Introduction

Retailers play a key role in changing clients’ buying patterns. Most green supply chain management (GSCM) studies have concentrated on manufacturing enterprises. Systems analysis methods have advanced retailing and proven their usefulness. However, downstream distribution networks and retailers have been less frequently studied than other supply chain members. Green commerce studies focus on consumer interactions. South Carolina retailers are essential, but green and green retailing research is still in its infancy. Retail operations' impact on the community and the environment, which determines what products buyers buy, appears to have affected the conventional markers of a retailer's competitive advantage (pricing, quality, service, and store location). Retailers must assess their environmental effects due to supply chain constraints.

The Indian retail industry has become the world's most attractive and fast-paced due to new participants. It contributes 10% of GDP and 8% of employment. India came in at position 73 on the UNCTAD's 2019 B2C e-commerce index. According to the Global Business 2020 report from the World Bank, India has the fifth-largest retail market and ranks 63rd overall..

Merchants must own supply chain procedures. This accountability raises environmentally conscious practices among supply chains and improves their ecological efficiency and durability. Wiese (2012) provides an in-depth overview of sustainability in organized retailing, noting that while much study has concentrated on certain areas such as corporate social responsibility, corporate social responsibility, more cross-functional studies that take an integrated or holistic approach to GSCM represent future research potential. Due to perishability, refrigeration, and waste management, food preservation is a key area of retail sustainability. This paper answers the following research question:

RQ.What relationship exists between green in-store procedures, GSCM and outcomes in a well-functioning retail system?

This study contributes the following: It provides a link between retail operations-related components (green in-store processes) and environment-friendly supply chain processes, as well as environmental, economic, and social performance with overall organization performance implications. It also includes actual data from a well-organized retail store that has been little studied in the literature. As a direct consequence of this, there is a growing interest in, as well as respect for, the field of retail supply chain research in India.

The organization of this report is as follows: The examination of green in-store procedures, GSCM, and sustainable and ecological literature actions in organized retail is done in Section 2. This enables us to create an organized model in Section 3 and develop hypotheses for research. We then describe the scales utilized to quantify each structural model. Section 4 discusses the data acquired during the data collection, and the validation of the suggested model was accomplished using the PLS structural equation modeling approach. Section 5 compares the model's conclusions to existing state-of-the-art expertise in the area. Finally, Sections 6 and 7 summarize the major theoretical and managerial contributions, the research's limits, and exploration ideas.

Literature Review and Hypotheses Development

Green retailing studies customer views of environmental retailing and retail sustainability issues. Green consumer behavior performance. Retail research must also consider logistics and in-store operations. Youn et al. (2017) mention green retailing measures, and Erol et al. (2009) are among the pioneers in the field who proposed environmentally friendly practices for the retail industry.

Sustainability includes social performance, environmental performance, and economic performance. Sustainability research is mature. We prioritize environmental responsibility. Environmental supply chain management, according to Seuring (2004), ‘manages material and information flows along the supply chain to meet customer demand for green products and services created through green processes’.

Managers will make decisions to integrate and coordinate GSCM practices throughout the supply chain as they become aware of consumer demand for environmentally friendly services and products. Organizations and supply chains can benefit by adopting GSCM and environmental sustainability. Preuss (2002) emphasizes SCM's ‘cross-boundary’ aspect in applying environmental rules upstream and downstream in the supply chain.

In addition to the demands of consumers, environmental policy and legislation have been key drivers in the application of environmentally friendly practices. Environmental laws and business competitiveness are disputed. Jorgensen and Wilcoxen (1990) examine how pollution control costs affect US product and service prices. According to Jaffe et al. (1995), there is scant evidence that environmental regulations harm competitiveness. To determine the influence of environmental sustainability standards on business company attractiveness, more research is needed.

Most GSCM literature is theoretical and anecdotal. Several scholars also developed environmental sustainability measurement scales. King and Lenox (2001) question environmental sustainability's benefits. They discover inadequate evidence to establish a clear and decisive conclusion. Environmental sustainability methods and financial and environmental performance need more empirical research. Research is informative but not conclusive.

Hypotheses

As a result, internal metrics drive the greening of supply chain processes, which investigate the following hypotheses presented in figure 1:

Green Information Systems and Internal Environmental Management

Businesses can establish green information systems once they prioritize environmental sustainability. Information systems are necessary for supply chains. Green information systems are needed to achieve environmental sustainability. For environmental sustainability, GSCM requires monitoring manufacturing, purchasing, and sales. Information systems allow supply chain actors to connect and commit. Organizations employ information systems to facilitate collaboration. Management support for information system implementation was found by Jiang and Klein (1999).

 

Internal environmental management has a Positive relationship with green information systems.

Internal environmental management has a Positive relationship with green purchasing.

Internal environmental management has a Positive relationship with Cooperation with customers.

Internal environmental management has a Positive relationship with eco-design and green Marketing.

Internal environmental management has a Positive relationship with Green Logistics.

Internal environmental management has a Positive relationship with investment recovery.

Internal environmental management has a Positive relationship with Reverse Logistics.

Green Supply Chain Techniques and Internal Environmental Management

After establishing environmental sustainability as a strategic aim and getting mid-level management and top-level commitment and support, the firm can begin implementing the GSCM processes of customer cooperation, eco-design, green marketing, green purchasing, green logistics, reverse logistics, and investment recovery. The organization's overarching strategy must include the imperative as part of it in order to properly implement the procedures. Senior management support is essential for implementing activities, programs, and new technology. Environmental success demands top management support.

 

Green Information Systems confidently impacts green purchasing.

Green Information Systems confidently impacts green purchasing. Cooperation with customers.

Green Information Systems confidently impacts eco-design and green Marketing.

Green Information Systems Confidently impacts Green Logistic.

Green Information Systems Confidently impacts investment recovery.

Green Information Systems Confidently impacts Reverse Logistics.

Green Purchasing Confidently impacts Environmental Performance.

Green Purchasing Confidently impacts Economic Performance.

Green Purchasing Confidently impacts Social Performance.

Cooperation with Customers Confidently impacts Environmental Performance.

Cooperation with Customers Confidently impacts Economic Performance.

Cooperation with Customers Confidently impacts Social Performance.

Eco-design & Green Marketing Confidently impacts Environmental Performance.

Eco-design & Green Marketing Confidently impacts Economic Performance.

Eco-design & Green Marketing Confidently impacts social Performance.

Green Logistics has a Confidently impacts Environmental Performance.

Green Logistics has a Confidently impacts Economic  Performance.

Green Logistics has a Confidently impacts Social  Performance.

Investment Recovery has a Confidently impacts  Environmental Performance.

Investment Recovery has a Confidently impacts  Economic Performance.

Investment Recovery has a Confidently impacts  Social Performance.

Reverse Logistics has a Confidently impacts  Environmental Performance.

Reverse Logistics has a Confidently impacts  Economic Performance.

Reverse Logistics has a Confidently impacts  Social Performance.

Environmental Performance Confidently impacts Firm Performance.

Economic Performance has a Confidently impacts Firm Performance.

Social Performance has a Confidently impacts Firm Performance.

 

Figure 1. Conceptual Model for GSCM in Organized Retailing.

Designing of a Study

Data Collecting and Research Environment

Hypothetical relationships are tested empirically. Our study applied to organized retailing because of its economic importance and dominance in India. Six Gujarat retail specialists were interviewed for exploratory research.

The exploratory study examined retail retailers' supply chain and store sustainability measures. Semi-structured interviews were used. The semi-structured interviews permitted us to examine the spectrum of environmental measures adopted in-store by organized retailers and supply chain. Based on existing metrics and fresh information from practitioners, we created a GSCM questionnaire for organized retailing, to account for our respondents’ diverse roles, from store owners to supply chain managers. To ensure validity and comfort, the questionnaire was pretested.

The survey has three parts. The first component uses a five-point Likert scale to assess firms' green efforts. The second portion uses a five-point Likert scale to evaluate GSCM techniques' effects on effectiveness. Finally, the third element gathers organization data.

Our study included 554 respondents from eight Gujarat municipal corporations, with a 51.29% response rate. After partial least square SEM fitting, 554 of these were ready for further study. Retailers and logistics directors responded. Online directories such as Just Dial and company directories like Yellow Pages under various chambers of commerce provided example information. Data collection took place from April to September 2021. Supermarkets (20.0%) and hypermarkets (12.0%) are followed by department stores, convenience stores, and discount stores (68.00%).

The Measurement Consistency

In every instance when it was feasible to do so, each of the measurement scales that were used in our survey were reflective, multi-item frameworks that were constructed from previously used items and scales. The items were translated and then retranslated to ensure that they had the correct meaning. A five-point Likert scale was used (1 indicating not considering and 5 indicating implementing successfully). The questionnaire was pretested, and small wording changes were made. The constructions and their internal coherence are summarized in Table 1.

Reliability

To purify the scales, we utilized an exploratory factor analysis. Items with a communality of less than 0.4 were removed. Items with loadings of less than 0.5 and low variance were also removed. Following Hulland (1999), we tested indicator reliability, employed standardized indicator loadings of 0.7, and checked loadings of 0.4. Cronbach’s thresholds are met for all measures, and composite reliability (CR) and average variance extracted (AVE) demonstrate convergent validity and internal consistency reliability. The Fornell–Larcker criterion is used to verify discriminant validity. The AVE of every construct is greater than the squared correlation of any other construct. Cross-loadings were also examined.

 

 

Results of Data Analysis

Common Method Bias

To examine common method bias, Harman's single-factor test was used. The test found that a single-factor solution only explained 44.533% of the total variation, which is much less than the 50% threshold number. This finding recommends that common technique bias is minor in this investigation.

Reliability and Validity

As part of the measurement model evaluation, six items (IEM5, GIS2, GP1, GP5, GL4, and SP1) with a low factor loading (< 0.600) were eliminated from the assessment. Cronbach's alpha and composite reliability were utilized in order to perform reliability tests on the constructions.

All constructs' dependability exceeded the acceptable 0.700. Each construct's Cronbach's alpha value exceeded the 0.700 cutoff. Convergent validity was acceptable because AVE was more than 0.500. Table 2 shows the reliability and validity results, as well as the factor loadings for the items. The Fornell–Larcker criterion assessed discriminant validity. The square root of AVE for the construct was bigger than the inter-construct correlation, as seen in Table 3. The ratio of correlations between heterotraits and monotraits was also used to evaluate the discriminant validity of the test, with values below the threshold of 0.90. Hence, it is proven that discriminant validity exists (see Table 4).

SmartPLS 3 SEM analysis shows route coefficients (Table 2) and total effect size (Table 3). Business research now uses SEM to determine latent component cause–effect correlations. Business researchers utilize SEM to examine ideas and hypotheses. Five thousand bootstrap draws were used to find non-significant moderating effects.

 

Internal environmental management positively impacts all seven GSCM processes. Green information systems positively affect all six GSCM activities. Green purchasing affects two GSCM performances but not social performance. All three GSCM performances benefit from customer cooperation. All three GSCM performances positively impact eco-design and green marketing. All three GSCM performances are not affiliated with green logistics. Social performance affects investment recovery more than economic and environmental performance.

Reverse logistics is crucial to all three GSCM performances. Economic, environmental, and social performance improve business performance.

GSCM practices increase environmental performance except green purchasing, which improves social performance. This supports prior studies on GSCM's environmental benefits. Businesses investing in linked activities internally and with suppliers can create win-win scenarios. This is remarkable and contradicts prior data that explicitly link green logistic with economic, social, and environmental performance. Cost and accounting-related factors drive economic performance. Thus, cost savings may be overemphasized compared to performance outcomes, which may improve service.

Model of Structure

The structural model depicts the study framework's postulated routes. The R2, Q2, and importance of the routes are used to evaluate a structural model. The model's goodness is determined by each structural path's strength, which is determined by the dependent variable's R2 value, which should be 0.1 or above. Table 4 shows that all R2 values are more than 0.1. As a result, the ability to predict is established. Q2 also establishes the endogenous components' predictive relevance. A Q2 greater than 0 indicates that the model is predictive. The findings demonstrate that forecasting the constructs is important (see Table 4). SRMR was also utilized in order to assess how well the model fits the data. The SRMR score was 0.043, which is below the minimum requirement of 0.10, indicating that the model fit was adequate.

 

 

 

To determine the significance of the association, the goodness-of-fit hypotheses were reevaluated. H1 evaluates whether IEM significantly impacts CWC, EDGM, GIS, GL, GP, IR, RL (p < 0.001). The results revealed (see Table 5) that internal environmental management (IEM) significantly impacts cooperation with consumers (CWC), eco-Design & Green Marketing (EDGM), green information systems (GIS), green logistics (GL), green purchasing (GP), investment recovery (IR), and reverse logistics (RL). Hence, H1 was supported.

 

 

SRMR is the model's observed–suggested correlation matrix difference. Thus, the (model) fit criteria can be measured by the average difference between actual and expected correlations. A fit under 0.10 or 0.08 is good. Henseler et al. (2014) established the PLS-SEM goodness-of-fit metric SRMR to avoid model misspecification. Dijkstra and Henseler (2015) used squared Euclidean distance (ULS) and d G (geodesic distance) to calculate this disagreement in Table 6.

Data analysis provides NFI values from 0 to 1. Fit increases NFI. Good matches have NFI scores over 0.9. Lohmöller (1989) describes the NFI computation of PLS route models in detail. RMS theta determines outer-model residual correlation. The score should be near zero to indicate a good model fit and low correlations between outside model residuals (close to zero).

 

Figure 2. Hypotheses Test Results.

 

 

We looked at the aggregate effects of green in-store operations and performance outcomes in addition to verifying the hypotheses. Green information systems have a large beneficial overall impact on green supply chain practices. The is a classic example of a situation in which both parties benefit, in which increased information technology use reduces environmental impact and costs. There is a good association between environmental, economic, and social performance while working with consumers.

Contributions in Theory and Practice Through Discussion

We have never seen GSCM in organized retailing empirically proven. It empirically proves that greening in-store operations greens SCM practices, combining downstream and upstream supply chain activities. According to the statistics, there is a correlation between the installation of environmental protection measures in a store and an increased likelihood of that store's participation in GSCM, which improves environmental performance. By studying the overall structural model, we used GSCM to organize the supply chains for both retailing and services, two areas in which it is hardly ever employed. The model is the first approach to analyze the general supply chain management practices and performance of organized merchants. This was accomplished by operationalizing a component of the conceptual model.

Second, this study emphasizes eco-friendly in-store activities such as trash and energy management. The two models simplify and cover a portion of retail activity during this time. Similar structures and objects were utilized in manufacturing and retailing investigations.

Third, retailers' green supply chain operations are holistically viewed through green purchasing, customer cooperation, eco-design and green marketing, green logistics, investment recovery, and reverse logistics, which summarizes the studied constructs. Zsidisin and Siferd (2001) studied environmental buying, whereas Zhu and Sarkis (2004) examined operational methods. Wong et al. (2015) examine cooperation. An empirical investigation examining all six categories and their correlations had not yet been conducted. The literature review describes these essential processes as operational (logistics), tactical (purchasing), and strategic.

Limitation

Despite GSCM and organized retail contributions, this study has disadvantages. This study must consider several constructs. The methodology helps merchants discover causes, behaviors, and performance. Testing the conceptual model suffices. Many Gujarati shops consented to generalize this sample. The SEM-PLS study has two limitations. First, the analysis checks theories, not patterns. Explanatory component analysis shows no model data structure differences. Second, PLS may improve prediction; however, it just does a superficial comparison of theoretical hypotheses. Our exploratory research is unrestricted.

Conclusions

Retailers handle the most complicated supply chains. GSCM research evaluates secondary data including merchants' green activities on their websites, CSR reports, and industrial groups' viewpoints. The organized sector has not investigated internal and external supply chain greening. Thus, this study evaluated how organized retail, green in-store, GSCM practices, and social, environmental, and economic performance are linked. Structural equation modeling in organized retail studied green in-store practices, green supply chain performance. Lack of research on the relationship between in-store greening and activities, GSCM practices, and the organization's overall performance as a well-organized retail supply chain. The study adds empirically to the rising debate about retail durability from the perspective of key retailers in supply chain management. This answers our research question. Green store processes help GSCM. Consumer collaboration, eco-design, green marketing, green logistics, investment recovery, and reverse logistics enable green purchasing. Environmental, social, and economic factors affect the relationship concerns. However, retailing and GSCM service have been improving.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Amitkumar L. Shah  https://orcid.org/0000-0001-8163-3798