When Does a Firm Have Faster Speed Despite Inferior Capability? Disintegrating Capability and Incentive Effects When Examining Firm Speed

Firm speed has long been a construct of interest among managers and researchers. Although both a firm’s capabilities and incentives to be fast determine observed firm speed, practitioners and academic scholars have typically focused on the capability mechanism alone. However, the omission of incentives in understanding firm speed can lead to mistaking faster firm speed for superior firm capability. To address this shortcoming, we develop a theoretical framework considering both capabilities and incentives simultaneously to examine faster firm speed. Our developed framework allows us to discern whether superior capabilities or greater incentives lead to a faster speed. We also show how to apply our framework to empirical analysis by analyzing actual firm data in the Liquefied Natural Gas industry from 1996 to 2007. In this way, the current paper contributes to the literature on firm speed by providing a theoretical framework that enables a more nuanced understanding of firm speed

Clinical analysis of pediatric patients who visited Masan Samsung Emergency Center

Purpose : Through a clinical and retrospective analysis of pediatric patients who visited the Regional Emergency Medical Center of Masan Samsung Hospital from January 2007 to December 2008, we characterized pediatric and adolescent emergency patients to improve emergency care in future. Methods : We reviewed the medical records of 14,065 pediatric patients below 19 years of age. Results : The male to female ratio was 1.5:1, and the most common age group was less than 3 years (49.6%). The peak month was May (10.0%), the peak day of the week was Sunday (24.7%), and the peak time of day was 20:00&amp&#59;#8211&#59;20:59 (8.5%). There was no difference in the number of visits per day based on weather (sunny, rain [below 10 mm per day], snow, and fog) or daily temperature difference&#59; however, visits increased on sandy, dusty days and decreased on rainy days with more than 10 mm of rain per day. Based on the international classification of disease (ICD)-10 system, the most common disease code was code R (symptoms, sign, and abnormal clinical laboratory finding) (31.5%), and the most common symptom was fever (13.1%). Final outcomes were discharged (73.8%), admitted (25.7%), transferred (0.4%), and expired (0.1%). In adolescent patients aged 15&amp&#59;#8211&#59;19 years, the most common disease code was Injury &amp&#59; Poisoning (code S&amp&#59;T, 36.9%)&#59; the most common symptom was abdominal pain (9.6%). Conclusion : Pediatric patients visiting the emergency center were most likely to be male and under 3 years of age and to visit between 20:00 and 21:00 on Sundays and in May, and the most common symptom was fever. Differences between adolescents and pediatric patients showed that adolescents had a higher visiting rate with abdominal pain and a larger temperature difference

The Information Systems Academic Discipline in Korea: A Focus on Leading Universities

Information Systems (IS) as an academic discipline is in different stages of evolution across countries because of different environmental and situational factors. In spite of thist, most previous studies on IS have been focused mainly in western countries, while scant attention has been given to understanding its status in non-western countries especially in the Pacific Asia Region (PAR). To address this shortcoming, and as a part of the Pacific Asia multi-country case study called IS-in-PA, this study explores the status of IS as an academic discipline in Korea by analyzing the characteristics of IS programs and IS research across 10 leading Korean universities. In order to do this, in-depth interviews and intensive secondary data gathering and analysis based on the case study approach were conducted. The results of this study offer a basic understanding of the unique aspects of IS as a discipline in Korean universities, thereby enabling more effective AIS initiatives to enhance the IS discipline in Pacific Asia, in general, and Korea, in particular. This can also serve as an early groundwork for other researchers seeking to understand the current situation and emerging trends in IS as a discipline in Korea

Optical Air-Gap Attacks:Analysis and IoT Threat Implications

Since 2008, the Korean government has instituted network separation technology, which physically isolates external internet networks from internal networks, aiming to thwart cyber-attacks. Consequently, the domestic financial sector was largely unaffected during global crises (2017 WannaCry ransomware outbreak and the 2021 Log4j vulnerability incident). However, there exist certain vulnerabilities owing to the presumption of their relative safety against cyber intrusions and the integration of cloud and Internet of Things (IoT) technologies in the current smart revolution. The existing network separation measures only mitigate one facet of potential cyber threats, rendering a comprehensive defense elusive. The rise of “air-gap” attacks, which exploit the isolated space between closed and external networks to illicitly transfer data and the existing research primarily substantiating the potential for data breaches from closed networks to their external counterparts are problems yet to be addressed. Thus, our study proposed a tangible optical air-gap attack methodology, harnessing readily available optical mediums within closed networks. Intricate measurement metrics that consider vital factors of the transmission environment were proposed. Moreover, acknowledging the proliferating integration of IoT devices, such as smart bulbs, to facilitate automation within closed networks, this study demonstrated the viability of optical air-gap attacks using these devices

CLOCIS:Cloud-based conformance testing framework for IoT devices in the future internet

In recent years, the Internet of Things (IoT) has not only become ubiquitous in daily life but has also emerged as a pivotal technology across various sectors, including smart factories and smart cities. Consequently, there is a pressing need to ensure the consistent and uninterrupted delivery of IoT services. Conformance testing has thus become an integral aspect of IoT technologies. However, traditional methods of IoT conformance testing fall short of addressing the evolving requirements put forth by both industry and academia. Historically, IoT testing has necessitated a visit to a testing laboratory, implying that both the testing systems and testers must be co-located. Furthermore, there is a notable absence of a comprehensive method for testing an array of IoT standards, especially given their inherent heterogeneity. With a surge in the development of diverse IoT standards, crafting an appropriate testing environment poses challenges. To address these concerns, this article introduces a method for remote IoT conformance testing, underpinned by a novel conceptual architecture termed CLOCIS. This architecture encompasses an extensible approach tailored for a myriad of IoT standards. Moreover, we elucidate the methods and procedures integral to testing IoT devices. CLOCIS, predicated on this conceptual framework, is actualized, and to attest to its viability, we undertake IoT conformance testing and present the results. When leveraging CLOCIS, small and medium-sized enterprises (SMEs) and entities in the throes of IoT service development stand to benefit from a reduced time to market and cost-efficient testing procedures. Additionally, this innovation holds promise for IoT standardization communities, enabling them to champion their standards with renewed vigor

K\"{a}hler-Einstein metrics on smooth Fano symmetric varieties with Picard number one

Symmetric varieties are normal equivarient open embeddings of symmetric homogeneous spaces, and they are interesting examples of spherical varieties. We prove that all smooth Fano symmetric varieties with Picard number one admit K\"{a}hler-Einstein metrics by using a combinatorial criterion for K-stability of Fano spherical varieties obtained by Delcroix. For this purpose, we present their algebraic moment polytopes and compute the barycenter of each moment polytope with respect to the Duistermaat-Heckman measure.Comment: 13 pages, 6 figure

K-stability of Gorenstein Fano group compactifications with rank two

We give a classification of Gorenstein Fano bi-equivariant compactifications of semisimple complex Lie groups with rank two, and determine which of them are equivariant K-stable and admit (singular) K\"{a}hler-Einstein metrics. As a consequence, we obtain several explicit examples of K-stable Fano varieties admitting (singular) K\"{a}hler-Einstein metrics. We also compute the greatest Ricci lower bounds, equivalently the delta invariants for K-unstable varieties. This gives us three new examples on which each solution of the K\"{a}hler-Ricci flow is of type II.Comment: 33 pages, 8 figure

The GitHub Recent Bugs Dataset for Evaluating LLM-based Debugging Applications

Large Language Models (LLMs) have demonstrated strong natural language processing and code synthesis capabilities, which has led to their rapid adoption in software engineering applications. However, details about LLM training data are often not made public, which has caused concern as to whether existing bug benchmarks are included. In lieu of the training data for the popular GPT models, we examine the training data of the open-source LLM StarCoder, and find it likely that data from the widely used Defects4J benchmark was included, raising the possibility of its inclusion in GPT training data as well. This makes it difficult to tell how well LLM-based results on Defects4J would generalize, as for any results it would be unclear whether a technique's performance is due to LLM generalization or memorization. To remedy this issue and facilitate continued research on LLM-based SE, we present the GitHub Recent Bugs (GHRB) dataset, which includes 76 real-world Java bugs that were gathered after the OpenAI data cut-off point