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Memory consolidation during wakeful rest: Evidence from EEG and fMRI LEI Xu, WENG Linman, YU Jing 2025, 33 (5):  729-743.  doi: 10.3724/SP.J.1042.2025.0729 Abstract ( 212 )   PDF (983KB) ( 317 )   Peer Review Comments Both wakeful rest and sleep are beneficial for offline memory consolidation. However, our understanding of the connections and differences in memory consolidation between these two states, particularly regarding the shared cognitive neural mechanisms, remains limited. This study will focus on “memory consolidation during wakefulness”, using declarative and procedural memory tasks to examine memory consolidation activities under natural conditions as well as during modulation by neural replay-based closed-loop Targeted Memory Reactivation (TMR) and closed-loop electrical stimulation. The aim is to investigate the roles of wakeful rest and sleep in memory consolidation and explore the underlying neural mechanisms involved. To this end, the study will address the following key objectives: (1) Propose a unified theory of offline memory consolidation that spans both sleep and wake states, leveraging the identification of common characteristics between these states as a breakthrough to explore neural biomarkers of memory consolidation during wakeful rest. (2) Use neural replay activity as an entry point, this study will capture it to pinpoint the time window during which memory consolidation occurs and specifically identify the relevant neural features. (3) Building on sleep-state research to verify the effectiveness of the neural replay-based closed-loop TMR and provide guidance for its application during wakeful rest, while exploring the corresponding neural mechanisms. (4) Investigate the modulatory effects of direct hippocampal stimulation on memory consolidation and develop an electrical stimulation protocol for memory enhancement. (5) Conduct long-term follow-up studies to assess the effects of memory consolidation interventions over time, observing changes in memory performance across extended time scales, verifying the ecological validity of the interventions, and exploring the potential to apply laboratory findings to real-world learning contexts. This study presents three major innovations. First, it enhances our understanding of the role of wakeful rest in facilitating memory consolidation. While sleep has been extensively studied in the context of offline memory consolidation, with its mechanisms well understood, research on memory consolidation during wakefulness remains insufficient and requires further in-depth exploration. Currently, most human studies focus on the behavioral level, with few examining the underlying neural mechanisms, which limits our understanding of offline memory consolidation during wakefulness. Therefore, this study specifically focuses on memory consolidation during wakefulness and conducts a series of experiments to broaden our understanding of offline consolidation. Second, it offers an accurate characterization of the macroscopic neural representation of offline memory consolidation during wakeful rest. Neural replay, a key mechanism in memory consolidation, is challenging to detect directly in healthy humans using non-invasive methods. However, with the aid of computational neuroscience techniques, we can capture neural replay activity using non-invasive neuroimaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). By focusing on neural replay activity, this study offers a more precise depiction of the neural processes involved in offline memory consolidation during wakeful rest, in contrast to traditional approaches that rely on correlation analysis to infer neural representations. Third, it provides new approaches to memory regulation. This study leverages neural replay activity to explore closed-loop TMR and closed-loop electrical stimulation as novel memory regulation techniques. By providing new insights into memory modulation, this study offers valuable directions for future research on memory intervention. In summary, this study aims to utilize advanced techniques such as EEG, fMRI, temporal interference (TI) electrical stimulation, and computational neuroscience techniques to capture the dynamic memory consolidation activities during both waking and sleep states, uncover the core characteristics of offline memory consolidation, and explore novel pathway for memory regulation based on real-time neural feedback. The implementation of this study will be instrumental in elucidating the neural mechanisms underlying memory consolidation across different brain states and laying the foundation for regulating memory consolidation during wakeful rest. Going forward, this study aims to apply its findings to educational interventions, such as learning strategy design, and initiate translational research to unlock the full potential of these interventions in real-world applications. References | Related Articles | Metrics

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The cognitive and neural mechanisms underlying the effects of food-specific inhibition training on eating behaviors YANG Yingkai, XIA Haishuo, NIE Haoyu 2025, 33 (5):  744-752.  doi: 10.3724/SP.J.1042.2025.0744 Abstract ( 175 )   PDF (736KB) ( 274 )   Peer Review Comments Overconsumption of high-calorie foods has become a critical contributor to overweight and obesity, posing substantial threats to individual health and increasing societal costs. Traditional interventions, such as pharmacotherapy or surgical procedures, although somewhat effective, can be invasive and carry risks. In contrast, cognitive training approaches are noninvasive, simple to administer, and relatively easy to scale, making them promising for modifying maladaptive eating behaviors. Recent advances have shown that food-specific inhibition training, which embeds food images into a Go/No-go task, can indeed alter individuals’ choices of high-calorie foods. However, how exactly this training exerts its effects remains insufficiently understood. To address this gap, the present research proposes a dual-cognitive-pathway theoretical model and systematically investigates its behavioral and neural underpinnings. Rather than improving general inhibitory control—an approach shown to have limited success in changing eating behaviors—food-specific inhibition training focuses on pairing specific foods with “Go” (respond) or “No-go” (inhibit) actions. Past behavioral evidence indicates that repeated “Go” actions can raise the subjective value of the paired foods, while repeated “No-go” actions can diminish it. Additionally, training may form stimulus-response (S-R) links such that “Go” foods are processed as automatically actionable, whereas “No-go” foods are associated with automatic inhibition. Building on this body of work, we propose two main pathways through which food-specific inhibition training modifies eating behavior: (1) Food Value Updating: By frequently responding to certain “Go” foods, individuals may infer that these foods are more desirable; likewise, repeated inhibition of certain “No-go” foods may decrease their subjective value.(2) Automatic Response/Inhibition Formation: By repeatedly pairing specific foods with action (Go) or inhibition (No-go), individuals form automatic links. In subsequent eating scenarios, these learned links can bias behavior toward “Go” foods and away from “No-go” foods, even without explicit conscious deliberation. We further argue that these processes are supported by distinct neural circuits: (a) a reward-related circuit that mediates value changes, and (b) conflict monitoring and control networks that help instantiate automatic action or inhibition associations. To test our dual-pathway model, we plan four overarching studies, each with two experiments (behavioral and fMRI): (1) Study 1 (Experiments 1 & 2) examines Go-food value elevation. We predict that frequent “Go” actions raise the subjective and neural indices of these foods’ value (e.g., stronger activation in reward areas). Post-training, participants should choose these “Go” foods more often in a food-choice task. (2) Study 2 (Experiments 3 & 4) focuses on No-go-food value reduction. We expect that repeated inhibition lowers the perceived value of “No-go” foods and reduces reward-related neural responses, leading participants to select these foods less frequently. (3) Study 3 (Experiments 5 & 6) targets the Go-food-automatic-response link. We hypothesize that training repeatedly pairing certain foods with action yields faster behavioral responses to these “Go” items and, neurologically, reduced activation in conflict-related brain regions when selecting them. This translates into higher choice frequency for these “Go” foods. (4) Study 4 (Experiments 7 & 8) investigates the No-go-food-automatic-inhibition link. We propose that repeated inhibition for certain foods slows subsequent behavioral responses when individuals are unexpectedly required to “Go” for the same items, reflecting an established automatic-inhibition link. Neurally, we anticipate corresponding alterations in conflict monitoring and default-mode network connectivity, predicting lower choice rates for these “No-go” foods. A key contribution of this research is the dual-cognitive-pathway model, which posits that food-specific inhibition training modifies eating behavior by (a) updating food value and (b) establishing automatic S-R links. Unlike prior attempts to explain training effects solely via improved inhibitory control—which often fail to translate into real-world eating behavior—our approach delineates the more plausible routes by which food-specific actions or inhibitions shape subsequent choices. On the neural level, we systematically distinguish between changes in reward-related activation (underlying value updates) and changes in activation and connectivity within conflict-monitoring and control networks (underlying automatic response/inhibition formation). This distinction may help identify precise neural targets for future interventions—such as transcranial magnetic stimulation or neurofeedback—that could enhance the effectiveness of food-specific inhibition training. Lastly, although our immediate participants are non-obese individuals, the framework developed here will be highly relevant to clinical populations if the hypothesized mechanisms prove robust. By illuminating how simple, noninvasive cognitive tasks can alter the neural and behavioral responses to high-calorie foods, this research could inform the design of scalable, practical interventions to curb overeating and promote healthier dietary habits. References | Related Articles | Metrics

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The effect of feedback from social media interactions on food reward processing and its mechanisms ZHANG Xuemeng, LIU Yong, HAN Yin, CHEN Hong 2025, 33 (5):  753-765.  doi: 10.3724/SP.J.1042.2025.0753 Abstract ( 172 )   PDF (1051KB) ( 328 )   Peer Review Comments Enhanced food reward responses and the lure of food cues in the environment may be important contributors to the obesity epidemic. Social media exposure has been found to be a risk factor for overeating, but the underlying mechanisms of influence have not been explored. Research analyses suggest that the seemingly innocuous “likes” and comment exchanges related to delicious food on social media can set off a chain reaction in the brain, triggering a reward response. This response might disrupt the normal regulatory mechanisms of our eating patterns and could well be the linchpin of the dietary disorders that often accompany heavy social media use. Most of the previous attempts at intervention have centered around strategies such as attempting to dampen the food reward response. This could involve dietary restrictions that limit the intake of highly palatable foods or the use of medications that aim to reduce the brain's sensitivity to food rewards. Alternatively, efforts have been made to enhance the inhibitory control ability, which requires individuals to exercise self-restraint when faced with food temptations. But these methods demand an extraordinary amount of willpower. For example, asking someone to resist the urge to eat a favorite dessert after seeing it repeatedly on social media is a Herculean task. Many individuals find it nearly impossible to maintain such control over the long term, leading to a cycle of failed attempts and frustration. Based on the food reward and sociocultural theories, and using the well-observed phenomenon that social media use is linked to dietary disorders as a springboard, this study zeroes in on the influence mechanism and intervention strategies of food social media interaction on the food reward processing of obese individuals. In the first part of the study, the spotlight is on determining whether social media interaction has any bearing on the food reward processing of obese individuals. To achieve this, the study aims to peel back the layers and reveal the underlying influence mechanism from a theoretical standpoint. Given the unique capabilities of ERP (Event-Related Potentials) in precisely measuring the timing of neural activities and fMRI (Functional Magnetic Resonance Imaging) in mapping the spatial aspects of neural pathways, both techniques are harnessed. Study One utilizes the ERP technique to meticulously explore, from the dimension of time course, how social media “likes” and comments impact the neuroelectrophysiological activities associated with food reward in obese individuals. It looks at how quickly and intensely the brain responds to such stimuli. Study Two employs the fMRI technique to separate the anticipation (“wanting”) and acquisition (“liking”) of food through the incentive delay task. By carefully distinguishing the time course of reward processing, it can then examine, from the spatial pathways dimension, how social media “likes” and comments affect the neural circuitry and connections involved in food reward in obese individuals. In the second part, the main thrust is on devising ways to help obese individuals foster healthy eating behaviors via social media platforms. This is accomplished by training social media interaction behaviors. Study Three uses the ERP technique to dig deeper into the impact of such training and comments on the neuroelectrophysiological activities related to the reward of healthy food in obese individuals. It aims to understand if and how the brain can be rewired to respond more favorably to healthy options. Study Four employs the fMRI technique to comprehensively assess the impact on the neural mechanism of healthy food reward, looking at changes in brain regions and their functional connectivity. Previously, the reward mechanisms of “wanting” and “liking” for food among obese individuals have been a subject of much speculation and inconsistent findings. This research breaks new ground by delving into these two psychological processes from the novel vantage point of social media interaction. It crafts simulated social media interaction and behavior training tasks. These innovative efforts not only expand the frontiers of the food reward theory but also offer novel directions and solid theoretical underpinnings for obesity intervention and the cultivation of a more health-conscious social media environment. Concurrently, it also formulates intervention strategies for enhancing the public cultural service system and promoting healthy eating, which could potentially be a game-changer in the global battle against obesity. References | Related Articles | Metrics

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Identification and fulfillment of psychological support needs for disabled elderly: Dynamic optimization based on customized resource allocation WU Lili, LI Ze, BI Tianyi, FU Rao 2025, 33 (5):  766-779.  doi: 10.3724/SP.J.1042.2025.0766 Abstract ( 119 )   PDF (754KB) ( 196 )   Peer Review Comments The aging population is increasing rapidly worldwide, particularly in China, leading to a growing number of disabled elderly individuals with complex and dynamic psychological needs. Traditional psychological care models, which are often static, are inadequate to address these evolving and individualized needs. The present research proposes a novel framework for identifying and addressing the psychological needs of disabled elderly individuals, focusing on dynamic resource allocation, personalized care, and real-time feedback mechanisms. The goal is to optimize service delivery by continuously adapting to the changing psychological needs of elderly individuals, ensuring the efficient and effective use of resources. The study adopts a mixed-methods approach, combining both qualitative and quantitative research methodologies to provide a comprehensive understanding of the psychological needs of disabled elderly individuals. The research design involves conducting in-depth interviews with elderly individuals, their caregivers, and healthcare providers. Additionally, surveys are carried out to assess various psychological needs, including emotional support, social interaction, spiritual comfort, and psychological counseling. Standardized psychological assessment tools, such as the Geriatric Depression Scale (GDS) and WHOQOL-OLD, were utilized to measure mental health and emotional distress. This comprehensive data collection approach enables the creation of personalized care profiles for each participant based on their unique psychological and social needs. The research seeks to test several hypotheses. First, it hypothesizes that personalized psychological support services, which dynamically adjust based on real-time data, will significantly improve the mental health and well-being of elderly individuals. Second, it is proposed that integrating real-time feedback mechanisms into service delivery will enhance the responsiveness and effectiveness of psychological support, ensuring that services are continuously aligned with the evolving needs of the elderly. Third, the study investigates whether multi-stakeholder collaboration—including healthcare providers, family caregivers, and community resources—can lead to more effective, equitable, and holistic care for disabled elderly individuals. To achieve these goals, we created personalized care profiles for each participant, identifying their unique psychological needs and adjusting interventions accordingly. The study also designed a dynamic feedback model that continuously adjusts resource allocation based on assessments of health status, social interaction, and psychological well-being. This feedback mechanism ensures that psychological support services are continuously aligned with the individual’s needs, providing adaptive and responsive care. In addition to real-time data collection, the study incorporated a longitudinal design to track the long-term impact of dynamic, personalized care on mental health and quality of life. By monitoring participants' progress over time, the research can assess whether ongoing adjustments to care plans result in improved overall well-being. The study also focuses on theoretical innovations that contribute to advancing the field of elderly care. These innovations include the development of four core theories: Dynamic Needs Hierarchy Theory, Resource Precision Matching Theory, Closed-loop Feedback Optimization Theory, and System Collaborative Optimization Theory. Each theory addresses specific challenges in providing psychological care to disabled elderly individuals, particularly in ensuring that care is personalized, dynamic, and collaborative. Dynamic Needs Hierarchy Theory extends traditional models by proposing that psychological needs are not fixed but fluctuate depending on various factors such as health, family support, and social circumstances. This theory offers a more adaptable approach to care, recognizing the need for flexibility in addressing changing psychological priorities. Resource Precision Matching Theory introduces an approach for precisely allocating psychological resources based on the intensity and urgency of individual needs. By matching resources with the specific requirements of elderly individuals, this theory ensures that services are delivered efficiently and equitably, particularly for vulnerable populations. Closed-loop Feedback Optimization Theory emphasizes the use of dynamic feedback loops to continuously adjust care plans based on real-time assessments of the elderly's needs, improving the efficiency and responsiveness of psychological support services. Lastly, System Collaborative Optimization Theory highlights the importance of multi-stakeholder collaboration, ensuring that psychological care involves coordinated efforts from healthcare providers, families, and communities to deliver comprehensive and equitable care. In conclusion, this study presents an innovative framework for identifying and addressing the psychological needs of disabled elderly individuals. By integrating dynamic feedback mechanisms, personalized care, and multi-stakeholder collaboration, the framework provides a flexible and adaptive approach to psychological support. The research also introduces several theoretical innovations that advance the field of elderly care, offering new insights into the dynamic, personalized, and collaborative nature of care. This framework has the potential to significantly improve the quality of life and mental health of elderly individuals, especially the disabled. Moreover, it can be applied to enhance elderly care systems globally. References | Related Articles | Metrics

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The influence of temporary team’s collaboration history on proactive collaborative behavior based on a social network perspective LIN Yuying, ZHAO Kai 2025, 33 (5):  780-796.  doi: 10.3724/SP.J.1042.2025.0780 Abstract ( 100 )   PDF (689KB) ( 134 )   Peer Review Comments Dynamic changes and competitive environment have spawned a large number of temporary teams. Temporary team can be defined as a type of team where a temporally bounded group of interdependent members, form to complete a specific task over certain time periods. Compared to regular teams with long-term shared goals and rich interaction bases, members of temporary teams focus more on individual tasks, lack common cognitive and emotional foundations, and are thus less motivated to collaborate with each other. How to promote proactive collaborations of temporary teams under circumstances of limited teamwork-time expectations and compressed interaction process is crucial to team development. Existing research has mainly focused on emergent states and behaviors that affect temporary team performance, neglecting the important role of existent connections when a temporary team is first built. This is not conducive for temporary teams to leverage of initial social resources in order to improve the proactive collaborative behaviors. Therefore, this paper draws upon social network perspective to explore how a temporary team’s collaboration history network influences proactive collaborative behaviors from views of individual network position and team network structure in three theoretical models. Specifically, at the individual level, this paper first examines the cognitive and emotional approaches through which individual collaboration history network centrality impacts individual proactive collaborative behavior, as well as the contingency effect of leader behaviors (model 1). Further at the team level, this study investigates the influences (model 2) and mechanisms (model 3) of the interaction between team collaboration history network structure (i.e., centralization and density) and contextual factors (task and team member characteristics) on team proactive collaborative behaviors. This study makes four primary theoretical contributions. First, the existing literature of the temporary team has focused on the emergence states and behaviors that can improve team performance. This study is one of the few research efforts to introduce individuals’ existent connections at the formation stage of a temporary team when studying team effectiveness, offering a new perspective for the development of temporary team research. Secondly, this paper further discusses the important effects, influencing mechanisms and boundary conditions of the temporary team’s collaboration history network, which expands the theoretical explorations in the field of collaboration history network. In addition, previous research on collaboration history has mainly concentrated on its quantity. This paper enriches the measurement of collaboration history by incorporating a network perspective including individual network position and team network structure, which more accurately captures the essential attributes of collaboration history and advances research methodologies. Finally, this paper integrates both individual and team levels to provide a comprehensive framework for understanding how a temporary team’s collaboration history network can affect members’ proactive collaborative behaviors, thereby enriching the research level of temporary team literature. This study also has some practical implications. First, we highlight the important role of past collaborative experiences in shaping members’ proactive collaborative behaviors in a temporary team. Thus, managers should recognize that collaborations among temporary team members are not “one-shot deals” and the collaboration history network should be paid attention to before teaming up. An appropriate collaboration history network together with a “collaboration-friendly” social context can facilitate and amplify positive collaborative connections in more temporary teams. Besides, organizations are recommended to boost individuals’ proactive collaborative behaviors by carefully arranging their positions within a temporary team’s collaboration history network. Additionally, teams’ proactive collaborative behaviors can be promoted by adopting different collaboration history network structures in various situations. In sum, this paper reveals a new perspective on the research of temporary teams’ collaboration, clarifies the mechanisms and boundary conditions of collaboration history network on proactive collaborative behavior, and provides insights for enterprises to promote collaboration through strategic formation of temporary teams. References | Related Articles | Metrics

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The antecedents and multilevel mechanisms of awe in leaders: An exploration based on intrapersonal and interpersonal perspectives BAI Yang, TENG Xiaofei 2025, 33 (5):  797-812.  doi: 10.3724/SP.J.1042.2025.0797 Abstract ( 174 )   PDF (647KB) ( 258 )   Peer Review Comments Awe, a deeply ingrained emotional state in Chinese culture, is conceptualized in Confucian philosophy as respect for destiny, virtuous figures, and moral doctrines. It transcends fear, embodying reverence for moral order and alignment with ethical principles. Historically, awe has guided leaders, particularly those in positions of power, by restraining their actions and ensuring decisions align with moral and ethical standards. Such reverence fosters fairness, humility, and accountability, ultimately enhancing leadership effectiveness and collective well-being. Despite its widespread exploration in psychology, the application of awe in management studies remains limited. Existing organizational research primarily focuses on employees’ experiences of awe, neglecting the antecedents and consequences of leader awe. Furthermore, the lack of attention to theoretical mechanisms and contextual factors has hindered the development of a comprehensive framework for understanding its unique organizational impacts. To address these gaps, this paper aims to propose a model that investigates the antecedents and outcomes of leader awe in organizational contexts. Drawing on Social Functional Accounts of Emotion and Emotions as Social Information (EASI) theory, this research proposes a multi-level approach, examining the triggers of leadership awe, its intrapersonal effects on leaders’ behaviors, and its interpersonal impacts on team dynamics. By employing a robust, interconnected research design, our proposed model not only seeks to identify the sources and effects of leadership awe but also delves into the psychological and social processes through which awe operates. The proposal includes three interconnected studies, each addressing different dimensions of leader awe. In Study 1, we aim to explore the antecedents of leader awe in organizational contexts. Building on social psychology research, this study wants to identify specific organizational factors (e.g., values and culture), interpersonal factors (e.g., interactions with mentors or subordinates), individual factors (e.g., personal virtues or self-awareness), and job characteristics (e.g., task complexity or significance) that trigger awe in leaders. By systematically categorizing these antecedents, the findings of this study will offer insights into the sources and nature of leadership awe, paving the way for a nuanced understanding of how awe emerges in professional settings. Study 2 aims to explore the effects of leader awe on leaders’ behaviors and outcomes. Drawing on the Social Functional Accounts of Emotion, this study proposes that leader awe can motivate a desire for self-enhancement. This motivation drives leaders to engage more in knowledge-sharing behaviors with employees, which, in turn, helps them gain trust and pursue higher power and positions. However, awe may also trigger a tendency toward self-deprecation. Feelings of self-doubt and inferiority may cause leaders to perceive their status as threatened, leading them to reduce the empowerment of followers in order to avoid potential losses and protect their superior social status and authority. Study 3 aims to examine how followers perceive and interpret leader awe, and how this influences their proactive behaviors. Using the Emotions as Social Information (EASI) theory, the study proposes that, on one hand, leader awe is seen by subordinates as a positive emotion, which spreads through emotional contagion and motivates them to self-improve, actively acquire knowledge, and integrate into the organization. On the other hand, leader awe can also evoke feelings of inadequacy, making followers feel helpless or less capable, which may lead to fear and reluctance, ultimately reducing their engagement in proactive behaviors. In sum, the findings from the aforementioned three studies will make several significant theoretical contributions. First, they will expand the scope of awe research from employees to leaders, addressing a notable gap in the literature. Second, by integrating the Social Functional Accounts of Emotion and the EASI framework, they will provide a comprehensive theoretical model that elucidates the cross-level mechanisms of leader awe, encompassing both intrapersonal and interpersonal perspectives. Third, they will identify the contextual factors that amplify the positive effects of leader awe, offering nuanced insights into its situational applications. On a practical level, these findings will offer actionable guidance for cultivating leadership awe in organizations. By highlighting how awe can be effectively triggered, they will equip managers with strategies to foster awe-inspiring environments. Additionally, the findings will underscore the importance of balanced awe management, helping leaders harness its benefits to enhance organizational effectiveness while mitigating potential downsides. References | Related Articles | Metrics

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“Do right things” and “do things right”: The influence of digital entrepreneurial team deep-level cultural diversity on social entrepreneurial resource orchestration XU Zuhui, ZUO Mingyue, ZHOU Yan, LIU Zhiyang 2025, 33 (5):  813-829.  doi: 10.3724/SP.J.1042.2025.0813 Abstract ( 103 )   PDF (791KB) ( 107 )   Peer Review Comments Digital technology provides an opportunity to improve the efficiency of social entrepreneurial resource, so that the composition of digital entrepreneurial team is more open, but the manifestation of digital entrepreneurial team deep-level cultural diversity and the influence mechanism on the process of social entrepreneurial resource orchestration have not been systematically discussed and verified. The specific research contents of this paper include: the unique connotation and key dimensions of digital entrepreneurial team deep-level cultural diversity are explored in the Chinese context; based on the attention-based view, the paper explores the influence mechanism of digital entrepreneurial team deep-level cultural diversity on the social entrepreneurial resource structuring from the two aspects of the attention allocation object and the linkage of multiple situational factors; in view of legitimacy perspective, this paper explores the evolutionary mechanism of digital entrepreneurial team deep-level cultural diversity on social entrepreneurial resource bundling from the two dimensions of bundling mode and time; on account of digital value creation perspective, this paper discusses the dynamic evolution process of digital entrepreneurial team deep-level cultural diversity to leverage social entrepreneurial resource from the two aspects of core and supporting entities. The theoretical construction of this paper mainly includes the following aspects: First, this paper identifies and refines the deep-level cultural diversity dimension of digital entrepreneurial team and the process of social entrepreneurial resource development, and enrich the theoretical framework of social entrepreneurial resource development research at the level of interaction between entrepreneurial team and digital technology. The current research on the process of social entrepreneurial resource development mainly explores resource mobilization strategies like resource bricolage and resource optimization. The starting point is that resource bricolage and resource optimization are considered to be very effective ways to break through the dilemma of resource development. However, in the context of the digital economy, entrepreneurial team members with different cultural backgrounds, social identities, and knowledge and experience have helped the development of social entrepreneurial resources. This paper extends the research on the social entrepreneurial resource development process to the level of interaction between entrepreneurial team and digital technology. Based on theoretical perspectives such as resource orchestration, attention-based view, legitimacy, and digital value creation, this paper constructs a theoretical framework for the influence of deep-level cultural diversity of digital entrepreneurial team on the process of social entrepreneurial resource orchestration, making more richer picture of social entrepreneurial resource orchestration at the level of interaction between entrepreneurial team and digital technology. Second, this paper explores the key constructs and operational indicators that explain entrepreneurial behaviors such as deep-level cultural diversity of digital entrepreneurial team and social entrepreneurial resource orchestration in the context of the digital economy, enriching the micro-knowledge base of entrepreneurial team heterogeneity for entrepreneurial resource management research. Although some studies have pointed out that the research on the relationship between entrepreneurial team heterogeneity and entrepreneurial resource is mainly based on theoretical perspectives such as information and decision making theory, social categorization theory, legitimacy theory, and signaling theory, the research on surface-level cultural heterogeneity such as gender, race, and nationality have the double-edged sword effect on entrepreneurial cognition and resource. This paper comprehensively considers the deep-level cultural diversity of digital entrepreneurial team and resource orchestration behavior of the social entrepreneurial enterprise in the context of digital economy. By systematically combing the relevant results of entrepreneurial team cultural heterogeneity and entrepreneurial resource, this paper further refines key concepts, develops relevant measurement indicators, and uses a combination of quantitative and qualitative research methods to analyze and test the mechanism of entrepreneurial behavior. On the one hand, it helps to make up for the shortcomings of existing research on the applicability of social entrepreneurial resource, especially in the digital economy context; on the other hand, it enriches the existing theoretical research on the relationship between entrepreneurial team heterogeneity and entrepreneurial resource. Third, this paper integrates the perspectives of resource orchestration and digital social entrepreneurship theory to deepen the internal mechanism and boundary condition of resource orchestration theory in the context of digital social entrepreneurship. The existing research field of resource orchestration theory is mainly based on commercial entrepreneurship in the context of the digital economy, and explores how entrepreneur-level factors, entrepreneurial firm-level factors, and multi-agent factors affect the resource orchestration process of the entrepreneurial enterprise. The current research on resource orchestration process is mainly based on the single entity of the entrepreneurial enterprise, which cannot interpret the dynamic process of multi-entities of resource orchestration. It is necessary to further explore the unique characteristics of the resource orchestration process of the social entrepreneurial enterprise, such as lack of legitimacy and dual value conflicts. This paper focuses on the application of resource orchestration theory, takes into account the characteristics of digital technology such as openness, and divides social entrepreneurial resource orchestration into three stages: resource construction, resource bundling and resource leveraging. Combining the attention-based view, legitimacy and digital value creation theory perspectives, this paper explores the internal mechanism, evolution mechanism and dynamic evolution process between the core entity like deep-level cultural diversity of digital entrepreneurial team and supporting entities such as government departments, digital users, universities and research institutions, investment institutions and entrepreneurial service agencies in the process of social entrepreneurial resource orchestration, providing new theoretical insight for exploring the digital social entrepreneurial context and boundary conditions of resource orchestration. References | Related Articles | Metrics

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User deviant behavior in sharing economy services: Identification of dimensions, formation mechanism, and optimization measures HOU Tingting, PAN Ling, LI Pulin 2025, 33 (5):  830-842.  doi: 10.3724/SP.J.1042.2025.0830 Abstract ( 72 )   PDF (648KB) ( 104 )   Peer Review Comments The core of the sharing economy lies in emphasizing the right of use instead of the right of ownership. This not only enhances the efficiency of resource allocation but also alleviates the psychological burden of users. However, to some extent, this alleviation of the psychological burden also prompts users to adopt a more relaxed attitude when engaging in deviant behaviors. Deviant behaviors, like users’ exclusive possession, occupation, and even destruction of goods in sharing- economy services, have emerged as practical challenges that hamper the healthy and sustainable development of the sharing economy. These behaviors not only go against the original intention of the sharing economy but also severely impede its long-term development. Nevertheless, the theoretical findings of existing research are still inadequate to account for the formation and management of this phenomenon. In view of the realistic predicament in the development of the sharing economy, this paper explores the deviant behavior of sharing-economy users from the perspective of social exchange theory. This study aims to explore, within the context of the sharing economy, the common deviant behaviors present in sharing-economy services, the formation mechanisms of these deviant behaviors, and the actions to be taken to regulate them. The research focuses on the following three aspects: (1) Uncovering the specific dimensions of such behavior and developing an operational measurement instrument; (2) Determining the perceived benefits, perceived risks, and personal characteristics that affect users’ deviant behavior, and revealing the formation mechanism of such behavior; (3) Identifying industry regulations and government supervision measures, exploring the influence of external intervention measures on the decision-making process of deviant behavior, and optimizing the management strategy. This research will demonstrate the following theoretical contributions. Firstly, the study is dedicated to enriching and deepening the connotation of research on user behavior in the sharing economy field. By categorizing the dimensions of deviant behavior and explaining its formation mechanism, it further enhances the understanding of users’ behavior in the sharing economy. Secondly, based on the social exchange theory and closely integrating the unique characteristics of the sharing economy services, the research deeply analyzes the delicate balance mechanisms between long-term risks and long-term benefits, as well as short-term risks and immediate benefits. Thus, it innovatively expands the social exchange theory in the spatio-temporal dimension, opening up new perspectives for the spatio-temporal research of this theory. In this study, full consideration is given to the influence of personal trait factors on deviant behavior. It is proposed that individual difference factors such as moral awareness, privacy and security awareness, risk preference, and conformist tendency have a direct impact on deviant behaviors. Therefore, the study contributes to enriching and deepening the research on user behavior in the sharing economy, promotes the development of sharing economy management theory, and in particular, expands new theoretical knowledge in the area of deviant behavior. Finally, the research constructs the influence mechanism of external intervention measures on the decision-making process of deviant behavior, providing in-depth theoretical and empirical support for how to correct deviant behavior through external intervention measures. Moreover, by deeply exploring how external intervention measures for deviant behavior regulate the trade-off mechanism between benefits and risks, it further expands the social exchange theory. By conducting an empirical exploration from three aspects: the dimensional classification of deviant behavior, its formation mechanism, and optimization measures, this work will contribute to understanding the dilemmas encountered in the development of the sharing economy, explain the internal mechanism of users’ deviant behavior in the sharing economy at the theoretical level, and provide practical solutions. As a result, it will enrich the dimensions of social exchange theory and promote theoretical innovation regarding deviant behavior in the sharing economy. References | Related Articles | Metrics

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A three-level meta-analysis of gender differences in spatial navigation ability XUE Xiaoran, CUI Wei, ZHANG Li 2025, 33 (5):  843-862.  doi: 10.3724/SP.J.1042.2025.0843 Abstract ( 114 )   PDF (1515KB) ( 152 )   Peer Review Comments Spatial navigation refers to an individual's ability to update his or her position and orientation in space, learn the layout of new locations, and plan and follow routes to reach a destination. This ability is one of the fundamental abilities essential for the survival of both humans and animals. Gender is a significant factor contributing to individual differences in spatial navigation ability. Although numerous studies have explored gender differences in spatial navigation, findings regarding the existence and extent of these differences remain inconsistent. In these studies, gender often interacts with various factors, such as study design, collectively influencing spatial navigation ability. Therefore, it is essential to systematically investigate whether significant differences exist between men and women in spatial navigation ability and to analyze how moderating factors shape the relationship between gender and spatial navigation performance. The present study integrated 173 original papers involving 372 independent effect sizes and 26,604 subjects between 2007 and 2023 through a three-level meta-analysis to clarify gender differences in spatial navigation ability and their potential moderating variables. The results indicate that males outperform females in spatial navigation ability under most conditions and that this gender difference is significantly moderated by age, mode of representation, time constraints, task environment, test scenario, and assistive equipment. Specifically, age was a significant moderating variable: males significantly outperformed females in spatial navigation between the ages of 4 and 65 years, whereas there were no significant differences in infancy (0~4 years) and late adulthood (65 years and older). Representational modality in task design also played a role, with smaller gender differences in egocentric representational tasks and larger differences in allocentric representational tasks. Gender differences were more significant in time-constrained tasks and less so when there were no time constraints. Task environment and test conditions also significantly affected results, with smaller gender differences in indoor environments only, real-scene tests, or conditions using paper-and-pencil instruments and no assistive devices, and more significant differences in dual indoor-outdoor test conditions or conditions using assistive devices. In addition, the study found that geographic region did not influence gender differences in spatial navigation ability, as participants from various continents consistently exhibited significant gender differences. On the one hand, this may be due to the uneven focus on different regions in previous research, resulting in an imbalanced distribution of participants. On the other hand, economic conditions and living environments may serve as more proximal factors influencing gender differences, potentially moderating these differences by providing varying resources and challenges. Furthermore, gender differences in spatial navigation ability remained consistent across different task types and measurement metrics, indicating the reliability of these assessments. However, in real-life situations, spatial environmental cues are considerably more complex and multifaceted than what simplified tasks in laboratory settings can fully capture. Therefore, future research should continue to explore evaluation methods that are more closely aligned with real-world conditions. This study examined gender differences in spatial navigation ability and its moderators through a three-level meta-analysis. The findings not only confirmed the phenomenon of male superiority in spatial navigation ability but also identified several key variables that moderate these gender differences. Future research should involve more diverse and representative population samples and employ task designs and measurement methods that closely reflect real-world environments to further explore the relationship between gender and spatial navigation ability. Moreover, in practical terms, educators should prioritize the development of students' spatial navigation skills, particularly through targeted teaching and hands-on activities aimed at enhancing women's confidence and ability in handling navigation tasks. These efforts will not only contribute to narrowing the gender gap but also improve students' ability to tackle spatial challenges in real-world contexts, ultimately promoting educational equity and social progress. References | Related Articles | Metrics

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Comparison of models for letter position encoding and their explanations of experimental effects LI Huangxia, CHEN Xinwei, YAO Panpan 2025, 33 (5):  863-886.  doi: 10.3724/SP.J.1042.2025.0863 Abstract ( 134 )   PDF (2031KB) ( 179 )   Peer Review Comments This article compares and analyzes six classic letter position encoding models, exploring the role of letter position in visual word recognition and the underlying cognitive mechanisms. The models discussed include the Overlap Model, the Open Bigrams Model, the Sequential Encoding Regulated by Inputs to Oscillations within Letter Units (the SERIOL Model), the Spatial-coding Model, the Bayesian Reader, and the Positional Ordering of N-Grams (the PONG). Each model is grounded on a distinct cognitive theory, offering unique perspectives on how letter positions are encoded and simulating various effects observed in word recognition. A common feature of these models is the claim that letter position plays a crucial role in word recognition. All models effectively account for several experimental effects, such as letter transposition effects and the effects of letter repetition, insertion, and deletion. Nonetheless, significant differences emerge in these models’ theoretical frameworks and conceptualizations of letter position encoding. The Overlap Model and the Bayesian Reader suggest that letter position encoding is highly susceptible to noise. The Overlap Model tolerates position shifts through an overlapping encoding mechanism, while the Bayesian Reader interprets position adjustment through a probabilistic framework, dynamically adjusting based on context to fit various cognitive scenarios. In contrast, the SERIOL Model encodes letter position via temporal activation patterns and multi-level structures (e.g., retinal layer, feature layer, letter layer), emphasizing the sequential and temporal characteristics of letter positions. The Spatial Encoding Model employs spatial phase coding and a two-dimensional coordinate system to process letter positions, enhancing encoding precision through external letter banks and word length modules. The Open Bigrams Model proposes a flexible encoding mechanism, focusing on the relative positions of adjacent letter pairs rather than strict letter order, thus offering a moderately flexible approach. The PONG introduces a theory of N-grams position encoding, positing that the position of N-grams is more critical than individual letter positions. Consequently, these models differ in their explanations of certain experimental effects of letter transposition. The Open Bigrams Model suggests that transposed nonwords overlap more with base words in terms of letter pairs, thereby triggering a stronger transposition effect. The Overlap Model posits that letter representations are distributed across sequential positions. Thus transposed nonwords, having more overlap with base words’ position distribution, are recognized more quickly than substituted nonwords. The Bayesian Reader, calculates the probability of each letter’s position and views transposed letters as having a smaller edit distance from the target word, thus enhancing the match score. The SERIOL Model incorporates the Open Bigrams framework and argues that the transposition conditions activate more matching letter pairs than the substitute conditions, further strengthening the transposition effect. The Spatial Encoding Model emphasizes phase encoding of letter positions, suggesting that transposed letters preserve more stable relative phase relationships, thus facilitating better word matching. Meanwhile, the PONG activates matching N-grams and contends that transposed nonwords engage more appropriate N-grams with similar hemispheric lateralization to the target word, resulting in better recognition compared to substituted nonwords. Additionally, each model offers unique insights into specific phenomena. The PONG Model, for example, explains the flanker effect using N-grams, a phenomenon has not been addressed by other models. Both the SERIOL and PONG Models account for optimal fixation locations through hemispheric lateralization. The Open Bigrams Model explains the influence of reading direction by positing that letter detectors are based on the relative position of eye fixations along the horizontal line. Based on the analysis and discussions of the above models, there are several key directions for the further development of letter position encoding models. First, there is a need to expand the scope of models to account for factors like prediction, word frequency, and transposition across word boundaries, which remain insufficiently explored. Second, integrating word recognition models with eye movement control models could improve ecological validity in understanding letter position encoding in reading. Third, research into Chinese character position processing should be further explored. Fourth, more attention should be paid to cross-language differences and the differential experimental effects observed across languages. Finally, with advances in EEG and neuroimaging technologies, integrating diverse sources of data would optimize existing models and address theoretical gaps. References | Related Articles | Metrics