. Discrepancies were resolved through discussion. The full coding protocol is provided in Supplementary Material S1.
Announcements were included if they explicitly stated firm resource commitment (financial, technological or strategic) to blockchain initiatives with specific scope details. We excluded general references, speculative commentary or non-blockchain IT activities without evidence of adoption. To mitigate confounding effects, announcements with other major news (e.g. M&A or earnings releases) within the [−5, +5] window around the event date were excluded. No overlapping announcements occurred within the same event window, and potential pre-announcement leakage was addressed by verifying each announcement as the first public disclosure. When multiple media articles reported the same event, only the earliest article was retained. Announcements related to the same blockchain investment but occurring at different implementation stages were treated as distinct initiatives. We further excluded private firms, illiquid stocks and repeated announcements.
The initial search yielded 342 announcements. After removing duplicates and applying exclusion criteria, the final sample consisted of 200 valid announcements across 138 firms from 2020 to 2022. This sample size aligns with prior IS event-study research and provides sufficient statistical power (e.g. Lui et al., 2021). Table S2 (see Supplementary Material S3) presents illustrative examples of included announcements.
Firm-level financial data were obtained from Compustat, and stock market data from CRSP (The Center for Research in Security Prices). Table 1 describes the details of our sample firms: Panel A shows industry distribution; Panel B demonstrates the distribution across key variables, including adoption strategy and application; and Panel C shows firms' characteristics (e.g. total assets, employees, return on assets, total liabilities and sales).
Description of sample firm
| Panel A: Industry distribution of the announcements | |||
|---|---|---|---|
| SIC (2-digit) | Industry | Frequency | Percentage |
| 20 | Food and kindred products | 13 | 6.5 |
| 25 | Furniture and fixtures | 5 | 2.5 |
| 28 | Chemical and allied products | 4 | 2.0 |
| 29 | Petroleum and coal products | 2 | 1.0 |
| 35 | Industrial and commercial machinery and computer equipment | 4 | 2.0 |
| 36 | Electronic Equipment | 7 | 3.5 |
| 37 | Transportation equipment | 12 | 6.0 |
| 48 | Communications | 5 | 2.5 |
| 53 | General merchandise stores | 13 | 6.5 |
| 54 | Food shops | 2 | 1.0 |
| 58 | Drinking and eating places | 4 | 2.0 |
| 59 | Miscellaneous retail | 5 | 2.5 |
| 60 | Depository institutions | 50 | 25.0 |
| 61 | Nondepository institutions | 11 | 5.5 |
| 62 | Security and commodity brokers | 18 | 9.0 |
| 63 | Insurance carriers | 11 | 5.5 |
| 73 | Business services | 28 | 14.0 |
| 80 | Health services | 2 | 1.0 |
| 99 | Nonclassifiable establishments | 4 | 2.0 |
| Panel A: Industry distribution of the announcements | |||
|---|---|---|---|
| SIC (2-digit) | Industry | Frequency | Percentage |
| 20 | Food and kindred products | 13 | 6.5 |
| 25 | Furniture and fixtures | 5 | 2.5 |
| 28 | Chemical and allied products | 4 | 2.0 |
| 29 | Petroleum and coal products | 2 | 1.0 |
| 35 | Industrial and commercial machinery and computer equipment | 4 | 2.0 |
| 36 | Electronic Equipment | 7 | 3.5 |
| 37 | Transportation equipment | 12 | 6.0 |
| 48 | Communications | 5 | 2.5 |
| 53 | General merchandise stores | 13 | 6.5 |
| 54 | Food shops | 2 | 1.0 |
| 58 | Drinking and eating places | 4 | 2.0 |
| 59 | Miscellaneous retail | 5 | 2.5 |
| 60 | Depository institutions | 50 | 25.0 |
| 61 | Nondepository institutions | 11 | 5.5 |
| 62 | Security and commodity brokers | 18 | 9.0 |
| 63 | Insurance carriers | 11 | 5.5 |
| 73 | Business services | 28 | 14.0 |
| 80 | Health services | 2 | 1.0 |
| 99 | Nonclassifiable establishments | 4 | 2.0 |
| Panel B: Distribution of the announcement across key variables | ||
|---|---|---|
| Adoption Strategy | Collaboration 84 (42%) | Individual 116 (58%) |
| Application | Financial 88 (44%) | Nonfinancial 112 (56%) |
| Panel B: Distribution of the announcement across key variables | ||
|---|---|---|
| Adoption Strategy | Collaboration 84 (42%) | Individual 116 (58%) |
| Application | Financial 88 (44%) | Nonfinancial 112 (56%) |
| Panel C: Description of the sample firms | |||||
|---|---|---|---|---|---|
| Variable | Total Assetsa | Employee No.b | ROA | Total Liabilitiesa | Salesa |
| Mean | 5.99 | 282 | 0.092 | 5.14 | 1.03 |
| Median | 1.99 | 100 | 0.086 | 1.19 | 0.57 |
| Std. Deviation | 8.28 | 561 | 0.098 | 7.61 | 1.28 |
| Minimum | 0.000015 | 0.033 | −0.346 | 0.00008 | 0.00002 |
| Maximum | 26.23 | 2,300 | 0.357 | 23.66 | 5.12 |
| Panel C: Description of the sample firms | |||||
|---|---|---|---|---|---|
| Variable | Total Assets | Employee No. | ROA | Total Liabilities | Sales |
| Mean | 5.99 | 282 | 0.092 | 5.14 | 1.03 |
| Median | 1.99 | 100 | 0.086 | 1.19 | 0.57 |
| Std. Deviation | 8.28 | 561 | 0.098 | 7.61 | 1.28 |
| Minimum | 0.000015 | 0.033 | −0.346 | 0.00008 | 0.00002 |
| Maximum | 26.23 | 2,300 | 0.357 | 23.66 | 5.12 |
USD in Billions
In Thousands
We measured stock market reactions using event study methodology, widely applied in accounting, finance and increasingly in IS research. Event studies provide timely and reliable assessments of investor expectations, allowing market reactions to be captured immediately rather than after accounting results become available (Bose and Pal, 2012). The unit of analysis is the blockchain investment announcement. Abnormal returns capture short-term investor belief updating regarding the announced initiative and are a forward-looking, market-based indicator of perceived value, rather than realized firm performance (McWilliams and Siegel, 1997). Table S1 (see Supplementary Material S2) summarizes prior IT and blockchain event-study literature.
4.2 Measures
4.2.1 Dependent variable
We used the capital asset pricing model (CAPM) to measure the abnormal stock returns, which capture the impact of blockchain investment announcements. CAPM is the most widely used market model and is calculated using Equation (1):
where Rit is the return for announcement i on day t, Rmt is the market index return, α is the y-intercept, βi represents the firm's systematic risk and εit is the error term. For each stock, we consider multiple stock indices and select the one with the highest R2.
Abnormal return (AR) during the event period is then calculated as the difference between actual and expected returns:
For each announcement, 200 trading days ending 30 days prior to the event date are used to develop a regression model. Consistent with prior event-study research, alternative market indices were evaluated for each stock and the benchmark producing the highest pre-event explanatory power (R2) was selected to ensure accurate expected return estimation. Stock returns are then calculated over a three-day event window [−1, 0, +1]. We adopt this short window, consistent with prior IT event-study research (e.g. Dehning et al., 2003), to capture immediate market reactions while limiting noise and confounding effects from unrelated firm or market events, making it more reliable than longer windows (McWilliams and Siegel, 1997).
Thus, the abnormal return on the announcement date (day 0) serves as the dependent variable (see Supplementary Material S4 for the abnormal returns of the full sample). Abnormal returns provide a forward-looking, market-based assessment of investor expectations and are standard in IT event-study research, capturing investor reactions before accounting outcomes are observable. Endogeneity concerns are mitigated by the event-study design, which exploits exogenous announcement timing and short event windows to capture investor belief updating. Nonetheless, we interpret the findings as expectation-based associations rather than definitive causal effects.
4.2.2 Cross-sectional regression model
To test the roles of CEO external directorships (H2), we regressed abnormal returns on CEO external directorships while controlling relevant industry-, firm- and CEO-level characteristics, using the cross-sectional regression model shown in Equation (3)
where ARi is the abnormal return on the event day (day 0) for firm i. Consistent with event-study practice, we focus on abnormal returns on the announcement day (day 0) to capture the immediate market reaction while minimizing potential contamination from confounding news. To address potential nonindependence from multiple announcements by the same firm, all regression standard errors are clustered at the firm level. Consistent with standard event-study methodology (e.g. Klöckner et al., 2022), we do not include lagged accounting performance as a control, as prior firm performance is already incorporated into stock prices and abnormal returns isolate investor belief updating around the announcement.
Subgroup analyses (Geletkanycz and Boyd, 2011; Peng and Luo, 2000) were conducted to examine whether the effect of CEO external directorships varies by adoption strategy (H2) and by application type (H3). We interpreted the coefficient β1 and its significance to assess the effect of CEO external directorships. Chow tests (Peng and Luo, 2000) were also conducted to determine whether differences between subgroup regression estimates were statistically significant.
4.2.3 Measurement of key variables
CEO external directorships: Following previous studies, CEO external directorships were defined as the number of external boards (excluding the focal firm) on which the CEO serves in a given year (Zhang and Wiersema, 2009; Oh and Barker III, 2018; Mutlu et al., 2021). Consistent with this stream of research, we use an unweighted count of external board seats, regardless of firm type or industry overlap, as the standard approach for capturing CEO external social capital. CEO external directorships provide various strategic benefits, including access to information and legitimacy (Geletkanycz et al., 2001). Data were obtained from BoardEx and firms' 10-K filings and annual reports. This count serves as a proxy for the CEO external social capital and network reach.
Adoption strategy: Adoption strategy was coded using Factiva news announcements. Initiatives were classified as collaborative (=1) when at least one external partner was involved in a formal partnership, consortium, or co-development agreement, and individual (=0) otherwise. Collaborative initiatives were identified through manual coding of keywords such as “partnership,” “joint venture,” “collaboration” and named partner organizations.
Application type: Blockchain application type was classified into two categories based on the initiative's primary functional domain. Financial applications (=1) included payments, asset management and trade-finance use cases. Nonfinancial applications (=0) include areas such as supply chain tracking, voting, digital identity, healthcare and loyalty programs.
4.2.4 Measurement of control variables
We controlled for several individual-, firm- and industry-level variables that may influence stock returns. Following previous studies (e.g. Lui et al., 2021; Dehning et al., 2003), the control variables included firm size, firm reputation, IT capability, industry type, industry clockspeed, initial investment announcement, year of announcement and project status. We also included CEO characteristics – age, gender, duality and tenure – which have been demonstrated to influence firm performance and innovation (Barker III and Mueller, 2002).
Firm size was measured as the natural logarithm of total assets (Lui et al., 2016). Firm reputation was coded as 1 if the firm appeared in the Fortune 500 ′most admired companies' list during the announcement year or the prior five years, and 0 otherwise (Bharadwaj, 2000). IT capability was coded as high (1) if the firm appeared in the InformationWeek (IW) 500 list during the announcement year or in the prior five years, and low (0) otherwise (e.g. Bharadwaj, 2000).
Industry type was coded as manufacturing (=1) for firms with four-digit SIC codes between 2000 and 3,999 and nonmanufacturing (=0) otherwise (e.g. Lui et al., 2021). Industry clockspeed followed Fine's (1998) classification, coded as low (1), medium (2) or high (3), to reflect differences in the rate of market and technological change. Blockchain investment may yield stronger returns for high-clockspeed industries due to their greater responsiveness to rapid market change.
Initial announcements were coded as 1 for the first blockchain initiative and 0 for subsequent announcements by the same firm (Zhao and Wang, 2017). New initiatives tend to be unexpected and may generate larger market responses (Ghosh and Woolridge, 1991). The year of announcement was recorded as the actual calendar year (e.g. 2020).
Our sample includes announcements at various project stages (e.g. pilot, prototype, full-scale deployment). Accordingly, project status was coded as 1 for post-implementation announcements and 0 for earlier stages. Post-implementation announcements may generate higher returns due to lower uncertainty and perceived risk.
CEO characteristics were measured as follows (Barker III and Mueller, 2002): gender (female = 1, male = 0), CEO duality (=1 if the CEO also served as board chair) and tenure (years served as CEO).
Based on prior literature, we expect firm reputation, IT capability and initial investment announcements to be positively associated with abnormal returns (Lui et al., 2021; Dehning et al., 2003). By contrast, firm size, manufacturing industry, year of announcement, CEO age, female CEO, CEO duality and CEO tenure are expected to be negatively associated with abnormal returns (Barker III and Mueller, 2002).
Because the event-study design focuses on short-window abnormal returns around discrete, publicly disclosed announcement dates, time-invariant firm fundamentals and stable governance structures (e.g. board size, ownership structure, audit quality) are largely absorbed and are unlikely to drive announcement-day market reactions. Accordingly, the models prioritize controls commonly used in IT event-study research – firm size, reputation, industry characteristics and CEO attributes – while avoiding overconditioning and multicollinearity. We therefore interpret the findings as expectation-based associations rather than definitive causal effects.
Table 2 presents the definitions, measurement and data sources of all variables used in this research, including CEO external directorships, adoption strategy (collaborative or individual) and application type (financial or nonfinancial).
Variable descriptions
| Variables | Description | Measurements | Data sources | References |
|---|---|---|---|---|
| CEO external directorships | Number of outside board seats held by the CEO (excluding the focal firm) | Count of external directorships | BoardEx, annual report, and 10-K documents | Oh and Barker III (2018), Zhang and Wiersema (2009) |
| Adoption strategy | Whether more than one firm involved in the blockchain initiative | Collaborative = 1; Individual = 0 | Blockchain announcements | Shipilov and Stern (2016) |
| Application type | Type of blockchain application | Financial = 1; Nonfinancial = 0 | Blockchain announcements | Zheng et al. (2018) |
| Firm reputation | Whether a firm has high reputation | Reputation = 1 if listed as “Most Admired Companies” in Fortune 500 in the announcement year or prior five years; otherwise 0 | Fortune | Bharadwaj (2000) |
| IT capability | Strength of the firm's IT innovativeness | High IT capability = 1 if listed in IW 500 in the announcement year or prior five years; otherwise 0 | InformationWeek 500 award | Bharadwaj (2000), Bose and Pal (2012) |
| Initial investment announcement | Whether this is the first blockchain initiative announced by the firm | First announcement = 1; otherwise 0 | Blockchain announcements | Zhao and Wang (2017) |
| Firm size | Size of the firm | Log of total assets | Compustat | Lui et al. (2016, 2023) |
| Industry type | Whether the firm is in manufacturing | Manufacturing (SIC 2000–3999) = 1; otherwise 0 | Compustat | Lui et al. (2021) |
| Industry clockspeed | Speed of industry change | 1 = Low; 2 = Medium; 3 = High | Compustat | Fine (1998) Lui et al. (2023) |
| Year of announcement | Year in which the blockchain initiative is announced | Calendar year (e.g. 2020) | Blockchain announcements | |
| Project status | Whether the blockchain initiative had already been implemented at the time of the announcement | Post-implementation = 1; otherwise 0 (pilot/prototype) | Blockchain announcements | |
| CEO age | CEO's age | From date of birth | BoardEx | Barker III and Mueller (2002) |
| CEO gender | CEO's gender | Female = 1; Male = 0 | BoardEx | Lui et al. (2016) |
| CEO duality | Whether the CEO also serves as chairman | Duality = 1; otherwise 0 | BoardEx | Lui et al. (2016), Cheng et al. (2021) |
| CEO tenure | Years the CEO has served the firm | Number of years in role | BoardEx | Barker III and Mueller (2002) |
| Variables | Description | Measurements | Data sources | References |
|---|---|---|---|---|
| CEO external directorships | Number of outside board seats held by the CEO (excluding the focal firm) | Count of external directorships | BoardEx, annual report, and 10-K documents | |
| Adoption strategy | Whether more than one firm involved in the blockchain initiative | Collaborative = 1; Individual = 0 | Blockchain announcements | |
| Application type | Type of blockchain application | Financial = 1; Nonfinancial = 0 | Blockchain announcements | |
| Firm reputation | Whether a firm has high reputation | Reputation = 1 if listed as “Most Admired Companies” in Fortune 500 in the announcement year or prior five years; otherwise 0 | Fortune | |
| IT capability | Strength of the firm's IT innovativeness | High IT capability = 1 if listed in IW 500 in the announcement year or prior five years; otherwise 0 | InformationWeek 500 award | |
| Initial investment announcement | Whether this is the first blockchain initiative announced by the firm | First announcement = 1; otherwise 0 | Blockchain announcements | |
| Firm size | Size of the firm | Log of total assets | Compustat | |
| Industry type | Whether the firm is in manufacturing | Manufacturing (SIC 2000–3999) = 1; otherwise 0 | Compustat | |
| Industry clockspeed | Speed of industry change | 1 = Low; 2 = Medium; 3 = High | Compustat | |
| Year of announcement | Year in which the blockchain initiative is announced | Calendar year (e.g. 2020) | Blockchain announcements | |
| Project status | Whether the blockchain initiative had already been implemented at the time of the announcement | Post-implementation = 1; otherwise 0 (pilot/prototype) | Blockchain announcements | |
| CEO age | CEO's age | From date of birth | BoardEx | |
| CEO gender | CEO's gender | Female = 1; Male = 0 | BoardEx | |
| CEO duality | Whether the CEO also serves as chairman | Duality = 1; otherwise 0 | BoardEx | |
| CEO tenure | Years the CEO has served the firm | Number of years in role | BoardEx |
5. Results
5.1 Results of moderating effect of CEO external directorships (H1) (RQ1)
To test H1 (RQ1), we conducted regression analyses. Table 3 shows the correlations, while Table 4 presents the regression results. As shown in Table 4, the F values generated by all models are over 3.14 and statistically significant at the 1% level or above. Moreover, comparative model fit is assessed by changes in adjusted R2 across nested specifications, which range from 0.289 to 0.410, indicating stable explanatory power as key variables and interaction terms are introduced. Across Models 2, 4 and 6, CEO external directorships consistently show a positive and statistically significant association with AR values (p < 0.01), supporting H1. Table 4 also reports 95% confidence intervals, which complement statistical significance tests by assessing the robustness and economic relevance of the estimated effects. Economically, an additional CEO external directorship is associated with an increase in abnormal returns of approximately 20 basis points on the announcement day. For the median firm in our sample (market capitalization ≈ USD 99.3 million), this corresponds to an increase of roughly USD 0.2 million in shareholder value.
Summary of variables in hierarchical regression
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | AR | 1 | |||||||||||||||
| 2 | Firm size | −0.539** | 1 | ||||||||||||||
| 3 | Firm reputation | −0.157 | 0.461** | 1 | |||||||||||||
| 4 | IT capability | −0.084 | 0.301** | 0.190 | 1 | ||||||||||||
| 5 | Industry type | 0.033 | −0.290** | −0.112 | −0.103 | 1 | |||||||||||
| 6 | Clockspeed | 0.016 | 0.199 | −0.125 | 0.040 | −0.015 | 1 | ||||||||||
| 7 | Initial investment announcement | 0.166 | −0.356** | −0.186 | −0.275* | 0.284* | 0.032 | 1 | |||||||||
| 8 | Year of announcement | 0.068 | −0.277* | 0.037 | −0.218 | 0.117 | 0.079 | 0.052 | 1 | ||||||||
| 9 | Project status | 0.057 | −0.013 | 0.057 | 0.134 | 0.065 | −0.008 | 0.078 | −0.111 | 1 | |||||||
| 10 | CEO age | −0.294* | 0.379** | 0.130 | 0.193 | −0.020 | −0.049 | 0.046 | −0.106 | 0 0.084 | 1 | ||||||
| 11 | CEO gender | −0.023 | −0.162 | −0.122 | −0.132 | 0.182 | −0.061 | 0.010 | −0.057 | −0.058 | −0.061 | 1 | |||||
| 12 | CEO duality | 0.064 | −0.079 | 0.058 | −0.019 | −0.015 | −0.125 | 0.001 | 0.040 | 0.126 | 0.137 | 0.142 | 1 | ||||
| 13 | CEO tenure | −0.183 | 0.030 | 0.165 | 0.193 | −0.024 | −0.099 | 0.040 | 0.036 | 0.054 | 0.286** | 0.022 | 0.259* | 1 | |||
| 14 | Adoption strategy | 0.319** | −0.149 | −0.169 | 0.005 | 0.036 | 0.090 | −0.024 | −0.186 | 0.020 | 0.081 | 0.177 | −0.019 | −0.246* | 1 | ||
| 15 | Application type | 0.162 | −0.377** | −0.101 | −0.151 | 0.294** | 0.007 | 0.218 | 0.261* | −0.146 | −0.146 | 0.017 | 0.164 | 0.206 | −0.101 | 1 | |
| 16 | CEO external directorships | 0.279** | 0.268* | −0.149 | −0.004 | −0.235* | 0.003 | −0.032 | −0.137 | 0.003 | 0.367** | −0.083 | 0.145 | −0.011 | 0.188 | −0.011 | 1 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | AR | 1 | |||||||||||||||
| 2 | Firm size | −0.539** | 1 | ||||||||||||||
| 3 | Firm reputation | −0.157 | 0.461** | 1 | |||||||||||||
| 4 | IT capability | −0.084 | 0.301** | 0.190 | 1 | ||||||||||||
| 5 | Industry type | 0.033 | −0.290** | −0.112 | −0.103 | 1 | |||||||||||
| 6 | Clockspeed | 0.016 | 0.199 | −0.125 | 0.040 | −0.015 | 1 | ||||||||||
| 7 | Initial investment announcement | 0.166 | −0.356** | −0.186 | −0.275* | 0.284* | 0.032 | 1 | |||||||||
| 8 | Year of announcement | 0.068 | −0.277* | 0.037 | −0.218 | 0.117 | 0.079 | 0.052 | 1 | ||||||||
| 9 | Project status | 0.057 | −0.013 | 0.057 | 0.134 | 0.065 | −0.008 | 0.078 | −0.111 | 1 | |||||||
| 10 | CEO age | −0.294* | 0.379** | 0.130 | 0.193 | −0.020 | −0.049 | 0.046 | −0.106 | 0 0.084 | 1 | ||||||
| 11 | CEO gender | −0.023 | −0.162 | −0.122 | −0.132 | 0.182 | −0.061 | 0.010 | −0.057 | −0.058 | −0.061 | 1 | |||||
| 12 | CEO duality | 0.064 | −0.079 | 0.058 | −0.019 | −0.015 | −0.125 | 0.001 | 0.040 | 0.126 | 0.137 | 0.142 | 1 | ||||
| 13 | CEO tenure | −0.183 | 0.030 | 0.165 | 0.193 | −0.024 | −0.099 | 0.040 | 0.036 | 0.054 | 0.286** | 0.022 | 0.259* | 1 | |||
| 14 | Adoption strategy | 0.319** | −0.149 | −0.169 | 0.005 | 0.036 | 0.090 | −0.024 | −0.186 | 0.020 | 0.081 | 0.177 | −0.019 | −0.246* | 1 | ||
| 15 | Application type | 0.162 | −0.377** | −0.101 | −0.151 | 0.294** | 0.007 | 0.218 | 0.261* | −0.146 | −0.146 | 0.017 | 0.164 | 0.206 | −0.101 | 1 | |
| 16 | CEO external directorships | 0.279** | 0.268* | −0.149 | −0.004 | −0.235* | 0.003 | −0.032 | −0.137 | 0.003 | 0.367** | −0.083 | 0.145 | −0.011 | 0.188 | −0.011 | 1 |
Note(s): *p < 0.10; **p < 0.05; ***p < 0.01
Results of hierarchical regression analysis
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CEO ext. directorships | 0.002 | (2.942)*** | 0.002 | (3.464)*** | 0.002 | (3.380)*** | 0.002 | (2.297)** | 0.002 | (1.728)* | ||||||
| Intercept | 6.453 | (1.199) | 8.509 | (1.660) | 6.390 | (1.151) | 7.622 | (1.493) | 5.159 | (0.917) | 5.997 | (1.159) | 4.192 | (0.801) | 4.048 | (0.761) |
| Firm size | −0.014 | (−5.660)****** | −0.016 | (−6.629)*** | −0.014 | (−4.980)*** | −0.015 | (−5.834)*** | −0.012 | (−3.890)*** | −0.013 | (−4.827)*** | −0.012 | (−4.291)*** | −0.012 | (−4.255)*** |
| Firm reputation | 0.009 | (1.960)* | 0.012 | (2.690)*** | 0.010 | (2.008)** | 0.012 | (2.716)*** | 0.009 | (1.813)* | 0.012 | (2.597)** | 0.010 | (2.153)** | 0.010 | (2.103)** |
| IT capability | 0.002 | (0.452) | 0.000 | (0.127) | 0.003 | (0.615) | 0.002 | (0.433) | 0.002 | (0.493) | 0.001 | (0.293) | 0.002 | (0.515) | 0.002 | (0.523) |
| Industry type | −0.007 | (−1.315) | −0.003 | (−0.533) | −0.007 | (−1.239) | −0.001 | (−0.180) | −0.007 | (−1.202) | 0.000 | (0.073) | −0.000 | (−0.072) | −0.001 | (−0.127) |
| Industry clockspeed | 0.006 | (1.630) | 0.009 | (2.418)** | 0.005 | (1.365) | 0.008 | (2.115)** | 0.004 | (0.967) | 0.007 | (1.851)* | 0.005 | (1.151) | 0.006 | (1.733)* |
| Initial investment announcement | 0.000 | (0.036) | −0.002 | (−0.491) | 0.000 | (0.103) | −0.001 | (−0.168) | 0.002 | (0.388) | 0.001 | (0.211) | 0.002 | (0.594) | 0.003 | (0.611) |
| Year of announcement | −0.003 | (−1.188) | −0.004 | (−1.649) | −0.003 | (−1.139) | −0.004 | (−1.478) | −0.003 | (−0.906) | −0.003 | (−1.144) | −0.002 | (−0.787) | −0.002 | (−0.747) |
| Project status | 0.002 | (0.257) | 0.001 | (0.125) | 0.002 | (0.235) | 0.002 | (0.236) | 0.002 | (0.288) | 0.000 | (0.058) | 0.001 | (0.288) | 0.001 | (0.338) |
| CEO age | −0.000 | (−0.134) | −0.000 | (−1.675)* | −0.000 | (−0.573) | −0.001 | (−2.090)** | −0.001 | (−2.029)** | −0.001 | (−1.979)* | ||||
| CEO gender | −0.005 | (−0.728) | −0.005 | (−0.742) | −0.008 | (−1.003) | −0.008 | (−1.093) | −0.007 | (−0.963) | −0.007 | (−0.921) | ||||
| CEO duality | 0.000 | (0.054) | −0.001 | (−0.160) | 0.001 | (0.191) | 0.001 | (0.153) | −0.000 | (−0.086) | −0.000 | (−0.084) | ||||
| CEO tenure | −0.000 | (−1.595) | −0.000 | (−1.163) | −0.000 | (−1.059) | −0.000 | (−0.426) | −0.000 | (−0.503) | −0.000 | (−0.487) | ||||
| Adoption strategy | 0.008 | (1.879)* | 0.007 | (1.724)* | 0.004 | (0.487) | 0.004 | (0.508) | ||||||||
| Application type | 0.002 | (0.375) | −0.002 | (−0.562) | 0.001 | (0.226) | 0.000 | (0.050) | ||||||||
| CEO ext. directorships x adoption strategy | 0.001 | (1.725)* | 0.002 | (1.718)* | ||||||||||||
| CEO ext. directorships x Application type | 0.001 | (1.813)* | ||||||||||||||
| Model of F value | 4.629*** | 5.585*** | 3.377*** | 4.631*** | 3.145*** | 4.243*** | 4.139*** | 3.800*** | ||||||||
| R square | 0.374 | 0.452 | 0.411 | 0.514 | 0.440 | 0.536 | 0.509 | 0.509 | ||||||||
| Adjusted R square | 0.293 | 0.371 | 0.289 | 0.403 | 0.300 | 0.410 | 0.386 | 0.375 | ||||||||
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CEO ext. directorships | 0.002 | (2.942)*** | 0.002 | (3.464)*** | 0.002 | (3.380)*** | 0.002 | (2.297)** | 0.002 | (1.728)* | ||||||
| Intercept | 6.453 | (1.199) | 8.509 | (1.660) | 6.390 | (1.151) | 7.622 | (1.493) | 5.159 | (0.917) | 5.997 | (1.159) | 4.192 | (0.801) | 4.048 | (0.761) |
| Firm size | −0.014 | (−5.660)****** | −0.016 | (−6.629)*** | −0.014 | (−4.980)*** | −0.015 | (−5.834)*** | −0.012 | (−3.890)*** | −0.013 | (−4.827)*** | −0.012 | (−4.291)*** | −0.012 | (−4.255)*** |
| Firm reputation | 0.009 | (1.960)* | 0.012 | (2.690)*** | 0.010 | (2.008)** | 0.012 | (2.716)*** | 0.009 | (1.813)* | 0.012 | (2.597)** | 0.010 | (2.153)** | 0.010 | (2.103)** |
| IT capability | 0.002 | (0.452) | 0.000 | (0.127) | 0.003 | (0.615) | 0.002 | (0.433) | 0.002 | (0.493) | 0.001 | (0.293) | 0.002 | (0.515) | 0.002 | (0.523) |
| Industry type | −0.007 | (−1.315) | −0.003 | (−0.533) | −0.007 | (−1.239) | −0.001 | (−0.180) | −0.007 | (−1.202) | 0.000 | (0.073) | −0.000 | (−0.072) | −0.001 | (−0.127) |
| Industry clockspeed | 0.006 | (1.630) | 0.009 | (2.418)** | 0.005 | (1.365) | 0.008 | (2.115)** | 0.004 | (0.967) | 0.007 | (1.851)* | 0.005 | (1.151) | 0.006 | (1.733)* |
| Initial investment announcement | 0.000 | (0.036) | −0.002 | (−0.491) | 0.000 | (0.103) | −0.001 | (−0.168) | 0.002 | (0.388) | 0.001 | (0.211) | 0.002 | (0.594) | 0.003 | (0.611) |
| Year of announcement | −0.003 | (−1.188) | −0.004 | (−1.649) | −0.003 | (−1.139) | −0.004 | (−1.478) | −0.003 | (−0.906) | −0.003 | (−1.144) | −0.002 | (−0.787) | −0.002 | (−0.747) |
| Project status | 0.002 | (0.257) | 0.001 | (0.125) | 0.002 | (0.235) | 0.002 | (0.236) | 0.002 | (0.288) | 0.000 | (0.058) | 0.001 | (0.288) | 0.001 | (0.338) |
| CEO age | −0.000 | (−0.134) | −0.000 | (−1.675)* | −0.000 | (−0.573) | −0.001 | (−2.090)** | −0.001 | (−2.029)** | −0.001 | (−1.979)* | ||||
| CEO gender | −0.005 | (−0.728) | −0.005 | (−0.742) | −0.008 | (−1.003) | −0.008 | (−1.093) | −0.007 | (−0.963) | −0.007 | (−0.921) | ||||
| CEO duality | 0.000 | (0.054) | −0.001 | (−0.160) | 0.001 | (0.191) | 0.001 | (0.153) | −0.000 | (−0.086) | −0.000 | (−0.084) | ||||
| CEO tenure | −0.000 | (−1.595) | −0.000 | (−1.163) | −0.000 | (−1.059) | −0.000 | (−0.426) | −0.000 | (−0.503) | −0.000 | (−0.487) | ||||
| Adoption strategy | 0.008 | (1.879)* | 0.007 | (1.724)* | 0.004 | (0.487) | 0.004 | (0.508) | ||||||||
| Application type | 0.002 | (0.375) | −0.002 | (−0.562) | 0.001 | (0.226) | 0.000 | (0.050) | ||||||||
| CEO ext. directorships x adoption strategy | 0.001 | (1.725)* | 0.002 | (1.718)* | ||||||||||||
| CEO ext. directorships x Application type | 0.001 | (1.813)* | ||||||||||||||
| Model of F value | 4.629*** | 5.585*** | 3.377*** | 4.631*** | 3.145*** | 4.243*** | 4.139*** | 3.800*** | ||||||||
| R square | 0.374 | 0.452 | 0.411 | 0.514 | 0.440 | 0.536 | 0.509 | 0.509 | ||||||||
| Adjusted R square | 0.293 | 0.371 | 0.289 | 0.403 | 0.300 | 0.410 | 0.386 | 0.375 | ||||||||
Note(s): “CEO ext. directorships” denotes “CEO external directorships”
t−statistics in parentheses
*p < 0.10; **p < 0.05; ***p < 0.01
95% confidence intervals (computed from coefficient and t-statistic estimates) for
•CEO external directorships: Model 2 [0.0007, 0.0033], Model 4 [0.0009, 0.0031], Model 6 [0.0008, 0.0032], Model 7 [0.0003, 0.0037], Model 8 [−0.0003, 0.0043]
•Interaction terms
o CEO external directorships x adoption strategy: Model 7 [−0.0001, 0.0021], Model 8 [−0.0003, 0.0004]
o CEO external directorships x Application type: Model 8 [−0.0001, 0.0021]
The positive coefficient on CEO external directorships aligns with social capital mechanisms, whereby information access, legitimacy signaling, and coordination capacity reduce perceived execution and regulatory risk, outweighing agency costs in blockchain's high-uncertainty context. These results highlight that external directorships offer access to information, legitimacy and strategic insight – resources that help firms navigate the execution and regulatory challenges of blockchain investment (Karahanna and Preston, 2013; Wagner et al., 2014; Nugroho et al., 2020), while contradicting studies that suggest minimal or negative effects (e.g. Gedajlovic et al., 2013).
Several control variables reveal meaningful patterns. Firm size is negatively associated with AR values, while industry clockspeed and firm reputation are positively related, suggesting stronger market reactions for smaller firms, firms in fast-moving industries and firms with established reputations. Because the models control industry type and industry clockspeed, the results are robust to cross-industry heterogeneity and are unlikely to be driven by industry-specific innovation dynamics. CEO age is negatively associated with AR values, aligning with the notion that younger CEOs may be perceived as more open to innovation. Collaborative strategy is positively associated with AR values, reinforcing the importance of credibility and inter-firm cooperation.
5.2 Results of contextual factors of CEO external directorships (H2–H3) (RQ2)
To test H2 and H3 (RQ2), we estimate interaction terms between CEO external directorships and adoption strategy as well as application type in the main regression models (Table 4). For H2, results in Models 7 and 8 show that the interaction between CEO external directorships and collaborative adoption strategy is positively related to AR values (p < 0.10). The results support H2 and indicate that CEO external directorships are particularly valuable when blockchain initiatives require interfirm trust and coordination. This supports prior empirical studies (e.g. Nawinna and Venable, 2019; Krause et al., 2007) showing that executive social networks facilitate collaboration and enhance firm performance.
H3 predicts that CEO external directorships provide substantial positive returns in the context of financial applications. Result in Model 8 shows that the interaction between CEO external directorships and financial applications is CEO external directorships is positive and significant (p < 0.10). These results suggest that CEO external directorships added legitimacy and regulatory insight in more complex financial settings, consistent with previous studies (Boso et al., 2013; Cornwell et al., 2017) showing that executive network ties facilitate access to legal and regulatory resources.
Overall, the magnitude of the effect suggests that investors place economically meaningful value on CEO external directorships when coordination or regulatory complexity is elevated. Stronger effects in collaborative and financial blockchain contexts are more consistent with social capital and signaling mechanisms than with agency-based predictions of CEO busyness, suggesting that investors prioritize legitimacy and coordination benefits when uncertainty is elevated. The results for H2 and H3 further demonstrate that the value of CEO external directorships is contingent on project context, aligning with prior work emphasizing the contextual nature of executive social capital (Finkelstein et al., 2009; Geletkanycz and Boyd, 2011).
5.3 Robustness checks
To address robustness to alternative specifications and potential endogeneity concerns, we conducted a series of robustness checks. First, we re-estimated models using an alternative measure of firm size (log of employees) and by adding financial leverage (debt/total assets) as an additional control. The results remained stable across these specifications (see Table S4 in Supplementary Material S5). We also re-estimated abnormal returns using the Fama–French three-factor model rather than the CAPM (see Table S5 in Supplementary Material S5). In addition, regression results remain qualitatively unchanged when using cumulative abnormal returns over the [−1, 0] window as the dependent variable instead of day 0 abnormal returns (see Table S6 in Supplementary Material S5). Cumulative AR[−1, 0] is commonly used in event studies to account for minor pre-announcement information leakage while minimizing contamination from post-announcement confounding events (MacKinlay, 1997). Together, these tests indicate that the findings are not sensitive to model choice, control specification or event-window definition.
Second, to address concerns regarding the count-based operationalization of CEO external directorships, we reestimated Models 6, 7 and 8 using an alternative specification based on the logarithmic transformation log(1 + number CEO external directorships). The results remain robust, with a consistent sign and statistical significance (see Table S7 in Supplementary Material S5).
Third, to assess robustness across subsamples, we conducted additional analyses restricting the sample to the first blockchain announcement per firm. The results remain qualitatively unchanged, indicating that the main findings are not driven by repeated announcements or sample composition. We further reestimated the models after excluding dominant industries in our sample (SIC 60, representing 25% of observations). The results remain consistent (see Tables S8 and S9 in Supplementary Material S5).
Finally, to confirm the robustness of results on H2 and H3, we conducted subgroup and Chow tests. Subgroup regressions and Chow tests yield qualitatively identical conclusions (see Table S10 in Supplementary Material S5).
6. Implications
Analyzing 200 blockchain announcements from 138 U.S. public firms, we find that CEO external ties enhance market value, particularly under collaborative strategies and financial application settings. By clarifying how CEO external social capital shapes IT investment outcomes, this study addresses the research gap: how CEO external directorships shape investor reactions to blockchain announcements and under what contingencies this effect is strongest. In doing so, this study contributes to research on executive governance and IT investment by clarifying how CEO external directorships shape investor expectations toward blockchain initiatives. Our findings demonstrate that the value of external ties is contingent on adoption strategy and application type, highlighting the context-dependent nature of executive social capital.
6.1 Theoretical implications
This study advances three distinct theoretical fronts, each tied to explicit gaps identified in the literature (Section 2.4). First, this research contributes to the long-standing debate on whether CEOs' external directorships benefit or harm their home companies. We show that external directorships positively influence market reactions to blockchain investment announcements, supporting research that highlights the value of executive social networks in facilitating IT adoption (e.g. Karahanna and Preston, 2013), and countering studies that emphasize minimal or negative effects (e.g. Gedajlovic et al., 2013). These results clarify the value of external ties in volatile, innovation-intensive environments. Importantly, the positive findings also suggest that in high-uncertainty blockchain investment contexts, social capital and signaling mechanisms outweigh agency-based concerns, as investors appear to value the legitimacy and coordination benefits of external ties more than potential governance downsides.
Second, integrating contingency theory, we establish adoption strategy and application type as theoretically grounded interaction factors that shape the moderating role of CEO external directorships, clarifying when external social capital creates value. By linking the pattern of abnormal returns to the theorized mechanisms, the results provide empirical support for the argument that executive social capital dominates agency costs when blockchain investments intensify coordination and regulatory demands. External directorships generate stronger positive value in collaborative strategies and financial applications – settings characterized by elevated coordination and regulatory complexity. This reinforces the view that external social capital is not inherently beneficial, but becomes valuable when aligned with the informational, legitimacy and coordination needs of the innovation context (e.g. Finkelstein et al., 2009; Burt, 1997).
Third, we extend the literature on executive network ties in IT investment by shifting attention from internal social capital (e.g. CIO-TMT relationships) and traditional top management support and characteristics (Farnoush et al., 2022) to CEO external board-level ties. We demonstrate that these ties function as boundary-spanning mechanisms that enable firms to navigate uncertainty, interorganizational interdependence and regulatory ambiguity associated with blockchain investment.
6.2 Practical implications
This research offers actionable insights for CEOs, boards, senior managers and investors involved in blockchain investment decisions.
First, for CEOs, the findings highlight the strategic value of cultivating strong external directorships. Such ties provide access to regulatory knowledge, technical expertise and collaboration opportunities – resources especially critical for blockchain projects in financial services or strategic partnerships. CEOs should view external board memberships not only as professional credentials but also as strategic tools for driving digital transformation and navigating uncertain technological contexts. Second, for boards, CEO network capital should be considered a strategic asset. CEOs with external directorships are better positioned to bring best practices, collaborative networks and reputational capital into the firm. When recruiting or evaluating CEOs for roles involving emerging technologies, boards may weigh external board experience as an important criterion, particularly for collaborative or regulation-intensive blockchain initiatives.
Third, for senior managers, aligning blockchain strategies with the CEO external network strength can improve execution outcomes. When CEOs possess extensive external ties, firms may benefit more from collaborative blockchain models. In financial or highly regulated applications, managers can leverage these ties to access external expertise and reduce compliance risk.
Fourth, for investors and analysts, CEO external directorships signal blockchain execution capability. Investors can use these ties as indicators of a firm's readiness to navigate blockchain complexity, particularly in collaborative or financial contexts. The stronger abnormal returns observed in such settings suggest that the market responds more favorably to firms led by CEOs who can mobilize external knowledge, legitimacy and partner support.
Finally, for organizations investing in blockchain, leveraging CEO external networks can strengthen stakeholder confidence – ultimately improving market perceptions. More broadly, well-connected CEOs bring governance experience, reputation incentives, regulatory access and collaborative capabilities that support responsible blockchain implementation. These qualities enhance transparency, trust and accountability in digital ecosystems—societal outcomes that are especially important given blockchain's role in financial services, data integrity and multi-party digital infrastructures.
Overall, while our findings suggest that CEO external directorships can be a strategic asset in blockchain initiatives – particularly collaborative or financial applications – boards and executives should weigh potential trade-offs. Excessive external commitments may increase CEO busyness or dilute firm-specific focus (Gedajlovic et al., 2013), potentially offsetting benefits in less uncertain contexts. Stakeholders may therefore value moderate external ties that balance network advantages with governance risks.
6.3 Limitations and future research
We acknowledge several limitations, which also offer opportunities for future work. First, our sample consists of publicly listed U.S. firms, which may limit generalizability. Governance structures, capital markets and the legitimacy of external directorships differ across countries, and firms that adopt blockchain without public announcements are not captured in our dataset. Subsequent studies could extend to private firms, non-U.S. contexts and alternative disclosure channels to provide richer insights into cultural, regulatory and institutional contingencies. Future studies could employ richer governance data (e.g. board expertise, independence) and more comprehensive firm-level controls (e.g. institutional ownership) to further isolate CEO external directorship effects.
Second, CEO external directorships were measured as the number of outside board positions, which captures breadth but not qualitative aspects such as board prestige, industry relevance or strategic alignment. Future research could incorporate weighted measures that reflect board influence or relevance. Similarly, our binary classification of adoption strategy (“individual” versus “collaborative”) simplifies the complex continuum of blockchain partnerships. More granular indices of collaboration may yield deeper insights.
Third, although our findings highlight the benefits of external ties, excessive board commitments may create distraction or agency costs. Future work could test nonlinear effects or account for board workload. In addition, our sample leans toward financial blockchain applications, limiting insight into nonfinancial domains such as supply chains, intellectual property and identity management. These areas may elicit different investor reactions and warrant explicit investigation.
Fourth, like other event studies (e.g. Roztocki and Weistroffer, 2015; Lui et al., 2021), our design cannot fully rule out unobserved confounding events during the event window, including cross-firm announcements (Dardan et al., 2005). Moreover, event studies capture only short-term market reactions, which may reflect temporary over- or underreaction. Consistent with event-study logic, our findings reflect short-term investor expectations at the time of announcement rather than realized or long-term firm performance outcomes. Future research could incorporate long-term performance measures such as ROA or Tobin's Q to provide a more comprehensive view of strategic impact.
Finally, relatively few CEOs in our sample were connected to firms that had previously adopted blockchain, preventing an analysis of whether ties to blockchain-experienced firms provide additional benefits. As blockchain investment becomes more widespread, future studies could investigate such network spillovers and employ qualitative methods such as case studies or surveys to provide additional insights into the mechanisms through which these ties impact blockchain investment outcomes.
The supplementary material for this article can be found online.

