CEO Personal Characteristics and Investment-Cash Flow Sensitivity: An Analysis of Indian Independent (Non-Business-Group-Affiliated) Firms and Business Group-Affiliated Firms

Abstract

This study investigates the relationship between the CEO characteristics and investment–cash flow sensitivity (ICFS) of Indian manufacturing firms. By using the GMM technique, this study finds that CEO characteristics reduce ICFS. Further, this study examines the moderating role of business group-affiliated firms, independent firms (non-business group-affiliated firms), and firm size on the relationship between CEO characteristics and ICFS. The results reveal that group affiliation moderates the effectiveness of CEO characteristics in reducing ICFS. In addition to this, independent firms rely more heavily on the individual capabilities of CEOs to overcome financial constraints and mitigate ICFS, whereas group firms benefit from structural advantages that diminish the relative impact of CEO characteristics on ICFS. Additionally, this study finds that firm size also moderates the relationship between CEO characteristics and ICFS. The results reveal that CEO characteristics significantly reduce ICFS, with a more pronounced effect in small-sized independent firms compared to their larger counterparts. However, in group-affiliated firms, CEO characteristics have a minimal effect on ICFS, and this impact remains consistent across small and large group firms. These findings offer valuable insights for firms, lending institutions, and investors, emphasizing the role of CEO characteristics in shaping financial decision making, especially in independent and smaller firms.

1. Introduction

This study investigates the effect of CEO (chief executive officer) characteristics on the investment–cash flow sensitivity (ICFS) of Indian firms. This study also examines whether the ownership structure (business group-affiliated firms and independent firms, i.e., non-business group-affiliated firms) and firm size moderate the relationship between CEO characteristics and ICFS.

It has been documented that internal and external financing are not perfect substitutes in an imperfect capital market due to the presence of agency costs (Jensen & Meckling, 1976) and information asymmetry costs (Myers & Majluf, 1984). In addition, these costs, i.e., agency costs and information asymmetry costs, create a wedge between the external and internal finances that ultimately makes external finance more costly. Therefore, when external finance becomes costly, firm investment becomes reliant on internal cash flow. Particularly, when a firm’s investment becomes more sensitive to the firm cash flow, it is referred to as investment-cash flow sensitivity (ICFS). Fazzari et al. (1988) revealed that ICFS would be robust for firms that confronted the maximum wedge between the cost of internal and external funds. It has been found that firm investment is highly sensitive to cash flow (Gupta & Mahakud, 2019).

The Upper Echelons Theory (UET) proposed by Hambrick and Mason (1984) posits that firm outcomes are partially predicted by the background characteristics of top executives, particularly the CEO. According to the UET, factors such as age, education, functional background, tenure, and personal values shape how CEOs interpret strategic situations and make decisions. These characteristics influence their cognitive base and values, thereby affecting the firm’s strategic direction. For example, studies have shown that younger CEOs adopt aggressive investment strategies, while those with financial backgrounds may favor capital-intensive projects (Bertrand & Schoar, 2003; Hambrick, 2007). Therefore, CEO characteristics not only shape risk preferences and strategic choices but also significantly influence firm-level investment behavior.

The influence of CEO traits on firm investment behavior is shaped by the institutional and ownership structures in which firms operate, and this varies significantly across countries (Aguilera & Jackson, 2003; Crossland & Hambrick, 2011). In India, business group-affiliated firms, hereafter referred to as group firms, are widespread and often controlled by family promoters who exert significant influence over strategic and financial decisions (Khanna & Palepu, 2000a). In such settings, CEOs, particularly in group firms, tend to have limited strategic autonomy, which can dilute the effect of their individual traits on firm-level outcomes (Carney & Gedajlovic, 2002; Khanna & Yafeh, 2007; Young et al., 2008). This is in contrast to independent firms, where CEOs typically enjoy greater discretion and their personal characteristics more directly shape investment decisions (Bertrand & Schoar, 2003).

In developed economies such as the United States and United Kingdom, dispersed ownership and strong legal protections for investors foster a governance environment where CEOs are held accountable for performance, and their individual traits are known to significantly affect firm strategy, risk taking, and financial policies (Custódio & Metzger, 2014). In emerging markets, these dynamics vary further due to differing institutional frameworks. In China, for instance, many large firms are state owned, and CEO appointments are often politically driven, with limited managerial discretion and strong bureaucratic oversight (Fan et al., 2007). Similarly, in South Korea’s chaebol system, CEO decision making is constrained by centralized family control, although regulatory reforms have begun to increase professionalization and accountability (Kim et al., 2004).

Against this backdrop, India presents a unique hybrid context. Business group affiliation reduces the observable impact of CEO traits on investment behavior, and CEO characteristics play a more significant role in shaping investment behavior. In addition to this, recent studies have revealed the influence of group affiliation on finance decisions taken by firms (Chang & Hong, 2000; Ghemawat & Khanna, 1998; Khanna & Rivkin, 2001; Khanna & Palepu, 1999a, 1999b, 2000a, 2000b). Consequently, it would be more interesting to investigate the impact of the CEO’s characteristics on ICFS considering the moderating role of ownership structure (group firms and independent firms). Empirical investigations of the moderating role of group firms and independent firms on the relationship between CEO characteristics and ICFS are mostly absent from the literature and particularly absent in the context of the Indian economy. Therefore, the following are the research objectives of this study.

To examine the impact of CEOs on ICFS in Indian manufacturing firms.

To analyze how ownership structure (group firms and independent firms) influences the relationship between CEO characteristics and ICFS.

To analyze how firm size moderates the relationship between CEO characteristics and ICFS in both group and independent firms.

To contribute to the UET by investigating how CEO traits, shaped by organizational and institutional context, influence ICFS in an emerging market.

The aforementioned objectives are motivated by research gaps in the existing literature. The following are the research gaps addressed by this study: First, most prior research on CEO traits and firm financial behavior is concentrated in developed economies, offering limited insight into emerging markets like India, where ownership structures, institutional settings, and managerial discretion differ significantly. Second, to add novel insights, the differences in features of group firms and non-group firms moderate the role of CEO characteristics on ICFS are partially explored. Third, the moderating effect of firm size on the relationship between CEO characteristics and ICFS remains underexplored. By addressing these gaps and grounding the analysis in UET, this study significantly contributes to the literature by empirically demonstrating these differences, thereby reinforcing the idea that the effect of CEO traits is context dependent and moderated by ownership structure and firm size.

The remainder of the paper is organized as follows. Section 2 presents a theoretical framework and hypothesis formation. Section 3 contains materials and methods. Section 4 presents the results. Section 5 presents the discussion and conclusion.

2. Theoretical Framework and Hypotheses Formation

2.1. Investment–Cash Flow Sensitivity (ICFS)

The literature review on ICFS has received much attention. However, there are several unexplored factors that can affect ICFS. According to Crisóstomo et al. (2014), Brazilian businesses incur financial constraints due to their dependence on internally generated funds for investment. Ro et al. (2017) conducted a recent study that also demonstrates that financial development has an impact on investment, thereby reducing the financial restrictions of companies in Korea. The impact of financial development on investment is contingent upon the scale of the firm, the extent of the financial crisis, and the industry. It is evident that the presence of family proprietors diminishes ICFS (Sitthipongpanich, 2017). Gupta and Mahakud (2019) posit that the investment decisions of Indian manufacturing firms are influenced by the availability of cash flow and that ICFS is reduced by favorable economic conditions.

Yi (2023) demonstrates that improved corporate governance substantially mitigates ICFS. Gupta (2023) discovers that GPR enhances the sensitivity of investment to cash flow. Moreover, this investigation demonstrates that the influence of GPR on investment–cash flow sensitivity is lower (greater) for group (independent) firms. Gupta et al. (2024) discover that during the crisis (pre- and post-crisis), economic policy uncertainty increases ICFS to a greater or lesser extent. Dash and Sethi (2024) demonstrate that the adverse impact of EPU on ICFS is because of firms’ Environmental, Social, and Governance (ESG) performance. Nguyen (2024) posits that the availability of internal capital flows is less of a limiting factor for firms, as it reduces information asymmetry. Consequently, firms are able to execute investments more efficiently. Doruk (2025) conducts a bibliometric and systematic literature review that emphasizes the necessity of examining financing constraints and ICFS in emerging markets in the context of capital market imperfections, financial liberalization, and macroeconomic conditions. Additionally, it has been asserted that ICFS is elevated by geopolitical risk; the age of the CEO mitigates the impact of geopolitical risk on ICFS (Gupta, 2025). Considering the studies mentioned above, it would be more interesting to examine the effect of CEO characteristics on ICFS considering the moderating role of ownership structure (group and independent firms). In this context, the next section highlights the features of group and independent firms.

2.2. Group Firms vs. Independent Firms

Several studies in corporate finance have explored the importance of business group affiliation (Khanna & Palepu, 1999a, 1999b, 2000a, 2000b; Chang & Hong, 2000; Khanna & Rivkin, 2001). Leff (1978) characterizes business groups as networks of legally independent firms. In India, these groups are typically highly diversified, predominantly family owned, and interconnected through mechanisms such as mutual board representation and cross-equity holdings. Khanna and Palepu (2000a) find that firms affiliated with business groups tend to outperform their independent counterparts. Numerous studies have argued that members of group firms shared several advantages, which includes mitigating information asymmetry (Hoshi et al., 1991), availability of intra-firm loans and easy access to the internal capital market (Khanna & Palepu, 1999a, 1999b), firm profitability and sharing of technology (Chang & Hong, 2000), and diversifying of risk and internal sharing of profit (Claessens et al., 2000; Khanna & Yafeh, 2005). Gupta and Mahakud (2018) find that the investment behavior of group firms is less affected by external and internal factors than independent firms. Gupta (2023) also reported that the effect of geopolitical risk is higher on the ICFS of non-business group firms than group firms.

On the other hand, independent firms are not affiliated with any business group. Thus, independent firms do not share the benefits of group affiliation, like internal capital sharing, technology, and risk sharing. In this context, this study documents that independent firms must obtain external financing from lending agencies, and ultimately, independent firms’ investments become highly sensitive to cash flow. Further, independent firms work hard to obtain external financing for the firm’s investment; therefore, it can be argued that independent firms’ investment is highly reliant on cash flow based on internal financing (Gupta & Mahakud, 2018; Gupta, 2023; Kumar & Ranjani, 2018). Further, group firms are large, reputable, and share risk, funds, and technology (Gupta & Mahakud, 2018; Gupta, 2023; Kumar & Ranjani, 2018). Considering the differences of the features of group firms and independent firms, it will be more thought provoking to examine the moderating role of group and independent firms on the relationship between CEO characteristics and ICFS. Therefore, the next sections briefly explain the CEO characteristics and their role in affecting ICFS.

2.3. CEO Characteristics

The Upper Echelons Theory posits that organizational outcomes such as strategic choices and performance levels can be partially predicted by the background characteristics of top executives, particularly the CEO. According to UET, factors such as age, education, functional background, tenure, and personal values shape how CEOs interpret strategic situations and make decisions. It has been reported that there is a relationship between corporate finance decisions and CEO characteristics (Shaheen et al., 2024; Bertrand & Schoar, 2003; Stetsyuk et al., 2024; Hambrick & Mason, 1984; Malmendier & Tate, 2005a; El Abiad et al., 2024; Alrobai & Albaz, 2025). This study considers CEOs’ characteristics, such as the CEO’s age, tenure, financial education, and career experience.

It has been argued that the CEO’s age impacts corporate finance decisions. However, studies have shown contradictory views on CEO age. The existing literature indicates that younger CEOs prioritize their careers over risk taking, resulting in an overly conservative investment policy (Hirshleifer & Thakor, 1992; Holmström, 1999; Scharfstein & Stein, 1990), and avoid risky and innovative investment due to their significant career concerns (Zwiebel, 1995). On the other side, the existing literature also reveals that younger CEOs are more likely to take risks and make bolder decisions in investment for firms (Li et al., 2017; Serfling, 2014). Consequently, older CEOs are inclined to prefer a tranquil lifestyle, maintain the status quo, and adopt a risk-averse approach, which results in their reluctance to invest in risky projects (Bertrand & Schoar, 2003; Serfling, 2014). The existing research also contends that long-tenured CEOs are risk-averse and have limited knowledge of the evolving environment, which hinders their capacity to increase the firm’s investment when internal funds are insufficient (Graham et al., 2013; Miller & Shamsie, 2001; Hambrick et al., 1993; Hambrick & Mason, 1984). As a result, CEOs who have been in office for an extended period of time are inclined to allocate more resources to riskier investment initiatives than their counterparts who have been in office for a shorter period of time (Miller & Shamsie, 2001; Richard et al., 2009).

Further, CEOs with educational background in financial stream education have better understanding of the financial market and macroeconomic conditions (Malmendier & Tate, 2005a; Ben Mohamed et al., 2014). Custódio and Metzger (2014) report that CEOs with financial expertise can raise funds under poor credit conditions. King et al. (2016) state that CEOs with better MBA education secure superior bank performance outcomes. All this supporting evidence suggests that these CEOs raise external capital cost-effectively and ultimately reduce the cost of capital. The existing literature also argues that CEOs with experience invest more, and their investment levels are not affected by the limited availability of internal funds (Gupta et al., 2018). It is also documented that experienced CEOs have a strong social network that helps them raise funds (Gupta et al., 2018; Haynes & Hillman, 2010; Hillman & Dalziel, 2003). Further, an experienced CEO is expert in formulating better investment strategies than inexperienced CEOs (Haynes & Hillman, 2010; Hillman & Dalziel, 2003). The aforementioned literature reveals that CEO characteristics play a significant role in investment and financing decisions, and it is thus important to examine the role of these characteristics on ICFS for group and independent firms.

2.4. Hypotheses Framework

Considering the overall outcome of the theoretical framework, it can be asserted that cash flow plays a significant role in determining corporate investment, and ICFS is a crucial issue for the financing and investment decisions of firms. Given that CEO characteristics such as age, tenure, financial education, and career experience influence managerial decision making and risk preferences, it is reasonable to expect that these traits will shape how investment decisions are made under financial constraints and may reduce the role of cash flow in the investment decisions of firms with easy access to external financing and ultimately may reduce ICFS. Specifically, CEOs with greater experience or financial expertise may be better equipped to access alternative financing sources, reduce reliance on internal cash flow, and allocate capital more efficiently. Based on this rationale, this study proposes the following hypothesis.

Hypothesis 1.

CEO Characteristics Significantly Reduce ICFS.

The literature reveals that group firms are different from independent firms in terms of their internal capital, investment level, capital financing, risk, and technology sharing (Gupta, 2023; Ghemawat & Khanna, 1998; Khanna & Palepu, 2000a, 2000b; Chang & Hong, 2000; Khanna & Rivkin, 2001). Therefore, group firms often benefit from internal capital markets, shared resources, reputational advantages, and easier access to external finance, which may reduce their dependence on internal cash flow for investment. In contrast, independent firms, lacking such advantages, are more likely to face financial constraints and thus rely more heavily on internal cash flow to fund investments. Within this context, it can be argued that CEO characteristics are associated with capabilities, risk-taking approach, experience, knowledge, and a strong network with leading agencies, which helps an independent firm access external finance and thus rely less on internal funds to execute investment decisions. Therefore, the influence of CEO characteristics such as financial expertise, experience, and networks may vary depending on the firm’s group affiliation. CEOs in independent firms may play a more pivotal role in reducing investment–cash flow sensitivity (ICFS) by leveraging their skills and connections to access external finance. Conversely, the same characteristics may have a diminished impact in group firms where strategic decisions and financing are more centralized or constrained. Therefore, this study posits following hypothesis:

Hypothesis 2.

Business group affiliation and non-business group affiliation moderate the association between CEO characteristics and ICFS.

Gertler and Gilchrist (1994) have contended that size serves as a proxy for accessing external markets and finance. Additionally, small-sized organizations are perceived as financially constrained (Iqbal et al., 2020). Gertler and Gilchrist (1994) contend that small firms are generally considered financially constrained due to their young age, limited collateral, high level of firm-specific risk, and limited ability to secure external financing. In contrast, larger firms, often affiliated with business groups, benefit from internal capital markets and hold more tangible assets (Gertler & Gilchrist, 1994), which can serve as collateral and enhance their ability to secure external financing. Therefore, small-sized firms are unable to invest more in firms’ assets due to the unavailability of sufficient internal funds and limited access to financial markets. Supporting this view, Gupta and Mahakud (2019) find that in India, small businesses are more financially constrained, and their investments are more susceptible to fluctuations in cash flow. In this context, the impact of CEO characteristics such as experience, financial education, and external networks may be especially significant for small independent firms, as leadership capabilities can be instrumental in alleviating financial constraints. However, in larger firms or those affiliated with business groups, these traits may have a weaker influence due to better access to finance and centralized decision-making structures. Therefore, this study argues firm size moderates the association between CEO characteristics and ICFS such that CEO characteristics have a stronger effect in reducing ICFS in small-sized independent firms than in small-sized group firms and proposes the following hypothesis:

Hypothesis 3.

Firm size moderates the association between CEO characteristics and ICFS differently across independent and group firms.

3. Materials and Methods

3.1. Materials (Data and Variables)

The data of this study were extracted from the Prowess database1 and Bloomberg database. The data of firm-level variables, i.e., group firms and independent firms, were extracted from the Prowess database, and the data of CEO characteristics were collected from the Bloomberg database. Overall, the study considers the balanced panel dataset of 581 firms for the period spanning from 2010 to 2022. The details of the sample, firm type, and their measurement are provided in

Table 1. Sample description.

Firm Type	Number of Firms	Description
Business group-affiliated firms (Group Firms)	319	Firms belonging to any business group are considered as business group-affiliated firms or group firms.
Independent Firms	262	Firms not belonging to any business group are considered as non-business group-affiliated firms or independent firms.
LBGA (large group firms)	137	Firms that are above the median of total assets of group firms.
SBGA (small group firms)	182	Firms that are below the median of total assets of group firms.
Large independent firms	92	Firms that are above the median of total assets of independent firms.
Small independent firms	170	Firms that are below the median of total assets of independent firms.

Source: Author’s calculation.

.

Corporate investment is the dependent variable of this study. This study includes independent variables such as cash flow (CF), sales (S), and Tobin’s Q ratio (Q). The major variables of the study are CEO characteristics, i.e., CEO age, tenure, financial education, and career experience. This study uses firm size, leverage, and firm age as control variables.

Table 2. Variable description.

Variables	Measurement
${\displaystyle \frac{I}{K_{t-1}}}$ (Corporate Investment)	Following the study of Crisóstomo et al. (2014), the dependent variable of investment in fixed assets (I) is scaled by the capital stock $(K_{t-1}$) of the beginning of the period.
Cash Flow (CF)	The ratio of profit after tax plus depreciation to capital stock at the beginning of the period.
Sales Growth (S)	S is measured as the sales to capital stock at the beginning of the period.
Tobin’s Q (Q)	Tobin’s Q is a ratio of the market value of a firm’s assets to the replacement cost of firm’s assets.
CEO’s age (CAGE)	CEO’s actual age.
CEO’s tenure (TENU)	CEO’s tenure is the number of years the CEO has held the position in the company.
CEO’s education background in finance stream (FE)	Following Malmendier and Tate (2005b), this study uses the financial education of CEOs2. CEOs who hold graduate degrees in accounting, finance, commerce, or economics are classified as having an educational background in the finance stream. Conversely, CEOs without qualifications in these areas are considered to have a non-finance educational background. The variable representing financial education (FE) is assigned a value of one if the CEO possesses any of the specified degrees and zero otherwise.
CEO’s career experience (CE)	CEO’s career experience (CE) is the actual total experience of the CEO.
Firm size (SZ)	The natural logarithm of total assets measures the size of the firm.
Leverage (LEV)	Leverage is calculated by taking the ratio of total debt to total assets.
Firm age (AGE)	Firm age is measured as the current year of the firm minus the incorporation year of firm.

Source: Author’s calculation.

presents the measurement of the variables used in this study. To reduce the impact of outliers, all variables are winsorized at the top and bottom 1% of the distribution.

Table 3. Descriptive statistics.

All Firms
Variables	No. of Obs.	Mean	Median	SD	Minimum	Maximum
	(1)	(2)	(3)	(4)	(5)	(6)
${\displaystyle \frac{I}{K_{t-1}}}$	6921	0.12	0.10	0.18	0.03	0.27
CAGE	6921	56.22	56.00	10.42	26.00	72.00
Tenure	6921	9.15	9.50	2.24	4.27	28.11
CEO’s Financial Education	6921	0.45	0.50	0.43	0.18	0.67
CEO’s Career Experience	6921	17.11	17.00	4.31	5.13	29.15
${\displaystyle \frac{CashFlow}{K_{t-1}}}$	6921	0.22	0.21	0.18	−0.132	0.484
${\displaystyle \frac{Sales}{K_{t-1}}}$	6921	0.29	0.25	0.75	−0.17	0.44
Tobin’s Q	6921	1.34	1.32	0.84	0.22	2.29
Leverage	6921	0.41	0.0621	0.0688	0.0004	0.4953
Ln (Firm Size)	6921	8.26	8.11	2.92	4.21	12.78
Firm Age	6921	35.24	35.78	22.38	19.22	57.28
Group firms
${\displaystyle \frac{I}{K_{t-1}}}$	3774	0.14	0.11	0.20	0.06	0.34
CAGE	3774	53.21	53.00	8.47	24.00	69.00
Tenure	3774	7.31	7.50	2.08	6.48	34.44
CEO’s Financial Education	3774	0.37	0.40	0.41	0.14	0.52
CEO’s Career Experience	3774	14.27	14.00	3.38	4.16	27.25
${\displaystyle \frac{CashFlow}{K_{t-1}}}$	3774	0.24	0.23	0.14	−0.012	0.513
${\displaystyle \frac{Sales}{K_{t-1}}}$	3774	0.31	0.28	0.71	−0.12	0.49
Tobin’s Q	3774	1.41	1.40	0.94	0.31	2.51
Leverage	3774	0.43	0.0573	0.0723	0.0064	0.4631
Ln (Firm Size)	3774	9.91	9.10	2.88	6.29	14.71
Firm Age	3774	33.21	33.00	21.23	18.87	52.33
Independent firms
${\displaystyle \frac{I}{K_{t-1}}}$	3117	0.11	0.105	0.19	0.04	0.28
CAGE	3117	57.25	57.00	11.47	29.00	70.00
Tenure	3117	6.11	6.00	2.11	5.66	23.27
CEO’s Financial Education	3117	0.47	0.45	0.39	0.21	0.64
CEO’s Career Experience	3117	19.21	19.00	5.11	7.41	31.11
${\displaystyle \frac{CashFlow}{K_{t-1}}}$	3117	0.21	0.20	0.18	−0.279	0.462
${\displaystyle \frac{Sales}{K_{t-1}}}$	3117	0.26	0.24	0.72	−0.18	0.47
Tobin’s Q	3117	1.32	1.30	0.81	0.21	2.17
Leverage	3117	0.46	0.080	0.0734	0.007	0.493
Ln (Firm Size)	3117	9.49	9.40	3.19	8.53	19.43
Firm Age	3117	37.44	37.00	21.65	24.11	61.57

Source: Author’s calculation.

presents the descriptive statistics of variables and demonstrates that the distribution of variables of this study is not significantly skewed, as the mean and median values are typically near to one another. Investment growth is responsible for 12% of the capital stock of an average Indian listed firm. Cash flow is 22% of capital stock. Additionally, the average age of CEOs is 56.22 years, which indicates that they are more experienced. The average tenure of a CEO is 9.15 years. It is observed that the average educational background of CEOs in the finance domain is 0.45. Lastly, the average percentage of CEO experience is 17.11%.

Table 3 also presents summary statistics on CEO and firm characteristics for group and independent firms. On average, Table 3 demonstrates that group firms experience higher investment, sales, and cash flow than independent firms. In addition, group firms have more debt than independent firms. Further, group firms are bigger compared to independent firms. In addition, CEOs of group firms are younger, have more tenure, and have less experience than those of independent firms. Group firms have fewer CEOs with educational background in the finance stream than independent firms. The correlation matrix does not find any multicollinearity issue; this study does not show the correlation matrix due to space limitations.

3.2. Estimation Methods and Model Specification

This study employs the system generalized method of moments (GMM) developed by Arellano and Bover (1995) and further refined by Blundell and Bond (1998). All equations in this study are estimated using system GMM, with lagged values of the right-hand side variables serving as instruments. To ensure the validity of the instruments and the robustness of the model, the study conducts several diagnostic tests. The Hansen over-identification test evaluates the validity of the instruments by testing whether they are uncorrelated with the error term, under the null hypothesis that the instruments are valid. Additionally, the AR(n) test is used to detect n-th order autocorrelation in the differenced residuals, which, under the null hypothesis, should not exhibit serial correlation. Overall, the system GMM estimator effectively addresses key estimation challenges in analyzing the dynamic relationship between CEO characteristics and ICFS.

Following the studies of Ratti et al. (2008), Samet and Jarboui (2017), and Gupta (2025), this study uses a model that incorporates the interactions of the CEO’s characteristics with cash flow along with firm level and control variables. Here, this study assumes that the CEO’s characteristics may change the role of the cash flow for investment, that is, ICFS, and the model is specified as follows:

$$\begin{array}{ll}{\left({\displaystyle \frac{I}{K_{t-1}}}\right)}_{it}=\alpha & + {\beta }_1{\left({\displaystyle \frac{I}{K_{t-1}}}\right)}_{it-1}+{\beta }_2{\left({\displaystyle \frac{S}{K_{t-1}}}\right)}_{it}+{\beta }_3{Q}_{it}+{\beta }_4{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}+{\beta }_5{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {CAGE}_{it}\\ & + {\beta }_6{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {TENU}_{it}+{\beta }_7{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {FE}_{it}+{\beta }_8{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {CE}_{it}+{\beta }_9{LEV}_{it}\\ & + {\beta }_{10}{SZ}_{it}+{\beta }_{11}{AGE}_{it}+{\theta }_i+{\gamma }_t+{\mu }_{it}\end{array}$$

(1)

The variables used in Equation (1) are defined in Table 2. ${\theta }_i$ is the firm-specific effect, ${\gamma }_t$ is the time-specific effect, and ${\mu }_{it}$ is an idiosyncratic error term. The subscripts $i$ and $t$ represent the firm and time, respectively.

The interaction term in Equation (1) examines the effect of the CEO’s characteristics on the role of cash flow for investment decisions. Further, this study modifies Equation (1) by removing the control variable of firm size from the model while examining the moderating role of firm size on the relationship between CEO characteristics and ICFS. The model is specified as follows:

$$\begin{array}{ll}{\left({\displaystyle \frac{I}{K_{t-1}}}\right)}_{it}=\alpha & + {\beta }_1{\left({\displaystyle \frac{I}{K_{t-1}}}\right)}_{it-1}+{\beta }_2{\left({\displaystyle \frac{S}{K_{t-1}}}\right)}_{it}+{\beta }_3{Q}_{it}+{\beta }_4{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}+{\beta }_5{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {CAGE}_{it}\\ & + {\beta }_6{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {TENU}_{it}+{\beta }_7{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {FE}_{it}+{\beta }_8{\left({\displaystyle \frac{CF}{K_{t-1}}}\right)}_{it}\times {CE}_{it}+{\beta }_9{LEV}_{it}\\ & + {\beta }_{10}{AGE}_{it}+{\theta }_i+{\gamma }_t+{\mu }_{it}\end{array}$$

(2)

4. Empirical Results

4.1. CEO Characteristics and ICFS

This section discusses the estimation results of Equation (1) in

Table 4. CEO characteristics and ICFS.

Variables	All Firms
	Equation (1)
	(1)
${\left({\displaystyle \raisebox{1ex}{$I$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it-1}$	0.1221 ** (2.49)
$Q_{it}$	0.0908 ** (2.14)
${\left({\displaystyle \raisebox{1ex}{$S$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.1113 *** (2.91)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.1905 *** (3.47)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CAGE\right)}_{it}$	−0.0711 ** (−2.14)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(TENU\right)}_{it}$	0.0034 (1.37)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(FE\right)}_{it}$	−0.0711 *** (−2.86)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CE\right)}_{it}$	−0.0529 ** (−2.24)
${LEV}_{it}$	−0.0312 ** (−2.35)
${SZ}_{it}$	0.1213 *** (3.75)
${AGE}_{it}$	−0.0178 *** (−2.13)
Constant	0.0911 * (1.74)
Industry and time effect	Yes
AR(1) [p-value]	−7.21 [0.00]
AR(2) [p-value]	1.15 [0.26]
Hansen Test [p-value]	62.37 [0.44]
Number of observations	6921

Notes: (i) Table 2 shows the definition and measurement of variables used in this table. (ii) i = number of firms represented as 1, 2 … n, and t = time period. (iii) z-statistics are given in parentheses, and p-values are given in square brackets. (vi) *** 1% level of significance. ** 5% level of significance. * 10% level of significance.

. From the estimation results, it was found that firm-level variables play a significant role in the determination of corporate investment. A positive and significant cash flow coefficient reveals that a firm’s investment is highly associated with the availability of cash flow, and this highly sensitivity to cash flow confirms that ICFS persists in the Indian manufacturing sector. Furthermore, Table 4 presents the estimation results for the interaction between CEO characteristics and cash flow. Based on these results, several key inferences can be drawn. First, the positive and significant relationship between investment and internal funds suggests that internal financing is a crucial driver of corporate investment. Additionally, the study finds a negative and significant association between CEO age and ICFS, indicating that as the CEO’s age increases, the influence of cash flow on corporate investment decreases.

The interaction between CEO financial education and cash flow indicates that financial education helps reduce ICFS. Similarly, the negative and significant coefficient for the interaction between CEO career experience and cash flow suggests that experienced CEOs are effective in lowering ICFS. These findings can be attributed to the fact that CEO age, financial education, and career experience enhance a CEO’s external networks, decision-making capabilities, and ability to identify promising investment opportunities, thereby facilitating more efficient access to external financing and relying less on internal cash flow. In contrast, the coefficients for the interaction between CEO tenure and cash flow remain positive and unchanged, suggesting that CEO tenure does not have a moderating effect on ICFS.

Overall, these results are consistent with the theoretical predictions in the literature (Malmendier & Tate, 2005a; Ben Mohamed et al., 2014; Hu & Liu, 2015). Further, these results confirm that CEO characteristics influence managerial decision making and risk preferences. These traits also shape how investment decisions are made under financial constraints and reduce the role of cash flow in investment decisions of firms by easy access to external finance, ultimately reducing ICFS and supporting Hypothesis 1.

4.2. CEO Characteristics and ICFS (Moderating Role of Group and Independent Firms)

This section investigates the moderating role of group firms and independent firms on the association between CEO characteristics and ICFS. Columns (1) and (2) of

Table 5. CEO characteristics, group firms, independent firms, and ICFS.

Variables	Group Firms	Independent Firms
	Equation (1)	Equation (1)
	(1)	(2)
${\left({\displaystyle \raisebox{1ex}{$I$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it-1}$	0.0788 ** (3.17)	0.1211 ** (2.44)
$Q_{it}$	0.0528 ** (2.35)	0.0781 *** (3.47)
${\left({\displaystyle \raisebox{1ex}{$S$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.1115 *** (2.55)	0.1191 *** (3.82)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.0503 * (1.78)	0.1217 *** (5.21)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CAGE\right)}_{it}$	0.0368 (1.17)	−0.0517 ** (−2.16)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(TENU\right)}_{it}$	−0.0031 (−1.11)	−0.0305 * (−1.72)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(FE\right)}_{it}$	−0.0421 ** (−2.33)	−0.0841 *** (−3.19)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CE\right)}_{it}$	−0.0436 * (−1.87)	−0.0929 *** (−3.68)
${LEV}_{it}$	−0.0421 * (−1.79)	−0.0615 *** (−4.37)
${SZ}_{it}$	0.0711 ** (2.11)	0.0913 *** (3.89)
${AGE}_{it}$	−0.0021 * (−1.82)	−0.0217 ** (−2.19)
Constant	0.1233 ** (2.23)	0.1451 ** (2.15)
Industry and time effect	Yes	Yes
AR(1) [p-value]	−7.41 [0.00]	−8.58 [0.00]
AR(2) [p-value]	1.29 [0.23]	1.35 [0.22]
Hansen Test [p-value]	68.31 [0.42]	58.11 [0.49]
Number of observations	3744	3117

Notes: (i) Table 2 shows the definition and measurement of variables used in this table. (ii) i = number of firms represented as 1, 2 … n, and t = time period. (iii) z-statistics are given in parentheses, and p-values are given in square brackets. (vi) *** 1% level of significance. ** 5% level of significance. * 10% level of significance.

show the estimation results of Equation (1) for group and independent firms, respectively. The high coefficient value of firm-level variables for independent firms reveal that these factors are more significant for independent firms, as these firms do not experience the benefits of group firms (Gupta & Mahakud, 2018; Gupta, 2023; Kumar & Ranjani, 2018; Lensink et al., 2003).

The estimation results for both categories of firms show positive and significant cash flow coefficients, indicating that Indian manufacturing firms face financial constraints. The relatively higher coefficient for independent firms, compared to group firms, suggests that the investment decisions of independent firms are more heavily influenced by the availability of internal funds. In contrast, the lower ICFS for group firms implies that cash flow plays a less critical role in their investment behavior. This can be attributed to the presence of internal capital markets within business groups, which facilitate the allocation of resources across affiliated firms. Moreover, group firms typically have better market access and enjoy a stronger reputation, making it less costly for them to raise external capital (Gupta, 2023; Kumar & Ranjani, 2018; Lensink et al., 2003).

The columns (1 and 2) of Table 5 also show the estimation results of interactions between cash flow and CEO characteristics. The negative (positive) and significant (insignificant) coefficient of the CEO’s age with cash flow for independent (group) firms indicates that the CEO’s age reduces ICFS for independent firms. This could be because older CEOs are experienced, have knowledge of investment decisions, and have networks with lending agencies (Gupta, 2025; Gupta et al., 2018; Serfling, 2014. These CEOs can better analyze external market conditions compared to younger CEOs, which helps older CEOs raise external capital cost-effectively and finance the firm’s investment, even in the absence of internal funds (Gupta et al., 2018; Serfling, 2014). Similarly to the CEO’s age, it was also found that the CEO’s tenure reduces ICFS only for independent firms.

The estimation results also show a negative and significant coefficient for the interaction between cash flow and CEO financial education in both firm types, indicating that financial education helps reduce ICFS. Furthermore, the lower (higher) coefficient for group (independent) firms suggests that the impact of CEO financial education on reducing ICFS is more pronounced in independent firms than in group firms. This may be attributed to the enhanced capabilities of financially educated CEOs, including better financial knowledge, sharper decision-making skills, and a greater ability to identify profitable investment opportunities. These qualities enable them to secure external financing more efficiently, allowing them to invest even when internal funds are limited (Gupta et al., 2021; Malmendier & Tate, 2005a; Hu & Liu, 2015). Further, the interaction of cash flow with the CEO’s experience displays a negative and significant coefficient; meanwhile, the low (high) coefficient value reveals that the impact of the CEO’s experience in group (independent) firms is lower (higher) on ICFS. This could be because the experience of CEOs is more important for financing in independent firms, as such firms are more financially constrained; meanwhile, group firms do not face difficulties in terms of the unavailability of internal funds (Gupta & Mahakud, 2018; Gupta, 2023; Kumar & Ranjani, 2018; Lensink et al., 2003). In summary, group affiliation moderates the effectiveness of CEO characteristics in reducing ICFS. In addition to this, independent firms rely more heavily on the individual capabilities of CEOs to overcome financial constraints and mitigate ICFS, whereas group firms benefit from structural advantages that diminish the relative impact of CEO traits on ICFS.

Overall, these findings reveal that group firms share several benefits; on the other hand, independent firms, lacking such advantages, are more likely to face financial constraints and thus rely more heavily on internal cash flow to fund investments. Therefore, CEOs who are associated with capability, risk-taking approaches, experience, knowledge, and a strong network with leading agencies can help independent firms access external finance, to rely less on internal funds to execute investment decisions and mitigate ICFS. Consequently, these findings support hypothesis 2 and confirm that business group affiliation and non-business group affiliation moderate the relationship between CEO characteristics and ICFS.

4.3. CEO Characteristics and ICFS (Moderating Role of Firm Size Across Group and Independent Firms)

The results presented in column (1) of

Table 6. CEO characteristics, group firms, firm size, and ICFS.

Variables	Large-Size Firms	Small-Size Firms
	Equation (2)	Equation (2)
	(1)	(2)
${\left({\displaystyle \raisebox{1ex}{$I$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it-1}$	0.0728 ** (2.35)	0.0839 ** (2.25)
$Q_{it}$	0.0615 ** (2.23)	0.0729 ** (2.44)
${\left({\displaystyle \raisebox{1ex}{$S$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.0531 ** (2.47)	0.0631 ** (2.31)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.0641 ** (2.13)	0.0657 ** (2.48)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CAGE\right)}_{it}$	−0.0421 * (−1.89)	−0.0351 * (−1.74)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(TENU\right)}_{it}$	0.0032 (1.12)	0.0041 (1.31)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(FE\right)}_{it}$	−0.0427 * (−1.81)	−0.0611 * (−1.74)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CE\right)}_{it}$	−0.0328 * (−1.74)	−0.0317 ** (−2.35)
Constant	0.0911 ** (2.38)	0.1121 * (1.89)
Control Variables excluding firm size	Yes	Yes
Industry and time effect	Yes	Yes
AR(1) [p-value]	−8.19 [0.00]	−7.48 [0.00]
AR(2) [p-value]	1.47 [0.25]	1.41 [0.24]
Hansen Test [p-value]	57.26 [0.34]	58.41 [0.35]
Number of observations	1624	2135

Notes: (i) Table 2 shows the definition and measurement of variables used in this table. (ii) i = number of firms represented as 1, 2 … n, and t = time period. (iii) z-statistics are given in parentheses, and p-values are given in square brackets. (vi) ** 5% level of significance. * 10% level of significance.

and

Table 7. CEO characteristics, independent firms, firm size, and ICFS.

Variables	Large-Size Firms	Small-Size Firms
	Equation (2)	Equation (2)
	(1)	(2)
${\left({\displaystyle \raisebox{1ex}{$I$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it-1}$	0.0711 ** (2.41)	0.0932 ** (2.24)
$Q_{it}$	0.0724 ** (2.37)	0.0717 ** (2.29)
${\left({\displaystyle \raisebox{1ex}{$S$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.0718 * (2.44)	0.1183 *** (3.47)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}$	0.0721 ** (2.17)	0.1211 *** (4.34)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CAGE\right)}_{it}$	−0.0621 * (−1.84)	−0.0911 ** (−2.17)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(TENU\right)}_{it}$	0.0021 (1.13)	−0.0327 * (−1.71)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(FE\right)}_{it}$	−0.0678 ** (−2.45)	−0.0921 *** (−5.21)
${\left({\displaystyle \raisebox{1ex}{$CF$}\!\left/ \!\raisebox{-1ex}{$K_{t-1}$}\right.}\right)}_{it}\times {\left(CE\right)}_{it}$	−0.0512 ** (−2.12)	−0.0912 *** (−3.32)
Constant	0.0827 ** (2.19)	0.0917 ** (2.47)
Control Variables excluding firm size	Yes	Yes
Industry and time effect	Yes	Yes
AR(1) [p-value]	−6.89 [0.00]	−7.21 [0.00]
AR(2) [p-value]	1.42 [0.34]	1.47 [0.31]
Hansen Test [p-value]	45.11 [0.21]	49.17 [0.17]
Number of observations	1092	1978

Notes: (i) Table 2 shows the definition and measurement of variables used in this table. (ii) i = number of firms represented as 1, 2 … n, and t = time period. (iii) z-statistics are given in parentheses, and p-values are given in square brackets. (vi) *** 1% level of significance. ** 5% level of significance. * 10% level of significance.

show the interaction between cash flow and CEO characteristics for the LBGA and large independent firms, respectively. On the other hand, column (2) of Table 6 and Table 7 shows the interaction between cash flow and CEO characteristics for the SBGA and small independent firms, respectively. Further, significant and positive values were found for cash flow for all sizes and both types of firms; meanwhile, the high (low) coefficient value of cash flow for small independent (large independent firms, SBGA, and LBGA) firms indicates that the investment decisions taken by small independent firms are strongly dependent on the firm’s internal funds.

A better explanation of these findings can be that firm size does not matter for group firms because any size of business group firm shares the benefits of business group membership, including the sharing of internal capital markets and easy access to external finances, making the investment less sensitive to cash flow (Gupta et al., 2021). In addition, size matters for independent firms because small independent firms face difficulties in accessing external financing due to a lesser-known reputation in the market and limited collateral assets. However, large independent firms can easily access the external market and have a good reputation in the market, with more collateral assets compared to small independent firms; therefore, the investment of small independent firms is highly affected by the internal cash flow.

The results (presented in Table 6) of the interaction between CEO characteristics and cash flow for SBGA and LBGA firms reveal that the CEO’s characteristics have a minimum impact on ICFS. This could be because group firms are reputed and large, which helps these firms borrow from the external capital market. In addition, these firms share internal capital markets, and therefore the investment of these firms is less dependent on cash flow. Taken together, there is limited need for CEO attributes to moderate the effect of cash flow on investment for group firms (Gupta & Mahakud, 2018; Gupta, 2023; Kumar & Ranjani, 2018; Lensink et al., 2003).

Further, estimation results (presented in Table 7) of the interaction between CEO characteristics and cash flow for small and large independent firms show that CEO characteristics significantly reduce the ICFS of small independent firms compared to large independent firms. This finding shows that small independent firms are trying to establish their position in the market and also face problems with external borrowing, as lending agencies do not trust small independent firms as compared to large independent firms. In this context, the CEO characteristics of small independent firms help in securing external financing and reducing ICFS, as the CEO’s characteristics comprise knowledge, experience, capabilities, social networks, and risk-taking skills (Gupta et al., 2018; Ben Mohamed et al., 2014).

In nutshell, these findings show that CEO characteristics are more (less) significant in reducing ICFS for small independent firms (large independent, SBGA and LBGA firms). Therefore, these finding support hypothesis 3, which states that firm size moderates the relationship between CEO characteristics and ICFS differently across independent and group firms.

5. Discussion and Conclusions

5.1. Discussion and Implications

This study examines the impact of the CEO’s characteristics on the ICFS of group and independent firms. This study finds that the investment of Indian firms is highly dependent on the availability of cash flow. Additionally, group firms are less financially constrained than independent firms, and the investment of group (independent) firms is less (more) dependent on cash flow. CEO characteristics influence managerial decision-making and risk preferences, and these traits may shape how investment decisions are made under financial constraints and may reduce ICFS through easy access to external finance. Therefore, we find that CEO characteristics such as CEO age, financial education (education in the financial stream), and career experience reduce ICFS. By using the segregated sample for group firms and independent firms, this study reveals that CEO experience and financial education reduce the ICFS of group firms. In addition, CEO age, tenure, financial education, and career experience significantly reduce the ICFS of independent firms. However, the effect of CEO career experience and financial education on ICFS is greater (less) for independent (group) firms. This finding reveals that group and independent firms moderate the role of CEO characteristics on ICFS. The better explanation of this finding can be that group firms share several benefits, and on the other side, independent firms lacking such advantages are more likely to face financial constraints and thus rely more heavily on internal cash flow to fund investments. Therefore, CEO characteristics like capability, risk-taking approaches, experience, knowledge, and a strong network with leading agencies can help an independent firm to access external finance in order to rely less on internal funds to execute investment decisions and mitigate ICFS. Further, this study finds that the impact of CEO characteristics significantly reduces the ICFS across firm sizes, and this effect is more pronounced for small-sized independent firms than large-sized independent firms. In addition, this study demonstrates that CEO age, financial education, and career experience have a very limited effect on the ICFS of group firms, and this effect is similar for both small-sized and large-sized group firms. This could be because small-size firms are considered as financially constrained firms where leadership capabilities can play a critical role in mitigating financial constraints. On the other hand, in larger firms or those affiliated with business groups, these traits may have a weaker influence due to better access to finance and centralized decision-making structures. Therefore, we argue that firm size may play a moderating role between CEO characteristics and ICFS across business group and independent firms; the findings support the argument and confirm that CEO characteristics are particularly important for small independent firms.

The findings of this study have substantial economic significance, particularly for understanding ICFS. The strong dependence of investment on cash flow highlights the limited access to external finance, especially for independent firms. Group firms share benefits such as internal capital markets, and this group support makes them less financially constrained, underscoring the economic role of organizational structure. Moreover, the study shows that CEO characteristics can reduce ICFS, particularly in small-sized and independent firms. This emphasizes the economic value of capable leadership in improving financial flexibility and driving efficient investment.

This study makes several important contributions to the literature on corporate finance. Theoretically, it extends UET by showing that the influence of CEO characteristics on firm investment behavior is contingent on organizational context, specifically, business group affiliation and firm size. By highlighting how the strategic discretion of CEOs through their traits varies across group firms and independent firms in India, the study adds a contextual layer to the understanding of executive influence. By focusing on the Indian manufacturing sector, the study adds to the theoretical understanding of how institutional context and leadership characteristics jointly impact strategic financial decisions.

This study also offers practical implications for firm stakeholders, financial institutions, and policymakers. Firms, especially small-sized and independent (non-group) firms, should recognize the strategic importance of CEO selection and development, prioritizing financial expertise and career experience to reduce ICFS. Lending agencies can enhance credit assessment models by incorporating CEO profiles and firm affiliations to better predict financial resilience. Investors should evaluate CEO characteristics and ownership structures when assessing firm stability and growth potential. Finally, policymakers might consider designing support mechanisms for independent firms that lack the financial cushioning typically available to group firms.

5.2. Conclusions, Limitations, and Future Scope

This study concludes that Indian firms face significant financial constraints, with investment closely tied to internal cash flows. However, group firms are relatively less constrained than independent firms. CEO characteristics play a crucial role in reducing ICFS, with their impact moderated by business group affiliation and firm size. The influence of these CEO attributes is more substantial in independent firms, especially smaller ones, while their effect is limited in group firms. These findings underscore the importance of leadership attributes in shaping firms’ financial flexibility, particularly for independent and small-sized firms. This study has certain limitations. It focuses solely on manufacturing firms, which limits the applicability of the findings to other sectors such as services or technology, which may have different financial and managerial dynamics. Additionally, the study does not consider other governance factors like board structure or ownership concentration, which could influence ICFS. These limitations suggest the need for future research to examine a broader range of industries and incorporate additional firm- and environment-level factors to enhance the generalizability and depth of the insights.