Quantitative relationships between key performance indicators for supporting decision-making processes

2009 ◽  
Vol 60 (2) ◽  
pp. 104-113 ◽  
Author(s):  
Raul Rodriguez Rodriguez ◽  
Juan José Alfaro Saiz ◽  
Angel Ortiz Bas
Keyword(s):  
Decision Making ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Decision Making Processes

The Impact of Rankings on Russian Universities' Student Choice

2019 ◽  
pp. 47-55
Author(s):  
Liliya Ravilevna Yagudina
Keyword(s):  
Decision Making ◽  
Performance Indicators ◽  
Foreign Students ◽  
Key Performance Indicators ◽  
Student Choice ◽  
Decision Making Processes ◽  
The Impact ◽  
Russian Universities

On the basis of its own hypotheses and analysis of foreign studies, the author determines how the informational and motivational functions of rankings have impact on Russian universities' student choice. The analysis of the rankings position of universities and some of their key performance indicators (the foreign students number, the quality of applicants) showed there is not any direct correlation between them. According to the author, in order to maximize the effectiveness of rankings, it is necessary to improve the ranking methodology, to develop universities' decision-making processes based on the rankings results, and to create customer culture on the rankings results using.

Entscheidungsorientierte Steuerung der Personalinformationen

2012 ◽  
Vol 53 (4) ◽  
pp. 26-31 ◽  
Author(s):  
Sven Mönkediek ◽  
Norbert Zdrowomyslaw
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
The Other ◽  
Know How ◽  
Competitive Capabilities ◽  
Other Hand ◽  
The One

Mitarbeiter sind zwar Kostenfaktor und Risikofaktor jedes Unternehmens, aber vor allem auch Leistungs-, Kreativ- und Wertschöpfungsfaktor. Legt man zugrunde, dass Humankapital und Wissen als zentrale Eckpfeiler der Innovations- und Wettbewerbsfähigkeit zu werten sind, ist die entscheidungsorientierte Steuerung von Personalinformationen geradezu ein Muss für eine zukunftsorientierte Unternehmensentwicklung. Kenngrößen sollten Intuition und Erfahrung von Unternehmern sowie Führungskräften bei der Entscheidungsfindung und Entscheidungsdurchsetzung unterstützen. Dabei ist zweierlei zu bedenken: Zum einen sind unternehmensspezifische Bedürfnisse in das Berichtswesen und das Kennzahlencockpit zu integrieren und zum anderen bedeutet die Umsetzung von Personalmaßnahmen vor allem auch Transparenz zu schaffen und Kommunikation zu pflegen. Employees are considered as cost and risk factors but most importantly represent creative and value adding potential for companies. Since personnel and know-how are cornerstones of the company´s innovative and competitive capabilities, utilization of relevant personnel information is absolutely essential for a future orientated development of companies. Key performance indicators support intuition and experience of entrepreneurs and managers in decision making. While doing so company specific needs have to be taken into account in designing reporting and data cockpits on the one hand. On the other hand implementation of personnel related activities always demands transparency as well as timely and continuous communication. Keywords: views, verhaltenssteuerung, querys, personalcontrolling, datenanalyse

scholarly journals Advanced decision-making in higher education: learning analytics research and key performance indicators

2018 ◽  
Vol 37 (10-11) ◽  
pp. 937-940 ◽  
Author(s):  
Miltiadis D. Lytras ◽  
Naif Radi Aljohani ◽  
Anna Visvizi ◽  
Patricia Ordonez De Pablos ◽  
Dragan Gasevic
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Performance Indicators ◽  
Learning Analytics ◽  
Key Performance Indicators

scholarly journals Dynamic Model and Graphical User Interface: A Solution for the Distribution Process of Regional Products

2020 ◽  
Vol 10 (13) ◽  
pp. 4481 ◽  
Author(s):  
Ernesto A. Lagarda-Leyva ◽  
Alfredo Bueno-Solano ◽  
Harvey P. Vea-Valdez ◽  
Daniel O. Machado
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
User Interface ◽  
Graphical User Interface ◽  
Performance Indicators ◽  
Process Analysis ◽  
Key Performance Indicators ◽  
Food Distribution ◽  
Technological Solution ◽  
Distribution Process

Organizations in the agroindustry sector face shorter delivery schedules; therefore, they are seeking ways to conduct more effective and less costly product distribution. Supply chain management efforts have focused on improving the flow of both products and information. Thus, the aim of this case study was to build a graphical user interface to enable decision-making based on quantitative information for a food distribution process. The problem to be solved was associated with the development of a technological solution to reduce and control variations in transportation times, delivery costs and capacities in cold and dry food distribution. An eight-step system for a dynamics methodology was used: (1) distribution process analysis, (2) route description, (3) variable and parameter description, (4) causal loop diagram creation, (5) current model simulation, (6) validation, (7) quantitative scenario construction based on key performance indicators, and (8) graphical user interface development. The main findings of this research were that the graphical user interface and simulation showed information that represented on average 56.49% of the total distribution costs regarding fuel and that maintenance and tire wearing costs had less of an impact on total costs, representing 9.21% and 3.66% of the total costs, respectively. Additionally, the technological solution—created for the supply chain in the distribution process against the background of changes in policies—makes it possible to improve decision-making based on different scenarios supported by a graphical interface according to key performance indicators. This solution could be used by different organizations who aim to reduce logistics and transportation costs. The main implications of this research were the available and organized information and the restructuring of the distribution process.

Implementation of a Simulation Model for Optimizing the Traffic Flow from Arafat to Muzdalifah

2017 ◽  
Vol 13 (33) ◽  
pp. 390
Author(s):  
Arwa Jamjoom
Keyword(s):  
Decision Making ◽  
Simulation Model ◽  
Traffic Flow ◽  
Visual Feedback ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Primary Objective ◽  
Experimental Results ◽  
Different Types ◽  
Support Decision Making

This project simulates the flow of pilgrims when they travel from Arafat to Muzdalifah. The system includes the roads network that connects Arafat to Muzdalifah, which is represented as a queuing system with different queue measurements that simulate reality. The system also includes different types of transportation, such as small and large buses and trains, all of which are represented as objects with different size and colors. All system objects carry specifications as their corresponding source system objects, and these specifications are based on data collected by the Ministry of Hajj. The primary objective of the system is to answer “what if” questions to support decision making to optimize Hajj traffic, which can be achieved by manipulating the system’s variables and then by observing the key performance indicators of the system. The system presents the experimental results as visual feedback alongside written reports with statistics and illustrations.

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