Competency-driven benefits realization model for minimization of post-contract transaction costs in design-build (d&b) delivery systems

The construction industry has been struggling with the issue of inconsistent performance with respect to cost of projects, completion time and the delivery of a quality product. In an attempt to address this issue the Design-Build (D&B) project delivery system was initiated primarily to overcome the shortcomings of the traditional procurement strategies. Although, traditionally D&B delivery system was aimed to greatly enhance client‘s benefits, this has not significantly been achieved. It lacks clear benefits realization management process to deliver the planned client‘s benefits. In particular, the Transaction Costs (TCs) incurred at the post-contract phase (PTCs) through D&B system has been the subject of criticism, wherein it has been unable to achieve the expected resounding success of a total shift away from the issues attributed to the traditional systems. This research aims to establish the importance of leveraging on D&B project team-competency and commitment structured within a strategic Benefits Realization Management framework to optimize client‘s benefits in terms of minimizing PTCs. The focus is on the aspect of competencies of key project participants and their project team commitment with respect to minimizing TCs that is structured within a Benefits Realization Management (BRM) practice. Questionnaire survey data was obtained from 231 respondents out of 357 administered questionnaires to G7 contractors registered under CIDB Malaysia that was based on a systematic sampling of the existing CIDB contractor database. The partial least squares structural equation modeling (PLS-SEM) technique was used to test the relationships being hypothesized and to validate and confirm the developed Competency Driven Benefits Realization Model (CD-BREM). Exploratory preliminary research findings reveal that post-contract TCs for D&B projects range from 3.5% to 13.5% of the project value. The primary research findings reveal that D&B team commitment has partial mediating effect between team competency and post-contract TCs. Whilst, BRM was found to have a partial mediating effect between team competency and post-contract TCs and no moderating effect as initially hypothesized. In general the research findings indicate that team competency, commitment and BRM have significant positive influences on post-contract TCs. This research provides a multi-dimensional perspective of the D&B project benefits realization concept and has the potential to address the issue of minimizing PTCs, which is seen as a social waste of wealth. Using CD-BREM it is possible to identify key human factors that can contribute to high project performance that also serves as an enabling mechanism for realizing the full potential of the D&B method for delivering successful projects. This research is timely to help reverse the trend of poor performance within the construction industry as a whole. Further work on the implementation of this CD-BREM model on construction projects and the consideration of including additional independent variables in the research theoretical framework can be explored to strengthen the credibility of the outcome of this research which is aimed at minimizing PTCs

Information Outlook, September 2004

Volume 8, Issue 9https://scholarworks.sjsu.edu/sla_io_2004/1008/thumbnail.jp

Information Outlook, September 2004

Volume 8, Issue 9https://scholarworks.sjsu.edu/sla_io_2004/1008/thumbnail.jp

Social Search with Missing Data: Which Ranking Algorithm?

Online social networking tools are extremely popular, but can miss potential discoveries latent in the social 'fabric'. Matchmaking services which can do naive profile matching with old database technology are too brittle in the absence of key data, and even modern ontological markup, though powerful, can be onerous at data-input time. In this paper, we present a system called BuddyFinder which can automatically identify buddies who can best match a user's search requirements specified in a term-based query, even in the absence of stored user-profiles. We deploy and compare five statistical measures, namely, our own CORDER, mutual information (MI), phi-squared, improved MI and Z score, and two TF/IDF based baseline methods to find online users who best match the search requirements based on 'inferred profiles' of these users in the form of scavenged web pages. These measures identify statistically significant relationships between online users and a term-based query. Our user evaluation on two groups of users shows that BuddyFinder can find users highly relevant to search queries, and that CORDER achieved the best average ranking correlations among all seven algorithms and improved the performance of both baseline methods

Information Outlook, September 2004

Volume 8, Issue 9https://scholarworks.sjsu.edu/sla_io_2004/1008/thumbnail.jp

Applying a Multidimensional Strategy to Mitigate Lateral Violence in a Small Rural Community Hospital in Western New York

Providing registered nurses with education and strategies to mitigate lateral violence is an evidenced-based method for creating a culture of civility. A descriptive pilot study with registered nurses was conducted on two medical/surgical units at a small rural community hospital. Strategies included a review of organizational policies, a one-day educational retreat for unit managers and registered nurse champions, and an online educational toolkit on lateral violence for the staff nurses on the pilot units

Growing Story Forest Online from Massive Breaking News

We describe our experience of implementing a news content organization system at Tencent that discovers events from vast streams of breaking news and evolves news story structures in an online fashion. Our real-world system has distinct requirements in contrast to previous studies on topic detection and tracking (TDT) and event timeline or graph generation, in that we 1) need to accurately and quickly extract distinguishable events from massive streams of long text documents that cover diverse topics and contain highly redundant information, and 2) must develop the structures of event stories in an online manner, without repeatedly restructuring previously formed stories, in order to guarantee a consistent user viewing experience. In solving these challenges, we propose Story Forest, a set of online schemes that automatically clusters streaming documents into events, while connecting related events in growing trees to tell evolving stories. We conducted extensive evaluation based on 60 GB of real-world Chinese news data, although our ideas are not language-dependent and can easily be extended to other languages, through detailed pilot user experience studies. The results demonstrate the superior capability of Story Forest to accurately identify events and organize news text into a logical structure that is appealing to human readers, compared to multiple existing algorithm frameworks.Comment: Accepted by CIKM 2017, 9 page

#Socialtagging: Defining its Role in the Academic Library

The information environment is rapidly changing, affecting the ways in which information is organized and accessed. User needs and expectations have also changed due to the overwhelming influence of Web 2.0 tools. Conventional information systems no longer support evolving user needs. Based on current research, we explore a method that integrates the structure of controlled languages with the flexibility and adaptability of social tagging. This article discusses the current research and usage of social tagging and Web 2.0 applications within the academic library. Types of tags, the semiotics of tagging and its influence on indexing are covered