A CONCEPTUAL MODEL OF BARRIERS TO DATA-DRIVEN BUSINESS INNOVATIONS

2018 ◽  
Vol 2018 ◽  
pp. 714-715
Author(s):  
Hallikainen Heli ◽  
◽  
Laukkanen Tommi
Keyword(s):  
Conceptual Model ◽  
Data Driven

scholarly journals ASSESSMENT OF RAINFALL-RUNOFF SIMULATION MODEL BASED ON SATELLITE ALGORITHM

2015 ◽  
Vol XL-1-W5 ◽  
pp. 529-541
Author(s):  
A. R. Nemati ◽  
M. Zakeri Niri ◽  
S. Moazami
Keyword(s):  
Conceptual Model ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Data Driven ◽  
Support Vector ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Research Fields ◽  
Hydrology And Water Resources ◽  
Trmm 3B42

Simulation of rainfall-runoff process is one of the most important research fields in hydrology and water resources. Generally, the models used in this section are divided into two conceptual and data-driven categories. In this study, a conceptual model and two data-driven models have been used to simulate rainfall-runoff process in Tamer sub-catchment located in Gorganroud watershed in Iran. The conceptual model used is HEC-HMS, and data-driven models are neural network model of multi-layer Perceptron (MLP) and support vector regression (SVR). In addition to simulation of rainfall-runoff process using the recorded land precipitation, the performance of four satellite algorithms of precipitation, that is, CMORPH, PERSIANN, TRMM 3B42 and TRMM 3B42RT were studied. In simulation of rainfall-runoff process, calibration and accuracy of the models were done based on satellite data. The results of the research based on three criteria of correlation coefficient (R), root mean square error (RMSE) and mean absolute error (MAE) showed that in this part the two models of SVR and MLP could perform the simulation of runoff in a relatively appropriate way, but in simulation of the maximum values of the flow, the error of models increased.

scholarly journals A validated model for the scoping process of quality requirements: a multi-case study

2021 ◽  
Vol 26 (2) ◽  
Author(s):  
Thomas Olsson ◽  
Krzysztof Wnuk ◽  
Slinger Jansen
Keyword(s):  
Conceptual Model ◽  
Success Factors ◽  
Ad Hoc ◽  
Assessment Model ◽  
Data Driven ◽  
Quality Requirements ◽  
Software Products ◽  
Improvement Potential ◽  
Do So

AbstractQuality requirements are vital to developing successful software products. However, there exist evidence that quality requirements are managed mostly in an “ad hoc” manner and down-prioritized. This may result in insecure, unstable, slow products, and unhappy customers. We have developed a conceptual model for the scoping process of quality requirements – QREME – and an assessment model – Q-REPM – for companies to benchmark when evaluating and improving their quality requirements practices. Our model balances an upfront forward-loop with a data-driven feedback-loop. Furthermore, it addresses both strategic and operational decisions. We have evaluated the model in a multi-case study at two companies in Sweden and three companies in The Netherlands. We assessed the scoping process practices for quality requirements and provided improvement recommendations for which practices to improve. The study confirms the existence of the constructs underlying QREME. The companies perform, in the median, 24% of the suggested actions in Q-REPM. None of the companies work data-driven with their quality requirements, even though four out of five companies could technically do so. Furthermore, on the strategic level, quality requirements practices are not systematically performed by any of the companies. The conceptual model and assessment model capture a relevant view of the quality requirements practices and offer relevant improvement proposals. However, we believe there is a need for coupling quality requirements practices to internal and external success factors to motive companies to change their ways of working. We also see improvement potential in the area of business intelligence for QREME in selecting data sources and relevant stakeholders.

scholarly journals Tiedonkäytön ilmiöitä ammattikorkeakoulujen opinnäytetöissä. Aineistolähtöinen tarkastelu ja käsitteellinen mallinnus

2018 ◽  
Vol 37 (1) ◽  
Author(s):  
Juha Kämäräinen
Keyword(s):  
Applied Sciences ◽  
Conceptual Model ◽  
Qualitative Data ◽  
Information Use ◽  
Data Driven ◽  
Universities Of Applied Sciences ◽  
Data Driven Approach

FM Juha Kämäräisen informaatiotutkimuksen alaan kuuluva väitöskirja Tiedonkäytön ilmiöitä ammattikorkeakoulujen opinnäytetöissä. Aineistolähtöinen tarkastelu ja käsitteellinen mallinnus (Information use phenomena in bachelor theses at the Finnish universities of applied sciences. Qualitative data driven approach toward a conceptual model) tarkastettiin 13.1.2018 Oulun yliopiston humanistisessa tiedekunnassa. Vastaväittäjinä toimivat ylikirjastonhoitaja, dosentti Kimmo Tuominen (Helsingin yliopisto) ja dosentti Seppo Raiski (Tampereen yliopisto) ja kustoksena kirjastonjohtaja, dosentti Jarmo Saarti (Itä-Suomen yliopisto). Väitöskirja on julkaistu sarjassa Acta Universitatis Ouluensis. B, Humaniora ja se on luettavissa myös Oulun yliopiston Jultika-julkaisuarkistossa osoitteessa http://urn.fi/urn:isbn:9789526217536

A 3D Multi-Source Conceptual Model to Support the Remediation of a Jet Fuel Contaminated Site

2020 ◽  
Author(s):  
Paolo Ciampi ◽  
Carlo Esposito ◽  
Giorgio Cassiani ◽  
Marco Petrangeli Papini
Keyword(s):  
Conceptual Model ◽  
Real Time ◽  
Source Model ◽  
Aviation Fuel ◽  
Data Driven ◽  
Contaminated Site ◽  
Multiscale Approach ◽  
Illustrative Case ◽  
Process Data ◽  
Data Set

<p>The management of a contaminated site requires to integrate simultaneously the information related to the hydrogeophysical sphere in all its dimensions. The construction of a 3D multidisciplinary geodatabase and the realization of an integrated model constitute the tools for the management, the fusion, the integration, and the analysis of multi-source data. The research aims to demonstrate the contributions of a multiple lines approach leading to the refinement of the Conceptual Site Model (CSM), the assessment of contamination, and successful remediation of a polluted site. An illustrative case history is here presented. It concerns the military airport of Decimomannu (Cagliari, Italy), affected by various aviation fuel (jet phuel-JP8) spills in 2007 (40000 L), in 2009 (5000 L), and in 2010 (5000 L). A multiscale approach was followed for the creation of a 3D hydrogeophysical model which acts as an effective “near real time” decision support system able to manage and release data during the different remediation phases from the site characterization up to the proper remediation intervention, all by allowing the user to view, query and process data in 3D space. The construction of a multi-source conceptual model along with Laser Induced Fluorescence (LIF) and Electrical Resistivity Tomography (ERT) capture the information related to the hydrogeochemical sphere in all its dimensions. The 3D pseudo-real visualization catches the high resolution characterization of geological eterogeneity and contaminated bodies at the scale of pollution mechanisms and decontamination processes. The physicochemical and data-driven model, which links geophysical signals to contaminant characteristics within contaminated porous media, explains the observed contaminant-geophysical behaviour. The interpretation of contaminant dynamic has strong implications for the reliability of the CSM, affecting the selection and the performance of remediation strategy. The display of integrated data allows a real-time interaction with the multi-source model (and the 3D geodatabase), to extract useful information for the decision-making processes during the different stages of remediation. The rich data set, and the data-driven models comprise, collect, and establish a connection between the environmental variables. They optimize the contribution of each aspect and support unequivocally the design and the adoption of an effective and sustainable clean-up intervention.</p>

Critical data-driven decision making: A conceptual model of data use for equity

2021 ◽  
Vol 99 ◽  
pp. 103272
Author(s):  
Stephanie L. Dodman ◽  
Katy Swalwell ◽  
Elizabeth K. DeMulder ◽  
Jenice L. View ◽  
Stacia M. Stribling
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Data Use ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Critical Data

scholarly journals Are the States United? An Analysis of U.S. Hotels’ Offers Through TripAdvisor’s Eyes

2019 ◽  
Vol 43 (7) ◽  
pp. 1112-1129 ◽  
Author(s):  
Sérgio Moro ◽  
Fernando Batista ◽  
Paulo Rita ◽  
Cristina Oliveira ◽  
Ricardo Ribeiro
Keyword(s):  
Support Vector Machine ◽  
Customer Satisfaction ◽  
Conceptual Model ◽  
Empirical Data ◽  
Data Driven ◽  
Support Vector ◽  
Web Scraping ◽  
The U.S

This empirical data-driven research aims to unveil thought-provoking insights on the U.S. hotel offer across its 50 states. Information of more than 30,000 hotels was collected through web scraping from TripAdvisor. Using such data, 50 support vector machine models were trained to model the TripAdvisor score, one per state, to assess the convergent and divergent factors in customer satisfaction across all the U.S. states. A conceptual model is proposed and validated through the data-driven support vector machine models developed for each state to identify convergent features across the states to explain customer satisfaction (here represented by TripAdvisor score). Hotel size, price, and stars are not moderated by the location, expressed by the corresponding state, although these highly influence satisfaction, whereas both hotel number of published photos and the amenities are affected by the location. Thus, adaptation issues were found regarding amenities and published photos within each state’s offer.

The Effects of Accounting Information on Individuals' Perceptual Processes

1992 ◽  
Vol 7 (1) ◽  
pp. 67-95 ◽  
Author(s):  
Waymond Rodgers
Keyword(s):  
Conceptual Model ◽  
Goal Attainment ◽  
Structural Model ◽  
Accounting Information ◽  
Decision Makers ◽  
Financial Accounting ◽  
Data Driven ◽  
Future Research ◽  
Decision Choices ◽  
Decision Making Processes

This research focuses on the influence of decision makers' perceptual processes on their decision choices when they are presented with financial accounting information. A conceptual model which depicted perceptual and judgmental processes was used to capture individuals' decision-making processes. A covariance structural model of the processes graduate students used to reach loan decisions was examined through measures designed to test the proposed conceptual model. Also, a multigroup analysis was used to compare whether individuals with a more data-driven perceptual approach would differ from those with a more conceptually driven perceptual approach when making loan decisions. The results indicated that their approaches caused different loan assessments of financial accounting information. The results also indicated that data-driven types outperformed the conceptually driven types. The relative usefulness of the conceptual model was discussed, and general suggestions for future research on perceptual processes and goal attainment were offered.

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