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This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

Three-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.

First, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.

To evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.

The proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.

The purpose of this paper is to investigate how absorptive capacity mediates the relationship between ambidextrous organizational learning and performance among small and medium-sized enterprises (SMEs).

Based on the resource-based view (RBV) and the dynamic capability approach, this paper uses the resource-capability-performance framework to construct the theoretical model of this study and tests the theoretical model with the questionnaire survey data of 189 SMEs in mainland China.

Ambidextrous organizational learning has different effects on SMEs' performance in terms of survival performance and growth performance. Both exploitative learning and exploratory learning have positive effects on absorptive capacity, and absorptive capacity has positive influences on both the survival performance and growth performance of SMEs. Absorptive capacity plays different mediating roles in the relationships between ambidextrous organizational learning and SMEs' performance: absorptive capacity plays a partial mediating role in the relationship between exploratory learning and SME growth performance, while absorptive capacity plays complete mediating roles in other relationships.

Managers must stress the use of exploratory learning in order to promote SMEs' growth performance. However, to foster both absorptive capacity and SME performance in terms of survival and growth, managers must pay more attention to take advantage of ambidextrous organizational learning. Government as policymakers should create a favorable environment that enable SMEs to benefit much more from the deployment of ambidextrous organizational learning and absorptive capacity.

To the best of authors’ knowledge, this study is the first to theorize and test the mediating role of absorptive capacity in the linkage between ambidextrous organizational learning and SME performance in terms of survival and growth. Additionally, this study also is the first to provide empirical support for the impact of ambidextrous organizational learning on absorptive capacity among SMEs.

Being interested in developing a natural preservative for the prolongation of shrimp shelf life, this study aims to evaluate the Sargassum horneri extracts for their antioxidant effect, copper reducing power, copper chelating activity and polyphenol oxidase (PPO) inhibitory activity, as well as explored their potential preservative activity in white leg shrimp.

The antioxidant properties of Sargassum horneri 75% ethanol aqueous extracts were measured by 2,2-diphenyl-1-picryl hydrazyl (DPPH), 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), ferric reducing antioxidant power (FRAP) and PPO inhibitory activity. Sample III displayed the highest antioxidant activity, PPO inhibitory activity, copper reducing power and copper chelating activity, so it was selected for further studying its impact on shrimp's quality changes such as pH value, total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS), melanosis and sensory score during storage at 4°C.

Among all three samples, sample III containing 49.88% total phenolic contents was selected for the further study on the prevention of quality loss and melanosis of shrimp, because it yielded the highest antioxidant activity, PPO inhibitory activity, copper reducing power and copper chelating activity than the other two samples (samples II and IV). It was found that shrimp treated with 0.2% sample III had the lowest melanosis scores throughout the storage (p < 0.05). During ten days of storage at 4°C, shrimp treated with 0.2% sample III had a higher score in sensory properties (color, segments, texture and odor), compared with the control, 0.1% kojic acid and 0.1% sample III treated shrimp (p < 0.05). The results indicated that the treatment of shrimp with 0.2% sample III could extend the shelf life to eight days at 4°C.

The extracts of Sargassum horneri displayed potent PPO inhibition, antimicrobial and antioxidant properties. Importantly, the 75% extracts of Sargassum horneri could extend the shelf life. Considering these results, the extracts of Sargassum horneri may be used as natural preservatives in the food industry after further evaluation of their other properties such as toxicity, as well as provide a choice target to source natural products intended for cosmetics.

The originality of this paper lies in the development and application of the extracts of edible algae. To extend the shelf life of seafood, the polyphenolic-rich extract of Sargassum horneri provided another possible selection.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.