INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)  
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
The Impact of Total Quality Management on Green Performance:  
The Mediating Role of Green Innovation  
1 Dorsaf Chaher*, 2 Lassaad Lakhal  
1 Doctor, University of Sousse, Faculty of Economics and Management, Tunisia  
2 Professor, University of Sousse, Faculty of Economics and Management, Tunisia  
*Corresponding Authors  
DOI: https://dx.doi.org/10.51244/IJRSI.2025.12110036  
Received: 21 November 2025; Accepted: 28 November 2025; Published: 04 November 2025  
ABSTRACT  
The current environment is characterized by complexity and uncertainty, requiring companies to develop new  
strategic choices and management approaches to remain competitive and fulfill their responsibilities to all  
stakeholders. Today, customers, investors, and stakeholders are increasingly demanding greater transparency  
and responsibility from companies, particularly regarding their green practices. Total Quality Management  
(TQM) and Green Innovation (GI) are considered strategic orientations for adapting to environmental changes  
and achieving green performance (GP). However, there is a gap in the literature regarding the study of the  
relationships among these three concepts in a single analysis. To address this gap, we proposed a conceptual  
model and formulated research hypotheses. The aim of this research is to analyze the relationships between  
TQM, GI, and GP in the context of an emerging country, namely Tunisia. More specifically, this study highlights  
the mediating effect of GI between TQM and GP. A questionnaire was administered to top managers of 105  
certified manufacturing companies in Tunisia. The data were analyzed using structural equation modeling (SEM)  
with the PLS approach to examine the effects of TQM on GI and GP. The results demonstrate that TQM  
positively affects both GI and GP. Additionally, GI positively influences GP. Furthermore, the findings indicate  
that GI partially mediates the relationship between TQM and GP. This study provides valuable guidance to  
practitioners on improving green performance by integrating TQM practices and green innovation into their  
business operations. It encourages managers to understand the potential connection between TQM and green  
innovation and to leverage this relationship as a catalyst for achieving sustainable performance and gaining a  
competitive advantage.  
Keywords: Total quality management (TQM), green innovation (GI), Green performance (GP).  
INTRODUCTION  
Manufacturing companies remain a key factor contributing to environmental problems such as natural resource  
depletion, climate change, and pollution (Aftab et al., 2023). Recently, the scope of Total Quality Management  
(TQM) has been broadened to include dimensions beyond the organization's internal structure, such as the  
incorporation of social responsibility and environmental policies (Tasleem et al., 2019). It is a management  
system that focuses on continuous improvement, aiming to use resources effectively, reduce costs, and optimize  
human effort (Abbes, 2019). The relationships between TQM practices and green performance (GP) have been  
studied by many researchers within distinctive contexts, leading to mixed results, calling for more research  
studies (Akanmu et al., 2023). However, Albloushi et al. (2023) suggest the existence of a positive link between  
TQM and CSP. On the other hand, Makhlouf et al. (2023) report that there is a negative relationship between  
TQM and GP. Green innovation is considered a mechanism to lead firms’ success in the long term (Aftab et al.,  
2023). Green innovation is considered a key factor that can help companies introduce environmentally friendly  
processes, technologies, products, and methods into production operations in order to protect the natural  
environment (Chang, 2011). This approach is essential for meeting sustainable development challenges and is  
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ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue XI November 2025  
often considered a key driver of business performance (Le, 2022; Albloushi et al., 2023). The studies that  
examined the link between GI and GP reveal a controversial relationship with mixed and inconclusive results  
(Chang, 2011; Przychodzen et al., 2018; Padilla-Lozano & Collazzo, 2022). The literature addressing the  
relationship between TQM and GP reveals significant gaps in specifying the causal links among these variables,  
particularly in developing countries (Abbas, 2020). Consequently, it is essential to examine the interrelationship  
between TQM, GI, and GP within a unified analytical framework.  
Therefore, the current study aims to answer the following research questions:  
1. What is the effect of TQM practices on GP?  
2. Does GI mediate the relationship between TQM and GP?  
This paper is organized into six sections. The second section presents the literature review and develops the  
hypotheses. The research methodology is outlined in the third section. The fourth and fifth sections present and  
discuss the results. Finally, the conclusion, implications, and limitations are presented in the last section.  
THEORETICAL FRAMEWORK AND DEVELOPMENT OF RESEARCH HYPOTHESES  
TQM and green performance  
TQM is a relevant factor that enables companies to achieve their green performance goals (Abbes, 2020). It is  
a management system that focuses on continuous improvement, aiming to use resources effectively, reduce costs,  
and optimize human effort. According to Shafiq et al. (2019), TQM is a tool that can help companies improve  
the quality of their products and services, reduce defect rates, and enhance customer satisfaction. Zhang et al.  
(2020) stated that the successful implementation of TQM has the potential to achieve performance across the  
three pillars of the triple bottom line (TBL) economic, social, and environmental. According to Qasrawi et al.  
(2017), integrating corporate sustainability (CS)with quality management can significantly enhance firms’  
performance in all TBL pillars. Abbas (2020) investigated the relationship between TQM in the Pakistani  
manufacturing and service sectors. The results revealed a positive relationship between TQM and corporate  
sustainability. Hassis et al. (2023) reported that TQM has a significant impact on CS in the Palestinian context  
using a sequential mixed-method research technique. In contrast, the study by Makhlouf et al. (2023) showed a  
negative relationship between TQM and CS in the Chinese industry. Aquilani et al. (2016) reported that TQM  
practices help organizations achieve sustainable development (SD).  
Thus, we propose the following hypothesis:  
H1. TQM positively influences GP.  
TQM and green innovation  
TQM has been considered a key driver of green innovation (Abbas, 2020). However, the assessment of the  
relationship between the two has been inconclusive (Prajogo and Sohal, 2001; Castillo-Rojas et al., 2012;  
Manders et al., 2016). The philosophy of continuous improvement advocated by quality management may hinder  
firms from pursuing radical green innovations Steiber and Alange (2013). Zeng et al. (2017) argued that the  
adoption of TQM practices creates a conducive environment for companies to innovate, serving as a significant  
catalyst for green innovation. In contrast, the study by Li et al. (2018) showed a negative relationship between  
TQM and green innovation in the Chinese industry. Results from the study of Albloushi et al. (2023) showed  
that TQM significantly enhances firms’ capabilities to innovate in the UAE industry. Azam et al. (2023)  
described green theory as providing a theoretical basis for clarifying the relationship between TQM and GI and  
reported that TQM practices positively impacted two aspects of GI, namely green product innovation and green  
process innovation, in Pakistani manufacturing firms.  
Hence, we propose the following hypothesis:  
H2. TQM positively influences GI  
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Green innovation and green performance  
Green innovation is a powerful lever for achieving green performance(Hur et al., 2013). GI is one of the tools  
that involves creating environmentally friendly products, processes, and management practices in order to  
achieve long-term sustainability (Xie et al., 2019; Li et al., 2017). GI encompasses various areas, such as  
reducing resource usage and minimizing waste and pollution (Rossiter and Smith, 2018). The study by Abbas  
and Sagsan (2019),which focused on a sample of industrial companies in Pakistan, confirmed a positive  
relationship between green innovation and corporate sustainability. Asadi et al. (2020) conducted an empirical  
investigation based on a questionnaire administered to 183 Malaysian companies, and the findings showed that  
GI significantly improves green performance. Azam et al.(2023) investigated how GI affects GP in the Pakistani  
manufacturing sector. The authors reported that GI, including green product innovation and green process  
innovation, positively impacts GP. Therefore, we hypothesize that,  
H3. Green innovation positively influences corporate sustainability  
The indirect effects of TQM on green performance  
The relationship between TQM and green performance (GP) has been extensively studied in the literature by  
several researchers, yet no consensus has emerged regarding the link between the two constructs (Alboushi et  
al., 2023 ; Makhlouf et al., 2023). As a result, some researchers have recommended that mediating variables  
may be essential for understanding the relationship between TQM and corporate sustainability performance  
(CSP). Thus, it is relevant to examine the mediating effect of green innovation (GI) in this relationship. Azam  
et al. (2023) argued that companies can increase their GI by implementing TQM. The study by Albloushi et al.  
(2023) in the UAE context showed that GI partially mediates the relationship between TQM and GP. This  
indicates that the efficient implementation of TQM practices can significantly enhance an organization's GI  
activities, which in turn positively impacts corporate sustainability. Therefore, we hypothesize that.  
H.4 TQM positively influences GP through GI.  
GI  
direct effect  
H2  
H3  
indirect effect  
H4  
GP  
TQM  
H1  
Figure 1. A conceptual model on the relationship between TQM, GI and GP  
RESEARCH METHODOLOGY  
Sample and Data collection  
The study sample in the current research consists of certified manufacturing industries in Tunisia. We selected  
the list of the target population from the Tunisian Industry Portal. Data were collected using a survey  
questionnaire covering TQM, GI, and GP. We contacted and then sent a questionnaire to 345 certified  
manufacturing companies. The questionnaire was administered by email to top management. We received 121  
questionnaires; however, only 105 were retained due to missing and/or doubtful responses. Table 1 summarizes  
the respondents’ and industries’ profiles.  
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Table 1. Demographics results  
Descriptions  
Characteristics  
of <50  
50-199  
Values  
Percentage %  
13.3  
Number  
employees  
14  
25  
46  
20  
7
23.8  
43.8  
19.1  
6.7  
200-500  
More than 500  
Female  
Gender  
Age  
Male  
98  
8
93.3  
7.6  
20-29  
30-39  
41  
42  
14  
12  
33  
19  
41  
39  
40-49  
40  
More than 50  
Less than 3 years  
3 to 5years  
6 to 10 years  
More than 10 years  
13.3  
11.4  
31.4  
18.1  
39.1  
Job experience  
Ethical Consideration  
During the research,ethical standards were strictly followed.To ensure confidentiality, participants were  
informed that all responses they provided would remain strictly confidential and be used exclusively for  
academic purposes. They were also informed that their participation was voluntary and that they could withdraw  
from the study at any time without any negative consequence. Furtheremore, no data that could personally  
identify the participants was collected.  
Variable measurement  
In this study, six TQM practices were considered: leadership, strategic planning, customer focus, human resource  
management, process management, and information and analysis, as these are the most widely cited in the  
literature (chaher et Lakhal,2024 ; Abbes, 2021). To measure the TQM dimensions, we used the scales developed  
by Abbas and Kumari (2021) and Chaher and Lakhal (2024). Strategic planning, customer focus, human resource  
management, process management, and information and analysis were each measured using five items, while  
leadership was measured using four items. Green performance was assessed using five items adapted from Yu  
et al. (2017), Roscoe et al. (2019), and Singh et al. (2020). The green innovation dimension—namely green  
product innovation and green process innovation—was measured using four items each, based on the scale  
developed by Chen et al. (2006).  
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RESULTS  
The collected data were analyzed using partial least squares structural equation modeling (PLS-SEM).  
Assessment of the the measurement model  
In accordance with Hair et al. (2019), measurement model reliability was assessed using Cronbach’s alpha and  
composite reliability (CR). Table 1 confirms that all values exceed the recommended threshold of 0.7 (Hair et  
al., 2018). Furthermore, validity was established through the examination of factor loadings, convergent validity,  
and discriminant validity. Table 1 demonstrates that all factor loadings exceed the 0.7 cutoff suggested by Hair  
et al. (2018), confirming that each item has a strong correlation with its corresponding construct.  
Average Variance Extracted (AVE) was used to evaluate convergent validity. The findings reveal that all AVE  
values exceed the threshold of 0.5, as suggested by Fornell and Larcker (1981), confirming convergent validity.  
Table 2. Reliability and convergent validity analysis  
Cronbach’s  
Composite  
Reliability  
Factor  
Loading  
Constructs  
No. of items  
AVE  
Alpha  
LD1  
0.842  
LD 2  
LD3  
LD5  
IA1  
0.895  
0.910  
0.873  
0.764  
0.853  
0.829  
0.844  
0.867  
0.776  
0.771  
0.732  
0.895  
0.873  
0.814  
0.791  
0.861  
0.932  
Leadership  
0.903  
0.888  
0.775  
IA2  
0.918  
Information and  
analysis  
IA3  
0.693  
IA4  
IA5  
PS1  
PS2  
PS3  
PS4  
PS5  
PM1  
PM2  
PM3  
Policy and strategy  
0.849  
0.878  
0.894  
0.911  
0.630  
0.672  
Process  
management  
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PM4  
PM5  
0.823  
0.809  
HRM1  
HRM2  
HRM3  
HRM4  
HRM5  
CS1  
0.808  
0.865  
0.712  
0.845  
0.797  
0.855  
0.793  
0.870  
0.832  
0.893  
0.876  
0.914  
0.887  
0.876  
0.773  
0.788  
0817  
Human resource  
management  
0.865  
0.903  
0.651  
0.702  
0.773  
CS2  
Customer focus  
0.859  
0.902  
0.870  
0.904  
0.932  
0.906  
CS3  
CS4  
GPI1  
GPI2  
GPI3  
GPI4  
GP1  
Green product  
innovation  
GP2  
GP3  
Green performance  
0.659  
GP4  
GP5  
0.802  
0.768  
0.829  
0.786  
0.820  
GPRI1  
GPRI2  
GPRI3  
GPRI4  
Green Process  
Innovation  
0.814  
0.872  
0.642  
The Fornell and Larcker criterion and the HTMT ratio are generally used to evaluate discriminant validity (Hair  
et al., 2014). According to Fornell and Larcker (1981), to establish discriminant validity, the square root of the  
AVE of each construct should be greater than its correlation with any other construct in the model ;According  
to Hair et al. (2019), the HTMT ratio should be below the threshold of 0.90 to confirm discriminant validity.  
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Tableau 3. Fornelle-Larcker criterion analysis  
CS  
GP  
GPI  
GPRI LD  
MP  
IA  
PS  
RH  
0,838  
0,214  
0,238  
0,316  
0,180  
0,207  
0,210  
0,289  
0,195  
CS  
0,812  
0,329  
0,552  
0,414  
0,504  
0,509  
0,461  
0,532  
GP  
0,879  
0,329  
0,230  
0,270  
0,180  
0,195  
0,257  
GPI  
GPRI  
LD  
0,801  
0,404  
0,448  
0,414  
0,406  
0,455  
0,880  
0,670  
0,490  
0,602  
0,606  
0,820  
0,729  
0,648  
0,733  
MP  
IA  
0,832  
0,602  
0,705  
0,794  
0,647  
PS  
0,807  
HRM  
Notes : LD : Leadership; CS : Customer Focus; GPI : Green Product Innovation; GPRI : Green Process  
Innovation; MP : Process Management;  
PS : Politics and Strategy; IA : Information and Analysis; HRM : Human Resources Management; GP : Green  
Performance  
Tableau 4. HTMT Ratio  
CS  
GP  
GPI  
GPRI  
LDSH  
MP  
IA  
PS  
HRM  
CS  
0,242  
GP  
0,382  
0,199  
0,234  
0,238  
0,329  
0,224  
0,651  
0,368  
0,252  
0,302  
0,202  
0,224  
0,285  
GPRI  
LDSH  
MP  
0,462  
0,578  
0,577  
0,533  
0,605  
0,471  
0,534  
0,493  
0,492  
0,542  
0,749  
0,546  
0,682  
0,668  
0,826  
IA  
0,743 0,687  
0,826 0,793 0,743  
PS  
HRM  
Structurel Model  
The coefficient of determination (R²) and the cross-validated redundancy (Q²) were checked to evaluate the path  
model's predictive accuracy. Chin et al. (1998) suggested that an the R² values of 0.26, 0.13, and 0.02 indicate  
substantial, moderate, and weak relevance , respectively. According to Hair et al. (2014), a Q² value greater than  
0is considered satisfactory. The data in Table 5 indicate that TQM and GI together are responsible for 42% of  
the variation in GP.  
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Table 5. Coefficient of determination (R²)  
R Square  
0. 341  
R Square Adjusted  
Résults  
0.334  
0.409  
substantial  
substantial  
GI  
0.420  
GP  
Table 4 show that Q2 Values for all endogenous construct exceeding zero indicating that the path model meets  
predictive relevance.  
Table 6. Cross-validated redundancy(Q²)  
Variables endogènes  
Q2  
Résultat  
GI  
0,103  
0,270  
Significatif  
Significatif  
GP  
In the end, a bootstrapping procedure was conducted to test the direct and indirect relationships between TQM,  
GI, and GP. The results reveal a positive and significant relationship between TQM and GP (β = 0.413; T =  
4.433; p < 0.001), confirming Hypothesis 1. Additionally, a positive relationship was found between TQM and  
GI (β = 0.491; T = 7.958; p < 0.001), supporting Hypothesis 2. The results also indicate a positive and significant  
relationship between GI and GP (β = 0.336; T = 3.662; p < 0.01), confirming Hypothesis 3. Finally, regarding  
the mediation hypothesis, the results show that TQM has an indirect effect on GP through the mediating role of  
GI (β = 0.165; T = 2.905; p < 0.01).  
Table 7. Hypothesis testing.  
Standar  
Sampl  
e
Mean  
(M) (STDEV  
)
d
Deviatio  
n
Original  
Sample  
(O)  
T Statistics  
(|O/STDEV  
|)  
Hypothesi  
s
P
Hypothesi  
Constructs  
Values s Decision  
Direct effect H1  
TQM  
GP  
Accepted  
0,413  
0,491  
0,336  
0,093  
4 .433  
7.958  
0,000  
0,403  
H2  
H3  
TQM  
GI  
GI  
GP  
Accepted  
0,500 0,062  
0,352 0,092  
0,000  
Accepted  
0,002  
3.662  
2.905  
Mediation  
H4  
TQM  
GI  
GP  
Partial  
0,004  
0,165  
0,178 0,057  
Mediation  
DISCUSSION  
The aim of this study is to analyze the effect of TQM on GP through the mediating role of GI. The results show  
that TQM has a positive relationship with GP. This finding is consistent with the study of Abbas (2020) which  
confirmed that the implementation of TQM practices promotes green performance. Furthermore, the results  
indicate a positive relationship between TQM and GI. This finding aligns with the study of Nazarian et al. (2025),  
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which demonstrated that TQM is a pivotal factor in enhancing green innovation in Pakistani manufacturing  
companies. However, this result contradicts the findings of Li (2018), who reported that TQM has no significant  
effect on GI.TQM is based on a set of principles, including continuous improvement, customer focus, employee  
involvement, and leadership, which can enhance a company’s capacity to foster a culture oriented toward green  
innovation (GI) and corporate sustainability. The results also show that GI has a positive effect on GP. This  
finding is consistent with the study by Hussain et al. (2022) , which suggests that GI can promote environmental,  
social, and economic sustainability in manufacturing companies in the UAE. Finally, the results of this empirical  
study illustrate that TQM has an indirect effect on GP through the mediating role of GI. The introduction of GI  
as a mediating variable strengthens the impact of TQM on GP. These results are consistent with the findings of  
Albloushi et al.(2023) in the UAE context, which showed that GI partially mediates the relationship between  
TQM and GP. Overall, the findings of the current study indicate that adopting TQM practices enables companies  
to promote green innovation, which, in turn, contributes to achieving green performance.  
CONCLUSION  
The main aim of this study is to analyze the relationship between TQM GI and GP in developing country context.  
The findings showed that TQM positively associate with GI and GP. Additionally, the study shows that GI  
positively influences GP. Furthermore, the results indicate that GI partially mediates the association between  
TQM and GP  
Theoretical contribution  
This study contributes to the current literature in several ways. First, this study provides a conceptual model to  
examine the relationship between TQM, GI and GP, by explaining the path of this relationship. Second, the  
conceptual model highlights the mediating effect of GI between TQM and GP  
Managerial contribution  
This research provides managerial contributions. It encourages managers to understand the potential connection  
between TQM and green innovation and to leverage this relationship as a catalyst for enhancing the GI of their  
companies. The study highlights the importance of TQM in promoting green innovation and corporate  
sustainability. Businesses are encouraged to adopt a comprehensive set of TQM practices—such as continuous  
improvement, top management commitment, employee involvement, and evidence-based decision-making—to  
foster a culture that supports green innovation and achieves long-term sustainability goals. Furthermore, this  
research emphasizes the significant role of green innovation in enhancing green performance . Managers are  
encouraged to actively integrate green innovation into operational activities, such as the use of eco-efficient  
technologies, green materials innovation, waste-reduction practices, and energy-efficient processes. By  
incorporating these green practices into daily operations, managers can strengthen their organizations’ social,  
economic, and environmental sustainability. Finally, the study urges managers to consider TQM and GI as  
strategic investments that contribute to sustainable development and provide a competitive advantage  
Limitations and Future Perspectives  
This study has certaines limitations. First, the sample size was relatively small (105 companies). Future research  
could test this model on a larger sample to enhance the generalizability of the results. Second, a cross-sectional  
design was employed. Future studies are encouraged to adopt a longitudinal approach to more accurately  
examine the causal relationships between total quality management , green innovation , and green performance  
over time. Finally, although this study focused on certified manufacturing companies located in Tunisia, future  
research could explore other industries or regions to assess whether the findings hold across different contexts.  
Additionally, other potential mediators, such as green entrepreneurial orientation or green knowledge  
management, could be investigated in the relationship between TQM and GP.  
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