Strategic Choices of General Contractors in the Context of China’s Industry Chain of Construction Industrialization

Abstract

Amidst the challenges of economic downturn and construction industrialization, the profits obtained by general contractors through comparative advantage strategies are slowly decreasing, and thus, new strategic choices are required. The collaborative division of labor effect in the industry chain can improve profits and labor productivity, which is an important driving force for enterprise transformation and development. Therefore, a need arises to improve the profits of general contractors in the industrial chain system composed of prefabricated component suppliers, general contractors, and building development enterprises. Accordingly, this paper constructs a backward integration, forward integration, and bidirectional integration Stackelberg game model based on the proportion of resource investments, with general contractors as the main decision-making body. It then compares and analyzes the optimal decision-making values in different situations to study the optimal strategic decision-making problem of general contractors. Research results indicate the following. (1) All three integrated strategies can improve the profits of general contractors. When the proportion of resource investment meets certain conditions, the profits of general contractors under the bidirectional integration strategy are the highest, while the sustainable performance of the industrial chain and prefabricated buildings can be increased and the coordination of the industrial chain can be achieved. Thus, it is the best choice for a general contractor. (2) As a prefabricated component supplier needs to carry out continuous technological innovation activity to obtain a cumulative effect, the return on investment of forward integration is less than that of backward integration. (3) General contractors may consider choosing to carry out bidirectional integration strategies of forward integration followed by backward integration.

1. Introduction

The practice of implementing project-based construction in China’s construction industry since 1987 has led to Chinese general contractors achieving rapid development through the comparative advantage strategy [1]. In the 2023 ENR “Top 250 International Contractors”, eighty-one Chinese construction companies are on the list, ranking first in the world [2]. The rapid development of China’s general contractors is primarily due to the growth of social fixed assets investment, which has driven GDP growth for a long time, and the pull of macro strategic policies, whose competitiveness is derived from low-cost resources and labor dividends [3]. However, currently, Chinese general contractors are facing the challenges of a declining growth rate of fixed assets investment, rising costs of resources and labor, and increasing standards of sustainable development. The increasing cost pressure on enterprises has weakened the competitiveness brought about by the comparative advantage strategy. The weakening of corporate competitiveness is also reflected in the ENR250 list, which focuses on overseas revenue. Although eighty-one Chinese companies are on the list, only one of them ranks in the top five [2]. Through in-depth research on the development mode of general contractors, their main mode of business can be concluded to be engineering contracting, which is located in the production stage of the industrial chain. The smile curve hypopaper suggests that the production stage has the lowest added value throughout the entire value chain [4], which is precisely where Chinese general contractors are located. The comparative advantage strategy can quickly expand a company’s scale, but expanding its vertical boundaries is difficult. Once the cost pressure of the main business increases, it will lead to a weakening of profitability [5]. Integration, cooperation, or consortia are becoming increasingly important in large construction projects [6]. Therefore, Chinese general contractors should change their comparative advantage strategies and make new strategic choices to improve corporate profits and sustainable development capabilities.

Research on the strategic management of general contractors is relatively scattered and has not yet formed a unified understanding. Svetlana (2016) pointed out that technological innovation is the key to the survival of general contractors; if reliance on one enterprise is not able to drive the technological enhancement of the overall industry and achieve prosperity in the building construction industry, there is a need to build a collaborative innovation alliance strategy for building construction companies and to integrate new technologies into the industrial chain [7]. This could include, for example, artificial intelligence techniques such as machine learning [8]. Albert (2017) summarized the opinions of global experts in the field of construction using a comprehensive survey questionnaire method and conducted sorting and research [9]. He believes that green building technology is an important tool for the in-depth development of the construction industry and is an important strategic choice for enterprises to obtain cost–benefit, convenient construction, and market leadership, which is also conducive to accelerating the standardization process of the construction industry [9]. Zhu and Ning (2023) empirically tested the impact of digital reform on the strategic investment of construction enterprises based on panel data for China’s construction industry from 2007 to 2018. The results indicate that digital reform policies have significantly increased the investment of digital resources in enterprises and promoted the digital transformation of construction enterprises [10]. Nikmehr (2021) believes that implementing digital strategies in construction enterprises can help improve sustainable development performance and has developed an evaluation framework for an enterprise’s sustainable performance [11]. Yildiz et al. (2020) established a dynamic relationship model between corporate strategy and performance based on a balanced scorecard and system dynamics, which can be used to help employees improve their development strategies [12]. Overall, consistent with most industries, most research focuses on the strategic development of general contractors in the context of digitalization, with less attention paid to the unique background of the construction industrialization industry chain in the construction industry.

Therefore, the purpose of the research is to find out possible development strategies for general contractors in the context of the construction industrialization industry chain and to determine the optimal development strategy from among the available alternatives. In view of the advantages of resource-based theory in analyzing strategic management and vertical integration, this paper aims to distinguish between different integration strategies from a resource perspective, construct and analyze game models to find the optimal strategy, with a view to promoting the practice of the construction industry in terms of strategic management and making suggestions for the development of integration strategies in construction enterprises. The remainder of this paper is structured as follows. Section 2 provides a literature review to propose the future development direction of general contracting and the research methods. Section 3 designs the model based on the selected methods. Section 4 and Section 5 provide model solving and analysis. Section 6 presents the research conclusions and insights.

2. Literature Review

2.1. Construction Industrialization

In China, construction industrialization is considered a green and low-carbon production method that improves environmental and social sustainability. It enhances enterprise competitiveness through technological and organizational improvements, leading to increased profits for both individual enterprises and total industrial chain [13]. In addition, industrialization of construction reduces waste and enhances the project sustainability [14]. However, construction industrialization has also brought many challenges to enterprises. Uusitalo and Lavikka (2020) argued that owing to path dependence, many traditional construction enterprises have difficulty in transitioning to construction industrialization. Through a case study of vertical integration of a construction industrialization enterprise, it is demonstrated that integration or cooperation with external enterprises can help construction enterprises change their path dependence mentality [15]. Qi et al. (2020) conducted a survey questionnaire to gain a deeper understanding of the cognition of construction industry practitioners toward the new generation of information technology [16]. The results showed that 3D modeling and sensing technology are currently the most widely adopted technologies, while virtual reality and additive manufacturing are the most promising future technologies [16]. Galera Zarco and Campos (2021) found that prefabricated production not only has a significant impact on project costs, timelines, and quality, but also subtly influences the business model of enterprises. The integration trend between construction enterprises and prefabricated component suppliers is gradually expanding [17]. He et al. (2018) believed that the rapid development of e-commerce could help enterprises solve the problem of large and scattered stakeholders and proposed an Internet procurement platform based on Building Information Modeling (BIM) to achieve real-time query of information and processes [18]. Popovic et al. (2022) proposed that general contractors need to constantly adjust their strategies and products to adapt to the changes in market environment and product demand brought about by construction industrialization [19]. However, this strategic adjustment is ineffective due to market information asymmetry, and vertical integration of enterprises can largely avoid the problem of information asymmetry [19]. Dhawan et al. (2023) also believed that the decentralized construction supply chain leads to information delays and inefficiencies at the delivery interface at each stage of the project, which is exactly the problem that vertical integration can avoid [20]. By comparing construction industrialization with manufacturing industrialization, Mansoori et al. (2024) found that systematic integrated data management in the industrial chain contributes to higher production efficiency of the manufacturing industry compared to the construction industry [21]. Guo and Li (2022) put forward a framework for advancing construction industrialization, in which industrial synergy and structural synergy are important driving forces for enterprises to develop towards construction industrialization [22]. To sum up, although construction industrialization can improve productivity, enterprises must constantly change their strategies to meet the needs of construction industrialization. The vertical integration of the industrial chain is considered to be the main method to help enterprises adapt to construction industrialization, but in terms of how to implement the integration, there is a lack of exploration of related paths.

2.2. Industry Chain of Construction Industrialization

Amidst the challenge of construction industrialization, vertical integration, green and low-carbon initiatives, and technological innovation have emerged as the mainstream trends for the future transformation and development of construction enterprises [23]. A well-developed industrial chain is an important strategic driving force for enterprise transformation and development [24,25]. Ruan and Choi (2023) found in their study on the economic profits of enterprises in the post-pandemic era that the technological innovation profits of industrial chain enterprise alliances are 34.2% higher than those of individual enterprises [26]. Teng and Lin (2024) found in their study on panel data of China’s industrial chain from 2002 to 2017 that the synergistic division of labor effect in the industrial chain can significantly improve resource utilization by improving labor productivity and enterprise competitiveness, and this effect is more pronounced in high-energy-consuming and high-pollution industries [27]. Ji et al. (2022) believed that the construction industrialization industry chain is the driving force for promoting the sustainable development of construction enterprises. In addition, the integration of construction enterprises is the foundation for the coordinated development of the industry chain [23]. Therefore, developing towards the industrial chain of construction industrialization is an important strategic direction for general contractors to reduce resource and labor costs, strengthen technological innovation capabilities, and thereby improve the added value and profits of enterprise products. The main approach for achieving this is enterprise integration. The Chinese Ministry of Housing and Urban Rural Development also believes that the construction industrialization industry chain can guide general contractors to target the final product and comprehensive benefits of construction, and promote resource sharing, system integration, and coordinated development of the upstream and downstream of the industry chain. The ministry also defines the construction industrialization industry chain as an industry chain that covers the production and transportation of components, construction installation, and operation and maintenance.

In practice, the integration between general contractors, prefabricated component suppliers, and construction developers is not only conducive to reducing the pressure on upstream prefabricated component suppliers in the industry chain’s research and development costs, promoting material research and development to improve the sustainability of prefabricated buildings, but also promotes the adoption and sales of prefabricated buildings, thereby promoting the development of the construction industry [28]. Liu et al. (2020) conducted a systematic review of 152 precast supply chains from 2001 to 2018 and found that integration and management of supply chains is becoming a mainstream trend [29]. Therefore, studying the strategic vertical integration of general contractors in the context of the construction industrialization industry chain has profound practical necessity. However, further research should be conducted on which integration strategy can bring the best profits. Salinger et al. (1988) argued that vertical consolidation from upstream enterprises to downstream can increase the product prices and increase the profits of integrated enterprises [30]. Fan et al. (2017) believed that enterprises can avoid a series of transaction difficulties caused by external environmental factors through vertical integration, reduction in transaction costs, and expansion of market demand [31]. Wei et al. (2019) argued that the bidirectional integration strategy brings more profits to enterprises than upstream and downstream integration, but upstream and downstream integration does not affect the total profit of the industrial chain [32]. It has become a research consensus that the implementation of integration strategy can improve profits, but how to simultaneously increase the total profit of the industrial chain still needs further research. Therefore, the main research objective of this paper is to select the strategies that can bring the maximum profit to the general contractors through bidirectional, forward, and backward integration strategies and to maximize the total profit of the industrial chain as much as possible. Next, the research methods will be discussed.

2.3. Methods of Strategic Choice

SWOT analysis, system dynamics, and game theory are currently the main research methods for strategic choices. Wang et al. (2022) used SWOT analysis to study the strengths, weaknesses, opportunities, and threats of rural e-commerce development in Shenyang City, and combined the hierarchical analysis method to calculate the weights of the influencing factors, put forward a strategy to help rural e-commerce develop [33]. Gao and Zhao (2020) used system dynamics to simulate the evolutionary game model of government, investors, and the public in public–private partnership projects and analyzed the equilibrium point and important influencing factors of the three parties’ win–win situation [34]. Zhang et al. (2023) combined evolutionary game theory and system dynamics simulation to investigate the impact of government regulation on the safety management of general contractors during the construction process of prefabricated buildings [35]. Zhou et al. (2021) established a tripartite game model based on Stackelberg theory, which includes logistics service providers, property service enterprises, and customers. They compared and analyzed the resource and cost allocation under different cooperation modes and solved the profit allocation problem of the last mile industry in the distribution industry [36]. Bo and Ning (2022) studied the strategic choices of distributors and recyclers in the supply chain context of scrapped electronic and electrical equipment based on the Stackelberg game model, achieving the maximization of profits between distributors and the supply chain [37]. Liu et al. (2017) established a Stackelberg game model with one manufacturer and multiple retailers, studied the cooperation between them under different direct sales costs, and verified the results through numerical simulations [38].

The research methods for strategic choice primarily include SWOT analysis, system dynamics, and game theory. The SWOT analysis can create new development strategies based on the existing industry environment and enterprise situation. System dynamics is generally combined with evolutionary game models to simulate and analyze the long-term effects of a single established strategy, such as policy effects and management profits. The Stackelberg game model selects the optimal strategy suitable for the enterprise from several alternative development strategies, which can achieve the goal of maximizing profits between the enterprise and the industrial chain. Therefore, this paper deems the Stackelberg game model appropriate in examining the integrated strategic choice problem of general contractors.

3. Model Description and Basic Assumptions

3.1. Logical Framework for the Research

The workflow of this research method is shown in Figure 1 and comprises five sub-sections: literature review, modeling decision making, modeling the game, numerical simulation and results, and discussion.

3.2. Model Description

This paper considers that the construction industrialization industry chain operates across three levels: a prefabricated component supplier, a general contractor, and a construction development enterprise. The prefabricated component supplier provides prefabricated components to the general contractor. The general contractor builds projects for the construction development enterprise, and the construction development enterprise sells prefabricated residential buildings to consumers. Figure 2 illustrates the specific decision-making process, which aims to maximize the profits of the general contractors while increasing the profits of the industrial chain.

In this strategic decision-making model, the general contractor can choose to implement an integrated strategy based on the proportion of resource investment, as shown in Figure 3. This paper assumes that the resource value required for vertically expanding the prefabricated component supplier and the construction development enterprise is equal, and both are 1. Thus, the number of resources required for centralized decision making in the industrial chain is 2. In the integration strategy, three strategies are based on the different vertical integration directions of general contractors: backward integration, where general contractors integrate prefabricated component suppliers; forward integration, where general contractors integrate construction development enterprises; and bidirectional integration, where general contractors integrate both types of enterprises.

3.3. Basic Assumptions

Appendix A shows the notations and parameter descriptions used in the research institute with specific explanations as follows:

(1) Sustainable development performance refers to the benefits of comfortable and safe living for consumers, and the economic benefits of thermal insulation and energy and power savings. The initial sustainable development performance of the prefabricated building is $v_0$, but it can be improved to $v$ through the R&D and innovation of the prefabricated component suppliers; thus, ${0<v}_0<v$. At the present stage, the prefabricated components of the technology research and development patents are chiefly concentrated in the main structure and the building enclosure, overall kitchen, overall bathroom, and other parts and components of the two major directions. The patent heat of the main structure has dominated in the past two decades, and its R&D and innovation technology is close to maturity, so the main goal in the future is to reduce costs; the invention patent heat related to the parts and components is higher than the overall level, and it may become the dominant future direction of the R&D and innovation of prefabricated components for prefabricated buildings. Owing to the diminishing returns of the technology R&D and innovation expenditures or the dis-economical effect of the scale of investment, the cost function of this part of the R&D investment is assumed as $k({v-v}_0{)}^2/2$ [39]. $k$ is the R&D investment cost coefficient of the prefabricated component suppliers, which reflects their R&D and innovation capabilities. The main structure of R&D activities reduces the cost of prefabricated components $\alpha w$. In the paper, the cost of such R&D is assumed as $k{\alpha }^2{w}^2$, where $\alpha$ is any number between 0 and 1.

(2) The cost and price of prefabricated components are $w$ and $p_e$, respectively. The engineering cost and contract price are $c_n$ and $p_{n,}$ respectively. The selling price of prefabricated buildings is $p$. $c_r$ refers to the marketing costs and land costs for construction and development enterprises.

(3) The market demand is jointly determined by sustainable development performance, selling price, and operation and maintenance cost. Thus, a linear demand function form $Q=a-bp+\theta v$ [40] is used to represent the market demand for prefabricated buildings. Among them, $a$ denotes meeting the potential market demand for prefabricated buildings; $b$ is the price coefficient; $a,b$ are any positive constant; $p$ is the selling price for prefabricated buildings; and $\theta$ is the coefficient of consumer preference for the sustainable development performance of prefabricated buildings.

In this paper, $\pi$ represents profits; the lower right subscripts X, Y, Z, and M, respectively, represent prefabricated component suppliers, general contractors, construction development enterprises, and industrial chains. The upper right subscripts T, B, A, and D, respectively, represent centralized decision making, forward integration, backward integration, and bidirectional integration strategies.

4. Solution of Game Model in Different Strategic Situations

4.1. Centralized Decision Making

Centralized decision making can be seen as only the general contractors conducting all businesses in the industrial chain. The general contractors aim to maximize the profits of the entire industrial chain and have the decision-making power over the sustainable development performance and selling price of the prefabricated buildings. At this time, the objective function of the industrial chain system is as follows:

$${\pi }_M^T=\left[p-c_m-c_e-\left(1-\alpha \right)w\right]\left(a-bp+\theta v\right)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}-k{\alpha }^2{w}^2.$$

(1)

Solve for ${\partial }^2{\pi }_M^T(p,v)/\partial p^2$ = A, ${\partial }^2{\pi }_M^T(p,v)/\partial v^2=C$ and ${\partial }^2{\pi }_M^T(p,v)/\partial p\partial v=B$, respectively. Assume that $AC-B^2=2kb-v^2>0$, at which point ${\pi }_M^T$ is a concave function with respect to $p \mathrm{a}\mathrm{n}\mathrm{d} v$, and an extreme value exists. According to $\partial {\pi }_M^T(p,v)/\partial p=0 \mathrm{a}\mathrm{n}\mathrm{d} \partial {\pi }_M^T(p,v)/\partial v=0$, the optimal decision of the industrial chain during centralized decision making can be obtained as follows:

$$v^T={\displaystyle \frac{\theta \left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w\right]+2kb{v}_0}{2kb-{\theta }^2}},$$

(2)

$$p^T={\displaystyle \frac{k\left[a+b{c}_m+b{c}_r+b\left(1-\alpha \right)w+\theta v_0\right]-{\theta }^2\left(b{c}_m+b{c}_r+b\left(1-\alpha \right)w\right)}{2kb-{\theta }^2}}.$$

(3)

Furthermore, the market demand for prefabricated buildings under a centralized decision-making strategy $Q^T$, and the profit from the industrial chain ${\pi }_M^T$ can be obtained as follows:

$$Q^T={\displaystyle \frac{kb\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}{2kb-{\theta }^2}},$$

(4)

$${\pi }_M^T={\displaystyle \frac{k[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{2\left(2kb-{\theta }^2\right)}}-k{\alpha }^2{w}^2.$$

(5)

Accordingly, when the industrial chain is centralized for decision making, the optimal decision for the entire industrial chain of construction industrialization is $(p^T,v^T,Q^T)$, and the profit of the industrial chain is ${\pi }_M^T$.

4.2. Backward Integration Strategy

With the backward integration strategy, the proportion of resources invested by the general contractors in expanding the business of the prefabricated component suppliers is ${\lambda }_1[{\lambda }_1\in \left(\mathrm{0,1}\right)]$. Under this strategic scenario, the profit functions of the prefabricated component suppliers, the general contractors, and the construction development enterprises are, respectively, represented as follows:

$${\pi }_X^A\left(v,p_e\right)=\left(1-{\lambda }_1\right)\left\{\left[p_e-\left(1-\alpha \right)w\right](a-bp+\theta v)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}-k{\alpha }^2{w}^2\right\}.$$

(6)

s.t.

$$\begin{array}{cc}{\pi }_Y^A\left(p_n\right)=(p_n-c_m)& (a-bp+\theta v)+{\lambda }_1\left\{\left[p_e-\left(1-\alpha \right)w\right](a-bp+\theta v)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}\right\}\\ & -\lambda k{\alpha }^2{w}^2,\end{array}$$

(7)

$${\pi }_Z^A\left(p\right)=(p-p_n-p_e-c_r)(a-bp+\theta v).$$

(8)

Similarly, the optimal response function for the construction development enterprises is obtained as follows:

$$p={\displaystyle \frac{a+\theta v+b\left(p_n+p_e+c_r\right)}{2b}}.$$

(9)

Substituting Equation (9) into Equation (7) yields:

$$p_n={\displaystyle \frac{a+\theta v+b\left(c_m-c_r-p_e-\lambda p_e\right)+{\lambda }_{1}b\left(1-\alpha \right)w}{2b}}.$$

(10)

Therefore,

$$p={\displaystyle \frac{3a+3\theta v+b\left(c_m+p_e+c_r\right)+{\lambda }_{1}b\left(1-\alpha \right)w-\lambda b{p}_e}{4b}}.$$

(11)

Equation (11) is applied to the profit function of the prefabricated component suppliers ${\pi }_Y^N\left(v,p_e\right)$; adjusting the ${\pi }_Y^N\left(v,p_e\right)$ to determine the second partial derivative, it can be judged that ${\pi }_X^N$ is the concave function of $v$ and $p_e$. The maximum value at a certain point indicates the existence of a uniquely optimal selling price and sustainability performance of the prefabricated component suppliers. Taking the first-order derivative of $p_e$ and $v$, respectively, and making them 0, Equations (12) and (13) can be obtained as follows:

$$p_e^A={\displaystyle \frac{4k\left(a-b{c}_m-b{c}_r+\theta v_0\right)+\left(1-\alpha \right)w\left(4kb-8kb{\lambda }_1-{\theta }^2\right)}{8kb\left(1-{\lambda }_1\right)-{\theta }^2}},$$

(12)

$$v^A={\displaystyle \frac{\theta \left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w\right]+8kb\left(1-{\lambda }_1\right)}{8kb\left(1-{\lambda }_1\right)-{\theta }^2}}.$$

(13)

Substituting $p_e^A$ and $v^A$ into Equations (10) and (11) further yields the following:

$$p^A={\displaystyle \frac{k\left(1-{\lambda }_1\right)\left[7a+b{c}_m+b{c}_r+7\theta v_0+b\left(1-\alpha \right)w\right]-{\theta }^2\left[c_m+c_r+\left(1-\alpha \right)w\right]}{8kb\left(1-{\lambda }_1\right)-{\theta }^2}},$$

(14)

$$p_n^A={\displaystyle \frac{2k\left[\left(1-3{\lambda }_1\left)\right(a+b{c}_m+\theta v_0-b{c}_r-bw+\alpha bw\right)+\left(3-{\lambda }_1\right)b{c}_m\right]-{\theta }^2{c}_m}{8kb\left(1-\lambda \right)-{\theta }^2}},$$

(15)

$$Q^A={\displaystyle \frac{k\left(1-{\lambda }_1\right)\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}{8kb\left(1-{\lambda }_1\right)-{\theta }^2}}.$$

(16)

Substituting the above five optimal decision variables into the backward integration profit function, the profit of prefabricated component suppliers ${\pi }_X^A$, the profit of general contractors ${\pi }_Y^A$, and the profit of construction development enterprises ${\pi }_Z^A$ under the backward integration strategy can be obtained as follows:

$${\pi }_X^A={\displaystyle \frac{k\left(1-{\lambda }_1\right){\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}^2}{{2\left[8kb\left(1-{\lambda }_1\right)-{\theta }^2\right]}^2}}-\left(1-{\lambda }_1\right)k{\alpha }^2{w}^2,$$

(17)

$${\pi }_Y^A={\displaystyle \frac{k\left[4kb{\left(1-{\lambda }_1\right)}^2-{\theta }^2{\lambda }_1\right]{\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}^2}{{2\left[8kb\left(1-{\lambda }_1\right)-{\theta }^2\right]}^2}}-{\lambda }_{1}k{\alpha }^2{w}^2,$$

(18)

$${\pi }_Z^A={\displaystyle \frac{k^{2}b{{\left(1-{\lambda }_1\right)}^2\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}^2}{{2\left[8kb\left(1-{\lambda }_1\right)-{\theta }^2\right]}^2}},$$

(19)

$${\pi }_Z^A={\displaystyle \frac{\left\{k\left(1-{\lambda }_1\right){+k}^{2}b{\left(1-{\lambda }_1\right)}^2+\left.k\left[4kb{\left(1-{\lambda }_1\right)}^2-{\theta }^2{\lambda }_1\right]\right\}\right.G^2}{{2\left[8kb\left(1-{\lambda }_1\right)-{\theta }^2\right]}^2}}-k{\alpha }^2{w}^2.$$

(20)

Among them, G = $\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]$.

Accordingly, when the general contractors implement the backward integration strategy, the optimal decision for the entire industrial chain of construction industrialization is $(p_e^A,v^A,p_n^A,p^A,Q^A)$. At this point, the profits of the prefabricated component suppliers, the general contractors, and the construction development enterprises are $({\pi }_X^A,{\pi }_Y^A,{\pi }_Z^A)$, respectively, and the profit of the industrial chain is ${\pi }_M^A$.

$${\pi }_M^T-{\pi }_M^A={\displaystyle \frac{2k[{8kb\left({\lambda }_1-1\right)+{\theta }^2{]}^2-5k^{2}b\left({\lambda }_1-1\right)}^2+2k(1-{\lambda }_1)(2kb-{\theta }^2)}{2\left(2kb-{\theta }^2\right){\left(8kb-{\theta }^2\right)}^2}}\ast G^2.$$

(21)

According to $\left(2kb-{\theta }^2\right)>0,$ $(128-5)k^{2}b\left({\lambda }_1-1\right)>0$, ${\pi }_M^B-{\pi }_M^B>0$. The industrial chain profit of the general contractors implementing the backward integration strategy is smaller than the profit of the industrial chain when implementing centralized decision making. In this case, the coordination of the industrial chain cannot be achieved.

4.3. Forward Integration Strategy

With the forward integration strategy, the proportion of resources invested by the general contractors in expanding the business of the construction development enterprise is ${\lambda }_2({\lambda }_2\in (\mathrm{0,1})$. Under this strategic scenario, the profit functions of the prefabricated component suppliers, the general contractors, and the construction development enterprises are, respectively, as follows:

$${\pi }_X^B\left(v,p_e\right)=\left[p_e-\left(1-\alpha \right)w\right]\left(a-bp+\theta v\right)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}-k{\alpha }^2{w}^2.$$

(22)

s.t.

$${\pi }_Y^B\left(p_n\right)=(p_n-c_m)(a-bp+\theta v)+{\lambda }_2(p-p_n-p_e-c_r)(a-bp+\theta v),$$

(23)

$${\pi }_Z^B\left(p\right)=(1-{\lambda }_2)(p-p_n-p_e-c_r)(a-bp+\theta v).$$

(24)

As above, substituting Equation (9) into Equation (23) can also prove that it is a concave function. According to $d{\pi }_Z^B\left(p_n\right)/d{p}_n=0$, the optimal response function can be obtained as follows:

$$p_n={\displaystyle \frac{\left(1-{\lambda }_2\right)\left(a+\theta v-b{p}_e-b{c}_r\right)+b{c}_m}{b\left(2-{\lambda }_2\right)}}.$$

(25)

Equations (9) and (25) are brought into the profit function of the prefabricated component suppliers; by applying ${\pi }_X^B\left(v,p_e\right)$, the second partial derivative can be judged such that ${\pi }_X^B$ is the concave function of $v$ and $p_e$ that has a maximum value at a certain point. According to $\partial {\pi }_X^B\left(v,p_e\right)/\partial \left(p_e\right)=0$ and $\partial {\pi }_X^B\left(v,p_e\right)/\partial \left(v\right)=0$, $v$ and $p_e$’s most reactive function can be obtained as follows:

$$p_e^B={\displaystyle \frac{2k\left(2-{\lambda }_2\right)\left[a-b{c}_m-b{c}_r+\theta v_0+b\left(1-\alpha \right)w\right]-\left(1-\alpha \right){\theta }^{2}w}{4kb\left(2-{\lambda }_2\right)-{\theta }^2}},$$

(26)

$$v^B={\displaystyle \frac{\theta \left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w\right]+4kb{v}_0\left(2-{\lambda }_2\right)}{4kb\left(2-{\lambda }_2\right)-{\theta }^2}}.$$

(27)

Substituting $p_e^B$ and $v^B$ into Equations (23) and (24), the contract price of the general contractors and the selling price and market demand of the prefabricated building can be obtained. As above, ${\pi }_X^B$, ${\pi }_Y^B$, ${\pi }_Z^B,$ and ${\pi }_M^B$ can be further obtained as follows:

$${\pi }_X^B={\displaystyle \frac{k[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{2\left[4kb\right(2-{\lambda }_2)-{\theta }^2]}}-k{\alpha }^2{w}^2,$$

(28)

$${\pi }_Y^B={\displaystyle \frac{k^{2}b(2-{\lambda }_2)[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{\left[4kb\right(2-{\lambda }_2)-{\theta }^2{]}^2}},$$

(29)

$${\pi }_Y^B={\displaystyle \frac{k^{2}b(1-{\lambda }_2)[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{\left[4kb\right(2-{\lambda }_2)-{\theta }^2{]}^2}},$$

(30)

$${\pi }_M^B={\displaystyle \frac{k\left[2kb\right(7-{4\lambda }_2{-\theta }^2)G^2}{2\left[4kb\right(2-{\lambda }_2)-{\theta }^2{]}^2}}-k{\alpha }^2{w}^2.$$

(31)

Accordingly, when the general contractors implement the forward integration strategy, the optimal decision for the entire industrial chain of construction industrialization is $(p_e^B,v^B,p_n^B,p^B,Q^B)$. At this point, the profits of the prefabricated component suppliers, the general contractors, and the construction development enterprises are $({\pi }_X^B,{\pi }_Y^B,{\pi }_Z^A)$, respectively, and the profit of the industrial chain is ${\pi }_M^B$.

$${\pi }_M^T-{\pi }_M^B={\displaystyle \frac{2k^3{b}^2(3-{\lambda }_2{)}^2}{\left(2kb-{\theta }^2\right)\left[4kb\right(2-{\lambda }_2)-{\theta }^2{]}^2}}\ast G^2.$$

(32)

As can be seen from the above equation, ${\pi }_M^T-{\pi }_M^B>0$. The industrial chain profit of the general contractors implementing the forward integration strategy is smaller than the profit of the industrial chain when implementing centralized decision making. At this time, the coordination of the industrial chain cannot be achieved.

4.4. Bidirectional Integration Strategy

With the bidirectional integration strategy, resource investment proportion $\beta \left[\beta \in \left(\mathrm{0,1}\right)\right)]$ represents the resource investment of the general contractors when expanding the business of the prefabricated component supplier; resource investment proportion $\gamma \left[\gamma \in \left(\mathrm{0,1}\right)\right)]$ represents the resource investment of the general contractors when expanding the business of the construction development enterprises. Under this strategic scenario, the profit functions of the prefabricated component suppliers, the general contractors, and the construction development enterprises are, respectively, as follows:

$${\pi }_X^D\left(v,p_e\right)=\left(1-\beta \right)\left\{\left[p_e-\left(1-\alpha \right)w\right]\left(a-bp+\theta v\right)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}-k{\alpha }^2{w}^2\right\},$$

(33)

s.t.

$$\begin{array}{cc}{\pi }_X^D\left(p_n\right)=& \left(p_n-c_m\right)\left(a-bp+\theta v\right)+\gamma (p-p_n-p_e-c_r)(a-bp+\theta v)\\ & +\beta \left\{\left[p_e-\left(1-\alpha \right)w\right]\left(a-bp+\theta v\right)-{\displaystyle \frac{k({v-v}_0{)}^2}{2}}-k{\alpha }^2{w}^2\right\}\end{array},$$

(34)

$${\pi }_Z^N\left(p\right)=(1-\gamma )(p-p_n-p_e-c_r)(a-bp+\theta v).$$

(35)

As above, using a backward stochastic differential equation, substituting Equation (9) into Equation (34) can be proven to be a concave function. According to $d{\pi }_Z^B\left(p_n\right)/d{p}_n=0$, the optimal response function can be obtained as follows:

$$p_n={\displaystyle \frac{\left(1-\gamma \right)\left(a+\theta v-b{p}_e-b{c}_r\right)-\beta b[p_e-\left(1-\alpha \right)w]+b{c}_m}{b\left(2-\gamma \right)}}.$$

(36)

Equations (9) and (36) are introduced into the profit function of the prefabricated component suppliers; applying ${\pi }_X^D\left(v,p_e\right)$ to determine the second partial derivative, it can be judged that ${\pi }_X^D$ is the concave function of $v$ and $p_e$, and there is a maximum value at a certain point. According to $\partial {\pi }_X^B\left(v,p_e\right)/\partial \left(p_e\right)=0$ and $\partial {\pi }_X^B\left(v,p_e\right)/\partial \left(v\right)=0$, $v$ and $p_e$’s most reactive function can be obtained:

$$p_e^D={\displaystyle \frac{2k\left(2-\gamma \right)\left[a-b{c}_m-b{c}_r+\theta v_0+b\left(1-\alpha \right)w\right]+\left(1-\alpha \right)w\left[4kb\beta \left(1-\alpha \right)\left(\gamma -2\right)-{\theta }^{2}w\right]}{4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2}},$$

(37)

$$v^D={\displaystyle \frac{\vartheta \left(a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w\right)+4kb{v}_0\left(1-\beta \right)\left(2-\gamma \right)}{4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2}}.$$

(38)

Further, through the above equation, the market demand for prefabricated buildings under the bidirectional integration strategy $Q^D$, the sustainable performance of prefabricated buildings determined by prefabricated component suppliers $v^D$, the price of prefabricated components $p_e^D$, the cost excluding prefabricated components in the construction price to be paid by the general contractors $p_n^D$, and the selling price determined by the construction development enterprises $p^D$ can be obtained as follows:

$$p_n^D={\displaystyle \frac{2k\left[\left(1-\gamma \right)\left(1-2\beta \right)-\beta \right]\left[a-b{c}_r+\theta v_0-b\left(1-\alpha \right)w\right]+2kb{c}_m\left(3-\beta -\gamma \right)-{\theta }^2{c}_m}{4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2}},$$

(39)

$$P^D={\displaystyle \frac{k\left(1-\beta \right)\left(7-4\beta \right)\left(a+\theta v_0\right)+\left[kb\left(1-\beta \right)-{\theta }^2\right]\left[c_m+c_r+\left(1-\alpha \right)w\right]}{4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2}},$$

(40)

$$Q^D={\displaystyle \frac{kb\left(1-\beta \right)\left[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0\right]}{4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2}}.$$

(41)

Substituting the above five optimal decision variables into the backward integration profit function, the profit of prefabricated component suppliers ${\pi }_X^D$, the profit of general contractors ${\pi }_Y^D$, and the profit of construction development enterprises ${\pi }_Z^D$ under the forward integration strategy can be obtained as follows:

$${\pi }_X^D={\displaystyle \frac{k(1-\beta )[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{2\left[4kb\left(1-\beta \right)\left(2-\gamma \right)-{\theta }^2\right]}}-\left(1-\beta \right)k{\alpha }^2{w}^2,$$

(42)

$${\pi }_Y^D={\displaystyle \frac{[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2[2k^{2}b(1-\beta {)}^2\left(3-2\gamma \right)-{\theta }^2\beta ]}{2\left[4kb\right(1-\beta \left)\right(2-\gamma )-{\theta }^2{]}^2}}-\beta k{\alpha }^2{w}^2,$$

(43)

$${\pi }_Z^D={\displaystyle \frac{k^{2}b(1-\beta {)}^2(1-\gamma \left)\right[a-b{c}_m-b{c}_r-b\left(1-\alpha \right)w+\theta v_0{]}^2}{\left[4kb\right(1-\beta \left)\right(2-\gamma )-{\theta }^2{]}^2}},$$

(44)

$${\pi }_M^D={\displaystyle \frac{\left[2kb\right(1-\beta {)}^2\left(5-3\gamma \right)-{\theta }^2]G^2}{2\left[4kb\right(1-\beta \left)\right(2-\gamma )-{\theta }^2{]}^2}}-k{\alpha }^2{w}^2.$$

(45)

Accordingly, when the general contractors implement the backward integration strategy, the optimal decision for the entire industrial chain of construction industrialization is $(p_e^D,v^D,p_n^D,p^D,Q^D)$. At this point, the profits of the prefabricated component suppliers, the general contractors, and the construction development enterprises are, respectively, $({\pi }_X^D,{\pi }_Y^D,{\pi }_Z^D)$, and the profit of the industrial chain is ${\pi }_M^D$.

$${\pi }_M^D-{\pi }_M^T={\displaystyle \frac{k\left[3kb\right(1-\beta {)}^2(5-3\gamma {)}^2-{\theta }^2(4-\beta \left)\right(7-3\gamma \left)\right]}{4\left(2kb-{\theta }^2\right)\left[4kb\right(1-\beta \left)\right(2-\gamma )-{\theta }^2{]}^2}}\ast G^2.$$

(46)

As can be seen from the above equation, when the general contractors implement the bidirectional integration strategy and when $3kb(1-\beta {)}^2(5-3\gamma {)}^2-{\theta }^2(4-3\beta )\left(7-3\gamma \right)=0,{\pi }_M^D={\pi }_M^T$,

$${\displaystyle \frac{3kb}{{\theta }^2}}={\displaystyle \frac{(1-\beta {)}^2(5-3\gamma {)}^2}{\left(4-3\beta \right)\left(7-3\gamma \right)}}.$$

(47)

Thus, it can achieve industrial chain coordination.

5. Numerical Simulation

This paper uses MATLAB 2023 to illustrate the impact of implementing a bidirectional integration strategy for the general contractors on the optimal decision making of the entire industrial chain of construction industrialization through numerical examples and then conduct an analysis on this basis. This section numerically simulates the effects of resource investment ratios $\beta$ and $\gamma$ in forward and backward integration strategies on the profit of the general contractors and the profit of industrial chain, respectively. Subsequently, it simulates the combined effects of $\beta$ and $\gamma$ on the profit of the general contractors and industrial chain. Drawing on relevant research [41,42], the model parameters are set as follows: $a=100, b=0.8, w=20, c_m=20, c_r=25, v_0=5, k=10, \theta =5, \alpha =0.15$.

5.1. Impact of Resource Investment Proportion β

Under the setting of the above parameters, $\gamma$ is taken to be 0.2, 0.4, and 0.6, respectively, to analyze the impact of the resource investment ratio $\beta$ invested in the prefabricated component suppliers on the sustainable development performance of the prefabricated buildings, the profit of the general contractors, and the profit of the industrial chain. Figure 4, Figure 5 and Figure 6 show the results.

From Figure 4, the sustainable development performance of the prefabricated buildings constantly increases with the proportion of resources required for the vertical expansion of prefabricated component suppliers by the general contractors. In addition, this trend grows faster as resource investment increases.

The reason is that through the resources invested by the general contractors, it can enable the general contractors to bear part of the research and development costs of prefabricated components, thereby reducing the innovation obstacles caused by high research and development costs for the prefabricated component suppliers. Therefore, it can effectively improve the motivation of the prefabricated component suppliers to conduct research and development and increase the sustainable development performance of the prefabricated buildings. From an economic perspective, implementing backward integration strategies by the general contractors has a cumulative effect on the utility of the prefabricated buildings. Although conducting R&D and innovation activities in enterprises can bring benefits, being imitated by later innovators or imitators will make this part of the benefits disappear. To ensure the sustained or innovative benefits and continuous improvement of enterprises, establishing a Sumpit rent isolation mechanism is necessary [43]. When an enterprise continues to invest in research and development and the isolation mechanism brings more profits to the enterprise than the R&D investment funds, it marks the formation of the isolation mechanism. At this time, innovation activities will enable the company to obtain further extraordinary income. In today’s highly competitive market environment, one-time innovation activities may bring unexpected profits to enterprises. However, these profits are often unsustainable. The use of accidental innovation activities makes the transformation and development of enterprises increasingly unattainable. Therefore, what enterprises need to do is to continuously invest in research and development to bring cumulative effects, which is more demonstrative. The cumulative effect of R&D investment has been proven to exist in high-tech and manufacturing industries, and the simulation results of the game model in this paper also indicate that construction enterprises also have cumulative effects. For the government, the various preferential policies introduced should not only focus on whether enterprises meet certain technical conditions and whether R&D investment meets standards, such as the star rating evaluation standards for green buildings. The government can consider providing sustained policy incentives to enterprises engaged in research and development innovation. This scenario not only helps enterprises accumulate benefits through continuous investment, but also prevents some enterprises from stealing policy incentives through false innovation.

As can be seen from Figure 5 and Figure 6, when the proportion of resources invested by the general contractors backward to the expanding precast component supply enterprise is appropriate, the profit of the general contractors and the industry chain increases with the increase in the proportion of resources invested $\beta$. In addition, when the proportion of resources invested by the general contractors backward to the expanding precast component supply enterprise $\beta$ is larger, the profit of the general contractors and the industry chain decreases with the increases and decreases. This phenomenon occurs because when the proportion of resource investment is small, the general contractors invest less in the prefabricated component suppliers, which enables the general contractors to bear the research and development costs, promote the research and development innovation of the prefabricated component suppliers, improve the sustainable development performance of the prefabricated buildings, increase the market demand for the prefabricated buildings, and consequently improve the profits of the general contractors and the entire industry chain. When the proportion of resource investment is large, the R&D expenses borne by the prefabricated component suppliers are far less than the profits obtained by their general contractors, leading to the phenomenon of “free riding”, increasing the unfair psychology of the prefabricated component suppliers, inhibiting their enthusiasm for R&D activities, and thus reducing the profits of the general contractors and industrial chains.

5.2. Impact of Resource Investment Proportion γ

With the above parameters set, $\beta$ is taken as 0.3, 0.5, and 0.7 to analyze the impact of the proportion of resources invested $\gamma$ in the prefabricated component suppliers on the sustainable development performance of prefabricated buildings, the profit of the general contractors, and the profit of the industrial chain. Figure 7, Figure 8 and Figure 9 show the results. It can be seen that the sustainable development performance of prefabricated building and industry chain profit both increase with the increase in the proportion of forward investment resources. This trend will be more positive with higher proportions of forward investment resources allocated by the general contractors. The profit of the general contractors shows a decreasing and then increasing trend because of the land cost and marketing cost. However, it also shares the capital pressure of the construction development enterprises, which effectively improves their sales momentum. Bulan et al. (2009) argued that a company’s capital investment largely affects its strategic behavior in market competition, but the market environment also has a reverse effect on the company’s capital allocation [44]. When in a fierce market environment, the profit margin of a company is compressed by competitors, leading to a decrease in cash flow. External investors will keenly capture signals of a decline in the company’s debt-paying ability, increasing the difficulty for the company to obtain capital investment. Construction development enterprises are in a fiercely competitive market, which indicates that they are highly susceptible to financing constraints. Moreover, the risk of being squeezed by competitors in the industry is substantially increased. At this time, the investment of funds and resources by the general contractors and construction development enterprises has increased their enthusiasm to use the investment to improve their competitive position. Therefore, the increase in profits of construction development enterprises has driven the increase in profits of the general contractors and industrial chains.

The increasing market demand for prefabricated buildings has brought additional profits to the prefabricated component suppliers, which have a positive impact on their research and development activities. The reason may be that prefabricated component suppliers carry out research and development activities based on the needs of the final customers. Additionally, the gradual increase in market demand reduces the uncertainty of enterprise research and development innovation investment while increasing the conversion rate of achievements. Moreover, in the post-pandemic era of economic downturn, the market demand in the construction industry has shown a clear downward trend. When market demand is sluggish, enterprises will reduce their R&D investment to maintain their profit margins. The increase in market demand will induce enterprises to increase their research and development intensity, and reasonably increasing consumer demand can promote enterprises to improve supply quality. Therefore, the increase in demand has increased the enthusiasm of enterprises for innovation.

5.3. Impact of Resource Investment Proportion β and γ

Under the setting of the above fixed parameters, the comprehensive impacts of investment resource ratios $\beta$ and $\gamma$ of the prefabricated component suppliers on the sustainable development performance of prefabricated buildings, the profit of the general contractors, and the profit of industrial chain are analyzed. Figure 10, Figure 11 and Figure 12 show the results. In Figure 9, the sustainable development performance of the prefabricated buildings increases with the increase in the resource investment ratios $\beta$ and $\gamma$. The degree of influence of the backward investment resource ratio $\gamma$ of the general contractors on the sustainable development performance of prefabricated buildings is greater than the degree of influence of the forward investment resource ratio $\beta$, and this trend increases faster with the increase in the resource investment proportion. From Figure 11 and Figure 12, the general contractors can be seen to increase with the increase in the proportion of resource investments $\beta$ and $\gamma$, but the industry chain profit increases first and then decreases, which confirms that $3kb(1-\beta {)}^2(5-3\gamma {)}^2-{\theta }^2(4-3\beta )\left(7-3\gamma \right)=0$ makes the industry chain coordinated. This finding shows that the bidirectional integration strategy can maximize the profits of the general contractors while realizing the coordination of the industry chain, which is the optimal development strategy in the entire industry chain of construction industrialization of the general contractors.

This study used a three-level industry chain game model of a general contractor to solve the impact of five alternative strategies on industry chain profits and enterprise profits. The correctness of the derived formula was verified through MATLAB numerical simulation, and the results were further visualized intuitively. The results indicate that when implementing a bidirectional integration strategy, under specific resource ratio conditions, enterprises successfully maximize profits while achieving full industry chain coordination. At this time, resource investment is less than centralized decision making in the industry chain, reflecting the advantages of industry chain resource coordination. The industrial chain has stimulated the synergistic effect of vertical integration and diversification strategies and achieved advantages such as business integration and value appreciation through internal resource management allocation and re-layout of industrial chain resources within the enterprise.

6. Conclusions

Given the challenges of construction industrialization, the existing development strategies of the general contractors are no longer able to meet the requirements brought about by changes in the industry environment. Thus, helping the general contractors choose the optimal development strategy in the context of construction industrialization has profound value and significance. This paper reviews the research methods of strategic choices and adopts the Stackelberg game model. Based on the positioning of the enterprise’s industrial chain, a game model for strategic choices is established. Through model solving and MATLAB numerical simulation, the optimal development strategy is found to be a bidirectional integrated development strategy, that is, expanding building development business forward and prefabricated component business backward. The specific research conclusions are as follows:

(1) In the analysis of the backward integrated game model, we found that the prefabricated component suppliers have a bear bit rental mechanism for technological innovation. Enterprises rely on accidental innovation activities to make their transformation and development increasingly impossible. Therefore, continuous R&D investment is needed to bring cumulative effects. For the general contractors, the backward integration strategies need long-term investments to obtain a cumulative effect, so they can consider the forward and then backward bidirectional integration development strategy. For the government, the various preferential policies introduced should not only focus on whether enterprises meet the one-time standard. The government can consider providing sustained policy incentives to enterprises engaged in research and development innovation. This scenario not only helps enterprises accumulate benefits through continuous investment but also prevents some enterprises from stealing policy incentives through false innovation.

(2) In the analysis of the forward integration game model, the integration of activities by the general contractors into the construction development enterprises shares the financial pressure of the construction development enterprises, effectively improving the sales motivation of the construction development enterprises and the enthusiasm to use capital investment to improve its competitive position.

(3) The results of solving, analyzing, and numerical simulation of the three-stage game model of “prefabricated components suppliers-general contractors-construction development enterprises” show that, without investing all the resources, the general contractors choose the bidirectional integration strategy to achieve the effect of industry chain centralized decision making. The strategy achieves the effect of centralized decision making in the industry chain, and the improvement of sustainable development performance of prefabricated buildings drives the improvement of industry chain profits. The latter not only meets the goal of profit maximization, but also coordinates the industry chain. Thus, bidirectional integration is the optimal strategy.

This research has the following limitations. The impact of competition among multiple general contractors or competition among multiple upstream and downstream enterprises on corporate profits is not considered in the modeling. Future research can be carried out from the following two aspects.

(1) As for the composition of the whole industrial chain of construction industrialization, the game model proposed in this paper only includes the upstream and downstream enterprises adjacent to the construction general contract. In fact, the whole process of engineering consulting enterprises, design institutes, financing institutions, and governments can also be included to establish a more comprehensive game model.

(2) In the construction of the game model, this paper did not consider the competition between multiple general contractors or the influence of competition between multiple upstream and downstream enterprises on corporate profits. In the future, studies can be considered in the whole industrial chain of one-to-many, many-to-one, and many-to-many.