scholarly journals BIMp-Chart—A Global Decision Support System for Measuring BIM Implementation Level in Construction Organizations

2021 ◽  
Vol 13 (16) ◽  
pp. 9270 ◽  
Author(s):  
Qurratulain Malik ◽  
Abdur Rehman Nasir ◽  
Rabiah Muhammad ◽  
Muhammad Jamaluddin Thaheem ◽  
Fahim Ullah ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Success Factors ◽  
Information Modeling ◽  
Sustainable Construction ◽  
Measurement Tool ◽  
Market Demand ◽  
Construction Organizations ◽  
Implementation Level

Building Information Modeling (BIM) is recognized as one of the most significant technological breakthroughs in the Architecture, Engineering, and Construction (AEC) industry. The pace of implementation of BIM in AEC has increased during the past decade with an enhanced focus on sustainable construction. However, BIM implementation lags its potential because of several factors such as readiness issues, lack of previous experience in BIM, and lack of market demand for BIM. To evaluate and solve these issues, understanding the current BIM implementation in construction organizations is required. Motivated by this need, the main objective of this study is to propose a tool for the measurement of BIM implementation levels within an organization. Various sets of indexes are developed based on their pertinent Critical Success Factors (CSFs). A detailed literature review followed by a questionnaire survey involving 99 respondents is conducted, and results are analyzed to formulate a BIMp-Chart to calculate and visualize the BIM implementation level of an organization. Subsequently, the applicability of the BIMp-Chart is assessed by comparing and analyzing datasets of four organizations from different regions, including Qatar, Portugal, and Egypt, and a multinational organization to develop a global measurement tool. Through measuring and comparing BIM implementation levels, the BIMp-Chart can help the practitioners identify the implementation areas in an organization for proper BIM implementation. This study helps understand the fundamental elements of BIM implementation and provides a decision support system for construction organizations to devise proper strategies for the effectual management of the BIM implementation process.

scholarly journals The perils of meta-regression to identify clinical decision support system success factors

2015 ◽  
Vol 56 ◽  
pp. 65-68 ◽  
Author(s):  
Christopher L. Fillmore ◽  
Casey A. Rommel ◽  
Brandon M. Welch ◽  
Mingyuan Zhang ◽  
Kensaku Kawamoto
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Success Factors ◽  
Clinical Decision ◽  
Meta Regression ◽  
System Success

Adoption of Cloud Based Decision Support System for Building Information Modeling Software Selection

2016 ◽  
Vol 22 (5) ◽  
pp. 1310-1313 ◽  
Author(s):  
Ahmad Taufik Nursal ◽  
Mohd Faizal Omar ◽  
Mohd Nasrun Mohd Nawi ◽  
Mohammad Azwanie Naim Mohammad Asri
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Building Information Modeling ◽  
Information Modeling ◽  
Software Selection ◽  
Building Information ◽  
Modeling Software

scholarly journals CRITICAL SUCCESS FACTORS IN THE IMPLEMENTATION OF INFORMATION SYSTEMS FROM THE PERCEPTION OF USERS: A PUBLIC SECTOR EXPERIENCE

2019 ◽  
Vol 3 ◽  
pp. 1-19
Author(s):  
Platini Gomes Fonseca ◽  
Dennis Marinho Oliveira Ramalho De Souza ◽  
Ernani Marques Dos Santos ◽  
Tainã Gomes Barbosa Dos Santos ◽  
Morjane Armstrong Santos De Miranda
Keyword(s):  
Information System ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Critical Success Factors ◽  
Success Factors ◽  
Organizational Factors ◽  
Positive Perception ◽  
Critical Success ◽  
Adequate Management

The objective of the article is to identify the perception of users of the Decision Support System (DSS), used by the Federal University of Brazil (UNIVASF), about the management of the Critical Success Factors (CSF) in the implementation of the Information System. The research, descriptive and quantitative, had data collected through a structured questionnaire, applied to Decision Support System users of the Federal University. The results reveal that organizational factors were perceived as those that received more adequate management, when compared to technological CSFs, while compliance with legislation was the factor that obtained the highest positive perception index. It should also be noted that preventive corrective initiatives adopted by managers were not sufficient, leading to this factor being the one with the least positive perception of adequate management. In addition, the career can affect to a certain extent the level of perception Management of the process of implementation of the information system.

A Personalized Ontology-based Decision Support System for Complex Chronic Patients: Clinical Validation (Preprint)

2021 ◽  
Author(s):  
Esther Román-Villarán ◽  
Celia Alvarez-Romero ◽  
Alicia Martínez-García ◽  
German Antonio Escobar-Rodríguez ◽  
María José García-Lozano ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Chronic Diseases ◽  
Support System ◽  
Drug Prescription ◽  
Information Modeling ◽  
Snomed Ct ◽  
Chronic Patients ◽  
Retrospective Case ◽  
Start Criteria

BACKGROUND Due to an increase in life expectancy, the prevalence of chronic diseases is on the rise too. Clinical Practice Guidelines (CPGs) provide recommendations for suitable interventions regarding different chronic diseases. But a deficit in the implementation of these CPGs could be identified. The PITeS-TIiSS tool, a personalized ontology-based Clinical Decision Support System (CDSS), aims to reduce the variability, prevent errors and consider interactions between different CPGs recommendations, among other benefits. OBJECTIVE To design, develop and validate an ontology-based CDSS which provides personalized recommendations related to drug prescription. The target population is polymedicated elderly patients with chronic diseases aiming to reduce complications related to these types of conditions and, also, offering integrated care. METHODS A study scenario about atrial fibrillation and treatment with anticoagulants was selected to validate the tool. After this, a series of knowledge sources were identified, such as CPGs, PROFUND index, LESS/CHRON criteria, and STOP/START criteria, to extract the information. Modeling was carried out using an ontology, and mapping was done with HL7 FHIR and SNOMED CT. Once the CDSS was developed, validation was carried out by using a retrospective case study. RESULTS This project was funded in January 2015 and approved by the Ethics Committee on 24 November 2015. A retrospective validation has been carried out through the analysis of a clinical case and an adoption model through the study of the requirements and features that a CDSS must fulfill to be well accepted by healthcare professionals. The results have been favorable and allow the proposed research to continue to the next phase. CONCLUSIONS An ontology-based CDSS has been successfully designed, developed, and validated. However, as future work, the validation in a real environment should be performed to ensure the tool is usable and reliable.

scholarly journals Multi-Criteria Decision Making Model for Application Maintenance Offshoring Using Analytic Hierarchy Process

2021 ◽  
Vol 11 (18) ◽  
pp. 8550
Author(s):  
Hanif Ur Rahman ◽  
Mushtaq Raza ◽  
Palwasha Afsar ◽  
Abdullah Alharbi ◽  
Sultan Ahmad ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Success Factors ◽  
Offshore Outsourcing ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Critical Success ◽  
Hierarchy Process

The phenomenon of Global Software Development (GSD) has attracted the interest of businesses all over the world. It brings together partners from various national and corporate cultures to develop applications with numerous advantages, including access to a vast labor pool, cost savings, and round the clock growth. GSD, on the other hand, is technologically and organizationally diverse and poses a number of obstacles for the development team, such as geographical distance, cultural differences, communication and language barriers. Global services are provided by selecting one of the suitable global delivery options, i.e., the onshore model, nearshore model or offshore model. Experts typically choose one of the models based on the nature of the project and the needs of the customer. However, the vendors and clients lack an adequate decision support system that can assist them in making suitable sourcing decisions. Therefore, the current study presents a Multi-Criteria Decision Making (MCDM) model for offshore outsourcing decisions of application maintenance. To achieve our target, two systematic literature reviews were conducted that explored a list of 15 influencing factors. The identified factors were further evaluated in the outsourcing industry by performing an empirical study that resulted in a list of 10 critical success factors. We propose a sourcing framework based on the critical success factors that can assist decision makers in adopting a suitable sourcing strategy for the offshore outsourcing of application maintenance. In order to further enhance the decision-making process, the MCDM model is developed based on the Analytic Hierarchy Process (AHP). The MCDM model is evaluated with three case studies in highly reputable international companies, including IBM Stockholm, Sweden, Vattenfall AB, Stockholm, Sweden and a London based company in the United Kingdom. The outcomes of these case studies are further reviewed and validated by the outsourcing specialists in other firms. The proposed model is used as a decision support system that determines the ranking of sourcing alternatives and suggests the most suitable option for application maintenance offshoring.

scholarly journals BIM ON ARTIFICIAL INTELLIGENCE FOR DECISION SUPPORT IN E-HEALTH

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 207-214
Author(s):  
B. Plaß ◽  
C. Prudhomme ◽  
J. J. Ponciano
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Expert Knowledge ◽  
The Elderly ◽  
Living Environment ◽  
Information Modeling ◽  
The European Union ◽  
Living Space

Abstract. Looking ahead of 2070, the number of the elderly population will increase rapidly in the European Union and beyond. As society ages, it will be confronted to novel challenges related with other concerns like the concept aging in place that the majority of the elderly prefer. Concerning that, the living space must be adapted to the requirements of people with a disability, to support their relatives or friends that will become more and more important in future due to a lack of professional’s and both overstressed and expensive hospitals or nursing homes. Compounding this, those living space requirements are highly individual, depending on the disease. Our study focuses on a medical white box decision support system providing advice even for unknowledgeable users by evaluating the suitability of an elderly’s living environment in terms of their individual disease. In this paper, we propose tackling this issue with a decision support system linked to Building Information Modeling (BIM) and based on Artificial Intelligence using semantic technologies. The proposed approach's contribution is a reliable process that uses up-to-date 3D point cloud data of the person’s living environment and predicts suitable, non-suitable and adaptable zones therein according to different pathologies using formalised knowledge. We are able to provide deep expert knowledge linked from different domains inside a knowledge base and thus produce an outcome through BIM, which is understandable and helpful for two types of users, ordinary people concerned by the matter and building experts. We illustrate our methodology by a proof of concept concerning a wheel-chaired person.

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