Search

Information technology (IT) developments of large magnitude organize as collections of multiple projects into a single program, especially under dynamic conditions of market uncertainty that frequently change requirements or solutions midstream. Successful completion of an IT development program requires that the multiple teams work effectively together as well as independently in response to changes by relying on the differentiation of talent and knowledge available to the program manager. We consider and empirically support a model derived from principles in the multi-team systems (MTS) literature to determine the influence of differentiation among the IT program in the sharing of knowledge and information. The relationship from differentiation to program success is mediated by knowledge and information sharing, showing how to manage change through the dissemination of information and knowledge. Uncertainty of the market positively moderates the relation from differentiation among projects to information sharing. These findings contribute to the literature by empirically validating that MTS frameworks are exceptionally well suited for dealing with complex environments in the context of IT development.

PurposeTwo challenges faced by automotive component design projects within contracted design agencies are (1) specification changes requested by the manufacturers and (2) product information or core technology knowledge leakage to external actors. We examine the effects of targeted boundary activities that address these challenges under the contingencies of environmental uncertainty and project complexity.Design/methodology/approachBased on Boundary management theory, a bidirectional model of boundary buffering was conceptualized in the context of design agency teams developing automotive components. A survey is derived from the proposed model. Regression analysis is performed using empirical data from 234 auto component design projects in Chinese design agencies.FindingsBoundary buffering activities that strengthen outside-in boundaries and inside-out boundaries directly improve the final design quality. Further, the magnitude of effect for outside-in buffering on design quality is enhanced under environmental uncertainty, while the impact of inside-out buffering on design quality is enhanced under project complexity.Research limitations/implicationsBoundary activities should consider differences in boundary targets, directional flow of information, and context of scope.Practical implicationsAutomotive component design agents should attend to both outside-in and inside-out boundary buffering, especially under conditions of environmental uncertainty or project complexity.Originality/valueThe proposed bidirectional view on boundary buffering adds perspective to team boundary management theory. Specific contingencies include common risk elements of project complexity and environmental uncertainty not typically associated with the need for buffering activities.

Career demands on the information technology (IT) professional have evolved. No longer do organizations demand strictly managerial or technical competencies. Instead, IT professionals face demands that require the ability to produce technically proficient software or systems while managing projects and stakeholders in a variety of situations. Prior research in desired career demands and job burnout indicates that this will lead to lower levels of career satisfaction and higher levels of turnover. To address this issue, we draw on the career orientation literature to build and test a model of career satisfaction derived from the organizational demands placed on the IT professional. The results suggest that pure managerial demands lead to the highest satisfaction while adding technical demands lessens satisfaction but in a complex pattern that allows potential compromises. Prior models of career paths should be reconsidered in light of newer career demands.

One of the major challenges for Minimally Invasive Surgery (MIS) is the limited field of vision (FOV) of the endoscope. A previous study by the authors designed a MIS Panoramic Endoscope (MISPE) that gives the physician a broad field of view, but this approach is still limited, in terms of performance and quality because it encounters difficulty when there is smoke, specular reflections, or a change in viewpoint. This study proposes a novel algorithm that increases the MISPE’s performance. The method calculates the disparity for the region that is overlapped by the two cameras to allow image stitching. An improved evaluation of the homography matrix uses a frame-by-frame calculation, so the stitched videos are more stable for MIS. The experimental results show that the revised MISPE has a FOV that is 55% greater, and the system operates stably in real time. The proposed system allows a frame rate of 26.7 fps on a single CPU computer. The proposed stitching method is 1.55 times faster than the previous method. The stitched image that is obtained using the proposed method is as similar as the ground truth as the SURF-based stitching method that was used in the previous study.

Social media is an important data source to compliment traditional epidemic surveillance. However, misinformation in social media hinders the exploitation of valuable information. Analysis of information credibility has drawn much attention of academia in recent years. In this paper, we focus on analyzing the credibility of influenza posts published on Sina Weibo. We propose a semi-supervised probabilistic graphical model to jointly learn the interactions between user trustworthiness, content reliability, and post credibility. To test the performance of the approach, we apply it to identify credible influenza posts published from May 2013 to June 2014 on Sina Weibo. Random Forests and the Bayesian Network are used as baselines for evaluation. The results show that our approach performs effectively with the highest average accuracy of 71.7i¾?%, f-measure 51i¾?%. Our proposed framework significantly outperformed the baselines in detecting credible influenza posts on Sina Weibo.

Social network services, such as Facebook and Twitter in U.S.A., RenRen, QQ and Weibo in China, have grown substantially in recent years. Friend recommendation is an important emerging social network service component, which expands the networks by actively recommending new potential friends to users. We introduce a new friend recommendation system using a user's information of total attributes and based on the Law of total probability. The proposed method can be easily extended according to the number of user's attributes in different social networks. Our experimental results have demonstrated that superior performance the proposed method. In our empirical studies, we have observed that the performance of our algorithm is related with the number of user's friends. Our findings have important and practical applications in social network design and performance.