1 Introduction

A firm can become more socially accountable to the public, its stakeholders, by implementing a self-regulating business model known as corporate social responsibility [50]. Corporate Social Responsibility (CSR) is becoming important as businesses production, investment, and operational activities are hurting the natural and social environments. CSR has been supported by political and economic discussions, documented by empirical data, and promoted by literature [31, 65]. It has been altered to the degree that investment decisions are made, and some company strategy growth has been moved to a more environmentally friendly direction [25]. Customers of today seek out “green products,” or those that are not only made using green technologies but are also environmentally beneficial [27]. All sizes of businesses can embrace green innovations and technology, while larger businesses may find it simpler to adopt because they have access to resources that smaller businesses may not have [34, 63]. Green technologies are products and services that address issues with waste, noise, water, air, and soil quality [30]. Businesses that invest in green technologies run more sustainably without sacrificing profitability. Several scholars have examined “triple bottom line” [26, 66] to examine the influence of firm’s state equity on CSR initiatives [44].

Study have suggested state equity often prioritize social and environmental concern as they are influenced by government policies and regulations [44]. The study affirm that businesses serve society and the significance of achieving success. Similarly, extant studies have increasingly focused on understanding the impact of high-tech performance on innovation. For example, study of [38] uses Resource Based Theory (RBV) to assess Chinese high-tech industries and finds innovation performance significantly influence high-tech firms.

In the same vein, [87] affirm Chinese firms high-tech contribute to sustainable technologies thereby fostering social development. In addition, as innovation is driving the development of sustainable products and services that align with CSR goals. Companies are investing in research and development to create eco-friendly alternatives, reduce resource consumption, and thereby minimize environmental footprints [1, 71, 73]. Therefore, the intricate relationship between green innovations and CSR performance of China high-tech firms motivates this study to investigate the nexus between these innovations and CSR performance in African countries (Angola, DRC Congo, South Africa, Ethiopia Kenya, Guinea, Algeria and Nigeria), where the intersection of innovation and CSR presents both opportunities and challenges for businesses operating within dynamic socio-economic landscapes. In addition, as many of these countries face many deficits such as infrastructural deficits, energy security, waste management (i.e. solid waste, E-waste, food waste, Agri-waste) which are considered as socio-economic and environmental issues that directly affect and hinder economic growth and development of the region under study. By leveraging Chinese high-technology and green innovation practices, this may address these challenges more effectively towards sustainable socio-economic development and environmental conservation.

Thus, amidst the rapid pace of technological advancements and shifting societal expectations, aligning innovation strategies with CSR principles becomes imperative for businesses seeking to foster sustainable development in the region [27]. Furthermore, we cannot ignore the role of firm’s market value in promoting CSR. Study has shown that firm’s commitment to CSR can impact market value through reputation, brand royalty and stake holder trust [78]. Nevertheless, while these studies have focused on the concept of CSR, little is known about whether green innovations can influence CSR performance through high-tech performance in the African nation. According to [11, 75] define green innovations as a process that contributes to the creation of new production and technologies with the aim of reducing environmental risks, pollution and negative consequences of resource exploitation (e.g. energy).

While green innovation has been highlighted by recent studies [75, 80] green entrepreneurship innovation [49] green absorptive capacity on corporate environmental performance [46], green innovation and organizational performance [53], knowledge sharing and firms green innovation performance [50,51,52] all suggested to enhance green innovation practices. Furthermore, other recent study [47] have also assess green entrepreneurship orientation on environmental performance and finds that green entrepreneurship enhances green practices performance.

Against this consideration, our study draws upon Corporate Social Performance (CSP) and Innovation Diffusion theory (IDT) to explore the complex relationship between green innovations, CSR performance and China high-tech, with the inclusion of key control variables (state equity, innovation level, marketing value) in the context of African nation. Further we assess how China’s high-tech innovation affect CSR outcomes and what impact does green innovation have between China’s high-tech innovation and CSR. This research gap is important because the exploration of how different innovation approaches correlate with CSR performance metrics is crucial for businesses navigating the African business landscape. Specifically, understanding the interplay among green innovation [75, 80] CSR performance [48, 55, 59] and Chinese high-tech [38] is crucial in the country under study due to the issues on socio-economic and environmental challenges. We aim to fill this gap by consider some important factors such as state equity, innovation level, and marketing value. We intend to identify how these variables can manifest in driving green innovations practices and CSR performance, especially for businesses and policymakers tailor their strategies, encourage green innovation and enhance CSR practices for sustainable development in African countries. Given the lack of clarity surrounding the relationship between green innovations, CSR performance, and high-tech firms, especially in the African context, it is essential to delve into the contributions of Chinese high-tech companies in African nations. The specific impact of Chinese high-tech innovations on CSR outcomes and the interplay between green innovation and China's high-tech advancements pose important questions regarding the influence of green innovation in this setting. As we address this gap, we hope businesses, policy makers and stakeholder, (investors, NGOs, local communities) can benefit from the implications of this study to promoting sustainable practices, fostering corporate social responsibility, and leveraging technological advancements for positive social and environmental impacts. From empirical point of view, we aim to uncover empirical insights that can inform strategic decision-making and policy formulation, providing businesses with actionable insights to enhance their social and environmental impact [72, 74]. Building on CSP and IDT theory, we examine the nexus between high-tech, green innovation and CSR performance in African countries. With the purpose of strengthening the broader discourse on sustainable development, aiming to empower businesses, policymakers, and stakeholders to collaboratively chart a path towards sustainable prosperity [27]. First, we propose that these contingencies may be particularly important in explaining how China high-tech firms may benefit from CSR practices through green technology innovation. Our study, therefore, contribute to theories in following ways.

First, previous research suggests that high -tech firms are liable to engage in CSR practices, such that engaging in CSR activities can showcase their commitment to ethical practices [23, 27]. We therefore argue that not all high-tech firms may engage or show their commitment to CSR practices, but instead, this depends on leadership values and corporate strategy. Second previous show that green technology innovations and green product may improve firms’ high-tech performance [19, 30, 36, 37] enabling firms to reduce their environmental footprint, and meet consumer demand for sustainable products. However, we argue that besides consideration of green technology can also enhance firm competitiveness, differentiate themselves in the market. Thus, our study is different from the past literatures as we established concepts, including Innovation Diffusion Theory (IDT) and Corporate Social Performance Theory (CSP), to provide a comprehensive understanding of the intricate dynamics that govern the relationship between innovation and CSR in African nation [57]. Third, our study further provides a comprehensive understanding of the mechanisms driving CSR outcomes in African countries such as Angola, DRC Congo, South Africa, Ethiopia Kenya, Guinea, Algeria and Nigeria going beyond standard theories that clarifies how green innovation influences the relationship between innovation strategies and CSR performance [68] in the region under study.

China is particularly a suitable setting for this research not only their technology partnership and best trade partner with Africa. But because, Chinese companies operating in Africa often cite various motivations for engaging in CSR initiatives. Beyond profit-driven objectives, factors such as building a positive corporate image, gaining social license to operate, and aligning with host countries’ development goals play crucial roles [43, 61]. The Belt and Road Initiative (BRI), a significant Chinese development strategy, has prompted increased CSR activities as Chinese companies aim to integrate their operations with local communities and contribute to the economic and social development of African nations [81, 84]. Despite their endeavours, Chinese companies encounter challenges when implementing CSR initiatives in Africa. As Chinese firms spearhead initiatives ranging from artificial intelligence applications to renewable energy solutions across the African continent, it becomes imperative to assess how these innovations align with or influence CSR practices [6] in Africa, a continent pulsating with opportunity, stands poised for transformative advancement. China’s high-tech innovation, particularly spearheaded by Chinese firms, acts as a catalyst for this profound shift [2, 12, 21, 60, 78]. However, amidst the undeniable economic impetus these advancements bring, concerns regarding their impact on corporate social responsibility by Chinese firms in Africa's burgeoning markets emerge. Chinese firms are at the vanguard of introducing cutting-edge technologies like mobile telecommunications, renewable energy solutions, and fintech across Africa [7, 8, 18, 35, 76]. These advancements facilitate infrastructural development and economic growth [4, 72].

1.1 Empirical literature review

Study of [37] examined regional differences influencing the effectiveness of green technology innovation in China’s high-tech industry. The study developed SBM-DEA model that considers innovation and environmental challenges and finds that various quantiles and clusters had distinct influential characteristics, which guided the development of specific policy proposals to improve the efficiency of green innovation in China’s high-tech sector. Furthermore, [15, 16, 36] examined technical innovation efficiency (TIE) and green growth in China’s high-tech industry (HTI) in relation to the Belt and Road with an emphasis on resource coordination, environmental preservation, and economic performance. The study employed global Malmquist–Luenberger (GML) index models and the directional distance function (DDF) to examine TIE while accounting for environmental contamination. Technical innovation efficiency (TIE) variations were revealed using ArcGIS for geographic analysis. Other study such as [39] explored corporate social responsibility (CSR) and environmental sustainability in EU companies. The study emphasized the shift towards eco-innovations and the production of green products and revealed a strong link between innovation and environmental consciousness.

Scholarship studies [23, 28, 33] further examine how innovation affects the adoption of corporate social responsibility (CSR) in national business systems by examining the relationship between CSR and innovation at a macro level. Furthermore, past studies have also emphasized on the extant theories concerning the performance of corporate social responsibility and innovation methods [57]. The study synthesizes established concepts, including Innovation Diffusion Theory (IDT) and Corporate Social Performance Theory (CSP), to provide a comprehensive understanding of the intricate dynamics that govern the relationship between innovation and CSR in African nations [1]. Other recent study highlights a thorough theoretical framework that clarifies how green innovation influences the relationship between innovation strategies and CSR performance [68]. The researchers approach provides a comprehensive understanding of the mechanisms driving corporate social responsibility (CSR) outcomes going beyond standard theories by including Environmental, Social, and Governance (ESG) aspects together with changes in industrial structure. The study provides a strong theoretical framework for empirical research and strategic decision-making by understanding the relationship between innovation, sustainability, and business behaviour [19].

Study of [14] emphasize the complexity of this relationship and the significance of taking contextual variances into account in strategic decision-making by considering contextual elements of digitization and environmental control. In addition, [48] also advance our understanding of innovation tactics and corporate social responsibility (CSR) performance. Furthermore, other recent studies have empirically emphasized the importance of green innovation on environmentally friendly product [46, 80]. For example, the researchers affirm that investing in green innovation can positively influence environmental sustainability thereby improving firms’ green innovation performance [47, 75]. Furthermore, previous studies, highlight the relationship between state equity and market value [44, 82]. For instance [56] from government interference point of view argue that higher state equity can affect market value due to government interference. Conversely, state equity can also positively impact firms market value. For instance, our focus is how can China high-tech and CSR engagement benefit green innovation, we posit that China high-tech firms may contribute to market value if they invest in technology and innovation. However, we found no conclusive evidence about the relationship between green innovation, market value on corporate social responsibility. Although some studies [45, 46, 75, 79] have emphasized on the effect of green innovation on economic development and corporate performance, but none of this study has investigated relationship between innovation strategies and Corporate Social Responsibility (CSR) performance, with a special emphasis on the moderating effect of Green Innovation (GI).

Notably, other study in this context emphasizes the positive effect that green technology innovation on China's high-tech industry [30]. Similarly, previous study also concentrates on CSR performance in other regions like China and European Union. But a noticeable attention on African nations focusing on green innovation, high-tech and CSR remain inadequately explore [70]. Although, recent studies [50,51,52,53] have further made substantial contribution to the influence of green innovation on green knowledge and dynamic capacities. Particularly, how knowledge sharing can enhance firms to develop green innovation. The scholarship study further emphasized how green insights and green strategies play a crucial role to reduce environmental impacts and enhance firms’ productivity. Other study [50] opined that green knowledge sharing boosts dynamic capabilities, fosters green innovation, and leads to green competitive advantages. Additionally, the researchers further argued that green knowledge sharing plays a moderating role in the connection between green entrepreneurship and environmental sustainability. We cannot but refer to the importance of green innovation practices on firm performance. For instance, study of [53] affirm how government support, play a crucial factor in green innovation performance, suggesting that green innovation practice has a positive influence on firm performance. Drawing upon these studies, examining the green innovations, CSR performance in the context of high-tech firms still ambiguous, particularly in the Africa context. In addition, understanding the significance contribution of Chinese firms high-tech in the African states is crucial. It remains unclear how Chinese high-tech innovation affect CSR outcomes and what impact does green innovation have between China’s high-tech innovation and CSR raises a critical question of the influence green innovation in these settings. Thus, our study aims to close this gap and advances our understanding of these variables impacting CSR outcomes in Africa markets by placing current theories within the distinct socioeconomic context.

1.2 Moderating effect of green innovation

Green innovation has been emphasised by recent studies [50,51,52,53]. Green innovation as defined by [49] refer to the firm’s ability to spread eco-practices and eco-products and eco-process. For example, [10] argue that firms green strategy relies on eco-eco innovation with aim to minimize eco-system degradation and achieve green value-added. Notably, study by [80] expressed green innovation from the perspective of green process and product innovation, their study affirm that green innovation can reduce negative impact on product life cycle by integrating greenness, while green process innovation promotes the designs and promote of green products. Similarly, [46, 47, 49] draw on natural resource-based view support the argument that green business practices enhance firms to deal with environmental issues. The study further demonstrate that green organizations ambidexterity plays a moderating role in the relationship between green entrepreneurship orientation and eco-innovation. In addition, green innovation performance and green entrepreneurship was found to have a relationship with corporate environmental performance. Against this backdrop, scholarship study affirms that green process innovation play an important role in producing green products [29]. Green innovation enables firms to address societal, government pressure and customer adaptability [79]. Furthermore, researcher suggest that enterprises green process innovation has a positive correlation with its product innovation [80]. This is the case for African nation where innovation strategies and Corporate Social Responsibility performance is significantly shaped by green innovation [30]. Creating and implementing environmentally friendly technology, procedures, and practices inside businesses is known as “green innovation”. Within the framework of this research, green innovation serves as a moderator, affecting the perception and realisation of the influence of innovation strategies on corporate social responsibility performance. Green innovation works to ramp up the benefits that innovative techniques have for CSR performance. Companies that place a high priority on green innovation show that they are committed to environmental sustainability, which is in line with stakeholder expectations and broader societal trends towards eco-friendly behaviours [30].

Through the incorporation of green innovation into their tactics, entities can alleviate their ecological footprint, curtail their resource usage, and foster sustainable growth. By fostering goodwill among stakeholders and improving CSR performance, this proactive strategy boosts the competitiveness and reputation of the organization. Furthermore, Green Innovation serves as a safeguard against any unfavourable effects that innovation methods may have on CSR performance [85]. Innovation initiatives, including process or technology advances, can boost productivity and revenue, but they can also damage the environment or disregard social obligations. Organisations may lessen these negative effects by implementing green innovation. To lessen the environmental impact of their innovative endeavours, companies can, for instance, invest in waste reduction programmes, sustainable supply chain procedures, or renewable energy solutions. By doing this, they can pursue innovation-driven growth and maintain adherence to CSR ideals.

In addition, by encouraging sustainability-driven innovation, green innovation promotes synergies between innovation strategies and CSR performance. Companies that adopt green innovation are more likely to incorporate social and environmental factors right from the start of their innovation processes [14]. This all-encompassing strategy guarantees that innovation endeavours have favourable social and environmental consequences in addition to economic benefit. For example, businesses might create goods or services to tackle social or environmental issues, benefiting society as well as business. Through the integration of Green Innovation with traditional innovation methodologies, entities can establish enduring innovation ecosystems that promote enduring value generation and social influence [14]. Moreover, the moderating influence of green innovation depends on several variables, notwithstanding its potential advantages. First, efforts promoting green innovation must have the backing of the leadership and the organisation. Green innovation initiatives may lack focus and momentum in the absence of high-level support and funding, which would restrict their ability to moderate the link between innovation strategies and CSR performance [14]. Second, the market dynamics and regulatory framework also have an impact on the incentives and limitations that businesses encounter while implementing green innovation. While loose rules or little customer knowledge may impede progress in this sector, strong environmental legislation and consumer demand for sustainable products/services can encourage organisations to prioritise green innovation [81].

1.3 Hypothesis development

Based on the extant studies, we argue that technological and process innovations, or “high-tech innovation,” have the power to transform entire industries and spur economic expansion. Recent study [53] opined that African nations frequently lack access to cutting-edge technology; therefore, the entry of Chinese high-tech innovation may have a significant impact on CSR performance. Implementing Chinese high-tech innovation may help African companies explore new markets, increase operational effectiveness, and improve product quality—all of which can help them in corporate social responsibility goals. Furthermore, Chinese businesses that invest in high-tech innovation in African nations may also provide resources, best practices, and improving CSR performance [56, 67]. In the same vein, recent study on green innovation, which is defined by ecologically friendly methods and tools, is becoming a major force behind CSR campaigns all over the world. Researchers [19, 20, 24, 45] have analysed green innovation from different perspective, including green products, processes, and managerial frameworks. Green products and processes signify firm that use environmentally friendly technologies to improve production systems and operations, resulting in decreased resource consumption, sustainable work environment, improved product features, and adherence to environmental regulations. Green innovation offers firms the opportunity to attract customers and improve its competitive advantage. Green innovation increases customer loyalty and firms’ financial performance resulting in promoting firms’ green image [54]. Scholarship study have also shown that green innovation (green process, product and management) plays a crucial role in promoting economic, environmental and social performance [68, 69, 75]. Green innovation is especially important for CSR success in African countries, where environmental issues are common and social expectations for sustainable development are rising [1]. Businesses in African nations can lessen their carbon footprint, minimise environmental risks, and improve community well-being by incorporating green innovation into their operations [3]. Furthermore, green innovation can build stakeholder trust, draw in eco-aware customers, and improve an organization's reputation—all critical elements of CSR performance. Based on the above consideration, we posit the following hypotheses:

HI: Green innovation moderates the association between China’s high-tech innovation and Corporate social responsibility (CSR) performance in African countries.

Furthermore, study have opined that green innovation and high-tech innovation each have advantages in promoting CSR performance [69]. Our following proposes hypotheses contends that their combined influence might be more than the sum of their separate effects. Businesses in African nations can forge synergies that improve CSR results by utilising both green and high-tech innovation. For example, incorporating ecologically friendly procedures into advanced manufacturing processes can minimise negative effects on the environment while simultaneously maximising resource efficiency and advancing societal welfare [32]. Similarly, maximising the positive contributions to CSR performance can be achieved by integrating high-tech solutions into green innovation efforts to improve efficiency, scalability, and effectiveness [55]. Against this development, we put forth that CSR performance also has a significant effect on innovation level, which is a measure of total innovation across industries [77]. We posit that a correlation between increased levels of innovation and enhanced corporate social responsibility (CSR) performance in African nations, where innovation is commonly perceived as a driving force behind economic growth and social advancement [3]. Innovative organisations are more likely to invest in community development projects, embrace progressive CSR techniques, and uphold moral principles, all of which improve their overall CSR performance [59]. Following the above consideration, we thus posit that:

H2: There is an association between green innovation and corporate social responsibility (CSR) performance in African countries.

H3: There is a significant interaction effect between high-tech innovation and green innovation on corporate social responsibility performance in African countries.

Furthermore, we argue businesses that prioritise innovation can tackle environmental and social issues, benefiting stakeholders and society. Furthermore, previous research has emphasized the impact of state equity or state ownership on CSR performance [59]. This study posits that in African nations where state-owned firms are common, the degree of governmental equity will influence corporate social responsibility practices. Increased accountability, openness, and compliance with laws are all benefits of government involvement in corporate operations and are essential elements of corporate social responsibility (CSR) performance [87]. Furthermore, in keeping with larger governmental goals and public expectations, state-owned businesses might be more likely to give social welfare, community development, and environmental sustainability a top priority [13]. In addition to this development, we suggest stakeholder expectations and competitive dynamics, market share—a measure of a company’s market position to its peers can affect CSR activities [27]. We propose that in African nations where market rivalry is increasing, firms possessing greater market shares will exhibit superior CSR performance. Businesses with a large market share are subject to increased scrutiny from investors, customers, and government agencies; as a result, they must abide ethical business practices to preserve their position as industry leaders and goodwill. Furthermore, businesses with bigger market shares could have more power and resources to carry out CSR programmes, interact with local communities, and successfully handle social and environmental issues [55]. Based on the above consideration, we posit the following hypotheses (Fig. 1).

Fig. 1
figure 1

Source: Author’s work

Conceptual framework.

Full size image

H4: There is a significant connection between innovation level and corporate social responsibility performance in African countries.

H5: There is a significant relationship between state equity and corporate social responsibility performance in African countries.

H6: There is a positive influence between market share and corporate social responsibility performance in African countries.

As depicted in Fig.1, the research model of this study is created based on the literature review and the ensuing creation of the hypotheses. This study incorporates CSR as independent variable, while high-tech innovation as dependent variable. Green innovation represents the study moderating variable. The study controls variable includes (innovation level, state equity and market value).

1.4 Theoretical assumption

1.4.1 Corporate social performance and innovation diffusion theory

According to scholars of corporate social performance (CSP) and innovation diffusion theory (IDT) [9, 59] posits that the adoption of innovations follows a predictable pattern characterized by five stages: knowledge, persuasion, decision, implementation, and confirmation. The theory also introduces the concept of adopter categories, classifying individuals based on their willingness to embrace innovations. These categories include innovators, early adopters, early majority, late majority, and laggards. The theory's adaptability allows scholars to apply its principles to diverse fields, including healthcare, education, information technology, and sustainability. High-tech sectors acknowledge innovation play a crucial role in firms’ sustainability [5]. In the process of improving green practices, green innovation refer to the development and implementation of new products, processes, and technologies that are aimed at reducing environmental impact and promoting sustainability [46, 75]. Furthermore, in the context of high-tech sectors, green innovation plays a crucial role in helping firms improve their environmental performance and contribute to a more sustainable future [80].

While high-tech firms aim to boost green innovation, by engaging corporate social responsibility with the aim to enhance sustainability performance by incorporating environmental and social considerations into business practices [31]. Engaging in CSR initiatives related to green innovation, high-tech companies may enhance their environmental stewardship, minimize their carbon footprint, and contribute positively to society and the environment [35]. In addition, we cannot but mention the influence of corporate social responsibility on economic, legal, ethical, and philanthropic dimensions [42]. In the contemporary business landscape. The relevance of CSP has heightened with increased on corporate behaviour including stakeholders, consumers, investors, and employees, demand transparency and ethical conduct.

For instance, as employee well-being gains prominence in corporate agendas, a study by [55] emphasize the importance of human-centric approaches within the CSP framework [44]. Investigates how ethical leadership practices influence the integration of CSR initiatives within corporate strategies. The study emphasizes the importance of leaders who prioritize ethical decision-making, fostering a corporate culture where social responsibility becomes intrinsic to organizational identity. Therefore, drawing upon IDT and CSP to explain the relationship between high-tech innovation, CSR and green innovation is crucial. In addition, bridging this gap and extend on this theory can provide further provide high-tech firms impacts to green behaviour, CSR practices and sustainability performance. In addition, the choice of exploring IDT and CSP theory to the research of this context can enhance companies to implement socially responsible practices, particularly in understanding how CSR and innovations strategies [5] across industries enhance firms sustainability performance through green innovation practices [80]. Furthermore, integrating CSP and IDT theory, can promote firms strategic alignment with stakeholders engagement which in turn can enhance firm overall corporate social performance and innovation outcomes in the African context. Further, the application of IDT and CSP in understanding China’s high-tech firms, state equity [87], innovation level and market value on CSR outcomes, we tend to provide new insights on how CSR initiatives can help policymakers, investors, and managers make informed decisions about promoting sustainable practices through green innovation in the region under study. Thus, as we extend on this theory (IDT and CSP) in understanding the connection between state equity, innovation level, market value, and CSR outcomes in China's high-tech firms, our study further introduce a new insight to understanding how these factors influence CSR practices and Innovation strategies within the context of African states [1, 44].

2 Methodology

2.1 Sample and data collection

In this study, we adopt an empirical approach to examine how China’s high-tech firms, green Innovation, State Equity (SE), Innovation Level (IL), and Market Value (MV) influences CSR outcomes. We tested our hypotheses using a panel data of Chinese firms operating in the region under study spanning from 2014 to 2023. The dataset encompasses annual observations sourced from the World Bank indicators, specifically targeting variables such as high-tech innovation, innovation level, state equity, green innovation, and market value.

2.2 Variable measures

2.2.1 Independent variable

We measure the independent variable (Corporate social responsibility) by the extent to which companies engage in socially responsible practices. We target a range of activities and initiatives aimed at firms that contribute to society and the environment. Social expenditure and number of CSR projects undertaken by each firm.

2.2.2 Dependent variable

We measure the dependent variable (High-tech innovation performance) using the number of patents granted to the high-tech firm yearly. This innovation performance occurs within Africa in the region where the firms operate, and the in dependent variable denotes Chinese firms’ CSR practices in Africa and capturing the degree to which these industries contribute to technological advancements.

2.2.3 Moderating variable

Because green innovation is all about improving products or process in terms of pollution-prevention in the field of environmental management [69], thus, we measure green innovation by focusing on the firm’s product that produce each year. Particularly on the materials product development or design or the extent to which environmentally friendly innovation influences green practices such as green product labels, recycling waste products [80].

2.2.4 Interaction

China’s high-tech and Green Innovation: We examine the interaction on how the combined effects of high-tech and green innovation impact CSR.

2.2.5 Control variables

Innovation level: This variable controls for the overall level of innovation across industries, ensuring that the effects of China’s high-tech innovation on CSR are not confounded by general innovation trends.

State equity: To operationalize the state equity variables, we measured the shared of state owned paid in capital over the total paid-in capital of the firms [77]. This variable represents the ownership stake of the government or state in companies, controlling for the influence of state ownership on CSR engagement.

Market value: This variable controls for market competitiveness, considering the market position of companies relative to their peers and its potential influence on CSR engagement.

2.2.6 Panel least square

The association between CSR, China’s high-tech innovation, green innovation, their interaction, and control factors is examined using Panel Least Square (PLS) regression analysis. PLS takes into consideration both cross-sectional and time series fluctuations in the data, making it appropriate for panel data analysis. By adjusting for other pertinent variables like innovation level, and market value, we use PLS to evaluate the influence of both China’s high-tech and green innovation on CSR as well as the moderating effect of green innovation on the relationship between China’s high-tech innovation and CSR. Consequently, the empirical equation is formulated as:

$$ Corporate \,Social\, Responsibility = \alpha + \beta_{1} \left( {High\, Tech\, Innovation} \right) + \beta_{2} \left( {Green\, Innovation} \right)_{t} + \beta_{3} \left( {Interaction\, effect} \right)_{t} + \beta_{4} \left( {State\, Equity} \right)_{t} + \beta_{5} \left( {Innovation\, Level} \right)_{t} + \beta_{6} \left( {Market\, Share} \right)_{t} $$
(1)

where the \(interaction\, effect = High\, Tech Innovation*Green\, Innovation\).

2.2.7 Pesaran (2004) diagnostic test for panel cross-section dependence

It is well known that the Lagrange multiplier test statistic of Breusch Pagan for cross-sectional dependence does not have high power and is not appropriately centered for a fixed T. To overcome these limits, we proposed a modified Lagrange multiplier (CDLM) statistic test for cross-sectional dependence.

The CDLM statistic is specified as follows:

$$ CD_{LM} = \sqrt {\frac{1}{{N\left( {N - 1} \right)}}\sum\nolimits_{i = 1}^{N - 1} {\sum\nolimits_{j = i + 1}^{N} {\left( {T\hat{\rho }_{ij}^{2} - 1} \right)} } } $$
(2)

where \({\rho }_{ij}\) refers to the product-moment correlation coefficient of the disturbances11. Under the null assumption of absence of cross-sectional dependence with the first \(T\to \infty \) and then \(N\to \infty \) \(\left({H}_{0}:{\rho }_{ij}={\rho }_{ji}=0\text{ for i}\ne \text{j versus }{H}_{1}: {\rho }_{ij}={\rho }_{ji} for some i\ne j\right).\)

CDLM asymptotically follows a normal distribution. Nonetheless, this check is likely to show evidence of considerable and significant size distortions when N is large compared with T. To deal with this issue, Pesaran (2004) subsequently developed a new test for cross-sectional dependence (CD) that can be performed where N is large, and T is small. This test is based on the pairwise correlation coefficients of the OLS residuals obtained from standard augmented Dickey-Fuller (1979) specifications of each variable in the panel rather than their squares utilized in the LM test. The CD statistic is derived as follows:

$$ CD_{LM} = \sqrt {\frac{2T}{{N\left( {N - 1} \right)}}} \sum\nolimits_{i = 1}^{N - 1} {\sum\nolimits_{j = i + 1}^{N} {\hat{\rho }_{ij} } } $$
(3)

Under the null assumption of the absence of cross-sectional dependence (H0) with \(T\to \infty \) and then \(N\to \infty \) in any order, CD asymptotically follows a normal distribution.

2.2.8 PVAR specification

This analysis used the panel data vector autoregressive (PVAR) model developed by [41], this model allowed us to account for unobserved individual heterogeneity for the entire series via the introduction of fixed effects that improve the coherence and the consistency of the measurement. PVAR has obvious realistic value as a practical instrument for exploring the mutual impact of China’s high-tech technological innovation, innovation level, state equity, green innovation, and market value on corporate social responsibility (CSR) in African countries and for providing strategic advice. The proposed panel VAR model is given by:

$${Y}_{it}={\mu }_{i}+A\left(L\right){Y}_{it}+{\alpha }_{i}+{\delta }_{t}+{\varepsilon }_{it}$$
(4)

where \({Y}_{it}\) is a vector of the endogenous stationary series Corporate social responsibility (CSR), (China’s high-tech technology innovation (HTI), innovation level (IL), state equity (SE), green innovation (GI), market value (MV), and \({\mu }_{i}\) represents the matrix of country-specific fixed effects. The subscripts, which are defined as i and t refer to country and time, respectively. \(A\left(L\right)\) represents the matrix polynomial in the lag operator with \(A\left(L\right)={A}^{1}{L}_{1}+{A}^{2}{L}_{2}+\dots +{A}_{p}{L}^{p}\), \({\alpha }_{i}\) indicates the vector that determines the specific effects of the country found in this regression, \({\delta }_{t}\) represents the dummy variables for the country’s specific time and \({\varepsilon }_{it}\) denotes the residual vector of innovation level, product innovation, state equity, green innovation, market value, and financial performance.

The matrix form of the PVAR model reported in (4) can also be rewritten as follows:

$$ \Delta Ln\left( {CSR_{it} } \right) = \mu_{1i} + \sum\nolimits_{j = 1}^{p} {\alpha_{1j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{1j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{1j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{1j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{1j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{1j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{1j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{1i} + \delta_{1t} + \varepsilon_{1it} $$
(5)
$$ \Delta Ln\left( {GI_{it} } \right) = \mu_{2i} + \sum\nolimits_{j = 1}^{p} {\alpha_{2j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{2j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{2j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{2j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{2j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{2j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{2j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{2i} + \delta_{2t} + \varepsilon_{2it} $$
(6)
$$ \Delta Ln\left( {HTI_{it} } \right) = \mu_{3i} + \sum\nolimits_{j = 1}^{p} {\alpha_{3j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{3j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{3j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{3j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{3j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{3j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{3j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{3i} + \delta_{3t} + \varepsilon_{3it} $$
(7)
$$ \Delta Ln\left( {IL_{it} } \right) = \mu_{4i} + \sum\nolimits_{j = 1}^{p} {\alpha_{4j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{4j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{4j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{4j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{4j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{4j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{4j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{4i} + \delta_{4t} + \varepsilon_{4it} $$
(8)
$$ \Delta Ln\left( {INTERACTION_{it} } \right) = \mu_{5i} + \sum\nolimits_{j = 1}^{p} {\alpha_{5j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{5j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{5j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{5j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{5j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{5j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{5j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{5i} + \delta_{5t} + \varepsilon_{5it} $$
(9)
$$ \Delta Ln\left( {MV_{it} } \right) = \mu_{6i} + \sum\nolimits_{j = 1}^{p} {\alpha_{6j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{6j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{6j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{6j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{6j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{6j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{6j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{6i} + \delta_{6t} + \varepsilon_{6it} $$
(10)
$$ \Delta Ln\left( {SE_{it} } \right) = \mu_{7i} + \sum\nolimits_{j = 1}^{p} {\alpha_{7j} } \Delta Ln\left( {CSR_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {b_{7j} } \Delta Ln\left( {GI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {c_{7j} } \Delta Ln\left( {HTI_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {d_{7j} } \Delta Ln\left( {IL_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {e_{7j} } \Delta Ln\left( {INTERACTION_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {f_{7j} } \Delta Ln\left( {MV_{it - j} } \right) + \sum\nolimits_{j = 1}^{p} {g_{7j} } \Delta Ln\left( {SE_{it - j} } \right) + \alpha_{7i} + \delta_{7t} + \varepsilon_{7it} $$
(11)

3 Result

The results in Table 1 gives an overview of the distribution and features of the variables within the sample, and they are based on a dataset of 540 observations. Notably, the average ratings in Table 1 show that green innovation is valued at 5208.212, China’s high-tech innovation is valued at roughly 98.5 million, and CSR is rated at 2.417 on average. The average value of state equity is 0.707, indicating a high degree of state ownership. With mean values of 0.204 and 12.403, respectively, the innovation level and market value demonstrate a degree of innovation and a competitive market position. The range and standard deviation, however, show a significant amount of variability. This is especially true for the category of "China’s high-tech innovation," where the standard deviation is noticeably high at 358 million. Furthermore, the distributional properties of the variables are revealed by the skewness and kurtosis values, which point to departures from a normal distribution, especially in the China’s high-tech and green innovation sectors.

Table 1 Summary statistics
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Table 2 presents the correlation coefficient measures of the strength and direction of linear relationships between pairs of variables, ranging from − 1 to 1. A coefficient of 1 indicates a perfect positive correlation, − 1 indicates a perfect negative correlation, and 0 indicates no correlation. Notably, the correlation coefficients between CSR and the other variables range from − 0.374 to 0.106, suggesting weak to moderate relationships. China’s high-tech innovation exhibits a moderate and strong positive correlation with Green Innovation (0.667) and Market Value (0.843) respectively indicating that higher levels of China’s high-tech Innovation are associated with higher levels of green technology innovations and market value which follows the work of [37] which posit that the degree of regional China’s high-tech development is directly correlated with the green innovation efficiency level of the China’s high-tech industry.

Table 2 Correlation matrix
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Similarly, green innovation shows a moderate positive correlation with Market Value (0.6224746). State equity demonstrates weak negative correlations with other variables, while innovation level displays moderate positive correlations with China’s high-tech Innovation (0.465) and Green Innovation (0.471), suggesting that higher innovation levels are associated with increased levels of China’s high-tech and Green Innovation which align with the work of [36] which suggest that the higher the innovation level contribute to firm high-tech and green practices.

The Cross Dependence Test presented in Table 3 examines the potential cross-sectional dependence among observations in the regression model. The associated p-value, 0.1308, suggests that there is insufficient evidence to reject the null hypothesis of no cross-sectional dependence at conventional significance levels. This indicates that the observations in the regression model are not significantly dependent on each other across different cross-sections. Consequently, the results suggest that the model's assumptions regarding cross-sectional independence are valid, enhancing the reliability of the regression analysis and the interpretation of the relationships between CSR, China’s high-tech Innovation, green innovation, and the control variables [39].

Table 3 Cross Dependence Test
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Table 4 presents the results of a Panel Least Squares (PLS) regression analysis, aiming to understand the relationship between Corporate Social Responsibility (CSR) and several key variables: China’s high-tech Innovation, green technology innovations, state equity, innovation level, and market value, along with the interaction between the main independent variable (China’s high-tech innovation) and the moderating variable (Green Innovation). The intercept term indicates that, when all other variables are held constant, the expected value of CSR is approximately 2.956. Notably, both China’s high-tech and green technology innovations exhibit negative coefficients, indicating that higher levels of these innovations are associated with lower CSR scores. These findings suggest that while innovation may drive corporate performance in certain aspects, it might not necessarily translate into enhanced CSR practices following the work of [48]. However, the significant interaction term between China’s high-tech and green technology innovations reveals a crucial moderating effect: as Green Innovation levels increase, they positively moderate the negative impact of China’s high-tech Innovation on CSR, potentially even reversing it, emphasizing the importance of a combined approach to innovation for fostering CSR. State equity, innovation level, and market value also show significant associations with CSR, albeit with smaller coefficients, highlighting the multifaceted nature of factors influencing CSR outcomes within organizations which aligns with the work of [23] highlighting the potential multifaceted relationship between CSR and innovation.

Table 4 Panel least square co-efficient
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Table 5 presents the results of a Hausman test, a diagnostic tool used to assess the potential endogeneity of variables in a regression model. The p-values associated with each variable's test statistic indicate whether they are likely exogenous (not subject to endogeneity concerns) or endogenous (potentially biased). Notably, all p-values exceed the conventional significance level of 0.01 and 0.05, suggesting that these variables are exogenous and not affected by endogeneity issues in the regression model. Therefore, the coefficient estimates derived from the models are consistent, enhancing the reliability of the regression results.

Table 5 Test for endogeneity (hausman test)
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The findings of a Panel Vector Autoregression (VAR) analysis are shown in Table 6. The size and direction of each lagged variable's influence on the current values of the variables are vitally revealed by the coefficients for each one. Notably, the high R-squared and Adjusted R-squared values that are getting close to unity point to a strong model fit with the data, suggesting that the lagged values account for a sizable amount of the variance in the dependent variables. The low p-values linked to the F-statistic further emphasize the model's overall statistical significance. The dependent variables' mean, and standard deviation give context for their central tendency and temporal dispersion, while the standard errors shed light on the accuracy of the coefficient estimations. Together, these diagnostic statistics improve knowledge of the intricate temporal dynamics influencing business performance and behaviour. They also offer important insights into the interactions between state participation, market dynamics, innovation, and corporate social responsibility.

Table 6 Panel VAR
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The Hausman test is sometimes described as a test for model misspecification. In panel data analysis (the analysis of data over time), the Hausman test can help researchers to choose between fixed effects model and a random effects model. The null hypothesis is that the preferred model is random effects; the alternate hypothesis is that the model is fixed effects. Essentially, the tests look to check if there is a correlation between the unique errors and the regressors in the model. The null hypothesis is that there is no correlation between the two.

4 Discussion

Drawing upon corporate social performance (CSP) and innovation diffusion theory, this study aims to explore the relationship between innovation strategies and Corporate Social Responsibility (CSR) performance, with a special emphasis on the moderating effect of Green Innovation (GI). Our study tested China’s high-tech firms, green Innovation, State Equity (SE), Innovation Level (IL), and Market Value (MV) influences CSR outcomes. Moreover, our study tested interaction on how the combined effects of high-tech and green innovation impact CSR. As stated in H1. Green innovation moderates the association between China’s high-tech and CSR [40]. This suggest that green innovation play a crucial role in firms’ performance. Furthermore, results showed that there is an association between CSR and green innovation, thereby confirming H2. From the CSP theory, we find the theoretical justification on how green innovation associate with CSR performance [20]. The majority of past studies [38, 46, 47, 49, 75, 80] have mainly focus on green absorptive capacity and green entrepreneurship orientation for both corporate environmental performance and economic performance while ignored to establish and examine the role of green innovation on firms high-tech and CSR performance. This finding inferred that companies should give socially conscious practices top priority when incorporating them into their innovation plans [48], and ensure that innovation projects are in line with the organization's CSR aims and values by considering their social and environmental impacts. This current study extends on past studies [14, 46, 69, 85] and establish the complex relationship between green innovations, CSR performance and China high-tech, with the inclusion of key control variables (state equity, innovation level, marketing value) in the context of African nation.

Besides, this study found interaction effect between high-tech innovation and green innovation on corporate social responsibility performance. Thus, confirming our H3. Also, findings shows the significant connection between innovation level and corporate social responsibility performance, the result further suggest that higher innovation level contribute to firm high-tech, green practices and state equity, and market value show significant associations with CSR. Thus, our H4, H5 and H6 is thereby supported. The implication of this findings indicates that companies are better positioned to produce sustainable value for all stakeholders, including shareholders, employees, communities, and the environment when they include CSR principles in innovation initiatives [69].

Furthermore, through the implementation of a triple-bottom-line strategy that considers economic, social, and environmental aspects, businesses in Africa can cultivate trust, strengthen their resilience, and promote sustainable development [83]. Businesses can position themselves as agents of positive social and environmental change while concurrently creating value for stakeholders and society at large. By aligning innovation strategies with CSR principles, investing in green innovation, considering contextual factors, fostering stakeholder engagement and transparency, building capacity and sharing knowledge, offering policy support and incentives, fostering collaborative initiatives and partnerships, measuring and evaluating impact, managing risks, and placing a priority on long-term value creation [69].

4.1 Theoretical implications and novelty of the study

This research is among the few study that applied corporate social performance (CSP) and innovation diffusion theory (IDT) by incorporate several innovation strategies and corporate Social Responsibility (CSR) performance, with a special emphasis on the moderating effect of green Innovation. This study asserted that while green innovation may drive corporate performance in certain aspects, it might not necessarily translate into enhanced CSR practices following the work of [48]. In contrast, green innovation focuses on firms that develop more environmentally friendly products, to reduce the negative impact on the environment [80]. For instance [17], explain innovation as the process of introducing new ideas, methods, products, or processes that create value for businesses and society.

While green innovation on the other hand, focuses on developing and implementing solutions that address environmental challenges and promote sustainability. Green innovation aims to minimize the environmental impact of business activities, reduce resource consumption, and enhance ecological resilience while simultaneously delivering economic benefits [24]. Further, this study argue that China’s high-tech innovation exhibits a strong and positive correlation with green innovation and market value respectively, indicating that higher levels of China’s high-tech innovation are associated with higher levels of green innovation and market value which follows the work of [37] which posit that the degree of regional China’s high-tech development is directly correlated with the green innovation efficiency level. This research extends to the body of knowledge of green innovation and corporate social responsibility from the lens of TD and CSP theory. Also, our study expands the IDT and CSP theory by applying the theory in the body of social responsibility and sustainability. This study addressed how high-tech firms, state equity, innovation and market value influences CSR outcomes through awareness of green practices. Furthermore, this current study also draws on empirical literature and establishes a theoretical framework on CSP and IDT. The findings underscoring the significance of incorporating ecologically sound practices into innovative approaches to improve corporate social responsibility (CSR) outcomes. Interestingly, this study found that green innovation is important moderator that lessens the possible harm that China’s high-tech innovation may cause to CSR. Furthermore, we cannot ignore that our theoretical assumption of this current study builds on CSP and IDT theory literature to address the relationship between innovation strategies and Corporate Social Responsibility (CSR) performance, with a special emphasis on the moderating effect of green innovation (GI). The study advances past scholarship work by extending the literature and provide new insights into the view of how China’s high-tech firms, State Equity (SE), Innovation Level (IL), and Market Value (MV) influences CSR outcomes through the moderating effect of green Innovation practices. Notably, this is related by how well companies can engage in green innovation practices [53, 80] engage in social responsibility, improve business performance and management practices [55, 56, 61]. Past studies on green innovation and CSR are examined from the dynamic capability, stakeholder, institutional and resource based view theories [51, 68, 77, 85].This study differs from the previous study by extending the body green innovation by incorporating CSR practices in the Chinese high-tech firms with the inclusion of key variables (state equity, innovation level and market value) to address how green innovation moderates the relationship between innovation strategies and Corporate Social Responsibility (CSR) performance. This leads to our research question of whether green innovations can influence CSR performance through high-tech performance in the African nation and how China’s high-tech innovation affect CSR outcomes and what impact do green innovation has between China’s high-tech innovation and CSR. Hence, combining the research theories helps researchers understand influence of green innovations on CSR performance in the African nations. In this study, ours evidence emphasized an association between green innovation and CSR performance in the African state. Our study further showed that green innovation plays a moderator factor in promoting the association between China’s high-tech innovation and CSR performance. While innovation level, market value and state equity were found to positively influence CSR performance in the region under study. This evidence suggest that firm are advised to prioritize and invest in green innovation initiatives into CSR strategies [88].

5 Conclusion and recommendation

This study offers insightful information about the interactions between Corporate Social Responsibility (CSR), China’s high-tech innovation, green innovation, state equity, innovation level, market value involvement across the countries under study. Through regression analysis, significant associations were uncovered, particularly highlighting the moderating effect of green innovation on the relationship between China’s high-tech innovation and CSR. The Hausman test results further affirmed the reliability of the regression findings. Additionally, the Panel Vector Autoregression (VAR) analysis shed light on the dynamic interactions among CSR, innovation, and market factors over time. These findings underscore the importance of integrating environmentally sustainable practices into innovation strategies to enhance CSR performance across the African continent [62]. The implications of this study extend to both corporate and policy levels, suggesting the need for organizations in African countries to prioritize sustainable innovation strategies and for policymakers to incentivize and promote environmentally responsible practices. Based on these findings, it is recommended that organizations should prioritize the integration of both China’s high-tech and Green Innovations into their strategies to enhance CSR performance. Additionally, policymakers should consider incentivizing and promoting environmentally sustainable innovation to facilitate CSR initiatives.

5.1 Limitations and directions for future study

While this study provides valuable insights into the relationship between innovation strategies and Corporate Social Responsibility (CSR) performance in African countries, several limitations warrant consideration for future research. Firstly, the study primarily focuses on quantitative analysis, which may overlook the nuanced qualitative aspects of CSR implementation and innovation strategies. Future studies could adopt a mixed methods approach to provide a more comprehensive understanding of the underlying mechanisms and contextual factors shaping this relationship. Additionally, the study predominantly examines the influence of internal factors on CSR performance, neglecting the broader external environment, such as regulatory frameworks, market dynamics, and cultural norms. Future research could explore the impact of external factors on the relationship between innovation strategies and CSR performance, providing a more holistic perspective. Moreover, the study’s findings may be limited by data availability, particularly in the context of African countries with diverse socio-economic and political landscapes. Future studies could address these limitations by collecting primary data through surveys, interviews, and case studies to capture the complexities of CSR practices and innovation strategies in African contexts. Furthermore, given the dynamic nature of innovation and CSR, longitudinal studies could offer insights into the long-term effects of innovation strategies on CSR performance, allowing for the identification of trends and patterns over time.