Improving Transportation Construction Project Performance: Development of a Model to Support the Decision-Making Process for Incentive/Disincentive Construction Projects, MTI Report 09-07

This research presents a project time and cost performance simulation model to assist project planners and managers by providing a complete picture during the Incentive/Disincentive (I/D) contracting decision-making process of possible performance outcomes with probabilities based on historical data. This study was performed by collecting transportation construction project data. The collected project data from the Florida Department of Transportation were evaluated using time and cost performance indices and then statistical data analysis was performed to identify important factors that influence construction project time performance. Using Monte Carlo simulation procedures, this study demonstrated a methodology for developing an I/D project time and cost performance prediction model. User-friendly visual interfaces were developed to perform the simulation and report results using Visual Basic Application programming. The developed model was validated using additional cases of transportation construction projects. Based on statistical analysis, this research found that several project factors influence I/D contracting performance. The important factors that had significant impacts on project performance were the effects of contract type, project type, district, project size, project length, maximum incentive amount, and daily I/D amount. In conclusion, the developed model applied to I/D contracting projects will be a useful tool to assist the project planners and managers during the decision-making process and will promote the efficient use of I/D contracting, which will benefit the traveling public by saving their travel time from construction delays. With additional project data, the developed model can be updated easily and the more data used for the model, the better the accuracy of prediction that can be expected

Cost Estimate Modeling of Transportation Management Plans for Highway Projects, Research Report 11-24

Highway rehabilitation and reconstruction projects frequently cause road congestion and increase safety concerns while limiting access for road users. State Transportation Agencies (STAs) are challenged to find safer and more efficient ways to renew deteriorating roadways in urban areas. To better address the work zone issues, the Federal Highway Administration published updates to the Work Zone Safety and Mobility Rule. All state and local governments receiving federal aid funding were required to comply with the provisions of the rule no later than October 12, 2007. One of the rule’s major elements is to develop and implement Transportation Management Plans (TMPs). Using well-developed TMP strategies, work zone safety and mobility can be enhanced while road user costs can be minimized. The cost of a TMP for a road project is generally considered a high-cost item and, therefore, must be quantified. However, no tools or systematic modeling methods are available to assist agency engineers with TMP cost estimating. This research included reviewing TMP reports for recent Caltrans projects regarding state-of-the-art TMP practices and input from the district TMP traffic engineers. The researchers collected Caltrans highway project data regarding TMP cost estimating. Then, using Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) software, the researchers performed case studies. Based on the CA4PRS outcomes of the case studies, a TMP strategy selection and cost estimate (STELCE) model for Caltrans highway projects was proposed. To validate the proposed model, the research demonstrated an application for selecting TMP strategies and estimating TMP costs. Regarding the model’s limitation, the proposed TMP STELCE model was developed based on Caltrans TMP practices and strategies. Therefore, other STAs might require adjustments and modifications, reflecting their TMP processes, before adopting this model. Finally, the authors recommended that a more detailed step-by-step TMP strategy selection and cost estimate process be included in the TMP guidelines to improve the accuracy of TMP cost estimates

Commonalities and differences between service and manufacturing supply chains: Combining operations management studies with supply chain management

The service sector of the US economy has been gaining importance. As the service sector evolves, the study of service supply chain starts to gain attention. In this study, we conduct an exploratory review on the studies of manufacturing and service supply chains. We focus on the studies that explore the differences and commonalities between manufacturing and service supply chains. We combine operations management literature with supply chain studies in order to provide an interdisciplinary framework that brings up both the operational and strategic views on the management commonalities and differences between the two types of supply chains

An Exploratory Study to Improve Sales Operations When Selling Multiple Prescription Drugs

This paper explores the importance of integrating knowledge with quantitative modeling process to improve sales operations in multiple product selling situations in the pharmaceutical industry. A knowledge-based approach is proposed to minimize challenges in detailing multiple products to physicians who are more and more difficult accessing in recent years. The performance of this new approach is compared against the traditional approach via actual implementation by the firm that is sponsoring the research. Results based on three months of implementation indicate that the knowledge-based approach performs significantly better with increasing the number of responsive physicians by 71% and profit by 9%

Applications of open innovation to the supply chain system in the SMEs

The close-knitted structure of a supply chain seems to leave no room for the word \u27open\u27. Closeness builds trust, enables information sharing, benefits transportation and more. Somehow, openness started to benefit supply chain management recently, through a trend called \u27open innovation\u27. Based on gathered anecdotes and our interviews of industry professionals, we attempted to present a more complete picture of open innovation in supply chain management, including its potential benefits, major concerns, adoption hurdles, and future solutions. Our findings identified current perceptions of supply chain practitioners on open innovation and major hurdles and difficulties of implementing open innovation in supply chain functions other than just product development. Our research contributed to the current literature of open innovation by updating its implementation status, identifying adoption and implementation issues, and proposing strategic considerations within the context of supply chain management

Motivational Factors Influencing Sport Spectator Involvement At NCAA Division II Basketball Games

The purpose of this study was to investigate the motivational factors affecting sport spectator involvement using 304 spectators from NCAA Division II men\u27s and women\u27s basketball games. Two aspects (behavioral and socio-psychological) of sport spectator involvement were examined. The results revealed that spectators at intercollegiate basketball games had a higher level of socio-psychological involvement than behavioral involvement. A series of multiple regression analyses were conducted to examine the affects of sociomotivational factors (perceived value, fan identification, involvement opportunity, and reference groups) on sport spectator involvement. Fan identification, involvement opportunity, and reference groups were identified as influential factors that had a significant impact on overall sport spectator involvement. The results also indicated that the four motivational factors predicted more variance for socio-psychological involvement (R2 = .33) than behavioral involvement (R2 = .22). The findings of this study provide valuable insight to Division II athletic administrators about how to attract additional spectators to collegiate basketball games

Pediatric Korean Triage and Acuity Scale

Symptoms and signs of childhood disease are different according to age. Initial assessment process in emergency department should consider a broad presentation of illness and injuries of pediatric patients. In 2012, the Korean Society of Emergency Medicine developed the Korean Triage and Acuity Scale (KTAS) by expert consultation including a survey to emergency physicians, nurses, and emergency medical technicians based on the Canadian Triage and Acuity Scale. KTAS research group performed the analysis of distribution of pediatric populations by KTAS classification in 8 hospitals and showed the correlation with the disposition results with KTAS scores in 2014. KTAS could improve the patient safety by the real-time scoring of severity in pediatric patients. KTAS would generate important data for distributing patients to the less crowded emergency departments in near future

Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models

Advances in Large Language Models (LLMs) have inspired a surge of research exploring their expansion into the visual domain. While recent models exhibit promise in generating abstract captions for images and conducting natural conversations, their performance on text-rich images leaves room for improvement. In this paper, we propose the Contrastive Reading Model (Cream), a novel neural architecture designed to enhance the language-image understanding capability of LLMs by capturing intricate details typically overlooked by existing methods. Cream integrates vision and auxiliary encoders, complemented by a contrastive feature alignment technique, resulting in a more effective understanding of textual information within document images. Our approach, thus, seeks to bridge the gap between vision and language understanding, paving the way for more sophisticated Document Intelligence Assistants. Rigorous evaluations across diverse tasks, such as visual question answering on document images, demonstrate the efficacy of Cream as a state-of-the-art model in the field of visual document understanding. We provide our codebase and newly-generated datasets at https://github.com/naver-ai/crea