https://hdl.handle.net/10419/161795 2026-09-14T01:48:12Z 2026-09-14T01:48:12Z Tavana, Madjid https://hdl.handle.net/10419/185054 2023-12-18T02:28:49Z 2017-01-01T00:00:00Z

Title: Editorial Authors: Tavana, Madjid

2017-01-01T00:00:00Z Chakraborty, Subrata Mengersen, Kerrie Fidge, Colin Ma, Lin Lassen, David https://hdl.handle.net/10419/185051 2023-11-08T02:39:49Z 2016-01-01T00:00:00Z

Title: A Bayesian Network-based customer satisfaction model: A tool for management decisions in railway transport Authors: Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David Abstract: We formalise and present an innovative general approach for developing complex system models from survey data by applying Bayesian Networks. The challenges and approaches to converting survey data into usable probability forms are explained and a general approach for integrating expert knowledge (judgements) into Bayesian complex system models is presented. The structural complexities of the Bayesian complex system modelling process, based on various decision contexts, are also explained along with a solution. A novel application of Bayesian complex system models as a management tool for decision making is demonstrated using a railway transport case study. Customer satisfaction, which is a Key Performance Indicator in public transport management, is modelled using data from customer surveys conducted by Queensland Rail, Australia.

2016-01-01T00:00:00Z Baars, Thijs Mijnhardt, Frederik Vlaanderen, Kevin Spruit, Marco https://hdl.handle.net/10419/185052 2023-11-20T02:07:13Z 2016-01-01T00:00:00Z

Title: An analytics approach to adaptive maturity models using organizational characteristics Authors: Baars, Thijs; Mijnhardt, Frederik; Vlaanderen, Kevin; Spruit, Marco Abstract: Ever since the first incarnations of maturity models, critics have voiced several concerns with these frameworks. Indeed, a lack of model fit and oversimplification of the real world can be attributed to the rigidity of these models, which assumes that each organization that uses the framework is equal. This research investigates this fundamental rigidity from an analytics perspective, analysing in casu a focus area maturity matrix targeted at information security. The results show that organizational characteristics influence the maturity framework both in parts and as a whole significantly, concluding that current maturity frameworks have a poor model fit and advising that a maturity framework should account for the differences between the characteristics of their target organizations.

2016-01-01T00:00:00Z Giacchi, Evelina Corrente, Salvatore Di Stefano, Alessandro Greco, Salvatore La Corte, Aurelio Scatá, Marialisa https://hdl.handle.net/10419/161807 2023-12-16T02:51:39Z 2016-01-01T00:00:00Z

Title: A context-aware and social model of dynamic multiple criteria preferences Authors: Giacchi, Evelina; Corrente, Salvatore; Di Stefano, Alessandro; Greco, Salvatore; La Corte, Aurelio; Scatá, Marialisa Abstract: We discuss a social decision making model in which individuals, represented by nodes, interact with each other through ties in a social network. Each node takes its decisions considering a set of points of view in a multiple criteria decision making perspective. Our model suggests the interplay of the following two features in the decision making process: the dynamic nature and the context-awareness of decisions. The dynamic nature is the result of the interaction among nodes producing a changing in preferences. The context-awareness, instead, represents the capability to take into account the knowledge background exploited by nodes to take their decisions. Thus, the two factors affecting the dynamics of preferences are: the inclination of each node to be influenced by the other nodes in the network and the variability of the context-awareness. As a result, the network could oscillate between several configurations or it could converge to a fixed one. From this new social perspective of multiple criteria decision making, the behaviour of each node is represented by different parameters whose variation determines the dynamics of the social network. The proposed model could be applied to various socio-economic contexts, such as fashion economy, housing location and viral marketing.

2016-01-01T00:00:00Z