Evaluation of the Environmental Cost of Integrated Inbound Logistics: A Case Study of a Gigafactory of a Chinese Logistics Firm

Abstract

In recent years, sustainable development has become an emerging trend in the logistics industry. Smart manufacturing factories pursue green logistics processes with lower energy consumption and reduced carbon emission. The environmental sustainability of the logistics process is widely acknowledged as an important issue. However, a standardized methodology for assessing the environmental cost of logistics-process-aided smart manufacturing is lacking. This paper presents a concept for determining the inbound logistics environmental cost (ILEC) of a gigafactory. Additionally, a novel structured methodology for ILEC assessment is proposed to uniformly describe the gigafactory’s logistics environmental cost, regarding the “double carbon” goal (peak carbon dioxide emissions and carbon neutrality). First, eight types of basic logistics activities and six logistics phases associated with the gigafactory’s inbound logistics are defined. The mapping relationships between the logistics phases and the basic logistics activities are constructed. Then, the novel concepts of environmental price cost (EPC) and environmental impact cost (EIC) are defined and presented. Finally, the ILEC of the gigafactory, including EPC and EIC, is assessed based on mapping relationships and an environmental cost model. We validate this model using the advanced Geely Automobile factory in China in order to analyze the actual inbound logistics environmental costs and how to assess its environmental price and environmental impact. Results from the data model show the environmental costs throughout the whole process and the detailed composition ratio of EPC and EIC in the inbound logistics. Based on the implementation of the ILEC model, our study helps gigafactories to identify critical logistics nodes through energy consumption and to measure the environmental performance of the inbound logistics process. Furthermore, our study helps gigafactories to develop practical environmental strategies.

1. Introduction

There has been an increased focus on environmental sustainability in recent years due to recent developments and the estimated future state of the climate [1]. Existing research reveals that logistics contribute substantially to greenhouse gas (GHG) emissions [2]. A total of 95% of GHG emissions come from energy consumption [3] and more than 20% of energy consumption can be attributed to logistics and transportation [4]. Emissions from the transport sector also account for the fastest-growing source of GHG emissions [5,6]. The logistics industry has become one of the most dominant carbon emission contributors in China [7]. To solve this problem, the country has proposed the double carbon goal to achieve a carbon peak by 2030 and carbon neutrality by 2060 [8]. In line with the global trend of green and sustainability, there is growing concern about energy availability and its impacts on the logistics industry [9].

The rapid development of state-of-the-art technologies has paved the way for new logistics and transportation models [10]. For example, new logistics transportation equipment and a new logistics model are used in the Tesla gigafactory to maximize the inbound logistics efficiency and reduce costs [11,12]. Inbound logistics refers to the optimization, integration, and management of the logistical flow of information, material goods, supply chain, and production and distribution within a fulfillment or distribution center, which are important activities in a smart manufacturing factory [13]. Reducing inbound logistics’ energy consumption and pollution is key to the logistics industry’s sustainable development [14]. However, there is currently a scarcity of contributions to environmental cost assessments of gigafactories’ inbound logistics, and even specific inbound logistics’ energy consumption and emission figures are often incomplete. A practical inbound logistics environmental cost model to quantify the environmental costs of each procedure in the entire logistics process is lacking [15]. Therefore, we studied the construction of gigafactory inbound logistics systems and define the environmental cost of inbound logistics. Additionally, we comprehensively measured and evaluated the environmental cost of inbound logistics in response to the new demand for models of the logistics of gigafactories.

Given these goals, our study aims to fill the highlighted gap by proposing a structured methodology for accessing the environmental costs of inbound logistics in terms of energy consumption costs and generated GHG emissions. In this study, a novel assessment model of the inbound logistics environmental cost (ILEC) is proposed to uniformly describe the environmental cost of the inbound logistics process in a gigafactory. First, to reduce the complexity of the inbound logistics process, the model is divided into eight types of basic logistics activities; mapping relationships between the six phases of the inbound logistics process and the eight types of basic logistics activities are constructed. Additionally, the novel concepts of the environmental price cost (EPC) and the environmental impact cost (EIC) are defined and presented. Furthermore, EPC and EIC calculation methods for each basic logistics activity are given. The ILEC of the gigafactory, including the EPC and EIC, is calculated based on the mapping relationships. Our study provides a novel idea and potential application prospect for the cost assessment of the gigafactory’s logistics environment. Our study provides a novel perspective for identifying the key logistics nodes for gigafactories through energy consumption. The environmental performance of the inbound logistics process can then be measured. Furthermore, our study helps to develop environmental strategies for gigafactories.

The paper is structured as follows. Section 2 reviews the current status of the double-carbon-goal-directed inbound logistics industry and the related logistics costs and GHG emissions studies. Section 3 presents the methodology for this study. The ILEC model is established in Section 4. In Section 5, the ILEC is verified using the Geely Automobile Group gigafactory case study. The conclusions and future studies are outlined in the last section.

2. Literature Review

This section reviews related research, categorized into three dimensions: inbound logistics research, logistics process cost research, and logistics GHG emissions research.

2.1. Inbound Logistics Research

Inbound logistics is a subdivision of the overall logistics system and is an important activity in supply chain management [16] that has been studied relatively extensively. For example, Wang J et al., described a new JIT (Just In Time)-based inbound logistics model for cruise ship construction that provides high-quality supply chain management for inbound logistics [17]. Boysen N et al., described the basic process of parts logistics in the automotive industry, from the initial call for orders to the return of empty parts to containers [18]. Costa et al., identified how the relationships between inbound logistics (IL) activities can contribute to organizational resilience. Two in-depth case-based studies were conducted in the dairy industry [19]. Fink and Benz proposed a process-oriented approach for measuring and planning IL flexibility in global production networks [14]. Zhang et al., studied the container transport of Changan Ford auto parts logistics. They re-engineered the existing transport process based on a cost analysis derived from the program evaluation and review technique [20]. Marques et al., addressed the integration of the planning decisions concerning inbound logistics (from the suppliers to the mill) and outbound logistics (from the mill to the customers) in an industrial setting [21]. Mao et al., investigated a new logistics method that collects automobile parts by integrating the progress lane into the corresponding vehicle routing problem [22]. Baller et al., presented a mixed-integer linear programming approach to solve the optimization of inbound logistics from the first-tier suppliers at the aggregation level of a factory [23]. Agrawal et al., used supply chain visibility to improve inbound logistics [24]. Overall, most of the research on inbound logistics focuses on supply chain management or the optimization of inbound logistics processes, and there are few studies on the structuring of activities in the inbound logistics process.

2.2. Logistics Cost Study

Logistics costs are a significant and relevant proportion of the overall business costs, often exceeding 10 percent of company turnover. However, the definitions of logistics cost are many and vary considerably [25]. Engblom Janne, Solakivi Tomi, and Töyli Juuso et al., (2012) claimed that the total logistics cost consists of six individual components: transport, warehousing, inventory carrying, logistics administration, transport packaging, and the indirect costs of logistics. Their results indicate the need for caution when interpreting changes in logistics costs and simultaneously controlling the effects of background variables [26]. The contribution of Li et al., (2019) presents a method for minimizing the total costs, including vehicle operating cost, quality loss cost, product freshness cost, penalty cost, energy cost, and GHG emissions cost [27]. Minken (2019) presented a more detailed model of the transport, loading, and unloading costs. Transport costs were shown to be highly relevant when determining the optimal order quantity in the model [28]. Hernandez et al., emphasized that green logistics is an important factor in reducing logistics costs [29]. With the current emphasis on sustainable development, logistics environmental costs are gaining increasing attention among academic researchers and industrial practitioners [30].

2.3. Research on Logistics GHG Emissions

The energy consumption of logistics processes is the basis of carbon emissions [31]. Liu et al., (2023) examined the spatial spillover effects of the Chinese logistics industry on carbon emissions using the spatial Durbin model based on panel data from 30 Chinese provinces from 2000 to 2019 [32]. Villamizar et al., created a discrete event simulation model to understand the environmental impact of inbound logistics using fast shipping [33]. Hakan et al., described a model to calculate the total ecological pollution cost based on the environmental cost of carbon dioxide. The difference between a diesel engine using diesel fuel and an engine using biodiesel fuel was analyzed [34]. Fahimina et al., presented a tactical supply chain planning model that can be used to investigate tradeoffs between cost and environmental degradation, including carbon emissions, energy consumption, and waste generation [35]. Jehean Sim et al., assessed the emissions of seven air pollutants and four types of environmental impact potentials from finished vehicles transported using three transportation modes [36]. Sara Perotti et al., proposed a structured model to quantify both consumed and generated greenhouse gas (GHG) emissions, adopting a three-phase methodology that combined multiple methods [15]. Lei Yang et al., proposed a method for measuring carbon emissions in the port-integrated logistics system [37]. Xu et al., investigated the influence of incentive and mandatory environmental regulations on energy efficiency and carbon dioxide (CO₂) emissions in the logistics industry [4]. Wang et al., studied the dynamic relationships between growth in the logistics industry [38]. In recent years, more studies have shifted their focus to both energy consumption and carbon emissions in the logistics industry.

2.4. Summary

As determined from the literature review, there are many studies on cost assessments and environmental issues regarding the inbound logistics process, and some scholars have also begun to study environmental issues such as energy consumption and carbon emissions. Most of the existing research on the environmental problems of logistics focuses on a specific node of the logistics process, such as warehouses or suppliers. There are also some studies on logistics processes such as transportation processes. However, little has been done to analyze the environmental aspects of the entire inbound logistics process. There are also very few studies that have conducted a structured analysis of the entire inbound logistics process. Therefore, this paper helps to fill this research gap. It not only structurally analyzes the complete inbound logistics process, but also considers environmental issues such as energy consumption and carbon emissions during the logistics process.

3. Methodology

The inbound logistics process of a gigafactory involves all logistics phases and activities that occur, from the suppliers and the distribution center to the assembly line. Each logistics phase includes one or more logistics activities. Logistics activities are the basis of inbound logistics. Therefore, we next present the calculation model of the environmental price cost and environmental impact cost of logistics activities to assess the ILEC. The architecture of the ILEC is shown in Figure 1.

3.1. The Architecture of Inbound Logistics

There exist three nodes within the inbound logistics process of a gigafactory: the supplier, the distribution center, and the assembly line. The assembly line and distribution center are located within the gigafactory [39]. Based on the gigafactory’s inbound logistics process, the assembly line transmits demand information through an exclusive ERP system to the distribution center based on customer demand planning. Then, the distribution center formulates order plans according to inventory data and distributes them to the suppliers at all levels. Finally, the suppliers create replenishment and transportation plans based on the order plan and deliver the products to the distribution center via the designated transportation road [11]. At the distribution center, the components are stored quickly and subsequently delivered to the assembly line for production and assembly according to the pull production planning from the customers. The specific logistics phases and activities involved in the inbound logistics process are shown in Figure 2.

3.1.1. Six Logistics Phases

The inbound logistics process is divided into six phases: ordering, replenishment, transportation, storage, inventory management, and delivery. These six phases are explained as follows:

(1)

Ordering phase: The ordering phase is the starting point of gigafactory inbound logistics. The assembly line transmits information on the demand for component products to the distribution center. Then, the distribution center places orders to suppliers based on the inventory information in the warehouse.

(2)

Replenishment phase: The supplier makes replenishment and transportation plans after receiving the order. Generally, the first-level supplier stores the necessary products in a temporary storage area (located at the first-level supplier). The second-level supplier’s products will then be sent to the temporary storage area of the first-level supplier by the distribution center.

(3)

Transportation phase: the suppliers’ goods in the temporary storage area are assigned and transported by the distribution center to the warehouse by way of a milk run.

(4)

Storage phase: the distribution center sorts and stores goods in the warehouse according to the demand information of the assembly line and sends information about goods stored in the distribution center to the gigafactory and suppliers in real-time.

(5)

Inventory management phase: the distribution center monitors the inventory levels, predicts warehouse overflows (exceeding the storage capacity), and transmits inventory warning information, overflow prediction, and inventory data to the gigafactory.

(6)

Delivery phase: after receiving real-time assembly demand information from the assembly line, the distribution center will conduct timely distribution according to the pull production planning from the customers.

3.1.2. Eight Basic Logistics Activities

Logistics activities are the basis for assessing the ILEC. In this section, the logistics phase is divided into eight logistics activities. These specific logistics activities are as follows:

(1)

Information processing activity: An important activity throughout the whole gigafactory’s inbound logistics, which is generated by communication between all nodes. Basic activities are present in all phases.

(2)

Replenishment activity: the main activity that occurs in the replenishment phase, in which the supplier makes replenishment plans according to different order information.

(3)

Packaging activity: the activity occurring in the replenishment phase, in which the supplier packages and transports the commodities to be supplied according to specifications and other requirements.

(4)

Transport activity: The most important activity in inbound logistics, which occurs in the transport and distribution phases. It is an activity for the suppliers and the distribution center to transport and deliver goods needed by the gigafactory.

(5)

Storage activity: the main activity occurring in the storage phase, in which the distribution center sorts and stores goods in the warehouse according to the demand information of the assembly line.

(6)

Loading and unloading activity: an activity that occurs during the storage phase and accompanies the transportation and storage of goods.

(7)

Inventory management activity: the most important activity in the inventory management phase, in which the distribution center manages and constrains the warehouse facilities.

(8)

Circulation processing activity: the most important activity in the distribution phase, in which the distribution center detects and numbers goods and assists transportation to the gigafactory.

3.1.3. Mapping Relations between Logistics Phases and Basic Logistics Activities

Based on the architecture of inbound logistics, the mapping relationships between the six inbound logistics phases and eight basic logistics activities are defined. The ordering phase is controlled by the assembly line, which includes the processing of assembly line demand information. The replenishment and transportation phases are controlled by the supplier. During the replenishment phase, suppliers at all levels supply the required goods according to a pre-determined replenishment plan and subsequently pack them according to specific specifications and requirements. The replenishment activity is, therefore, the most critical logistics activity in the replenishment phase, accounting for 70% of the entire logistics phase, while the packaging activity accounts for 30%. In the transport phase, the supplier transports the goods based on a transport plan and transmits information about the goods in real-time. Transport is, therefore, the most critical logistics activity in the transport phase, accounting for 90% of the total logistics phase, while information transfer activities account for 10% of the total.

Meanwhile, the storage, inventory management, and delivery phases are controlled by the distribution center. In the storage phase, the distribution center sorts and stores the goods in a warehouse. Therefore, storage activities are the most critical logistics activities in the storage phase, which account for 70% of the entire logistics phase, while loading and unloading activities account for 30% of the total. In the inventory management phase, the distribution center undertakes the management and monitoring of the warehouse equipment and personnel and transmits warehouse information in real-time. Therefore, inventory management activities are the most critical logistics activities in the inventory management phase, accounting for 80% of the entire logistics phase, while information transmission activities account for 20% of the total in the delivery phase, the distribution center processes the goods and delivers them in a timely manner according to the customer’s pull production plan. Transport activities are therefore the most critical logistics activity in the delivery phase, accounting for 60% of the overall logistics phase, while distribution and processing activities account for 40% of the total. The specific mapping relationships are shown in Figure 3.

3.2. Calculation of the Inbound Logistics Environmental Cost

The ILEC is composed of two key components: the environmental price cost and the environmental impact cost of the inbound logistics process. The environmental price cost refers to the energy consumption of the logistics activities throughout the inbound logistics process. On the other hand, the environmental impact cost represents the carbon emissions resulting from energy consumption. Each logistics activity has a corresponding environmental price cost. Furthermore, the energy consumption of logistics activities inevitably produces a corresponding environmental impact cost. The details of the environmental cost, which are helpful for the environmental cost evaluation model in the following section, are as follows (Figure 4):

• Environmental Price Costs

The environmental price is the direct or indirect energy consumption of equipment or services (e.g., logistics information and packaging) in logistics activities. Energy consumption in the logistics process is the basis and source of carbon emissions. For transportation and delivery activities, fuel consumption by various vehicles is the main source of carbon emissions. For storage, inventory management, and loading and unloading activities, fixed warehouse facilities and mobile handling facilities are the main emission sources when managing and moving goods. As for information processing and replenishment as well as packaging activities, energy is unavoidably consumed through the utilization of personnel, communication facilities, and materials, leading to indirect carbon emissions.

2.

Environmental Impact Costs

The environmental impact cost pertains to the greenhouse gas emissions released during logistics activities, arising from various energy-consuming processes throughout the logistics process. An integrated inbound logistics system has four main carbon emission sources: carbon emissions from fuel combustion, carbon emissions from electrical energy consumption, carbon emissions from packaging material consumption, and carbon emissions from exhaust gas purification.

Figure 4. Inbound logistics environmental cost model framework.

Figure 4. Inbound logistics environmental cost model framework.

3.3. The Environmental Costs of Inbound Logistics Phases

The weighting of each logistics activity varies between the different logistics phases. Therefore, based on the definition of the inbound logistics process and the ILEC, this section assesses the environmental costs of each logistics phase. The following are the specific formulae for the calculation:

$$\left\{\begin{array}{l}{E}_{O\mathrm{r}de}\\ E_{\mathrm{Re}p}\\ E_{Tran}\\ E_{Stor}\\ E_{Inve}\\ E_{Del}\end{array}\right\}=\left\{\begin{array}{l}{E}_{Orde(EPC)}+E_{Orde(EIC)}\\ E_{Rep(EPC)}+E_{Rep(EIC)}\\ E_{Tran(EPC)}+E_{Tran(EIC)}\\ E_{Stor(EPC)}+E_{Stor(EIC)}\\ E_{Inve(EPC)}+E_{Inve(EIC)}\\ E_{Del(EPC)}+E_{Del(EIC)}\end{array}\right\}=\left\{\begin{array}{l}EP{C}_{Info}^1+EI{C}_{Info}^1\\ 0.7(EP{C}_{Rep}+EI{C}_{Rep})+0.3(EP{C}_{Pack}+EI{C}_{Pack})\\ 0.9(EP{C}_{Tran}+EI{C}_{Tran})+0.1(EP{C}_{Info}^2+EI{C}_{Info}^2)\\ 0.7(EP{C}_{Stor}+EI{C}_{Stor})+0.3(EP{C}_{L\&U}+EI{C}_{L\&U})\\ 0.8(EP{C}_{Inve}+EI{C}_{Inve})+0.2(EP{C}_{Info}^3+EI{C}_{Info}^3)\\ 0.4(EP{C}_{Circ}+EI{C}_{Circ})+0.6(EP{C}_{Tran}+EI{C}_{Tran})\end{array}\right\}$$

(1)

The definitions of the specific parameters are provided in

Table 1. Environmental cost parameter definitions.

Parameters	Definitions
$E_{Orde}$	Order phase environmental costs
$E_{\mathrm{Re}p}$	Replenishment phase environmental costs
$E_{Tran}$	Transportation phase environmental costs
$E_{Stor}$	Storage phase environmental costs
$E_{Inve}$	Inventory management phase environmental costs
$E_{Del}$	Delivery phase environmental costs
$ILE{C}_{EPC}$ $ILE{C}_{EIC}$	The environmental price cost of the inbound logistics process The environmental impact cost of the inbound logistics process
$A{l}_{EPC}$ $A{l}_{EIC}$	The environmental price cost of the assembly line nodes The environmental impact cost of the assembly line nodes
$Sup{p}_{EPC}$ $Sup{p}_{EIC}$	The environmental price cost of the supplier node The environmental impact cost of the supplier node
$Dis{t}_{EPC}$ $Dis{t}_{EIC}$	The environmental price cost of the distribution center node The environmental impact cost of the distribution center node
$E_{Orde(EPC)}$ $E_{Orde(EIC)}$	The environmental price cost of the ordering phase The environmental impact cost of the ordering phase
$E_{\mathrm{Re}\mathrm{p}(EPC)}$ $E_{\mathrm{Re}\mathrm{p}(EIC)}$	The environmental price cost of the replenishment phase The environmental impact cost of the replenishment phase
$E_{T\mathrm{ran}(EPC)}$ $E_{T\mathrm{ran}(EIC)}$	The environmental price cost of the transportation phase The environmental impact cost of the transportation phase
$E_{Stor(EPC)}$ $E_{Stor(EIC)}$	The environmental price cost of the storage phase The environmental impact cost of the storage phase
$E_{Inve(EPC)}$ $E_{Inve(EIC)}$	The environmental price cost of the inventory management phase The environmental impact cost of the inventory management phase
$E_{Dist(EPC)}$ $E_{Dist(EIC)}$	The environmental price cost of the delivery phase The environmental impact cost of the delivery phase

.

4. Model

To accurately assess the inbound logistics environmental cost of a gigafactory based on the logistics environmental cost model mentioned in Section 3.2, this section details the evaluation of the environmental cost and environmental impact cost of inbound logistics activities.

The parameters used in this section are defined as follows (

Table 2. Logistics activities environmental cost symbol definitions.

Parameters	Definitions
$EP{C}_{Tran}$	Transportation phase environmental price costs
$EI{C}_{Tran}$	Transportation phase environmental impact costs
$EI{C}_{Tran-a}$	Vehicle fuel combustion emissions
$EI{C}_{Tran-b}$	Exhaust gas cleaning process emissions
$Q_{oi}^{s_o(s_o+1)}$	Fuel consumption function for Tier 1 suppliers
$W_i^{s_o(s_o+1)}$	Tier 1 suppliers corresponding to vehicle loads
$Q$	Fuel consumption for 100 km of the unladen vehicle
$Q_{oj}^{s_t(s_t+1)}$	Fuel consumption function for Tier 2 suppliers
$\alpha$	Fuel consumption per 1 T increase in vehicle load for 100 km
$W_j^{s_t(s_t+1)}$	Tier 2 suppliers corresponding to vehicle loads
$L$	Distance from distribution center to the first Tier 1 supplier
$c$	Fuel prices
$l_i^{s_o(s_o+1)}$	Distance traveled by the ith vehicle of the Tier 1 supplier
$l_i^{s_t(s_t+1)}$	Distance traveled by the ith vehicle of the Tier 2 supplier
$A{D}_{Tran}$	Total fuel consumption
$NC{V}_{Tran}$	Average fuel heat output
$C_i$	The density of fossil fuels
$E{F}_{Tran}$	Fuel emission coefficient for transportation activities
$C_{Tran.i}$	Carbon content per unit calorific value of fuel for transport activities
$O{F}_i$	The oxidation rate of fuel
$44/12$	The molecular weight ratio of carbon dioxide to carbon
$M_i$	Mass of urea additives consumed
$12/60$	The conversion factor of pure carbon content in urea
$P$	The mass ratio of urea in urea additives
$EP{C}_{\mathrm{Re}p}$	Replenishment activity environmental price cost
$EI{C}_{\mathrm{Re}p}$	Replenishment activity environmental impact cost
$R$	Electricity price
$c_r$	Manual electricity consumption in replenishment activities
$c_d$	Power consumption of facilities in replenishment activities
$t_o$	Manual replenishment time
$t_w$	Equipment replenishment service time
$t_{n1}$	Manual normal replenishment time
$t_{n2}$	Manual abnormal replenishment time
$t_{n3}$	Normal replenishment time of the facility
$t_{n4}$	Abnormal replenishment time of the facility
$C_{\mathrm{Re}p}$	Electricity utilization rate of replenishment activities
$\beta$	Expedited amplification factor
$R{D}_{\mathrm{Re}p}$	Total power consumption of replenishment activities
$P{F}_{\mathrm{Re}p}$	Electric emission coefficient of replenishment activities
$P_{\mathrm{Re}p}$	Power emission ratio of replenishment activities
$EP{C}_{Info}$	Information activities’ environmental price costs
$EI{C}_{Info}$	Information activities’ environmental impact costs
$C_P$	Information facility construction costs
$A{D}_{Info}$	Total power consumption of the facility
$I$	Network communication cost
${\lambda }_1$	Hourly internet rate
$t_{12}$	Information processing phase from the distribution center to the assembly line
$t_{23}$	Information processing phase from the assembly line to the suppliers
$t_{13}$	Information processing phase from the distribution center to the supplier
$c_M$	Facility development cost of the assembly line
$c_T$	Facility development cost of the distribution center
$c_S$	Facility development cost of the suppliers
$R{D}_{Info}$	Total electricity consumption of information activities
$P{F}_{Info}$	Information activity electric emission coefficient
$P_{Info}$	Electricity emission ratio of information activity
$C_{Info}$	Electricity usage for information activities
$EP{C}_{Pack}$	Packing activities’ environmental price costs
$EI{C}_{Pack}$	Packing activities’ environmental impact costs
$P{M}_{i.j}$	Total amount of materials and supplies j used in packing operation i
$T{M}_i$	Total amount of materials and supplies
$P{R}_{i.j}$	Proportion of materials and supplies used
$A_{P.n}$	Electricity consumption of packaging materials and supplies
$E_{P.n}$	Emission coefficient of packaging materials and supplies
$NC{V}_{P.n}$	Average calorific value of packaging materials and supplies
$C{R}_j$	Emission factors for packaging materials and supplies
$P_i^j$	Recycling ratio of packaging material j
$EP{C}_{L\&U}$	Loading and unloading activities’ environmental price costs
$EI{C}_{L\&U}$	Loading and unloading activities’ environmental impact costs
$EP{C}_{Ss}$	Environmental costs of fixed installations
$EP{C}_{Sm}$	Environmental costs of mobile facilities
$P_{Ss}$	Electricity consumption rate of fixed facilities
$t_{Ss}$	Fixed facility service time
$l_j^{Sm}$	j range of mobile facilities
$W_j^{Sm}$	j the consumption function of mobile facilities
$t_{Sm}$	Use time of mobile facility j
$A_{Sm}$	Mobile facility heat consumption activity data
$E_{Sm}$	Mobile facility fuel emission coefficient
$R{D}_{Ss}$	Power consumption activity data of fixed facilities
$P{F}_{Ss}$	Electric emission coefficient of fixed installations
$NC{V}_{Sm}$	Average calorific value of mobile facility fuel
$C_{Sm.i}$	Carbon content per unit calorific value of mobile facility fuel
$P_{Sm}$	Electricity emission ratio of fixed installations
$EP{C}_{Stor}$	Storage activities’ environmental price costs
$EI{C}_{Stor}$	Storage activities’ environmental impact costs
$t_r$	Labor hours for storage activities
$c_h$	Labor rate of storage activities
$t_s$	Facility hours for storage activities
$c_b$	Facility electricity rate for storage activities
$R{D}_{Stor}$	Storage activity power consumption activity data
$P{F}_{Stor}$	Electric emission coefficient of storage activities
$P_{Stor}$	Electricity emission ratio of storage activities
$EP{C}_{Inve}$	Inventory management activities’ environmental price costs
$EI{C}_{Inve}$	Inventory management activities’ environmental impact costs
$M_m$	Working status of the inventory management activity facility
$t_m^n$	Working hours of different facilities m in the inventory
$c_n$	Total electricity usage rate of inventory management activity facilities
$R{D}_{Inve}$	Power consumption activity in inventory management activities data
$P{F}_{inve}^n$	Electric emission coefficient of different facilities
$P_{Stor}^n$	Electricity emission ratio of different facilities
$EP{C}_{Circ}$	Circulation processing activities’ environmental price costs
$EI{C}_{Circ}$	Circulation processing activities’ environmental impact costs
$c_e$	Electricity consumption rate of circulation processing facilities
$t_l$	Working hours of circulation processing
$R{D}_{Circ}$	Circulation processing power consumption activity data
$P{F}_{Circ}$	Electric power emission coefficient
$P_{Circ}$	Electric power emission ratio

).

4.1. Transport Activity Environmental Cost Model

Transportation activity: The environmental price cost of transportation activities includes fuel consumption due to different load patterns and road conditions during the transportation process. The environmental impact cost includes the total greenhouse gas emissions during the process, including the emissions from fuel combustion during transportation and the emissions from tail gas purification processes.

The fuel consumption of a vehicle can be estimated based on the fuel consumption function and distance traveled by suppliers at all levels. $Q_{oi}^{S_0\left(S_0+1\right)}$ is the fuel consumption function from the sth first-level supplier to the (s + 1)th first-level supplier. $Q_{oj}^{S_t\left(S_t+1\right)}$ is the fuel consumption function from the sth second-level supplier to the (s + 1)th second-level supplier. The amount of fuel consumed varies depending on the load. Q₁₀₀ represents the fuel consumption of the transport vehicle when running for 100 km with no load. α is the fuel consumption of the transport vehicle when running for 100 km every time the load is increased by 1 T. Therefore, the formula for calculating the environmental price cost is:

$$\left\{\begin{array}{l}{Q}_{oi}^{s_o(s_o+1)}\\ Q_{oj}^{s_t(s_t+1)}\end{array}\right\}=\left\{\begin{array}{l}0.01(\alpha \cdot W_i^{s_o(s_o+1)}+Q)\\ 0.01(\alpha \cdot W_j^{s_t(s_t+1)}+Q)\end{array}\right\}$$

(2)

$$EP{C}_{Tran}=0.01L\cdot Q\cdot c+{\displaystyle {\sum }_{i=1}^n{\displaystyle {\sum }_{s=1}^k{l}_i^{s_o(s_o+1)}\cdot Q_{oi}^{s_o(s_o+1)}\cdot c+l_i^{s_t(s_t+1)}\cdot Q_{oj}^{s(s_t+1)t}\cdot c}}$$

(3)

The emissions from vehicle fuel combustion EIC_Tran-a are determined by the total amount of fuel and the different types of fuels used. To estimate the fuel emissions during transportation, fuel consumption AD_Tran and emission factors data for transportation activities EF_Trran are used. The emissions from the tail gas purification process EIC_Tran-b are estimated based on the principles of the tail gas purification agent.

$$EI{C}_{Tran}=EI{C}_{Tran-a}+EI{C}_{Tran-b}$$

(4)

$$EI{C}_{Tran-a}={\displaystyle \sum \left(A{D}_{Tran}\cdot E{F}_{Tran}\right)}$$

(5)

$$A{D}_{Tran}=NC{V}_{Tran}\cdot {\displaystyle \sum (l_i^{s_o(s_o+1)}\cdot Q_{oi}^{s_o(s_o+1)}+l_i^{s_t(s_t+1)}\cdot Q_{oj}^{s(s_t+1)t})\cdot C_i\cdot {10}^{-5}}$$

(6)

$$E{F}_{Tran}=C_{Tran.i}\cdot O{F}_i\cdot \frac{44}{12}$$

(7)

$$EI{C}_{Tran-b}=M_i\times 12/60\times P\times 44/12\times {10}^{-3}$$

(8)

4.2. Replenishment Activity Cost Model

Replenishment activity: The environmental price cost of the replenishment activities includes the sum of the energy consumption of labor and facilities during the replenishment process. The environmental impact cost includes the greenhouse gas emissions from the net purchased electricity during the replenishment process.

The replenishment plan depends on the order plan, and suppliers must complete the replenishment between the ordering time and the pick-up time at the gigafactory. If the replenishment is not timely or the order quantity is incorrect, an expedited replenishment is required. The difference between expedited replenishment and normal replenishment is an increase in manual and facility electricity consumption; hence, an expedited cost amplification factor β is introduced. To estimate the total electricity consumed during the replenishment activities, the electricity consumption rates for manual labor c_r and the facility c_d are calculated. For environmental impact costs, greenhouse gas emissions from the overall net purchased electricity are estimated using electricity consumption activity data RD_Rep and the standard electricity emission factor PF_Rep for replenishment activities.

$$EP{C}_{\mathrm{Re}p}=R\cdot \left(c_r+c_d\right)$$

(9)

$$\left\{\begin{array}{l}{c}_r\\ c_d\end{array}\right\}=\left\{\begin{array}{l}{t}_{n1}+\beta \cdot t_{n2}\\ t_{n3}+\beta \cdot t_{n4}\end{array}\right\}$$

(10)

$$EI{C}_{\mathrm{Re}p}=R{D}_{\mathrm{Re}p}\cdot P{F}_{\mathrm{Re}p}$$

(11)

$$\left\{\begin{array}{l}R{D}_{\mathrm{Re}p}\\ P{F}_{\mathrm{Re}p}\end{array}\right\}=\left\{\begin{array}{l}(c_r+c_d)\cdot C_{\mathrm{Re}p}\\ 0.58\cdot P_{\mathrm{Re}p}\end{array}\right\}$$

(12)

4.3. Information Processing Activity Cost Model

Information processing activity: Information communication is an indispensable activity in inbound logistics system operations. It is a necessary activity for real-time communication and decision-making assistance in the various phases of each node. The environmental price cost includes the information infrastructure construction cost of each node, network communication costs, and the electricity consumption of facility communication. The environmental impact cost includes greenhouse gas emissions from the net purchased electricity of the communication equipment during communication.

The communication nodes are determined to estimate the cost of network communications. The communication nodes of a gigafactory’s inbound logistics include the distribution center, the assembly line, and the suppliers. The communication nodes are numbered 1, 2, and 3. t₁₂ is the communication time between the distribution center and the assembly line, and t₂₃ and t₁₃ are similar. λ₁ is the network traffic cost per hour. The total cost of building the information facility is determined by the cost of developing the information facilities of the assembly line (c_M), the supplier (c_S), and the distribution center (c_T).

$$EP{C}_{Info}=C_P+A{D}_{Info}+I$$

(13)

$$\left\{\begin{array}{l}I\\ CP\\ A{D}_{Info}\end{array}\right\}=\left\{\begin{array}{l}{\lambda }_1(t_{12}+t_{23}+t_{13})\\ t_{12}\cdot (c_M+c_T)+t_{23}\cdot (c_M+c_S)+t_{13}(c_S+c_T)\\ R\cdot {\displaystyle \sum (t_{12}+t_{23}+t_{13})\cdot C_{Info}}\end{array}\right\}$$

(14)

$$EI{C}_{Info}=R{D}_{Info}\cdot P{F}_{Info}$$

(15)

$$\left\{\begin{array}{l}R{D}_{Info}\\ P{F}_{Info}\end{array}\right\}=\left\{\begin{array}{l}{\displaystyle \sum (t_{12}^i+t_{23}^i+t_{13}^i)}\cdot C_{Info}^i\\ 0.58\cdot P_{Info}\end{array}\right\}$$

(16)

4.4. Packaging Activity Cost Model

Packaging activity: The environmental price cost of packaging activities includes the electricity consumption of the packaging equipment during use. The environmental impact cost is the greenhouse gas emissions from various emission sources in the packaging process, including the greenhouse gas emissions from various packaging materials and the net purchased electricity of the packaging activity.

The greenhouse gas emissions from the packaging process are determined by the total usage, PM_i,j, of materials and supplies i in the packaging operations. To estimate the energy consumption of the packaging process, the total amount of materials and supplies used in service operation, TM_i, and the usage ratio of materials to supplies, PR_i,j, are estimated. Then, to estimate the greenhouse gas emissions of the activity, the emission factor of packaging materials and supplies, E_p,n, and the electrical activity data of the packaging facility, A_p,n, are estimated.

$$EP{C}_{Pack}=R\cdot {\displaystyle \sum P{M}_{i.j}}$$

(17)

$$P{M}_{i.j}=T{M}_i \cdot P{R}_{i.j}$$

(18)

$$EI{C}_{Pack}={\displaystyle \sum (A_{P.n}\cdot E_{P.n})}$$

(19)

$$\left\{\begin{array}{l}{A}_{P.n}\\ E_{P.n}\end{array}\right\}=\left\{\begin{array}{l}P{M}_{i.j}\cdot NC{V}_{P.n}\\ {\displaystyle \sum 0.58P_i^j}\cdot C{R}_j\end{array}\right\}$$

(20)

4.5. Loading and Unloading Activity Cost Model

Loading and unloading activity: The environmental price cost of loading and unloading activities includes costs associated with the fuel consumption and electricity usage of the fixed and mobile facilities involved in the handling processes. The environmental impact cost includes the total greenhouse gas emissions from the fuel combustion of fixed and mobile facilities and greenhouse gas emissions from the net purchased electricity.

Due to the different primary energy sources used by fixed and mobile facilities, to estimate the energy consumption of the loading and unloading process, the total electricity consumption P_Ss of the fixed facilities and the total heat consumption $W_j^{Sm}$ of the mobile facilities are used to estimate the energy consumption, and the corresponding greenhouse gas emissions are estimated separately. The electricity emission factor, PF_Sm, and the heat emission factor, E_Sm, of the loading and unloading process are introduced.

$$EP{C}_{L\&U}=EP{C}_{Ss}+EP{C}_{Sm}$$

(21)

$$\left\{\begin{array}{l}EP{C}_{Ss}\\ EP{C}_{Sm}\end{array}\right\}=\left\{\begin{array}{l}R\cdot t_{Ss}\\ c\cdot {\displaystyle \sum l_j^{Sm}\cdot W_j^{Sm}\cdot t_{Sm}}\end{array}\right\}$$

(22)

$$EI{C}_{L\&U}={\displaystyle \sum (A_{Sm}\cdot E_{Sm})}+R{D}_{Ss}\cdot P{F}_{Ss}$$

(23)

$$\left\{\begin{array}{l}R{D}_{Ss}\\ A_{Sm}\\ E_{Sm}\\ P{F}_{Ss}\end{array}\right\}=\left\{\begin{array}{l}{t}_{Ss}\cdot P_{Ss}\\ NC{V}_{Sm}\cdot {\displaystyle \sum l_j^{Sm}\cdot W_j^{Sm}\cdot t_{Sm}}\\ C_{Sm.i}\cdot O{F}_i\cdot \frac{44}{12}\\ 0.58\cdot P_{Sm}\end{array}\right\}$$

(24)

4.6. Storage Activity Cost Model

Storage activity: The environmental price cost of this activity includes the electricity consumption of the facilities and labor involved in sorting and retrieving goods. The environmental impact cost includes the greenhouse gas emissions resulting from the distribution center’s net purchase of electricity during the process.

The electricity consumption of labor and facilities is determined by the model and the total electricity consumption. To estimate the energy consumption of the entire process, the electricity usage rates of labor c_h and facilities c_b in the storage activities can be estimated. The greenhouse gas emissions resulting from energy consumption can be estimated by introducing the standard electricity emission factor PF_Stor for the storage process and the total electricity consumption RD_Stor.

$$EP{C}_{Stor}=R\cdot (t_r\cdot c_h+t_s\cdot c_b)$$

(25)

$$EI{C}_{Stor}=R{D}_{Stor}\cdot P{F}_{Stor}$$

(26)

$$\left\{\begin{array}{l}R{D}_{Stor}\\ P{F}_{Stor}\end{array}\right\}=\left\{\begin{array}{l}{\displaystyle \sum t_l}(c_h+c_b)\\ 0.58\cdot P_{Stor}\end{array}\right\}$$

(27)

4.7. Inventory Management Activity Cost Model

Inventory management activity: The environmental price cost includes the total amount of electricity consumed in the operation of warehouse facilities, and the environmental impact cost includes the greenhouse gas emissions generated by the electricity consumption during facility usage.

The energy consumption of warehouse facilities is determined by the electricity consumed by different facilities during certain warehouse activities. Therefore, to estimate the overall energy consumption, the total power consumption rate of the facilities, C_n, and the operating status of different equipment, M_m, are introduced for estimation. The greenhouse gas emissions caused by energy consumption can be estimated by introducing the emission coefficient, PF_Inve, of electricity for standard inventory management processes.

$$EP{C}_{Inve}=R\cdot {\displaystyle \sum M_m\cdot t_m^n\cdot c_n}$$

(28)

$$EI{C}_{Inve}={\displaystyle \sum R{D}_{Inve}\cdot P{F}_{inve}^n}$$

(29)

$$\left\{\begin{array}{l}R{D}_{Inve}\\ P{F}_{Inve}\end{array}\right\}=\left\{\begin{array}{l}{\displaystyle \sum M_m\cdot t_m^n\cdot c_n}\\ {\displaystyle \sum 0.58\cdot P_{I\mathrm{n}ve}^n}\end{array}\right\}$$

(30)

4.8. Circulation Processing Activity Cost Model

Circulation processing activity: Circulation processing is guided by the distribution center and is the final stage before transporting goods to the main factory. Its main task is to inspect and number the goods and assist in their transportation to the main factory. The environmental price cost includes the electricity consumption of the facilities and the labor. The environmental impact cost includes the greenhouse gas emissions caused by the net purchase of electricity in the circulation processing activity.

The energy consumption of the infrastructure in circulation processing activities is determined by the total amount of electricity consumption. To estimate the energy consumption of the overall process, the electricity usage rate of manual labor, represented by c_e, can be used as an estimation for circulation and processing activities. The greenhouse gas emissions resulting from energy consumption can be estimated by introducing the emission factor PF_Circ and the total electricity consumption RD_Cric for the circulation processing activity.

$$EP{C}_{Circ}=R\cdot c_e\cdot {\displaystyle \sum t_l}$$

(31)

$$EI{C}_{Circ}={\displaystyle \sum R{D}_{Circ}\cdot P{F}_{Circ}}$$

(32)

$$\left\{\begin{array}{l}R{D}_{Circ}\\ P{F}_{Circ}\end{array}\right\}=\left\{\begin{array}{l}{\displaystyle \sum t_l}\cdot c_e\\ {\displaystyle \sum 0.58\cdot P_{Circ}}\end{array}\right\}$$

(33)

5. Case Study: The ILEC in Geely Gigafactory

Geely Automobile Group is an advanced automobile manufacturer in China that operates advanced automobile factories both domestically and internationally, including locations in various parts of China and overseas countries like Belarus. Geely Automobile’s Baoji factory in Shaanxi province is one of their most advanced factories. With advanced equipment such as intelligent robots, automated production lines, and automatic guided vehicles (AGVs), the annual output can reach about 200,000 units. However, the environmental impact and resource consumption associated with the factory’s inbound logistics process have not been adequately assessed or quantified. To address this, we aimed to comprehensively evaluate the consumption and environmental impacts of the factory’s inbound logistics by employing the ILEC model.

5.1. Basis Data

The data utilized in this study were sourced from both the distribution center of Geely’s Baoji factory and its 18 suppliers. The data encompass various aspects, including order data, warehousing data, and transportation and replenishment process data, and cover the timeframe from October 2021 to December 2021. The order data comprise the communication time for each node and the associated communication application costs. Warehousing data consist of metrics such as pick-up time, safety stock time, and facility tool usage time. Transportation and replenishment process data encompass details such as distances, cargo loads, fuel consumption, and labor-related information.

In this case, for the automotive assembly line, the process of placing an order entails information processing activities that result in energy consumption and generation of carbon emissions (data are shown in

Table 3. Assembly line logistics activity data.

Parameters	Data
$t_{12}^1$	0.017 h
$t_{13}^1$	0.017 h
$t_{23}^1$	0.3 h
λ1	2 CNY/h
cM	CNY 5000
cT	CNY 5000
cS	CNY 5000
$C_{Info}^1$	90 kw
PInfo	1

). For suppliers, the replenishment and transportation of goods generate significant carbon emissions and consume substantial amounts of energy (data are shown in

Table 4. Suppliers’ logistics activity data.

Parameters	Data
$Q_j^{s(s+1)}$, j = 1, 2, 3 s = 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 17, 18	0.233; 0.2331; 0.234; 0.236; 0.237; 0.2373; 0.237 0.233; 0.2332; 0.2337; 0.2342; 0.2344; 0.2347 0.233; 0.2336; 0.2339; 0.0.2344; 0.2347(L)
$Q_i^{s(s+1)}$, i = 1 s = 1, 2, 3	0.2373; 0.2448; 0.2475(L)
c	7.1 CNY/L
L	1649 km
li	25.562; 21.253; 1649 (km)
lj	8.806; 30.559; 15.246; 53.505; 4.775; 3.821; 0.246; 4.894; 42.298; 16.107; 19.535; 8.276; 31.3; 25.993; 8.413; 12.412; 45.886; 4.71. (km)
Ci	2.35 kg/m3
OFi	98%
NCVtran	43.070 GJ/104 Nm3
EFtran	0.11 tCO2e/GJ
$M_i$	0.012375 L
$P$	32.5%
$R$	0.875 CNY/kwh
cr	40 kw
cd	180 kw
CRep	98%
β	1.83
PRep	1
TMi	4.61 T
PRi,j	48%
$NC{V}_{p.n}$	2.67 GJ/104 Nm3
CRj	0.98
$P_i^j$	44.68%
$t_{12}^2$	0 h
$t_{13}^2$	0.018 h
$t_{23}^2$	0.3 h
$C_{Info}^2$	80 kw

). For distribution centers, the inventory management and handling of goods are significant sources of carbon emissions and energy consumption (data are shown in

Table 5. Distribution center logistics activity data.

Parameters	Data
tSs	65 h
tSm	2.5 h
PSm	0.98
PSs	0.86
$l_j^{Sm}$	0.45
$W_j^{Sm}$	1.353 T
h	2
$NC{V}_{Sm}$	17.6 GJ/104 Nm3
th$C_{Sm,i}$	0.15
$t_{12}^3$	0.02 h
$t_{13}^3$	0.02 h
$t_{23}^3$	0.3 h
$C_{Info}^3$o	120 kw
tr	42.5 h
ch	1.375
ts	50 h
cb	0.89
PStor	0.89
$t_m^n$	250 h
cn	0.98
$P_{Stor}^n$	1
tl	720 h
ce	98%

).

5.2. Calculating the Environmental Cost

The inbound logistics process of the factory includes three key nodes: the assembly line, the suppliers, and the distribution center. The environmental cost within a node is determined by the environmental price cost and the environmental impact cost that arises from the logistics activities across all phases within that node. The environmental cost of each logistics activity can be calculated using the environmental cost model proposed in Section 4. The specific logistics phase environmental cost can be calculated by applying the model proposed in Section 3.3. The environmental price cost and environmental impact cost of each stage are shown in

Table 6. Environmental costs of the inbound logistics of Geely’s Baoji factory.

Environmental Cost	Assembly Line	Suppliers		Distribution Center			Total
	${\mathit{E}}_{\mathit{o}\mathit{r}\mathit{d}\mathit{e}}$	${\mathit{E}}_{\mathbf{Re}\mathit{p}}$	${\mathit{E}}_{\mathit{T}\mathit{r}\mathit{a}\mathit{n}}$	${\mathit{E}}_{\mathit{S}\mathit{t}\mathit{o}\mathit{r}}$	${\mathit{E}}_{\mathit{I}\mathit{n}\mathit{v}\mathit{e}}$	${\mathit{E}}_{\mathit{D}\mathit{e}\mathit{l}}$
EPC	CNY 4954	CNY 3006	CNY 11,731	CNY 4589	CNY 1368	CNY 1029	CNY 26,677
EIC	1046 kg	2026 kg	8936 kg	4410 kg	398 kg	409 kg	17,225 kg

.

Based on the calculations, the environmental price cost of the automobile assembly line in this cycle accounts for 18.6% of the total environmental price cost, while the corresponding environmental impact cost accounts for 6.1%. Suppliers, on the other hand, account for 55.2% of the total environmental price cost and 63.6% of the total environmental impact cost in this cycle. Additionally, the distribution center accounts for 26.2% of the total environmental price cost, with its environmental impact cost accounting for 30.3% of the total environmental impact cost. The comparison and detailed data of the environmental price cost and environmental impact cost of the each node are shown in Figure 5.

5.3. Discussion

The above calculations and results show the environmental price cost and environmental impact cost of each logistics phase in the inbound logistics process, and the proportion of each node. It provides a novel perspective for identifying environmentally critical logistics nodes in gigafactories.

Today, carbon emissions from energy consumption pose serious problems, and awareness of the relevance of sustainability has increased dramatically [40]. How to assess, detect, and manage GHG emissions in the logistics process has been extensively researched and received much attention. However, there is no structured way of estimating the environmental costs of the entire inbound logistics process. This study extends previous research by providing a comprehensive assessment model for calculating the environmental costs of inbound logistics processes. However, specific environmental impact management has not been studied.

First, most available models for assessing the environmental impact of logistics processes focus on a certain node, such as warehouses [15]. The proposed model covers an environmental cost assessment of the entire inbound logistics process. Many available studies only pay attention to the environmental cost of greenhouse gas emissions, often ignoring the corresponding energy consumption [41]. Energy consumption is the basis for greenhouse gas emissions [31]. The model not only takes into account greenhouse gas emissions but also evaluates the corresponding energy consumption.

The proposed model identifies environmental impacts and energy consumption at key nodes (i.e., assembly lines, suppliers, and distribution centers) of a gigafactory. It can also help factories formulate appropriate environmental strategies and understand the environmental impacts of the inbound logistics process, laying the foundation for the sustainable development of gigafactories.

6. Conclusions and Perspective

Environmental costs have gradually become a factor that must be considered in the development of the logistics industry. Inbound logistics is an essential part of gigafactory logistics. However, so far, there is no structured method or model with which to evaluate the environmental cost of the inbound logistics of a gigafactory. Therefore, this paper provides a comprehensive evaluation model with which to evaluate the environmental impact and energy consumption of the whole inbound logistics process. Taking the key logistics nodes of inbound logistics as the entry point, and using the relationship between logistics stages and activities, the environmental cost of each node was evaluated so as to comprehensively measure and evaluate the environmental cost of inbound logistics. This research expands the existing literature on the cost of logistics.

Both theoretical and practical implications can be drawn. Regarding the theoretical implications, this paper proposes a structured method and model for determining the environmental impact and energy consumption of the whole inbound logistics process, expanding the sustainable logistics development field. From a practical point of view, this paper uses a structured method to construct a framework for an inbound logistics system and its environmental costs. Aiming to fulfill the new demands for logistics evaluations of gigafactories, the framework can comprehensively evaluate the environmental performance of inbound logistics, improving the environmental efficiency of super factories, raising awareness, and helping to better develop sustainable strategies.

Finally, the limitations of this study must be acknowledged, as this can pave the way for future promising research avenues. First, the case study and the proposed methodology both have limitations. One of the limitations of this study is the use of a single case study to create one ILEC model. Therefore, the application of the ILEC model to multiple case studies would be an appropriate next step. Additionally, in terms of the transportation model, we only modeled trucks as a means of transportation. Adding other means such as waterways, airways, and railways may take this research a step further. Third, we used GHG emission standards and green logistics evaluation indicators to develop our model. Future research could consider additional sources for model tuning and application scenarios. The focus of this study was the environmental cost assessment of inbound logistics. Future research can explore the environmental cost assessment of different logistics and under different conditions, such as environmental cost assessment of outbound logistics and cold chain logistics.