Research on Responsible Innovation Performance Evaluation in the Blue Economic Zone of Marine Industry

Abstract

Responsible innovation is attracting theoretical and practical research attention worldwide due to global climatic changes, severe resource shortages and intensifying environmental deterioration. However, there are still no studies concerning the performance evaluation of responsible innovation in the marine industry. Based on the practices of blue economic zones in China, a responsible innovation performance evaluation system for the marine industry was developed. Based on the data from 2013 to 2018, the responsible innovation performance of the blue economic zone of the marine industry in Shandong Province was evaluated by principal component analysis. The results demonstrated that (1) There was a rank of regions in terms of the comprehensive responsible innovation performance from high to low: Qingdao > Yantai > Weifang > Weihai > Dongying > Binzhou > Rizhao. (2) Considering annual variations, the comprehensive performance of responsible innovation of different regions exhibited slight fluctuations; however, Weihai had demonstrated significant improvement since 2016. (3) The performance trends across various regions indicated that regions exhibiting high performance consistently expanded their advantage over the six-year period. There was a “Matthew effect” in regional development, particularly evident in the disparities between Qingdao and other regions. (4) In regions that rank at the lower end, such as Rizhao, Binzhou, and Dongying, the development of responsible innovation progressed slowly. Finally, some management suggestions to improve innovation performance in the blue economic zone of the marine industry were proposed.

1. Introduction

In the 21st century, human beings are still facing challenges such as resource scarcity, environmental degradation, and a widening gap between the rich and the poor, making humans reflect on whether innovation is conducive to the development of human society and whether innovation is responsible for various issues [1,2,3]. Responsible innovation is an emerging innovation management concept proposed after the concept of sustainable development was defined [4]. The main goal is to closely integrate corporate technological innovation practice with social responsibility and to evaluate and influence technological innovation from an ethical perspective to ensure the sustainability and social acceptability of the results [5,6,7]. Since then, responsible innovation has continued to be enriched and expanded, both in theory and practice, going beyond the field of science and technology to the integrated development of science and technology, economy, society, and government decision making [8].

The “13th Five-Year National Science and Technology Innovation Plan” issued by the State Council proposes adhering to the development concepts of coordination, greenness, openness, and sharing, advocating responsible research and innovation, strengthening the construction and education of scientific research ethics, improving scientific and technological workers’ ethical awareness and guiding enterprises to pay attention to and assume social responsibilities such as protecting the ecology and ensuring safety in technological innovation activities [9]. Innovation-driven development is not only limited to the technological advancement and economic growth of innovation but also requires the country to adhere to the goal of improving the quality and efficiency of economic development, pay more attention to meeting the needs of the people, and promote the realization of quality, efficiency and sustainable development to realize the value of responsible innovation under the medium- and long-term development concepts of innovation, coordination, greenness, openness and sharing [10,11].

With the wide application of high technology in the marine field, marine ecological environment pollution, ecological degradation, resource depletion and other marine problems are becoming increasingly prominent, not only destroying the ecological environment of the ocean itself but also posing serious challenges to the sustainable development of human society and the living space of human beings themselves. However, at present, no regional industry-level responsible innovation performance evaluation system exists, and there is a lack of relevant research on combining evaluation methods to establish an innovation performance evaluation mechanism [12,13]. In practice, the problem of social fairness becomes increasingly prominent, which has adverse impacts on the public and attracts high concerns from the government. The government not only has realized the importance of technological innovation but also is concerned about employment and social guarantees, information sharing, etc.

The Shandong Peninsula Blue Economic Zone has 68 industrial parks at or above the provincial level. It has planned three new marine economic zones, including the Qingdao West Coast, three marine economic international cooperation parks, including the Sino-German Ecological Park, and nine centralized and intensive sea areas, to promote the agglomeration and development of the marine industry with solid carrier support. This study focuses on the blue economic zone of the marine industry, selecting seven regions within the Shandong Blue Economic Zone as research subjects: Qingdao, Dongying, Yantai, Weifang, Weihai, Rizhao, and Binzhou. Sustained innovation activities can be facilitated by establishing a scientific evaluation system for the responsible innovation performance of industrial parks and mastering the level of responsible innovation performance of industrial parks [14,15]. The main contributions of this research are as follows. First, general research on innovation performance is aimed at measuring the effects of innovation activities at the enterprise, regional and national levels. This research conducts a responsible innovation performance evaluation of regional industrial development, enriching the theoretical basis for innovation performance evaluation. Second, most of the research on innovation performance evaluates innovation activities based on indicators of one aspect of input or output. This research establishes a multidimensional and multilevel responsible innovation performance measure based on the three dimensions of innovation input, innovation output and innovation environment. The evaluation system provides a research framework for the innovative development of the marine industry. Third, this study pioneers the idea of enhancing the responsible innovation system of the marine industry, making the research results and conclusions more feasible.

The framework of this research is as follows: first, the theoretical connotation of responsible innovation is reviewed; next, a responsible innovation performance evaluation system is established; then, principal component analysis is used to evaluate the responsible innovation performance of the Shandong Peninsula Blue Economic Zone; finally, conclusions and recommendations are presented.

2. The Connotation and System of Responsible Innovation Theory

2.1. The Connotation of Responsible Innovation Theory

The concept of responsible innovation comes from the community of philosophers, aiming to reflect social concerns caused by studies on policy-level responses and innovation [16]. It has attracted wide attention from academic circles since it was proposed by Hellstrom [17]. The connotations of the concept are expanding and deepening continuously. At present, the widely used definition is that responsible innovation is a transparent and interactive process in which social actors and innovators support each other and give full consideration to the acceptability, sustainability and social expectations of the innovation process and marketable products (ethically), thus embedding technological progress into our social life appropriately.

Scholars have reached a basic consensus on the connotation of “responsible innovation”:

(1)

The theory of “responsible innovation” is centered on human behaviors and activities with innovative characteristics. By embedding “responsibility” demands into the process and various aspects of innovation, its extension involves theoretical innovation, institutional innovation, cultural innovation, technological innovation, etc. [18,19,20].

(2)

Technological innovation is an indispensable path to achieve sustainable development, but technological innovation may also cause harmful consequences. Therefore, the combination of responsibility and innovation is an important strategic path to achieve sustainable development for a “better tomorrow” [21].

(3)

The high risks implied by technological innovation and the vicious consequences of technological abuse and misuse have caused people’s distrust of technological innovation and even the government, enterprises, scientific research institutes and other innovation entities and governance entities [22,23].

(4)

Science and technology have an unprecedented strategic position as an important way for the country, society, enterprises and institutions to win core competitiveness, and their role and influence are also comprehensive and integral [24,25].

Therefore, an understanding of the comprehensive impact of scientific and technological innovation on the economy, society, environment, etc., is helpful for ensuring harmless innovation and pursuing the humanization of innovation so that innovation results can be effectively combined with national needs, people’s requirements, and market demands.

2.2. Theoretical System of Responsible Innovation

Grunwald notes that responsible innovation is based on the tradition of technical evaluation, including evaluation procedures, participation of different doers and technical foresight, adding ethical reflection on responsibility to various methods and processes of technical evaluation. The process includes the theoretical results of science, technology, innovation and social research [17,26,27].

Regarding the theory of responsible innovation, the classic model is the four-dimensional model established by Stigoe, which includes inclusiveness, reflectiveness, responsiveness, and anticipation [28,29,30].

(1) Inclusiveness means facilitating the public and different stakeholders to conduct collective discussions on innovative visions, goals, problems and dilemmas through dialog, participation and debate, listening to the voices of different stakeholders and facilitating innovation to be better embedded in society. Inclusiveness aims to open up the participation of multilevel stakeholder entities in innovation activities. Innovative entities engage in discussions on terms of reference, roles, division of labor, and interdisciplinary collaboration, listening to the demands of different entities for specific innovations, and realizing the openness of technological innovation. (2) Reflectiveness means that innovative entities need to examine themselves as a part of the larger society and understand the impact of their own behavior on social development in time and region in addition to prediction and innovation activities, reflecting on the impact of innovation, including known and unknown, related uncertainties, risks, areas of ignorance, assumptions, problems, and dilemmas, and proposing effective coping strategies through introspection. (3) Responsiveness means using the process of collective reflection to determine the direction, trajectory and pace of innovation through effective participation and expected governance mechanisms. This is an iterative, inclusive, open and adaptive learning process with dynamic ability. Responsible innovation is the basis for the ability to place innovation activities under the conditions of dynamic matching between technological evolution and social activities, addressing innovation uncertainties through institutional modularization to establish a continuous adaptive learning process and to realize the institutional coupling of the innovation evolution process in response to societal value. (4) Anticipation describes and analyzes the social, economic, environmental and other impacts that may occur, whether intentional or unintentional, not only to clarify the expected commitment narrative but also to explore other ways of impact to promote scientists and innovators in enquiries into “what will happen” and “what else can be done”. Existing innovation practices have introduced a large number of forward-looking governance models, which have triggered the skills required for technological innovation under forward-looking mechanisms, as well as thinking about the adjustment of culture, processes, and organizational plans involved in existing policy governance, relying on technical evaluation and value sensitivity analysis, vision evaluation, scanning and other methods as support [31].

In addition, the three-dimensional space model proposed by Stahl includes a three-dimensional space model of actors-activities-norms [32], which regards responsible innovation as a future-oriented, uncertain, and complex collective behavior, having attracted widespread attention. Actors are stakeholders, such as scientists, universities, innovators, companies, and policy makers, who are critical to innovation activities. Activities are related technologies for detecting and controlling innovation activities, such as risk assessment, impact assessment, technology assessment, predictive activities, value-sensitive design, internal feedback, and ethical assessment. Normative foundations are used to evaluate whether a particular type of research or innovation is indeed desirable or acceptable. The three-dimensional space model covers most of the dimensions and aspects proposed by scholars in this field [33]. This study believes that the three-dimensional model and the four-dimensional model are essentially the same (Figure 1). The establishment of a responsible innovation performance evaluation system combines these two theoretical models.

3. Responsible Innovation Performance Evaluation System for the Blue Economic Zone

The responsible innovation performance evaluation system for the Blue Economic Zone is designed from three aspects: actors in responsible innovation, responsible innovation activities, and normative foundations of responsible innovation.

(1)

Actors in responsible innovation. Actors in responsible innovation represent the input factor in the responsible innovation process. If there are many input factors and relatively more innovative activities, the results will be more ideal. Input factors include human resources, material resources, financial resources, information resources, relationship resources, etc. Different combinations of resources yield considerable differences in the process and results of the relationship. However, material resources, information resources, and relationship resources are numerous and difficult to quantify and obtain. With reference to previous studies, combined with the needs of this research, resource inputs are investigated from human resources, capital, resources, and other dimensions. Human resource input uses the full-time equivalence of R&D personnel and full-time equivalence of R&D personnel in industrial enterprises above a designated size. Capital input chooses general public budget expenditures, R&D expenses and R&D expenses in industrial enterprises above a designated size. The resource input chooses the power consumption.

(2)

Responsible innovation activities. Innovation activities represent the process and results of activities occurring between innovation elements. The essence of management lies in the division of labor and integration. If the ability to integrate resources is strong, the result of innovation activities, namely, innovation performance, will be ideal. Considering that management factors and data are difficult to quantify and obtain, the indicators of responsible innovation activities in the Blue Economic Zone are examined from the output dimension. Referring to the research process of related scholars, combined with the needs of this research, patent, standardization, foreign trade and capital output are common index contents. Combined with the reasonability of data, patents choose the number of three types of patent applications in China and the number of three types of granted patents in China. Standardization chooses high-quality provinces and the implementation and standardization tasks of brand strategies. Foreign trade chooses the gross import value and gross output value. Capital output chooses revenue in the general public budgets and the main business income of industrial enterprises above a designated size.

(3)

Normative foundations of responsible innovation. Normative foundations of responsible innovation represent the environment in which innovation actors, innovation activities and innovation results occur. Social, economic, and environmental factors are all included in responsible innovation norms. However, under different environmental backgrounds, there are obvious differences in innovation actors, innovation activities, and innovation results. The environment for responsible innovation in the Blue Economic Zone involves economic conditions and information exchanges. With reference to the research process of relevant scholars, combined with the needs of this research, economic indexes include per capita GDP, household consumption level and total wages of employees in urban units. Social insurance indexes choose retirement insurance benefits, basic endowment insurance of residents and number of health institutions. Information exchange chooses enterprise informatization and e-commerce level as the measurement indexes of responsible innovation norms.

The construction of a responsible innovation performance evaluation system for the blue economic zone adheres to the previously mentioned four-dimensional and three-dimensional models. The actors in responsible innovation align with the principle of inclusiveness, while the activities align with the principles of responsiveness and reflexivity. Additionally, the normative foundations are consistent with the principle of anticipation. The marine industry responsible innovation performance evaluation system includes an element system of 3 first-level indicators and 21 third-level indicators, as shown in

Table 1. The responsible innovation performance index system.

Level-1 Indexes	Level-2 Indexes	No.	Level-3 Indicators	Units	Hemphill [34]	Buhmann & Fieseler [35]	Ko et al. [36]	Kwee et al. [37]	Sovacool et al. [38]	Zhang et al. [39]	Wang et al. [40]
Actors in responsible innovation	Human resource input	f1	Full-time equivalence of R&D personnel	Person/year	✓	✓	✓	✓	✓	✓	✓
		f2	Full-time equivalence of R&D personnel in industrial enterprises above the designated size	Person/year	✓	✓	✓	✓	✓	✓	✓
	Capital input	f3	General public budget expenditures	10,000 yuan	✓	✓	✓	✓	✓	✓	✓
		f4	R&D expenses	10,000 yuan	✓	✓	✓	✓	✓	✓	✓
		f5	R&D expenses in industrial enterprises above designated size	10,000 yuan	✓	✓			✓	✓	✓
	Resource input	f6	Power consumption	100 million kWh	✓				✓	✓	✓
Responsible innovation activities	Patents	f7	Number of three types of patent applications in China	pcs	✓	✓	✓	✓
		f8	Number of three types of granted patents in China	pcs	✓	✓	✓	✓
	Standardization	f9	High-quality provinces and the implementation of brand strategies	pcs			✓		✓
		f10	Standardization	pcs						✓	✓
	Foreign trade	f11	Gross imports	10,000 dollars						✓	✓
		f12	Gross outputs	10,000 dollars						✓	✓
	Capital output	f13	General public budgets	10,000 dollars		✓	✓	✓		✓	✓
		f14	Main business income of industrial enterprises above designated size	100 million yuan		✓	✓	✓		✓	✓
Normative foundations of responsible innovation	Economic conditions	f15	Per capita GDP	yuan	✓			✓	✓	✓	✓
		f16	Household consumption level	yuan	✓	✓		✓	✓	✓
		f17	Total wages of employees in urban units	100 million yuan	✓	✓		✓	✓	✓
	Social security	f18	Retirement insurance benefits	10,000 yuan	✓			✓	✓	✓	✓
		f19	basic endowment insurance of residents	Person	✓			✓	✓	✓	✓
		f20	number of health institutions	pcs	✓			✓	✓		✓
	Information exchange	f21	Enterprise informatization and E-commerce level	10,000 yuan	✓			✓	✓	✓	✓

.

4. Responsible Innovation Performance Evaluation of the Blue Economic Zone

4.1. Evaluation Method

Principal component analysis (PCA) is chosen as the performance evaluation method of responsible innovation in the blue economic zone. PCA is a multivariate statistical analysis method that screens some important variables through linear transformation of several variables. When studying multivariate problems based on statistical analysis, too many variables will increase the complexity of the topic. In many cases, there are some correlations among variables. When there is a correlation between two variables, it can be interpreted that these two variables overlap to reflect the information of this topic. PCA is used to delete repeated variables from all original variables and establish as few new variables as possible. These new variables are independent from each other and can maintain the original information of the topic as much as possible.

The idea of PCA in this study is introduced as follows: first, the annual condition has to be calculated since the data span is from 2013 to 2018 (The Blue Economic Zone of Marine Industry was approved and established by the Chinese central government in 2011, and official statistics became available in 2013, with the latest statistics as of 2018. The data interval of this study is limited to 2013–2018). Next, the overall condition is calculated according to the average level. In this process, the mean of the variables is calculated, and then the overall condition is calculated by the same method as the annual condition. Second, data normalization is performed first when calculating the annual performance level, and then it tries to calculate how many principal components are there by PCA. According to the calculation results, there are 3 factors with characteristic roots higher than 1. There are 3 principal components. The proportions of these 3 principal components are calculated by PCA, which are weights in the following text. On this basis, the factor score matrix is obtained, which contains scores of variables on 3 principal components. Third, the annual performance is calculated by Equation (1), and the performance scores of different regions are acquired through range standardization by Equation Finally, the annual performance scores from 2013 to 2018 and the comprehensive performance scores of different regions are calculated by Equation (3).

$${\mathrm{F}}_{\mathrm{j}}={\sum }_{\mathrm{i}=1}^{21}{\mathrm{f}}_{\mathrm{i}}\times {\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}}_{\mathrm{i}}\hspace{1em}\mathrm{j}=1,2,3$$

(1)

$${\mathrm{F}}_{\mathrm{j}}={(\mathrm{f}}_{\mathrm{i}}-{\mathrm{f}}_{\mathrm{m}\mathrm{i}\mathrm{n}})/({\mathrm{f}}_{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{f}}_{\mathrm{m}\mathrm{i}\mathrm{n}})\hspace{1em}\mathrm{j}=1,2,3$$

(2)

$$\mathrm{F}={\sum }_{\mathrm{j}=1}^3{\mathrm{F}}_{\mathrm{j}}\hspace{1em}\mathrm{j}=1,2,3$$

(3)

4.2. Evaluation Results

Data from 2013 to 2018 are collected from the statistical yearbooks. Here, only the data from 2013 are selected for a detailed analysis of the process and results due to the article’s length constraints. The PCA results are shown in

Table 2. PCA results.

Principal Component	Initial			Extracted
	Eigenvalue	Proportion	Cumulative	Eigenvalue	Proportion	Cumulative
1	14.9257	0.7107	0.7107	14.9257	0.7107	0.7107
2	2.5026	0.1192	0.8299	2.5026	0.1192	0.8299
3	1.8979	0.0904	0.9203	1.8979	0.0904	0.9203
4	0.9907	0.0472	0.9675
5	0.5123	0.0244	0.9919
6	0.1709	0.0081	1.0000

. A total of 6 principal components are extracted, including 3 with characteristic roots higher than 1. In other words, there are 3 principal components that can be used. Principal component 1 interprets 71.07% of the factors, principal component 2 interpreted 11.92% of the factors, and principal component 3 interprets 9.04% of the factors. The cumulative contribution of these three principal components is 92.03%.

The factor score matrix is shown in

Table 3. Factor score matrix.

Index (Variables)	No.	Principal Component 1	Principal Component 2	Principal Component 3
	fi	Component 1	Component 2	Component 3
Full-time equivalence of R&D personnel	f1	0.2563	−0.0294	0.0202
Full-time equivalence of R&D personnel in industrial enterprises above the designated size	f2	0.2500	−0.1072	0.0571
General public budget expenditures	f3	0.2524	0.0824	−0.0721
R&D expenses	f4	0.2543	0.0725	0.0477
R&D expenses in industrial enterprises above designated size	f5	0.2487	0.0074	0.1011
Power consumption	f6	0.1954	−0.3694	0.0106
Number of three types of patent applications in China	f7	0.2287	0.1466	−0.1010
Number of three types of granted patents in China	f8	0.2417	0.0102	−0.0360
High-quality provinces and the implementation of brand strategies	f9	0.2212	−0.2712	0.0139
Standardization	f10	−0.1387	−0.3167	0.4289
Gross imports	f11	0.1225	0.2906	−0.4943
Gross outputs	f12	0.2406	0.1807	−0.0911
General public budgets	f13	0.2547	0.0780	−0.0492
Main business income of industrial enterprises above designated size	f14	0.2235	−0.0239	0.2893
Per capita GDP	f15	0.0042	0.3537	0.5076
Household consumption level	f16	0.0375	0.3937	0.3781
Total wages of employees in urban units	f17	0.2463	0.1213	0.1212
Retirement insurance benefits	f18	0.2540	0.0752	0.0606
Basic endowment insurance of residents	f19	0.1807	−0.4434	−0.0293
Number of health institutions	f20	0.2319	−0.1510	0.1475
Enterprise informatization and E-commerce level	f21	0.2525	0.0071	−0.0493

. This coefficient is the factor gained by various indexes on the principal components, which refers to coefficients of all principal components on the above three principal components. The product of index (variable) and the principal component is the performance in the responsible innovation stage. After weight calculation, the responsible innovation performance is gained. During the calculation of the annual performance level, data normalization is performed first to eliminate the influences of different units. In the process of data normalization, the comparison results with means might be positive or negative, and the negative values are not reasonable. Range standardization is carried out during the comparison of regional differences in responsible innovation, and all results range between 0 and 1, indicating that range standardization is relatively reasonable.

The responsible innovation performances and comprehensive performances of regions from 2013 to 2018 are shown in

Table 4. General orders of scores.

Year	Region ➀	Region ➁	Region ➂	Region ➃	Region ➄	Region ➅	Region ➆
2013	Qingdao	Yantai	Weifang	Dongying	Weihai	Binzhou	Rizhao
	(1)	(0.6167)	(0.5041)	(0.2563)	(0.1761)	(0.1269)	(0)
2014	Qingdao	Yantai	Weifang	Dongying	Weihai	Binzhou	Rizhao
	(1)	(0.6151)	(0.4918)	(0.2559)	(0.2309)	(0.1444)	(0)
2015	Qingdao	Yantai	Weifang	Dongying	Weihai	Binzhou	Rizhao
	(1)	(0.5893)	(0.4724)	(0.2322)	(0.2285)	(0.1120)	(0)
2016	Qingdao	Yantai	Weifang	Weihai	Dongying	Binzhou	Rizhao
	(1)	(0.5220)	(0.3890)	(0.2002)	(0.1867)	(0.1018)	(0)
2017	Qingdao	Yantai	Weifang	Weihai	Dongying	Binzhou	Rizhao
	(1)	(0.5272)	(0.3826)	(0.2120)	(0.1933)	(0.0926)	(0)
2018	Qingdao	Yantai	Weifang	Weihai	Dongying	Binzhou	Rizhao
	(1)	(0.4708)	(0.3572)	(0.1407)	(0.1371)	(0.0747)	(0)
Total	Qingdao	Yantai	Weifang	Weihai	Dongying	Binzhou	Rizhao
	(1)	(0.5350)	(0.4243)	(0.1698)	(0.1691)	(0.1015)	(0)

Notes: scores are shown in the brackets.

. The results demonstrated that (1) the ranking of regions based on comprehensive responsible innovation performance, from highest to lowest, was as follows: Qingdao, Yantai, Weifang, Weihai, Dongying, Binzhou, and Rizhao. The scores for Qingdao, Yantai, and Weifang were significantly higher than those of the other regions. The results are presented in Figure 2. (2) In view of annual changes, the comprehensive responsible innovation performances of different regions fluctuated slightly. Only Weihai began to exceed Dongying in 2016, indicating that the responsible innovation elements of Weihai were improved significantly. The trends and changes are shown in Figure 3. Weihai, in accordance with the strategic plan of building the Blue Economic Zone on the Shandong Peninsula, actively promotes the integrated development of sea and land, vigorously implements the strategy of high-end, high-quality and high-efficiency development, and focuses on introducing modern industrial organization methods such as industrial chain and value chain into the marine economy, becoming a national modernized fishery demonstration area, China’s ocean-going aquatic products processing and cold chain logistics base, China’s leisure fishery capital, and a national marine high-tech industrial base. (3) Regarding the variation trends of different regions, Figure 4 demonstrates that those with high performance extended their lead over the six-year period. The differences among the top three regions—Qingdao, Yantai, and Weifang—became more pronounced in 2018, indicating the presence of a “Matthew Effect” in regional development. Specifically, the gap between Qingdao and Yantai widened more rapidly, while the gap between Qingdao and Weifang also increased. In contrast, the gap between Yantai and Weifang remained stable. Qingdao established a more comprehensive marine industry system, and its marine industry structure was optimizing development more rapidly than in other regions. (4) In regions that rank at the bottom, such as Rizhao, Binzhou, and Dongying, responsible innovation has developed slowly. This reflects that it is necessary to increase resource input and resource integration levels to increase stocks and optimize structures, thus improving the comprehensive performance level.

5. Conclusion and Insights

The major research conclusions of this study are as follows: (1) The ranking of regions based on comprehensive responsible innovation performance, from highest to lowest, was as follows: Qingdao, Yantai, Weifang, Weihai, Dongying, Binzhou, and Rizhao, with Qingdao showing significant leading advantages. (2) With respect to annual changes, the comprehensive responsible innovation performances of different regions fluctuated slightly; however, Weihai had surpassed Dongying since 2016, indicating a significant improvement in the responsible innovation elements of Weihai. (3) In terms of variation trends, regions with high performance extended their lead over the six-year period. The differences among the top three regions—Qingdao, Yantai, and Weifang—became more pronounced in 2018, indicating the presence of a “Matthew Effect” in regional development. Specifically, the gap between Qingdao and Yantai widened more rapidly, while the gap between Qingdao and Weifang also increased. (4) In regions that rank at the bottom, such as Rizhao, Binzhou, and Dongying, responsible innovation has developed slowly.

5.1. Theoretical Significance

(1)

The four-dimensional model and three-dimensional model of responsible innovation are integrated, and a conceptual framework of responsible innovation in the blue economic zone is constructed. At present, no agreement on responsible innovation has been reached in academic circles. This study deems that the three-dimensional model and four-dimensional model are essentially consistent. Responsible innovation covers the overall framework of the actors—activities—norms. Responsible innovation performance in the blue economic zone shall contain the logic framework of input—transformation—output.

(2)

Based on the overall framework of the actors—activities—norms, the performance evaluation index system of innovation performance in the blue economic zone is built by PCA. This index system has three dimensions and involves 21 indexes. Specifically, the responsible innovation elements of actors include human resource input, capital input and resource input. The responsible innovation activity includes patent, standardization, foreign trade and capital incomes. The responsible innovation norms include economic conditions, social insurance and information exchange.

(3)

The responsible innovation performance in the blue economic zone is evaluated using data from 7 regions from 2013 to 2018. As the process of establishing the index system follows the principles of being mutually exclusive and collectively exhaustive, the results prove the validity of the index system. In addition, it is found that the rank of regions in terms of comprehensive responsible innovation performance in the blue economic zone of the marine industry changed slightly, but the regional gap was expanding. In view of the time span, regions with high performance achieved higher performance, and regions with low performance achieved poorer performance. There is a “Matthew effect” in regional development.

5.2. Practical Significance

(1)

Increase input and pay attention to elements of actors in responsible innovation in the blue economic zone from the source. As a directional behavior, innovation involves not only correlations among the scientific community and scientific research institutes and social organizations but also conflict between the right to speak and comprehensive benefits. The stakeholders involved in responsible innovation development are diverse and are expected to share the associated responsibilities and risks. Responsible innovation is a huge systematic process that requires responsibility of the leader but also supports and participates in all social sectors, including government, universities, scientific institutions and social organizations.

(2)

Strengthen resource integration to assure high utilization of resources in the process. When perfecting the national innovation system, the government should further explore technological development strategies that conform to social needs, meet public expectations and realize the long-term win–win of stakeholders from the perspective of national innovation-driven development values. The value dimensions of innovation activities in public health and environmentally friendly aspects are recreated by responsible innovation. The social consequences of technological innovation, especially emerging technologies, are evaluated by constructive technological evaluation. Potential opportunities and threats are investigated systematically, and evaluations are feedback to the innovation process.

(3)

Paying attention to institutional innovation, building a long-term guarantee mechanism of responsible innovation, further perfecting laws and regulations about innovations, and determining the innovation management system and duties and properties of participating subjects in the blue economic zone through legislative forms are important tasks to assure innovation development in the blue economic zone. These are also beneficial to realize a uniform layout of innovative development in the blue economic zone, thus making local innovation management legalized and standard. It is suggested to build “responsible” management and service institutions for innovative development in the blue economic zone and provide one-stop services for innovation to assure the implementation of relevant innovation policies and regulations.

5.3. Limitations and Future Research

There are limitations in this research owing to the knowledge level and research conditions. This paper obtains the relevant data from statistical yearbooks as the main analysis object. However, some other important measurement index data are difficult to obtain, and only relative conclusions can be drawn under relative conditions due to the limitation of the existing provisions of the statistical yearbook. It is believed that more accurate evaluation conclusions will be drawn as statistical indicators gradually improve. Additionally, the most recent data from this source is only available up to the year 2018. Future research endeavors should prioritize continuous monitoring of this area and analyze the data promptly upon updates to ensure that the research accurately reflects the latest trends. In addition, the use of expert evaluations to obtain qualitative indicators can be a useful supplement to the existing statistics, which cannot cover all the connotations of “responsible innovation performance”. Therefore, the next step involves the development of a comprehensive evaluation system that incorporates both qualitative and quantitative indicators.