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This paper provides an introduction to the topic of enterprise social networks (ESN) and illustrates possible applications, potentials, and challenges for future research. It outlines an analysis of research papers containing a literature overview in the field of ESN. Subsequently, single relevant research papers are analysed and further research potentials derived therefrom. This yields seven promising areas for further research: (1) user behaviour; (2) effects of ESN usage; (3) management, leadership, and governance; (4) value assessment and success measurement; (5) cultural effects, (6) architecture and design of ESN; and (7) theories, research designs and methods. This paper characterises these areas and articulates further research directions.
Purpose – This paper aims to complement the current understanding about user engagement in electronic word-of-mouth (eWoM) communications across online services and product communities. It examines the effect of the senders’ prior experience with products and services, and their extent of acquaintance with other community members, on user engagement with the eWoM.
Design/methodology/approach – The study used a sample of 576 unique user postings from the corporate fan page of two German firms: a service community of a telecom provider and a product community of a car manufacturer. Multiple regression analysis is used to test the conceptual model.
Findings – Senders’ prior experience and acquaintance positively affect user engagement with eWoM, and these effects differ across communities for products and services and across their influence on “likes” and “comments”. The results also suggest that communities for products are orientated toward information sharing, while those discussing services engage in information building.
Research limitations/implications – This research explains mechanisms of user engagement with eWoM and opens directions for future research around motives, content and social media tools within the structures of online communities. The insights on information-handling dimensions of online tools and antecedents to their use contribute to the research on two prioritized topics by the Marketing Science Institute – "Measuring and
Communicating the Value of Online Marketing Activities and Investments" and "Leveraging Digital/Social/Mobile Technology".
Practical implications – This research offers insights for firms to leverage user engagement and facilitate eWoM generation through members who have a higher number of acquaintances or who have more experience with the product or service. Executives should concentrate their community engagement strategies on the identification and utilization of power users. The conceptualization and empirical test about the role of likes and comments will help social media managers to create and better capture value from their social media metrics.
Originality/value – The insights about the underlying factors that influence engagement with eWoM advance our understanding about the usage of online content.
This paper presents a concurrency control mechanism that does not follow a "one concurrency control mechanism fits all needs" strategy. With the presented mechanism a transaction runs under several concurrency control mechanisms and the appropriate one is chosen based on the accessed data. For this purpose, the data is divided into four classes based on its access type and usage (semantics). Class O (the optimistic class) implements a first-committer-wins strategy, class R (the reconciliation class) implements a first-n-committers-win strategy, class P (the pessimistic class) implements a first-reader-wins strategy, and class E (the escrow class) implements a first-n-readers-win strategy. Accordingly, the model is called OjRjPjE. The selected concurrency control mechanism may be automatically adapted at run-time according to the current load or a known usage profile. This run-time adaptation allows OjRjPjE to balance the commit rate and the response time even under changing conditions. OjRjPjE outperforms the Snapshot Isolation concurrency control in terms of response time by a factor of approximately 4.5 under heavy transactional load (4000 concurrent transactions). As consequence, the degree of concurrency is 3.2 times higher.
Background and purpose: Transapical aortic valve replacement (TAVR) is a recent minimally invasive surgical treatment technique for elderly and high-risk patients with severe aortic stenosis. In this paper,a simple and accurate image-based method is introduced to aid the intra-operative guidance of TAVR procedure under 2-D X-ray fluoroscopy.
Methods: The proposed method fuses a 3-D aortic mesh model and anatomical valve landmarks with live 2-D fluoroscopic images. The 3-D aortic mesh model and landmarks are reconstructed from interventional X-ray C-arm CT system, and a target area for valve implantation is automatically estimated using these aortic mesh models.Based on template-based tracking approach, the overlay of visualized 3-D aortic mesh model, land-marks and target area of implantation is updated onto fluoroscopic images by approximating the aortic root motion from a pigtail catheter motion without contrast agent. Also, a rigid intensity-based registration algorithm is used to track continuously the aortic root motion in the presence of contrast agent.Furthermore, a sensorless tracking of the aortic valve prosthesis is provided to guide the physician to perform the appropriate placement of prosthesis into the estimated target area of implantation.
Results: Retrospective experiments were carried out on fifteen patient datasets from the clinical routine of the TAVR. The maximum displacement errors were less than 2.0 mm for both the dynamic overlay of aortic mesh models and image-based tracking of the prosthesis, and within the clinically accepted ranges. Moreover, high success rates of the proposed method were obtained above 91.0% for all tested patient datasets.
Conclusion: The results showed that the proposed method for computer-aided TAVR is potentially a helpful tool for physicians by automatically defining the accurate placement position of the prosthesis during the surgical procedure.