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- Data analytics to advance the inference of origin–destination in public transport systems: tracing network vulnerabilities and age-sensitive trip purposesPublication . Cerqueira, Sofia; Arsenio, Elisabete; Barateiro, José; Henriques, RuiKnowing the passengers' final destinations, underlying motifs, and commuting habits is critical to optimise public transportation systems, guide urban planning and contribute to a more sustainable urban mobility. In entry-only Automated Fare Collection systems, the body of literature has focused on the spatial dimension by estimating alighting stops, overlooking the inference of robust alighting times. Moreover, discriminating between transfers and activities is pivotal for determining their ultimate destinations. However, current methods often struggle to adapt to the stochastic nature of passenger behaviour, further disregarding the multiplicity of routes and stops to access specific facilities and individual motivations. Further research is required to address an effective spatio-temporal and contextual inference in both challenges. With the above concerns in mind, this research uses data analytics to propose an enhanced methodology for the inference of OD matrices, with the final goal of providing a comprehensive view of OD mobility patterns across distinct age-sensitive profiles-youth, adults, and older adults. Our methodological framework integrates the following approaches: (i) alighting stop-and-time inference, (ii) ensembled model for transfer classification, (iii) indicators retrieved from statistical analysis of network vulnerabilities (e.g., number of transfers, walkability needs), frequent destinations and their underlying putative motifs against the city amenities and others points-of-interest. The reliability of alighting data (timestamp and location) inference is improved by integrating OpenStreetMap data and the past boarding data from bus and railway systems. Considering Lisbon as the target study case, we apply the methodology over smart card data collected both from metro and bus systems. A comparative analysis with state-of-the-art methods revealed that the enhanced framework for alighting and OD inference led to longer journey times for trips. Furthermore, throughout the day, the older adult group experiences longer transfer times on average compared to both the children and young adult segment and the adult segment.
- The balanced scorecard ontology: a semantic approach to enhance strategy managementPublication . Antunes, António Lorvão; Cardoso, Elsa; Barateiro, JoséThe Balanced Scorecard, developed in 1992 by Kaplan and Norton, has evolved into a communication and strategy execution system widely adopted by organizations across various industries. This article explores the use of an ontology to bridge the gap between strategy management and data within the Balanced Scorecard framework. The Balanced Scorecard Ontology is introduced to store, validate, and analyze knowledge, containing information about the strategy map and quantification frameworks, essential for evaluating the strategy execution. The proposed ontology is designed, developed, and evaluated using competency questions (CQs), and further validated by an online tool. Specifically, the proposed formalization of the Balanced Scorecard framework provides a semantic layer aimed at facilitating an effective Balanced Scorecard implementation, enabling accurate, traceable, and continuous monitoring and improvement of the strategy execution, based on a data-driven approach. The formalization of this knowledge through an ontology encompasses several advantages, such as improved interoperability and validation of the framework’s elements, inference of new knowledge, and enhanced communication between different stakeholders. In addition, managerial implications include ensuring alignment between the Balanced Scorecard and organizational goals, supporting compliance and governance efforts, improving communication and knowledge transfer, enhancing the strategic decision-making process, and facilitating the integration of data into the Balanced Scorecard.