IT Affordances in Online Social Commerce: Conceptualization Validation and Scale Development

IT affordances have gained much attention in theoretically interpreting social media-associated behavior in information systems literature and played a crucial role in conceptually realizing IT-implicated mechanisms of human-computer interaction. But these efforts have been practically impeded in empirical research due to the lack of a validated scale. Here we address a context-specific conceptualization and a fine-grained measurement for IT affordances in online social commerce (OSC). We used a mixed-method approach to conduct a rigorous and comprehensive instrumental-development and validation procedure. We found that IT affordances in OSC are a multidimensional and formative construct, which consists of visibility, metavoicing, triggered attending, guidance shopping, social connecting, and trading. Results of psychometric properties based on two datasets (n=255 and n=326) show the scale is reliable and valid. The findings provide a theoretical springboard for further research and implication for practice

The Impact Mechanism of Charismatic Leadership on Individual\u27s Tacit Knowledge Sharing

Drawing upon charismatic leadership and intrinsic motivation theory, we developed a theoretical model to examine the impact mechanism of charismatic leadership on employees’ tacit knowledge sharing intention in a temporary Enterprise Systems learning team. We conducted a survey-based field study to examine the theoretical model and hypotheses. A total of 153 questionnaires were distributed to ERP users of more than 20 subsidiaries of Beidahuang Group in China and 117 valid questionnaires were returned. Results from structural equation modelling analysis suggest that leader charisma has strong influence on psychological safety climate, which in turn has positive impact on individual’s intrinsic motivation and their tacit knowledge sharing intention. Our results unpack the impact mechanism of leader charisma on individual’s knowledge sharing behaviors, and provide guidelines for the team leader to exhibit appropriate leadership traits in order to promote a psychological safety climate and facilitate an effective knowledge sharing of Enterprise Systems

Pedicled iliac crest bone flap transfer for the treatment of upper femoral shaft fracture nonunion: An anatomic study and clinical applications

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146632/1/micr30278.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146632/2/micr30278_am.pd

‘Computing’ Requirements in Open Source Software Projects

Due to high dissimilarity with traditional software development, Requirements Engineering (RE) in Open Source Software (OSS) remains poorly understood, despite the visible success of many OSS projects. In this study, we approach OSS RE as a sociotechnical and distributed cognitive activity where multiple actors deploy heterogeneous artifacts to ‘compute’ requirements as to reach a collectively-held understanding of what the software is going to do. We conduct a case study of a popular OSS project, Rubinius (a Ruby programming language runtime environment). Specifically, we investigate the ways in which this project exhibits distribution of cognitive efforts along social, structural, and temporal dimensions and how its requirements computation takes place accordingly. In particular, we seek to generalize to a theoretical framework that explains how three temporally-ordered processes of distributed cognition in OSS projects, denoted excavation, instantiation, and testing-in-the-wild, tie together to form a powerful distributed computational structure to manage requirements

A Continuous Trust-Region-Type Method for Solving Nonlinear Semidefinite Complementarity Problem

We propose a new method to solve nonlinear semidefinite complementarity problem by combining a continuous method and a trust-region-type method. At every iteration, we need to calculate a second-order cone subproblem. We show the well-definedness of the method. The global convergent result is established

LDL-C: An important independent risk factor for new-onset heart block in patients with severe aortic stenosis and heart failure after TAVR

Transcatheter aortic valve replacement (TAVR) is an effective alternative treatment for patients with aortic stenosis (AS) who have intermediate to high surgical risk or who are inoperable. However, the incidence of conduction abnormalities is high after TAVR, which can reduce the effectiveness of the surgery. Our research objective is to explore the risk factors of new-onset conduction abnormalities after TAVR, providing reference value for clinical doctors to better prevent and treat conduction abnormalities. Patients who underwent TAVR were divided into those who developed heart block and those who did not. Baseline clinical characteristics, cardiac structural parameters, procedural characteristics, electrocardiogram (ECG) changes before and after TAVR ( = postoperative minus preoperative), and surgical complications were compared. Logistic regression was applied to identify significant risk factors for new-onset heart block. We studied 93 patients, of whom 34.4% developed heart blocks. Univariate logistic regression showed that prior history of malignancy, atrial fibrillation, preoperative high-level total cholesterol and low-density lipoprotein cholesterol (LDL-C), HR, QRS interval, QT interval, and QTc interval were risk factors of new-onset heart block after TAVR. Multivariate analysis showed that preoperative high-level LDL-C and QRS interval remained significant independent risk factors after adjusting for potential confounds. Heart block is the most common complication of TAVR, and its significant independent risk factors include high-level LDL-C and QRS interval. [Abstract copyright: Copyright: © 2023 The Author(s). Published by IMR Press.

Challenges to China's new stock market for small and medium-size enterprises: trading price falls below the IPO price

This study discusses the development of the Growth Enterprise Board (GEB), a part of the Shenzhen Stock Exchange (SZSE), which allows small and medium-size enterprises (SMEs) to raise capital on favourable terms by issuing shares in China. We use all initial public offerings (IPOs) in the GEB market to model the probability of the trading price for new issues that will fall below their IPO price from October 2009 to December 31, 2011. Three probability models (logit, probit and scobit models) are used. The results show that four important factors explain the probability of trading price falling below their IPO price. A high first-day turnover ratio, a small price update, an optimistic stock market, and high average initial returns of other firms prior to an IPO issue all reduce the risk that the trading price will fall below the IPO price. The stock market returns have a non-linear significant effect on that probability. Our results are useful for regulators, underwriters, and issuers in the development of the GEB market

Effects of saponins Rb1 and Re in American ginseng combined intervention on immune system of aging model

Aging is a major risk factor for the development of many pathological processes, such as reduced immunity, cancer, cardiovascular diseases or neurodegenerative diseases, while age-related chronic diseases are the most common causes of death. This paper studies the effects of American ginseng saponin Rb1 and Re alone and combined intervention on the immune system of aging mouse models, by using 30 mg/kg Rb1, 15 mg/kg Re, and Rb1 + Re (30 mg/kg Rb1 and 15 mg/kg Re (co-intervention) was used to intervene in the aging model, and immune indicators such as thymus index, spleen index, interleukin and interferon were detected to evaluate the impact of Rb1 and Re on immune function. The results show that Rb1 and Re intervention alone can increase the spleen index by 7%–12% and the thymus index by 12%–19% in the aging model. After Rb1 or Re alone intervened, the apoptotic cells in the thymus were slightly reduced, and the proportion of apoptotic cells was reduced. The combination of Rb1 + Re can promote the thymus index and spleen index to increase by 23.40% and 25.5% respectively, which is more advantageous than Rb1 or Re alone. In addition, Rb1 and Re intervention can reduce the level of interferon INF to a level comparable to that of young mice. Rb1 + Re can not only reduce the INF content, but also reduce the TNF content. The above results show that American ginseng saponin Rb1 and Re can delay the decline of the immune system in the aging model, and the combined intervention of the two is significantly better than individual intervention in the recovery of the immune system. This paper can provide theoretical basis and data support for the development of American ginseng nutritional supplements and its application in aging groups products to improve immunity

An empirical study on digitalization's impact on operational efficiency and the moderating role of multiple uncertainties

While many organizations are increasingly willing to invest in adopting digitalization in recent years, they might not be aware that different levels of uncertainty within and outside their organizations may impend digitalization's effectiveness. This study aims to empirically explores the performance impact from digitalization on organizations and the effect from uncertainty on the impact. More specifically, the objectives are pertinent to examining 1) the association between digitalization and operational efficiency and 2) the moderating effect of macro-level uncertainty, industrial-level uncertainty, and firm-level uncertainty on this association. Using a dataset collected from multiple sources employing innovative methodologies including natural language processing (NLP) to analyze digitalization announcements from Factiva and measuring operational efficiency based on the stochastic frontier approach (SFA), this study analyzes the impact from digitalization via 2,520 samples from 496 listed firms in North America during 2015-2021. The results show that digitalization significantly enhances operational efficiency, and this positive impact from digitalization is weakened by macro-level uncertainty and industrial-level uncertainty. Our findings provide researchers and practitioners with useful insights into digitalization's important role in enhancing operational efficiency and guidance indicating the business environments deserve extra attention so as to retain digitalization's positive impact