Big Data Analytics (BDA) has evolved from a predominantly technical batch function into a socio-technical capability integrating cloud-native platforms, stream processing, Lakehouse architecture, machine learning operations (MLOps), visualization, go...
The rapid proliferation of wearable sensors and advanced tracking technologies has revolutionized data collection in elite sports, enabling continuous monitoring of athletes’ physiological and biomechanical states. This study proposes a compreh...
This paper presents a systematic approach to developing big data analytics for manufacturing process-relevant decision-making activities from the perspective of smart manufacturing. The proposed analytics consist of five integrated system components:...
Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world’s growing population while limiting environmental pollution. The aim of th...
Autonomous supply chains (ASC) are the next generation of digitally empowered logistics and operations systems that can make adaptive, data-driven, and intelligent decisions. Innovations in artificial intelligence (AI), digital twins (DT), and predic...
The integration of the industrial Internet and big data analytics is reshaping enterprise decision-making models and providing new momentum for the transformation and upgrading of traditional manufacturing industries. In this study, a decision suppor...
Cognitive biases continue to pose significant challenges in executive decision-making, often leading to strategic inefficiencies, misallocation of resources, and flawed risk assessments. While traditional decision-making relies on intuition and exper...
Interest in smart cities (SCs) and big data analytics (BDA) has increased in recent years, revealing the bond between the two fields. An SC is characterized as a complex system of systems involving various stakeholders, from planners to citizens. Wit...
This narrative review examines how big data analytics supports geospatial decision-making in smart cities through the combined roles of spatial data foundations, GeoAI methods, and urban digital twins. Methodologically, the article follows a structur...
Inefficiencies and low productivity persist in the construction industry due to limited digital integration and weak data use in decision-making. This study examines how internal data analytics, such as the systematic use of organisational data-like...
The managerial and environmental studies conducted in the energy research area reflect its substantial importance, particularly when optimizing and modifying consumption patterns, transitioning to renewable sources away from fossil ones, and designin...
Agriculture firms face an array of struggles, most of which are financial; thus, the role of decision making is discerned as highly important. The agroeconomic indexes (AEIs) of Agriculture Employment Rate (AER), Chemical Product Price Index (CPPI),...
Ecuador’s agricultural sector plays a strategic role in the national economy; however, agricultural data remains fragmented across heterogeneous and isolated sources, limiting integrated analysis and evidence-based decision-making. This study p...
This study introduces a novel informatics framework for assessing regional sustainability by integrating Twin Mean-Variance Two-Stage Data Envelopment Analysis (TMV-TSDEA) with a desirability-based decision analytics system. The model evaluates both...
Artificial Intelligence (AI)-based educational systems increasingly support personalised learning, adaptive feedback, and learning analytics. However, these capabilities are often addressed separately, with comparatively less attention paid to their...
In this paper, an intelligent data analysis method for modeling and optimizing energy efficiency in smart buildings through Data Analytics (DA) is proposed. The objective of this proposal is to provide a Decision Support System (DSS) able to support...
Business intelligence (BI) and business process management (BPM) have traditionally addressed related managerial problems from partly separate perspectives, while big data analytics, process mining, generative AI, and decision support systems are inc...
Management Information Systems (MIS) are increasingly expected to support real-time, evidence-based decision-making and to automate routine workflows. Nevertheless, many organizations still struggle to transform heterogeneous, high-velocity data into...
Research on augmented reality (AR) and mixed reality (MR) demonstrated their potential to support decision-making in construction. However, most efforts emphasized technological advancements, often overlooking how to present and interact with informa...
Geopolitical conflict, tariff shocks, and rapidly evolving environmental, social, and governance (ESG) regulation have made global supply chains markedly less predictable. This study examined how manufacturing supply chain decision-makers perceive si...
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This research identifies patterns of conflicting interorganisational information exchange requirements in precinct modelling and simulation (M&S) depending on the interaction and expertise of the collaborating actors. Internationally surveying le...
In recent years, much effort has been put into developing dedicated dashboards for instructors, in which data about students’ activity are presented. However, in many cases, such endeavors take a top-down approach and do not involve instructors...
This study presents a comparative analysis of urban land-use sustainability in Barcelona and Izmir using a four-tier Decision Support Framework (DSF) supported by automated Google Earth Engine workflows. The framework integrates open satellite data,...
With the advent of the first pandemic wave of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the question arises as to whether the spread of the virus will be controlled by the application of preventive measures or will follow a differ...
Using biomass ash to partially replace cement reduces the cement industry’s environmental impact and prevents these agro-industrial wastes from ending up in landfills, eroding soils, or being openly burned. This research aims to select three bi...
Effective construction-equipment monitoring requires persistent equipment-level information linking visual observations to utilization and planning decisions. This study develops and evaluates an identity-centered framework integrating ten-class YOLO...
Learning analytical chemistry requires not only mastery of analytical and calculation methods but also the ability to make consistent experimental decisions. This study tested a process-oriented assessment framework based on the experimental decision...
We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The...
Decision-making problems in complex environments are often characterised by uncertainty, vagueness, and dynamically evolving information. In such contexts, decision makers may express hesitant and fluctuating evaluations over time, which cannot be ad...
This paper introduces a pioneering model that merges coupled Markov chains (CMC) with the fuzzy analytic hierarchy process (FAHP) to enhance multi-criteria decision making (MCDM) amidst the dynamic interplay of criteria. Traditional MCDM frameworks o...
The Analytic Hierarchy Process (AHP) multicriteria method can be cognitively demanding for large-scale decision problems due to the requirement for the decision maker to make pairwise evaluations of all alternatives. To address this issue, this paper...
Tech mining is an analytical method of technology monitoring that can reveal technology trends in different industries. Patent databases are the major sources for information retrieval by tech mining methods. The majority of the commercially viable r...
Prescriptive analytics uses predictions to recommend decisions, but its superiority over the current approach is commonly evaluated on historical data in which only the cost of the implemented decision is observed. When a prescribed decision differs...
The increasing outsourcing of critical activities in the mining industry has transformed contractor selection into a strategic decision that is closely associated with operational risk management and the integration of critical capabilities within hi...
Clinical prediction rules often suffer from a translation gap, balancing high-dimensional statistical accuracy against practical bedside interpretability. This study presents the Surgical Complication Risk Index (S-CRI), an explainable, data-decouple...
The relevant role of freight lorry parking facilities as a tool to reduce nuisances and impact of economic activities in densely populated urban areas is widely recognised in the literature. Nevertheless, the literature currently lacks specific contr...
In response to the requirement to address the global climate crisis in urban areas caused by the logistics sector, an increasing number of governments around the world have begun aggressive strategic actions to encourage manufacturers and consumers t...
Following the financial crisis of the last decade and the increasing complexity of financial products, the European Union has introduced investor protection tools that require professionals to carry out a client profiling process. The aim is to offer...
The Airport ground handling services (AGHS) equipment supplier provider selection requires a safety guarantee in terms of the daily operations AGHS provider. AGHS providers seek to avoid aircraft damage and airline delays and ensure the provision of...
In modern systems, there is a tendency to model issues more accurately with low computational cost and considering multiscale decision-making which increases the complexity of the optimization. Therefore, it is necessary to develop tools to cope with...
In this review, we discuss the role of sensor analytics point solutions (SNAPS), a reduced complexity machine-assisted decision support tool. We summarize the approaches used for mobile phone-based chemical/biological sensors, including general hardw...
The analytic hierarchy process (AHP) has been a widely used method for handling multi-criteria decision-making (MCDM) problems since the 1980s. However, it postulates that criteria are independent and static, which may not always hold true in realist...
Organizations may examine both past and present data with the aid of information management, giving them access to all the knowledge they need to make sound strategic choices. For the majority of contemporary enterprises, using data to make relevant,...
This research presents an innovative data fusion model that utilizes Monte Carlo simulations (MC) and the Gray Analytic Hierarchy Process (G-AHP) to address the complexity and uncertainty in decision-making processes, particularly in selecting sustai...
Industries have to integrate environmental, social, and economic aspects into their supply chain management to achieve sustainability. Hence, the industry needs to take appropriate actions in choosing the right suppliers. The aim of this study is to...
This paper presents a novel development methodology for artificial intelligence (AI) analytics in energy management that focuses on tailored explainability to overcome the “black box” issue associated with AI analytics. Our approach addre...
Additive manufacturing (AM) became widespread through several organizations due to its benefits in providing design freedom, inventory improvement, cost reduction, and supply chain design. Process planning in AM involving various AM technologies is a...
Data science can help farmers when making a decision about tractor purchase. Buying a tractor represents a big investment for farmers, and price is one of their main concerns. This study presents the development of a web-based decision support tool (...
Bridge expansion and contraction installation (BECI) has proved to be an indispensable component of bridge structures due to its stability, comfort, and durability benefits. At present, conventional replacement technologies for modular-type, comb pla...
E-Learning is a popular computer-based teaching–learning system that has been rapidly gaining global attention during and post COVID-19. The leaping changes in digital technology have enabled E-Learning to become more effective in recent years....
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