Managing Human Factors to Reduce Organisational Risk in Industry

Carpitella, Silvia; Carpitella, Fortunato; Certa, Antonella; Benítez, Julio; Izquierdo, Joaquín

doi:10.3390/mca23040067

Cited by 10 publications

(9 citation statements)

References 37 publications

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“…DEMATEL is helpful when dealing with complex systems, such as water networks, since they are characterised by many aspects/elements directly or indirectly interdependent with each other, and this condition makes hard many decision-making tasks. As asserted, for example, in [12], the use of DEMATEL supports the visualisation of interferences existing among the relevant aspects of a given problem, thereby helping comprehensive understanding of the intensity and direction of direct and indirect relations for each pair of factors under study. This technique deals with interactions through a step-by-step approach [13]; it has been widely applied in the literature for management problems characterised by the presence of heavy interdependence among elements [14][15][16][17]; and many developments of its application have been proposed in a wide number of fields (see [18][19][20], among others).…”

Section: Introduction and Literature Reviewmentioning

confidence: 93%

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Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence

Francés-Chust

Brentan

Carpitella

et al. 2020

Water

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Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes’ sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influence among the nodes. This analysis is performed within a multi-criteria decision-making approach: specifically, a herein proposed variant of DEMATEL, which uses fuzzy logic and builds comparison matrices derived from information obtained through leakage simulations of the network. We apply the proposal first to a toy example to show how the approach works, and then to a real-world case study.

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Section: Introduction and Literature Reviewmentioning

confidence: 93%

“…This accomplished, the traditional (crisp) DEMATEL method follows a procedure consisting on a number of steps. These steps are conceptually recalled here (readers can study them further, for example, in [12], among many other sources).…”

Section: Dematel-based Approach To Establish Interdependencies Among Sensorsmentioning

confidence: 99%

Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence

Francés-Chust

Brentan

Carpitella

et al. 2020

Water

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“…where I is the identity matrix. As observed, for example, in lim n→∞ N n = 0 [46], since the spectral radius of N is smaller than 1, being bounded by the maximum row and column sum. Then, as shown for instance by Meyer [47], the power series of the normalised direct relation matrix converges to (I -N) −1 .…”

mentioning

confidence: 81%

Decision-Making Tools to Manage the Microbiology of Drinking Water Distribution Systems

Carpitella

Olmo

Izquierdo

et al. 2020

Water

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This paper uses a two-fold multi-criteria decision-making (MCDM) approach applied for the first time to the field of microbial management of drinking water distribution systems (DWDS). Specifically, the decision-making trial and evaluation laboratory (DEMATEL) was applied removing the need for reliance on expert judgement, and analysed interdependencies among water quality parameters and microbiological characteristics of DWDS composed of different pipe materials. In addition, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) ranked the most common bacteria identified during trials in a DWDS according to their relative abundance while managing vagueness affecting the measurements. The novel integrated approach presented and proven here for an initial real world data set provides new insights in the interdependence of environmental conditions and microbial populations. Specifically, the application shows as the bacteria having associated the most significant microbial impact may not be the most abundant. This offers the potential for integrated management strategies to promote favourable microbial conditions to help safeguard drinking water quality.

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“…Moreover, von Malmborg [38] argued that an environmental management system can be understood not only as a technical tool for analytical management but also as a tool for communicative action and organizational learning. Carpitella et al [39] discussed organizational risk assessment in industrial environments by employing decision-making trial and evaluation laboratory method. Zhu and Sarkis [40] declared that GSCM tended to have win-win relationships in terms of environmental and economic performances in addition to providing an insight into the growing field of the relationship between environmental and operational practices and performance.…”

Section: Green Supply Chainmentioning

confidence: 99%

Quantitative Analysis of Key Performance Indicators of Green Supply Chain in FMCG Industries Using Non-Linear Fuzzy Method

et al. 2019

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Nowadays, along with increasing companies’ activities, one of the main environmental protective tools is green supply chain management (GSCM). Since fast-moving consumer goods (FMCG) companies are manufacturing materials that usually require special warehousing as well as different distribution systems, and since companies of food products tend to fall into this area, the safety of their manufactured materials is a vital global challenge. For this reason, organizations in addition to governments have realized the importance of the green supply chain in these industries. Therefore, the present study examines the key performance indicators (KPIs) of the green supply chain in the FMCG industry. There are several performance indicators for the green supply chain. In this study, the KPIs were extracted based on the literatures as well as the opinions of experts through which key indicators in FMCG industries were identified. Using the fuzzy decision -making trial and evaluation laboratory (DEMATEL) method, the relationships and interactions of these key indices were determined. Moreover, a fuzzy nonlinear mathematical modeling was used to investigate the significance of these indicators. It is revealed that the organizational environmental management factor has the highest priority.

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Managing Human Factors to Reduce Organisational Risk in Industry

Cited by 10 publications

References 37 publications

Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence

Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence

Decision-Making Tools to Manage the Microbiology of Drinking Water Distribution Systems

Quantitative Analysis of Key Performance Indicators of Green Supply Chain in FMCG Industries Using Non-Linear Fuzzy Method

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