Development of Green Supermarket Evaluation Model Based on Green Process and Green Output—Case of Bangkok City

Abstract

The study aimed to develop a green supermarket evaluation model based on a green process and green output to provide empirical evidence on the model’s relationship with the green process, green output, and green supermarket. To this end, the study combined data from a survey of one store manager, one facility manager, and three assistant store managers from each of the 190 supermarket branches in Bangkok, Thailand with data from an in-depth interview of a sample group of green supermarket management specialists. The green supermarket evaluation model is divided into three levels, two elements (green process and green output), nine major indicators for green supermarket evaluation, and one hundred one sub-indicators for green supermarket evaluation, according to the findings. The five major indicators of the green process are green procurement, green storage, green service, green transportation and green environmental and energy management system, while the four major indicators of green output are social performance, environmental performance, economic performance, and organization image performance. In addition, the sub-indicator details were also identified for this evaluation model.

1. Introduction

Nowadays, many organizations are moving towards green business practice as a key strategy that has the potential to deliver better performance compared to the conventional business models in this age of sustainability [1]. The new business direction aims to establish an eco-friendly stance, demonstrate cost-effective resource use and environmental protection, and generate a positive image for enterprises in the community and in the eyes of the public [2]. It can be stated that green business plays a significant role since it is a sustainable development approach in the economy that aims to create a balance between humans and the environment. At present, many organizations, in both public and private sectors, are placing a greater focus on addressing problems to restore the environment to a higher level. Likewise, organizations in the supermarket business sector will need to adjust their business operations as the increased importance of the environment to consumers has created a trend of environmental conservation [3]. Although the green operations of supermarkets today are focused primarily on environmental action, problems still remain in terms of air pollution, wasted energy, and food waste [4,5]. As a result of these impacts, supermarket retailers have been required to adjust to the setting of the circular economy and green supply chain management, which includes implementing environmentally friendly measures into the supply chain, supply selection, supply chain management, and the final delivery to the customer process [6].

The Thai economy, similar to that of other developing countries, has transformed from an agriculture-based to an industry-based model over the last century. This condition contributes to the food supply chain and consumer behavior as a result of the urbanization process [7]. Aside from these direct economic contributions, the retail sector is important in defining consumer behavior and supporting productivity, growth, and development throughout the country [8]. Commodity consumption has risen as the economy has continued to grow, especially in the modern retail industry, which has grown steadily from the 1990s to the 2010s. This is evident in the fact that the proportion of modern retail and wholesale enterprises has increased from 25% of the wholesale retail market in 2001 to 61% in 2014 [9].

Although supermarkets drive the economy on a national and global scale, their business operations have an impact on environmental issues such as energy usage and air pollution. The electrical energy consumption is also a problem since each supermarket has a very high level of power consumption. The supermarket industry accounts for approximately 3–4% of all the electrical energy consumed by businesses nationwide [10]. The food waste (FW) problem that exists with large supermarkets is due to errors in the storage of fresh food, such as failure to control the shelf-life of food products, inefficient storage spoilage, excessive supply as compared to product demand, and food waste from the food court [11]. Supermarkets are known to waste approximately 10% of their food along the supply chain [12]. Consumption of environmental-friendly products is becoming popular while corporate social responsibility is also increasingly important in the business world [13]. Companies have been put under pressure as a result of these phenomena, which force them to incorporate more ecologically friendly practices and become more involved in their communities. Some businesses may do so in order to comply with legal requirements in order to protect their reputation, as well as to improve resource management and supply chain management efficiency [14]. However, the relationship between environmental sustainability and economic efficiency is generally doubtful. This implies that there is still a limited incentive for businesses to “go green” [15]. This is especially true in the modern retail industry, which consumes massive amounts of resources and has a wide range of environmental impacts throughout the company supply chain. The importation and management of these resources could produce a lot of supply chain waste, especially food waste. As a result, there is a growing interest in determining the extent of the need for supermarkets to reduce their waste production and energy consumption [4]. At present, one urgent issue is the question of how to develop the overall green supermarket indicator to evaluate performance in various dimensions. Therefore, the following research question is addressed in this study: “What is the appropriate green indicator for supermarkets to evaluate their supply chain management (SCM) performance in various dimensions?”.

Depending on the socioeconomic context, the development of green supermarket indicators based on the green business idea may differ. These indicators, on the other hand, are commonly based on three essential concepts: reduce, recycle, and replenish [16]. The recommended green supermarket metric in Thailand is the Green Building Standard, which consists of eight parameters that encompass the building’s energy usage and environmental sustainability scores in terms of operation and maintenance [17]. Another popular green supermarket metric is the “UK Supermarkets Scorecard,” which uses software to assess the social and environmental responsibility of UK supermarkets.

In addition, green indicators have been developed from various perspectives; for example, the major engagements in sustainable procurement are the green and social equity procurement indicators (energy conservation, recyclability, water pollution, air quality, greenhouse gas emissions, reduced packaging, volatile organic compounds, and biodiversity) [18]. Meanwhile, the green business model indicator consists of awareness, organization culture, innovation, technology, and learning, which are the drivers of stakeholder engagement that are considered one of the key elements helping to facilitate an increased uptake of green business [1]. It should be noted that these above-mentioned green indicators still do not cover all aspects of SCM evaluation. The SCM indicators, in particular, are critical to the performance measurement of green supermarket management. As is well known, SCM practices have the potential to improve not only environmental protection, but also the company’s efficiency. This will assist in offsetting operating costs, improving operational efficiency, and increasing competitive advantages [19].

However, there is currently no direct way to evaluate green supermarkets under the SCM perspective, which cannot cover all four aspects of sustainability evaluation, namely social, environmental, economic, and organization image. Therefore, a green supermarket evaluation system with appropriate indicators and evaluation criteria must be considered in order to motivate supermarkets to become green supermarkets. At present, there are no clear guidelines or directions for evaluating green supermarkets. For this reason, the purpose of this research is to study the factors affecting green supermarkets as well as to develop a green supermarket evaluation model with appropriate major indicators and sub-indicators. Due to the combination of multi-level indicators, at both major and sub levels, the metric model can cover all aspects of green supermarket evaluation. Hence, closing the research gaps in the evaluation can be obtained when it is applied as a metric model in business organizations. This work provides practical value by highlighting the development of a green supermarket evaluation model that encompasses multi-level indicators throughout the supply chain in green supermarket management. Additionally, this work also reveals the need to review strategies or practices for driving a green supermarket evaluation model for real-world applications.

2. Materials and Methods

2.1. Theoretical Framework

This evaluation model aims to determine and provide an appropriate value based on set criteria. For the green supermarket evaluation, this refers to a process that includes collecting and analyzing information to generate data to be used as a reference for decision-making in the development of green operations, compared with the criteria that have been established to judge the green value for evaluation at various levels. The evaluation is a role that comes from the nature of the information needed to make decisions in assessing the value of the factor to be measured. It can be characterized as a formative role and a summative role. The acquisition of the aforementioned information will require an evaluation in which the presentation of information during the operation must also assess the progress of the operation with a formative evaluation. The formative evaluation is important for judging the progress value of operations that are information-based for decision-making or the approach to operational adaptation because the information presented after the end of the operation uses a summative evaluation [20]. From the valuation theory, the ultimate aim of the evaluation is the acquisition of information to measure the value of the appraisal. The value is a feature that depends on various factors that can change according to the situation; hence it is difficult to define the absolute value [21].

The value of the factor to be measured can be observed from the indicators through empirical data that is compared with the metric. This can determine the value of the factor to be measured. Values can be classified into two categories: intrinsic and extrinsic. Intrinsic value is the internal hidden value in the factor to be measured. For the extrinsic value, it is the external value of the factor to be measured, which depends on various factors within the established scope that can be clearly evaluated [22]. In addition, the intrinsic and extrinsic values are interrelated only when various factors are taken into account and cannot be independent of each other. The extrinsic values are a subset of intrinsic values and the decisions about extrinsic values contribute to the intrinsic value.

2.2. Research Design

This study relied on primary data and used a mixed methodology approach (qualitative and quantitative research) as shown in Figure 1. In the first stage, questionnaires were used to conduct quantitative research for the development of major indicators for green supermarket evaluation. In the second phase, an in-depth interview approach was used to conduct qualitative research for the development of sub-indicators for green supermarket evaluation. In the third phase, a focus group interview was used to conduct qualitative research for the development of sub-indicator details. The researcher’s personal mathematics skills were used to complete the final stage of the mathematical model analysis for the development of the green supermarket evaluation model. The approach to the quantitative research is based on structural equation modeling (SEM) and multiple regression analysis (MRA). The major indicators for green supermarket evaluation are the factors influencing a green supermarket that were obtained from the preceding literature analysis and can be defined as a conceptual framework, as illustrated in Figure 2.

The major indicators for green supermarket evaluation include five sub-factors of the green process (GPRO): green procurement (GPUR), green storage (GSTO), green service (GSER), green transportation (GTRA) and green environmental and energy management system (GEES), as well as four sub-factors of green output (GOUT): social performance (SOCP), environmental performance (ENVP), economic performance (ECOP), and organization image performance (OIMP). The research hypothesis can be defined using the research conceptual framework as follows:

Hypothesis 1 (H1).

Green process (GPRO) is a factor affecting the green output (GOUT).

Hypothesis 2 (H2).

Green output (GOUT) is a factor affecting green supermarkets (GSPM).

Green procurement (GPUR) is the procurement of a product or service that has less of an environmental footprint than normal procurement, whereby the entire life cycle of the product and service would be taken into consideration, starting from the procurement of raw materials to the waste disposal at the end of the usable period, and including cooperation with the supplier in finding a suitable replacement for hazardous materials, or more eco-friendly substitutes [23]. Green storage (GSTO) is storage that focuses on minimizing impacts on society and the environment, without negatively affecting profit and corporate image. Green service is a customer service process that covers from storage to the end of the process, and which has no impact on the environment, profit, or corporate image, while impressing the customers with high-quality standards [24]. Green transportation (GTRA) is a transportation process that uses technology, packaging, and methodology that does not have a negative impact on the environment, including during the delivery of products and services to the customer, and reverse logistics to suppliers [23]. Green environmental and energy management system (GEES) is a management process that includes environmental management system, which is a work process that enables supermarkets to reduce their environmental impacts from activities in order to increase operating efficiency [24], and energy management system, which is an information management system to support works related to energy management and cost, energy measurement, energy efficiency and energy consumption control [25].

Social performance (SOCP) is the impact on society arising out of the work process from the start all the ways through to delivery to the customer [23], such as, social value generation, the risk to the ecological system, emission of greenhouse gases, generation of waste, and generation of air pollution. Environmental performance (ENVP) is the impact on the environment due to the work process from the start all the way through to delivery to the customer, such as, all waste generation and resources consumption [23], including the consumption of energy, materials, area, and water [26]. Economic performance (ECOP) is efficiency that shows the ability of a producer to select the least number of inputs and achieve the lowest cost [27] from the systematic and efficient use of resources [28]. Organization image performance (OIMP) is the performance arising out of social and environmental campaigns, along with green supply chain management and allowing consumer engagement in environment conservation [29].

According to the research conceptual framework, the green supermarket is the supermarket’s intrinsic value, while the green output is the supermarket’s extrinsic value, and the green process is the extrinsic value of the green output. Green procurement, green storage, green service, green transportation and green environmental and energy management system (GEES) were among the variables included in the domain of the green process. The variables considered in the realm of green output were environmental performance, economic performance, and organization image performance.

2.3. Data Collection

The quantitative research was conducted through a structured questionnaire sent to one store manager, one facility manager, and three assistant store managers from each of the 190 supermarket branches in Bangkok and Metropolitan, Thailand. A total of 274 respondents completed the questionnaire. The aim of the questionnaire was to study the factors influencing green supermarkets and to develop the factors and major indicators to be used for green supermarket evaluation. The respondents were asked to react to each of the issues specified in the questionnaire by recording their responses on a five-point Likert scale.

The qualitative research for the development of the sub-indicators for the green supermarket evaluation was conducted by in-depth interviews with each key informant in order to develop the draft sub-indicators for the green supermarket evaluation from the major indicators. The major indicators of the green process are green procurement, green storage, green service, green transportation and green environmental and energy management system, while the four major indicators of green output are social performance, environmental performance, economic performance, and organization image performance. The key informants included a group of nine persons, consisting of three supermarket store managers, three top supermarket management personnel, and three specialists on environmental policy and green building support from Thai government agencies. In addition, a focus group interview with five specialists on green business standard settings from Thai government agencies was also conducted as part of qualitative research methodology for the development of sub-indicator details. Furthermore, all study instruments were evaluated for content validity and reliability by five experts: a social and environmental expert, an economic expert, an organization image expert, a statistics and research expert, and a qualified person with measurement and evaluation knowledge.

2.4. Data Analytics

The data for the quantitative research were all inspected and analyzed in the following order: (1) a reliability study was performed to determine the reliability of the research equipment and data; (2) descriptive statistical analysis of the responders’ data was performed; (3) descriptive statistical analysis of the model’s variables was performed to determine the arithmetic mean, standard deviation, skewness, and kurtosis; (4) correlation analysis was performed on all factors in the model to investigate the link between each pair of factors; (5) SEM was used to test hypothesis 1; and (6) MRA was used to test hypothesis 2. An in-depth interview with each key informant was conducted to study the draft sub-indicators in order to develop the sub-indicators for green supermarket evaluation from the major indicators for the qualitative data analysis. A focus group with five specialists on establishing green business standards from Thai government agencies conducted the qualitative data analysis for the development of the sub-indicator details. In addition, the mathematical model analysis for the development of the green supermarket evaluation model was performed through the researcher’s own arithmetic knowledge.

3. Results and Discussion

3.1. Development of Major Indicators for Green Supermarket

3.1.1. Analysis of H1

Reliability Analysis

As shown in

Table 1. Internal consistency and reliability.

Factors	Sub-Factors	Items	n	$\overline{\mathit{x}}$ *	SD *	Alpha
On a scale of one (1: least agree) to five (5: most agree), please select the number that best describes the level of your opinion, the factors affecting a green supermarket from the following:
Green process	Green procurement	Green procurement affects social performance	274	4.50	0.697	0.897
		Green procurement affects environmental performance	274	4.50	0.697
		Green procurement affects economic performance	274	4.36	0.768
		Green procurement affects organization image performance	274	4.45	0.668
	Green storage	Green storage affects social performance	274	4.43	0.704	0.889
		Green storage affects environmental performance	274	4.43	0.704
		Green storage affects economic performance	274	4.28	0.800
		Green storage affects organization image performance	274	4.46	0.685
	Green service	Green service affects social performance	274	4.42	0.687	0.881
		Green service affects environmental performance	274	4.42	0.687
		Green service affects economic performance	274	4.36	0.777
		Green service affects organization image performance	274	4.48	0.680
	Green transportation	Green transportation affects social performance	274	4.43	0.709	0.891
		Green transportation affects environmental performance	274	4.43	0.709
		Green transportation affects economic performance	274	4.31	0.772
		Green transportation affects organization image performance	274	4.41	0.772
	Green environmental and energy management system	Green environmental and energy management system affects social performance	274	4.48	0.652	0.894
		Green environmental and energy management system affects environmental performance	274	4.48	0.652
		Green environmental and energy management system affects economic performance	274	4.33	0.732
		Green environmental and energy management system affects organization image performance	274	4.50	0591
Green output	Social performance	Social performance affects green supermarket	274	4.53	0.653	0.880
	Environmental performance	Environmental performance affects green supermarket	274	4.53	0.653
	Economic performance	Economic performance affects green supermarket	274	4.39	0.764
	Organization image Performance	Organization image performance affects green supermarket	274	4.48	0.670
Green supermarket	-	Green supermarket is a modern retail business of the supermarket type with social responsibility, environmental responsibility, economic responsibility and organization image responsibility, and doing various activities, the aim of which is to generate appropriate income in a manner that has the least impact on the environment	274	4.56	0.597	N/A

* $\bar{x}$: Mean value.

, the observed exogenous variables (green process) and the observed endogenous variables (green output) were measured on a 5-point Likert scale. All multi-item scales included in the questionnaires have Cronbach’s Alpha values above 0.6, which is in the acceptable range of internal consistency between the items against each variable [30].

Descriptive Statistical Analysis

As shown in

Table 2. Branch manager sample demographics.

Variable	Attribute	Branch Manager
		Number of People	Percentage (%)
Gender
	Male	218	79.56
	Female	56	20.44
	Total	274	100.00
Work experience in
management
	1–5 years	8	2.92
	6–10 years	32	11.68
	11–15 years	193	70.44
	16–20 years	41	14.96
	Total	274	100.00

, most respondents were male (79.56%) and had working experience in management for 11–15 years (14.96%). As can be seen in

Table 3. Descriptive statistics for all parameters.

Factor	Sub-Factor (Major Indicator)	n	$\overline{\mathit{x}}$	SD	SK	KS
Green process (GPRO)	Green procurement (GPUR)	274	4.453	0.619	−0.776	−0.563
	Green storage (GSTO)	274	4.400	0.628	−0.714	−0.543
	Green service (GSER)	274	4.419	0.609	−0.742	−0.439
	Green transportation (GTRA)	274	4.394	0.632	−0.646	−0.743
	Green environmental and energy management system (GEES)	274	4.484	0.574	−0.650	−0.692
Green output (GOUT)	Social performance (SOCP)	274	4.529	0.653	−1.065	−0.021
	Environmental performance (ENVP)	274	4.526	0.653	−1.050	−0.048
	Economic performance (ECOP)	274	4.391	0.764	−1.391	2.770
	Organization image performance (OIMP)	274	4.482	0.670	−0.928	−0.307

$\overline{x}$: mean, SD: standard deviation, SK: skewness, KS: kurtosis.

, the value of various sub-factor is transformed from the mean of each individual observed variable value. The sub-factors of the green process with the highest to the lowest mean are green environmental and energy management system ($\overline{x}$ = 4.484; SD = 0.574), green procurement ($\overline{x}$ = 4.453; SD = 0.619), green service ($\overline{x}$ = 4.419; SD = 0.609), green storage ($\overline{x}$ = 4.400; SD = 0.628) and green transportation ($\overline{x}$ = 4.394; SD = 0.632). The sub-factors of green output with the highest to the lowest mean are social performance ($\overline{x}$ = 4.529; SD = 0.653), environmental performance ($\overline{x}$ = 4.526; SD = 0.653), organization image performance ($\overline{x}$ = 4.482; SD = 0.670) and economic performance ($\overline{x}$ = 4.391; SD = 0.764), respectively. Additionally, all sub-factors had the normal distribution characteristics (−2 > SK < 2; −3 > KS < 3).

Correlation Analysis

Table 4. Pearson correlation coefficient of the subfactors of green process and green output.

Pearson Correlation Coefficient of the Sub-Factors of Green Process
	GPUR	GSTO	GSER	GTRA	GEES
GPUR	1.000
GSTO	0.844 **	1.000
GSER	0.828 **	0.816 **	1.000
GTRA	0.860 **	0.842 **	0.858 **	1.000
GEES	0.840 **	0.846 **	0.850 **	0.838 **	1.000
Bartlett’s Test of Sphericity = 1613.068, p < 0.001
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = 0.971
Pearson Correlation Coefficient of the Sub-Factors of Green Output
	SOCP	ENVP	ECOP	OIMP
SOCP	1.000
ENVP	0.772 **	1.000
ECOP	0.605 **	0.557 **	1.000
OIMP	0.689 **	0.692 **	0.619 **	1.000
Bartlett’s Test of Sphericity = 1613.068, p < 0.001
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = 0.971

** p < 0.01.

illustrates the results of the Pearson correlation coefficient analysis among five sub-factors of the green process: green procurement (GPUR), green storage (GSTO), green service (GSER), green transportation (GTRA), and green environmental and energy management system (GEES). It was found that the correlation between the sub-factors with a statistically significant difference from zero (p < 0.01) shows correlation coefficient values among the sub-factors in the range of 0.816 to 0.860.

Table 4 shows the results of the Pearson correlation coefficient analysis among four sub-factors of green output: social performance (SOCP), environmental performance (ENVP), economic performance (ECOP), and organization image performance (OIMP). The correlation between the sub-factors with a statistically significant difference from zero (p < 0.01) shows the correlation coefficient value among the sub-factors are in the range of 0.557 to 0.772.

Analysis of Major Indicators for Green Supermarket Evaluation

From the conceptual framework, the sub-factors of green process and green output are the green evaluation criteria for green supermarket evaluation. The SEM is used to prove that such sub-factors of the green process and green output can be used as green evaluation criteria (the SEM is used to prove whether these factors can be good representatives to measure the green supermarket or not).

As can be seen in Figure 3 and

Table 5. Model consistency with empirical data.

Major-Indicator (or Variable)	Component Weight/Influence		t
	b (SE)	Beta (β)
GPRO
GPUR	0.965 (0.035)	0.918	27.530 ***
GSTO	0.967 (0.037)	0.907	26.429 ***
GSER	0.941 (0.035)	0.911	26.771 ***
GTRA	1	0.932	------
GEES	0.909 (0.035)	0.931	26.093 ***
GOUT
SOCP	1.002 (0.079)	0.827	12.755 ***
ENVP	0.986 (0.079)	0.814	12.552 ***
ECOP	1	0.708	------
OIMP	1.043 (0.080)	0.841	13.027 ***
GPRO ---> GOUT (or GPRO)	0.825 (0.063)	0.903	13.203 ***

CMIN/d_f = 1.666, d_f = 21, RMSEA = 0.049, CFI = 0.995, GFI = 0.974, *** p < 0.001. ------: SE and t values are not reported as this is a constrained parameter, ---> is the influence line.

, the relative Chi-square (CMIN/d_f) equals 1.666 (CMIN/d_f < 3) at 16 degrees of freedom (d_f), and the root mean square error of approximation (RMSEA) equals 0.049 (RMSEA < 0.05), which corresponds to the comparative fit index of 0.995 (CFI > 0.9), and the goodness of fit index of 0.974 (GFI > 0.95). Therefore, the results have indicated that the model has high consistency with empirical data. Considering the component weight and influence, all variables (major indicators) were statistically significant at the 0.001 level (p < 0.001), and therefore hypothesis H₁ is accepted.

3.1.2. Analysis of H2

As shown in

Table 6. The sub hypothesis analysis test.

ANOVA a		Sum of Squares	Degree of Freedom	Mean Squares	F	p-Value
	Regression Residual Total	86.413 11.153 97.566	4 269 274	21.603 0.041	521.070	<0.01 b

^a dependence: Y₁, ^b Predictors: Constant, X₁, X₂, X₃, X_4.

, the MRA was performed to test hypothesis H₂ (green output affects green supermarket), and it can be defined for sub-hypothesis 1 as follows:

H₀: β₁ = β₂ = β₃ = β₄ = 0: X₁, X₂, X₃ and X₄ have no influence on Y₁

H_sub1: β₁ or/and β₂ or/and β₃ or/and β₄ ≠ 0: X₁ or/and X₂ or/and X₃ or/and X₄ have influence on Y₁

When

• X₁ is social performance.
• X₂ is environmental performance.
• X₃ is economic performance.
• X₄ is organization image performance.
• Y₁ is green supermarket.

Table 6 shows the statistical significance with a p-value < 0.01, therefore the H₀ is rejected and the H_sub1 is accepted. This means that X₁ or/and X₂ or/and X₃ or/and X₄ have influence on Y₁ (or at least one independent variable has influence on green supermarkets). Therefore, four sub-hypotheses can be defined as follows:

Sub hypothesis 2

H₀: β₁ = 0: X₁ has no influence on Y₁

H_sub2: β₁ ≠ 0: X₁ has influence on Y₁

Sub hypothesis 3

H₀: β₂ = 0: X₂ has no influence on Y₁

H_sub3: β₂ ≠ 0: X₂ has influence on Y₁

Sub hypothesis 4

H₀: β₃ = 0: X₃ has no influence on Y₁

H_sub4: β₃ ≠ 0: X₃ has influence on Y₁

Sub hypothesis 5

H₀: β₄ = 0: X₄ has no influence on Y₁

H_sub5: β₄ ≠ 0: X₄ has influence on Y₁

From

Table 7. Coefficient analysis.

Model	Unstandardized Coefficients		Standardized Coefficients	t	p-Value
	B	Std. Error	Beta (β)
Constant	0.259	0.095		2.715	0.07
Social performance (X1)	0.284	0.032	0.310	8.750	<0.01
Environmental performance (X2)	0.241	0.032	0.263	7.583	<0.01
Economic performance (X3)	0.074	0.022	0.094	3.408	<0.01
Organization image performance (X4)	0.357	0.029	0.400	12.515	<0.01
R2 = 0.941, R2 Adjusted = 0.886

, the coefficient analysis shows the statistical significance with the p-value < 0.01. Therefore, H₀ is rejected, and H_sub2, H_sub3, H_sub4, and H_sub5, are accepted. This means that X₁, X₂, X₃, and X₄ have an influence of 94.1% (R²) on Y₁. Hence, all the independent variables that influence green supermarkets are social performance, environmental performance, economic performance, and organization image performance. The remaining 5.9% were due to other factors that were not studied in this research. Therefore, the green output is the extrinsic value of a green supermarket that can be measured by the intrinsic value of a green supermarket. In addition, the five sub-factors of the green process are green procurement (GPUR), green storage (GSTO), green service (GSER), green transportation (GTRA) and green environmental and energy management system (GEES), while the four sub-factors of green output are social performance (SOCP), environmental performance (ENVP), economic performance (ECOP), and organization image performance (OIMP), which are considered major indicators for green supermarket evaluation.

3.2. Development of the Draft Sub-Indicators for Green Supermarket Evaluation

3.2.1. Draft Sub-Indicators of Green Procurement

The findings from the in-depth interviews about the sub-indicators of green procurement that are important for green supermarket evaluation, as well as the frequency and percentage of the selected draft sub-indicators are shown in

Table 8. Indicator analytic from in-depth interviews for green process (GPRO).

Major Indicators	Draft Sub-Indicators		Selected Indicator Frequency and Percentage
	Codes	Detail	Frequency *	%
Green procurement (GPUR)	GPUR1	There is an evaluation system for green product standards (green label, green livestock, etc.)	6	66.67
	GPUR2	The ratio of products that have green standards	6	66.67
	GPUR3	There is a complaint system for stakeholders in procurement	5	55.56
	GPUR4	There is a complaint management system for stakeholders in procurement	5	55.56
	GPUR5	There is a complaint communication system for stakeholders in procurement	5	55.56
	GPUR6	The ratio of suppliers who received green standard certification.	5	55.56
	GPUR7	The ratio of products that have green label standards	4	44.44
	GPUR8	The ratio of revised purchase complaints	4	44.44
	GPUR9	There is a product requirement planning system	4	44.44
	GPUR10	The ratio of product items available.	5	55.56
	GPUR11	There is a food safety product management system	6	66.67
	GPUR12	The ratio of food product items with international safety production standards (GMP, etc.)	6	66.67
	GPUR13	There is a green procurement policy that is communicated to employees at all levels	3	33.33
	GPUR14	There are supplier selection standards (e.g., contract of sale)	3	33.33
	GPUR15	There is a legal product selection standard.	6	66.67
	GPUR16	The number of suppliers who have performed illegal operations	8	88.89
	GPUR17	The number of illegal products	6	66.67
Green storage (GSTO)	GSTO1	There is a complaint system for stakeholders in storage	3	33.33
	GSTO2	There is a complaint management system for stakeholders in storage	3	33.33
	GSTO3	There is a complaint communication system for stakeholders in storage	6	66.67
	GSTO4	The ratio of revised storage complaints	5	55.56
	GSTO5	The ratio of product items available for sale in the sales area	4	44.44
	GSTO6	The ratio of product items found to be expired	4	44.44
	GSTO7	There is a green storage policy that is communicated to employees at all levels	2	22.22
	GSTO8	There is a management system for occupational safety and health	4	44.44
	GSTO9	The number of accidents at work	5	55.56
Green service (GSER)	GSER1	There is a complaint system for customers at sales area	5	55.56
	GSER2	There is a complaint management system for customer	5	55.56
	GSER3	There is a complaint communication system for customer and related staffs	4	44.44
	GSER4	There is a complaint system for stakeholders in service	3	33.33
	GSER5	There is a complaint management system for stakeholders in service	5	55.56
	GSER6	There is a complaint communication system for stakeholders in service	5	55.56
	GSER7	The ratio of revised service complaints	6	66.67
	GSER8	The number of recurring customer complaints	3	33.33
	GSER9	The ratio of customer complaints that are fully communicated	5	55.56
	GSER10	The ratio of product items that have been stored clearly for customers	6	66.67
	GSER11	The ratio of revised service complaints	5	55.56
	GSER12	There is an electronic shelves label system	5	55.56
	GSER13	The ratio of product items using electronic shelves labels	6	66.67
	GSER14	There is a system for assessing cleanliness and hygiene in the supermarket area.	3	33.33
	GSER15	There is a screening system for epidemics	4	44.44
	GSER16	There is green service policy that is communicated to employees at all levels	6	66.67
	GSER17	The ratio of refill products to the total product items	4	44.44
Green transportation (GTRA)	GTRA1	There is a complaint system for stakeholders in transportation	6	66.67%
	GTRA2	There is a complaint management system for stakeholders in transportation	4	44.44%
	GTRA3	There is a complaint communication system for stakeholders in transportation	3	33.33%
	GTRA4	The ratio of revised transportation complaints	3	33.33%
	GTRA5	There is a payment waiting time check system	3	33.33%
	GTRA6	The ratio of the number of customers waiting in the payment queue for more than 5 min	6	66.67%
	GTRA7	There are degradable packaging bags for customers	5	55.56%
	GTRA8	The ratio of the number of use of the degradable packaging bags for customers	4	44.44%
	GTRA9	There is a green transportation policy that is communicated to employees at all levels	3	33.33%
(GEES)	GEES1	The organization has a green energy management and energy system policy and management framework in place to ensure that all staff are conscious of the guidelines	9	100%
	GEES2	Employees at all levels are required to accept the policy and communication of the green environmental and energy management system	9	100%
	GEES3	Inspection and evaluation of treated wastewater quality in compliance with the requirements mandated by law	9	100%
	GEES4	A focused working group on the environment and energy have been established	9	100%
	GEES5	Employees within the company have been tasked with taking care of the environment and energy management	9	100%
	GEES6	The organization promotes environmental and energy knowledge and skills of its employees	9	100%
	GEES7	The organization has a procedure for collecting, analyzing, and evaluating quantitative information on all water utilization	9	100%
	GEES8	The company continuously improves the training requirements for employees who work in environmental and energy protection	9	100%
	GEES9	The organization continually monitors the treated wastewater’s quality	9	100%
	GEES10	The organization has sorted food waste for further use or management	9	100%
	GEES11	The organization adopts effective trash management and garbage separation	9	100%
	GEES12	The organization follows a standard waste management system	9	100%
	GEES13	The organization has implemented a process for wastewater recycling and reuse	9	100%
	GEES14	The organization has utilized by-products from food waste management such as fertilizer, biogas	9	100%
	GEES15	An environmental and energy action plan for the organization supports overall environment and energy management dimensions	9	100%
	GEES16	The organization has been working on process guidelines for instructing staff members on environmental and energy conservation	9	100%
	GEES17	Organizations have set timeframes for cleaning and maintaining equipment that consumes large amount of energy	9	100%
	GEES18	The organization uses high-efficiency air conditioners and chillers	9	100%
	GEES19	The organization has modified or installed energy-saving lamps in place of the old incandescent lamps	9	100%
	GEES20	An apparatus that manages the operation of automatic outside lamps is installed in the organization	9	100%

* A total of nine key informants.

(the frequency is between 3 and 8 or from 33.33% to 88.89%). Then the draft sub-indicators of green procurement with a score greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.2. Draft Sub-Indicators of Green Storage

The findings from the in-depth interviews about the draft sub-indicators of green storage that are important for green supermarket evaluation, as well as the frequency and percentage of the selected draft sub-indicators are shown in Table 8 (the frequency is between 2 and 6 or from 22.22% to 66.67%). Then the draft sub-indicators of green storage with a score equal to or greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.3. Draft Sub-Indicators of Green Service

The findings from the in-depth interviews about the draft sub-indicators of green service that are important for green supermarket evaluation, as well as the frequency and percentage of the selected draft sub-indicators are shown in Table 8 (the frequency is between 3 and 6 or from 33.33% to 66.67%). Then the draft sub-indicators of green service with a score greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.4. Draft Sub-Indicators of Green Transportation

The findings from the in-depth interviews about the draft sub-indicators of green transportation that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in Table 8 (the frequency is between 3 and 6 or from 33.33% to 66.67%). Then the draft sub-indicators of green transportation with a score greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.5. Draft Sub-Indicators of Green Environmental and Energy Management System

The findings from the in-depth interviews about the draft sub-indicators of green environmental and energy management systems that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in Table 8 (the frequency equals 9 points (or ≥100%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.6. Draft Sub-Indicators of Social Performance

The findings from the in-depth interviews about the draft sub-indicators of social performance that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in

Table 9. Indicator analytic from in-depth interviews for green output (GOUT).

Major-Indicators	Draft Sub-Indicators		Selected Indicator Frequency and Percentage
	Codes	Detail	Frequency *	%
Social performance (SOCP)	SOCP1	Number of work accidents for employees	5	55.56%
	SOCP2	Number of customers who have been involved in an accident in the supermarket area	4	44.44%
	SOCP3	Number of suppliers/contractors have been involved in an accident in the supermarket area	5	55.56%
	SOCP4	Employee turnover rate	5	55.56%
	SOCP5	The satisfaction ratio of investor	4	44.44%
	SOCP6	The satisfaction ratio of government	3	33.33%
	SOCP7	The satisfaction ratio of employee	6	66.67%
	SOCP8	The satisfaction ratio of supplier (or contractor)	6	66.67%
	SOCP9	The satisfaction ratio of customer	2	22.22%
	SOCP10	The satisfaction ratio of community	3	33.33%
Environmental performance (ENVP)	ENVP1	The ratio of food waste recycled	4	44.44%
	ENVP2	The ratio of electricity consumption from renewable energy systems (or clean energy)	5	55.56%
	ENVP 3	The unavailable waste ratio	5	55.56%
	ENVP4	The ratio of water reused	7	77.78%
Economic performance (ECOP)	ECOP1	Current ratio	3	33.33%
	ECOP2	Quick ratio	5	55.56%
	ECOP3	Leverage ratio	6	66.67%
	ECOP4	Average collection period	6	66.67%
	ECOP5	Inventory turnover ratio	5	55.56%
	ECOP6	Return on assets	8	88.89%
	ECOP7	Free cash flow ratio	2	22.22%
	ECOP8	Gross profit margin	2	22.22%
	ECOP9	Operating profit margin	7	77.78%
	ECOP10	Return on equity	6	66.67%
	ECOP11	Cash cycle	4	44.44%
	ECOP12	Net profit ratio	6	66.67%
	ECOP13	Acid ratio	3	33.33%
Organization image performance (OIMP)	OIMP1	The number of ethical complaints	7	77.78%
	OIMP2	The good organization image ratio from the public	6	66.67%
	OIMP3	The number of news programs communicating the bad image of the organization	5	55.56%
	OIMP4	Trust of stakeholders to the organization	4	44.44%

* A total of nine key informants.

(the frequency is between 2 and 6 or from 22.22% to 66.67%). Then the draft sub-indicators of social performance with a score equal to or greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.7. Draft Sub-Indicators of Environmental Performance

The findings from the in-depth interviews about the draft sub-indicators of environmental performance that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in Table 9 (the frequency is between 4 and 7 or from 44.44% to 77.78%). Then the draft sub-indicators of environmental performance with a score greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.8. Draft Sub-Indicators of Economic Performance

The findings from the in-depth interviews about the draft sub-indicators of economic performance that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in Table 9 (the frequency is between 2 and 7 or from 22.22% to 77.78%). Then the draft sub-indicators of economic performance with a score equal to or greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

3.2.9. Draft Sub-Indicators of Organization Image Performance

The findings from the in-depth interviews about the draft sub-indicators of organization image performance that are important for green supermarket evaluation, as well as the frequency and percentage of selected draft sub-indicators are shown in Table 9 (the frequency is between 4 and 7 or from 44.44% to 77.78%). Then the draft sub-indicators of organization image performance with a score greater than 2 points (or ≥22.22%) were selected for consideration as draft sub-indicators for green supermarket evaluation.

From the findings of the in-depth interview about the draft sub-indicators, we found that some indicators had a score of only 2 points; however, the draft sub-indicators were deemed acceptable because the key informants’ s opinions were consistent among two or more persons, which is typical for non-simultaneous interview.

3.3. Development of Sub-Indicator Detail

After the draft sub-indicators had been defined, the draft sub-indicators were interpolated by five experts from the government agencies that set up the green business standards. In addition, the sub-indicator details were also identified by these five experts from the government agencies. The sub-indicators that were renamed are G_PD4, G_PD6, and G_PD7. G_PD4 was renamed as “The ratio of product with green packaging”, G_PD6 was renamed as “The ratio of the number of customers waiting in the payment queue for more than 1 min”, and G_PD7 was renamed as “the number of non green packaging bags received by customer”. The type of sub-indicator measure consisted of nominal scale (Yes/No), count scale, and ratio scale. The sub-indicator score is between one and three and it is mostly a monthly evaluation (the first 3 business days of every month period for evaluating the results of the previous month). The sub-indicator detail is illustrated in

Table 10. Sub-indicator detail.

Codes	Type of Measure	Criterion	Score of Indicator	Codes	Measured Type	Criterion	Score of Indicator
GPUR1	Yes/No	Yes	3	GEES10	Yes/No	Yes	3
GPUR2	Ratio	Ratio obtained	3	GEES11	Yes/No	Yes	3
GPUR3	Yes/No	Yes	2	GEES12	Yes/No	Yes	3
GPUR4	Yes/No	Yes	2	GEES13	Yes/No	Yes	3
GPUR5	Yes/No	Yes	2	GEES14	Yes/No	Yes	3
GPUR6	Ratio	Ratio obtained	3	GEES15	Yes/No	Yes	3
GPUR7	Ratio	Ratio obtained	3	GEES16	Yes/No	Yes	3
GPUR8	Ratio	Ratio obtained	3	GEES17	Yes/No	Yes	3
GPUR9	Yes/No	Yes	2	GEES18	Yes/No	Yes	3
GPUR10	Ratio	Ratio obtained	2	GEES19	Yes/No	Yes	3
GPUR11	Yes/No	Yes	3	GEES20	Yes/No	Yes	3
GPUR12	Ratio	Ratio obtained	3	GTRA1	Yes/No	Yes	2
GPUR13	Yes/No	Yes	2	GTRA2	Yes/No	Yes	2
GPUR14	Yes/No	Yes	2	GTRA3	Yes/No	Yes	2
GPUR15	Yes/No	Yes	2	GTRA4	Ratio	Ratio obtained	3
GPUR16	Count	0	2	GTRA5	Yes/No	Yes	2
GPUR17	Count	0	2	GTRA6	Ratio	Ratio obtained	3
GSTO1	Yes/No	Yes	2	GTRA7	Count	0	3
GSTO2	Yes/No	Yes	2	GTRA8	Ratio	Ratio obtained	3
GSTO3	Yes/No	Yes	2	GTRA9	Count	0	3
GSTO4	Ratio	Ratio obtained	2	SOCP1	Count	0	1
GSTO5	Ratio	Ratio obtained	2	SOCP2	Count	0	1
GSTO6	Ratio	0%	3	SOCP3	Count	0	1
GSTO7	Yes/No	Yes	3	SOCP4	Ratio	<10%	1
GSTO8	Yes/No	Yes	3	SOCP5	Ratio	Ratio obtained	2
GSTO9	Count	0	3	SOCP6	Ratio	Ratio obtained	2
GSER1	Yes/No	Yes	2	SOCP7	Ratio	Ratio obtained	2
GSER2	Yes/No	Yes	2	SOCP8	Ratio	Ratio obtained	2
GSER3	Yes/No	Yes	3	SOCP9	Ratio	Ratio obtained	2
GSER4	Yes/No	Yes	2	SOCP10	Ratio	Ratio obtained	2
GSER5	Yes/No	Yes	2	ENVP1	Ratio	Ratio obtained	3
GSER6	Yes/No	Yes	2	ENVP2	Ratio	Ratio obtained	3
GSER7	Ratio	100%	3	ENVP 3	Ratio	Ratio obtained	3
GSER8	Count	0	3	ENVP4	Ratio	Ratio obtained	3
GSER9	Ratio	100%	3	ECOP1	Ratio	>200%	1
GSER10	Ratio	100%	3	ECOP2	Ratio	>100%	1
GSER11	Ratio	Ratio obtained	3	ECOP3	Ratio	>40%	1
GSER12	Yes/No	Yes	2	ECOP4	Ratio	<40	1
GSER13	Ratio	0%	3	ECOP5	Ratio	>200%	1
GSER14	Yes/No	Yes	3	ECOP6	Ratio	>8%	1
GSER15	Yes/No	Yes	3	ECOP7	Ratio	>20%	1
GSER16	Yes/No	Yes	2	ECOP8	Ratio	>30%	1
GSER17	Ratio	Ratio obtained	2	ECOP9	Ratio	>20%	2
GEES1	Yes/No	Yes	3	ECOP10	Ratio	>15%	3
GEES2	Yes/No	Yes	3	ECOP11	Count	2	3
GEES3	Yes/No	Yes	3	ECOP12	Ratio	>10%	3
GEES4	Yes/No	Yes	3	ECOP13	Ratio	>200%	1
GEES5	Yes/No	Yes	3	OIMP1	Count	0	3
GEES6	Yes/No	Yes	3	OIMP2	Ratio	Ratio obtained	3
GEES7	Yes/No	Yes	3	OIMP3	Count	0	3
GEES8	Yes/No	Yes	3	OIMP4	Ratio	Ratio obtained	3
GEES9	Yes/No	Yes	3

.

3.4. Development of Green Supermarket Evaluation Model

Definition of Key Parameters Used in the Proposed Evaluation Model:

GI	The green degree of the first level (or composite indicator)
GII	The green degree of the second level
GIII	The green degree of the third level
GPURi	The set of sub-indicators for green procurement
GSTOi	The set of sub-indicators for green storage
GSERi	The set of sub-indicators for green service
GTRAi GEESi	The set of sub-indicators for green transportation The set of sub-indicators for green environmental and energy management system
SOCPi	The set of sub-indicators for social performance
ENVPi	The set of sub-indicators for environmental performance
ECOPi	The set of sub-indicators economic performance
OIMPi	The set of sub-indicators organization image
GGPRO	The green degree of green process
GGPUR	The green degree of green procurement
GGSTO	The green degree of green storage
GGSER	The green degree of green service
GGTRA GGEES	The green degree of green transportation The green degree of green environmental and energy management system
GSOCP	The green degree of social performance
GENVP	The green degree of environmental performance
GECOP	The green degree of economic performance
GOIMP	The green degree of organization image performance
GGPUR	The green degree of the set of sub-indicators for green procurement
GGSTOi	The green degree of the set of sub-indicators for green storage
GGSERi	The green degree of the set of sub-indicators for green service
GGTRAi GGEESi	The green degree of the set of sub-indicators for green transportation The green degree of the set of sub-indicators for green environmental and energy management system
GSOCPi	The green degree of the set of sub-indicators for social performance
GENVPi	The green degree of the set of sub-indicators for environmental performance
GECOPi	The green degree of the set of sub-indicators for economic performance
GOIMPi	The green degree of the set of sub-indicators for organization image performance
β of GPUR	Indirect influence of green procurement on the green process
β of GSTO	Indirect influence of green storage on the green process
β of GSER	Indirect influence of green service on the green process
β of GTRA β of GEES	Indirect influence of green transportation on the green process Indirect influence of green environmental and energy management system on the green process
β of GPRO	Indirect influence of green process on the green supermarket
β of SOCP	Direct influence of social performance on the green supermarket
β of ENVP	Direct influence of environmental performance on the green supermarket
β of ECOP	Direct influence of economic performance on the green supermarket
β of OIMP	Direct influence of organization image performance on the green supermarket

3.4.1. Determine the Green Supermarket Evaluation Model

From the SEM model (see Figure 3) and the development of sub-indicators in Section 3.2, the green supermarket evaluation is divided into three levels, two factors, nine major indicators (nine sub-factors), and a total of one hundred one sub-indicators. The main sub-indicators are green procurement, green storage, green service, and green transportation in order to evaluate the green degree of green supermarket, which refers to the determination method of the evaluation model on the hierarchy of the green degree of the green supply chain [31]. In this work, the green degree can be divided into every aspect of the indicator from the hierarchical step model as follows:

• G_I = {green degree of green supermarket as 0–1 or 0–100%} $\approx$ 0.941 × GOUT = G_II
• G_II = {G_GPRO, G_SOCP, G_ENVP, G_ECOP, G_OIMP}
• G_II = {G_GPUR, G_GSTO, G_GSER, G_GTRA, G_GEES, G_SOCP, G_ENVP, G_ECOP, G_OIMP}
• G_III = {G_GPUR1, …, G_GPUR17; G_GSTO1, …, G_GSTO9; G_GSER1, …, G_GSER17;
• G_GTRA1, …, G_GTRA9; G_GEES1, …, G_GEES20; G_SOCP1, …, G_SOCP13; G_SOCP1,…, G_SOCP4;
• G_ECOP1, …, G_ECOP10; G_OIMP1, …, G_OIMP4;}

Therefore:

• Green supermarket (G_I) = G_II = G_III

3.4.2. Mathematical Model for Green Supermarket Evaluation

From the SEM model and hierarchical model, the evaluation model for the green degree of green supermarket (as 0–1 or 0–100%) can be developed as follows;

Green supermarket (G_I) ₌ G_II

(1)

G_II = G_GPRO + G_SOCP + G_ENVP + G_ECOP + G_OIMP

(2)

When:

$${\mathrm{G}}_{\mathrm{GPRO}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GPRO}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }1}=\frac{0.903 }{4.093}=0.222$$

$${\mathrm{G}}_{\mathrm{SOCP}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{SOCP}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }1}=\frac{0.827 }{4.093}=0.202$$

$${\mathrm{G}}_{\mathrm{ENVP}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{ENVP}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }1}=\frac{0.814 }{4.093}=0.198$$

$${\mathrm{G}}_{\mathrm{ECOP}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{ENVP}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }1}=\frac{0.708}{4.093}=0.173$$

$${\mathrm{G}}_{\mathrm{OIMP}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{ENVP}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }1}=\frac{0.841}{4.093}=0.205$$

And when (see Table 5):

Sum of β1 = β of GPRO + β of SOCP + β of ENVP + β of ECOP + β of OIMP

Sum of β1 = 0.903 + 0.827 + 0.814 + 0.708 + 0.841 = 4.093

G_II = (G_GPUR + G_GSTO + G_GSER + G_GTRA+ G_GEES) + G_SOCP + G_ENVP + G_ECOP + G_OIMP

(3)

When:

G_GPRO = G_GPUR + G_GSTO + G_GSER + G_GTRA+ G_GEES

$${\mathrm{G}}_{\mathrm{GPUR}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GPUR}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }2} \times {\mathrm{G}}_{\mathrm{GPRO}}=\frac{0.918 }{4.599} \times 0.222=0.044$$

$${\mathrm{G}}_{\mathrm{GSTO}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GSTO}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }2} \times {\mathrm{G}}_{\mathrm{GPRO}}=\frac{0.907 }{4.599} \times 0.222=0.044$$

$${\mathrm{G}}_{\mathrm{GSER}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GSER}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }2} \times {\mathrm{G}}_{\mathrm{GPRO}}=\frac{0.911 }{4.599} \times 0.222=0.044$$

$${\mathrm{G}}_{\mathrm{GTRA}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GTRA}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }2} \times {\mathrm{G}}_{\mathrm{GPRO}}=\frac{0.932}{4.599} \times 0.222=0.045$$

$${\mathrm{G}}_{\mathrm{GEES}}=\frac{\mathsf{\beta } \mathrm{of} \mathrm{GGES}}{\mathrm{Sum} \mathrm{of} \mathsf{\beta }2} \times {\mathrm{G}}_{\mathrm{GPRO}}=\frac{0.931}{4.599} \times 0.222=0.045$$

And when (see Table 5):

Sum of β2 = β of GPUR + β of GSTO + β of GSER + β of GTRA+ β of GEES

Sum of β2 = 0.918 + 0.907 + 0.911 + 0.932 + 0.931 = 4.599

G_{II I} = G_II

(4)

$$\begin{gathered} {\mathrm{G}}_{\mathrm{III}}={{\displaystyle \sum }}_1^{17}{\mathrm{G}}_{\mathrm{GPURi}}+{{\displaystyle \sum }}_1^9{\mathrm{G}}_{\mathrm{GSTOi}}+{{\displaystyle \sum }}_1^{17}{\mathrm{G}}_{\mathrm{GSERi}}+{{\displaystyle \sum }}_1^9{\mathrm{G}}_{\mathrm{GTRAi}}+{{\displaystyle \sum }}_1^{20}{\mathrm{G}}_{\mathrm{GEESi}} \\ +{{\displaystyle \sum }}_1^{10}{\mathrm{G}}_{\mathrm{SOCPi}}+{{\displaystyle \sum }}_1^4{\mathrm{G}}_{\mathrm{ENVPi}}+{{\displaystyle \sum }}_1^{13}{\mathrm{G}}_{\mathrm{ECOPi}}+{{\displaystyle \sum }}_1^4{\mathrm{G}}_{\mathrm{OIMPi}} \end{gathered}$$

(5)

According to the above Equation (5), the green degree of sub-indicators (see

Table 11. Sub-indicator weights (third level).

Codes	Score of Indicator	Indicator Weight (β)	Codes	Score of Indicator	Indicator Weight (β)
GPUR1	3	0.00321951219512195	GEES1	3	0.00225
GPUR2	3	0.00321951219512195	GEES2	3	0.00225
GPUR3	2	0.00214634146341463	GEES3	3	0.00225
GPUR4	2	0.00214634146341463	GEES4	3	0.00225
GPUR5	2	0.00214634146341463	GEES5	3	0.00225
GPUR6	3	0.00321951219512195	GEES6	3	0.00225
GPUR7	3	0.00321951219512195	GEES7	3	0.00225
GPUR8	3	\0.00321951219512195	GEES8	3	0.00225
GPUR9	2	0.00214634146341463	GEES9	3	0.00225
GPUR10	2	0.00214634146341463	GEES10	3	0.00225
GPUR11	3	0.00321951219512195	GEES11	3	0.00225
GPUR12	3	0.00321951219512195	GEES12	3	0.00225
GPUR13	2	0.00214634146341463	GEES13	3	0.00225
GPUR14	2	0.00214634146341463	GEES14	3	0.00225
GPUR15	2	0.00214634146341463	GEES15	3	0.00225
GPUR16	2	0.00214634146341463	GEES16	3	0.00225
GPUR17	2	0.00214634146341463	GEES17	3	0.00225
Sum	41	0.044	GEES18	3	0.00225
GSTO1	2	0.004	GEES19	3	0.00225
GSTO2	2	0.004	GEES20	3	0.00225
GSTO3	2	0.004	Sum	60	0.045
GSTO4	2	0.004	SOCP1	1	0.012625
GSTO5	2	0.004	SOCP2	1	0.012625
GSTO6	3	0.006	SOCP3	1	0.012625
GSTO7	3	0.006	SOCP4	1	0.012625
GSTO8	3	0.006	SOCP5	2	0.025250
GSTO9	3	0.006	SOCP6	2	0.025250
Sum	22	0.044	SOCP7	2	0.025250
GSER1	2	0.00204651162790698	SOCP8	2	0.025250
GSER2	2	0.00204651162790698	SOCP9	2	0.025250
GSER3	3	0.00306976744186047	SOCP10	2	0.025250
GSER4	2	0.00204651162790698	Sum	16	0.202
GSER5	2	0.00204651162790698	ENVP1	3	0.0495
GSER6	2	0.00204651162790698	ENVP2	3	0.0495
GSER7	3	0.00306976744186047	ENVP 3	3	0.0495
GSER8	3	0.00306976744186047	ENVP4	3	0.0495
GSER9	3	0.00306976744186047	Sum	12	0.198
GSER10	3	0.00306976744186047	ECOP1	1	0.00865
GSER11	3	0.00306976744186047	ECOP2	1	0.00865
GSER12	2	0.00204651162790698	ECOP3	1	0.00865
GSER13	3	0.00306976744186047	ECOP4	1	0.00865
GSER14	3	0.00306976744186047	ECOP5	1	0.00865
GSER15	3	0.00306976744186047	ECOP6	1	0.00865
GSER16	2	0.00204651162790698	ECOP7	1	0.00865
GSER17	2	0.00204651162790698	ECOP8	1	0.00865
Sum	43	0.044	ECOP9	2	0.01730
GTRA1	2	0.00391304347826087	ECOP10	3	0.02595
GTRA2	2	0.00391304347826087	ECOP11	3	0.02595
GTRA3	2	0.00391304347826087	ECOP12	3	0.02595
GTRA4	3	0.00586956521739130	ECOP13	1	0.00865
GTRA5	2	0.00391304347826087	Sum	20	0.173
GTRA6	3	0.00586956521739130	OIMP1	3	0.05125
GTRA7	3	0.00586956521739130	OIMP2	3	0.05125
GTRA8	3	0.00586956521739130	OIMP3	3	0.05125
GTRA9	3	0.00586956521739130	OIMP4	3	0.05125
Sum	23	0.045	Sum	12	0.205

) of various major indicators can be described as follows:

(1)

The green degree of sub-indicators of green procurement:

$${\mathrm{G}}_{\mathrm{GPURi}}=\left(\frac{{\mathrm{G}}_{\mathrm{GPUR}}\times { \mathrm{Score} \mathrm{of} \mathrm{GPUR}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^{17}{\mathrm{GPUR}}_{\mathrm{i}}}\right)$$

(6)

(2)

The green degree of sub-indicators of green storage:

$${\mathrm{G}}_{\mathrm{GSTOi}}=\left(\frac{{ \mathrm{G}}_{\mathrm{GSTO}}\times { \mathrm{Score} \mathrm{of} \mathrm{GSTO}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^9{\mathrm{GSTO}}_{\mathrm{i}}}\right)$$

(7)

(3)

The green degree of sub-indicators of green service:

$${\mathrm{G}}_{\mathrm{GSERi}}=\left(\frac{{\mathrm{G}}_{\mathrm{GSER}}\times { \mathrm{Score} \mathrm{of} \mathrm{GSER}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^{17}{\mathrm{GSER}}_{\mathrm{i}}}\right)$$

(8)

(4)

The green degree of sub-indicators of green transportation:

$${\mathrm{G}}_{\mathrm{GTRAi}}=\left(\frac{{\mathrm{G}}_{\mathrm{GTRA}}\times { \mathrm{Score} \mathrm{of} \mathrm{GTRA}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^9{\mathrm{GTRA}}_{\mathrm{i}}}\right)$$

(9)

(5)

The green degree of sub-indicators of green environmental and energy management system:

$${{\mathrm{G}}_{\mathrm{GEESi}}}_{ }=\left(\frac{{\mathrm{G}}_{\mathrm{GEES}}\times { \mathrm{Score} \mathrm{of} \mathrm{GEES}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^{20}{\mathrm{GEES}}_{\mathrm{i}}}\right)$$

(10)

(6)

The green degree of sub-indicators of social performance:

$${\mathrm{G}}_{\mathrm{SOCPi}}=\left(\frac{{\mathrm{G}}_{\mathrm{EFSO}}\times { \mathrm{Score} \mathrm{of} \mathrm{SOCP}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^{10}{\mathrm{SOCP}}_{\mathrm{i}}}\right)$$

(11)

(7)

The green degree of sub-indicators of environmental performance:

$${\mathrm{G}}_{\mathrm{ENVPi}}=\left(\frac{{\mathrm{G}}_{\mathrm{ENVP}}\times { \mathrm{Score} \mathrm{of} \mathrm{ENVP}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^4{\mathrm{ENVP}}_{\mathrm{i}}}\right)$$

(12)

(8)

The green degree of sub-indicators of economic performance:

$${\mathrm{G}}_{\mathrm{ECOPi}}=\left(\frac{{\mathrm{G}}_{\mathrm{ECOP}}\times { \mathrm{Score} \mathrm{of} \mathrm{ECOP}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^{13}{\mathrm{ECOP}}_{\mathrm{i}}}\right)$$

(13)

(9)

The green degree of sub-indicators of organization image performance:

$${\mathrm{G}}_{\mathrm{OIMPi}}=\left(\frac{{\mathrm{G}}_{\mathrm{OIMP}}\times { \mathrm{Score} \mathrm{of} \mathrm{OIMP}}_{\mathrm{i}}}{{{\displaystyle \sum }}_1^4{\mathrm{OIMP}}_{\mathrm{i}}}\right)$$

(14)

Therefore:

$$\begin{gathered} \mathrm{Green} \mathrm{degree} \mathrm{of} \mathrm{green} {\mathrm{supermarket}}_{ }={{\displaystyle \sum }}_1^{17}{\mathrm{G}}_{\mathrm{GPURi}}+{{\displaystyle \sum }}_1^9{\mathrm{G}}_{\mathrm{GSTOi}}+{{\displaystyle \sum }}_1^{17}{\mathrm{G}}_{\mathrm{GSERi}}+ \\ +{{\displaystyle \sum }}_1^9{\mathrm{G}}_{\mathrm{GTRAi}} +{{\displaystyle \sum }}_1^{20}{\mathrm{G}}_{\mathrm{GEESi}}+{{\displaystyle \sum }}_1^{10}{\mathrm{G}}_{\mathrm{SOCPi}} \\ +{{\displaystyle \sum }}_1^4{\mathrm{G}}_{\mathrm{ENVPi}}+{{\displaystyle \sum }}_1^{13}{\mathrm{G}}_{\mathrm{ECOPi}}+{{\displaystyle \sum }}_1^4{\mathrm{G}}_{\mathrm{OIMPi}} \end{gathered}$$

(15)

Example:

From Table 8 and Table 10, the GPUR₁ and GPUR₂ (the sub-indicators of green procurement) are selected as two cases in this green degree calculation.

GPUR₁ means “There is an evaluation system for green product standards (green label, green livestock, etc.)”, which considers the type of measure to be “Yes/No”. If the criterion is “Yes”, then the score of the indicator equals “3”.

If GPUR₁ is evaluated as “Yes” then the score of the indicator equals “3” and therefore the green degree (G_GPUR1) of GPUR₁ equals “0.00321951219512195” $\left(\frac{0.044\times 3}{41}\right)$, whereas if GPUR₁ is evaluated as “No” then the score of the indicator equals “0” and therefore the green degree (G_GPUR1) of GPUR₁ equals “0” $\left(\frac{0.044\times 0}{41}\right).$

GPUR₂ means “The ratio of products that have green standards”, which considers the type of measure to be “Ratio”. If the criterion is “Ratio obtained”, then the score of the indicator equals “3”.

If GPUR₂ is evaluated as “100%” then the score of the indicator equals “3”. Therefore, the green degree (G_GPUR2) of GPUR₂ equals “0.00321951219512195” $\left(\frac{0.044\times \left(3\times 100\%\right)}{41}\right)$. Alternately, if GPUR₂ is evaluated as “50%”, then the score of the indicator equals “1.5”, and therefore the green degree (G_GPUR1) of GPUR₂ equals “0.0016097560975609756098” $\left(\frac{0.056\times \left(3\times 50\%\right)}{41}\right).$

4. Discussion

A green supermarket evaluation model based on green process and green output is proposed in this research. The developed model encompasses multi-level indicators in green supermarket management throughout the supply chain. According to the SEM model, the green indicators for green supermarket evaluation are divided into two categories with nine major-indicators. The major-indicators of the green process consist of green procurement, green storage, green service, green transportation and green energy and environmental management system, while the major-indicators of green output consist of social performance, environmental performance, economic performance, and organization image performance. In addition, the major-indicator weight indicates that social performance is the most important, followed in order by organization image performance, environmental performance, economic performance, green procurement, green storage, green transportation, and green service. Earlier research on the incorporation of social responsibility concepts into business activities has demonstrated that it could have a significant impact on a company’s finances [32]. Furthermore, environmental management performance indicators are an important consideration. Previous research demonstrated that organizations which adopt proactive environmental management strategies could develop distinctive skills and competencies that enhance their business competitiveness [33]. For this research, the results also found that the proposed green supermarket evaluation model is divided into one hundred one sub-indicators, comprised of seventeen sub-indicators of green procurement, nine sub-indicators of green storage, seventeen sub-indicators of green service, nine sub-indicators of green transportation, twenty sub-indicators of green environmental and energy management system, ten sub-indicators of social performance, four sub-indicators of environmental performance, thirteen sub-indicators of economic performance, and four sub-indicators of organization image performance to evaluate the green degree of green supermarket.

For this study, the measure level for the green degree of green supermarket is calculated as a ratio scale, and the green degree of green supermarket as 0–1 or 0–100%. Another intriguing element is that the major green metrics, such as social performance, environmental performance, economic performance, and organization image performance, may all be evaluated by a single person for summative review in a green supermarket. Finally, the major indicators that cover the supply chain management (SCM) perspective, such as green procurement, green storage, green service, and green transportation, are reviewed for formative evaluation, making the green supermarket evaluation more appropriate and complete. The findings clearly reveal that social performance indicators have a significant influence on green supermarket perception. This is due to the higher efficiency provided by social and environmental initiatives combined with greener procedures, which have created opportunities for consumers to contribute to long-term environmental conservation [34]. According to other studies, positive impacts may be significant mainly in specific aspects of environmental performance or competitiveness [34,35]. According to some past research, non-economic considerations can drive voluntary contributions to corporate social and environmental responsibilities more strongly than economic incentives [35]. In addition, the details of the green procurement indicators (the ratio of products that have green standards, and the ratio of products that have green label standards) in this study are consistent with those from an earlier study about the similarities and differences of the features and the importance of a green office standard for sustainable environmental management [36]. This study also indicated that green procurement is an evaluation method on purchasing items. The certified green label products which can be recycled should be selected. The details of green service (green service affects environmental performance) in this study are consistent with those from an earlier study on performance implications and the role of environmental management systems [37]. The findings of this study indicate that green service is also positively related to environmental performance.

Finally, the findings of this present study serve as a basis for future development and improvement of an innovative green supermarket evaluation system for real-world application. Therefore, it is necessary to understand the concept of green indicators in various dimensions. Further research should therefore be conducted to enhance the existing knowledge about green input factors and green context factors through various case studies of green supermarket evaluation. This is a significant requirement in order to achieve the relevant sustainable development goal, especially for promoting green supermarkets in many countries throughout the world.

5. Conclusions

There is a significant practical application of the integration of valuation theory and the green supply chain theory to develop the outcomes of green indicators for green supermarket evaluation. The results also revealed that the green indicators for green supermarket evaluation are classified into three levels, two components, nine major indicators, and a total of one hundred one sub-indicators. The major-indicator weight indicated that social performance is the most important, followed in order by organization image performance, environmental performance, economic performance, green procurement, green storage, green transportation, green service, and green environmental and energy management system. Therefore, this developed evaluation model is promising as an effective tool to motivate green supermarket development in developing countries, including Thailand in the near future.