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This study explores the antecedent configurations shaping ambidextrous environmental strategy (AES) and the subsequent performance outcomes. The lack of literature from the configurational perspective and inconsistent performance results suggest that this study has significant implications for practitioners, policymakers and the public. Therefore, this study aims to investigate how different antecedent conditions interact to shape AES and subsequent performance outcomes.

To achieve the research aims, the current research utilize research techniques based on technology–organization–environment framework and configurational perspective. This study collects data from 317 Chinese manufacturing enterprises and tests the theoretical framework using fuzzy set qualitative comparative analysis and propensity score matching.

Perceived institutional pressure, green supply chain integration and digital technology adoption form four paths that lead to the existence of AES. There are four sets of replaceable conditions between distinct paths. In addition, except for configuration P3, all other configurations promote environmental, operational and financial performance.

Our results provide new insights for enterprises to shape AES and achieve multiple performances, and new ideas for promoting environmental policies and public environmental awareness.

This study adds literature on AES and confirms multiple drivers, revealing their interaction mechanisms and key antecedent conditions. In addition, this study promotes the performance practice of AES by examining different AES configurations that achieve triple performance and insignificant operational performance.

Public reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study explores the public attitudes and emotions toward educational robots through online reviews on Weibo and Twitter by using text mining methods.

Our study applied topic modeling to reveal latent topics about educational robots through online reviews on Weibo and Twitter. The similarities and differences in preferences for educational robots among public on different platforms were analyzed. An enhanced sentiment classification model based on three-way decision was designed to evaluate the public emotions about educational robots.

For Weibo users, positive topics tend to the characteristics, functions and globalization of educational robots. In contrast, negative topics are professional quality, social crisis and emotion experience. For Twitter users, positive topics are education curricula, social interaction and education supporting. The negative topics are teaching ability, humanistic care and emotion experience. The proposed sentiment classification model combines the advantages of deep learning and traditional machine learning, which improves the classification performance with the help of the three-way decision. The experiments show that the performance of the proposed sentiment classification model is better than other six well-known models.

Different from previous studies about attitudes analysis of educational robots, our study enriched this research field in the perspective of data-driven. Our findings also provide reliable insights and tools for the design, development and management of educational robots, which is of great significance for facilitating artificial intelligence in education.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

Based on social exchange and resource dependence theories, this research investigates how manufacturing firms’ commitment to low-carbon operations management (CLCOM) prompts manufacturing carbon performance (MCP) through low-carbon supply chain collaboration (SCC), as well as the moderating role of supply chain risk management (SCRM).

This study verifies the hypotheses employing hierarchical regression analysis and bootstrapping methods through an online survey of 297 Chinese manufacturers.

The results demonstrate that manufacturers’ low-carbon SCC mediates the influence of affective and continuance CLCOM on MCP. SCRM dampens the link between affective CLCOM and low-carbon SCC. Further, SCRM heightens the relationship of continuance CLCOM–low-carbon collaboration with suppliers, but does not enhance the level of continuance CLCOM–low-carbon collaboration with customers.

This research contributes to the theory and practice area by unveiling the “black-box” of the CLCOM–MCP relationship and considers SCRM’s moderating effect.

The rapid development of information technology, epitomized by AIGC and the metaverse, presents unprecedented challenges to techno-ethics, exposing society to significant risks and uncertainties. A systematic investigation and discussion of the construction of techno-ethical order become crucial under the paradigm of risk society theory. The selection of conditions and pathways for constructing a techno-ethical order under the risk society theory paradigm becomes an unavoidable and vital issue.

Drawing on risk society theory, this study employs scientometrics and qualitative comparative analysis (QCA) to empirically analyze the key factors and conditional pathways in the construction of techno-ethical order. Initially, a quantitative analysis is conducted on 1,490 thematic literature retrieved from CNKI and WoS to identify the hot topics and core concepts in techno-ethical research. Subsequently, QCA configuration analysis is applied to calculate eight evaluation indicators and their weights from the perspectives of government, society and individuals. Finally, the study explores the mechanisms of the impact of these indicators’ weights on the construction of techno-ethical order.

The analysis of factor weights and pathways indicates that the selection of pathways for constructing techno-ethical order is influenced both by the inherent development patterns of technology and societal systems and cultural values. Literature metrics analysis reveals an overall trend of sustained growth in techno-ethical research, indicating an unprecedented prosperity in this field. Alongside technological advancements, keywords related to “artificial intelligence” play a crucial role in current techno-ethical research. Configuration analysis demonstrates that conditional variables from the dimensions of government, society and individuals form a configuration pathway, influencing and synergistically impacting the overall level of techno-ethical order construction. Attention should be given to the mutual constraints and synergistic effects of factors related to technological development, societal systems and cultural values.

This study, grounded in the risk society theory paradigm, quantitatively explores the key factors and pathways of techno-ethical order construction in academic texts, expanding new perspectives, providing novel insights, establishing innovative methodologies and extending new boundaries in the field. Further enrichment of the dataset and in-depth discussions are warranted for continued advancement.

The purpose of this paper is to design a flying wheel-legged humanoid robot (FWLR), endowing the robot with flight capability to improve the obstacle-crossing ability of the wheel-legged humanoid robot. A flight control method using thrust-vector-control (TVC) under constant thrust strength is proposed, which reduces the performance requirements on the response speed of thrusters.

To endow the robot with flight capability, three sets of thrusters are installed at the robot’s back and two arm ends to provide flight lift and the direction of thrust can be changed through the arm swing. According to the robot configuration, this paper established a linearized dynamic model and proposed a constant-strength-thrust-vector-control (CSTVC) framework enabling the robot to achieve flight without thrust intensity change.

With the proposed modeling method and CSTVC framework, FWLR can inhibit attitude and position drift during takeoff and hovering, and has certain adaptability to takeoff attitude. Finally, FWLR reached a flying height up to 1 m under a 30 kg large self-weight with fixed thrust strength.

The design, modeling and flight control method proposed in this paper enables a human-sized wheel-legged humanoid robot to achieve takeoff and hovering for the first time. The movement range of wheel-legged humanoid robot is extended to the air, thereby enhancing its application value in emergency tasks such as disaster search-and-rescue.

This study aims to design a novel 3 degree-of-freedom parallel-driven hydraulic wrist (PHW) joint, characterized by a compact structure, heavy payload capacity and spherical workspace.

In this paper, the kinematics and dynamics mathematical model of PHW is analyzed based on the closed-loop vector method, screw theory and virtual work principle. And the key parameters of PHW are determined based on the singularity analysis. The integrated design method of hydraulic and mechanical systems is used, thereby enabling a hose-less configuration that fosters a low-leakage hydraulic system structure with reduced self-weight. Additionally, this research proposed a dynamic nonlinear compensation control methodology predicated on a payload model to enhance the stability and precision of trajectory tracking for PHW. Finally, several experiments have been conducted to evaluate and validate the performance of the proposed approach and the payload capacity of PHW.

Experiment results show that PHW has a payload-to-self-weight ratio of 4(payload 14 kg with self-weight 3.5 kg) under supply pressure 7 MPa. The experimental assessment of payload capacity substantiates the efficacy of the dynamic nonlinear compensation control method for PHW. Remarkably, the trajectory tracking errors for PHW remain under 0.03 rad, even when subjected to payloads of 10.5 and 14 kg.

This study presents an effective parallel hydraulic-driven wrist structure. This parallel structure provides a spherical workspace with flexible motion, and larger payload capacity compared with the existing robot wrist.

Despite the growing importance of digital transformation, few studies have investigated its precise effects on firm efficiency. This research explores the differential effects of digital transformation on the profitability and marketability of manufacturing firms.

We analyze the relationship between digital transformation and firm efficiency using a dataset of Chinese-listed manufacturing firms from 2011 to 2023.

The results indicate that digital transformation improves marketability and has a U-shaped relationship with profitability. Moreover, industry competition amplifies the positive effect of digital transformation on marketability but attenuates its U-shaped effect on profitability. In contrast, media coverage attenuates the positive effect of digital transformation on marketability and amplifies its U-shaped effect on profitability.

While the existing conclusion about the efficiency of digital transformation is inconsistent, this research enriches the literature on digital transformation and provides insights for improving firm efficiency in terms of both profitability and marketability.

Building on upper echelons theory, this study explores the influence of managerial cognition on firm innovation during times of crisis. Specifically, we aim to disentangle the concept of cognitive complexity by examining how CEOs’ cognitive depth and cognitive width differently influence their firms’ innovation outcomes. Additionally, we investigate how organizational slack moderates the impact of these cognitive attributes on innovation, providing a deeper understanding of the conditions under which managerial cognition drives firm adaptability in crises.

This study utilized a sample of 115 listed US firms ranked in the top 200 in terms of market capitalization share in 2020. We measured the key variables by analyzing text and archival data from interviews with CEOs, particularly focusing on their discussions regarding the impacts of the COVID-19 pandemic. Regression analysis was employed to test the hypothesized relationships in the research model.

The results reveal that under the crisis, CEO cognitive depth enhances firm innovation, while CEO cognitive width impedes firm innovation. Moreover, organizational slack weakens the positive relationship between CEO cognitive complexity and innovation.

This study significantly contributes to and extends the established body of research on a leader’s cognition during a crisis. Our study goes beyond traditional views of cognitive complexity by highlighting the distinct impacts of two critical elements: cognitive depth and width, on decision-making processes. This study contributed to the innovative decision-making literature by opening up the black box behind the decision-making process of innovation during uncertainty. This underscores the multifaceted nature of cognitive processes in innovation, highlighting the interplay between cognitive depth, cognitive width and organizational resources in driving firm innovative outcomes during the crisis. We also broaden the temporal scope of empirical research on CEO cognition by gathering data from CEO interviews conducted during the COVID-19 pandemic.

This study reveals that when CEOs have a broader focus and attend to a wide range of information, their ability to quickly utilize firm resources for formulating competitive actions decreases during uncertainty. Consequently, it is crucial for CEOs to acknowledge the limitations of their attentional capacity. The allocation of their attention and information processing capacity has significant implications for their innovative decision-making processes, particularly in navigating through crises.

Our study finds that excessive attention during times of crisis may not necessarily be beneficial to firm innovation. An excessive focus on problems can lead to scattered attention, impairing judgment and decision-making abilities. Moreover, excessive attention to problems may trigger panic and unnecessary stress, further impacting decision quality. High cognitive width can trap teams in short-term thinking and emergency mode, neglecting long-term strategies and opportunities such as innovation investment. Yet, firms with more slack resources can reduce the negative impacts of cognitive depth.

This study proposes a comprehensive cognitive model to understand managers’ decision-making during a crisis. The research posits that different dimensions of CEOs’ managerial cognition have distinct impacts on firm innovation in crisis environments. This study significantly contributes to the study of managerial cognition and innovation literature.

This article investigates the influence of marine ecological compensation policy on enterprises’ environmental investment and explores whether enterprise ownership could impact the said influence.

Using the data of China's A-share listed enterprises for the period 2007–2020, the paper develops a difference-in-differences model and a moderating effect model.

The outcomes corroborate that the marine ecological compensation policy positively influences enterprises' environmental investment, and the effect is nonlinear. Specifically, the marine ecological compensation policy significantly impacts enterprises with lower and higher environmental investment. The empirical evidence from the moderation model shows that the effect of the policy is more significant on the non-state-owned enterprises’ environmental investment.

The findings are based on a sample of 559 listed A-share enterprises in China. Additional studies could focus on data from other countries.

Based on the present scenario of Chinese enterprises' environmental investment, the results report that the marine compensation policy needs to be differentiated for firms having different ownership and different levels of environmental investment. The study provides valuable insights for the government to formulate marine ecological compensation policies.

Marine ecology increasingly affects the economic development of countries, and the study on the influence of relevant environmental policies is of practical significance. However, most scholars concentrate on the research of environmental regulation, and have little focus on the policy effect of marine environmental compensation. This paper studies how marine ecological compensation policy influences the environmental investment behavior of enterprises, and further analyzes the difference in the policy effect caused by the nature of enterprises’ ownership, which not only fills the gap in this field, but also provides a scientific basis for the formulation and adjustment of marine ecological compensation policy.