Analysis of Critical Factors for the Entrepreneurship in Industries of the Future Based on DEMATEL-ISM Approach

Abstract

In the face of the fourth industrial revolution (Industry 4.0 era), in order to cope with the various crises that may come, countries around the world are accelerating the research and development of cutting-edge technologies and promoting and deploying the Industries of the Future in order to seize the high ground in the new round of strategic competition in science and technology. Therefore, entrepreneurship in Industries of the Future has become an urgent problem for governments and enterprises to solve. Entrepreneurship in Industries of the Future is a systematic project with uncertainties, which is dynamically influenced by many factors and has different levels of division among them. Inspired by the form of Porter’s diamond model, this paper constructs a diamond model of the driving mechanism of entrepreneurship in Industries of the Future. Using the DEMATEL-ISM analysis method, each critical factor and influence mechanism of entrepreneurship in Industries of the Future is explored, and a multi-level structural model is established. The study found eight critical factors affecting entrepreneurship in Industries of the Future, among which technology, creation, need, and aspiration are the critical factors, and relevant enterprises and governments should prioritize these influencing factors and deal with them.

1. Introduction

The world is currently entering the fourth industrial technology revolution (Industry 4.0 era), which is a manufacturing revolution based on the development of intelligent, digital technology [1], and with a new round of disruptive innovation, there will be waves of explosions of technology. The strategic game of major powers intensified. New technologies, new industries, and new business models are emerging, bringing challenges to countries around the world but also bringing a vital leapfrog development [2]. Based on Industry 4.0, Industries of the Future, driven by disruptive frontier technologies, have colossal development potential, are tomorrow’s strategic emerging industries and the pillar industries of the future, and will become the engine of social and economic development in the future [3]. Due to their technological disruptiveness and advanced nature, the development level of Industries of the Future will also determine a country’s international competitiveness, global industrial chain, supply chain control [4], national and industrial security, science, technology security, and other aspects that are closely related. Thus, promoting the deployment of Industries of the Future is a national strategic initiative to build a modern industrial system, promote social and economic growth, and reshape the competitive advantage of science and technology.

Industries of the Future is a new field and a new business for both entrepreneurs and investors, so it can be said that most of the R&D, production, and business activities engaged in Industries of the Future are of a typical entrepreneurial nature; therefore, those engaged in Industries of the Future are entrepreneurs themselves, which shows the important role of entrepreneurship in the development of Industries of the Future. At the same time, entrepreneurship in Industries of the Future has its unique characteristics compared to entrepreneurship in general industries, among which, mainly, the industries in future industries are not entirely profit-oriented, and interest, ambition, and social responsibility play an essential role in them. The uncertainty and risks faced by entrepreneurship in Industries of the Future are also much more severe. Therefore, it is undoubtedly of great theoretical and practical significance to study the problem of entrepreneurship in Industries of the Future.

At present, the development of the Industries of the Future is in full swing, but there are few theoretical studies or development mechanism studies on Industries of the Future. There needs to be more research on Industries of the Future’s conceptual content, influencing factors, and entrepreneurial behavior. For example, Luis argues that the current characteristics of the global economy define “knowledge-intensive services” (KIS) as part of the so-called “industry of the future” and that public policies can be used to promote the development of KIS. Using the local service industry in Mexico as an example [5], Chen Xiaoyi and others cite the latest deployment focus of the global Industries of the Future, that for the Industries of the Future development needs, it is necessary to build a new model of in-depth collaboration between industry, academia, and research while diversifying capital investment to support enterprise technology innovation and promote enterprise transformation and upgrading [6]. Hao Kun and others believe that new economic elements such as scenarios, new species of enterprises, and innovation ecology are the key to developing Industries of the Future and to promoting the tripartite participation of the market, enterprises, and the government in the joint governance mechanism of Industries of the Future, to strengthen future research traction and promote the development of Industries of the Future [7]. However, there is a richer body of scholarly research on entrepreneurial motivation; for example, some scholars consider entrepreneurial motivation as the “spark” and key to transforming entrepreneurial cognition and intention into entrepreneurial behavior [8,9]; those who are also able to maintain a strong and sustained belief in entrepreneurial activity are in the minority [10]. Some scholars believe that the external environment can have an impact on entrepreneurial motivation; support and encouragement from the entrepreneur’s surroundings [11], positive influence from family [12], influence from national policies [13], and relevant laws and regulations have a more significant impact on potential entrepreneurs. It can be seen that research on Industries of the Future is mainly practical case studies and policy and planning studies, and there needs to be more theoretical research in this area. Of course, there is a considerable body of research on entrepreneurial motivation. However, there is also a need for more research on the motivation aspect of entrepreneurship in Industries of the Future. The study in this paper tries to fill the gap in this area.

Therefore, it is necessary to conduct a comprehensive and systematic sorting of Industries of the Future, analyzing and studying the critical influencing factors of entrepreneurship in Industries of the Future to provide a reference for the government in formulating policies related to Industries of the Future and promoting the deployment of Industries of the Future.

The purpose of this paper is to clarify the various drivers of entrepreneurship in Industries of the Future, as well as to analyze the influence of the relationship between the drivers, the degree of influence, and the structural hierarchy. By sorting out the theoretical logic of the basic concept of entrepreneurship in Industries of the Future and combining the practical logic of Industries of the Future development in countries around the world, this paper provides reference for the government to formulate policies to promote entrepreneurship in Industries of the Future.

The contribution of this paper is, firstly, the establishment of the Industries of the Future influence factor system, which is designed according to three aspects of positive constrained and support and three profiles for each indicator, and this design is relatively novel. The second is establishing a diamond model of critical factors of Industries of the Future which shows the three-dimensional influence relationship and the resulting ISM hierarchy with theoretical innovation and practical inspiration.

The following parts of this paper are developed in the following order: firstly, we analyze the concept of Industries of the Future and its development status, elaborate on the characteristics of entrepreneurship in Industries of the Future, construct its critical factors influencing the diamond model, and use the DEMATEL-ISM method and questionnaire-based survey to carry out empirical analysis and stratified analysis of critical factors and influencing mechanisms of entrepreneurship in Industries of the Future. The results of the empirical analysis are discussed, and research recommendations are made. Finally, the whole paper is summarized and concludes with ideas for future research.

2. The Conceptual and Practical Analysis of Entrepreneurship in Industries of the Future

2.1. The Conceptual Analysis of Industries of the Future

Regarding the concept of “Industries of the Future,” scholars have conducted some preliminary studies. Although these studies have described the characteristics of Industries of the Future, they have yet to reach a consensus, and the contents and essence of the Industries of the Future still need to be accurately grasped. Chen Junying defined “Industries of the Future” earlier and believed that “Industries of the Future” is an industry based on the application of knowledge, focusing on the improvement of human beings’ quality of life and has inter-industry solid correlation [14]. Yu Donghua believes that the Industries of the Future is a forward-looking strategic new industry based on significant scientific and technological innovation and high-tech industrialization, which is future-oriented and determines the competitiveness and economic strength of the Industries of the Future and is a pioneering industry affecting the future and a leading industry supporting future economic development [15]. Yang Yucheng and others believe that Industries of the Future are the products of major scientific and technological breakthroughs and industrialization, leading to new application scenarios and new consumer needs under the paradigm change of science and technology innovation and are pioneer industries with strong traction [16]. Shen Hua et al. point out that Industries of the Future are industries that aim to meet new needs for future human and social development, are driven by emerging technological innovation, aim to expand the space for human understanding, enhance human capabilities, and promote sustainable social development [17].

The concepts of Industries of the Future and Industry 4.0 are also important links in academic research. The term “Industry 4.0” comes from the German government’s “Industry 4.0” initiative launched in 2011 to preserve the long-term competitiveness of manufacturing [18], Some analysts point out that “Industry 4.0” is not only limited to manufacturing but also covers every industry and sector including healthcare, supply chain management, etc. [19,20]. The concept of “Industry 4.0” is the introduction of networked intelligent systems that enable self-regulating production: people; machines; equipment; and products will communicate with each other [21]. “Smart manufacturing” or “digital manufacturing” can be considered as the core of “Industry 4.0,” and the use of “Industry 4.0“ technologies can improve the sustainability of manufacturing [22], where sustainability means achieving sustainable development through smart technologies to meet economic, environmental, and social needs [23], enabling the development of value chains and improving product quality and organizational performance [24], which coincides with the meaning of “industry of the future”.

The term “Industries of the Future” is also expressed differently in official documents. For example, the Shanghai Municipal Government pointed out in the “14th Five-Year Plan for the Development of Strategic Emerging Industries and Pioneer Industries in Shanghai” that “pioneer industries, also called Industries of the Future, refer to those industries that have an important strategic position in the economic system, can drive the development of other industries, play a guiding role in the future development of the national economy, and represent the direction of technological development and industrial upgrading.” Shenyang City points out in the “Shenyang Industries of the Future Cultivation and Development Plan (2018–2035)” that the Industries of the Future is an industrial ecosystem driven by the cross-fertilization of a new generation of information technology, new materials, new energy, biotechnology and industrial technology, which significantly drives productivity development, improves human beings’ quality of life, and leads economic and social development, involving various economic activities. Shanxi Province, in the “Fourteen Five” future industrial development plan, “mentioned: that the Industries of the Future is a new generation of information technology, new materials, new energy, new equipment, and modern industrial technology for the deep integration of the drive to support the future economic growth of strategic industries, determine the future direction of development of pioneering industries, affect the future development potential of Disruptive industries, forward-looking industries to enhance future competitiveness, with a global driving role and significant leading role in economic and social development, representing a new round of scientific and technological revolution and industrial change direction of development.”

From the above different scholars and official documents on the different concepts of “Industries of the Future,” it can be considered that the Industries of the Future refers to a forward-looking industry with broad future application prospects, relying on disruptive innovation technology to meet the needs of future social development and is at the same time high in risk but currently in the incubation stage.

As can be seen from the above definition, the future of industry has three main characteristics: (1) Disruptive. Disruptive technologies are those that replace existing mainstream technologies by changing the existing technological paradigm, generating new products and service functions with disruptive and disruptive effects on the industry or market landscape [25]. However, not all technological innovation can be called technological change, only a small portion of innovation has the potential to make a difference [26]; disruptive technologies exist in the time and space where a large number of technological changes emerge and are rapidly connected. (2) Infancy. The Industries of the Future is in the early stage of technology and industry development, in the stage of immaturity of both technology and market [27], so the Industries of the Future is infantile. Generally speaking, the formation and development of the Industries of the Future is relatively short, resulting in the immaturity of its related technology, and market need space has not yet opened. (3) Ultra-risky. Because of the uncertainty of the input and output of the Industries of the Future, it will bring super riskiness. The development of Industries of the Future depends on many factors, such as technological progress, market need and government policies; if the breakthrough of technology stagnates, it will not only make a large amount of resources invested in the early stage into the mire of sunk costs but also prevent the Industries of the Future from entering the industrialization stage, thus forming a vicious circle.

2.2. The Practical Status Quo of Industries of the Future

From an international perspective, the “Industries of the Future” has become a strategic highland of science and technology that countries worldwide are competing for, and it is crucial to winning a national sustainable competitive advantage. The new round of scientific and technological revolution and industrial change characterized by multi-disciplinary, interdisciplinary, and group breakthroughs is constantly giving rise to major disruptive technologies; the speed of transformation of scientific and technological achievements is significantly accelerated, and the form of industrial organization and industrial chain is showing a trend of increasing monopoly [28]. In the United States, for example, since 2019, the U.S. government has repeatedly proposed that it should invest in research and development in new technologies, such as artificial intelligence, advanced manufacturing, quantum information technology, and 5G communications, to safeguard the leadership position of the United States in those as mentioned above future new technologies. In October 2021, France proposed the development of industrial competitiveness and future technologies, including the energy industry, healthy food, space exploration, and other directions. In May 2020, Japan proposed to prioritize the development of critical technologies such as the Internet of Things and digital technologies that support a hyper-intelligent society. In November 2019, Germany considered the most important areas of fundamental innovation to be digitalization, the application of artificial intelligence, Internet of Things technologies, nanotechnology and biotechnology, new materials, light structure technologies, and the development of quantum computers.

In China, economic development is in the old and new dynamic energy transformation period. Some cities have started implementing “Industries of the Future” policies to become the engine of the new round of economic development. For example, Beijing mentioned vigorously developing strategic emerging industries, forward-looking deployment of quantum information, artificial intelligence, and other Industries of the Future, cultivating new technologies, products, and business models. Wuhan proposes strengthening frontier exploration and forward-looking deployment, promoting the incubation and acceleration of Industries of the Future, deploying several Industries of the Future laboratories, creating a base for training future technology talents, and promoting the research and development, transformation, and application of frontier-leading technologies and disruptive technologies. In addition, Shenyang, Shenzhen, Tianjin, Shanghai, Jiangxi Province, Jiangsu Province, and other provinces and cities will also use “Industries of the Future” as the “14^th Five-Year Plan” period for the relevant planning ahead of the deployment of brain-like intelligence, quantum information, gene technology, future networks, other frontier technology and industrial change areas, the organization and implementation of Industries of the Future incubation and acceleration plan, and planning and deploying of several Industries of the Future.

It can be seen that governments around the world are actively introducing industrial policies in response to the various crises that may arise in the future, and we can see the unprecedented degree of government leadership in the development of “Industries of the Future,” the strong support for human resources and research funding, and the competitive strategy of significant countries to ensure the leadership of each country in technological innovation.

2.3. Entrepreneurship in Industries of the Future

As countries around the world are deploying their Industries of the Future, traditional enterprises are not only facing the pressure brought by the constant renewal of cutting-edge technologies but also the impact brought by new entrants, and some studies show that new entrants have more opportunities to pursue sustainable development than existing enterprises in entrepreneurial activities [29]. Especially in the entrepreneurship in Industries of the Future, new entrants can adapt to the needs of industrial development more quickly due to the accelerated iteration of technology. Here, the term new entrants refers to start-ups or SMEs in transition, which are often able to identify and respond to market needs, think outside the box, and become providers of emerging intelligent technologies, providing a constant source of power for sustainable innovation activities [30]. However, at the same time, new entrants may also lose competitiveness in the face of large traditional enterprises due to a lack of entrepreneurial experience, resources, and policy support [31].

How can start-ups or SMEs acquire sustainable competitiveness in entrepreneurship in the Industries of the Future process? Innovation and entrepreneurship are the key factors of business competitiveness [32]. Innovation includes technologies, organizational structures, and business models [33,34,35]; entrepreneurship and business leadership are inseparable [36]; entrepreneurship is to a certain extent, the same as entrepreneurship, especially when it comes to the future industry, which is a forward-looking industry with high risks and uncertain returns; entrepreneurship can have a positive impact on the sustainability of the company [37].

There are also many risks in the process of entrepreneurship in Industries of the Future. For example, Li et al. argue that emerging technologies such as fifth-generation communications (5G) and the Internet of Things (IoT) are operating in tandem and will drive global business transformation, but the IoT currently faces many challenges such as network performance, security, and standardization [38]. Silvia H et al. argue that in the evolution of production and industrial processes in the era of Industry 4.0, technologies related to the Internet of Things, big data analytics, and physical information systems still have unknown potential impacts on sustainability and the environment [39].

From the above analysis, it can be concluded that: the main body of entrepreneurship in Industries of the Future should be start-up enterprises, which can quickly respond to future industrial development needs, and the future development of enterprises is inseparable from the entrepreneurial spirit of their leaders, while facing huge risks and challenges.

2.4. Entrepreneurship in Industries of the Future: A Diamond Conceptual Model

In the process of industrial economic development, the importance of technological innovation is self-evident. According to the research on innovation driving mechanism in modern innovation theory, the representative theories are “technology push theory” and “market pull theory,” both of which have formed. Both of them have distinct theoretical views. The technology push theory asserts that technological innovation is driven by technological development and that breakthroughs in science and technology are the driving force of technological innovation and the fundamental cause of technological innovation [40], while the market pull theory asserts that technological innovation originates from market demand; market demand information is the starting point of technological innovation activities [41,42]. However, technology and market are the two ends of the technological innovation process, and neither the technology-push theory nor the demand-pull theory is a single biased theory about the dynamics of innovation; thus, a compromise between the two theories naturally emerges [43]. The “Eclectic theory” analyzes both ends of the technological innovation process, rather than focusing on one side only, and is represented by the scholar N. Rosenberg, who argues that science and technology, together with market demand, play a central role in innovation in an interactive way and that ignoring either side will lead to wrong conclusions and policies [44]. In conclusion, the “Eclectic theory” is more in line with the development trend and characteristics of the future industry.

Technology push and market pull are indispensable to the development of Industries of the Future, and the synergistic effect generated by the two can accelerate the landing of Industries of the Future [45]. For start-ups, technology-driven startups often change to market-pull direction due to new partners, new market information, or changes in management priorities [46], and it is only when the market need pulls that the industry can enter “market need expansion—sales revenue increase—R&D investment growth, production scale expansion—technology improvement, cost reduction-more market need” virtuous cycle [15]; the development of the industry only then can the industry be healthy and sustainable. Therefore, in the process of entrepreneurship in Industries of the Future, the progress of innovation in cutting-edge technology determines the ease of entrepreneurship, and the extent to which market need can be met determines whether entrepreneurship can be sustainable. Technology and the market form the binary drive of entrepreneurship in Industries of the Future, driving the process of entrepreneurship in Industries of the Future.

However, with the accelerated process of modern technology and the industrial revolution and with the increasingly complex international environment and changing market need, the dual drive of technology and market cannot well meet the requirements of entrepreneurship in Industries of the Future; in this case, more innovative elements of integration and crossover are needed better to promote the development needs of entrepreneurship in Industries of the Future. The diamond theory was proposed by the American scholar Michael Porter in his 1990 publication “National Competitive Advantage,” which provides a more comprehensive model of industrial competitiveness analysis and can be used to analyze how a country can form an overall advantage and thus hold a solid competitive position in the international arena. The diamond model is currently considered the most influential theory of international competitiveness of industries [47] and consists of four key elements and two auxiliary elements, of which the main factors include the production factor, need factor, related industry factor, and enterprise strategy factor, and the two additional factors are opportunity and government.

As an essential engine to promote industrial economic growth and social development, the theory of entrepreneurial motivation behind entrepreneurial activities has attracted much attention from scholars at home and abroad, and some theoretical results have been achieved. Among the classical theories of entrepreneurial motivation, the “pull theory” and “push theory” proposed by Gilad and Levine are the most well-known by scholars [48]. The “push theory” states that individuals are “pushed” to start a business by external damaging factors such as dissatisfaction with their current job, conflict in the co-location, low wages, unemployment, inflexible working hours, etc. These negative factors activate the talents of potential entrepreneurs. The “pull theory” suggests that individuals are attracted to entrepreneurial activity by the search for independence, self-fulfillment, wealth, and other plausible outcomes. These two theories complement each other in explaining the negative and positive aspects of entrepreneurial activity, while the “pull theory” seems to scholars to be more supportive of the primary motivation behind entrepreneurial activity [49,50].

This paper combines the relevant literature and representative theories to condense critical factors, which are finalized through two rounds of in-depth interviews; the first round is with eight entrepreneurs in the Industries of the Future, who propose possible factors; the other round is to synthesize the factors proposed by the entrepreneurs with the literature elements and then to interview eight experts in the field of entrepreneurship management and innovation management. Also inspired by the form of Porter’s diamond model, the diamond model of the driving mechanism of entrepreneurship in Industries of the Future is constructed, as shown in Figure 1.

The specific meaning of the model can be explained as follows: the four key elements can be summarized as positive factors, namely need factor, creation, technology, and aspiration, while the two additional factors can be summarized as constraints and support factors, which can be used as a reference for entrepreneurs to make decisions when starting a business and as a reference for government policies to promote entrepreneurship in Industries of the Future. Due to the disruptive, infantile, and ultra-risky nature of the future industry itself, the constraints and support factors are not simply additional. They are essential factors that can influence other positive factors. We can identify the risk factors in entrepreneurship in Industries of the Future, control and eliminate them through supporting factors, and provide good conditions and environment for the generation and development of positive factors.

Based on the above model, this paper innovatively proposes a 3 × 3 scale of critical influencing factors of entrepreneurship in Industries of the Future, which is mainly divided into three aspects, namely positive, constrained, and supported. In contrast, each influencing factor is divided into three profiles; for example, the influencing factor of need contains personal, organizational, and governmental attributes, considering three levels of profiles. Meanwhile, in terms of constraints, the risks and barriers are divided into separate profiles, and the detailed indicator factor decomposition is shown in

Table 1. Critical factors for entrepreneurship in Industries of the Future.

Category	Factors	Code
Positive	Need (personal, organizational, governmental)	S1
	Creation (personal, organizational, external)	S2
	Aspiration (personal interest, status ideals, wealth)	S3
	Technology (basic research results, applied research results, patented results)	S4
Constrained	Risk constraints (technology, operations, market)	S5
	Barrier constraints (licensing, legal, incumbency)	S6
Supported	Government support (policy, funding, risk compensation)	S7
	Public support (experts, users, public opinion)	S8

.

The positive factors include need, creation, aspiration, and technology. Among them, need includes individual, organizational, and government-oriented needs [51,52,53]: how start-ups can meet the individual needs of customers in the development of Industries of the Future; how organizations can use them to drive competitive business models, markets, and sustainable growth; and how government can meet the scientific and technological needs of great power competition when deploying out Industries of the Future. This set of needs is driving the entrepreneurship in Industries of the Future. Creation includes personal, organizational, and external creation [54]. As the main force of entrepreneurship in Industries of the Future, the entrepreneurial spirit of the individuals who are the leaders of the organization can bring the motivation for continuous innovation [32], while creation from the organization as well as from external sources can help the company to better sustain entrepreneurship. Aspiration mainly refers to the entrepreneur’s personal interests, status ideals, and the pursuit of wealth [55,56]. For technology entrepreneurs, the study argues that closer and broader dreams and efforts to create change in the world may bring us a more comprehensive and holistic understanding of the process of discovery, change, value creation, and ultimately wealth creation. The technology factor mainly refers to disruptive technology [57]; an industry or multiple industries will experience fundamental changes due to the emergence of disruptive technology; especially in Industries of the Future, disruptive technologies can accelerate the growth of industries, lead to more industry changes and create more technological achievements, mainly including basic research results, application research results, patent results, etc.

Constraining factors include risk factors and obstacle factors. The risk factors are mainly from technology, product operation, and market risks [39,58]. For Industries of the Future, the ultra-risky nature of entrepreneurship also determines the difficulty of starting a business because it is a journey into the unknown. Obstacles include licensing factors, laws, incumbent companies [29,59], the degree of social licensing, adverse legal provisions and the original enterprises which all play a role in hindering the new enterprises.

Support factors include government support factors and public support factors. Among them, government support mainly refers to the government’s promulgation of policies related to Industries of the Future, allocation of project funds and risk compensation [7,60]; a distinctive feature of the Industry of the Future is government dominance as a means of ensuring leadership in the relevant industry sectors [61]. Therefore, the government needs to create favorable conditions for the enterprises when formulating relevant policies, such as capital investment and risk compensation in case of business failure. The public support factor mainly refers to the support from experts, users, and public opinion [62,63]. For technology-based startups, the support from users of their products can facilitate the operation of their business models and lead to continuous innovation.

3. Research Framework and Methodology

3.1. Research Framework

There are various factors affecting entrepreneurship in Industries of the Future, and in this complex system, the interactions between the factors are usually non-linear and provide feedback to each other, forming multiple cycles of interaction and extremely complex impact mechanisms, thus making the system uncertain and overall opaque [64].

Decision Experiment Evaluation Laboratory (DEMATEL) is a factor analysis tool for decision making in complex systems, which can be used to explore causal and logical correlations among factors in complex systems. Interpretive Structural Modeling (ISM) is a similar tool that expresses a structured model of factors in terms of intuitive multilevel structural relationships. ISM and DEMATEL are well suited for in-depth analysis of complex problems in complex systems issues and have been used separately in past studies [65]. However, since both methods have their own focus when used individually, they do not provide a comprehensive and accurate response to the mechanisms of influence on the operation of complex systems. Therefore, in order to determine the importance and influence mechanism of critical influencing factors of entrepreneurship in Industries of the Future, this paper adopts the DEMATEL-ISM method to quantitatively calculate the centrality and causality of key factors and establish the relevant interrelationships and hierarchical structure models.

The flow chart of Industries of the Future influence factors based on the DEMATEL-ISM model is shown in Figure 2.

3.2. Data Receipt and Processing

Based on the discussion in Section 2.4, this study created a questionnaire of entrepreneurship in Industries of the Future influencing factors based on the scale of the critical factors derived from two rounds of in-depth discussions with entrepreneurs and experts in related fields, and the questionnaire types were mainly divided into pre-questionnaires and formal questionnaires. The pre-questionnaires were mainly distributed to government staff, universities/research institutions, employees of related enterprises, business people, etc. The purpose was to ensure that each influencing factor was relevant to the other and could have a particular influence on future industrial entrepreneurship and to ensure the formal questionnaire’s validity and reliability.

In this study, a pre-questionnaire was designed and distributed online to government staff, university/research institutes, relevant business personnel, and others through literature collection and relevant expert opinions to ensure that the above key factors (S1, S2, ..., S8) play an influence in entrepreneurship in Industries of the Future, and the meaning of each influencing factor as well as the theme of this study was elaborated in the pre-questionnaire. A total of 313 pre-questionnaires were distributed, and 6 questionnaires that were too long and had mutilated answers were excluded, resulting in a total of 307 questionnaires with a 98% return rate.

In this study, SPSS software was used to analyze the reliability and validity of the collected pre-questionnaires. Scale reliability refers to the stability of the measurement results, and this study used Cronbach’s alpha coefficient method for reliability analysis, and the final questionnaire had a Cronbach’s alpha coefficient value of 0.707, indicating that the questionnaire had acceptable reliability. KMO and Bartlett’s sphericity test were used to verify the suitability of factor analysis.

Table 2. Pre-questionnaire validity test.

Category		Value
KMO value		0.647
Bartlett’s sphericity test	Approximate chi-square	626.349
	df	28
	p	0.000 ***

Note: *** represents 1% significance levels.

shows KMO = 0.647 > 0.5, a chi-square statistic value of 1490.09, and Bartlett’s sphericity p = 0.000, rejecting the original hypothesis and indicating a correlation between the variables.

The results of the pre-questionnaire, after passing the reliability test, indicated that the factors were correlated and, therefore, could be used to create a formal expert questionnaire which collected data on the interrelationship and degree of influence between the eight factors and used a five-point Likert scale, asking the experts to score the relationship between the influence of the two factors: strongly disagree (0); disagree (1); average (2); agree (3); strongly agree (4). The formal questionnaires were distributed to 12 experts in the relevant fields and collected online, and 12 expert questionnaires were finally recovered for the DEMATEL-ISM analysis.

3.2.1. DEMATEL-ISM Analysis Process

(1)

Build the direct influence matrix $\mathrm{A}$. Summarize the average of all expert questionnaire scores for each pair of interacting elements to build matrix $\mathrm{A}$. The form of matrix $\mathrm{A}$ is as follows. Where $n$ represents the number of impact factors, $a_{ij}$ denotes the degree of influence of influence factor $i$ on $j$, If $i$ = $j$, the $a_{ij}$ = 0.

$$\mathrm{A}=\left[\begin{array}{ccc}{a}_{11}& \cdots & a_{1n}\\ ⋮& \ddots & ⋮\\ a_{n1}& \cdots & a_{nn}\end{array}\right]$$

(1)

(2)

Establish the canonical influence matrix $\mathrm{M}$. Normalize the direct influence relationship matrix to directly obtain the canonical influence matrix $\mathrm{M}$. The calculation method is as follows.

$$\mathrm{M}=\frac{1}{\underset{1\le x\le n}{\max }{{\displaystyle \sum }}_{j=1}^n{x}_{ij}}\mathrm{A}$$

(2)

(3)

Establish the integrated influence matrix $\mathrm{T}$. Calculate the integrated impact matrix $\mathrm{T}$ among the system impact factors with the following formula where $\mathrm{I}$ is the unit matrix.

$$\mathrm{T}=\mathrm{M}{\left(\mathrm{I}-\mathrm{M}\right)}^{-1}$$

(3)

(4)

Calculate the degree of influence ($D_i$), the degree of being influenced ($C_i$), the degree of centrality $M_i$, and the degree of cause $R_i$ for each factor in the integrated influence matrix. The calculation formula is as follows. The centrality is the sum of the degree of influence and the degree of being influenced by the system factors, denoted as $M_i$. The difference between the two is called the reason degree, which is written as $R_i$.

$$D_i={\displaystyle \sum }_{j=1}^n{t}_{ij}\left(i=1,2,3\cdots ,n\right)$$

(4)

$$C_i={\displaystyle \sum }_{j=1}^n{t}_{ji}\left(i=1,2,3\cdots ,n\right)$$

(5)

$$M_i=D_i+C_i$$

(6)

$$R_i=D_i-C_i$$

(7)

Draw a Centrality–Causality degree distribution diagram. Centrality–Causality relationships are represented by a two-dimensional graph composed of coordinates in ($M_i$,$R_i$), with the horizontal axis $M_i$ and the vertical axis $R_i$.The cause–effect diagram can simplify the complex cause–effect relationship into an easy-to-understand structure which provides direction for a deeper understanding of the problem. With the assistance of this diagram, decision-makers can make rational decisions based on causal factors or influential factors among the factors.

(5)

Calculate the overall influence matrix $\mathrm{H}$. The overall impact matrix is formed by combining the integrated impact matrix $\mathrm{T}$ and the unit matrix $\mathrm{I}$. The formula is as follows.

$$\mathrm{H}=\mathrm{T}+\mathrm{I}$$

(8)

(6)

Determine the reachable matrix $\mathrm{K}$. Transforming the overall influence matrix H into a reachable matrix $\mathrm{K}$ requires the introduction of a threshold $\lambda$. The purpose of the threshold $\lambda$ setting is to eliminate influence relations with a small degree of influence, simplify the system structure, and facilitate the division of the hierarchical structure. The value of $\lambda$ can be determined based on expert opinion or knowledge experience. The specific formula is as follows.

$$K_{ij}=\left\{\begin{array}{c}1,h_{ij}\ge \lambda \left(i,j=1,2,3\cdots ,n\right)\\ 0,h_{ij}<\lambda \left(i,j=1,2,3\cdots ,n\right)\end{array}\right.$$

(9)

(7)

Hierarchy division. The reachability and antecedent sets of the factors are first determined. The reachable set of a factor, denoted as $\mathrm{R}\left(S_i\right)$,consists of the corresponding element 1 in the $i$-th row of the reachability matrix $\mathrm{K}$. Similarly, the prior set of factors, denoted as $\mathrm{P}\left(S_i\right)$, consists of the corresponding element 1 in the $i$-th column of the reachability matrix $\mathrm{K}$. The intersection of these two sets is calculated and denoted as $\mathrm{C}\left(S_i\right)=\mathrm{R}\left(S_i\right)\cap P\left(S_i\right)$. These factors are then removed from the set and the process is repeated until all factor layers are completed.

4. DEMATEL-ISM Study Results

Based on the returned expert questionnaires and Equation (1), a direct influence matrix of factors influencing entrepreneurship in Industries of the Future can be derived, as shown in

Table 3. Direct influence matrix.

Factor	S1	S2	S3	S4	S5	S6	S7	S8
S1	0.000	3.417	3.500	3.083	0.000	0.000	3.167	3.083
S2	2.833	0.000	2.667	3.250	3.250	3.000	2.500	2.250
S3	0.000	2.917	0.000	0.000	3.083	3.167	2.083	2.000
S4	2.833	3.083	3.417	0.000	2.833	3.083	3.167	2.583
S5	0.000	0.000	3.250	0.000	0.000	0.000	3.000	3.250
S6	2.667	0.000	0.000	0.000	3.000	0.000	2.667	2.250
S7	3.250	2.667	3.167	0.000	3.167	0.000	0.000	3.000
S8	3.333	2.833	2.917	0.000	0.000	0.000	3.167	0.000

.

Processing Table 3 according to Equations (2)–(7), The comprehensive influence matrix of each factor and the influencing degree, influenced degree, centrality, and causality can be obtained, as shown in

Table 4. The comprehensive influence matrix.

Factor	S1	S2	S3	S4	S5	S6	S7	S8
S1	0.275	0.448	0.503	0.328	0.286	0.188	0.479	0.456
S2	0.409	0.308	0.493	0.333	0.438	0.310	0.488	0.459
S3	0.247	0.366	0.307	0.280	0.388	0.290	0.403	0.383
S4	0.427	0.457	0.543	0.211	0.441	0.325	0.534	0.492
S5	0.143	0.164	0.327	0.093	0.145	0.086	0.309	0.312
S6	0.265	0.165	0.209	0.094	0.269	0.069	0.312	0.289
S7	0.357	0.366	0.443	0.172	0.362	0.144	0.299	0.412
S8	0.346	0.353	0.395	0.162	0.213	0.134	0.394	0.247

and

Table 5. Influencing degree, influenced degree, centrality, and causality of factors.

Factor	Influencing Degree D	Ranking	Influenced Degree C	Ranking	Centrality M	Ranking	Causality R	Ranking
S1	2.963	3	2.469	6	5.432	4	0.494	3
S2	3.237	2	2.625	4	5.862	2	0.612	2
S3	2.664	4	3.220	1	5.884	1	−0.556	5
S4	3.428	1	1.673	7	5.101	6	1.755	1
S5	1.577	8	2.541	5	4.118	7	−0.964	8
S6	1.671	7	1.547	8	3.218	8	0.124	4
S7	2.556	5	3.217	2	5.773	3	−0.661	6
S8	2.246	6	3.052	3	5.298	5	−0.806	7

.

According to the calculation results in Table 5, the centrality degree M is the horizontal coordinate, representing the importance of the factors. The larger the value, the more influential the factor is in the system. With the degree of cause as the vertical coordinate, it can divide the factors into result factors (less than 0) and cause factors (greater than 0) and draw a Centrality–Causality degree distribution diagram of entrepreneurship in Industries of the Future influence factors. The Centrality–Causality degree distribution diagram can provide a valuable perspective for determining the importance and interrelationship of factors [66], as shown in Figure 3.

According to the multiple values and combined with expert opinions, when taking the threshold value $\mathsf{\lambda }$ = 0.3, the calculation results of Table 4 are calculated according to Equations (8) and (9), and the reachable matrix of entrepreneurship in Industries of the Future influence factors can be calculated, as shown in

Table 6. Reachable matrix.

Factor	S1	S2	S3	S4	S5	S6	S7	S8
S1	1	1	1	1	0	0	1	1
S2	1	1	1	1	1	1	1	1
S3	0	1	1	0	1	0	1	1
S4	1	1	1	1	1	1	1	1
S5	0	0	1	0	1	0	1	1
S6	0	0	0	0	0	1	1	0
S7	1	1	1	0	1	0	1	1
S8	1	1	1	0	0	0	1	1

.

The reachable matrix is hierarchically divided according to the method in step (8) in Section 3.2.1, and the results are shown in

Table 7. Hierarchy of factors influencing entrepreneurship in Industries of the Future.

Factor	Reachable Set R (Si)	Antecedent Set A (Si)	R∩A = R	Level
S1	1, 2, 3, 4, 7, 8	1, 2, 4, 7, 8		Ⅰ
S2	1, 2, 3, 4, 5, 6, 7, 8	1, 2, 3, 4, 7, 8
S3	2, 3, 5, 7, 8	1, 2, 3, 4, 5, 7, 8	Y
S4	1, 2, 3, 4, 5, 6, 7, 8	1, 2, 4
S5	3, 5, 7, 8	2, 3, 4, 5, 7		Ⅰ
S6	6, 7	2, 4, 6
S7	1, 2, 3, 5, 7, 8	1, 2, 3, 4, 5, 6, 7, 8	Y
S8	1, 2, 3, 7, 8	1, 2, 3, 4, 5, 7, 8	Y
S1	1, 2, 3	1, 2, 3	Y	Ⅱ
S2	1, 2, 3, 4, 5	1, 2, 3
S4	1, 2, 3, 4, 5	1, 2, 3
S5	4	2, 3, 4	Y
S6	5	2, 3, 5	Y
S2	1, 2	1, 2	Y	Ⅲ
S4	1, 2	1, 2	Y

. It is easy to see that there are three levels of division in the whole system: factors S3, S7, and S8 constitute the first level of factor level; S1, S5, and S6 constitute the second level of factor set; and S2 and S4 constitute the third level of factor set.

Based on the results i based on the results in Table 7, a multi-level structural model of the factors influencing entrepreneurship in Industries of the Future is built from the third level, as shown in Figure 4.

5. Discussion and Implication

5.1. Discussion

5.1.1. Importance and Causality of Each Factor

As can be seen from Table 5, in the ranking of the influence degree of each factor, science and technology (S4) is the most critical influence factor, followed by creation (S2), need (S1), aspiration (S3), government support (S7), public support (S8), barrier constraints (S6), and risk constraints (S5), and the influence degree is the main attribute that indicates that the factor determines the creation and development of other factors, and the formation of the influence factor plays a fundamental role. This indicates that among the factors influencing entrepreneurship in Industries of the Future, technology, creation, need, and aspiration are the most dominant factors that determine and drive the development of the behavior of entrepreneurship in Industries of the Future as a whole, and this just validates the diamond model of the entrepreneurship in Industries of the Future driving mechanism constructed in the previous article. In the ranking of the influence degree of each factor, it can be seen that the top four factors with the highest ranking are aspiration (S3), government support (S7), public support (S8), and Creation (S2). The influenced degree refers to the fact that the generation and development of a factor are more influenced by other factors, indicating that these factors are susceptible to the influence of other factors. Therefore, we can cultivate students’ aspirations and guide their motivation to engage in future industries through education. At the same time, the government can create a social atmosphere that encourages entrepreneurship and strengthens people’s recognition and appreciation of entrepreneurial activities.

Centrality indicates the total degree of influencing and being influenced by other factors, and the greater the centrality, the greater the role played by the factor in the influence factor system; cause degree indicates the difference between influencing and being influenced through this factor, and if the cause degree is greater than 0, it is called the cause factor; on the contrary, it is called the resulting factor [67]. In the ranking of centrality, in order, aspiration (S3), creation (S2), government support (S7), need (S1), public support (S8), technology (S4), risk constraints (S5), and barrier constraints (S6), compared with other factors, aspiration (S3), creation (S2), and government support (S7) are in the top three, indicating that in entrepreneurship in Industries of the Future, organizational leaders’ entrepreneurship plays a dominant role, while Creation and government support also plays an essential role.

According to the causality diagram (Figure 2), the cause elements are ranked in order of numerical magnitude as technology (S4), creation (S2), need (S1), and barrier constraints (S6), which indicates that they exert more influence on the other factors than they are influenced by the other factors and are the leading causes driving the other factors. With the technology factor ranking first and having the highest causality, the reason being that the Industries of the Future is dependent on disruptive technologies to drive industry development, so the technology factor can be considered a critical element that has a significant impact on other factors. The fourth-ranked barrier constraint (S6), which has low centrality, causality, and influence, indicates that it is disconnected from other factors in the system. The outcome factors in order of magnitude are aspiration (S3), government support (S7), public support (S8), and risk constraints (S5), which indicates that these factors are highly susceptible to the influence of other factors. The three factors of technology (S4), creation (S2), and need (S1) are in the lead in terms of ranking of the degree of influence, degree of being influenced, centrality, and causality, indicating that these three factors are strongly associated with other factors. Aspiration (S3), government support (S7), and public support (S8) are in the middle of the ranking in terms of influence degree, influenced degree, and centrality, so these three factors play a relatively important role in the whole system of factors influencing entrepreneurship in Industries of the Future.

5.1.2. Multi-Level Structural Model Analysis

Through the DEMATEL-ISM method, a multi-level structural model of the factors influencing entrepreneurship in Industries of the Future was identified (Figure 4), divided into three layers from top to bottom.

Creation (S2) and technology (S4) occupy the bottom layer (third layer). These two factors are the starting point of the multi-level model and the most fundamental influencing factors. Their influence on entrepreneurship in Industries of the Future is solid and continuous.

Need (S1), risk constraints (S5), and barrier constraints (S6) occupy the middle level (second level). These three factors belong to the middle of the whole multilevel model and play an indirect influence on entrepreneurship in Industries of the Future, with creation (S2) leading to the flow of need (S1), risk constraints (S5), and barrier constraints (S6), and technology (S4) leading to the flow of need (S1) and risk constraints (S5).

Aspiration (S3), government support (S7), and public support (S8) occupy the surface (first level). These three levels belong to the superficial layer of the whole multilevel model; these factors have a limited connection to the system, directly impact entrepreneurship in Industries of the Future, and are the most easily perceived factors in the analysis. The need (S1) leads to the flow of aspiration (S3), government support (S7), and public support (S8), and the risk constraint (S5) leads to the flow of government support (S7) and public support (S8).

In the analysis of the importance and causality of each factor, Creation (S2) and technology (S4) belong to the two factors with the highest causality, and these two factors are at the third level in the multi-level structure model; that is the starting position which can be considered as the root cause of other factors. At the same time, need (S1) is ranked at the top with centrality in the degree of influence of each factor, which indicates that it is an essential factor with a close connection with other factors, and through the analysis of multi-level structure model, need (S1) is in the critical node position in the system. It influences aspiration (S3), government support (S7), and public support (S8) and is influenced by creation (S2) and technology (S4) at the same time. In the multi-level structural model, it can be seen that the barrier factor (S6) is only influenced by the bottom (third level) creation (S2). It does not influence the surface factors due to its low level of centrality, causality, and influence and is in a disconnected state. However, it does not mean that this factor is not essential and can impact entrepreneurship in Industries of the Future through other factors. Finally, aspiration (S3), government support (S7), and public support (S8) are in the superficial layer of the whole model and belong to the factors that can have a direct influence on entrepreneurship in Industries of the Future.

Therefore, the DEMATEL-ISM method was used to classify entrepreneurship in Industries of the Future’s causality and hierarchical structure. The two methods have a certain degree of agreement in the results, which also indicates the reliability of the multilevel structure model. The joint use of the two methods analyzes the importance and causality of each factor and establishes the influence mechanism and hierarchical model among the factors.

In the existing research, entrepreneurial motivation and entrepreneurship are mainly used to analyze how startups form competitiveness in the process of development, while the research on Industries of the Future is limited to case studies and policy analysis [5], and the two are not organically combined to form a more complete theoretical chain [32]. This paper tries to summarize the key elements of entrepreneurship in Industries of the Future system, integrate entrepreneurial motivation and entrepreneurship into Industries of the Future development, combine the two through the diamond model to form the entrepreneurship in Industries of the Future driving mechanism, and after empirical analysis, fill in the research on entrepreneurship in Industries of the Future motivation.

In fact, the results of the DEMATEL-ISM method also support the diamond model of the driving mechanism of entrepreneurship in Industries of the Future, where four critical factors dominate the diamond model and are the main influencing factors of entrepreneurship in Industries of the Future. The obstacle and support factors can be used for entrepreneurs to make decisions when conducting entrepreneurship and as a reference for government policies to entrepreneurship in Industries of the Future.

5.2. Implication

Research shows that:

(1) Technology, creation, need, and aspiration are the crucial factors influencing entrepreneurship in Industries of the Future and also validate the theoretical feasibility of the diamond model of the driving mechanism of entrepreneurship in Industries of the Future. Enterprises as the main subject of entrepreneurship should give priority to these influencing factors to improve the success rate of entrepreneurship; as the publisher and supervisor of policies, the government support can directly affect the entrepreneurship in Industries of the Future, should give more policy and financial support to the future industrial entrepreneurial enterprises, and provide a certain degree of risk compensation so as to promote the healthy and sustainable development of the Industries of the Future.

(2) Since the diamond model involves personal, organizational, and governmental needs, government procurement support can be enhanced for Industries of the Future start-ups to initiate the initial needs of future industrial start-ups.

(3) Since aspiration drive is vital in entrepreneurship in Industries of the Future, fostering a sense of vision, achievement, and ambition for the future in the education system is essential. It is also vital to increase public recognition and appreciation of Industries of the Future entrepreneurs.

6. Conclusions

In this study, we established eight major influencing factors affecting entrepreneurship in Industries of the Future based on the literature review and the opinions of experts and scholars and explored each key factor and influence mechanism using the DEMATEL-ISM method to improve the reliability and accuracy of the multi-level structural model, and the analysis results revealed the complex relationship between various factors promoting entrepreneurship in Industries of the Future.

The theoretical implications of this paper are three main points. (1) Summarizing and expanding the critical factors system of entrepreneurship in Industries of the Future, categorizing the critical factors into three levels: positive; constrained; and supported, each of which is divided into three profiles to form a 3 × 3 structure, which enriches the system of influencing factors and gives it a sense of hierarchy. Among them, separating risk factors and obstacles and considering individual, organizational, and government needs are also new. (2) The proposed diamond model of the driving mechanism of entrepreneurship in Industries of the Future is inspired by the Poter diamond model, but it is a new model; the Poter diamond model is used to analyze the competitive market situation, while the diamond model in this paper is used to analyze the driving mechanism of entrepreneurship in Industries of the Future. Therefore, the critical factor system of entrepreneurship in Industries of the Future and the diamond model proposed in this paper is theoretically innovative and significant. (3) Enriching the research on entrepreneurial motivation in Industries of the Future. By integrating entrepreneurial motivation and entrepreneurship into the development of Industries of the Future, the critical influencing factors of entrepreneurship in Industries of the Future are empirically explored.

The practice implications of this paper are three main points. (1) Many countries have implemented Industries of the Future development plans (programs). The most vital work to be promoted is an appropriate industrial deployment and spatial deployment of Industries of the Future. Regarding industrial deployment, cooperation among government, universities, and enterprises can be promoted based on the triple helix model to form a complete industrial chain and innovation chain and to realize the integration of the value chain, demand chain, and policy chain. In terms of spatial deployment, several Industries of the Future venture parks can be established to provide services such as incubation, insurance, and scene display. (2) The R&D, production, and operation activities of Industries of the Future are inherently entrepreneurial. Therefore, on the one hand, Industries of the Future practitioners and investors should make decisions and manage in accordance with entrepreneurial management, the most important of which is to carry out risk identification and risk evaluation and to weigh entrepreneurial risks and entrepreneurial opportunities; for the government, it should give preferential support to Industries of the Future enterprises for business incubation, and at the same time, it should provide risk protection to Industries of the Future entrepreneurial enterprises, for example, providing risk guarantee, risk compensation, and reinsurance services. (3) The diamond model established here and the conclusions of the empirical analysis conducted have practical reference significance for developing future industrial entrepreneurship enterprises and for the government to formulate entrepreneurship in Industries of the Future promotion policies.

This study also has some limitations and shortcomings. Firstly, the selection of crucial influencing factors was not collected as comprehensively as possible in the existing literature, and some influencing factors may not be considered. Secondly, the DEMATEL-ISM method depends mainly on experts’ subjective judgment and empirical knowledge, and the value of the threshold $\mathsf{\lambda }$ has been discussed with experts after several attempts, which may have some influence and bias on the final results.

Future research is proposed to be improved in two aspects. First, it is proposed to deeply dissect well known Industries of the Future startups such as SPACEX and Neur-Link to identify the influence mechanism of five critical factors in the diamond model on the success of Industries of the Future startups; second, it is proposed to select three Industries of the Future pioneer zones in China as the case study of Industries of the Future startup clusters to study the influence of policies and industrial ecology on Industries of the Future startups; third, based on the data parameters of the two types of cases, the Multi-agent method is applied to model and simulate in order to deduce the mechanism of synergistic evolution among entrepreneurship in Industries of the Future enterprises, government, users, and other subjects and to conduct policy experiments and make policy recommendations.