The interplay between green supply chain management practices and firm performance: does green technological innovation and institutional pressure matter? Open Access

Green supply chain management (GSCM) practices have become a critical global sustainability priority for countries and organisations due to escalating environmental challenges, such as climate change, environmental degradation and pollution, alongside rapid advancements in technology (Chandio et al., 2021; Steenkamp, 2019). GSCM practices are defined as environmental improvement strategies and policies that integrate environmental considerations into an organisation’s supply chain management practices, including procurement, manufacturing, distribution and reverse logistics (Al-Maáitah, 2018; Çankaya and Sezen, 2018; Dong et al., 2021). Studies have shown that adopting GSCM practices is on an increasing trajectory and ensures compliance with all environmental regulations driven by institutional and stakeholder pressures to promote environmentally friendly industrial processes (Bhatia and Gangwani, 2021; Tseng et al., 2019). Stakeholders, including governments, regulators and customers, increasingly demand that companies adopt GSCM and green innovation to enhance performance and gain sustainable competitive advantage by meeting customer expectations (Oduro et al., 2022; Román et al., 2022; Yan et al., 2021).

Similarly, there is growing interest in how practices, such as GSCM, contribute to environmental preservation and firm performance (Pinto, 2020). The global market turbulence has pressurised firms to explore all avenues for enhanced performance. Consequently, managers are keen on evaluating firm performance outcomes (Uchenna and Onuoha, n.d.). For instance, Prashar (2023) assessed firm performance through accounting-based outcomes (e.g. return on equity) and market performance outcomes (a firm’s operational performance relative to investments measured as return on assets, sales growth). This study defines firm performance as a measure of a firm’s effectiveness in terms of financial and operational efficiency (Saraf et al., 2007; Soesetio et al., 2023). Previous research has investigated the link between GSCM practices and firm performance, but the empirical findings have been inconsistent and contradictory, showing positive, negative or no effects, making the value proposition of GSCM practices unclear (Holling and Backhaus, 2023; Silva et al., 2021; Younis et al., 2020). Some studies indicate a positive relationship (Mallikarathna and Silva, 2019; Santoso et al., 2022; Wang and Yang, 2021; Yan et al., 2021), whereas others report a negative relationship (Geng et al., 2017; Holling and Backhaus, 2023) or no significant effect of GSCM on performance (Esfahbodi et al., 2023; Novitasari and Agustia, 2021). Consequently, there is a dearth of studies explaining the mechanisms and boundary conditions under which GSCM practices contribute to firm performance (Alsuraihi et al., 2022; Bandoophanit, 2024; Nazir et al., 2024; Somjai and Jermsittiparsert, 2019; Khan and Qianli, 2017), particularly in developing countries, specifically within the African context, where challenges related to sustainability, technological adoption and institutional weaknesses are more pronounced (Agyapong et al., 2023; Amoako-Gyampah et al., 2020; Nazir et al., 2024; Silva et al., 2021). Thus, African business leaders require better insight into how GSCM practices benefit firms (Agyapong et al., 2023; Gera et al., 2022).

Scholars have argued that innovations in products, processes, marketing strategies and technology can provide competitive advantages, thereby affecting price, quality, delivery and environmental well-being (Sahoo et al., 2023; Wang et al., 2019). Innovation enhances competitiveness by enabling swift responses to environmentally friendly technologies, market shifts and emerging trends (Román et al., 2022). However, investing in innovation and eco-friendly technology incurs costs, necessitating frugality in green technological innovation (Stucki, 2019). Green technological innovation (GTI) offers two benefits: reducing environmental challenges and contributing to technological modernisation of the economy (Umar et al., 2016). GTI is defined as a firm’s ability to develop novel processes and products with a green orientation (Abdallah et al., 2016; Castellano et al., 2022). GTI improves firm performance (Umar et al., 2016) and enhances operational efficiency, productivity, quality and cost-effectiveness (Ju et al., 2016).

Businesses face pressure from governments, regulatory institutions and customers to comply with rules and regulations influenced by cultural-cognitive, normative and regulatory controls (Kros et al., 2020). Institutional pressure, defined as external forces limiting organisational choices, is crucial in GSCM practices (Moser et al., 2020). These pressures guide initiatives towards social, financial and environmental values (Thong and Wong, 2018). External stakeholders, such as government agencies and NGOs, impose formal and informal pressure on organisations to meet environmental requirements (Abu Talib et al., 2020). Manufacturers face global industry pressure to adopt GSCM practices to remain competitive (Abdallah and Al-Ghwayeen, 2019). In addition, GSCM practices benefit firms, especially those with limited resources and budgets, by seamlessly integrating strategic planning and daily operations (Menon and Shah, 2020).

Environmental issues such as pollution, global warming, resource depletion and degradation threaten the ecological balance (Zhu et al., 2022). Similarly, firms encounter ecological challenges due to regulatory bodies, shareholders, competitors, voluntary charters, legislation and technological challenges (Mohamad and Koilpillai, 2018; Suryanto et al., 2018). Again, societal and government pressures compel companies to reassess their production processes and supply chain activities (Yildiz Çankaya and Sezen, 2019). In response, entities such as governments, firms, communities and individuals adopt GSCM practices to address these environmental issues. GSCM practices have become policy tools for many companies (Onyinkwa and Ochiri, 2016). Organisations are expected to enhance their GSCM capabilities owing to new regulations and growing business enthusiasm for ecological initiatives (Uygun and Dede, 2016). In light of this context, this study aims to achieve the following objectives:

1. to examine the impact of GSCM practices on firm performance;

2. to assess the mediating role of GTI in the relationship between GSCM practices and the firm; and

3. to test the moderation role of institutional pressure in the link between GSCM practices and firm performance via GTI.

To meet the study objectives, we used the Resource-Based View (RBV) (Barney, 1991) and Institutional Theory (DiMaggio and Powell, 1983) to examine a model addressing two significant but less-explored questions:

The RBV posits that GSCM practices and GTI capabilities (Umar et al., 2016) are critical for sustainably enhancing firm performance and achieving competitive advantage because of their valuable, real, imperfectly imitable and non-substitutable characteristics (Barney, 1991). Furthermore, from the RBV perspective of input-transformation-output resources (Brandon-Jones et al., 2014; Lado et al., 1992), GSCM practices are valuable input resources for generating technological innovation and improving performance outcomes (Lado et al., 1992; Umar et al., 2016; Yan et al., 2021). However, institutional theory argues that isomorphic pressures (coercive, mimetic and normative) compel organisations to embrace GSCM practices to protect the environment and enhance firm performance (Huang et al., 2016). This study investigates the effects of GSCM practices on firm performance by applying GTI under varying degrees of institutional pressure (Figure 1). It addresses existing gaps in the GSCM literature by analysing data from 303 firms in Ghana, a sub-Saharan African market, to demonstrate that institutional pressure moderates the positive indirect relationship between GSCM practices and firm performance through the GTI. Furthermore, this study uniquely integrates the input-transformation-output resources perspective of the RBV (Brandon-Jones et al., 2014; Lado et al., 1992) with the isomorphic pressures of institutional theory (Huang et al., 2016) to explore the interaction between GSCM, GTI, institutional pressure and firm performance.

The research indicates a notable positive correlation between GSCM practices and firm performance, with GTIs playing a mediating role in this relationship. In addition, the results show that institutional pressure influences the link between GSCM practices and firm performance through GTIs. This paper is structured as follows: chapter two explores the conceptual frameworks of the study constructs and outlines the hypotheses along with their theoretical foundations, followed by chapter three, which presents a description of the empirical data. Chapter four also presents the data analyses and results. Finally, chapter five discusses the research contributions, implications, limitations and potential directions for future research.

GSCM practices involve integrating environmentally responsible principles into supply chain management activities (Mumtaz et al., 2018) and broader environmental contexts (Khan et al., 2018; Mumtaz et al., 2018). According to Qorri et al. (2018), GSCM practices involve the deliberate and strategic alignment of business processes throughout the supply chain to achieve environmental, social and economic objectives. Scholars argue that many firms have adopted GSCM practices to mitigate the environmental impacts of their products or services (Khan et al., 2018; Wang and Yang, 2021). The adoption of GSCM practices significantly enhances organisations’ long-term sustainability performance (Dong et al., 2021). GSCM practices include green manufacturing, purchasing, eco-design, green information systems, investment recovery, internal environmental management and customer cooperation (Abdullah et al., 2019; Khan et al., 2018).

Despite the significance of firm performance as a frequently used dependent variable, there is no consensus on its definition, dimensions, or measurement (Santos and Brito, 2012). Hansen and Wernerfelt (1989) note that firm performance is multifaceted and can be assessed through metrics, like shareholder wealth and staff satisfaction. Schulze et al. (2022) limited the measure of firm performance to revenue generation, and Ali et al. (2022) operationalised it as a return on asset. Liang et al. (2010) identified three measurement categories: finance (e.g. ROA, ROI, ROE, ROS, sale/growth and stock share returns), efficiency (e.g. productivity and administration expenses to sales) and others (e.g. customer satisfaction, value addition and market share). Prior studies on GSCM have often used multidimensionality to measure firm performance (e.g. social, economic, operational and environmental performance measures) (Amjad et al., 2022; Borazon et al., 2022). Alternatively, some researchers define firm performance as a unidimensional construct, such as sustainability outcomes (Novitasari et al., 2023). Ricardianto et al. (2023) argue that broadening the concept of firm performance is vital for assessing overall success. Zhu et al. (2022) emphasised that achieving superior overall success motivates firms to integrate sustainability standards. Accordingly, based on financial, efficiency and other performance categories, this study measures firm performance as organisational effectiveness in financial and operational efficiency (Saraf et al., 2007; Soesetio et al., 2023).

The current dynamic and rapidly changing business environment is characterised by technological advancement, innovation and environmental awareness. Consequently, GTI involves integrating new ideas and technology into developing products, services, or processes with a greener focus (Abdallah et al., 2016; Castellano et al., 2022). This has garnered significant attention owing to growing environmental concerns and remains crucial for companies to deliver advanced products while maintaining cost efficiency and environmental integrity (Abdallah et al., 2016; Umar et al., 2016). Nolan (2019) stated that innovation novelty involves the integration and customisation of new or modified technologies. Industries are increasingly adopting eco-friendly technologies, green innovations and renewable energy sources to enhance the sustainability of environmental and technological advancements (Cui et al., 2021). These eco-friendly technologies have revitalised modern economies (Wang et al., 2021). Given these conditions, organisations are driven to foster creativity to improve the consistency, quality and design of their products and services. Firms must enhance their innovation capabilities to maintain a competitive edge, enabling them to generate and promote innovative green technologies effectively (Khan et al., 2022).

Institutional pressure, captured as external influences that have the potential to impact the activities of organisations (Roszkowska and Melé, 2021; Shahzad et al., 2022), includes various institutional actors and isomorphic mechanisms (coercive, mimetic and normative) that prompt organisations to adopt environmentally friendly strategies (DiMaggio and Powell, 1983). Coercive pressure involves external forces (such as political and legislative actors) that affect an organisation’s regulatory compliance and environmental sustainability, considering internal factors (DiMaggio and Powell, 1983; Wang et al., 2019). Normative pressures stem from professionalisation arising from adherence to industry standards and norms held by professionals, professional associations and educational institutions (Alda, 2019), including suppliers, customers, unions, social groups, end users and supply chain partners (Somjai and Jermsittiparsert, 2019). Mimetic pressure refers to the tendency of organisations to imitate the successful strategies of other firms, especially competitors, during uncertainty (DiMaggio and Powell, 1983). In such circumstances, organisations often replicate successful practices observed in peers and rivals linked to competitive norms and regulations, particularly when competitors uphold prevailing standards (Saeed et al., 2018). We argue that these isomorphic forces collectively pressure organisations to adopt GSCM practices to protect the environment and enhance firm performance (Huang et al., 2016).

The existing literature from the RBV perspective suggests that a firm’s resources and competencies influence its performance (Barney, 1991; Wernerfelt, 1984). This theory comprises both tangible and intangible resources, including an organisation’s GSCM practices (Vitorino Filho and Moori, 2020). Accordingly, firms with valuable resources are more competitive (Barnett and Burgelman, 1996). Scholarly work has shown that GSCM practices (Yan et al., 2021) and GTI capabilities (Umar et al., 2016) are crucial for better performance. In addition, firms can use the input, transformation and output resource dimensions of the RBV (Brandon-Jones et al., 2014; Lado et al., 1992) to develop resources and capabilities that support environmental sustainability. Consequently, this study views GSCM practices as valuable input resources for developing the GTI as a transforming resource to achieve superior performance (Lado et al., 1992; Umar et al., 2016; Yan et al., 2021).

Institutional theory traditionally examines how organisations maintain and enhance their influence and legitimacy by adhering to established norms within their institutional context (Brandon-Jones et al., 2014; Sirmon and Hitt, 2009). It posits that external social, political and economic forces shape an organisation’s strategic decisions to secure stakeholder approval (Jennings and Zandbergen, 1995). This study posits that conformity to societal norms significantly influences the adoption and execution of GSCM practices, thus aligning actions with social expectations. Accordingly, we relied on institutional theory (DiMaggio and Powell, 1983) to investigate the interplay between GSCM practices, GTI, Institutional Pressures and firm performance among firms in Ghana, a Sub-Saharan African country.

Previous studies have explored the determinants of firm performance using various outcomes (Holling and Backhaus, 2023; Novitasari and Agustia, 2021). Younis et al. (2020) noted that the connection between the green supply chain and organisational performance was mixed and inconclusive. The literature from the RBV perspective suggests that strategic resources, such as GSCM practices, may influence firm performance (Barney, 1991; Wernerfelt, 1984; Yan et al., 2021). Conversely, Holling and Backhaus (2023), Geng et al. (2017) and Esfahbodi et al. (2023) reported a negative relationship with performance and Novitasari and Agustia (2021) find no significant effect of GSCM on performance. However, GSCM practices can be regarded as resources that can enhance performance (Khan et al., 2018; Wang and Yang, 2021). Firms that use GSCM principles often improve their performance (Mallikarathna and Silva, 2019; Santoso et al., 2022; Yildiz Çankaya and Sezen, 2019). Thus, this study hypothesises the following:

Due to varied and inconsistent findings regarding the relationship between GSCM practices and firm performance, where some studies have found a positive link (e.g. Santoso et al., 2022; Wang and Yang, 2021), while others have reported a negative relationship (e.g. Geng et al., 2017; Holling and Backhaus, 2023) or no significant effect of GSCM on performance (e.g. Esfahbodi et al., 2023; Novitasari and Agustia, 2021) there is the need to have a deeper understanding on the relationship (Agyapong et al., 2023; Gera et al., 2022). Consequently, several studies have examined the impact of GSCM practices on organisational performance using various mediators (Khan and Qianli, 2017; Mumtaz et al., 2018; Somjai and Jermsittiparsert, 2019). Alsuraihi et al. (2022) found that innovation mediates the relationship between green supply chain-social performance links. Li and Hu (2021) suggested that GTI intervenes in the environmental regulation-economic development link. Xiao and Su (2022) argued that the GTI is crucial for firm innovation, digitisation and environmental and social performance. No studies have used GTI as a mediator between GSCM and firm performance. Some studies report a positive link between GSCM and technological innovation (Alsuraihi et al., 2022; Rao, 2002) and technological innovation and firm performance (Alsuraihi et al., 2022; Khan et al., 2022). From an RBV perspective (Brandon-Jones et al., 2014; Lado et al., 1992), GSCM practices (Yan et al., 2021) and GTI capabilities (Umar et al., 2016) are valuable inputs that transform resources to drive performance (Lado et al., 1992; Umar et al., 2016; Yan et al., 2021). Thus, this study argues that GTI may positively mediate the relationship between GSCM and firm performance. Thus, we propose the following hypothesis:

Committing to sustainability standards is very challenging for firms in developing countries because of the relatively low concern about sustainability issues by citizens, cost implications, relatively weak institutions, inefficient laws and regulations and technological and infrastructural deficits (Amoako-Gyampah et al., 2020; Massoud et al., 2010). Accordingly, motivation and sanctions are required to drive these initiatives. Adomako et al. (2023) argued that stakeholder pressures offer the output constraints – such as standards and regulations – that outline what a product or service should or should not contain or be able to perform to encourage the decrease in environmental degradation. Regulatory pressures influence organisational green innovation, particularly for firms whose operations have the greatest impact on the environment (Liu et al., 2024). Liao (2018) highlighted the need to examine the role of institutional pressure in promoting green innovation (Chen et al., 2018). Institutional pressure (normative, coercive and mimetic) is a multifaceted construct which has been less explored in the literature because of several boundary circumstances such as a firm’s values, slack resources and other industry-specific features which have the potential to constrain a firm’s response to change (Chen et al., 2018; Risi et al., 2023). Pereira et al. (2023) stressed that institutional pressures have the potential to result in sustainability certifications, which in turn can raise a company’s innovative capabilities and performance. Thakur-Wernz and Bosse (2023) suggested that institutional theory can be used to explain several firms’ innovative strategies, particularly green innovation. Moreover, the drive for sustainability in recent times and the bandwagon’s proposition that stakeholders exert pressure on firms to adopt innovations that promote operations and generate economic and social performance based on the success stories of other firms, industries and developed economies (Wang et al., 2023). Based on this backdrop and the moderated mediation perspective, this study hypothesises the following:

To investigate the impact of GSCM practices on firm performance in environments with limited resources, data were collected from Ghanaian businesses, predominantly small and medium-sized enterprises. Like many other African nations, Ghana’s business landscape is marked by various environmental, technological and institutional challenges (Agyapong et al., 2023; Amoako-Gyampah et al., 2020; Nazir et al., 2024). Companies in Ghana face not only sustainability, innovation and technological capacity issues (Nazir et al., 2024; Silva et al., 2021) but also institutional weaknesses (Agyapong et al., 2023; Amoako-Gyampah et al., 2020). These obstacles present significant challenges Ghanaian firms must overcome to survive and compete in the dynamic global market, making Ghana an ideal setting for studying GSCM practices under institutional pressure. This study used primary data from firms in Ghana, an emerging market in sub-Saharan Africa, to test its hypotheses. Ghana’s socioeconomic transformation (Acquaah, 2007) and market-based activities (Boso et al., 2013a) have enhanced entrepreneurial and supply chain activities (Amankwah-Amoah et al., 2024; Boso et al., 2013b). As a fast-growing economy (African Development Bank, 2018; Zougmoré et al., 2018) with rapid institutional changes (World Bank, 2017), firms in Ghana are facing increasing social and environmental issues, such as pollution and resource depletion (Zhu et al., 2022). They also encounter unique GSCM challenges owing to weak institutions, inefficient laws and technological shortfalls (Amoako-Gyampah et al., 2020). In addition, global change drivers such as regulatory bodies and competitors exacerbate these problems (Mohamad and Koilpillai, 2018; Suryanto et al., 2018). This underscores the need for GSCM practices and GTI, making the investigation of their influence on firm performance in Ghana significant.

The target population includes 135,954 registered small and medium-scale businesses in Ghana’s manufacturing, service, agri-business, construction and extractive industries (Ghana Statistical Service, 2017). Sampling across industries (Zhu et al., 2018) provides data heterogeneity to test our conceptual model (Bouquet et al., 2009). Developing market firms, mainly small and medium businesses (Amoako-Gyampah et al., 2020), were selected if they had at least five full-time employees and operated continuously for at least three years. Consistent with previous GSCM studies (Khan et al., 2023; Vidal et al., 2023), data were collected from key informants in each firm, such as CEOs, procurement officers, supply chain officers, logistics managers, operations officers and environmental officers, who had at least five years of relevant experience. Considering the fact that survey studies are often characterised by issues of non-response (Lynn, 2012; Peytchev, 2013), 450 companies were selected for this study, exceeding the recommended minimum sample size of 200 for structural equation modelling (Bagozzi and Yi, 2012). This was done to ensure that the usable data that would be left after accounting for non-responses would be adequate for this study. Access to the organisations was negotiated by doing the following: first, the target firms were contacted via phone to obtain permission for survey participation, followed by an introductory letter outlining the study’s aims and assuring anonymity. After several follow-up calls, 350 firms responded to the questionnaires. After evaluation for completeness, 303 valid responses were retained, resulting in a 67.3% effective response rate. We performed t-tests to assess non-response bias by comparing the first 25% of respondents to the last 25% based on demographic data, such as age, educational level, experience and organisational sector, revealing no significant differences (p < 0.05), indicating no non-response bias in this study (Amstrong and Overton, 1977). Common method bias was addressed using Harman’s single-factor test (Podsakoff et al., 2003), which showed that only 27.55% of the variance in the outcome variable was explained by the independent variable, below the threshold suggested by Humaidi and Balakrishnan (2015). Statistical analyses confirmed the absence of common method bias (Flynn et al., 2010). The unit of analysis in this study was the organisation.

The data for this study were obtained through a structured questionnaire, a vital and commonly used instrument in supply chain management research (Kotzab, 2005; Montabon et al., 2018). To ensure the precise measurement of the research constructs, four established instruments with confirmed validity and reliability were adopted. For initial validation, these instruments were evaluated by five academics and four professionals with expertise in supply chain management. The study constructs were measured using items established in previous research. Six items for GSCM practices were adapted from Feng et al. (2018), Adomako and Tran (2022) and Khan et al. (2022). Four items on institutional pressure were adapted from Liu et al. (2010) and Chu et al. (2017). Similarly, five items for GTIs were based on Khan et al. (2022), and five items for firm performance were adapted from Adomako and Tran (2022). The measures underwent expert review and pilot testing to ensure their relevance and accuracy. These efforts were made to avoid measurement errors and verify that the measurements were relevant and suited to the study setting. Consistent with the literature from which the instruments were adapted, a seven-point Likert scale was used to assess the study’s constructs, with 1 representing Strongly Disagree and 7 representing Strongly Agree. The scale items are detailed in Table 1.

To address omitted variable bias and endogeneity concerns, we incorporate both internal and external control variables that could potentially influence the predictor, mediator and outcome variables (Adomako et al., 2023; Chatterjee et al., 2024; Lu et al., 2018). Prior research indicates that firm characteristics such as age and size can affect practice adoption and performance (Ferreira et al., 2024; Gu et al., 2024). Firm size refers to the number of employees, whereas firm age indicates the number of years of operation (Børing, 2020). Asad et al. (2024) suggested that variations in experience, resource acquisition and risk-taking between young and mature firms influence performance, and Shakil et al. (2024) noted that firm age impacts financial performance. Consequently, these variables were controlled for to examine their relationships with the study variables.

Consistent with the relevant literature (Aguirre-Urreta and Hu, 2019), potential issues related to common method variance were addressed both procedurally and statistically (Podsakoff et al., 2024). The procedural strategy included enlisting senior managers as the survey respondents. Given their involvement in decision-making and operational processes, senior managers typically have a comprehensive understanding of and valuable insights into business activities, making them a dependable and credible information source. Another procedural tactic was to create psychological separation by positioning the predictor and outcome variable items in different sections of the questionnaire. In addition, the participants were assured of the anonymity of their responses to promote objectivity and accuracy (Podsakoff et al., 2003). The purpose of the study was also communicated to the participants to ensure confidentiality, along with providing clear instructions and conducting a pilot study to refine the items. Participants who failed to answer at least 95% of the survey questions were excluded, resulting in 47 discarded questionnaires and 303 valid responses. Next, we used SPSS’s expectation-maximisation technique to substitute ten cases of missing data (ranging from one to three items) (Hair et al., 2014).

Best practices were used to evaluate the reliability and validity of the conceptual framework. Factor loadings were satisfactory (>0.7). Scale reliability was confirmed using Cronbach’s alpha and composite reliability (Bagozzi and Yi, 2012; Fornell and Larcker, 1981), and the Cronbach’s alpha value for each set of items exceeded the minimum threshold of 0.70 (Hair et al., 2014), as shown in Table 1. Exploratory factor analysis with maximum likelihood and varimax rotation validated the measures for the constructs, ensuring that items were appropriately loaded and distinct from unrelated measures. Accordingly, the validity of the items used to measure the study variables was confirmed. Krabbe (2016) stressed the importance of discriminant validity in distinguishing between constructs. Convergent validity was tested using the average variance extracted (AVE) (Hair et al., 2021), with AVE values of 0.50 or, indicating good convergent validity (Hair et al., 2021). Discriminant validity was confirmed by comparing each construct’s AVE with the squared inter-construct correlation (Fornell and Larcker, 1981). Fornell and Larcker (1981) proposed that the shared variance of each model construct should be smaller than its AVEs to ensure discriminant validity (see Table 2).

The total explained variance was 68.45%. Again, the CFA results suggested that the four-factor model passed the initial fitness test (see Figure 2 and Table 1) (chi square = 249.40, degree of freedom (df) = 164, RMSEA = 0.042, TLI = 0.98, CFI = 0.98, RFI = 0.94). Table 2 further reveals that both convergent and discriminant validity were achieved.

The results in Table 3 show the distribution of the industry characteristics. The study found that most of the companies we gathered data from were in the manufacturing sector 38.9% (n = 118), and service 41.26% (n = 126) sectors. The industries employ between 5 and 100 full-time workers 97.4% (n = 295) and have operated for between 3 and 20 years 86.8% (n = 263).

One of the goals of this study was to examine the direct effect of GSCM practices on firm performance. The results in Table 4 show that GSCM practices have a direct positive association with firm performance (β = 0.22, p-value = 0.0001, CI = 0.119,0.302). Although the literature presents mixed and inconsistent findings regarding GSCM practices and various performance outcomes (Younis et al., 2020), while some studies, such as Geng et al. (2017) and Holling and Backhaus (2023), report a negative relationship with performance. Esfahbodi et al., 2023; Novitasari and Agustia (2021) found no significant effect of GSCM practices on performance. However, the present findings align with several other studies from the RBV perspective, suggesting that GSCM practices may influence firm performance (Barney, 1991; Santoso et al., 2022; Wang and Yang, 2021; Wernerfelt, 1984; Yan et al., 2021).

The second objective of this study was to examine the mediating role of GTI on the link between green supply chain management and firm performance using the Hayes process macro (Hayes, 2013). Table 4 demonstrates that GTIs mediate the positive association between GSCM practices and firm performance (total effect size = 0.093, CI = 0.0411,0.1501). This result confirms the existing literature, which suggests that GTIs may mediate the relationship between GSCM practices and firm performance (Alsuraihi et al., 2022; Khan et al., 2022; Li and Hu, 2021; Rao, 2002; Xiao and Su, 2022). This result is consistent with the RBV perspective (Brandon-Jones et al., 2014; Lado et al., 1992), wherein GSCM practices (Yan et al., 2021) and GTIs (Umar et al., 2016) are considered valuable inputs that transform resources to enhance performance (Lado et al., 1992; Umar et al., 2016; Yan et al., 2021). Eventually, this study’s proposition that GTI may positively mediate the relationship between GSCM practices and firm performance is supported.

Finally, the study sought to examine the conditional effect of institutional pressure on the indirect association between GSCM practices and firm performance through GTIs using Hayes Process Macros (Model 7) (see Table 4 and Figure 2). Institutional pressure (normative, coercive and mimetic) positively moderates the indirect relationship between GSCM practices and firm performance through GTIs. This is also consistent with Adomako and Tran (2022), who found that high levels of stakeholder pressure drive environmental collaboration and innovation. In addition, as suggested by Thakur-Wernz and Bosse (2023), institutional theory can elucidate green innovation and the push for sustainability in contemporary times, where stakeholders apply pressure (normative, coercive and mimetic) on companies to embrace technological innovation, which is consistent with the results of this study. Consequently, all hypotheses were supported.

This study contributes to the green supply chain literature and its interface with scholarly works on the RBV in several ways. Specifically, this study provides important theoretical contributions to the GTIs mechanisms and institutional pressure conditions under which GSCM practices contribute to firm performance.

Existing literature on sustainability suggests that the link between GSCM practices and firm performance is unclear (Yildiz Çankaya and Sezen, 2019; de Sousa Jabbour et al., 2015). Nevertheless, this study identifies a positive and significant relationship between GSCM practices and firm performance, which is consistent with previous studies (e.g. Huma et al., 2023; Al-khawaldah et al., 2022). García Alcaraz et al. (2022) found that GSCM practices are related to environmental performance and cost reduction. Astawa et al. (2021) found that GSCM practices are positively associated with competitive advantage. Drawing on the RBV) (Brandon-Jones et al., 2014; Lado et al., 1992; Yan et al., 2021), this study expands the theoretical framework concerning the performance outcomes of GSCM practices by illustrating a direct positive relationship between GSCM practices and firm performance (Huma et al., 2023; Al-khawaldah et al., 2022; Junaid et al., 2022).

Previous research identified a gap in the implementation of GSCM practices (Amjad et al., 2022). Zhang et al. (2022) emphasised the need to comprehend the underlying mechanisms of GSCM practices and their impact on firm performance rather than merely focusing on the features of GSCM practices and their relationship to organisational performance. This study seeks to address this gap by investigating the mechanisms by which GSCM practices influence firm performance. Specifically, it examines the mediating role of GTIs in the relationship between GSCM practices and firm performance. The findings of this study indicate that GTIs mediate the direct impact of GSCM practices on firm performance, which is consistent with the literature (e.g. Alsuraihi et al., 2022; Khan et al., 2022; Li and Hu, 2021). Huma et al. (2023) contended that a firm’s commitment to sustainability standards necessitates the adoption of Information and Communication Technology (ICT). Ashima et al. (2021) highlighted that the implementation of advanced manufacturing technologies, including robotic automation, could reduce resource consumption, waste production and energy usage. Technological advancements that enhance supply chain transparency and traceability, such as blockchain technology and Internet of Things devices, enable businesses to monitor and control environmental performance across their supply networks. Consequently, businesses can identify opportunities for waste reduction, sustainable sourcing and efficiency improvements by tracking the origin, production process and transit of items to ensure compliance with environmental standards and to promote business performance (Kharche et al., 2024). More specifically, this study draws insights from the input-process-output resource perspective of the RBV (Brandon-Jones et al., 2014; Lado et al., 1992; Umar et al., 2016; Yan et al., 2021), where GSCM practices (Yan et al., 2021) and GTIs (Umar et al., 2016) are considered valuable inputs that transform resources to enhance performance and expand the theoretical lenses of the RBV.

Third, this study uses institutional theory (Thakur-Wernz and Bosse, 2023) to argue that institutional pressures – normative, coercive and mimetic – can compel companies to adopt GSCM practices and GTIs to enhance firm performance. While environmental policy mechanisms are recognised as significant catalysts for firms’ innovation performance, the precise nature and timing of this relationship remain unclear (Lapologang and Zhao, 2023). Consistent with previous research, this study finds that institutional pressure moderates the relationship between GSCM practices and firm performance through GTIs. For example, Foo et al. (2019) emphasised that the implementation of green purchasing is influenced by institutional pressure. Environmental regulations and standards imposed by government agencies or industry bodies frequently exemplify institutional pressure. The adoption of green supply chain techniques such as sustainable sourcing or eco-friendly production methods may be required to comply with environmental regulations and standards by adopting new technologies that enable firms to effectively meet these requirements. Accordingly, Xu et al. (2023) demonstrated that institutional pressure – coercive, mimetic and normative – drives a firm’s green innovation behaviour. The application of institutional pressure to moderate the indirect relationship between GSCM practices and firm performance through GTIs, as suggested by Thakur-Wernz and Bosse (2023), can help elucidate green innovation and the push for sustainability in contemporary contexts. This is further supported by Adomako and Tran (2022), who find that high levels of stakeholder pressure drive environmental collaboration and innovation.

Fourth, it can be empirically argued that this study offers a perspective on GSCM practices from the perspective of a developing economy. The literature indicates that developing economies are characterised by significant institutional weaknesses (Agyapong et al., 2023; Amoako-Gyampah et al., 2020), which complicates the acquisition and replication of resources and capabilities for resource-constrained small and medium-sized enterprises (SMEs). Furthermore, firms in developing economies are posited to operate within underserved local markets; thus, those with advanced GSCM practices and GTIs are more likely to achieve superior firm performance (Umar et al., 2016; Yan et al., 2021). Consequently, this study extends the previous application of the RBV in green supply chain research by using input-transformation-output resource logic (Lado et al., 1992) to address the question of how GSCM practices should be sequenced to enhance firm performance in developing economies. From this perspective, the research underscores and illustrates that the effectiveness of GSCM practices in contributing to firm performance is contingent on the extent to which they stimulate GTIs (Lado et al., 1992; Umar et al., 2016). Therefore, this study integrates RBV and institutional theory to elucidate how varying conditions of institutional pressure account for the extent to which GSCM practices mediated by GTIs enhance firm performance. This study underscores the significance of GSCM and GTIs for firms in emerging markets, which is crucial for developing countries that encounter similar environmental and regulatory challenges. These findings offer valuable insights for businesses that operate under resource constraints or institutional voids. Researchers examining GSCM in the context of developing economies may find the results beneficial for comparative studies in other African or South Asian countries

This study offers several managerial and practical insights. Managers of SMEs in developing countries might find the findings particularly beneficial. First, this study indicates that SMEs in developing nations with characteristics similar to Ghana can enhance their operations. This provides decision-makers with valuable information on the economic feasibility of adopting GSCM practices and GTIs, especially in resource-constrained economies. Practical insights into GTIs as mediators in boosting firm performance will be advantageous for managers and policymakers striving to meet both environmental and operational objectives. Furthermore, a focus on institutional pressures can guide firms in various regulatory settings on how to anticipate or react to external demands. This study provides significant insight to managers and decision-makers regarding the mechanism through which GSCM impacts firm performance. Managers need to be aware that, although developing countries face cost challenges in the adoption of GTIs (Shahadat et al., 2023), they pay off, particularly as an intervening factor between green supply chain management and firm performance. Currently, several ICT tools and GTIs have a significant impact on environmental performance. For instance, computer-aided monitoring, control and optimisation tools, such as solar, wind and hydropower technologies, promote more efficient and dependable renewable energy use. In Ghana, the use of drones to distribute emergency drugs to remote health facilities has substantially reduced transportation costs and health risks. Yadav and Sidana (2023) highlighted that smart farming uses sensors, GPS and data analytics to ensure effective water, fertiliser and pesticide utilisation. This method reduces the negative effects of unsustainable agricultural practices on the environment and increases productivity. Managers, decision-makers and governments in developing economies can tap into GTIs to ensure the effective management of solid waste using machine learning which drives automated sorting, route optimisation, predictive maintenance, real-time monitoring and focused public education to address waste management cankers in developing economies (Chien et al., 2023; Munir et al., 2023).

While this study offers substantial insights into the mechanisms by which green supply chain management influences firm performance, its scope is confined to firms within Ghana, a developing economy in sub-Saharan Africa. Future research should examine data from multiple developing countries to facilitate more comprehensive comparative analysis. This would enhance the generalisability of the findings regarding the impact of GTIs and institutional pressure on the relationship between green supply chain management and firm performance, particularly in the context of developing economies. In addition, this study uses a quantitative methodology that does not elucidate the nuanced role of institutional pressure and GTIs in the nexus between green supply chain management and firm performance. Future research could consider a mixed-methods approach to further explore how institutional pressure and GTIs influence the study’s model. The study’s limitations include those inherent to cross-sectional surveys, reliance on single respondents and a single-country context. A cross-sectional design may constrain the ability to infer causal relationships, as the empirical data reflect conditions at a specific point in time. Consequently, it is suggested that future studies adopt a longitudinal data collection approach that captures information over time and facilitates trend analysis to assess the consistency of the findings. The use of a single respondent per organisation for both independent and dependent variables introduces the potential for common method variance. Although this potential weakness was addressed both precautionarily and statistically, it is recommended that future studies use alternative data collection techniques, such as phased data collection, using different respondents for predictor and outcome variables, as well as observation and simulation methods. Finally, future research should conceptualise institutional pressure as a multidimensional construct to elucidate how its components (coercive, mimetic and normative) individually and collectively affect the study’s model. Nevertheless, these limitations did not invalidate the findings of this study.