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Articles 3181 - 3210 of 8723
Full-Text Articles in Entire DC Network
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
We propose a novel deep example-based image colourization method called dense encoding pyramid network. In our study, we define the colourization as a multinomial classification problem. Given a greyscale image and a reference image, the proposed network leverages large-scale data and then predicts colours by analysing the colour distribution of the reference image. We design the network as a pyramid structure in order to exploit the inherent multi-scale, pyramidal hierarchy of colour representations. Between two adjacent levels, we propose a hierarchical decoder-encoder filter to pass the colour distributions from the lower level to higher level in order to take both …
Image Enhanced Event Detection In News Articles, Meihan Tong, Shuai Wang, Yixin Cao, Bin Xu, Juaizi Li, Lei Hou, Tat-Seng Chua
Image Enhanced Event Detection In News Articles, Meihan Tong, Shuai Wang, Yixin Cao, Bin Xu, Juaizi Li, Lei Hou, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Event detection is a crucial and challenging sub-task of event extraction, which suffers from a severe ambiguity issue of trigger words. Existing works mainly focus on using textual context information, while there naturally exist many images accompanied by news articles that are yet to be explored. We believe that images not only reflect the core events of the text, but are also helpful for the disambiguation of trigger words. In this paper, we first contribute an image dataset supplement to ED benchmarks (i.e., ACE2005) for training and evaluation. We then propose a novel Dual Recurrent Multimodal Model, DRMM, to conduct …
Bounding Regret In Empirical Games, Steven Jecmen, Arunesh Sinha, Zun Li, Long Tran-Thanh
Bounding Regret In Empirical Games, Steven Jecmen, Arunesh Sinha, Zun Li, Long Tran-Thanh
Research Collection School Of Computing and Information Systems
Empirical game-theoretic analysis refers to a set of models and techniques for solving large-scale games. However, there is a lack of a quantitative guarantee about the quality of output approximate Nash equilibria (NE). A natural quantitative guarantee for such an approximate NE is the regret in the game (i.e. the best deviation gain). We formulate this deviation gain computation as a multi-armed bandit problem, with a new optimization goal unlike those studied in prior work. We propose an efficient algorithm Super-Arm UCB (SAUCB) for the problem and a number of variants. We present sample complexity results as well as extensive …
Deepdualmapper: A Gated Fusion Network For Automatic Map Extraction Using Aerial Images And Trajectories, Hao Wu, Hanyuan Zhang, Xinyu Zhang, Weiwei Sun, Baihua Zheng, Yuning Jiang
Deepdualmapper: A Gated Fusion Network For Automatic Map Extraction Using Aerial Images And Trajectories, Hao Wu, Hanyuan Zhang, Xinyu Zhang, Weiwei Sun, Baihua Zheng, Yuning Jiang
Research Collection School Of Computing and Information Systems
Automatic map extraction is of great importance to urban computing and location-based services. Aerial image and GPS trajectory data refer to two different data sources that could be leveraged to generate the map, although they carry different types of information. Most previous works on data fusion between aerial images and data from auxiliary sensors do not fully utilize the information of both modalities and hence suffer from the issue of information loss. We propose a deep convolutional neural network called DeepDualMapper which fuses the aerial image and trajectory data in a more seamless manner to extract the digital map. We …
The Paradoxical Consequences Of Choice: Often Good For The Individual, Perhaps Less So For Society?, Shilpa Madan, Kevin Nanakdewa, Krishna Savani, Hazel Rose Markus
The Paradoxical Consequences Of Choice: Often Good For The Individual, Perhaps Less So For Society?, Shilpa Madan, Kevin Nanakdewa, Krishna Savani, Hazel Rose Markus
Research Collection Lee Kong Chian School Of Business
The proliferation of products and services, together with the rise of social media, affords people the opportunity to make more choices than ever before. However, the requirement to think in terms of choice, or to use a choice mind-set, may have powerful but unexamined consequences for judgment and decision making, both for the chooser and for others. A choice mind-set leads people to engage in cognitive processes of discrimination and separation, to emphasize personal freedom and independent agency, and to focus on themselves rather than others. Reviewing research from social psychology, legal studies, health and nutrition, and consumer behavior, we …
On Mandatory Criminal Sentences, Legislative Interpretation, And The Prospective Application Of The Law: A View From Singapore, Kwan Ho Lau
Research Collection Yong Pung How School Of Law
Cana court find that a criminal sentence is mandatory under the penal legislation butchoose, exceptionally, to apply that finding only to future cases? This raisesan interesting question on the prospective application of a correctconstruction of legislation, requiring consideration of difficult issuessurrounding not just the temporal application of the law but also theprotection of the interests belonging to all citizenry, including convictedpersons. Recent decisions in Singapore and elsewhere provide an opening for amore detailed inquiry to be undertaken.
Corrigendum To "On Time-Varying Factor Models: Estimation And Testing" [J. Econometrics 198 (2017) 84-101], Liangjun Su, Xia Wang
Corrigendum To "On Time-Varying Factor Models: Estimation And Testing" [J. Econometrics 198 (2017) 84-101], Liangjun Su, Xia Wang
Research Collection School Of Economics
We note that Su and Wang (2017, On Time-varying Factor Models: Estimation and Testing, Journal of Econometrics 198, 84-101) ignore the bias terms when estimating the time-varying factor models. In this note, we correct the theoretical results on the estimation of time-varying factor models. The asymptotic results for testing the correct specification of time invariant factor loadings are not affected.
The Relative Price Of Capital And Economic Structure, Roberto Samaniego, Juliana Yu Sun
The Relative Price Of Capital And Economic Structure, Roberto Samaniego, Juliana Yu Sun
Research Collection School Of Economics
Are trends in the price of capital technological in nature? First, we find that trends in the relative price of capital vary significantly across countries. We then show that a multi-industry growth model, calibrated to match differences in economic structure around the world and productivity growth rates across industries, accounts for this variation – mainly due to variation in the composition of capital. The finding indicates that the rate of change in the relative price of capital can be interpreted as investment-specific technical change – the extent to which productivity growth is relatively more rapid in the capital-producing sector. The …
Libertarianism Without Self-Ownership, Chandran Kukathas
Libertarianism Without Self-Ownership, Chandran Kukathas
Research Collection School of Social Sciences
Libertarianism is a political philosophy whose defenders have set its foundations in the principle of self-ownership. But self-ownership supplies an uncertain basis for such a theory as it is prone to a number of serious difficulties, some of which have been addressed by libertarians but none of which can ultimately be overcome. For libertarianism to be a plausible way of looking at the world, it must look elsewhere for its basic principles. In particular, it needs to rethink the way it understands property and its foundations.
Stochastically Robust Personalized Ranking For Lsh Recommendation Retrieval, Dung D. Le, Hady W. Lauw
Stochastically Robust Personalized Ranking For Lsh Recommendation Retrieval, Dung D. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Locality Sensitive Hashing (LSH) has become one of the most commonly used approximate nearest neighbor search techniques to avoid the prohibitive cost of scanning through all data points. For recommender systems, LSH achieves efficient recommendation retrieval by encoding user and item vectors into binary hash codes, reducing the cost of exhaustively examining all the item vectors to identify the topk items. However, conventional matrix factorization models may suffer from performance degeneration caused by randomly-drawn LSH hash functions, directly affecting the ultimate quality of the recommendations. In this paper, we propose a framework named SRPR, which factors in the stochasticity of …
Mcdpc: Multi‐Center Density Peak Clustering, Yizhang Wang, Di Wang, Xiaofeng Zhang, Wei Pang, Chunyan Miao, Ah-Hwee Tan, You Zhou
Mcdpc: Multi‐Center Density Peak Clustering, Yizhang Wang, Di Wang, Xiaofeng Zhang, Wei Pang, Chunyan Miao, Ah-Hwee Tan, You Zhou
Research Collection School Of Computing and Information Systems
Density peak clustering (DPC) is a recently developed density-based clustering algorithm that achieves competitive performance in a non-iterative manner. DPC is capable of effectively handling clusters with single density peak (single center), i.e., based on DPC’s hypothesis, one and only one data point is chosen as the center of any cluster. However, DPC may fail to identify clusters with multiple density peaks (multi-centers) and may not be able to identify natural clusters whose centers have relatively lower local density. To address these limitations, we propose a novel clustering algorithm based on a hierarchical approach, named multi-center density peak clustering (McDPC). …
How Institutions Enhance Mindfulness: Interactions Between External Regulators And Front-Line Operators Around Safety Rules, Ravi S. Kudesia, Ting Lang, Jochen Reb
How Institutions Enhance Mindfulness: Interactions Between External Regulators And Front-Line Operators Around Safety Rules, Ravi S. Kudesia, Ting Lang, Jochen Reb
Research Collection Lee Kong Chian School Of Business
How is it that some organizations can maintain nearly error-free performance, despite trying conditions? Within research on such high-reliability organizations, mindful organizing has been offered as a key explanation. It entails interaction patterns among front-line operators that keep them attentive to potential failures—and relies on them having the expertise and autonomy to address any such failures. In this study, we extend the mindful organizing literature, which emphasizes local interactions among operators, by considering the broader institutional context in which it occurs. Through interview, observational, and archival data of a high-reliability explosive demolitions firm in China, we find that external regulators …
How Smart Is Institutional Trading?, Jingi Ha, Jianfeng Hu
How Smart Is Institutional Trading?, Jingi Ha, Jianfeng Hu
Research Collection Lee Kong Chian School Of Business
We estimate daily aggregate order flow at the stock level from all institutional investors as well as for hedge funds and the other institutions separately. We achieve this by extrapolating the relation between quarterly institutional ownership in 13F filings, aggregate market order imbalance in TAQ, and a representative group of institutional investors’ transaction data. We find that the estimated institutional order imbalance has positive price impact in the short term, which reverses in the long term. The “smart” order flow from hedge funds generates greater and more persistent price impact than the “dumb” order flow from all the other institutions. …
Is It All In The Eye Of The Beholder? The Importance Of Situation Construal For Situational Judgment Test Performance, Jan-Philipp Freudenstein, Philipp Schaepers, Lena Roemer, Patrick Mussel, Stefan Krumm
Is It All In The Eye Of The Beholder? The Importance Of Situation Construal For Situational Judgment Test Performance, Jan-Philipp Freudenstein, Philipp Schaepers, Lena Roemer, Patrick Mussel, Stefan Krumm
Research Collection Lee Kong Chian School Of Business
Recent research challenges the importance of situation descriptions for situational judgment test (SJT) performance. This study contributes to resolving the ongoing debate on whether SJTs are situational measures, by incorporating findings on person x situation interactions into SJT research. Specifically, across three studies (N-Total = 1,239), we first tested whether situation construal (i.e., the individual perception of situations in SJTs) predicts responses to SJT items. Second, we assessed whether the relevance of situation construal for SJT performance depends on test elements (i.e., situation descriptions and response options) and item features (i.e., description-dependent vs. description-independent SJT items). Lastly, we determined whether …
Deepbindiff: Learning Program-Wide Code Representations For Binary Diffing, Yue Duan, Xuezixiang Li, Jinghan Wang, Wang, Heng Yin
Deepbindiff: Learning Program-Wide Code Representations For Binary Diffing, Yue Duan, Xuezixiang Li, Jinghan Wang, Wang, Heng Yin
Research Collection School Of Computing and Information Systems
Binary diffing analysis quantitatively measures the differences between two given binaries and produces fine-grained basic block matching. It has been widely used to enable different kinds of critical security analysis. However, all existing program analysis and machine learning based techniques suffer from low accuracy, poor scalability, coarse granularity, or require extensive labeled training data to function. In this paper, we propose an unsupervised program-wide code representation learning technique to solve the problem. We rely on both the code semantic information and the program-wide control flow information to generate block embeddings. Furthermore, we propose a k-hop greedy matching algorithm to find …
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
We propose a novel deep example-based image colourization method called dense encoding pyramid network. In our study, we define the colourization as a multinomial classification problem. Given a greyscale image and a reference image, the proposed network leverages large-scale data and then predicts colours by analysing the colour distribution of the reference image. We design the network as a pyramid structure in order to exploit the inherent multi-scale, pyramidal hierarchy of colour representations. Between two adjacent levels, we propose a hierarchical decoder–encoder filter to pass the colour distributions from the lower level to higher level in order to take both …
Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network, Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua
Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network, Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Recognizing ingredients for a given dish image is at the core of automatic dietary assessment, attracting increasing attention from both industry and academia. Nevertheless, the task is challenging due to the difficulty of collecting and labeling sufficient training data. On one hand, there are hundred thousands of food ingredients in the world, ranging from the common to rare. Collecting training samples for all of the ingredient categories is difficult. On the other hand, as the ingredient appearances exhibit huge visual variance during the food preparation, it requires to collect the training samples under different cooking and cutting methods for robust …
Joint Learning Of Answer Selection And Answer Summary Generation In Community Question Answering, Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Joint Learning Of Answer Selection And Answer Summary Generation In Community Question Answering, Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Research Collection School Of Computing and Information Systems
Community question answering (CQA) gains increasing popularity in both academy and industry recently. However, the redundancy and lengthiness issues of crowdsourced answers limit the performance of answer selection and lead to reading difficulties and misunderstandings for community users. To solve these problems, we tackle the tasks of answer selection and answer summary generation in CQA with a novel joint learning model. Specifically, we design a question-driven pointer-generator network, which exploits the correlation information between question-Answer pairs to aid in attending the essential information when generating answer summaries. Meanwhile, we leverage the answer summaries to alleviate noise in original lengthy answers …
Automated Deprecated-Api Usage Update For Android Apps: How Far Are We?, Ferdian Thung, Stefanus Agus Haryono, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang
Automated Deprecated-Api Usage Update For Android Apps: How Far Are We?, Ferdian Thung, Stefanus Agus Haryono, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
As the Android API evolves, some API methods may be deprecated, to be eventually removed. App developers face the challenge of keeping their apps up-to-date, to ensure that the apps work in both older and newer Android versions. Currently, AppEvolve is the state-of-the-art approach to automate such updates, and it has been shown to be quite effective. Still, the number of experiments reported is moderate, involving only API usage updates in 41 usage locations. In this work, we replicate the evaluation of AppEvolve and assess whether its effectiveness is generalizable. Given the set of APIs on which AppEvolve has been …
Interpretable Rumor Detection In Microblogs By Attending To User Interactions, Ling Min Serena Khoo, Hai Leong Chieu, Zhong Qian, Jing Jiang
Interpretable Rumor Detection In Microblogs By Attending To User Interactions, Ling Min Serena Khoo, Hai Leong Chieu, Zhong Qian, Jing Jiang
Research Collection School Of Computing and Information Systems
We address rumor detection by learning to differentiate between the community’s response to real and fake claims in microblogs. Existing state-of-the-art models are based on tree models that model conversational trees. However, in social media, a user posting a reply might be replying to the entire thread rather than to a specific user. We propose a post-level attention model (PLAN) to model long distance interactions between tweets with the multi-head attention mechanism in a transformer network. We investigated variants of this model: (1) a structure aware self-attention model (StA-PLAN) that incorporates tree structure information in the transformer network, and (2) …
Are The Code Snippets What We Are Searching For? A Benchmark And An Empirical Study On Code Search With Natural-Language Queries, Shuhan Yan, Hang Yu, Yuting Chen, Beijun Shen
Are The Code Snippets What We Are Searching For? A Benchmark And An Empirical Study On Code Search With Natural-Language Queries, Shuhan Yan, Hang Yu, Yuting Chen, Beijun Shen
Research Collection School Of Computing and Information Systems
Code search methods, especially those that allow programmers to raise queries in a natural language, plays an important role in software development. It helps to improve programmers' productivity by returning sample code snippets from the Internet and/or source-code repositories for their natural-language queries. Meanwhile, there are many code search methods in the literature that support natural-language queries. Difficulties exist in recognizing the strengths and weaknesses of each method and choosing the right one for different usage scenarios, because (1) the implementations of those methods and the datasets for evaluating them are usually not publicly available, and (2) some methods leverage …
The Future Of Work Now: Medical Coding With Ai, Thomas H. Davenport, Steven M. Miller
The Future Of Work Now: Medical Coding With Ai, Thomas H. Davenport, Steven M. Miller
Research Collection School Of Computing and Information Systems
The coding of medical diagnosis and treatment has always been a challenging issue. Translating a patient’s complex symptoms, and a clinician’s efforts to address them, into a clear and unambiguous classification code was difficult even in simpler times. Now, however, hospitals and health insurance companies want very detailed information on what was wrong with a patient and the steps taken to treat them— for clinical record-keeping, for hospital operations review and planning, and perhaps most importantly, for financial reimbursement purposes.
Political Ideology Of The Board And Ceo Dismissal Following Financial Misconduct, Uisung Park, Warren Boeker, David Gomulya
Political Ideology Of The Board And Ceo Dismissal Following Financial Misconduct, Uisung Park, Warren Boeker, David Gomulya
Research Collection Lee Kong Chian School Of Business
Why do some boards refuse to take serious action against CEOs who have committed financial misconduct? Past work has directed attention to the antecedents of misconduct while largely overlooking this question. The relatively few studies to examine it have typically revolved around the capacity of boards to take action, or their relationships to their CEOs. This study instead examines how the beliefs and values held by board members can influence their actions following financial misconduct. Focusing on political ideology, we argue and find that politically conservative boards are more likely to respond by dismissing the CEO than are liberal boards. …
Privacy At Work: A Review And A Research Agenda For A Contested Terrain, Devasheesh P. Bhave, Laurel H. Teo, Reeshad S. Dalal
Privacy At Work: A Review And A Research Agenda For A Contested Terrain, Devasheesh P. Bhave, Laurel H. Teo, Reeshad S. Dalal
Research Collection Lee Kong Chian School Of Business
Privacy in the workplace is a pivotal concern for employees and employers. Employees expect to be in control of the personal information and access they provide to the organization. Employers, however, expect extensive information regarding their employees as well as extensive access to employees’ presence. The chasm between these two often competing expectations has been magnified by regulatory and technological trends. We begin the review by integrating viewpoints from multiple disciplines to disentangle definitions of privacy and to delineate the privacy contexts of information privacy and work environment privacy. We then identify the key stakeholders of privacy in the workplace …
Artificial Intelligence-Enhanced Decision Support For Informing Global Sustainable Development: A Human-Centric Ai-Thinking Approach, Meng-Leong How, Sin Mei Cheah, Yong-Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say
Artificial Intelligence-Enhanced Decision Support For Informing Global Sustainable Development: A Human-Centric Ai-Thinking Approach, Meng-Leong How, Sin Mei Cheah, Yong-Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say
CCX Research
Sustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was not easy for people who are not trained in computer science to use AI. The significance and novelty of this paper is that it shows how the use of AI can be democratized via a user-friendly human-centric probabilistic reasoning approach. Using this approach, analysts who are not computer scientists can also use AI to analyze sustainability-related EPI data. Further, this human-centric probabilistic …
Financial Vulnerability And The Reproduction Of Disadvantage In Economic Exchanges, Tianyu He, Rellie Derfler-Rozin, Marko Pitesa
Financial Vulnerability And The Reproduction Of Disadvantage In Economic Exchanges, Tianyu He, Rellie Derfler-Rozin, Marko Pitesa
Research Collection Lee Kong Chian School Of Business
Integrative value generation through negotiated business deals is a fundamental way in which organizations and economic systems attain economic benefits. It is also an important way in which individuals can improve their financial situation. We propose that individuals most in need of improving their financial standing, those in a financially vulnerable situation, are least likely to reap the benefits of integrative value generation. We theorize that financial vulnerability induces a more zero-sum construal of success, or a view that success for one person must come at another person’s success. A more zero-sum construal of success, in turn, hampers negotiators’ ability …
Performance Management: Quo Vadis?, Filip Lievens, Philipp Schapers, Christoph N. Herde
Performance Management: Quo Vadis?, Filip Lievens, Philipp Schapers, Christoph N. Herde
Research Collection Lee Kong Chian School Of Business
Traditionally performance management has been described as a powerful tool in Human Resource Management (HRM) because it has potentially a wide array of application possibilities for various HR topics. However, the reality in practice is different. Various surveys reported that more than 90 percent of the performance management systems are unsuccessful. Further studies have shown that up to 75% of staff feel that their organization’s performance management system does not help them to improve their performance and is largely a waste of time (e.g., Capelli & Tavis, 2016; Pulakos, 2009). Economic analyses of the return on investment (as compared to …
Information Externalities And Voluntary Disclosure: Evidence From A Major Customer’S Earnings Announcement, Young Jun Cho, Yongtae Kim, Yoonseok Zang
Information Externalities And Voluntary Disclosure: Evidence From A Major Customer’S Earnings Announcement, Young Jun Cho, Yongtae Kim, Yoonseok Zang
Research Collection School Of Accountancy
We examine the relation between information externalities along the supply chain and voluntary disclosure. Information transfers from a major customer's earnings announcement (EA) can substitute for its supplier's disclosure. Conversely, if the customer's EA increases uncertainties regarding the supplier's future prospects, it can increase the demand for disclosure. After controlling for information incorporated in supplier returns, we find that the supplier is more likely to issue earnings guidance after the customer's EA when the EA news deviates more from the market's expectation. The positive effect of the customer's news on earnings guidance is weaker when common investors, supply-chain analysts, or …
Memory And Resource Leak Defects And Their Repairs In Java Projects, Mohammadreza Ghanavati, Diego Costa, Janos Seboek, David Lo, Artur Andrzejak
Memory And Resource Leak Defects And Their Repairs In Java Projects, Mohammadreza Ghanavati, Diego Costa, Janos Seboek, David Lo, Artur Andrzejak
Research Collection School Of Computing and Information Systems
Despite huge software engineering efforts and programming language support, resource and memory leaks are still a troublesome issue, even in memory-managed languages such as Java. Understanding the properties of leak-inducing defects, how the leaks manifest, and how they are repaired is an essential prerequisite for designing better approaches for avoidance, diagnosis, and repair of leak-related bugs. We conduct a detailed empirical study on 452 issues from 10 large opensource Java projects. The study proposes taxonomies for the leak types, for the defects causing them, and for the repair actions. We investigate, under several aspects, the distributions within each taxonomy and …
Three Types Of Organizational Boundary Spanning: Predicting Csr Policy Extensiveness Among Global Consumer Products Companies, Alwyn Lim, Shawn Pope
Three Types Of Organizational Boundary Spanning: Predicting Csr Policy Extensiveness Among Global Consumer Products Companies, Alwyn Lim, Shawn Pope
Research Collection School of Social Sciences
As part of the rise of a worldwide corporate social responsibility (CSR) movement, companies have increasingly incorporated social and environmental concerns into their policies. This paper examines the extensiveness of these policies, proposing that an underappreciated contributor is the degree of organizational boundary spanning. The paper is novel in integrating multiple types of boundary spanning into a single empirical framework, including product, sub‐unit, and national boundary spanning. The paper adds complexity to the literature by theorizing that different types of boundary spanning associate with CSR policy extensiveness in different issue areas. The results show that product spanning associates with CSR …