Green logistics performance and infrastructure on service trade and environment-Measuring firm’s performance and service quality

2.1 Theoretical background and hypothesis development

In this study we employed two main theories “Logistic theory” and “New trade theory” to investigate the impact of logistic performance and infrastructure on Service Trade and Environment through the mediating role of service quality and firm’s performance. (Please see Fig. 1 for study model)

2.2 Green logistic performance and service trade and environment

Green logistic service providing in an international setting has evolved into a critical component of the organization (Cullinane and Wang, 2006). It has also become a primary concern in foreign trade, particularly in ongoing growth of economies (Akbari and Ha, 2020). The success of green logistic activities is reflected through an economic performance of a country. International trade poses a challenge to logistic activities in terms of transporting and storing goods. High logistic cost and poor service quality may be regarded as impediments to international trade (Martí et al., 2017). The empirical literature has revealed the association among green logistic performance and service trade & environment, based on this we presented our hypothesis as follows:

H1: Green logistic performance has a positive effect on Service trade and environment.

2.3 Infrastructure and service trade and environment

Infrastructure encompasses networking of transportation for import and export of goods, telecommunication network system required to accelerate the exchanges information, an appropriate system for handling import duties and many other services. Infrastructure of bold quality can help to increase communication among supply chain participants (Maqsoom et al., 2021a; Nawaz et al., 2021). While the investments in infrastructure are linked to increased exports and development of companies (Portugal-Perez et al., 2010). Innovative infrastructure such as efficient information technologies reduce transportation and trading costs and motivate the international trading system (Bojnec and Fertö, 2009). Hence, it has been found that variations in state of infrastructure have a greater influence on export performance than conventional trade in terms of environmental effects barriers (Arvis et al., 2007).

H2: Infrastructure has a positive effect on service trade and environment.

2.4 Green logistic performance and firm performance

Green logistics is a cost-effective activity that is often a necessity for economic development and cross-border trade. Logistic performance structure represents a firm’s performance in terms of its capacity to deliver products and services in accurate amount and at precisely timed intervals as demanded by consumers (Yang et al., 2018). Green logistic services of a company such as web-based ICT and efficient procedures provide competitive advantages to firms and increase its performance (Garrido Campos and Hardwick, 2006). According to Martí et al. (2017) growth in the logistic industry is predicted to have a beneficial influence on expanding output, trade and consumption, promoting economic growth. Wong et al. (2018) has revealed that in the green logistic sector, efficient supply chain management positively influences firm performance because such a supply chain resulted in better economic performance of organizations, enhancing profitability and market share, which ultimately influences the firm’s financial performance environmental sustainability. This shows that logistic prices significantly influence firm’s performance based on above discussion we presented our hypothesis as follows:

H3: Green logistic performance has a positive effect on firm’s performance.

2.5 Green logistic performance and service quality

The empirical findings reveals that in logistic sector improving transportation conditions, ICT development has substantial impact on economic growth (Martí et al., 2017). Previous studies (Jacobsson et al., 2020; Soh et al., 2021; Wong and Tang, 2018) has investigated that there are several factors which may affect the green logistic performance such as innovative logistic networks, cost associated, institutional service quality, supply chain integration, logistic operations, and financial performance. Dang & Yeo, (2018) noted that green logistic cost in Vietnam are higher than other developing countries and limiting its ability to compete in international supply chain. According to Garza-Reyes et al. (2016) growth in logistic industry is predicted to have a beneficial influence on expanding output, trade and consumption resulting in promoting economic growth. This illustrates that service quality has a significant positive impact on green logistics performance, based on above discussion we presented our hypothesis as follows:

H4: Green logistic performance has a positive effect on service quality.

2.6 Infrastructure and firm performance

The economy of a country is influenced by the quality of its infrastructure (Yeo et al., 2020). In essence, high quality infrastructure would allow the logistics sector to plan, control and store products, services and information related from purchasing raw material to manufacturing finished products in order to satisfy consumer’s demand (Rezaei et al., 2018). Infrastructure is a crucial aspect in transportation and domestic and international trade (Groh and Wich, 2012). The improved service quality and infrastructure has a significant impact on firm financial performance (Arvis et al., 2018). According to Garza-Reyes et al. (2016) growth in logistic industry is predicted to have a beneficial influence on expanding output, trade and consumption resulting in promoting economic growth. S. A. R. Khan et al. (2019) has revealed that in logistic sector efficient supply chain management positively influence firm performance because such type of supply chain resulted in better economic performance of organizations, enhance profitability and market share which ultimately influence firm’s financial performance. While Djankov et al. (2006) found that information sharing system in infrastructure leads to improvement in country’s green logistic performance. Based on above discussion on literature we proposed our hypothesis as follows:

H5: Infrastructure has a positive effect on firm’s performance.

2.7 Infrastructure and service quality

Infrastructure is the foundation of global economy and an essential component of all economic activities. Its involvement towards economic growth is essential for the well-being of citizens as well as for the country’s wealth (Szreter, 1997). Chen et al., (2019) has reported that advancement in infrastructure can save time and decrease information cost expedite the fellow of capabilities and technical components, encourage capital investments, and lessen negative impacts of trade expenses. Ladhari (2009) regarded service quality as a primary concern of businesses because it provides competitive edge in market, helps to maintain growth and boost efficiency of companies. The improved service quality and infrastructure has a significant impact on international service trade and environment (Shepherd and Wilson, 2009). Moreover, better infrastructure and service quality leads to reduction in cost, enhance satisfaction of customers which ultimately increase financial performance of a company (Derar Shaker Yaghi, 2010). Based on above liretarure we presented our hypothesis as follows:

H6: Infrastructure has a positive effect on service quality.

2.8 Firm performance and service trade & environment

In the green logistic sector, firm financial performance for supply chain operations focuses on cost savings, gaining market share, and profit growth. Chien & Shih (2007) has revealed that efficient supply chain management positively influences firm performance because such a supply chain resulted in better economic performance of organizations, enhancing profitability and market share, which ultimately influences the firm’s financial performance. Effective firm performance has evolved into a critical component in export competitiveness (Yang et al., 2018). The improved service quality and infrastructure significantly impact firm financial performance (Shepherd and Wilson, 2009). According to Garza-Reyes et al. (2016) growth in the logistic industry is predicted to have a beneficial influence on expanding output, trade and consumption resulting in promoting economic growth. Wong et al. (2018) has revealed that in the logistic sector, efficient supply chain management positively influences firm performance because such a supply chain resulted in better economic performance of organizations, enhancing profitability and market share, which ultimately influences the firm’s financial performance. On the basis of above discussion we proposed our hypothesis as follows:

H7: Firm performance has positive effect on service trade and Environment.

2.9 Service quality and service trade & environment

Service quality has a significant positive influence on firm’s performance. Researchers have documented that service quality helps lower cost and enhance customer satisfaction, leading to customer loyalty and increased company financial performance (Bontis et al., 2007; Derar Shaker Yaghi, 2010). Innovative infrastructure such as efficient information technologies reduce transportation and trading costs and motivate the international trading system (Bojnec and Fertö, 2009). In case of shipment quality standards usually quantify as on time delivery of goods, reliability, risk associated with shipment and frequency (Arvis et al., 2018). Better service quality leads to reduction in cost, enhances satisfaction of customers, and ultimately increases the company's financial performance (Derar Shaker Yaghi, 2010).

H8: Service quality has positive effect on service trade and environment.

2.10 Mediating role of firm performance

The literature has well documented that firm performance significantly impacts green logistic and trade services (Fernando et al., 2019; Khan et al., 2019; Rezaei et al., 2018; Richey et al., 2005; Wong et al., 2018). Effective firm performance has evolved into a critical component in export competitiveness (Garza-Reyes et al., 2016). According to Rezaei et al. (2018) growth in logistic industry is predicted to have a beneficial influence on expanding output, trade and consumption resulting in promoting economic growth. Effective firm performance has evolved into a critical component in export competitiveness. Fernando et al. (2019) has revealed that in the green logistic sector, efficient supply chain management positively influences firm performance because such a supply chain resulted in better economic performance of organizations, enhancing profitability and market share, which ultimately influences the firm’s financial performance. Prior studies have documented that firm performance efficiently mediate the relationship between infrastructure and service trade and environment (Mas-Verdu et al., 2010; Memedovic et al., 2008; Pechlaner et al., 2021).

H9: Firm’s performance mediates the relationship between green logistic performance and service trade and environment.

H10: Firm’s performance mediates the relationship between Infrastructure and service trade and environment.

2.11 Mediating role of service quality

The logistic sector performance influence positively the efficiency of international trade whereas a weak logistic industry with low quality infrastructure and transportation can stifle worldwide economies (Arvis et al., 2007). The investments in logistic sectors and its efficient performance significantly influence international trade flow (Hidalgo-Gallego et al., 2021). Moreover, information communication technologies in logistics helps to improve service quality and overall firm’s performance (Ul-Hameed et al., 2019). Better green logistics performance leads to reduction in trading cost, eliminate inefficiencies related to traditional shipping and handling business strategies (Miroudot et al., 2009). In overall better green logistic services quality can help companies fulfill customer demands and resolve disputes and consumer complaints (Richey et al., 2005). This reveals that service quality effectively mediate the relationship between green logistic performance and service trade & environment.

This shows that improved service quality and infrastructure significantly impact international service trade & environment (Shepherd and Wilson, 2009). Based on above mentioned literature we proposed our hypothesis as follows:

H11: Service quality mediates the relationship between green logistic performance and service trade & environment.

H12: Service quality mediates the relationship between Infrastructure and service trade & environment

Based upon the literature review, this research was designed and the following conceptual framework was developed. The research revolves around this.

3.1 Measurement development

There is not much literature about these constructs based on measurement and scales used to measure the causal linkage via survey technique. In Previous studies, it has been mentioned that future research should consider the managerial staff and top management experts therefore, this study considered economist, financial analysis and managerial staff of accountancy and research and development firms in China. The measurement scale for both exogenous constructs (Green logistic performance and infrastructure) and endogenous (Service trade and environment) construct are newly proposed and confirmed on the basis of reliability and validity analysis in Smart-PLS 3.3.3. The idea of these constructs was taken from the Yeo et al. (2020). We proposed five items scale for Infrastructure, six items scale for Green logistics performance and two items scale for Service trade and environment construct. Moreover, measurement scale for mediators are adapted from previous studies. Five items measurement scale for firm performance adapted from Haq et al. (2020) and three items scale for services quality from (Han et al., 2020; Pandey and Sahu, 2020). All these constructs are measure under 5 -point Likert scale from strongly agree (5) to strongly disagree (1).

4.1 Measurement model assessment

The first step of SEM analysis is assessment of the measurement model. The measurement of assessment involves the estimation of constructs and indicator’s reliability and validity that is usually measured through discriminant and convergent validity. The convergent validity is estimated through construct reliability (CR), Cronbach Alpha (α), factor loadings, and average variance extracted (AVE) (Haq and Awan, 2020). Afterward, the discriminant validity is estimated through two measures i.e., Fornell and Larcker ratio criterion and Heterotrait-Monotrait ratio for correlation. Table 2 illustrates the descriptive statistics of the data considering the mean and standard deviation.

All mean values are from 3.191 to 3.989 and standard deviations from 1.021 to 1.070 which shos the variations and interlinks of respondent’s perceptions. Other data in Table 2 illustrated the convergent validity of indicators in constructs. All the values of factor loadings are above the threshold point 0.70 (Avotra et al., 2021a; b) thus indicator reliability is fulfilled for all indicators in constructs. Talking about the reliability of constructs, it is measured through CR and α values. All coefficients are above 0.70 threshold point (Hair et al., 2017) and (Haq and Awan, 2020) thus the reliability condition is also met. AVE values are also above the threshold points 0.50 (Xialong et al., 2021).

The discriminant validity is usually measured through cross loadings, Fornell and Larcker ratio criterion and HTMT ration. This study considered Fornell and Larcker ratio and HTMT ration of correlation. The bold bigger diagonal values in Table 3 from their respective values demonstrate that the discriminant validity condition is fulfilled. It is because all the diagonal values are larger than that of their beneath values (Lia et al., 2020). Values above 0.85 to 0.90 show problem of multicollinearity in HTMT (Nawaz et al., 2021). Values in Table 4 are below the threshold point thus all the constructs and their indicators are distinct and can estimate respective constructs only.

4.2 Structural model assessment

The second step of SEM analysis technique is structural model assessment. The structural model assessment determines and support to estimate the linkage between the constructs. It usually captures the direct and indirect effects. Direct effects usually help to accept and reject the relationship between two constructs and indirect effects mainly accept and reject the mediation paths. To accept and reject the hypothesis structural model assessment author considered p-values, t-statistics, beta (β) values or original sample coefficients and R².

This study analyzes the direct and indirect effects of infrastructure and green logistics development on service trade and the environment. Overall, this research proposes 12 total hypotheses out that 8 are direct effects and the rest of 4 are indirect effects. The results for all direct and direct effects were illustrated in Table 5. The H1 was confirmed that green logistics performance meaningfully predict the services quality with $-statistic=8.641:p-value=0.000$ . The second hypothesis H2 also confirmed positive as Green logistics performance meaningfully predicts firm’s performance under $-statistic=7.077:p-value=0.000$ . In contrast, Green logistics performance does not positively predict the service trade and environment as there is no statistical significance $-statistic=1.091:p-value=0.308$ , thus H3 rejected. The second independent variable demonstrate a positive and significant relationship in all three direct effects with service quality, firm performance, services trade. H4, H5, and H6 were accepted under $-statistic=5.465:p-value=0.000$ , $t-statistic=6.978:p-value=0.000$ and $t-statistic=3.468:p-value=0.000$ respectively. Similarly, H5 and H6 were also accepted and confirmed a significant positive effect of services quality and firm’s performance on service trade and environment. Services quality and firms’ performance meaningfully predicts the service trade and environment constructs under $t-statistic=5.221:p-value=0.000$ and $t-statistic=5.805:p-value=0.000$ respectively.

The indirect effect or mediation hypothesis were also accepted. As H9 were accepted and illustrated a full mediation by firm performance as there was not a statistically significant direct relationship thus the positive significant indirect relationship $t-statistic=4.171:p-value=0.000$ confirmed that there is a full mediation by firm performance between green logistics performance and service trade & environment. Additionally, H11 was accepted and confirmed a positive partial mediating effect by firm performance between infrastructure and services trade as $-statistic=4.548:p-value=0.000$ . Moreover, service quality proved as a mediator between infrastructure & services trade and green logistics performance and service trade & environment. Thus, H12 and H14 were accepted, and partial mediation was approved as $t-statistic=4.543:p-value=0.000$ and $t-statistic=3.661:p-value=0.000$ respectively. Additionally, values (0.700 0.675, 0.766) of R² confirmed that independent variables meaningfully and statistically predict the dependent variable and (70%, 67.5%, 76.6%) changes in dependent variables are due to independent variables.