International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Operation research ppt chapter two mitkumitku assefa
The document discusses linear programming, which involves optimizing an objective function subject to constraints. It provides examples of formulating linear programming problems from descriptions of resource allocation scenarios. Linear programming can be used to maximize profits or minimize costs by determining the optimal allocation of limited resources among competing activities. The key components of a linear programming model are decision variables, constraints, and an objective function. Graphical and algebraic (simplex) methods can be used to solve linear programming problems. Special cases like multiple optimal solutions, unbounded solutions, and infeasible solutions are also discussed.
This document discusses Data Envelopment Analysis (DEA), a method for measuring the relative efficiencies of decision-making units that have multiple inputs and outputs. DEA assigns weights to inputs and outputs to calculate efficiency scores. There are variations in how DEA is formulated, including whether it is oriented towards minimizing inputs or maximizing outputs. The document provides an example to illustrate the graphical results and calculations of DEA under different formulations.
This document discusses Data Envelopment Analysis (DEA), a linear programming methodology used to measure the efficiency of decision-making units with multiple inputs and outputs. It provides a brief history of DEA, explaining that it was created to evaluate efficiency using an empirical production frontier. The document also outlines how DEA works by establishing an efficiency frontier using selected variables, defining the frontier, and giving each unit an efficiency coefficient. Finally, it discusses the advantages of DEA in handling multiple inputs/outputs without specifying a production function, as well as the disadvantages of being sensitive to input/output selection.
Liner programming on Management ScienceAbdul Motaleb
The document discusses management science and linear programming. It provides details on:
1) Management science uses various scientific principles and analytical methods to help organizations make rational decisions to maximize profit or minimize expenses.
2) Management science research can be done on fundamental, modeling, and application levels.
3) Linear programming is a method to achieve the optimal outcome given linear constraints and can be used to solve production planning, marketing mix, product distribution, and staff scheduling problems in business.
4) The key characteristics of linear programming problems are that they involve optimization with an objective function and constraints, and have linear relationships between variables.
Quantitative analysis for business decision (QABD)- Linear programming probl...Chandra Shekar Immani
Linear programming is an optimization technique for allocating limited resources to achieve the greatest benefit. It can be used to solve problems in various industries and fields. Some common applications include determining optimal product mixes, production schedules, transportation routes, and portfolio selections. The document provides examples of linear programming applications in industries like oil refining, transportation, manufacturing, and more. It also discusses the advantages of linear programming in improving decision quality and using resources efficiently with a scientific approach.
Linear Programming Problems {Operation Research}FellowBuddy.com
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
The document describes an Operations Research course. It includes 8 units covering topics like linear programming, transportation problems, queuing theory, PERT-CPM techniques, game theory, and integer programming. It provides details of each unit including the number of lecture hours and the topics to be covered. It also lists the textbooks and reference books for the course. The course aims to introduce students to various operations research techniques and their applications in decision making.
The document discusses data envelopment analysis (DEA) and its use in evaluating the relative efficiency of decision making units (DMUs) like bank branches, schools, hospitals, and more. It provides an example comparing four bank branches based on personal transactions and staff numbers. DEA is introduced as a non-parametric method that determines efficiency scores for each DMU based on input and output variables without needing to specify a functional form. The document also explains DEA models like CCR and variable returns to scale and provides an example solving a VRS DEA problem to evaluate the efficiency of the bank branches.
Operation research ppt chapter two mitkumitku assefa
The document discusses linear programming, which involves optimizing an objective function subject to constraints. It provides examples of formulating linear programming problems from descriptions of resource allocation scenarios. Linear programming can be used to maximize profits or minimize costs by determining the optimal allocation of limited resources among competing activities. The key components of a linear programming model are decision variables, constraints, and an objective function. Graphical and algebraic (simplex) methods can be used to solve linear programming problems. Special cases like multiple optimal solutions, unbounded solutions, and infeasible solutions are also discussed.
This document discusses Data Envelopment Analysis (DEA), a method for measuring the relative efficiencies of decision-making units that have multiple inputs and outputs. DEA assigns weights to inputs and outputs to calculate efficiency scores. There are variations in how DEA is formulated, including whether it is oriented towards minimizing inputs or maximizing outputs. The document provides an example to illustrate the graphical results and calculations of DEA under different formulations.
This document discusses Data Envelopment Analysis (DEA), a linear programming methodology used to measure the efficiency of decision-making units with multiple inputs and outputs. It provides a brief history of DEA, explaining that it was created to evaluate efficiency using an empirical production frontier. The document also outlines how DEA works by establishing an efficiency frontier using selected variables, defining the frontier, and giving each unit an efficiency coefficient. Finally, it discusses the advantages of DEA in handling multiple inputs/outputs without specifying a production function, as well as the disadvantages of being sensitive to input/output selection.
Liner programming on Management ScienceAbdul Motaleb
The document discusses management science and linear programming. It provides details on:
1) Management science uses various scientific principles and analytical methods to help organizations make rational decisions to maximize profit or minimize expenses.
2) Management science research can be done on fundamental, modeling, and application levels.
3) Linear programming is a method to achieve the optimal outcome given linear constraints and can be used to solve production planning, marketing mix, product distribution, and staff scheduling problems in business.
4) The key characteristics of linear programming problems are that they involve optimization with an objective function and constraints, and have linear relationships between variables.
Quantitative analysis for business decision (QABD)- Linear programming probl...Chandra Shekar Immani
Linear programming is an optimization technique for allocating limited resources to achieve the greatest benefit. It can be used to solve problems in various industries and fields. Some common applications include determining optimal product mixes, production schedules, transportation routes, and portfolio selections. The document provides examples of linear programming applications in industries like oil refining, transportation, manufacturing, and more. It also discusses the advantages of linear programming in improving decision quality and using resources efficiently with a scientific approach.
Linear Programming Problems {Operation Research}FellowBuddy.com
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
The document describes an Operations Research course. It includes 8 units covering topics like linear programming, transportation problems, queuing theory, PERT-CPM techniques, game theory, and integer programming. It provides details of each unit including the number of lecture hours and the topics to be covered. It also lists the textbooks and reference books for the course. The course aims to introduce students to various operations research techniques and their applications in decision making.
The document discusses data envelopment analysis (DEA) and its use in evaluating the relative efficiency of decision making units (DMUs) like bank branches, schools, hospitals, and more. It provides an example comparing four bank branches based on personal transactions and staff numbers. DEA is introduced as a non-parametric method that determines efficiency scores for each DMU based on input and output variables without needing to specify a functional form. The document also explains DEA models like CCR and variable returns to scale and provides an example solving a VRS DEA problem to evaluate the efficiency of the bank branches.
This document provides an overview of the history and objectives of operations research. It discusses how operations research originated during World War II to help optimize the use of limited military resources. After the war, operations research techniques were applied to industrial problems to maximize profits and minimize costs. The document outlines the key objectives of operations research as providing a scientific basis for management decision making and helping managers make better decisions through the use of mathematical modeling and analysis.
The document discusses using the linear programming technique to aid in decision making for marketing and finance problems. It provides an example of using linear programming to determine the optimal allocation of advertising budgets across multiple media (television, radio, newspaper) to maximize total audience reach given budget constraints. Linear programming can be applied to problems in marketing mix determination, financial decision making, production scheduling, and more. It also briefly describes the simplex method for solving linear programming problems.
The document provides an overview of operations research techniques. It discusses:
- Operations research aims to improve decision-making through methods like simulation, optimization, and data analysis.
- Major applications include production scheduling, inventory control, transportation planning, and more.
- The techniques were developed in World War II and are now used widely in business for problems like resource allocation, forecasting, and process improvement.
DEA is a linear programming technique used to measure the relative efficiency of decision-making units that have multiple inputs and outputs. It constructs a production frontier boundary defined by the most efficient DMUs to evaluate the efficiency of other DMUs relative to this frontier. Examples of DMUs include banks, schools, countries, etc. DEA allows each DMU to determine its own optimal input and output weights to calculate efficiency scores compared to best practice DMUs on the frontier. This document provides an overview of DEA, its applications, advantages over regression analysis, and the general DEA model.
All companies need to be more effectively than ever before. In the current financial climate, every dollar invested is important and know that your business is operating efficiently is an imperative need, but as a Manager not always easy to know if the decisions are really the best for your company.
The document discusses operations research and linear programming. It defines operations research as a scientific approach to determine the optimal solution to decision problems with limited resources. Linear programming is then introduced as a type of mathematical modeling where the objective function and constraints are linear. The key aspects of a linear programming problem are defined as the decision variables, objective function to maximize or minimize, and constraints. Graphical solutions and examples of linear programming problems are also provided.
This document discusses quantitative methods for decision making, also known as operations research. It defines decision making as the process of choosing among alternatives. The document then discusses different types of decisions, such as sequential, conscious/unconscious, and managerial decisions. It also discusses various farm management decisions including organizational, administrative, and marketing decisions. Finally, it provides an example of using linear programming to solve a problem involving maximizing profit from toy production given resource constraints.
Unit I (8 Hrs)
Introduction to Linear Programming – Various definitions, Statements of basic
theorems and properties, Advantages Limitations and Application areas of Linear
Programming, Linear Programming -Graphical method, - graphical solution
methods of Linear Programming problems, The Simplex Method: -the Simplex
Algorithm, Phase II in simplex method, Primal and Dual Simplex Method, Big-M
Method
Unit II (8 Hrs)
Transportation Model and its variants: Definition of the Transportation Model
-Nontraditional Transportation Models-the Transportation Algorithm-the Assignment
Model– The Transshipment Model
Unit III (8 Hrs)
Network Models: Basic differences between CPM and PERT, Arrow Networks,
Time estimates, earliest completion time, Latest allowable occurrences time,
Forward Press Computation, Backward Press Computation, Representation in
tabular form, Critical Path, Probability of meeting the scheduled date of completion,
Various floats for activities, Critical Path updating projects, Operation time cost trade
off Curve project,
Selection of schedule based on :- Cost analysis, Crashing the network
Sequential model & related problems, processing n jobs through – 1 machine & 2
machines
Unit IV (8 Hrs)
Network Models: Scope of Network Applications – Network definitions, Goal
Programming Algorithms, Minimum Spanning Tree Algorithm, Shortest Route
Problem, Maximal flow model, Minimum cost capacitated flow problem
Unit V (8 Hrs)
Decision Analysis: Decision - Making under certainty - Decision - Making under
Risk, Decision
under uncertainty.
Unit VI (8 Hrs)
Simulation Modeling: Monte Carlo Simulation, Generation of Random Numbers,
Method for
Gathering Statistical observations
The document provides examples of case studies where Pro Bono O.R. has been applied. The first case study describes how volunteers analyzed data and built a simulation model to recommend new staff shift patterns for a crimestoppers call center, improving performance without increasing costs. The second case study discusses how volunteers identified process improvements and value-adding activities for a charity matching volunteers to organizations. The third case study outlines how volunteers helped a youth venture define risks to sustainability and create a risk management plan.
This chapter introduces spreadsheet modeling and decision analysis as a field of management science that uses computers, statistics, and mathematics to solve business problems. It discusses how spreadsheet models represent real-world phenomena with mathematical relationships and can help analyze decisions by evaluating potential outcomes. Examples are given of companies that achieved significant cost savings and efficiency gains by developing spreadsheet and other mathematical models to optimize areas like procurement, logistics, inventory management, and operations. The chapter also covers characteristics of models, benefits of modeling approaches, categories of mathematical models, and cognitive biases that can influence decision-making.
The document provides an overview of linear programming, including its applications, assumptions, and mathematical formulation. Some key points:
- Linear programming is a tool for maximizing or minimizing quantities like profit or cost, subject to constraints. 50-90% of business decisions and computations involve linear programming.
- Applications in business include production, personnel, inventory, marketing, financial, and blending problems. The objective is to optimize variables like costs, profits, or resources while meeting constraints.
- Assumptions of linear programming include certainty, linearity/proportionality, additivity, divisibility, non-negativity, finiteness, and optimality at corner points.
- A linear programming problem is modeled mathemat
This document provides an introduction to quantitative techniques for management. It discusses the historical development of quantitative techniques from scientific management principles to their modern applications. The methodology of quantitative techniques involves formulating the problem, defining decision variables and constraints, developing a suitable mathematical model, acquiring input data, solving the model, validating the model, and implementing results. Quantitative techniques help managers make faster and more accurate decisions using a scientific approach. They allow for complex problems to be solved with greater ease and accuracy.
The document provides an overview of quantitative analysis. It discusses that quantitative analysis is the systematic study of an organization's structure, characteristics, functions, and relationships to provide executives with a quantitative basis for decision making. The characteristics of quantitative analysis include a focus on decision making, applying a scientific approach, using an interdisciplinary team, and applying formal mathematical models. The quantitative analysis process involves defining the problem, developing a model, acquiring data, developing a solution, testing the solution, and validating the model. Common tools used in quantitative analysis include linear programming, statistical techniques, decision tables, decision trees, game theory, forecasting, and mathematical programming.
Decision making and operations researchAmjad Idries
This document discusses decision making and operations research. It defines key concepts like logic, rationality, evidence and models. Models are simplified representations of systems or situations used to improve understanding or decision making. The document notes that operations research is useful for problems involving strategic management decisions, multiple options with different consequences, uncertainty, and risk. Areas that benefit from operations research include investment and return decisions, setting appropriate capacity levels, and fixing issues related to system flow. The document prompts choosing an example problem to discuss and illustrates understanding the problem and potential solutions.
Operational research (OR) is defined as a systematic and analytical approach to decision-making and problem-solving. It uses techniques from mathematics, statistics, and other fields to arrive at optimal or near-optimal solutions to complex problems. Some key points made in the document include: OR aims to help executives make better decisions; it follows a scientific approach and uses interdisciplinary teams; it considers the system as a whole and aims to find the best objective solution. OR has wide applications in fields like national planning, defense, industry, R&D, and agriculture. The OR modeling process typically involves 7 phases: problem formulation, system observation, model formulation, model verification, alternative selection, presentation of results, and implementation/evaluation.
The document provides a history of operations research, beginning with its origins during World War II when scientists were invited to study strategic and tactical military problems in England. It describes how linear programming was developed as a method to optimally allocate limited resources. After the war, operations research techniques were applied to industrial problems. Today, operations research is widely used across various domains to help managers make better decisions using quantitative modeling and analysis.
Use of quantitative techniques in economicsBalaji P
1. The document discusses three quantitative techniques used in economics: comparative static analysis, linear programming, and game theory.
2. Comparative static analysis compares economic equilibrium before and after changes in exogenous parameters like demand or supply. It examines how endogenous variables like price and quantity adjust.
3. Linear programming identifies the optimal allocation of limited resources to maximize profits or minimize costs. It formulates the problem as mathematical equations and graphs to find the best solution.
4. Game theory analyzes strategic decision-making in competitive situations. It models interactions between players and outcomes using payoff matrices and extensive forms to determine optimal strategies.
This document provides an overview of Data Envelopment Analysis (DEA), a technique for evaluating the relative efficiencies of decision making units that may have multiple inputs and outputs. It discusses the assumptions and formulations of DEA models, including input-oriented and output-oriented linear programming models. Examples are provided to illustrate DEA applications for banks, supply chains, and clothing shops. The document also compares constant returns to scale and variable returns to scale DEA models and references key papers on the development of DEA.
This presentations covers Definition of Operations Research , Models, Scope,Phases ,advantages,limitations, tools and techniques in OR and Characteristics of Operations research
The pure heuristic search algorithm maintains an open list of generated nodes that have not been expanded and a closed list of nodes that have. It begins with the initial state on the open list and at each cycle expands the node with the minimum heuristic value, generating its children and placing them on the open list in heuristic order. This continues until a goal state is expanded. Heuristic search sacrifices completeness for efficiency by using heuristics to guide the search towards the goal. Examples given include the 15-puzzle, maze navigation, and the missionaries and cannibals river crossing problem.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document provides an overview of the history and objectives of operations research. It discusses how operations research originated during World War II to help optimize the use of limited military resources. After the war, operations research techniques were applied to industrial problems to maximize profits and minimize costs. The document outlines the key objectives of operations research as providing a scientific basis for management decision making and helping managers make better decisions through the use of mathematical modeling and analysis.
The document discusses using the linear programming technique to aid in decision making for marketing and finance problems. It provides an example of using linear programming to determine the optimal allocation of advertising budgets across multiple media (television, radio, newspaper) to maximize total audience reach given budget constraints. Linear programming can be applied to problems in marketing mix determination, financial decision making, production scheduling, and more. It also briefly describes the simplex method for solving linear programming problems.
The document provides an overview of operations research techniques. It discusses:
- Operations research aims to improve decision-making through methods like simulation, optimization, and data analysis.
- Major applications include production scheduling, inventory control, transportation planning, and more.
- The techniques were developed in World War II and are now used widely in business for problems like resource allocation, forecasting, and process improvement.
DEA is a linear programming technique used to measure the relative efficiency of decision-making units that have multiple inputs and outputs. It constructs a production frontier boundary defined by the most efficient DMUs to evaluate the efficiency of other DMUs relative to this frontier. Examples of DMUs include banks, schools, countries, etc. DEA allows each DMU to determine its own optimal input and output weights to calculate efficiency scores compared to best practice DMUs on the frontier. This document provides an overview of DEA, its applications, advantages over regression analysis, and the general DEA model.
All companies need to be more effectively than ever before. In the current financial climate, every dollar invested is important and know that your business is operating efficiently is an imperative need, but as a Manager not always easy to know if the decisions are really the best for your company.
The document discusses operations research and linear programming. It defines operations research as a scientific approach to determine the optimal solution to decision problems with limited resources. Linear programming is then introduced as a type of mathematical modeling where the objective function and constraints are linear. The key aspects of a linear programming problem are defined as the decision variables, objective function to maximize or minimize, and constraints. Graphical solutions and examples of linear programming problems are also provided.
This document discusses quantitative methods for decision making, also known as operations research. It defines decision making as the process of choosing among alternatives. The document then discusses different types of decisions, such as sequential, conscious/unconscious, and managerial decisions. It also discusses various farm management decisions including organizational, administrative, and marketing decisions. Finally, it provides an example of using linear programming to solve a problem involving maximizing profit from toy production given resource constraints.
Unit I (8 Hrs)
Introduction to Linear Programming – Various definitions, Statements of basic
theorems and properties, Advantages Limitations and Application areas of Linear
Programming, Linear Programming -Graphical method, - graphical solution
methods of Linear Programming problems, The Simplex Method: -the Simplex
Algorithm, Phase II in simplex method, Primal and Dual Simplex Method, Big-M
Method
Unit II (8 Hrs)
Transportation Model and its variants: Definition of the Transportation Model
-Nontraditional Transportation Models-the Transportation Algorithm-the Assignment
Model– The Transshipment Model
Unit III (8 Hrs)
Network Models: Basic differences between CPM and PERT, Arrow Networks,
Time estimates, earliest completion time, Latest allowable occurrences time,
Forward Press Computation, Backward Press Computation, Representation in
tabular form, Critical Path, Probability of meeting the scheduled date of completion,
Various floats for activities, Critical Path updating projects, Operation time cost trade
off Curve project,
Selection of schedule based on :- Cost analysis, Crashing the network
Sequential model & related problems, processing n jobs through – 1 machine & 2
machines
Unit IV (8 Hrs)
Network Models: Scope of Network Applications – Network definitions, Goal
Programming Algorithms, Minimum Spanning Tree Algorithm, Shortest Route
Problem, Maximal flow model, Minimum cost capacitated flow problem
Unit V (8 Hrs)
Decision Analysis: Decision - Making under certainty - Decision - Making under
Risk, Decision
under uncertainty.
Unit VI (8 Hrs)
Simulation Modeling: Monte Carlo Simulation, Generation of Random Numbers,
Method for
Gathering Statistical observations
The document provides examples of case studies where Pro Bono O.R. has been applied. The first case study describes how volunteers analyzed data and built a simulation model to recommend new staff shift patterns for a crimestoppers call center, improving performance without increasing costs. The second case study discusses how volunteers identified process improvements and value-adding activities for a charity matching volunteers to organizations. The third case study outlines how volunteers helped a youth venture define risks to sustainability and create a risk management plan.
This chapter introduces spreadsheet modeling and decision analysis as a field of management science that uses computers, statistics, and mathematics to solve business problems. It discusses how spreadsheet models represent real-world phenomena with mathematical relationships and can help analyze decisions by evaluating potential outcomes. Examples are given of companies that achieved significant cost savings and efficiency gains by developing spreadsheet and other mathematical models to optimize areas like procurement, logistics, inventory management, and operations. The chapter also covers characteristics of models, benefits of modeling approaches, categories of mathematical models, and cognitive biases that can influence decision-making.
The document provides an overview of linear programming, including its applications, assumptions, and mathematical formulation. Some key points:
- Linear programming is a tool for maximizing or minimizing quantities like profit or cost, subject to constraints. 50-90% of business decisions and computations involve linear programming.
- Applications in business include production, personnel, inventory, marketing, financial, and blending problems. The objective is to optimize variables like costs, profits, or resources while meeting constraints.
- Assumptions of linear programming include certainty, linearity/proportionality, additivity, divisibility, non-negativity, finiteness, and optimality at corner points.
- A linear programming problem is modeled mathemat
This document provides an introduction to quantitative techniques for management. It discusses the historical development of quantitative techniques from scientific management principles to their modern applications. The methodology of quantitative techniques involves formulating the problem, defining decision variables and constraints, developing a suitable mathematical model, acquiring input data, solving the model, validating the model, and implementing results. Quantitative techniques help managers make faster and more accurate decisions using a scientific approach. They allow for complex problems to be solved with greater ease and accuracy.
The document provides an overview of quantitative analysis. It discusses that quantitative analysis is the systematic study of an organization's structure, characteristics, functions, and relationships to provide executives with a quantitative basis for decision making. The characteristics of quantitative analysis include a focus on decision making, applying a scientific approach, using an interdisciplinary team, and applying formal mathematical models. The quantitative analysis process involves defining the problem, developing a model, acquiring data, developing a solution, testing the solution, and validating the model. Common tools used in quantitative analysis include linear programming, statistical techniques, decision tables, decision trees, game theory, forecasting, and mathematical programming.
Decision making and operations researchAmjad Idries
This document discusses decision making and operations research. It defines key concepts like logic, rationality, evidence and models. Models are simplified representations of systems or situations used to improve understanding or decision making. The document notes that operations research is useful for problems involving strategic management decisions, multiple options with different consequences, uncertainty, and risk. Areas that benefit from operations research include investment and return decisions, setting appropriate capacity levels, and fixing issues related to system flow. The document prompts choosing an example problem to discuss and illustrates understanding the problem and potential solutions.
Operational research (OR) is defined as a systematic and analytical approach to decision-making and problem-solving. It uses techniques from mathematics, statistics, and other fields to arrive at optimal or near-optimal solutions to complex problems. Some key points made in the document include: OR aims to help executives make better decisions; it follows a scientific approach and uses interdisciplinary teams; it considers the system as a whole and aims to find the best objective solution. OR has wide applications in fields like national planning, defense, industry, R&D, and agriculture. The OR modeling process typically involves 7 phases: problem formulation, system observation, model formulation, model verification, alternative selection, presentation of results, and implementation/evaluation.
The document provides a history of operations research, beginning with its origins during World War II when scientists were invited to study strategic and tactical military problems in England. It describes how linear programming was developed as a method to optimally allocate limited resources. After the war, operations research techniques were applied to industrial problems. Today, operations research is widely used across various domains to help managers make better decisions using quantitative modeling and analysis.
Use of quantitative techniques in economicsBalaji P
1. The document discusses three quantitative techniques used in economics: comparative static analysis, linear programming, and game theory.
2. Comparative static analysis compares economic equilibrium before and after changes in exogenous parameters like demand or supply. It examines how endogenous variables like price and quantity adjust.
3. Linear programming identifies the optimal allocation of limited resources to maximize profits or minimize costs. It formulates the problem as mathematical equations and graphs to find the best solution.
4. Game theory analyzes strategic decision-making in competitive situations. It models interactions between players and outcomes using payoff matrices and extensive forms to determine optimal strategies.
This document provides an overview of Data Envelopment Analysis (DEA), a technique for evaluating the relative efficiencies of decision making units that may have multiple inputs and outputs. It discusses the assumptions and formulations of DEA models, including input-oriented and output-oriented linear programming models. Examples are provided to illustrate DEA applications for banks, supply chains, and clothing shops. The document also compares constant returns to scale and variable returns to scale DEA models and references key papers on the development of DEA.
This presentations covers Definition of Operations Research , Models, Scope,Phases ,advantages,limitations, tools and techniques in OR and Characteristics of Operations research
The pure heuristic search algorithm maintains an open list of generated nodes that have not been expanded and a closed list of nodes that have. It begins with the initial state on the open list and at each cycle expands the node with the minimum heuristic value, generating its children and placing them on the open list in heuristic order. This continues until a goal state is expanded. Heuristic search sacrifices completeness for efficiency by using heuristics to guide the search towards the goal. Examples given include the 15-puzzle, maze navigation, and the missionaries and cannibals river crossing problem.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
El Grado en Educación Infantil te habilita para ejercer como maestro en la etapa de 0 a 6 años de edad.
Si quieres aprender estrategias didácticas, promover el desarrollo cognitivo, social y de la personalidad en la etapa escolar, cursar magisterio a distancia y dominar las nuevas tecnologías, este título te capacita para ello. Aprende a conocer el desarrollo del lenguaje y de la escritura y a utilizar el juego como principal recurso pedagógico.
Struggling with pitching and convincing clients to adopt new digital tactics into their marketing strategy?
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At this event, you'll learn:
-How to pitch clients on new digital marketing strategies
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-How to grow client retainers with new kinds of work
-How to manage and grow reporting efforts in a scalable way
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
La Unión Europea se formó después de la Segunda Guerra Mundial para fomentar la cooperación entre las naciones europeas y prevenir futuros conflictos. Los líderes europeos fundaron la Comunidad Económica Europea en 1957 con el objetivo de hacer que los países dependieran unos de otros económicamente. Esta organización evolucionó para convertirse en la Unión Europea en 1992, que actualmente tiene 28 estados miembros comprometidos con la prosperidad, la paz, y los derechos de sus ciudadanos.
Evaluación anual de desempeño no motiva al colaborador ni lo compromete a la ...Talentia Gestio
1) La evaluación anual de desempeño ya no motiva a los colaboradores ni los compromete con la empresa debido a que se realiza de manera mecánica y no considera el desarrollo de competencias. 2) La evaluación se basa en criterios estadísticos forzados y no toma en cuenta el talento individual de los colaboradores. 3) Esto genera insatisfacción y desmotivación entre los trabajadores, afectando negativamente el clima laboral y el compromiso con la organización.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Este documento apresenta informações sobre lançamentos de livros, incluindo:
1) Um livro infantil sobre um zumbi do Minecraft que precisa lidar com planos de férias não desejados;
2) Livros de autoajuda e espiritualidade de Brian Weiss;
3) Um livro sobre estilo de vida anticâncer escrito por uma médica que venceu o câncer.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Este documento presenta un prólogo a una edición española del libro Progreso y Miseria de Henry George. Brevemente describe que Henry George fue un pensador estadounidense del siglo XIX que buscó explicar la causa de la asociación entre el progreso económico y el aumento de la pobreza, y proponer soluciones. Su libro Progreso y Miseria, publicado en 1879, ha sido muy influyente y ha tenido muchas ediciones y traducciones. Esta nueva edición española busca corregir deficiencias
Why do Muslims say same tongue on any Islam related Matter around the Globe? Main Uddin
Muslims say the same thing on Islamic matters globally because Islam teaches the concept of Islamic brotherhood. The Quran establishes that all believers are one brotherhood and commands Muslims to be united. It forbids division and commands upholding one religion. Islam bases brotherhood on shared faith rather than attributes like race or lineage to bring about a united global community. This Islamic brotherhood is meant to be a source of good, peace, and justice for all of humanity.
International Journal of Mathematics and Statistics Invention (IJMSI)inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Organ peredaran darah manusia terdiri atas jantung, pembuluh darah, dan paru-paru. Jantung berfungsi memompa darah ke seluruh tubuh melalui pembuluh darah. Darah yang sudah tidak mengandung oksigen diangkut ke paru-paru untuk mengikat oksigen sebelum dikirim kembali ke jantung.
El jefe de Multiactivos de NN Investment Partners describe cómo los mismos factores de miedo de 2015, como el crecimiento débil de China, las tensiones geopolíticas y la caída de los precios del petróleo, están aumentando la volatilidad en los mercados nuevamente en 2016. Aunque algunos aspectos fundamentales son similares al año pasado, existen diferencias clave como las divergencias en las políticas monetarias de los bancos centrales. Debido a la incertidumbre continua, NN Investment Partners mantendrá una postura
El documento analiza el comportamiento reciente del índice bursátil IBEX 35 en España. Predice que si el IBEX mantiene su nivel de cierre actual de 9.900 puntos puede moverse lateralmente entre 9.900-10.500 puntos, pero si supera este nivel podría subir a entre 11.000-11.500 puntos. El documento también explica brevemente el uso de medias móviles simples para analizar tendencias pasadas y predecir posibles movimientos futuros del mercado.
Measurement and Comparison of Productivity Performance Under Fuzzy Imprecise ...Waqas Tariq
The creation of goods and services requires changing the expended resources into the output goods and services. How efficiently we transform these input resources into goods and services depends on the productivity of the transformation process. However, it has been observed there is always a vagueness or imprecision associated with the values of inputs and outputs. Therefore, it becomes hard for a productivity measurement expert to specify the amount of resources and the outputs as exact scalar numbers. The present paper, applies fuzzy set theory to measure and compare productivity performance of transformation processes when numerical data cannot be specified in exact terms. The approach makes it possible to measure and compare productivity of organizational units (including non-government and non-profit entities) when the expert inputs can not be specified as exact scalar quantities. The model has been applied to compare productivity of different branches of a company.
This document proposes a methodology for evaluating statistical classification models for churn prediction using a composite indicator. It considers factors beyond just accuracy, like robustness, speed, interpretability and ease of use. The methodology will be tested on classification models applied to real customer data from a Spanish retail company. It also analyzes the impact of different variable selection methods on model performance.
Presenting a Pattern for Increasing the Relative Efficiency of the Bank by Us...IOSR Journals
One of the factors in success of the developed countries is considering the efficiency of units. Efficient units not only do not waste the energy but also they obtain the resources properly. As, in every economy, bank are important institutions and essential posts and have a determinant role in developing the economy, their performance assessment has always been important. In todays world, considering the limitation of resources and excessive cost of providing them, proper decisions about the strategy of applying resources are significant. For the time being, domestic banks use transactional mass–based methods and methods based on performance operations, on the amount of equipment, and on obtaining resources in order to assess the performance & ranking of branches. So efficiency index reflects the process of activity between inputs & outputs of a branch which can be a more suitable criterion in assessing the branches performance. Data envelopment analysis is a theoretical framework in assessing, analyzing, & measuring efficiency which do the function of evaluating Decision making units via solving its own models. In this study, for assessing relative efficiency of Agriculture Bank branches in Lorestan Province, two basic models in Data Envelopment Analysis have been used: input–oriented CCR, BCC. The results of this research show that, among 23 branches under evaluation in CCR model, 6 branches are efficient and 17 are inefficient and among 23 branches in BCC model, 15 branches are efficient and 8 are inefficient. By applying AP model, branches have been ranked and a model has been presented for inefficient branches.
Assessing and improving partnership relationships and outcomes a proposed fr...Emily Smith
This document proposes a framework for assessing partnership relationships and outcomes. The framework aims to: 1) improve partnership practice as programs are implemented, 2) refine and test hypotheses about how partnerships contribute to performance, and 3) provide lessons for future partnerships. The proposed assessment approach is continuous, participatory, and developmental. It measures compliance with partnership success factors, the degree of partnership practices, partnership outcomes, partner performance, and efficiency. The framework integrates process and institutional factors into performance measurement to provide a more holistic view of how partnerships function and contribute to outcomes.
Enhancement of the performance of an industry by the application of tqm conceptseSAT Journals
Abstract Nowadays many companies are unable to prove their performance, because they do not practice the TQM concepts in- total. In order to increase the awareness, certain TQM techniques are suggested to enhance overall performance of the organisations. Here an effort is made to apply two important basic concepts of TQM which are i)continuous improvement of production process by applying newer and innovative methods ii)establishing performance measures for the processes .This paper uses the real experimental results of cartons making industry which comprises the four machines such as Printing , Punching , Gluer and Lamination machines. We get all the machines input and output details, and then made certain suggestions based on the input values of all the four machines. Presently the four machines output values such as Availability, Performance, Quality and Overall Equipment Effectiveness are very low compared with the world class industry. In order to increase them it is suggested to reduce the downtime and other non-productive time by adopting certain simple TQM techniques. The new improved values found to be much higher than the existing values. Keywords: Total Quality Management, Availability, Performance, Quality, Overall Equipment Effectiveness, Quality Improvement.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Application Of The Data Envelopment Analysis Method To Evaluate The Perfor...Karin Faust
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MGT 3302 Case study Last updated July 26, 2019 Page 1 DioneWang844
MGT 3302 Case study
Last updated: July 26, 2019 Page 1 of 2
CASE STUDY
Instructions: This assignment requires that you demonstrate a sound understanding of the
concepts and principles included in this class. Read the case presented below and complete the
assignment presented at the end. Proofread your work before submitting. You can submit
multiple times. I will grade your last submission considering the quality and sufficiency of
answers given, your demonstration of understanding of the concepts included, and the extent to
which you satisfy the questions asked. In addition to the written report, you will need to submit a
video explaining your solution. This video must be less than 4 minutes long. The written report is
worth 50 points. The video is worth 50 points. Total value: 100 points.
MOTORS AND MORE INC.
You are hired as the HR director for the fictitious Motors and More, Inc. This business-to-
business sales company manufactures small motors and accessories for industrial and home
products. The industry is highly competitive and the company follows a prospector strategy.
A prospector strategy takes advantage of new markets and products. Organizational emphasis is
on growth, innovation, and new product development. A prospector wants to be first to the
market. To respond to competitive and rapidly changing markets, prospectors have flexible, flat,
and decentralized organizational structures.
Motors and More is headquartered in a small southern town of 28,000 people, with a low
unemployment rate of 3.1%. This means that demand for workers exceeds labor supply. There is
a technical school and a community college within 50 miles of Motors and More. Motors and
More’s president is a former military and is highly patriotic. He is committed to staying in the
community. Recently, other local companies have experienced labor organizing activities.
Motors and More employs 116 people. Until you were hired, there was no HR department.
Recently, the organization’s employee turnover rate has been higher than normal. The marketing
and sales department continues to sell products to an expanding market. Because of this
increased product demand, output must be increased by 96 percent.
In Motors and More, 88% of the employees are Caucasian. Except for one female supervisor in
the customer service department, the president and all other managers are Caucasian men.
Promotions have been based on seniority. Local labor market is approximately 48% minority,
with a growing Hispanic and Kurdish population not fully accepted into the community.
All the employees in manufacturing (including quality control), customer service and operations
(responsible for shipping and receiving; distribution of raw materials, components parts and
finished goods inventory; and maintenance and cleaning) have at least a high school degree or
GED. The organization provides some skills training courses. P ...
COMPARISON OF BANKRUPTCY PREDICTION MODELS WITH PUBLIC RECORDS AND FIRMOGRAPHICScscpconf
Many business operations and strategies rely on bankruptcy prediction. In this paper, we aim to
study the impacts of public records and firmographics and predict the bankruptcy in a 12-
month-ahead period with using different classification models and adding values to traditionally
used financial ratios. Univariate analysis shows the statistical association and significance of
public records and firmographics indicators with the bankruptcy. Further, seven statistical
models and machine learning methods were developed, including Logistic Regression, Decision
Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and
Neural Network. The performance of models were evaluated and compared based on
classification accuracy, Type I error, Type II error, and ROC curves on the hold-out dataset.
Moreover, an experiment was set up to show the importance of oversampling for rare event
prediction. The result also shows that Bayesian Network is comparatively more robust than
other models without oversampling.
A new Approach towards Cost and Benefit Enterprise Architecture AnalysisEditor IJCATR
This document proposes a new method for analyzing enterprise architecture scenarios in terms of cost and benefit. The method involves 6 steps: 1) determining organization scenarios and their activities, 2) determining quality attributes, 3) determining attribute response levels, 4) assigning activity benefits, 5) computing attribute utilities and estimating costs, and 6) analyzing scenarios based on return on investment. The method is demonstrated through a case study of an Iranian port organization considering two scenarios: increasing passenger transportation capacity and improving security levels. The scenarios are ranked based on their calculated return on investment, with the security improvement scenario found to have a higher ROI.
This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design \& test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of this paper.
International Journal of Business and Management Invention (IJBMI)inventionjournals
This document summarizes a research study that examined the relationships between environmental accounting implementation, environmental performance, environmental disclosure, and company value. The study used a sample of 59 companies in Indonesia. The main findings were:
1) Environmental accounting implementation was found to positively affect company value and environmental disclosure.
2) Environmental disclosure was found to positively affect company value.
3) Environmental performance was found to positively affect company value and environmental disclosure.
4) However, the study did not find environmental accounting implementation or environmental performance to positively affect company value through environmental disclosure. Environmental disclosure did not mediate these relationships.
International Journal of Business and Management Invention (IJBMI)inventionjournals
This document summarizes a study that examined the effect of environmental accounting implementation and environmental performance and disclosure on company value. The study used a sample of 59 companies and analyzed the relationships between environmental accounting, performance, disclosure, and value. The results found that environmental accounting implementation positively impacts company value and disclosure, and disclosure positively impacts value. However, the study did not find environmental accounting or performance to impact value through disclosure.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document discusses the design of performance measurement systems. It begins by defining performance measurement as quantifying the efficiency and effectiveness of actions. It then discusses issues around designing performance measurement systems at three levels: individual measures, the set of measures (system), and how the system relates to the environment.
The document reviews common measures used to quantify quality, time, cost and flexibility. It discusses challenges in measuring these concepts and provides examples of specific measures. Finally, it discusses frameworks for designing holistic performance measurement systems and analyzing systems at the individual measure, set of measures, and environmental relationship levels.
The effectiveness of social and environmental accounting (SEA) depends on two key objectives: 1) meeting stakeholders' non-financial information needs, and 2) enhancing business performance. At a societal level, the most effective SEA maximizes social efficiency by weighing overall societal costs and benefits. At an organizational level, the most effective SEA is the level that equalizes marginal costs and benefits for the reporting organization. The paper reviews economic theories on the costs and benefits of SEA for reporting organizations and society, presents empirical evidence on financial benefits to organizations, and discusses how political systems influence SEA. It concludes by suggesting future research directions.
The document summarizes an instrumental theory of social and environmental accounting (SEA) at the organizational and societal levels of analysis. At the organizational level, the effectiveness of SEA is measured by whether it maximizes the firm's utility by setting the level of SEA where marginal costs equal marginal benefits. At the societal level, effectiveness is measured by the level of SEA that achieves the greatest social efficiency by maximizing aggregate societal well-being relative to costs. The paper then analyzes potential benefits and costs of SEA based on signaling theory and transaction cost economics for both reporting organizations and stakeholders. It concludes by discussing how political governance systems may influence SEA and provides suggestions for future research.
Analysis on the Performance of Technology Companies with Z-score ModeljournalBEEI
Local technology sector plays a significant role in information and communication technology (ICT) based innovations and applications which enhance organizational performance as well as national economic growth and labor productivity. In this paper, financial performance of the listed Malaysia companies in technology sector is analyzed and evaluated. Altman’s Z-score model is proposed due to its robustness in determining companies’ financial distress level using five financial ratios as variables. The computed Z-score values classify the financial status of the companies into distress, grey and safe zones. This study investigates the financial data of 23 listed technology-based companies in the Main Market of Bursa Malaysia over the period of 2013 to 2017. The findings reveal that the percentage of safe zone companies increase throughout the five years whereas distress zone companies decline. It is concluded that financial ratio for market value of equity to total liabilities is the dominant factor that directly influences the level of financial distress among these technology-based companies in Malaysia. These research outcomes provide an insight to investors or policy makers to develop future planning in order to avoid financial failure in local
technology sector.
Today’s competitive environment has, lower manufacturing cost, more productivity in less time, high-quality product, defect-free operation are required to follow to every foundryman. For the improvement of products quality, there are diff-diff quality tools used in various review papers. Here I am going to review these papers and identify the different way of uses of those tools in manufacturing industries to increase the quality of the product. There are so many defects in the manufacturing process and these defects directly affect productivity, profitability and quality level of organization. This study is aimed to review the research work made by several researchers and attempt to get a technical solution for the various defects and to improve the entire process of the manufacturing
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International Journal of Mathematics and Statistics Invention (IJMSI)
1. International Journal of Mathematics and Statistics Invention (IJMSI)
E-ISSN: 2321 – 4767 P-ISSN: 2321 - 4759
www.ijmsi.org Volume 1 Issue 2 ǁ December. 2013ǁ PP-64-68
The contextual factors and efficiency;Data envelopment
analysis approach
Hadi Ghafoorian1, Melati Ahmad Anuar, Nik Intan Norhan2
1
(PHDcandidate, Department of Finance and Accounting, Faculty of Management,
UniversitiTeknologi Malaysia, corresponding author, ghafoorian77@gmail.com)
2
(Senior Lecturer, Department of Finance and Accounting, Faculty of Management,
UniversitiTeknologi Malaysia)
ABSTRACT:Data envelopment analysis (DEA) is a mathematical linear programming approach, based upon
the technical efficiency concept, and it can measure and analyze the technical efficiency of different entities,
productive and non-productive, public and private, profit and non-profit seeking firms. This non-parametric
approach calculates the efficiency level by performing linear calculations for each unit in the sample. Context
factors impact on efficiency level of organization that isn’t under control of management. In this paper we
define context factors and investigate the various methods of DEA that consider the role of contextual factors.
KEYWORDS:Data envelopment analysis; Efficiency; Contextual factors
I. INTRODUCTION
Evaluation of performance and productivity are among fundamental concepts in economy and
management. It is very clear to calculate the firm efficiency on the basis of their output and input. Efficient
organizations try to have maximized output production with given input or minimize input usage in the
production of given outputs, relative to the performance of other producers in some comparison set.
Data envelopment analysis (DEA) is applied for estimating efficiency, and it is a helpful and popular
nonparametric modeling approach. The DEA technique has been implemented to appraise efficiency of
company across a variety of organizations, including industrial, commercial, educational, and financial services
[2]. Since 1978 when Charnes, Cooper and Rhodes(CCR) offered a mathematical programming formulation for
the empirical evaluation of relative efficiency of the observed quantities of input and output for a group of
similar referent DMUs until now, DEA has kept improving. Primary input-oriented DEA efficiency scores have
estimated the relative reduction in input while the level of output is maintained. It is very important for
researchers that they know what the inefficiency factors are, and there is a desire to separate the component of
inefficiency that is under the control of management from the component that is out of management’s control.
To answer such a subject, the standard DEA model has been adjusted to distribute non-controllable or
environmental factors [12].
There are three distinctive factors that impact on efficiency level of organization. The first one is the
role of manager who directs production activities. The second one is environmental factors that surround an
organization. Finally, the role of luck, related variables and omitted factors that have influence in the process of
regression assessment [3]. The managerial factors have internal source and the other two have external source. It
is apparent that understanding the impact of three factors is so desirable in efficiency evaluation. To achieve
this, we would have information about environmental features, input and output, and improve the standard DEA
that consider environmental characteristics. Furthermore, in order to eliminate the impact of luck on efficiency
of firm, the model must be stochastic. However, most DEA models and virtually all operational DEA models
are deterministic.
II. PROBLEM STATEMENT
Traditionally, the efficiency is the ratio of output to input, so recognition of input and output is so
important to account efficiency. On the other hand, the contextual factors impact on input as a result of impact
on efficiency. Hence, in the first place, to estimate efficiency we are required to know what contextual factors
are and in the second place what the method is to calculate efficiency with contextual factors. We will review
the previous researches that used diffident methods in solving this problem and we will discuss contextual
factors.
www.ijmsi.org
64 | P a g e
2. The contextual factors and efficiency…
2.1 Deta Envelopment Analysis
DEA is a mathematical linear programming approach based upon the technical efficiency concept and
it can measure and analyze the technical efficiency of different entities, public and private, productive and nonproductive, profit and non-profit seeking firms. This non-parametric approach calculates efficiency level by
performing linear calculations for each unit in the sample. In this model, the efficiency of decision-makingunits
is estimated by comparing them with the best unit in the statistical sample.
In measuring relative units, Farrell focused on weighted sum of input in order to make a virtual unit.
The following equation was proposed as normal tool to measure technical efficiency [9].
(1)
DEA is able to estimatethe operational efficiency in consistent units with comparing them through a
number of sampled units, which form together a curve of efficiency frontier that envelope all observations [9].
This approach is called DEA because it envelops all observations[9]. Therefore, all efficient decision-making
units will be on the curve of efficient frontier. Other decision-making units that are not on the curve are certainly
inefficient.
For example, in Figure 1,five DMUs (A, B, C, D, and E) were shown which each of them had two
inputs X1 and X2 to produce Y quantity of output. The level of efficiency for each unit was determined by
related data of inputand outputas shown in Figure 1. The B, C and E DMUs have the lie on frontier curve,as a
result they are efficient, while Aand D DMUs are not on efficient curve hence, they are inefficient.
It is remarkable we know that, based upon the theoretical concepts, to be on the efficient frontier curve
is not the sign of optimal efficiency, but also represents a virtual performance. Accordingly, the actual style of
the distribution process of resources and products ismirrored in this model. In fact, DEA helps to recognize
inefficiency decision-making units and to improve themselves. To be efficient units and inefficient units near
each other provide an opportunity to identify inefficient and trying to improve it [7].
2.2 Contextual factors
All organizations run in a competitive environment that has different and various dimensions. Some of
them are controllable by manager while some of them are out of control. Although, some nondiscretionary
factors are effective in the trend of running organization,they aren’t observable. To the best of our knowledge
from investigation on various articles, there are several words for the same concept in this case. As seen, the
word contextual is replaced by other terms such as environmental [3], [4], external factors [8] and nondiscretionary factors [1]. In this respect, all firms compete in a context such as environment, position, rules and
regulations, the power of unions and etc. Thus, the terms environmental, external and nondiscretionary are not
as comprehensive as the term contextual, since it encompasses a broader range of the related concepts such as
the ones mentioned above [1].
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3. The contextual factors and efficiency…
Contrariwise, the concept of context can be a competent word to represent and express this concept.
Characteristics of contextual factors are: unobservable, non controllable, able to influence and external resource.
III. DEA MODELS AND CONTEXTUAL FACTORS
There are several models that the contextual factors take into consideration to estimate performance in
the following sections:
3.1 Banker and Morey
Banker and Morey want to improve the CCR and BCC models in order to account the extent to which
the discretionary or manageable input can be reduced by the DMU manager while keeping the exogenously
fixed input at their current. They used DEA standard model and modified that how can account exogenously
fixed inputs. Banker and Morey classified exogenously fixed input form high until low, and estimated their
impact on the efficiency of firm. Indeed, they succeeded to drive out one of the constraints in standard equation
[10].
They tested their model on 60 fast food restaurants. In this example, they particularly served to
illustrate the impact of fixed uncontrollable input. They compared the difference in controllable input targets
that results from two different treatments of the non-discretionary input; one in which all input is indeed treated
as discretionary, and the other in which only the truly controllable inputs are treated as discretionary. They
measured data on 6 inputs and 3 outputs for 60 restaurants in the fast food chain. All output was controllable and
only 4 inputs including supplies, materials, the age of the store, and the cost of advertising were clearly
discretionary. Last 2 inputs were demographic and pointed out whether the store was located in an urban or rural
area that they were contextual, uncontrollable and non-discretionary [10].
3.2 Ray’s model
To calculate efficiency in public schools, Ray offered a two-stage model for the first time. He classified
endogenous factors that directly affect efficiency. He used standard DEA in the first stage and then in the second
stage he used other socio-economic factors (contextual factors) as exogenous factors in a regression model [11].
This approach requires a priori functional form specification for the second-stage regression; mis- specification
leads to distorted measurement [6].
3.3 Ruggiero’s Model
In the first place, Ruggiero started his argument with the main purpose of developing a modified DEA
model that maintains consistency with known properties of public sector production. His model expanded the
Banker and Morey model to enable or activate uninterrupted contextual (environmental) variables [5]. This
model breaks the limits of categorizing the environment. In essence, the presence of non-discretionary input
leads to different frontiers. To control these fixed factors, Ruggiero added constraints to exclude DMUs for
more favorable production environment [6].
He criticized the two-stage models in research and presented a three-stage model. This model was
constructed on convexity assumption for contextual input. Ruggiero, in the first place, estimated efficiency by
standard DEA regardless of environment variables. In the second stage, all contextual or environmental factors
regressed with quantity of DEA obtained from stage one. Subsequently, he made indicatorZjinstead of
intervening contextual effects from the following equation:
(2)
While,
(3)
After that, the weights λh conditioned on indicator Zj was calculated, So that any firm having a more
favorable environment than that of firm j will not be included in the frontier. Solving the following problem was
the third stage of his model:
j=1,…,J
s.t
(4)
k=1,…,n
(5)
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4. The contextual factors and efficiency…
i=1,…,m
(6)
if
h=1,…,J
if
(7)
VRS
(8)
Ruggiero believed that the three-stage model took preference over the two-stage model due to
assuming that the second-stage regression produces unbiased estimates of the parameter weights the model
maintains for the desirable properties of the Ruggiero model. Second, this model overcomes the identified
weakness of identifying DMUs as efficient by default inherent in the Ruggiero model. Instead, this model is able
to weigh the importance of the non-discretionary input. Furthermore, Ray's model uses the error term to measure
efficiency, and hence, will be sensitive to mis-specification [6].
3.4 Four- stage Model
Fried et al (1999) offered a different approach for accounting contextual factors on DEA that involves
four stages. Like other models, in the first stage they accounted the standard DEA by normal input and output
while contextual variables were kept out. For each observation, they calculated scores of radial technical
efficiency. Followed by, every dependent variable for each equation is identified as sum of non-radial and radial
input for an input-oriented model or radial plus non-radial output surplus for an output-oriented model in the
stage two. Characteristic of contextual factors was measured by independent variables in this stage. The
variation in total by-variable measures of inefficiency chargeable to factors outside the control of management
was identified by made equation system. Subsequently, they predicted the total output surplus or input from the
second stage using the parameter estimates in the third stage. Eventually, the fourth step was to repeat the DEA
model under the specification of initial input, using the set of adjusted data [4].
3.5 Multi-stage
Fried et al (1999) offered a different approach for accounting contextual factors on DEA that involves
four stages. Like other models, in the first stage they accounted the standard DEA by normal input and output
while contextual variables were kept out. For each observation, they calculated scores of radial technical
efficiency. Followed by, every dependent variable for each equation is identified as sum of non-radial and radial
input for an input-oriented model or radial plus non-radial output surplus for an output-oriented model in the
stage two. Characteristic of contextual factors was measured by independent variables in this stage. The
variation in total by-variable measures of inefficiency chargeable to factors outside the control of management
was identified by made equation system. Subsequently, they predicted the total output surplus or input from the
second stage using the parameter estimates in the third stage. Eventually, the fourth step was to repeat the DEA
model under the specification of initial input, using the set of adjusted data [4].
(9)
Then, a relationship between contextual input and slacks was investigated by SFA
i=1,…, m
(10)
(11)
In order to regulate all discretionary inputs the following equation is used:
,
In the third stage, DEA is reused to modify data
score of organization efficiency.
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i= 1,…,J
and output
(12)
with the aim of accounting each
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5. The contextual factors and efficiency…
IV. SUMMARY
In this paper, the concept of contextual factors was defined and equivalents of this concept were
investigated in other papers. Generally, the contextual factors in organization have three essential features as
follows:
They are external factors;
They are out of control;
They impact on input while not observables;
Data envelopment analysis is a popular and flexible method to account efficiency of firms. As mentioned,
contextual factors impact the efficiency of firms and there are several models to estimate efficiency in this
situation that is classified in the table below:
row
Creator(s) model
year
1
Banke& Morey
1990
2
3
4
5
6
Roy
Ruggiero
Ruggiero
Fried et al
Fried et al
1991
1996
1997
1999
2002
consideration
It is good when we can classify contextual factors in the
specific ranked category
Two-stage model ,use DEA and regress
Two-stage
Three-stage
Four-stage
Multi-stage , use DEA and SFA
V. ACKNOWLEDGMENTS
We would like to thank Universiti Teknologi Malaysia (UTM) for supporting this researchfinancially.
The authors gratefully acknowledge the IDF financial support from Universiti Teknologi Malaysia.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
A. C. Worthington and B. E. Dollery, Incorporating contextual information in public sector efficiency analyses: a comparative
study of nsw local government, Applied economics, 34(1): 453- 464, 2002.
A.Chanes; W. W. Cooper and E. Rhodes, Measuring the efficency of decision making units, European journal of operational
research, 2:429- 444, 1978.
H. O. Fried; C. A.K. Lovell; S. S. Schmidt and S. Yaisawarng, Accounting for environmental effects and statistical noise in data
envelopment analysis. Journal of productivity analysis 17, 157-174, 2002.
H. O. Fried; S. S. Schmidt and S. Yaisawarng, Incorporating the operating environment into a nonparametric measure of
technical effciency, Journal of productivity analysis 12, 249-267, 1999
J. Ruggiero, On the measurement of technical efficiency in the public sector, European Journal of Operational Research, 90: 553565, 1996.
J. Ruggiero, Theory and methodology non-discretionary inputs in data envelopment analysis, European Journal of Operational
Research, 111:461-469, 1998
K. S. K. Al-Delaimi and A. H. B. Al-Ani, Using data envelopment analysis to measure cost efficiency with an application on
Islamic bank, scientific journal of administrative development, 4: 134-156, 2006.
M. A. Muniz, O. R. Applications Separating managerial inefficiency and external conditions in data envelopment analysis,
European Journal of operational research, 143:624-643, 2002.
M. J. Farrell, The measurement of productive efficiency, journal of the royal statistical society, 120: 253- 281, 1957.
R.J. Banker and R.C. Morey, Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34,4: 513-524,
1986.
S.C. Ray, Resource-use efficiency in public schools: a study of connecticut data. Management Science, 37: 1620-1628, 1991.
Ya. Chunyan, Theory and methodology: the effects of exogenous variables in efficiency measurement a monte carlo study,
European journal of operational research, 105: 569-580, 1998.
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