Caring but sharing unintentionally: Lobbying for innovations and the leakage of knowledge

Mapping Intimacies ◽

10.31235/osf.io/mqcj8 ◽

2022 ◽

Author(s):

Michael Park

Keyword(s):

Machine Learning ◽

Instrumental Variable ◽

Federal Agencies ◽

Regulatory Change ◽

Mediation Analyses ◽

Regulatory Changes ◽

Knowledge Leakage ◽

Prior Literature ◽

The Relationship ◽

Unintended Outcome

When firms engage in lobbying, their intended outcome is a regulatory change that benefits them. However, prior literature suggests that there may also be an unintended outcome of lobbying—the leakage of knowledge to competitors. In this paper, I explore when the intended and the unintended outcomes are more likely by theorizing about the relationship between lobbying and innovation. I predict that innovations that are novel are more likely to benefit from the intended regulatory changes. However, innovations that use knowledge uniquely possessed by a few firms are more likely to be compromised by the leakage of knowledge that happens during lobbying. I use new data from 1999-2013 on public U.S. firms that engaged in lobbying to federal agencies, the regulatory changes made by federal agencies, and the 16,000 patents applied for by those firms. I employ unsupervised machine learning (Doc2Vec) to measure knowledge leakage and an instrumental variable 2SLS mediation analyses to test the theory. The results suggest that the intended regulatory changes that follow lobbying can benefit innovations by facilitating wider adoption. However, unique technological knowledge that only a few firms possess may be expropriated by competitors during the process of lobbying. Overall, this paper demonstrates that fundamental aspects of innovation— such as institutional change, knowledge transfer, and technology adoption—are closely related to lobbying, a form of nonmarket activity.

Download Full-text

Delay Prediction of Aircrafts Based on Health Monitoring Data

International Journal of Business Analytics and Intelligence ◽

10.21863/ijbai/2016.4.1.015 ◽

2016 ◽

Vol 4 (1) ◽

Cited By ~ 1

Author(s):

B. A. Dattaram ◽

N. Madhusudanan

Keyword(s):

Machine Learning ◽

Health Monitoring ◽

Monitoring Data ◽

Machine Learning Techniques ◽

Learning Techniques ◽

Flight Delay ◽

Delay Prediction ◽

The Relationship

Flight delay is a major issue faced by airline companies. Delay in the aircraft take off can lead to penalty and extra payment to airport authorities leading to revenue loss. The causes for delays can be weather, traffic queues or component issues. In this paper, we focus on the problem of delays due to component issues in the aircraft. In particular, this paper explores the analysis of aircraft delays based on health monitoring data from the aircraft. This paper analyzes and establishes the relationship between health monitoring data and the delay of the aircrafts using exploratory analytics, stochastic approaches and machine learning techniques.

Download Full-text

Information Technology Capability, Management Forecast Accuracy, and Analyst Forecast Revisions

Accounting Horizons ◽

10.2308/acch-52113 ◽

2018 ◽

Vol 32 (3) ◽

pp. 49-70 ◽

Cited By ~ 4

Author(s):

Feiqi Huang ◽

He Li ◽

Tawei Wang

Keyword(s):

Forecast Accuracy ◽

Analyst Forecast ◽

Management Forecasts ◽

Forecast Revisions ◽

It Capability ◽

Management Forecast ◽

Prior Literature ◽

Technology Capability ◽

Information Technology Capability ◽

The Relationship

SYNOPSISPrior literature has firmly established the relationship between IT capability and firm performance. In this paper, we extend the research in this field and investigate (1) whether IT capability contributes to management forecast accuracy, and (2) whether IT capability improves the informativeness of management forecasts and enhances the extent to which analysts incorporate management forecasts in their revisions. Using firms listed on InformationWeek 500 as our high IT capability group, we empirically demonstrate that firms with high IT capability are able to increase management forecast accuracy, and that analysts incorporate more information from management forecasts in their revisions if the firm has high IT capability.

Download Full-text

Mother Phubbing and Adolescent Cyberbullying: The Mediating Role of Perceived Mother Acceptance and the Moderating Role of Emotional Stability

Journal of Interpersonal Violence ◽

10.1177/0886260520983905 ◽

2020 ◽

pp. 088626052098390

Author(s):

Jiahui Qu ◽

Li Lei ◽

Xingchao Wang ◽

Xiaochun Xie ◽

Pengcheng Wang

Keyword(s):

High School Students ◽

Positive Association ◽

Emotional Stability ◽

School Students ◽

Mediation Analyses ◽

Mediating Role ◽

Indirect Path ◽

Underlying Mechanisms ◽

The Relationship

Previous studies have found some risk factors of cyberbullying. However, little is known about how mother phubbing may influence adolescent cyberbullying, and the mediating and moderating mechanisms underlying this relationship. “Phubbing,” which is a portmanteau of “phone” and “subbing,” refers to snubbing other people and focus on smartphones in social interactions. This study examined whether mother phubbing, which refers to being phubbed by one’s mother, would be positively related to adolescent cyberbullying, whether perceived mother acceptance would mediate the relationship between mother phubbing and adolescent cyberbullying, and whether emotional stability would moderate the pathways between mother phubbing and adolescent cyberbullying. The sample consisted of 4,213 Chinese senior high school students (mean age 16.41 years, SD = 0.77, 53% were female). Participants completed measurements regarding mother phubbing, cyberbullying, perceived mother acceptance, and emotional stability. The results indicated that mother phubbing was positively related to cyberbullying, which was mediated by perceived mother acceptance. Further, moderated mediation analyses showed that emotional stability moderated the direct path between mother phubbing and cyberbullying and the indirect path between mother phubbing and perceived mother acceptance. This study highlighted the harmful impact of mother phubbing on adolescents by showing a positive association between mother phubbing and adolescent cyberbullying, as well as the underlying mechanisms between mother phubbing and adolescent cyberbullying.

Download Full-text

Advances of ECG Sensors from Hardware, Software and Format Interoperability Perspectives

Electronics ◽

10.3390/electronics10020105 ◽

2021 ◽

Vol 10 (2) ◽

pp. 105

Author(s):

Khaleel Husain ◽

Mohd Soperi Mohd Zahid ◽

Shahab Ul Hassan ◽

Sumayyah Hasbullah ◽

Satria Mandala

Keyword(s):

Machine Learning ◽

Heart Attack ◽

Privacy Preservation ◽

Causes Of Death ◽

Clinical Settings ◽

Data Format ◽

Medical Institutions ◽

Comprehensive Survey ◽

Electrocardiogram Ecg ◽

The Relationship

It is well-known that cardiovascular disease is one of the major causes of death worldwide nowadays. Electrocardiogram (ECG) sensor is one of the tools commonly used by cardiologists to diagnose and detect signs of heart disease with their patients. Since fast, prompt and accurate interpretation and decision is important in saving the life of patients from sudden heart attack or cardiac arrest, many innovations have been made to ECG sensors. However, the use of traditional ECG sensors is still prevalent in the clinical settings of many medical institutions. This article provides a comprehensive survey on ECG sensors from hardware, software and data format interoperability perspectives. The hardware perspective outlines a general hardware architecture of an ECG sensor along with the description of its hardware components. The software perspective describes various techniques (denoising, machine learning, deep learning, and privacy preservation) and other computer paradigms used in the software development and deployment for ECG sensors. Finally, the format interoperability perspective offers a detailed taxonomy of current ECG formats and the relationship among these formats. The intention is to help researchers towards the development of modern ECG sensors that are suitable and approved for adoption in real clinical settings.

Download Full-text

The relationship between trust in AI and trustworthy machine learning technologies

Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency ◽

10.1145/3351095.3372834 ◽

2020 ◽

Cited By ~ 2

Author(s):

Ehsan Toreini ◽

Mhairi Aitken ◽

Kovila Coopamootoo ◽

Karen Elliott ◽

Carlos Gonzalez Zelaya ◽

...

Keyword(s):

Machine Learning ◽

Learning Technologies ◽

The Relationship

Download Full-text

Algorithmic and human prediction of success in human collaboration from visual features

Scientific Reports ◽

10.1038/s41598-021-81145-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Martin Saveski ◽

Edmond Awad ◽

Iyad Rahwan ◽

Manuel Cebrian

Keyword(s):

Machine Learning ◽

Visual Cues ◽

Success Factors ◽

Group Performance ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Adventure Game ◽

Group Success ◽

The Relationship ◽

Better Than

AbstractAs groups are increasingly taking over individual experts in many tasks, it is ever more important to understand the determinants of group success. In this paper, we study the patterns of group success in Escape The Room, a physical adventure game in which a group is tasked with escaping a maze by collectively solving a series of puzzles. We investigate (1) the characteristics of successful groups, and (2) how accurately humans and machines can spot them from a group photo. The relationship between these two questions is based on the hypothesis that the characteristics of successful groups are encoded by features that can be spotted in their photo. We analyze >43K group photos (one photo per group) taken after groups have completed the game—from which all explicit performance-signaling information has been removed. First, we find that groups that are larger, older and more gender but less age diverse are significantly more likely to escape. Second, we compare humans and off-the-shelf machine learning algorithms at predicting whether a group escaped or not based on the completion photo. We find that individual guesses by humans achieve 58.3% accuracy, better than random, but worse than machines which display 71.6% accuracy. When humans are trained to guess by observing only four labeled photos, their accuracy increases to 64%. However, training humans on more labeled examples (eight or twelve) leads to a slight, but statistically insignificant improvement in accuracy (67.4%). Humans in the best training condition perform on par with two, but worse than three out of the five machine learning algorithms we evaluated. Our work illustrates the potentials and the limitations of machine learning systems in evaluating group performance and identifying success factors based on sparse visual cues.

Download Full-text

Pain intensity and physical performance among individuals with fibromyalgia in mid-to-late life: The influence of depressive symptoms

Journal of Health Psychology ◽

10.1177/13591053211009286 ◽

2021 ◽

pp. 135910532110092

Author(s):

Dylan G Serpas ◽

Laura Zettel-Watson ◽

Barbara J Cherry

Keyword(s):

Depressive Symptoms ◽

Pain Intensity ◽

Physical Performance ◽

Walk Test ◽

Mediation Analyses ◽

Mediating Role ◽

6 Minute Walk Test ◽

The Relationship ◽

Minute Walk

This study investigated the mediating role of depressive symptoms among 147 middle-aged and older adults with FM in the relationship between pain intensity and 4 objective measures of physical performance: Fullerton Advanced Balance scale (FAB), 6-Minute Walk Test (6MWT), 30-Second Chair Stand (30SCS), and 8-Foot Up and Go Test (8FUPGT). Asymptotic mediation analyses revealed that depressive symptoms fully mediated the relationship between pain intensity and FAB (95% CI [−0.40, −0.10]) and 8FUPGT (CI [0.02, 0.11]) and partially mediated the relationship to 6MWT (CI [−9.15, −2.20]) and 30SCS (CI [−0.29, −0.06]). Findings support the evaluation of co-morbid depression in FM.

Download Full-text

The role of self-construal in EFL vocabulary learning

IRAL - International Review of Applied Linguistics in Language Teaching ◽

10.1515/iral-2019.0082 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Mitsuko Tanaka

Keyword(s):

Technical College ◽

Engineering Students ◽

Vocabulary Learning ◽

Self Determination Theory ◽

Mediation Analyses ◽

Self Construal ◽

Learning Modes ◽

The Relationship ◽

Identified Regulation

AbstractVocabulary learning is often assigned as out-of-class learning, which learners need to autonomously initiate and be motivated to sustain. Under such learning modes, though independent learners may need less motivational scaffolding, learners who prefer a more interactive study environment may need to be provided with assistance to boost their motivation. Focusing on such personal determinants, this study examines the role of self-construal in vocabulary learning by employing self-determination theory. The participants were 155 engineering students from a Japanese technical college. Path and mediation analyses were performed based on vocabulary test scores and questionnaire responses. Results revealed that independent self-construal had a significant impact on more self-determined types of both motivation (i.e., intrinsic motivation and identified regulation) and amotivation, but interdependent self-construal was statistically irrelevant to them, in the context of vocabulary learning. Furthermore, perceived autonomy and competence mediated the relationship between independent self-construal and motivation. These findings indicate that vocabulary learning motivation is shaped and regulated by self-construal and may be enhanced through support of the mediators.

Download Full-text

Relationship of patient shame to working alliance and satisfaction: a preliminary investigation

The Journal of Mental Health Training Education and Practice ◽

10.1108/jmhtep-10-2017-0059 ◽

2019 ◽

Vol 14 (4) ◽

pp. 251-263

Author(s):

Daniel J. Carabellese ◽

Michael J. Proeve ◽

Rachel M. Roberts

Keyword(s):

Patient Satisfaction ◽

Working Alliance ◽

Preliminary Investigation ◽

Community Members ◽

Content Type ◽

Mediation Analyses ◽

External Shame ◽

Relationship Of ◽

The Relationship

Purpose The purpose of this paper is to explore the relationship of two distinct variants of dispositional shame (internal and external shame) with collaborative, purpose-driven aspects of the patient–provider relationship (working alliance) and patient satisfaction. The aim of this research was to conduct a preliminary investigation into the relevance of dispositional shame in a general healthcare population. Design/methodology/approach In total, 127 community members (mean age 25.9 years) who reported that they had regularly seen a GP over the past year were recruited at an Australian university. Participants were asked to reflect on their relationship with their GP, and completed instruments assessing various domains of shame, as well as working alliance and patient satisfaction. Findings Non-parametric correlations were examined to determine the direction and strength of relationships, as well as conducting mediation analyses where applicable. Small, negative correlations were evident between external shame and working alliance. Both external and internal shame measures were also negatively correlated with patient satisfaction. Finally, the relationship of external shame to patient satisfaction was partially mediated by working alliance. Practical implications Both the reported quality of patient–provider working alliance, and level of patient satisfaction are related to levels of dispositional shame in patients, and working alliance may act as a mediator for this relationship. Originality/value The findings from this preliminary study suggest that internal and external shame are important factors to consider in the provision of medical care to maximise the quality of patient experience and working alliance.

Download Full-text