1. Introduction
Commercial complexes, as architectural entities that integrate shopping, leisure, entertainment, and culture, boost urban functionality, fulfilling diverse needs for entertainment, consumption, and transportation and promoting an improvement in the standard of living [
1]. However, the multifunctionality of commercial complexes results in large building areas, complex structures, high human traffic, and challenges in ventilation and smoke extraction, posing firefighting challenges such as high fire loads, complex origins of fires, multiple pathways for fire spread, and difficult emergency evacuation and rescue [
2]. Fire accidents can lead to substantial losses of life and property. In recent years, the safety situation of urban commercial complexes in China has remained severe, with ongoing fire accidents. For example, the 13 June 2022 fire at a shopping center in Dongsheng District, Ordos City, Inner Mongolia, resulted in two fatalities and an affected area of about 1800 square meters [
3], and the 6 April 2021 fire at the Tongluowan Commercial Plaza in Chizhou, Anhui, affected about 400 square meters, resulting in four deaths, two injuries, and direct economic losses of 770,088 dollars [
4]. The analysis of the patterns of fire accidents in commercial complexes, the summary of the causes, and the exploration of trends in fire accident development are of significant importance for the advancement of urban public safety and urban firefighting management.
To effectively identify fire hazard factors and reduce the risk of fire accidents, scholars have undertaken extensive research on aspects such as building fire safety, primarily employing methods such as Building Information Modeling (BIM) platform [
5], uncertain clustering theory [
6], fuzzy comprehensive evaluation [
7], and grey analysis theory [
8] to analyze fire safety risks in general civil buildings, particularly conducting comprehensive studies on the fire risk of high-rise buildings. For instance, Li et al. [
9] developed a gray fuzzy hierarchical mathematical model for the fire risk of high-rise buildings and evaluated the fire hazard of five high-rise buildings, providing new references for fire prevention design in high-rise structures. Hansen et al. [
10] used the Fire Risk Model (FRM) to assess the safety of Danish high-rise single-staircase residential buildings; Morry [
11] developed an evacuation model for high-rise buildings, analyzing the impact of various evacuation routes on fire evolution. However, research on fire risk assessment for commercial complexes, a special type of building, is limited and primarily at the qualitative stage, without a mature and scientific evaluation system yet. Jiang [
12] studied the structural safety of the Shanghai Tower during fire accidents. Fang et al. [
13] used the basic principles of hierarchical analysis to establish a fire risk assessment index system for shopping malls, and determining the weights of the indexes in the assessment system based on cluster analysis to determine the fire risk level of the building. Liu et al. [
14] focused on fire equipment maintenance to establish a fire risk assessment system for large commercial buildings, using the structure entropy weighting method combined with the Analytical Hierarchy Process to evaluate fire risks in four large commercial buildings in Chongqing. EASIR et al. [
15] used the fire dynamic simulator (FDS) to simulate mall fires, studying the impact on emergency evacuation of people. Howard [
16] explored the relationship between fire damage in large urban complexes and changes in fire temperature, proposing enhancements based on their coupled effects. Nhiwakoti and Moriyama [
17,
18] conducted live evacuation experiments to study the factors influencing evacuation behavior in commercial complexes. Ahmed et al. [
19] analyzed multiple fire scenarios and corresponding evacuation plans in a large shopping center through simulations, showing that the location of a fire significantly affects smoke propagation.
In summary, in the research field of fire accidents in large commercial complexes, scholars have mainly concentrated on fire risk assessment, building fire resistance, fire simulation, and evacuation. Statistical analysis of fire accidents in commercial complexes has been relatively neglected, with a lack of in-depth exploration of the relationships between fire-influencing factors and difficulty in identifying the main and key factors of fire accidents. The importance of statistical analysis lies in its ability to objectively reflect the circumstances and characteristics of accidents [
20], playing a pivotal role in the development of accident prevention strategies, such as in road tunnel fire accidents [
21], laboratory fire and explosion accidents [
22], construction accidents [
23], and coal mine accidents [
24]. Therefore, this study collected and organized fire accident data in commercial complexes from 2002 to 2022, selected fire influencing factors, and aims to explore development trends and enhance fire prevention and control capabilities [
25], laying the foundation for constructing a system of indicators for fire influencing factors. Considering the diversity, uncertainty, and complex interconnections of fire risk factors in commercial complexes, this research utilized the Wuli–Shili–Renli (WSR) methodology to develop an index system for influencing factors, emphasizing the understanding and assessment of fire risks from the physical, logical, and human dimensions [
26].
Zio [
27] proposed from a systemic perspective that the causes of accidents not only involve the characteristics of the factors themselves but also originate from the relationships among them. In light of this, employing the Interpretative Structural Modeling (ISM) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods, this study further explored the interactions and hierarchical relationships among fire-influencing factors. The ISM method visualizes complex cause-and-effect relationships, constructing logical relationships and hierarchical structures among elements [
28]; meanwhile, the DEMATEL method determines the causal relationships and positions between factors, and their integration effectively reveals the influence and interactions of key elements within the system. The DEMATEL-ISM model is still in its initial stages of application in the field of fire safety, but it has been successfully used in areas such as construction [
29]
, urban gas systems [
30], highways [
28], and coal mining [
31], proving its effectiveness in integrating expert knowledge and establishing order, direction, and hierarchical structures among factors, offering valuable insights for fire risk control in commercial complexes. The application of this methodology enhances the scientific validity and rationality of comprehensive assessments of fire risk factors and, simultaneously, by constructing a hierarchical model of influencing factors, offers clear guidance for managing fire risks in commercial complexes.
The remainder of this paper is organized as follows.
Section 2 details the two main methods used in this statistical analysis (namely WSR and DEMATEL-ISM).
Section 3 develops an index system for the influencing factors of fire accidents in commercial complexes based on the WSR methodology. Numerical calculations and result analysis employing DEMATEL-ISM are detailed in
Section 4. The research conclusion and research limitations are in
Section 5.
3. Construction of Fire Risk Evaluation Index System for Commercial Complexes Based on WSR
The fire risk assessment of commercial complexes is a multi-level, multi-dimensional complex system. This study utilizes the principles of the WSR method, integrating findings from related literature [
13,
16,
18], to select 20 clearly defined fire impact factors in commercial complexes from three dimensions—physical, rational, and human—and four aspects: personnel, equipment, environment, and management. A fire accident impact factor index system for commercial complexes has been developed, as illustrated in
Figure 5.
On the physical level, these factors primarily encompass the use of fire prevention and firefighting equipment, along with environmental elements that support the safe operation of the entire commercial complex. The physical factors leading to fires in commercial complexes primarily manifest in issues such as electrical shorts, electrical equipment failures, insufficient firefighting equipment, and inadequate emergency facilities. The rational dimension primarily reflects management deficiencies in commercial complexes, including unfulfilled corporate fire safety responsibilities, inadequate government supervision, insufficient fire safety inspections, and inadequate safety training. The human dimension emphasizes reliance on individuals to organize and coordinate the daily operations of commercial complexes, where unsafe human behaviors primarily include unauthorized hot work, insufficient fire safety skills, and limited fire safety awareness.
5. Conclusions
Fire statistics are crucial for understanding the trends of fire accidents in commercial complexes, enhancing fire control capabilities, and preventing such accidents. Fire accidents are the result of the combined effects of factors including personnel, equipment, the environment, and management. This study offers a statistical analysis of fire accidents in mainland China’s commercial complexes from 2002 to 2022, summarizes the causes, establishes an index system for fire impact factors, and explores the interaction mechanisms among these factors. Here are the main conclusions:
- (1)
From 2002 to 2022, the number of accidents generally exhibited a fluctuating upward trend, with January recording the most accidents and July the fewest; February had the highest fatality rate.
- (2)
Based on a combination of literature studies and case studies, incorporating the principles of the fundamentals of security accident generation and integrating the basic elements of safety accidents, this study analyzed accident causes from four perspectives: unsafe human behaviors, unsafe conditions of objects, environmental factors, and management factors. Employing the WSR methodology and using physical, logical, and human perspectives as a foundation, it categorized 20 fire risk impact factors into four dimensions: personnel, equipment, environment, and management. This classification led to the creation of a scientifically sound system for evaluating and controlling fire risks in commercial complexes, marking a significant advancement in fire safety management.
- (3)
The DEMATEL model was applied to calculate and rank the degrees of influence, effect, centrality, and causality of causal factors. Based on these metrics, eight key factors were identified as critical to causing fire accidents in commercial complexes: S5 (unauthorized alterations), S10 (inadequate regulations), S13 (inadequate fire safety inspections), S12 (inadequate safety education and training), S16 (careless use of fire in operations), S14 (inadequate government supervision), S9 (failure to implement corporate fire safety responsibilities), and S11 (poor management of routine maintenance).
- (4)
Using ISM, a multi-level hierarchical structure model was established to analyze fire accident factors in commercial complexes, categorizing them into seven levels and dividing them into direct, intermediary, and essential factors. The direct factor layer includes ten impact indicators, which directly cause accidents and are the most easily perceived in accident analysis. Measures should be intensified to enhance safety monitoring and promptly identify fire hazards. The intermediary factor layer comprises eight indicators, representing significant factors between direct and essential factors that require effective intervention. S5 (unauthorized alterations) and S12 (inadequate safety training) are positioned at the highest level, constituting fundamental factors in fires within commercial complexes. This study employed the DEMATEL–ISM method to examine the impact and extent of the influence of these factors on fire accidents, further exploring their interactions. The findings offer valuable insights for scientifically managing fire risks in commercial complexes and contribute to enhancing their sustainable development.
However, several significant challenges emerged during the research process. These challenges are necessary and can be addressed in future research for improvement. Firstly, due to the limitations in calculating the matrix workload, this study only extracted 20 risk factors, resulting in the generalization of some factor indicators. Future research needs to be more detailed and extensive. Secondly, in the DEMATEL method, the degree of mutual influence between factors is determined by experts, fully reflecting the experts’ judgment based on their many years of experience in the field. However, this method also has subjective limitations. Additionally, the number of experts participating in the survey and their level of expertise should be considered, as this will help better identify the key factors contributing to fire risks in commercial complexes and their different structural relationships.