scholarly journals A Methodological Approach to Evaluate Structural Building Projects Through the Environmental Economic Index

2021 ◽  
Author(s):  
José Manuel Romo Orozco ◽  
Julio Contreras ◽  
José Ramón Corona Armenta ◽  
Luis Fernando Morales Mendoza
Keyword(s):  
Decision Making ◽  
Environmental Economic ◽  
Construction Industry ◽  
Methodological Approach ◽  
Economic Index ◽  
Building Projects ◽  
Development Goals ◽  
Economic Function ◽  
Support Decision Making

Abstract The construction industry has a relevant social and economic function and has become fundamental to achieving the Paris Agreement and the United Nations Sustainable Development Goals. This industry contributes significantly to global CO2 emissions due to embodied and operating energy. There are methodologies to evaluate them, but they lack integration with other variables. In the case of buildings and assessing safety and costs, environmental assessment needs to be incorporated; current methodologies are complex to implement and, in general, costly in terms of economic and human resources. This research proposes the Environmental Economic Index (EEI) to evaluate structural building projects and support decision-making, obtained from a simplified methodology. In the case study, located in San Luis Potosi, Mexico, the same building structure was designed to subject to different operational loads and lateral forces, with structural concrete and structural steel. For this building, the concrete structure subject to seismic actions had a better result when estimating the EEI and comparing it with the other structural alternatives. The contribution of this work is to develop a simplified methodology to evaluate structural projects in the design phase, which integrates economic, environmental, and safety variables and supports decision-making in designers and real estate developers.

A methodological approach to evaluate structural building projects through the Environmental Economic Index

2021 ◽  
Author(s):  
José Manuel Romo-Orozco ◽  
Julio César Contreras-Jiménez ◽  
José Ramón Corona-Armenta ◽  
Luis Fernando Morales-Mendoza
Keyword(s):  
Environmental Economic ◽  
Methodological Approach ◽  
Economic Index ◽  
Building Projects

scholarly journals How Cognitive Biases Influence the Data Verification of Safety Indicators: A Case Study in Rail

Safety ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 69
Author(s):  
Burggraaf ◽  
Groeneweg ◽  
Sillem ◽  
van Gelder
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Decision Makers ◽  
Human Cognition ◽  
Quality Data ◽  
Verification Process ◽  
Support Decision Making ◽  
Good Quality Data

The field of safety and incident prevention is becoming more and more data based. Data can help support decision making for a more productive and safer work environment, but only if the data can be, is and should be trusted. Especially with the advance of more data collection of varying quality, checking and judging the data is an increasingly complex task. Within such tasks, cognitive biases are likely to occur, causing analysists to overestimate the quality of the data and safety experts to base their decisions on data of insufficient quality. Cognitive biases describe generic error tendencies of persons, that arise because people tend to automatically rely on their fast information processing and decision making, rather than their slow, more effortful system. This article describes five biases that were identified in the verification of a safety indicator related to train driving. Suggestions are also given on how to formalize the verification process. If decision makers want correct conclusions, safety experts need good quality data. To make sure insufficient quality data is not used for decision making, a solid verification process needs to be put in place that matches the strengths and limits of human cognition.

scholarly journals A Predictive Analytics Model for E-commerce Sales Transactions to Support Decision Making: A Case Study

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Shereen Morsi
Keyword(s):  
Decision Making ◽  
Predictive Analytics ◽  
Strategic Decisions ◽  
Business Decision ◽  
Innovative Capabilities ◽  
Data Volume ◽  
Precautionary Measures ◽  
Support Decision Making

Given the significant growth in electronic commerce, firms are seeking technological innovations and innovative capabilities to deal concurrently with the data’ volume generated and gaining insights from it for better decisions. Although recent studies identify predictive analytics as becoming the keystone of all business decision making and a crucial aspect in firms by it is a possible means for driving strategic decisions. Significant inroads into the interrelationships between capabilities and the execution of a pathway to an analytical capability to many Egyptian e-commerce businesses have yet to be made. Therefore, this paper aims to shed light on the importance and the role of using predictive analytics models in the Egyptian e-commerce firms where these tools became dominant resources for gaining valuable knowledge for better decision making by precautionary measures from prediction rates and different applications that have been applied by global e-commerce firms. The aim of the paper was achieved by building a predictive analytics model for sales forecasting by tackling to one of the e-commerce company in Egypt, and the online transaction dataset has been analyzed. The result obtained from the model has been displayed, and some insights extracted from the prediction model have been explained.

scholarly journals BIG DATA AND DECISION-MAKING SUPPORT

2021 ◽  
Vol 2 ◽  
pp. 87-92
Author(s):  
Peter Procházka
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Methodological Approach ◽  
Timely Manner ◽  
Domestic Literature ◽  
Risk Definition ◽  
Similar Solutions ◽  
Support Decision Making ◽  
Big Data Technology

INTRODUCTION: Nowadays, Big Data is created in previously unimaginable quantities. Newly generated data from various Internet of Things (IoT) sensors and their use have never reached their current dimensions. Along with this trend, the availability of devices capable of collecting this data increases, the time for their evaluation is reduced and the volume of data collected at the same time increases. The most important task of research and development in this area is to bring solutions suitable for processing large amounts of data because our current storage and processing capabilities are limited and unable to compete with the storage, processing and publication of the resulting data. OBJECTIVES: Point out the importance of implementing Big Data technology. METHODS: To achieve the goal, the following methodological approach was chosen: study and processing of foreign and domestic literature, acquaintance with similar solutions for data processing, definition of Big Data and IoT, proposal for using Big Data solution to support decision-making, risk definition and evaluation. RESULTS: With the growing amount of disparate and incoherent data and the further growth of the Internet of Things, it is now almost impossible to evaluate all available information correctly and in a timely manner. Without this knowledge, the company loses its competitive advantage and is unable to respond in a timely manner to client requests. CONCLUSION: Implementing a solution for processing Big Data to support decision-making in the company is a complex process. As part of the implementation and use of the Big Data solution to support decision-making, the company must be prepared for the emergence of various problems. We can assume that Big Data technology will constantly be evolving in terms of streamlining analytical tools for obtaining information from large volumes of generated data. Therefore, it is appropriate to create space for the implementation of Big Data technology.

scholarly journals PARAMETRIC PARADIGMA: EXCEPTIONAL COFFERED CEILING ARCHITECTURE VS HBIM

2021 ◽  
Author(s):  
Olga Rosignoli ◽  
Barbara Scala ◽  
Daniele Treccani ◽  
Andrea Adami ◽  
Laura Taffurelli ◽  
...  
Keyword(s):  
Decision Making ◽  
Scientific Community ◽  
Conservation Management ◽  
Operational Strategies ◽  
Transcription Process ◽  
Combined Use ◽  
Decision Making Processes ◽  
Historical Heritage ◽  
Support Decision Making

The scientific community is confirming the advantages of using BIM in the processes of conservation, management, and intervention over architectural historical heritage. However, many difficulties remain in the transcription process of elements of the built environment, especially when the objective of the model is to support decision-making processes in restoration  operations. Even for apparently simple elements the procedures are not trivial; the need to define the most adequate operational strategies remains. In the context of this study, a possible approach concerning the documentation of a coffered ceiling has been proposed, a case study which takes into consideration the need to discretize information (to make it effective, transmissible, and understandable) and the potential offered by the combined use of further software automatization.

scholarly journals Evaluating Social Housing Retrofit Options to Support Clients’ Decision Making—SIMPLER BIM Protocol

2019 ◽  
Vol 11 (9) ◽  
pp. 2507 ◽  
Author(s):  
Patricia Tzortzopoulos ◽  
Ling Ma ◽  
João Soliman Junior ◽  
Lauri Koskela
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Cost Estimation ◽  
Social Housing ◽  
Integrated Approach ◽  
Energy Performance ◽  
Building Information ◽  
The Uk ◽  
Support Decision Making

The UK government made significant commitments to upgrading the energy efficiency of seven million British homes by 2020, aiming at reducing carbon emissions and addressing fuel poverty. One alternative to achieve better energy performance in existing houses is retrofit. However, there are difficulties associated with retrofitting social housing. It is currently challenging to compare scenarios (retrofit options) considering costs, potential energy efficiency gains, and at the same time minimising disruption to users. This paper presents a Building Information Modelling (BIM) protocol aimed to support decision making by social housing owners. It adopts BIM to simulate alternative retrofit options, considering: (a) potential reductions in energy consumption, (b) 4D BIM for retrofit planning and reduction of users’ disruption and (c) simulation of costs. A what-if scenario matrix is proposed to support decision making in the selection of social housing retrofit solutions, according to client and users’ needs. A case study of the retrofit of a mid-terrace house is presented to demonstrate the workflow. The main output of the work is the BIM protocol, which can support client decision making in diverse social housing retrofit projects, considering all three elements (energy simulation, planning for reduced disruption and cost estimation) in an integrated fashion. Such an integrated approach enables clients to make better informed decisions considering diverse social housing retrofit options through a simple process using readily available BIM technology.

scholarly journals Assessing and Prioritising Delay Factors of Prefabricated Concrete Building Projects in China

2018 ◽  
Vol 8 (11) ◽  
pp. 2324 ◽  
Author(s):  
Yingbo Ji ◽  
Lin Qi ◽  
Yan Liu ◽  
Xinnan Liu ◽  
Hong Li ◽  
...  
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Construction Projects ◽  
Analytic Network Process ◽  
Building Projects ◽  
Factors Affecting ◽  
Expert Interview ◽  
Concrete Building ◽  
Network Process ◽  
Improved Performance

Prefabricated construction has been widely accepted as an alternative to conventional cast-in-situ construction, given its improved performance. However, prefabricated concrete building projects frequently encounter significant delays. It is, therefore, crucial to identify key factors affecting schedule and explore strategies to minimise the schedule delays for prefabricated concrete building projects. This paper adopts the decision-making trial and evaluation laboratory (DEMATEL) model and analytic network process (ANP) method to quantify the cause-and-effect relationships and prioritise the key delay factors in terms of their importance in the Chinese construction industry. The DEMATEL model evaluates the extent to which each factor impacts other factors. The quantified extents are then converted into a prioritisation matrix through ANP. The delay factors of prefabricated construction projects are selected and categorised based on a literature review and an expert interview. Questionnaires are then implemented to collect the data. The results reveal that the issue of inefficient structural connections for prefabricated components is found to be the most significant factor and most easily affected by other delay factors. This research also suggests prioritising major delay factors, such as ‘lack of communication among participants’ and ‘low productivity’, in the Chinese construction industry during scheduling control. Overall, this research contributes an assessment framework for decision making in the scheduling management of prefabricated construction.

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