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The adverse effects on environmental sustainability, human health and animal welfare are often cited as the main reasons for reducing animal-based meat production and consumption. This study explored the food choice motives that determine consumer attitude toward plant-based meat (PBM) as a sustainable meat alternative. The theory of planned behavior (TPB) was applied to further determine whether an individual’s attitude toward PBM, subjective norms and perceived behavioral control influence their willingness to try novel meat substitutes (i.e. PBM). Finally, the moderating effect of meat attachment was also considered.

Online self-reported questionnaires were administered in Taiwan, and 294 valid questionnaires were collected. Structural equation modeling (SEM) and moderated regression were employed for analysis.

The results clarified the food choice motives that influenced consumer attitude toward PBM and revealed that attitude and subjective norms pertaining to trying PBM explained up to 35.03% of the variance in consumer willingness to try PBM. Notably, consumer meat attachment moderated the positive relationship between consumer attitude toward PBM and willingness to try PBM such that it became negative.

On the basis of the empirical findings regarding the food choice motives that influence consumer attitude and willingness to try PBM, this study provided practical implications for marketers seeking to increase consumer willingness to try PBM.

The main theoretical contribution of this research is that food choice motives should be considered in a TPB model to explain consumer willingness to try PBM. The moderating effect of consumer meat attachment should also be considered.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

This paper aims to design a magnetostrictive tactile sensor for surface depth detection. Unlike the human finger, although most tactile sensors have high sensitivity to pressure, they cannot detect millimeter-level depth information on the surface of objects precisely. To enhance the ability to detect surface depth information, a piezomagnetic sensor combining inverse magnetostrictive effect and bionic structure is developed in this paper.

A magnetostrictive tactile sensor based on Galfenol [(Fe₈₃Ga₁₇)_99.4B_0.6] is designed and studied for surface depth measurement. The optimal structure of the sensor is determined by experiment and theory. The test platforms for static and dynamic characteristics are set up. The static and the dynamic sensing performance of the sensor are studied experimentally.

The sensor can detect 0–2 mm depth change with a sensitivity of 91.5 mV/mm. A resolution of 50 µm can be achieved in the depth direction. In 50 cycles of loading and unloading tests, the maximum error of the sensor output voltage amplitude is only 2.23%.

The sensor can measure the depth information of object surface precisely with good repeatability through sliding motion and provide reference for object surface topography detection.

The purpose of this study is to investigate the influence mechanisms of multi-level ecological participants on technological innovation capabilities within the focal small and mid-size enterprises' (SME) innovation ecosystem. The author examines the moderating role of the innovation ecological environment.

With the lenses of innovation ecosystem theory, technological innovation theory and ecological theory, the author constructs and empirically tests a conceptual framework for exploring the effects of the focal SME's connections with universities and research institutions, and the industrial chain and ecosphere on their independent and collaborative innovation capabilities. The innovation ecological environment is employed as a moderating variable in the proposed model. The author issued email questionnaires to managers at innovative SMEs in Shenzhen, Shanghai and Jiangsu provinces. The data were used for multiple regression analyses to test the hypotheses.

As predicted, the author found that SMEs’ cooperation with universities and research institutions positively affects independent and collaborative innovation capability. The relationships between the industrial chain, the ecosphere and independent and collaborative innovation capabilities are all inverted U-shaped. Additionally, the author demonstrates that the innovation ecological environment positively moderates relationships between the focal SME's ecological participants and these two types of technological innovation capabilities.

The results enrich research on innovation ecosystems and technological innovation capability and provide important managerial implications for Chinese SMEs to enhance their technological innovation capability by constructing and coordinating innovation ecosystems. It also allows China, as well as other developing countries, to cultivate world-class enterprises as an innovative nation.

This study aims to present the cost and revenue efficiency evaluation models in data envelopment analysis in the presence of fuzzy inputs, outputs and their prices that the prices are also fuzzy. This study applies the proposed approach in the energy sector of the oil industry.

This study proposes a value-based technology according to fuzzy input-cost and revenue-output data, and based on this technology, the authors propose an approach to calculate fuzzy cost and revenue efficiency based on a directional distance function approach. These papers incorporated a decision-maker’s (DM) a priori knowledge into the fuzzy cost (revenue) efficiency analysis.

This study shows that the proposed approach obtains the components of fuzzy numbers corresponding to fuzzy cost efficiency scores in the interval [0, 1] corresponding to each of the decision-making units (DMUs). The models presented in this paper satisfies the most important properties: translation invariance, translation invariance, handle with negative data. The proposed approach obtains the fuzzy efficient targets corresponding to each DMU.

In the proposed approach, by selecting the appropriate direction vector in the model, we can incorporate preference information of the DM in the process of evaluating fuzzy cost or revenue efficiency and this shows the efficiency of the method and the advantages of the proposed model in a fully fuzzy environment.

Innovation is vital for sustainable regional development. Government is generally not a source of innovation per se, but the authors shows that by establishing and funding an industrial innovation ecosystem, it can create fertile conditions for research institutions to introduce innovative technologies into industry and for industry to introduce its gaps and needs to motivate and direct academic research. This paper aims to present a case study of the Jiangsu Industrial Technology Research Institute (JITRI) as a “triple helix” collaboration model engaging Industry-University-Research (IUR) institutions. The authors aim to provide a fresh perspective on constructing innovation ecosystems, promoting value creation and advancing the adoption of industrial technology.

Taking JITRI as a case study, this research examines its innovative approaches to interfacing with IUR organizations within China’s Yangtze Delta region. The authors propose a multilayered framework where JITRI serves as the core, facilitating the formation of a robust innovation ecosystem with diverse IUR entities.

This framework comprises three layers: core, platform and support. JITRI acts as the central nexus, binding these elements together and fostering a cohesive innovation ecosystem. By analyzing the operational mechanisms of the Jiangsu Provincial innovation system, the authors gain valuable insights into how JITRI bridges the gap between academia and industry. This facilitates the efficient commercialization of technologies. The success of the JITRI approach presents a compelling model for emulation by other provincial innovation ecosystems seeking to enhance their innovation capabilities.

This study enriches the ongoing conversation on innovation ecosystems, proposing novel avenues for further research. However, the field requires continuous monitoring through longitudinal studies. Given the long-term nature of such initiatives, the full impact of this approach might only be realized over several decades.

JITRI aims to create a robust and innovative provincial innovation ecosystem through its focus on IUR collaboration. This unique approach offers valuable insights and ideas for fostering the development of thriving innovation ecosystems in other provinces. These insights encompass new perspectives on innovation ecosystem development, value creation and industrial advancement.

This study pioneers the use of the JITRI system as a case study, offering valuable insights with potential application to innovation ecosystems across China and globally.

The purpose of this paper is to explore the high-quality development (HQD) strategy of Chinese mineral resource enterprises, which is important for Chinese mineral resource enterprises to improve the efficiency and benefit of resource utilization, reduce the intensity of resource and energy consumption and gradually form resource-saving and environment-friendly enterprises.

This study establishes an evaluation index system with four dimensions: economy, environment, society and management innovation. The entropy value method assigns weights to them and then uses the system dynamics (SD) model for case simulation.

The results of the SD simulation conclude that the fulfillment of social responsibility and the implementation of management innovation can accelerate the realization of HQD of mineral resource enterprises; profitability plays a crucial role in economic indicators; the improvement of energy-saving volume has the most significant impact on environmental benefits; the social contribution is the key element to measure social indicators; and the sales rate of core products has the most significant impact on the benefits of management innovation.

Based on the few studies on the evaluation of the development strategy of mineral resource enterprises, this study establishes an evaluation index system that considers the interactions between indicators, combines the entropy value method with SD and uses the SD model to comprehensively and systematically analyze the impact and degree of each factor on the HQD of mineral resource enterprises.

The purpose of this study is to understand the influence of the transformational, transactional and laissez-faire leadership styles and collaborative integrative behavior of the team with respect to organizational ambidexterity (the combination of exploration and exploitation learning) in university research groups.

From a survey conducted with a sample of 506 researchers, members of 165 research groups, working in an emerging economy, a multiple regression model analysis was performed.

Findings of this study provide evidence that the coordinator's transformational leadership and the collaborative integrative behavior of the team positively influence organizational ambidexterity of research groups. Transactional leadership and laissez-faire style do not show any significant influence.

This study addresses the lack of knowledge regarding organizational learning in research groups to explore and exploit knowledge through research result transfer processes based on the organizational ambidexterity logic in higher education institutions (HEIs) from emerging economies. The study aims to contribute to the literature on leadership styles and ambidexterity in HEIs in emerging economies, particularly in Latin America, where there is still a scarcity of research on the attributes of effective leadership.

Prosocial lending in online crowdfunding has flourished in recent years, and it has become a new way to fundraise for philanthropy. However, there is almost a 70% user attrition rate in crowdfunding. The purpose of this study is to understand what the lender’s lending experience and social connection influence lender retention of online prosocial lending from a self-determination perspective.

Drawing on self-determination theory (SDT), this research utilizes a quantifiable method for factors of the lender's lending experience and social connection. Additionally, the research constructs economic models to explore the impacts of these factors acting as the necessary conditions for basic psychological needs on lender retention, using a large-scale sample of over 380,000 lenders from Kiva.

The results indicate that, from the lender's lending experience aspect, the loan narratives with more profit language in the last lending and the failure of past participation are negatively related to lender retention. Regarding the lender's social connection aspect, their friends or small lending teams are positively related to lender retention, while whether they are invited and lending team size show negative influence. Furthermore, results indicate the moderating effects of the disclosure of lending motivation.

This research explores the mechanism of lender retention of online prosocial lending, providing a self-determination perspective about how previous experience influences long-term lending behavior. The study offers significant implications for the literature on online philanthropy, SDT and user retention of online platforms. At the same time, the study provides an understanding of the effects of different aspects of SDT.

A humanoid intelligent robot (HIR) possessing a human-like appearance can undertake human jobs, interact, communicate and even transmit emotions to human beings. Such robots have gradually been integrated into people's daily life and production scenarios. However, it is unclear whether and by what mechanism HIRs can stimulate people’s risk perception and its impact on consumption attitudes. Based on the risk decision theory, this study aims to take the social value substitution attribute of a HIR as the incentive and analyzes the influence of social value substitution and risk perception on the customers’ consumption attitudes.

Three experiments were conducted to investigate the related questions about the social value substitution attribute of a HIR, its impact on risk perception and the customers’ consumption attitudes.

The results reveal that physical labor, intellectual labor, friendship, kinship and the ego constitute the hierarchical elements of social value substitution. Among them, physical labor and intellectual labor pertain to the dimension of social function value substitution, while friendship, kinship and ego pertain to the dimension of social presence value substitution; social function value substitution and social presence value substitution affect the subjects’ risk perception positively, but the latter arouses a stronger risk perception; the 2 (risk perception of social function value: security/danger) × 2 (risk perception of social presence value: security/danger) condition corresponds to diverse consumption attitudes.

The results enrich the theories of the “cha-xu pattern” and “uncanny valley” and provide reference for the healthy development of the HIR industry.