1

期刊：Human Resource Management Journal

期刊介绍：ABS 4*

论文题目：How green human resource management affects employee voluntary workplace green behaviour: An integrated model

作者：袁艺玮（本院教师）; Ren, S.; Tang, G.; Ji, H.; Cooke, F. L.; & Wang, Z.

摘要：

Green human resource management (GHRM), a set of HRM practices targeted at environmental goals, has been proposed as the key to achieving organisational sustainable development. However, the mechanisms through which GHRM influences employee green behaviour are not yet well understood. Drawing on conservation of resources theory, this study presents an integrated model revealing the mixed effects of GHRM on employees' voluntary workplace green behaviour (VWGB). Path analysis based on two studies undertaken in China largely supported our hypotheses. Specifically, GHRM was found to positively influence employees' VWGB through environmental commitment, while simultaneously decreasing their VWGB through emotional exhaustion. Meanwhile, supervisory support for environmental behaviour mitigated the impact of GHRM on emotional exhaustion as well as the relationship between GHRM and employee VWGB via emotional exhaustion. This study contributes to the GHRM literature in particular and organisational environmental management literature in general.

2

期刊：IEEE Transactions on Knowledge and Data Engineering

期刊介绍：CCF A类

论文题目：Heterogeneous Latent Topic Discovery for Semantic Text Mining.

作者：Yawen Li（李雅文）；Di Jiang；Rongzhong Lian；Xueyang Wu；Conghui Tan；Yi Xu；Zhiyang Su.摘要：

In order to mine latent semantics from text data, word embedding and topic modeling are two major methodologies in the industry. From a pragmatic perspective, each of these two lines of semantic models faces increasing challenges from real-life applications. Topic modeling view documents as bags of words and is unable to capture the sequential relationship between words. On the other hand, word embedding models the co-occurrence of neighboring words but lacks the global view of the document. Therefore, they can only discover homogenous semantics from a single aspect. However, modern text mining tasks typically require a panoramic view of the latent semantics. Hence, discovering heterogeneous semantics (e.g., heterogeneous types of latent topics) is critical for the performance of these tasks, and it is necessary to design a model that meets this demand. Furthermore, with the arrival of the big data era and the increasing awareness of data privacy, it is necessary to study mining heterogeneous semantics with high efficiency while avoiding compromising data privacy. In this work, we develop a novel method called Heterogeneous Latent Topic Discovery (HLTD) which seamlessly integrates topic modeling with word embedding to discover heterogeneous latent topics. By coupling parameter-server architecture with new private sampling algorithms, HLTD can be efficiently trained to protect underlying data privacy. We evaluate HLTD through a wide range of qualitative and quantitative metrics in the industry. Extensive experiments demonstrate the superiority of HLTD over the state-of-the-arts.

3

期刊：Information Processing & Management

期刊介绍：中国科学院一区

论文题目：Coarse-grained privileged learning for classification

作者：付赛际（本院教师）; Xiaoxiao wang, Yingjie Tian, Tianyi Dong, Jingjing Tang, Jicai Li

摘要：

Privileged information, a form of prior knowledge, can significantly enhance traditional machine learning performance through a novel paradigm known as learning using privileged information (LUPI). Although effective, current studies on LUPI require a distinct piece of privileged information per input, and these fine-grained priors are difficult to collect in practice. To this end, this paper proposes a brand new problem of learning with class-wise privileged information, where instances within the same class share identical privileged information. As far as we know, this problem has not yet been explored. We build a support vector machine with coarse-grained class-wise priors (CGSVM+) and put forward a novel and reliable augmenting strategy to solve it. In addition, two datasets are collected from nature reserves in Xinjiang, China, along with their class-wise privileged information annotated by professionals. Extensive experiments demonstrate the effectiveness of CGSVM+, with the best average accuracy of 80.16% (94.70%) and the best average F-score of 79.87% (94.57%) on the plant (animal) datasets.

4

期刊：Pattern Recognition

期刊介绍：中国科学院一区

论文题目：Skeleton estimation of directed acyclic graphs using partial least squares from correlated data

作者：王晓康（本院教师）；Shan Lu； Rui Zhou；Huiwen Wang

摘要：Directed acyclic graphs (DAGs) are directed graphical models that are well known for discovering causal relationships between variables in a high-dimensional setting. When the DAG is not identifiable due to the lack of interventional data, the skeleton can be estimated using observational data, which is formed by removing the direction of the edges in a DAG. In real data analyses, variables are often highly correlated due to some form of clustered sampling, and ignoring this correlation will inflate the standard errors of the parameter estimates in the regression-based DAG structure learning framework. In this work, we propose a two-stage DAG skeleton estimation approach for highly correlated data. First, we propose a novel neighborhood selection method based on sparse partial least squares (PLS) regression, and a cluster -weighted adaptive penalty is imposed on the PLS weight vectors to exploit the local information. In the second stage, the DAG skeleton is estimated by evaluating a set of conditional independence hypotheses. Simulation studies are presented to demonstrate the effectiveness of the proposed method. The algorithm is also tested on publicly available datasets, and we show that our algorithm obtains higher sensitivity with comparable false discovery rates for high-dimensional data under different network structures.(c) 2023 Elsevier Ltd. All rights reserved.

5

期刊：Engineering Applications of Artificial Intelligence

期刊介绍：中国科学院一区

论文题目：Detection of outlying patterns from sparse and irregularly sampled electronic

health records data

作者：王晓康（本院教师）；Chengjian Li；Hao Shi；Congshan Wu；Chao Liu

摘要：Within the intensive care unit (ICU), vital signs such as arterial blood pressure (ABP) collected from electronic health records (EHRs) are typically recorded at different and uneven sampling frequencies and are often infrequently measured due to the nature of the medical treatment. Furthermore, from a temporal trajectory perspective, EHR data are likely to be corrupted by outlying patterns that deviate from normal samples in terms of the curves' magnitude and shape. In this work, we propose a two-stage outlier detection approach for sparse and irregularly sampled (SiS) temporal data using functional data analysis (FDA) tools. In the first stage, an outlier identification measure is defined by a max-min statistic and a clean subset that contains nonoutliers. In the second stage, a multiple hypothesis testing problem is formulated based on the asymptotic distribution of the proposed measure. The simulation-based framework shows that the proposed method is robust to different types of shape and magnitude outliers. The detection results are more accurate than the widely used functional depth methods, especially in extremely sparse settings where the proportion of the observed data points over the entire time series is approximately 10%. Extensive experiments are also conducted on the real-world MIMIC-II dataset, which demonstrate that the method effectively detects clinically meaningful outlying patterns.

6

期刊：European Journal of Operational Research

期刊介绍：ABS 4；中国科学院一区

论文题目：Robust regression under the general framework of bounded loss functions

作者：付赛际（本院教师）; Yingjie Tian; Long Tang

摘要：Conventional regression methods often fail when encountering noise. The application of a bounded loss function is an effective means to enhance regressor robustness. However, most bounded loss functions exist in Ramp-style forms, losing some inherent properties of the original function due to hard truncation. Besides, there is currently no unified framework on how to design bounded loss functions. In response to the above two issues, this paper proposes a general framework that can smoothly and adaptively bound any non-negative function. It can not only degenerate to the original function, but also inherit its elegant properties, including symmetry, differentiability and smoothness. Under this framework, a robust regressor called bounded least squares support vector regression (BLSSVR) is proposed to mitigate the effects of noise and outliers by limiting the maximum loss. With appropriate parameters, the bounded least squares loss grows faster than its unbounded form in the initial stage, which facilitates BLSSVR to assign larger weights to non-outlier points. Meanwhile, the Nesterov accelerated gradient (NAG) algorithm is employed to optimize BLSSVR. Extensive experiments on synthetic and real-world datasets profoundly demonstrate the superiority of BLSSVR over benchmark methods.

7

期刊：European Journal of Operational Research

期刊介绍：ABS4；中国科学院一区

论文题目：Responsive strategic oscillation for solving the disjunctively constrained knapsack problem（北京运筹学会优秀青年论文）

作者：魏泽群（本院教师），Jin-kao Hao，Jintong Ren, Fred Glover

摘要：This paper presents a responsive strategic oscillation algorithm for the NP-hard disjunctively constrained knapsack problem, which has a variety of applications. The algorithm uses an effective feasible local search to find high-quality local optimal solutions and employs a strategic oscillation search with a responsive filtering strategy to seek still better solutions by searching along the boundary of feasible and infeasible regions. The algorithm additionally relies on a frequency-based perturbation to escape deep local optimal traps. Extensive evaluations on two sets of 6340 benchmark instances show that the algorithm is able to discover 39 new lower bounds and match all the remaining best-known results. Additional experiments are performed on 21 real-world instances of a daily photograph scheduling problem. The critical components of the algorithm are experimentally assessed.(c) 2023 Elsevier B.V. All rights reserved.

8

期刊：IEEE Transactions on Engineering Management

期刊介绍：ABS 3，ESI全球Top 1%高被引论文(Economics & Business领域)

论文题目：How can government promote technology diffusion in manufacturing paradigm shift? Evidence from China

作者：许冠南（本院教师）, Yuan Zhou, and Huanyong Ji

摘要：Traditional technology diffusion literature focuses on the diffusion of technologies within the extant manufacturing paradigm. By contrast, few studies have explored the determinants and mechanisms of technology diffusion when moving across manufacturing paradigms. In this article, therefore, we aim to explore the intrinsic and institutional factors, as well as the impact mechanism on technology diffusion in the context of manufacturing paradigm shift. Specifically, this article investigates the role of the government in this scenario. A firm-level survey is conducted to investigate the National Programme "Made in China 2025" and its first demonstration city Quanzhou. The data comes from multiple sources, including questionnaires, official statistics data, and patent databases. Logistical regression is used to analyze 236 valid observations. Results reveal that besides the intrinsic factors including the characteristics of general purpose technology (GPT) and economic expectation, GPT-oriented service platforms also have significant impacts on technology diffusion in a manufacturing paradigm shift. In addition, government interventions, especially indirect ones, have significant moderating effects on this influential mechanism. This study provides insight into how government can promote technology diffusion in a manufacturing paradigm shift. These results will be of interest to policy makers, industrialists, and academics.

9

期刊：南开管理评论

期刊介绍：国家自然科学基金委管理科学部认定的A级重要期刊

论文题目：非国有股东参与治理能提高国有企业融资行为的“市场理性”吗？

作者：何瑛（本院教师），杨琳，文雯

摘要：国企“降杠杆”实现资本结构优化调整是国有企业改革的重要组成部分，混合所有制改革能否优化国企资本结构决策的关键在于能否加速实际资本结构向目标资本结构回归。本文基于正式制度与非正式制度研究视角，手工搜集整理2007-2018年中国沪深A股上市国企前十大股东多维治理的独特数据集，从股权治理、高层治理、网络治理三个维度构建非国有股东治理机制理论模型，系统考察非国有股东治理机制和资本结构动态调整的内在关联。研究结论表明：非国有股东参与治理能提高混改国企资本结构调整速度，其基于正式制度的股权治理和高层治理发挥着更为基础的作用。作用机理方面，基于“经理人观”与“政治观”，非国有股东参与治理主要通过“完善高管激励机制”提升混改国企资本结构调整速度，“预算软约束”虽然也是国企资本结构调整速度慢的诱因，但非国有股东对此暂未起到显著的修正作用。影响因素方面，非国有股东治理机制对资本结构调整速度的影响随行业竞争和经济区位不同而有所差异，应积极贯彻国务院“分类混改”总体方针提高改革效率，也应聚焦“双向混改”关注国有资本入股对非国有企业融资决策的影响。此外，非国有股东治理机制还能显著降低资本结构偏离度，在优化国有企业资本结构的同时降低股权融资成本。本研究结论丰富了混改政策背景下非国有股东治理机制与资本结构动态调整领域的文献，有利于引导混改国企在实践中完善治理机制，更好地发挥非国有股东治理作用。

10

期刊：政治学研究

期刊介绍：中国人文社会科学期刊AMI综合评价报告顶级期刊

论文题目：国外监管理论研究：制度主义及其评析

作者：李乐（本院教师），周志忍

摘要：制度主义是监管理论中的重要流派或监管研究中重要的理论视角。国内已有研究尚未系统解读监管制度主义理论。本文致力于国际相关文献的梳理综述，内容包括监管制度主义的起源和发展、监管制度主义的流派和主张，目的是给国内相关研究提供理论视角和方法上的启示和借鉴。监管制度主义与新制度主义关联密切，基于研究问题的差异性，本文将监管制度主义流派分为三类：一是关注监管病理及制度设计，探讨如何设计制度和制度间关系来避免监管过程存在的监管病理；二是关注监管发展和制度内部力量，聚焦思考组织内力量如何驱动与影响监管发展；三是关注监管网络与监管空间，聚焦探讨监管网络中策略的使用、协调机制的建立及监管空间中各种力量对监管发展的影响。监管的制度主义理论对当下中国的监管实践具有一定的启发意义。

11

期刊：中国软科学

期刊介绍：国家自然科学基金委管理科学部认定的A级重要期刊

论文题目：人才链支撑创新链产业链的融合发展路径:逻辑理路、中美比较以及政策启示

作者：赵晨（本院教师），林晨，高中华

摘要：人才是全面建设社会主义现代化国家的基础性战略性支撑，应深入探讨人才链支撑创新链产业链的逻辑理路。首先，构建人才链与创新链产业链融合的理论逻辑。然后，对比中美制度，提炼建设我国人才链的政策启示。最后，提出“人才—创新”闭环、“人才—产业”闭环及推动“创新—产业”螺旋三类人才链支撑创新链产业链的理论过程；从政策进程、政策基调、政策推进归纳中美在三类过程的差异；总结政策借鉴并结合我国国情和体制优势，提出激发人才链效能的中国方案。

12

期刊：中国管理科学

期刊介绍：国家自然科学基金委管理科学部认定的A级重要期刊

论文题目：快速交通网络化影响下的城市空间关联与经济溢出效应研究——以航空及高铁网络为例

作者：王雨飞（本院教师）；徐海东；王光辉

摘要：航空和高铁作为两种最为主要的交通方式相互补充，共同构成了现代化快速交通网络，通过改变城市间的空间关联关系，促进了经济格局的调整和区域经济的溢出。本文以柯布-道格拉斯生产函数理论为基础，构建了快速交通网络化影响下的城市经济溢出机理框架及其分析模型，分析了快速交通网络影响下城市空间关联对其经济溢出的影响，并基于中国地级及以上城市的面板数据，利用G2SLS工具变量估计等方法，实证检验了航空和高铁等快速交通网络影响下的城市空间关联与经济溢出效应的关系，并进一步开展了模型的情境分析。结果显示：航空网络影响下的城市空间关联具有明显的跨越性和等级性，高铁网络影响下的城市空间关联则带有鲜明的地缘属性和邻接属性；航空和高铁网络下城市之间的空间关联越广泛，对其经济溢出的贡献越明显，航空网络中心的过度集中导致城市空间关联的接近中心度与经济溢出之间存在负相关关系，但在高铁网络中这种关系并不稳定，城市在航空和高铁网络中的枢纽地位及对网络的控制能力对经济发展有着重要意义。

13

期刊：中国土地科学

期刊介绍：公共管理领域权威期刊

论文题目：空间异质性视角下公共服务设施对大城市住房租金的影响——基于一种机器学习改进方法的实证研究

作者：申犁帆（本院教师），龙雨，田莉，郝钰泽

摘要：研究目的：以北京市作为实证案例，基于多源数据探究各类公共服务设施对大城市租金水平的影响机制。研究方法：结合空间权重性关联和阈值效应，而“医疗设施”和“公交车站”等公服设施变量对住房租金水平的影响较为有限。（3）此外，改进后的XGBSH模型也影响城市租赁住房市场的可持续发展。

14

期刊：中国行政管理

期刊介绍：国家自然科学基金委管理科学部认定的A级重要期刊

论文题目：地方党政干部选拔的注意力分配与多元化晋升路径研究——基于X市干部选拔实践的模糊集定性比较分析

作者：赵晨（本院教师），周锦来，龚诗阳

摘要：对地方党政干部的有效选拔任用是推进中国式现代化的有力支撑，已有文献尚未从学理层面回答如何基于统一的干部评价标准选拔出多元化的地方党政干部。本研究以X市的干部选拔实践为研究对象，从注意力分配视角剖析了党政领导干部的多元化晋升路径及其解释逻辑。整合模糊集定性比较分析与非结构性访谈，分析该市2019-2022年1825名市管干部的考核与晋升的数据发现：地方党政干部“德、能、勤、绩、廉”五方面表现及年功组合形成的组态，构成不同单位（行政单位与事业单位）中不同职务（单位正职与单位副职）干部的多元化晋升路径。注意力分配是这一过程的主要解释逻辑，即通过“注意力聚焦-注意力情境化-注意力结构化配置”三个阶段，实现从形成考核焦点到塑造晋升路径的干部选选拔任用过程。本研究从注意力分配视角揭示了领导干部多元化晋升路径及其解释逻辑，对新时代干部选拔任用工作具有实践启示。

15

期刊：管理评论

期刊介绍：国家自然科学基金委管理科学部认定的A级重要期刊

论文题目：数字化转型能够提升企业投资效率吗？——来自制造业上市公司的证据

作者：严子淳（本院教师）；王伟楠；王凯；张志伟

摘要：数字化转型日益成为企业高质量发展的必然选择，那么企业的数字化转型对其投资效率会有怎样的影响呢？本文以2011—2020年A股制造业上市公司为样本，通过机器学习、文献计量及爬虫技术等方式对数字化转型进行刻画，实证检验了数字化转型对企业投资效率的影响。研究发现:数字化转型能够显著改善企业的投资效率，并主要体现为降低过度投资。进一步分析发现，数字化转型对投资效率的提高通过降低代理成本及优化资源配置两条路径实现。本文还发现，数字化转型对投资效率的影响在企业产权性质不同时存在差异，且数字化转型的不同细分维度对投资效率的影响不同。本文的研究结论既可以丰富数字化转型及投资效率的相关文献，也能够为企业在数字化转型过程中的重要投资战略提供决策依据。

16

期刊：管理评论

期刊介绍：国家自然科学基金委管理科学部认定的A类重要期刊

论文题目：工业机器人应用对城市空气污染治理的影响研究

作者：李宏兵（本院教师）;郑庆彪;李震（本院教师）;孙丽棠

摘要：本文基于国际机器人联合会(IFR)的工业机器人应用数据和中国地级及以上城市层面PM2.5排放浓度数据，利用2SLS、空间计量模型等多种计量方法，实证检验了工业机器人应用对城市空气污染治理的影响。研究发现，工业机器人应用显著降低了中国城市空气污染水平，这一效应在金融发展程度较高、财政支持较低、信息基础设施建设水平较高以及智慧城市试点城市中表现更加明显，且在地理区位特征上呈现出显著的异质性。同时，上述影响主要通过城市产业结构升级和科技水平提升的机制实现。基于SAR与SDM模型的空间溢出效应分析，也发现城市工业机器人应用的减污效应具有双向空间溢出效应，因此空气污染的地理相关性使其减污效应被低估。

17

期刊：管理工程学报

期刊介绍：国家自然科学基金委管理科学部认定的A类重要期刊

论文题目：内源性和外源性时间压力对员工创新行为的影响

作者：张生太（本院教师）张梦桃，仇泸毅（本院教师），何伟怡

摘要：本文以34家企业的60名主管和366名员工为研究对象,讨论内源性和外源性时间压力对员工创新行为的影响,并探讨心理距离的中介作用和敌意归因偏差的调节作用。研究结果表明:内源性时间压力正向影响员工创新行为,外源性时间压力负向影响员工创新行为;心理距离中介了时间压力和员工创新行为之间的关系;敌意归因偏差调节了外源性时间压力与心理距离之间的关系,并调节了外源性时间压力通过心理距离影响员工创新行为的间接效应,但对内源性时间压力和心理距离以及员工创新行为之间关系的调节效应不显著。本文从调节员工时间压力、重视员工与组织间心理距离和有效利用敌意归因偏差三方面提出相应的管理建议。

18

期刊：新闻与传播研究

期刊介绍：中国人文社会科学期刊AMI综合评价报告顶级期刊

论文题目：“怜悯之毒”如何攻克“谣言之毒”

作者：熊炎（本院教师）

摘要：为了探索外生怜悯情感对辟谣支持决断的影响及其调节因素，该研究进行了两次支持流感疫苗接种的线上辟谣实验。实验结果既支持外生怜悯情感在总体上会增强谣言支持度较高的且认知需求中等的人们对包含谣言受害者描述的辟谣信息的支持意愿，也支持外生怜悯情感会通过增强人们对谣言受害者的怜悯间接增强辟谣支持意愿，还支持外生怜悯情感会通过增强认知需求中等的人们的内生怜悯情感间接提高谣言支持度，但这一负面效应会被外生怜悯情感的正面效应抵消或被谣言受害者描述消减。该研究既有助于丰富辟谣信息构成要素、评估-倾向框架理论与外生怜悯说服效应，也有助于推动人们(更好地)利用外生怜悯情感来增强辟谣支持意愿。