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The purpose of this study is to assist brand and product managers in selecting appropriate ingredient names for environmentally friendly products. It investigates the effects of unfamiliar ingredients on consumers’ evaluations of environmental friendliness and their purchase intentions, based on the cue consistency theory.

Five experimental studies (n = 968) were conducted to achieve the research objectives. Study 1 found that consumers tended to avoid choosing unfamiliar ingredients. Study 2 examined the impact of ingredient familiarity on consumers’ perceived greenness. Study 3 investigated the mediating role of perceived naturalness. Studies 4 and 5, respectively, explored the moderating effects of emphasizing the importance of technology in environmental conservation and product category.

The findings indicate that when environmentally friendly products are labeled with unfamiliar ingredients (vs. familiar), consumers’ perceived greenness and purchase intentions decrease. This effect is mediated by perceived naturalness. Moreover, the negative impact of unfamiliar ingredients is mitigated by emphasizing the importance of technology and the high-tech product category.

This paper reveals the unique role of unfamiliar ingredients in shaping consumer attitudes toward environmentally friendly products. Based on cue consistency theory, it uncovers how unfamiliar ingredients influence the perceived greenness of environmentally friendly products through perceived naturalness. Furthermore, the paper demonstrates the impact of emphasizing the importance of technology (emphasis vs. control) and product category (high-tech vs. low-tech) on consumer attitudes and behaviors toward environmentally friendly products.

This paper aims to introduce a novel 4D hyperchaotic fractional-order system which can produce one-to-four-wing hyperchaotic attractors. In the study of chaotic systems with variable-wing attractors, although some chaotic systems can generate one-to-four-wing attractors, none of them are hyperchaotic attractors, which is incomplete for the dynamic characteristics of chaotic systems.

A novel 4D fractional-order hyperchaotic system is proposed based on the classical three-dimensional Lü system. The complex and abundant dynamic behaviors of the fractional-order system are analyzed by phase diagrams, bifurcation diagrams and the corresponding Lyapunov exponents. In addition, SE and C₀ algorithms are used to analyze the complexity of the fractional-order system. Then, the influence of order q on the system is also investigated. Finally, the circuit is implemented using physical components.

The most particular interest is that the system can generate one-to-four-wing hyperchaotic attractors with only one parameter variation. Then, the hardware circuit experimental results tally with the numerical simulations, which proves the validity and feasibility of the fractional-order hyperchaotic system. Besides, under different initial conditions, coexisting attractors can be obtained by changing the parameter d or the order q. Then, the complexity analysis of the system shows that the fractional-order chaotic system has higher complexity than the corresponding integer-order chaotic system.

The circuit structure of the fractional-order hyperchaotic system is simple and easy to implement, and one-to-four-wing hyperchaotic attractors can be observed in the circuit. To the best of the knowledge, this unique phenomenon has not been reported in any literature. It is of great reference value to analysis and circuit realization of fractional-order chaotic systems.

Quadrotor micro aerial vehicle (MAV) is nonlinear and under actuated plant, and it is difficult to obtain an accurate mathematical model for quadrotor MAV due to uncertainties. The purpose of this paper is to propose one robust control strategy for quadrotor MAV to accommodate system uncertainties, variations, and external disturbances.

The robust control strategy is composed of two self‐organizing interval type‐II fuzzy neural networks (SOIT‐IIFNNs) and one PD controller: the PD controller is adopted to control the attitude and position; one of the SOIT‐IIFNNs is designed to learn the inverse model of quadrotor MAV online; the other SOIT‐IIFNNs is the copy of the former one to compensate for model errors, system uncertainties and external disturbances, both structure and parameters of SOIT‐IIFNNs are tuned online at the same time, and then the stability of the resulting quadrotor MAV closed‐loop control system is proved using Lyapunov stability theory.

The validity of the proposed control method has been verified through real‐time experiments. The experimental results show that the performance of SOIT‐IIFNNs is significantly improved compared with Backstepping‐based controller.

This approach has been used in quadrotor MAV, the controller works well, and it could guarantee quadrotor MAV control system with good performances under uncertainties, variations, and external disturbances.

The proposed SOIT‐IIFNNs controller is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable, demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the quadrotor MAV control system based on SOIT‐IIFNNs controller can achieve favorable tracking performance.

The purpose of this paper is to present a method to accurately forecast the tendency of the gross amount of energy sources consumption of the country and construct a new kind of algorithm for forecasting that synthesizes the advantages of the grey model, Markov chains, and least square method.

With the application of this new algorithm, this paper have forecasted the trend of the gross amount of energy sources consumption of the country and come to the conclusions that the new algorithm is more precise than the grey model. It is proved that the improved grey‐Markov chain algorithm is effective and can be used by authorities to make decision.

It was found that combining the grey model, Markov chains, and least square method, can be a new algorithm for forecasting the trendency of the gross amount of energy sources consumption.

The new algorithm is only suitable for the short‐term forecast.

The grey forecasting method reflects the overall tendency of primitive data sequence of the gross amount of energy source, and the Markov chain forecasting method reflects the effect of the random fluctuation. The least square method reflects the tendency of increase. The new algorithm is more precise than the grey model.

“Poor” information systems are found everywhere. In this paper, a control approach to “poor” information systems, such as social economic systems, is proposed. First, “poor” information processing and SCGM‐model will be discussed. Secondly, we will develop an optimal controller of “poor” information systems.

Based on ideal absolute errors and relative errors, a new grey model‐GM^p(1,1) model is presented. The existence problem of its solution is also solved based on a few conditions. Then, MGM^p(1,n) model is presented. These optimized models GM^p(1,n) and MGM^p(1,n) have good anti‐noise property to absolute and relative errors. Examples illustrate that they have very good fitting and forecasting results.

The purpose of this paper is to identify from the literature the successful R&D management cooperation factors and then examine their relevance to R&D management cooperation efforts between China and Australia.

The case study method is used to encourage a deeper appreciation of the dynamics of R&D management projects. A theoretical framework is constructed based on the literature to highlight factors of successful R&D management, and this framework is then applied to a case study involving the Chinese Academy of Sciences (CAS) and the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO).

The result is a hybrid multi‐dimensional model incorporating cultural and social capital variables. Several critical success factors were found to exist: funding, government support, institutional support, complementary technology and expertise, mutual respect and strong commitment from leadership. One additional critical success factor was the bilingual expertise of facilitators who manage to help bridge the gaps between both intellectual capital (technical expertise) and cultural differences.

The framework of successful R&D cooperation identified in this study can act as a springboard for applying the successful principles in broader cases of R&D management cooperation.

The value of this study lies in the development of a model for successful cross‐cultural application of R&D management cooperation between China, Australia and (by extension) other countries that may foster successful cooperation, build global empathy and create inclusive competitive advantage.

This paper aims to define and measure the environmental capabilities that are applied when the circular economy (CE) is introduced in businesses. Founded on the dynamic capabilities theoretical approach, the study analyzes different environmental competences that firms apply during this process. Environmental management systems, corporate social responsibility, reporting and accountability and other environmental accounting practices are studied in the same analytical framework used to study the environmental capabilities that influence the circular scope (CS) of firms. This study contributes to bridging the gap between academic research focused on environmental accounting and that investigating the introduction of the CE in businesses.

The results were obtained by using partial least squares structural equation modeling to analyze the relationship between environmental capabilities for the CE and the CS achieved by a sample of Spanish firms with more than 50 employees that expressed interest in the CE, eco-design, eco-innovation and other environmental issues.

Based on an analysis using the dynamic capabilities theoretical approach, the results suggest a positive relationship between the CS of firms, their environmental accounting practices and their level of corporate social responsibility (CSR) and accountability. Stakeholders’ pressure – which has a mediating effect on the CS of firms – is also analyzed, adding new insights to recent studies of this topic at the micro-level. The authors also explore whether the CS of businesses, which is related to the degree of their development of capabilities, influences environmental and financial performance.

The new insights obtained in this study can help overcome the limitations of conventional accounting approaches and incorporates a much broader scale of environmental information that can be applied to CE practices. These results also offer insights to practitioners regarding the internal measurement processes related to the CE and regarding CSR in particular for small and medium enterprises, because these metrics can be partially applied depending on the practices introduced in each firm. For policymakers, a better understanding of the CE’s introduction into businesses will contribute to the design of policies that can enhance its deployment, for example, by providing tools that set up regional priorities depending on the CE-related practices adopted by the firms located in the territory.

A CE involves the transformation of a linear economic model into a circular one to reduce dependence on raw materials and energy and to reduce the environmental impact of production and consumption. Understanding how to manage the specific competences that integrate capabilities applied to the CE will allow firms to improve their social and environmental reporting. In addition, other social implications of this study relate to improving relationships with consumers and stakeholders and to the practice of social corporate sustainability.

This study goes beyond previous research on the CE to extend the authors’ knowledge about its adoption at the micro-level by taking a transversal approach, as its subject spans the fields of environmental accounting and the CE while addressing both in a framework of analysis. The analysis of the accounting concerns of the CE in businesses and the study of concerns related to endogenous environmental competences are quite original under the theoretical framework of dynamic capabilities, and this study is a first step in an incipient line of inquiry.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.

Mobile fitness apps (MFAs) are increasingly popular for people to promote physical activity (PA) and further enhance health status via behavioral change techniques (BCTs), but the phenomenon of users abandoning MFAs is still common. For improving users' PA and decreasing dropout rates of MFAs, this study intends to gain insights into the effects of major BCTs-based incentive factors on users' PA under MFAs context and the gender differences in their effects.

Based on self-determination theory, three major incentive factors were chosen from the perspective of self-peer-platform incentives, i.e. self-monitoring (SM), social support (SS) and platform rewards (PR). A dataset of 4,530 users from a popular mobile fitness app was collected and was analyzed using fixed effects models.

The results show that all three types of incentive factors are positively associated with users' PA. The estimated effect sizes can be ordered as: SM > PR > SS. Moreover, social support has a stronger positive impact on PA of females than males, whereas platform rewards have a weaker positive effect on PA of females than males. In addition, the results also indicate there are no significant gender differences in the effect of self-monitoring.

There is insufficient research on systematically examining the effects of different types of incentive factors of MFAs on users' PA in one study. This study extends the current understanding of incentive factors by simultaneously examining different incentive factors and the role of gender. The findings can also provide insightful guidance for the design of MFAs.