scholarly journals Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jana Fabianová ◽  
Peter Kačmáry ◽  
Vieroslav Molnár ◽  
Peter Michalik
Keyword(s):  
Input Data ◽  
Impact Analysis ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Software Tool ◽  
Data Uncertainty ◽  
Business Outcomes ◽  
Starting Point ◽  
The Impact

Abstract Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

scholarly journals Multi-hazard risk assessment for roads: probabilistic versus deterministic approaches

2020 ◽  
Vol 20 (11) ◽  
pp. 3135-3160
Author(s):  
Stefan Oberndorfer ◽  
Philip Sander ◽  
Sven Fuchs
Keyword(s):  
Risk Assessment ◽  
Road Safety ◽  
Input Data ◽  
Probabilistic Approach ◽  
Transport Infrastructure ◽  
Data Uncertainty ◽  
European Alps ◽  
Hazard Risk ◽  
The Impact

Abstract. Mountain hazard risk analysis for transport infrastructure is regularly based on deterministic approaches. Standard risk assessment approaches for roads need a variety of variables and data for risk computation, however without considering potential uncertainty in the input data. Consequently, input data needed for risk assessment are normally processed as discrete mean values without scatter or as an individual deterministic value from expert judgement if no statistical data are available. To overcome this gap, we used a probabilistic approach to analyse the effect of input data uncertainty on the results, taking a mountain road in the Eastern European Alps as a case study. The uncertainty of the input data are expressed with potential bandwidths using two different distribution functions. The risk assessment included risk for persons, property risk and risk for non-operational availability exposed to a multi-hazard environment (torrent processes, snow avalanches and rockfall). The study focuses on the epistemic uncertainty of the risk terms (exposure situations, vulnerability factors and monetary values), ignoring potential sources of variation in the hazard analysis. As a result, reliable quantiles of the calculated probability density distributions attributed to the aggregated road risk due to the impact of multiple mountain hazards were compared to the deterministic outcome from the standard guidelines on road safety. The results based on our case study demonstrate that with common deterministic approaches risk might be underestimated in comparison to a probabilistic risk modelling setup, mainly due to epistemic uncertainties of the input data. The study provides added value to further develop standardized road safety guidelines and may therefore be of particular importance for road authorities and political decision-makers.

scholarly journals Electrical Load Forecast by Means of LSTM: The Impact of Data Quality

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 91-101
Author(s):  
Alfredo Nespoli ◽  
Emanuele Ogliari ◽  
Silvia Pretto ◽  
Michele Gavazzeni ◽  
Sonia Vigani ◽  
...  
Keyword(s):  
Forecast Accuracy ◽  
Electric Load ◽  
Electrical Load ◽  
Autocorrelation Analysis ◽  
Load Forecast ◽  
Error Metrics ◽  
Input Dataset ◽  
Accurate Forecast ◽  
The Impact

Accurate forecast of aggregate end-users electric load profiles is becoming a hot topic in research for those main issues addressed in many fields such as the electricity services market. Hence, load forecast is an extremely important task which should be understood more in depth. In this research paper, the dependency of the day-ahead load forecast accuracy on the basis of the data typology employed in the training of LSTM has been inspected. A real case study of an Italian industrial load with samples recorded every 15 min for the year 2017 and 2018 was studied. The effect in the load forecast accuracy of different dataset cleaning approaches was investigated. In addition, the Generalised Extreme Studentized Deviate hypothesis testing was introduced to identify the outliers present in the dataset. The populations were constructed on the basis of an autocorrelation analysis that allowed for identifying a weekly correlation of the samples. The accuracy of the prediction obtained from different input dataset has been therefore investigated by calculating the most commonly used error metrics, showing the importance of data processing before employing them for load forecast.

scholarly journals Pricing Strategies of Multichannel Apparel Supply Chain Based on Showrooming and Information Sharing

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Shanshan Wang ◽  
Tian Luo ◽  
Daofang Chang
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Service Level ◽  
Clothing Industry ◽  
Pricing Strategies ◽  
Information Barriers ◽  
The Impact ◽  
Share Information

This paper examines the influence of information forecast accuracy on the profits of the supply chain under the circumstance of a multichannel apparel supply chain. Due to the emergence of multichannel, customer showrooming behavior is becoming increasingly prevalent. For example, consumers usually buy garments online after experiencing the service in the traditional bricks and mortar in the clothing industry. Meanwhile, there are often information barriers between the manufacturer and the retailer, which will affect enterprise decision-making. To solve these problems, this paper mainly investigates the information sharing and customer showrooming phenomenon, which includes four models: no information sharing without showrooming model (NN), information sharing without showrooming model (SN), no information sharing with showrooming model (NS), and information sharing with showrooming model (SS). The numerical analysis shows that under the impact of the forecast error, information sharing between channel members is more favorable than no information sharing when parameters satisfy certain conditions. From the perspectives of the retailer, the manufacturer, and the whole supply chain, customer showrooming behavior will bring them less profit. These conclusions mean that the retailer should share information with the manufacturer and adjust their service level and sales price to alleviate the effect of showrooming.

MoDSEL

2012 ◽  
pp. 572-594
Author(s):  
Ersin Er ◽  
Bedir Tekinerdogan
Keyword(s):  
Software Development ◽  
Impact Analysis ◽  
Software Evolution ◽  
Academic Research ◽  
Model Driven ◽  
Model Driven Software Development ◽  
Basic Concepts ◽  
The Impact ◽  
Development And Evolution

Model-Driven Software Development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. Like conventional non-MDSD practices, MDSD systems are also subject to changing requirements and have to cope with evolution. In this chapter, the authors provide a scenario-based approach for documenting and analyzing the impact of changes that apply to model-driven development systems. To model the composition and evolution of an MDSD system, they developed the so-called Model-Driven Software Evolution Language (MoDSEL) which is based on a megamodel for MDSD. MoDSEL includes explicit language abstractions to specify both the model elements of an MDSD system and the evolution scenarios that might apply to model elements. Based on MoDSEL specifications, an impact analysis is performed to assess the impact of evolution scenarios and the sensitivity of model elements. A case study is provided to show different kind of evolution scenarios and the required adaptations to model elements.

scholarly journals Sensitivity of Characterizing the Heat Loss Coefficient through On-Board Monitoring: A Case Study Analysis

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3322 ◽  
Author(s):  
Marieline Senave ◽  
Staf Roels ◽  
Stijn Verbeke ◽  
Evi Lambie ◽  
Dirk Saelens
Keyword(s):  
Sensitivity Analysis ◽  
Steady State ◽  
Data Analysis ◽  
Heat Loss ◽  
Input Data ◽  
Loss Coefficient ◽  
Wide Range ◽  
Board Monitoring ◽  
The Impact

Recently, there has been an increasing interest in the development of an approach to characterize the as-built heat loss coefficient (HLC) of buildings based on a combination of on-board monitoring (OBM) and data-driven modeling. OBM is hereby defined as the monitoring of the energy consumption and interior climate of in-use buildings via non-intrusive sensors. The main challenge faced by researchers is the identification of the required input data and the appropriate data analysis techniques to assess the HLC of specific building types, with a certain degree of accuracy and/or within a budget constraint. A wide range of characterization techniques can be imagined, going from simplified steady-state models applied to smart energy meter data, to advanced dynamic analysis models identified on full OBM data sets that are further enriched with geometric info, survey results, or on-site inspections. This paper evaluates the extent to which these techniques result in different HLC estimates. To this end, it performs a sensitivity analysis of the characterization outcome for a case study dwelling. Thirty-five unique input data packages are defined using a tree structure. Subsequently, four different data analysis methods are applied on these sets: the steady-state average, Linear Regression and Energy Signature method, and the dynamic AutoRegressive with eXogenous input model (ARX). In addition to the sensitivity analysis, the paper compares the HLC values determined via OBM characterization to the theoretically calculated value, and explores the factors contributing to the observed discrepancies. The results demonstrate that deviations up to 26.9% can occur on the characterized as-built HLC, depending on the amount of monitoring data and prior information used to establish the interior temperature of the dwelling. The approach used to represent the internal and solar heat gains also proves to have a significant influence on the HLC estimate. The impact of the selected input data is higher than that of the applied data analysis method.

scholarly journals The Impact of Demographic Changes on the Organization of Emergency Medical Services: the Case of Slovenia

Organizacija ◽  
2015 ◽  
Vol 48 (4) ◽  
pp. 247-258 ◽  
Author(s):  
Tatjana Kitić Jaklič ◽  
Jure Kovač
Keyword(s):  
Emergency Medical Services ◽  
Planning Process ◽  
National Level ◽  
Social Factor ◽  
Software Tool ◽  
Medical Services ◽  
Emergency Medical ◽  
Rate Of Increase ◽  
Starting Point ◽  
The Impact

Abstract Background and Purpose: The modern environment requires that organizations (profit and non-profit) continually harmonize their organizational models with changes in their respective environments and with their own visions and strategies for further development. The organizational structure of Emergency Medical Services (hereinafter EMS) is currently a very topical issue in Slovenia, given that a project to establish a new organization of EMS is currently underway at the national level. By examining the case of one region in Slovenia, this article presents an analysis of factors that impact on the number and types of EMS activities and depicts a forecast of future trends for the requirement of EMS. The analysis presents the initial phase of a strategic planning process for the mentioned activity and consequently, a starting point for the formation of an organizational EMS model. Methodology: This article presents an analysis of factors that impact on the formulation of an EMS model on the basis of research carried out for one geographical region of Slovenia. For the previous period, data was collected from 2002 to 2014. The software tool used for the analysis was STATA 13.0. For the purpose of forecasting a five-year period trend we used statistical package RStudio and Hyndman’s Forecast package given that this package contains algorithms for forecasting univariate time series including exponential smoothing using automated spatial models and ARIMA modelling. Results: The research has confirmed a correlation between social/environmental factors and the rate of increase in the demand for EMS. A population’s age structure has been identified as the key social factor that increases the need for EMS. On the basis of this finding, this article presents a model for forecasting growth trends in the scope of EMS activities. Conclusion: The research study has identified some important elements that are imperative to take into consideration when formulating an EMS network at the prehospital level. Population ageing has emerged as a key social factor. In the accordance with forecasted trends, an increase in the burden placed on EMS activities may also be anticipated in the future.

The impact of public relations on visibility of Croatian non-profits

2020 ◽  
Vol 25 (1) ◽  
pp. 87-97
Author(s):  
Mirela Polić ◽  
Nataša Cesarec Salopek
Keyword(s):  
Public Relations ◽  
Single Case ◽  
Strategic Communication ◽  
Content Type ◽  
Non Profit ◽  
Study Approach ◽  
Communication Campaign ◽  
Starting Point ◽  
The Impact

Purpose The purpose of this paper is to understand and show how public relations contributed to enhancing the visibility of Croatian non-profit organization Foundation “Croatia for Children” and its activities within its stakeholders, as well as how public relations contributed to the mobilization of target publics in Foundation’s activities. Design/methodology/approach Using a single case study approach, data were collected over a 12-month period. Quantitative and qualitative media research was applied in order to compare visibility of Foundation in the period before and after the strategic communication campaign. Findings Strategic communication campaign enhanced the visibility of Foundation “Croatia for Children” in national and local Croatian media and positioned it as the primary instance for children without an adequate parental care and children in need. However, local media devoted more attention comparing to the national media. All children wishes (1,000) were fulfilled by mobilizing the target publics. Research limitations/implications The results derived from this case study cannot be generalized since they are based on a single case in one country. Practical implications This study can serve as a starting point for another research about the role and importance that public relations have in enhancing the visibility of non-profit organizations. Originality/value The results of this study point to the role and importance public relations have in the non-profit sector in order to proactively communicate with all stakeholders in society.

Evaluating the Impact of a Futures-Oriented Organization

2019 ◽  
Vol 11 (4) ◽  
pp. 320-330
Author(s):  
Katri Vataja ◽  
Mikko Dufva ◽  
Pinja Parkkonen
Keyword(s):  
Societal Change ◽  
Operating Environment ◽  
Innovation Fund ◽  
Starting Point ◽  
Long Time ◽  
Societal Changes ◽  
Wide Scale ◽  
Evaluation Approaches ◽  
The Impact

Foresight and futures work aim at imagining, rethinking, and setting conditions for systemic changes in the society. The societal change as a starting point of evaluation poses challenges to the traditional evaluation approaches. To analyze whether something has an impact on systemic changes, we need methods that consider the dynamics of the operating environment, the multi-actor perspective, and the long-time span of societal changes. In this article, we explore the design and methodological questions related to evaluating the impact of actors, which have set goals for societal impact of their futures work. Our case is based on the wide-scale evaluations of the Finnish Innovation Fund Sitra. In this article, we describe the process and thinking behind the evaluation of the futures work at Sitra and illustrate it with a case study of an evaluation of one of Sitra’s impact goals. Based on our experience from this and other impact evaluations, we provide good practices and recommendations on how to evaluate futures work and foresight in a way that helps steer an organization’s actions.

scholarly journals The Impact Analysis of Water Body Landscape Pattern on Urban Heat Island: A Case Study of Wuhan City

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Bohan Yang ◽  
Fen Meng ◽  
Xinli Ke ◽  
Caixue Ma
Keyword(s):  
Water Body ◽  
Impact Analysis ◽  
Remote Sensing Technique ◽  
Multiple Stepwise Regression Analysis ◽  
Average Water ◽  
Urban Heat ◽  
City Water ◽  
The Impact ◽  
The Relationship

Based on the LST and the landscape metrics of water body with remote sensing technique and spatial analysis, the relationship between the mean LST and the attributes of water body was revealed via Pearson’s correlation analysis and multiple stepwise regression analysis. Result showed that, in 32 class-based metrics we selected, the proportion of water body, average water body size, the isolation and fragmentation of water body, and other eight metrics have high correlation with the LST. As a resultant force, the quantity, shape, and spatial distribution of water body affect the forming of temperature. We found that the quantity and spatial pattern of city water body could be allocated reasonably to maximize its cooling effect.

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