Globally, the transportation and logistics sector is facing economic disruptions owing to geopolitical tensions and post-COVID-19 global economic downturns. This disruption places more pressure on ...transportation companies to review their work methods and processes. Coupling data and model-driven approaches is essential for developing effective and efficient resilience strategies. To address this issue, this study provides an overview of the appearance of simulation in business analytics. However, a thorough review of the literature based on the PRISMA search process allowed us to identify that none of the previous studies could highlight the role or evaluate the hybridization between business analytics and simulation and their joint use in freight transportation. Moreover, this study proposes a collaborative framework based on the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique to select a business analytics-enabled simulation architecture. This study contributes to the freight transport sector by setting up an updated list of criteria and sub-criteria necessary for business analytics evaluation and enriches the literature by applying the IF-AHP technique to a concrete case of implementing data analytics and simulation. This study also suggests future directions to enrich the academic literature and offers insights to improve the framework for other use cases.
Over time, Decision Support Systems have helped decision makers solve complex problems through Operational Research and Simulation. Nowadays, data explosion is having a profound effect on the ways in ...which many sectors operate. This advent of massive data gives rise to new concepts and requires new methods and analysis tools. In this paper, we highlight the role of simulation in Business Analytics. In a framework-based analytics, simulation is a technique that can be incorporated into predictive or prescriptive stage. For that, we have posed research questions to limit results to what give a comprehensive description of models, techniques and architectures used in the hybridization between simulation and business analytics. The presented analyses confirm that simulation remains an indispensable mechanism for adding value to analytics project and the coupling between the two techniques is in its embryonic phase. A conclusion presented prospects and future improvements found during the writing of the research.
Nowadays, Business Intelligence (BI) plays a key role in the decision-making chain because of what it offers in terms of data availability, structuring, analysis and presentation in the form of ...dashboards or Key Performance Indicators (KPI) to assist decision-making. Despite its advantages in terms of historicizing the company's activity, traditional BI tools do not allow us to project our business into the future and evaluate the impact of a decision on the entire activity of a company. Given this consideration, What-if analysis positions itself as a data-intensive simulation to examine the impact of a decision. In this article, we intend to highlight the role that simulation techniques can play in prescriptive analysis. Then, we present the different architectures that combine the use of simulation in an analytical environment. Finally, we also provide an idea of the future perspectives and challenges in simulation-based analytics.
The freight transport sector is facing more than ever major innovations and challenges. Digital transformation and analytics tend to optimize traditional work methods and accelerate workflows. This ...paper focuses on the problem of choosing an analytics solution that allows the prediction of future cases based on historical data and integrates packages that permit to run what-if simulations. Faced with a multitude of criteria required by freight transport professionals, we propose to solve it by implementing the Analytical Hierarchy Process-AHP method. The use of a collaborative approach during the AHP process allowed us to obtain relevant and accurate results.
