Quantitative behavioral research depends on clear construct specification and psychometrically sound measurement tools, especially when emerging constructs are examined in context-sensitive organizational settings. This study developed and validated a scale of excellence-driven behavior among faculty and staff in Chinese public universities. A mixed-methods measurement-development design was used. First, the construct domain was derived from Excellence-Driven theory and contextualized within public universities. Second, qualitative evidence from semi-structured interviews and open-ended questionnaires using the Critical Incident Technique was used to generate and refine behavioral indicators. Third, the resulting instrument was examined through item analysis, exploratory factor analysis, confirmatory factor analysis, and reliability and validity assessment. The findings supported a two-dimensional structure consisting of Excellence-Driven Cognition and Learning and Excellence-Driven Display. The scale showed acceptable evidence of internal structure, internal consistency, convergent validity, discriminant validity between the two dimensions, and preliminary criterion-related validity. These results provide initial psychometric support for the use of the scale in future research on excellence-driven behavior among faculty and staff in Chinese public universities, while further evidence regarding temporal stability, measurement invariance, and broader empirical distinction from adjacent constructs is still needed.

Art education plays a vital role in preserving cultural heritage and promoting sustainable development. However, growing curricular complexity and abstraction present challenges to student satisfaction, a key metric in educational sustainability. This study investigates how perceived content complexity and modality structure affect student satisfaction in art-related programs, drawing on Construal Level Theory (CLT) to explain the psychological mechanisms involved. Based on aggregated data from 73,368 students across 1524 academic programs in China, the results indicate that higher content complexity significantly reduces satisfaction. Moreover, a lower auditory-visual (A/V) ratio-indicating reduced emphasis on visual input-also decreases satisfaction but moderates the negative effect of content complexity. The findings suggest that cognitive-perceptual mechanisms play a central role in shaping students' evaluative responses and offer implications for improving curriculum design and institutional strategies in art education.

This study explores how employee–AI collaboration can promote employees’ proactive behavior by reducing their workload, and examines the mediating role of workload and the moderating effect of AI literacy. Based on a survey of employees across multiple industries, the study finds that employee–AI collaboration significantly reduces employees’ workload, which in turn encourages more proactive behavior. In this process, workload serves as a central mediating mechanism, as it helps alleviate task pressure and frees up cognitive resources, enabling employees to take on additional responsibilities and put forward innovative suggestions. Furthermore, with increasing levels of employee–AI collaboration, employees with higher AI literacy tend to experience greater workload relief, while those with lower literacy demonstrate a stronger and more consistent proactive behavioral response. These findings offer theoretical insight into employee–AI interaction and practical implications for enhancing initiative and innovation through effective AI integration.

The expansion of higher education and economic development is widely believed to improve gender employment equity by enhancing women's access to education and skills. However, recent studies suggest these benefits may not extend universally, particularly regarding subjective well-being, where women often face new challenges amid educational and economic transitions. This study examines how education scale and regional economic scale moderate gender employment equity, offering a novel perspective on the intersection of higher education, labour markets, and gender disparities. Utilizing publicly available survey data from the China Higher Education Student Information Network (CHSI), comprising 49,615 undergraduate graduates from Chinese universities, the analysis reveals significant variations in job satisfaction across programmes with differing gender compositions. In high-female-proportion fields, educational expansion correlates negatively with job satisfaction, while in low-female-proportion fields, the correlation is positive. Furthermore, high-female-proportion fields show higher job satisfaction in economically underdeveloped cities, whereas low-female-proportion fields perform better in economically developed cities. These findings highlight the unintended consequences of educational and economic policies for gender equity, emphasizing the need for targeted, gender-sensitive interventions that consider programme composition, disciplinary characteristics, and regional economic contexts to advance equity in higher education and labour markets.

With the widespread application of AI technology, the skills and abilities required by employees in their work are undergoing fundamental changes, redefining the roles of employees. This research aims to explore the effect of job skill demands under AI embeddedness on well-being in organizations and job performance. Based on conservation of resources theory, this research randomly selected 479 employees from 8 companies in China using a time-lag method as samples, and conducted statistical analysis with ordinary least squares (OLS). This research found that, job skill demands under AI embeddedness will both increase employees’ competency needs, promoting their well-being in organizations and job performance and decrease employees’ job embeddedness, inhibiting their well-being in organizations and job performance. Meanwhile, technological anxiety moderated the impact of job skill demands under AI embeddedness on job embeddedness.

Within the sustainable development framework, organizations are tasked with creating strategies that ensure the enduring provision of value through human capital for the future. Our study emphasizes employee development and training, adopting a people-centric approach aligned with sustainability principles. By leveraging techniques for the identification of Characteristics of Individual Strengths (CIS), Agent Evaluation, and composite decision making, we introduce a novel approach to formulating personalized employee training strategies. This approach is structured around three pivotal steps: identifying CIS, assessing employee roles within the organization based on CIS, and analyzing training strategies. Demonstrated through illustrative examples, our method validates its applicability in real-world settings. This research provides organizations with an innovative pathway for effectively fostering employee skills and securing a steady influx of high-quality, diverse talent.

Embedded within the sustainable development framework, our research leverages proceduralized grounded theory to refine and universalize supervisory governance capabilities, thereby aiming to assess the theoretical saturation of the resultant model and to devise a comprehensive, sustainability-inclusive index of supervisory board governance competence. Focusing on five publicly traded Chinese companies, the research employs a tripartite coding process integral to grounded theory methodologies. By methodically refining case studies, it identifies sustainability-oriented governance capacity indicators. Data are conceptualized and compartmentalized via open coding, then divided into five primary clusters via axial coding, resulting in sustainability-focused governance capacity indicators for supervisory boards. Using selective coding strategies, the study uncovers forty-two competency indicators pertinent to sustainable corporate governance, organized into three domains across eight sustainability-related dimensions. These include individual characteristics, sustainability value judgment, experiential wisdom, collaborative communication for sustainable practices, resource integration, general employment prerequisites, professional application in sustainability, and sustainable business acumen. The findings enhance supervisory board member selection and performance assessment processes, promoting sustainable corporate governance. They also clarify supervisory roles in sustainability, offering a holistic view of supervisory board internal governance mechanisms. By maintaining the objectivity of these indicators, the study advances the field.

为识别高校学者学术创业影响因素之间的逻辑关系以及关键影响因素,本研究首先以高校学者为研究对象,从学者个体、高校组织、宏观环境及政策三个层面构建了高校学者学术创业影响因素体系.其次,运用DEMATEL计算各影响因素的影响度、被影响度、中心度及原因度值,揭示各影响因素的重要程度;借助ISM模型构建高校学者学术创业影响因素的多级递阶解释结构模型.最后,结合DEMATEL+ISM分析结果,识别了高校学者学术创业关键影响因素.研究发现,影响高校学者学术创业的因素可以划分为 7 个层次,共 11 个关键影响因素,分别为学者的学术水平与成就、学术影响力、技术背景、创业经历、人员优势、产学合作性网络、组织中的领导行为、组织文化、高校的社会资本、资源配置支持、行业形势.本研究不仅在一定程度上丰富了现有学术创业的相关理论体系,而且可以为高校学者培养自身创业素质、能力以及高校组织设计科学的学者学术创业激励体系提供理论依据.

监事会在现代企业制度中具有重要的作用,但目前在监事会组建和监事会治理能力分析方面尚缺少基于监事会成员个体特色、监事能力与监事会整体能力协调的有效分析方法.本文综合运用扎根理论、个体优势特征识别方法、整体能力优化整合分析方法,构建了监事会成员选聘方法及实施流程.首先,采用程序化扎根理论对 5家典型上市公司的监事会多年的运行过程进行分析、提炼和归纳,构建了监事会所需履职能力指标体系;然后,面向一般股份制企业,运用个体优势特征识别技术,实现对每一位监事候选成员履职优势结构的识别,进一步运用个体代理评价解决候选人之间的功能重复问题;最后,从监事会整体协调的角度构建"个体—群体"有效匹配的衡量方法,实现监事会整体进行优化组建的决策支持;形成比较完整的监事成员选聘与监事会组建的方法.论文还通过算例展示了本文所提出方法运行过程及结果.本文提出的监事会成员选聘方法既有助于实现监事会内部的分工与协调,有助于实现监事会整体履职能力的最大化,又易于得到监事会候选人的认可,完善了监事会成员选聘和管理的理论与方法.

员工竞优行为作为一种有效的优势干预和自我价值实现途径,是应该被组织倡导的行为.本文将竞优行为置于工作情境中,运用扎根理论的方法,基于认知理论构建了员工竞优行为的影响因素模型.研究结果表明:员工通过对外部匹配环境(个人-组织匹配)的感知和自身的调控系统来强化对竞优活动的认知,进而影响竞优行为,其中个体对竞优的认知因素包括对工作价值的认知、对竞优自主动机的认知和对竞优自我效能感的认知;竞优行为的形成和强化是由认知因素直接驱动的,在此过程中,外部支持性的环境(竞优氛围与文化和工作特征)起到调节作用.研究结论揭示了员工竞优行为的影响因素和作用机理,为组织激励员工竞优行为提供了可参考的依据.

事物的动态发展变化催生了对动态评价方法的需求.为解决动态评价中跨阶段动态可比性和对新增阶段的适应性等动态评价长效性需求问题,提出动态评价长效机制的构建原理.通过对数据标准化方式和多种评价方法的特征分析,在分析动态评价过程各环节技术的动态有效性基础上,从数据采集、数据标准化、评价方法的选择与使用等方面,基于线性加权模式下的竞优评析方法,构建了一种面向动态评价的"客观民主式"动态评价长效机制.最后,通过一个实例说明本研究在实际应用上的有效性.面向动态评价的长效评价机制为解决动态评价有效性问题提供了思路,可作为综合评价理论方法的一种有益补充.

行业结构环境分析是发现和掌握行业运行规律与发展状况的必经之路,也是在企业战略管理中的重要组成部分,其结果直接影响着企业战略决策与实施.针对企业战略管理的新价值理念,本文在协同学与竞优理论的基础上,通过对行业内群体结构特性与企业行为的重新考察,建立了行业结构环境分析的一种新方法即序参量分析方法与其应用范例.本文的研究结果,如行业内多层结构、企业群组定位及分布特性、行业基本发展模式、标杆与协同伙伴、企业群组或群组内企业构成与绩效之间的关系等都可为实现符合现代产业发展环境的企业战略管理提供方向性辅助与技术支持.

针对企业治理中的独立董事治理优势评价问题,提出了一种考虑层次结构的独立董事治理多优势评价方法.该方法以竞优理论为基础,运用其中的个体优势判别方法确定层次结构下各独立董事治理的优势权重;依据确定的权重结果,逐层构建代理评价和民主评价模型,并计算不同层次的比较优势和团体优势;然后采用聚类分析方法提炼共性优势模式,获得该模式下的优势分布和结构;进一步通过求解模型确定独立董事治理的多项优势.此外,以A公司独立董事治理评价为例,证明了该方法的有效性和优越性.

为发展我国集成电路企业,通过选择标杆企业进行有效激励,同时考虑该类企业具有高技术、重创新的产业特征,采用平衡积分卡技术构建综合评价指标集,以竞优思想为指引,制定分层次结构的评价模型,并选取26家典型上市企业进行应用.研究发现:(1)利用平衡计分卡技术设计的评价指标集能够有效地对集成电路企业进行综合评价;(2)制定的评价模型能够有效识别各企业发展优势特征,并识别隐形冠军企业及其发展优势;(3)在尊重各参评个体的差异和优势特征基础上选取优秀企业学习标杆,能使企业标杆管理更为科学.依据研究结论,基于各企业发展特征并结合国内集成电路产业所面临的现实困境,从政府角度如何通过组建企业联盟、政策激励等方面推动我国集成电路企业发展给出管理建议.

现有的竞优评析研究主要以线性加权、数据包络分析等线性模型为基础,缺少普适于非线性效用函数的竞优评析研究,限制了竞优评析理论的适用范围与发展空间.本文以TOPSIS效用函数为例,采用PSO优化算法解决非线性个体优势特征识别问题,实现竞优评析理论的拓展.最后,以人力资源管理中的人员业绩评价问题为例给出具体算例,对比验证了所提拓展方法的正确性与有效性;同时,结合计算结果所具有的"极端价值主张"现象,从评价方法的"后效"引导作用的角度,提出了评价方法的"引导功效"概念及其评判标准,供选择评价方法时参考.

针对竞优评价问题,文章提出了一种多方评价主体与客体共同参与的竞优评价方法.首先,从尽可能体现评价客体价值的角度得到其成员共识的价值参数结构;其次,获取多类别评价主体的意见,并依据各类别评价主体内成员意见的一致性对不同类别评价主体的意见进行集中,得到评价主体的最终意见;然后,依据竞优思想对主客体的信息进行综合,获得最终的评价值;最后,通过一个算例对该方法的有效性和可行性进行了验证.

通过文献查阅、问卷调查及专家访谈方式,构建出涵盖20个因素的影响因素体系.同时对影响员工绿色行为的各个因素进行系统化、层次化研究,通过Fuzzy-DEMATEL方法对于影响因素体系内的关键影响因素进行识别,并通过ISM方法对于员工绿色行为各影响因素进行系统分析,建立层次结构模型.研究表明,个体特质和组织绿色文化对员工绿色行为存在最深层的影响.其中,个体特质对于员工绿色行为存在根源影响,组织绿色文化对员工绿色行为存在深层影响.通过上述结论为企业鼓励、支持和引导员工践行绿色行为提供管理对策和建议.

基于信用评级行业的关键作用与改革争议,本文根据信用评级行业的双边市场特征,建立由信用评级机构、债券发行方、债券投资者组成的平台竞争模型,设定了发行方付费且单评级、投资者付费且单评级、发行方付费且双评级的三种信用评级制度,对信用评级机构的竞争行为与社会福利进行对比分析.研究发现:目前主流的发行方付费且单评级制度下,信用评级机构的评级费用和利润水平均为最高,社会总福利水平则居中.在单评级制度下推广投资者付费模式,可以在信用评级机构受冲击最小的情况下,适当提高社会总福利水平,不失为当前我国信用评级制度改革的最佳选择.单评级制度下,信用评级机构可以通过增加差异化程度来提高评级费用和利润水平,但在双评级制度下则面临全新竞争决策的挑战.

基于创新联合体结构特征,构建多寡头三阶段研发博弈模型分析纵向技术溢出无协同决策、横纵技术溢出无协同决策、横纵技术溢出有协同决策三种合作研发策略.结果 表明,提高纵向技术溢出程度,是创新联合体改善中小企业研发绩效,以及领军企业均衡利润的基础手段.增加横纵双向技术溢出,能够进一步提高中小企业研发绩效和领军企业利润水平.对于需求价格弹性较大行业,横纵技术溢出有协同决策研发策略则可以提高创新联合体的整体利润.

本文针对企业战略管理的新价值理念,以竞优思想为指导,构建了基于现代企业管理的有力工具——标杆学习的企业战略行为调整的一种新方法与其应用范例.从选择标杆、向标杆学习到确立调整方案,在该方法的全过程中采用了个体优势特征识别、个体及民主代理评价等竞优评析理论,因此,所得到的标杆就是竞优标杆,而且所产生的调整效果就是企业战略行为的竞优调整效果.本文研究过程中提出的理论、方法和对中国钢铁行业内一个上市公司的应用研究都具有公正性、客观性、易被接受性,并且所得到的分析及评价结果都可为企业战略的顺利运行和实现其最终目标提供方向性辅助与技术支持.