Managerial Decision Problems Research Articles

Optimal pricing model for non-instantaneous deterioration items with price and freshness sensitive demand under the e-commerce environment in China

PurposeThe purpose of this paper is to focus on determining the optimal sales price for non-instantaneous deterioration items according to consideration of freshness and demand.Design/methodology/approachIn this model, the authors have described the demand function which is dependent on price as well time. The products that the deterioration is considered as non-instantaneous have a determinate shelf life, and their demand rate will decrease over time after the beginning of the selling period. This paper depicts that the total profit of non-instantaneous deterioration items using the dynamic pricing strategy is higher than that using fixed pricing strategy.FindingsFinally, to illustrate and validate the model, the authors have used some numerical examples. A new freshness function and the model to study pricing policy are developed as well applied to solve managerial decision problems.Originality/valueThis paper complements the lack of the existing theoretical research of pricing for non-instantaneous deterioration items under an e-commerce environment. A new freshness function and the model to study pricing policy are developed as well applied to solve managerial decision problems.

Causal Machine Learning and Business Decision Making

Causal knowledge is critical for strategic and organizational decision making. By contrast, standard machine learning approaches remain purely pattern and prediction-based, rendering them unsuitable for being applied to a wide variety of managerial decision problems. Taking a mixed-methods approach, which relies on multiple sources, including semi-structured interviews with data scientists and decision makers, as well as quantitative survey data, this study makes a first attempt at delineating causality as a critical boundary condition for the application of machine learning in business. It highlights the crucial role of theory in causal inference and offers a new perspective on human-machine interaction for data-augmented decision making.

Causal Machine Learning and Business Decision Making

Causal knowledge is critical for strategic and organizational decision-making. By contrast, standard machine learning approaches remain purely correlational and prediction-based, rendering them unsuitable for addressing a wide variety of managerial decision problems. Taking a mixed-methods approach, which relies on multiple sources, including semi-structured interviews with data scientists and senior decision-makers, as well as quantitative survey data, this study argues that causality is a critical boundary condition for the application of machine learning in a business analytical context. It highlights the crucial role of theory in causal inference and offers a new perspective on human-machine interaction for data-augmented decision making.

Overconfidence in Probability Distributions: People Know They Don’t Know but They Don’t Know What to Do About It

Quantifying uncertainty in the form of a probability distribution is a critical step in many managerial decision problems. However, a large body of previous work has documented pervasive overconfidence in subjective probability distributions (SPDs). We develop new methods to analyze judgments about variables which entail both epistemic and aleatory uncertainty and, in three experiments, study the quality of people’s SPDs in such settings. We find that although SPDs roughly match the aleatory concentration of the real-world distributions, people’s judgments are consistently overconfident because they fail to spread out probability mass to account for their own epistemic uncertainty about the location and other properties of the distribution. Although people are aware of this lack of knowledge, they do not know how to appropriately incorporate it into their SPDs. Our results offer new insights into the causes of overconfidence in real-world judgment domains and shed light on potential ways to address this fundamental bias.

ПОДДЕРЖКА ПРИНЯТИЯ РЕШЕНИЙ ПРИ УПРАВЛЕНИИ ПРОЦЕССОМ РЕОРГАНИЗАЦИИ СОЦИАЛЬНЫХ ИНСТИТУТОВ РЕСПУБЛИКИ БАНГЛАДЕШ

The paper deals with the problem of managing the process of reorganizing the social institutions in the People’s Republic of Bangladesh and with possible solutions through the use of decision support methods. This problem arose as a result of the implementation of social programs aimed at increasing the social institution effectiveness on the basis of autonomy of social institutions from the state subsidies. To formalize the system of social institutions, a graph representation is proposed. The project of the theoretical foundations of decision support in managing the reorganization of social institutions is presented by the method that uses the comparison of alternatives. The control actions are formed decisions taken on changing the current structure of social institutions aimed at maximizing the utility function value. Using the method of managerial choice on the modification of available network at the cost of adding the new social institution has been demonstrated by the example of the a managerial decision problem including a new social institution “hospital”. There have been singled out the groups of criteria which are used to estimate the alternatives. To increase the quality of decision making there has been applied a second assessment of generalized criteria, analyzed the nature of hierarchical structure of the network and a geographic situation of the new node.

OPTIMIZATION OF RESOURCES WITH THE AID OF LINEAR PROGRAMMING MODEL IN STEVE SHOE PRODUCTION CENTRE, ENUGU, NIGERIA

This paper studied the optimization of resources with the aid of linear' programming model in Steve Shoe Production Centre (SSPC), Enugu. The Linear programming model is a complex mathematical tool used for solving managerial decision problems. From the researcher's observation, Steve Shoe Production Centre depended completely on trial and error method of decision making which often yielded suboptimal results. This gap brought about the need to amongst others demonstrate how the linear programming model developed in this study can assist SSPC Enugu to optimize its resources for effective output decisions. Review of related literature was performed. The findings show that the linear programming model developed by the researcher is workable for optimal results in Steve Shoe Production Centre, Enugu.

A decision support system for vessel speed decision in maritime logistics using weather archive big data

Speed optimization of liner vessels has significant economic and environmental impact for reducing fuel cost and Green House Gas (GHG) emission as the shipping over maritime logistics takes more than 70% of world transportation. While slow steaming is widely used as best practices for liner shipping companies, they are also under the pressure to maintain service level agreement (SLA) with their cargo clients. Thus, deciding optimal speed that minimizes fuel consumption while maintaining SLA is managerial decision problem. Studies in the literature use theoretical fuel consumption functions in their speed optimization models but these functions have limitations due to weather conditions in voyages. This paper uses weather archive data to estimate the real fuel consumption function for speed optimization problems. In particular, Copernicus data set is used as the source of big data and data mining technique is applied to identify the impact of weather conditions based on a given voyage route. Particle swarm optimization, a metaheuristic optimization method, is applied to find Pareto optimal solutions that minimize fuel consumption and maximize SLA. The usefulness of the proposed approach is verified through the real data obtained from a liner company and real world implications are discussed.

Learning and Education Experience in System Dynamics of Management Students

Article describes experiences in the teaching of a modelling and simulation course for students at Faculty of Organizational Sciences. The course consists of time-continuous simulation based on System Dynamics (SD) and discrete event simulation (DES). It is held in the 3rd year of studies, at which point students have taken courses in mathematics, statistics, theory of systems, as well as organizational and economic courses. The final grade for the course is derived from the student's project and written exam. Students took part in an experiment where they had to solve a managerial decision problem supported by a simulation model. Experimental results were then analysed and discussed in the students' projects. Students' contributions were part of their final grade. The results show that students, taking the course of Modelling and Simulation, thought that application of the simulation model contributes to a greater understanding of the problem, the faster finding of solutions, and enhanced confidence of the participants. The results are explained and discussed using a learning model.

RESEARCH AND TECHNOLOGY DEVELOPMENT FOR CONSTRUCTION OF 3D VIDEO SCENES

For the last two decades surface information in the form of conventional digital and analogue topographic maps has been being supplemented by new digital geospatial products, also known as 3D models of real objects. It is shown that currently there are no defined standards for 3D scenes construction technologies that could be used by Russian surveying and cartographic enterprises. The issues regarding source data requirements, their capture and transferring to create 3D scenes have not been defined yet. The accuracy issues for 3D video scenes used for measuring purposes can hardly ever be found in publications. Practicability of development, research and implementation of technology for construction of 3D video scenes is substantiated by 3D video scene capability to expand the field of data analysis application for environmental monitoring, urban planning, and managerial decision problems. The technology for construction of 3D video scenes with regard to the specified metric requirements is offered. Technique and methodological background are recommended for this technology used to construct 3D video scenes based on DTM, which were created by satellite and aerial survey data. The results of accuracy estimation of 3D video scenes are presented.

RESEARCH AND TECHNOLOGY DEVELOPMENT FOR CONSTRUCTION OF 3D VIDEO SCENES

Abstract. For the last two decades surface information in the form of conventional digital and analogue topographic maps has been being supplemented by new digital geospatial products, also known as 3D models of real objects. It is shown that currently there are no defined standards for 3D scenes construction technologies that could be used by Russian surveying and cartographic enterprises. The issues regarding source data requirements, their capture and transferring to create 3D scenes have not been defined yet. The accuracy issues for 3D video scenes used for measuring purposes can hardly ever be found in publications. Practicability of development, research and implementation of technology for construction of 3D video scenes is substantiated by 3D video scene capability to expand the field of data analysis application for environmental monitoring, urban planning, and managerial decision problems. The technology for construction of 3D video scenes with regard to the specified metric requirements is offered. Technique and methodological background are recommended for this technology used to construct 3D video scenes based on DTM, which were created by satellite and aerial survey data. The results of accuracy estimation of 3D video scenes are presented.

Wykorzystanie metod ELECTRE w projektowaniu złożonych systemów organizacyjnych

The paper focuses on a formal approach to the diagnosis and design of enterprise management systems when there is a lack of complete and accurate information. It first discusses the multicriteria evaluation system, in which the preferences of the decision-maker are modeled based on outranking relations. The binary outranking relation is typically used in ELECTRE methods. These methods involve a set of analytical procedures which allow the user to select, categorise and rank decision alternatives. The overall outranking preference in this method is developed according to the principle of concordance and disconcordance. In the article the basic relationships and thresholds used in preferences modeling are defined. The ELECTRE I method was introduced to illustrate this type of approach. The last part of the paper presents a method for determining the weights of evaluation criteria recommended for the ELECTRE methods. This method can also be used in other approaches to solve complex managerial decision problems.

A rank-based approach to the sequential selection and assignment problem

In the classical sequential assignment problem, “machines” are to be allocated sequentially to “jobs” so as to maximize the expected total return, where the return from an allocation of job j to machine k is the product of the value x j of the job and the weight p k of the machine. The set of m machines and their weights are given ahead of time, but n jobs arrive in sequential order and their values are usually treated as independent, identically distributed random variables from a known univariate probability distribution with known parameter values. In the paper, we consider a rank-based version of the sequential selection and assignment problem that minimizes the sum of weighted ranks of jobs and machines. The so-called “secretary problem” is shown to be a special case of our sequential assignment problem (i.e., m = 1). Due to its distribution-free property, our rank-based assignment strategy can be successfully applied to various managerial decision problems such as machine scheduling, job interview, kidney allocations for transplant, and emergency evacuation plan of patients in a mass-casualty situation.

On Managerial Decision Problem of the Auction Sites

This paper studies one managerial decision problem of the auction sites: how to combine penalties with commissions? It is shown that when there exists secondary auction market, the auction whose penalty is a linear function of the seller’s commission will be more efficient than the auction with only commissions but no penalties. It has also been proven that using this strategy can maximize the expected revenue for the seller, the auction site and their total expected revenues.

An Empirical Examination of Competing Theories to Explain the Framing Effect in Accounting-Related Decisions

The purposes of this study are to explore framing effects in a managerial accounting decision context and to test the explanatory power of prospect theory and two competing theories, fuzzy-trace theory and probabilistic mental models, on such effects. In Experiment 1, 86 undergraduate students made a choice between two alternatives in a managerial decision problem that illustrates a classic, Asian disease-type business scenario. Results show that the subjects committed the framing effect bias and that prospect theory, fuzzy-trace theory, and probabilistic mental models all predict the bias. In Experiment 2, a business variant of the Asian disease problem was designed to distinguish among the explanatory abilities of these theories in an accounting context. One hundred eighty-five undergraduate students participated in the experiment. Results of Experiment 2 indicate that the fuzzy-trace theory provides additional power to explain the framing effect. Hence, accounting professionals can design better approaches to reporting/presenting financial information that will help managers alleviate the framing effect in decision making.

Temporal interdependence in fuzzy MCDM problems

Contemporaneous MCDM methodology is based on the simplifying assumption of independent objectives. This restriction was partly relaxed through the concept of (static) interdependent objectives introduced by C. Carlsson and R. Fuller. Most real world managerial decision problems involve interdependent objectives, yet in a temporal setting. In the paper we generalize the static concept to temporal fuzzy multiobjective programming problem. We introduce the concepts temporal support and temporal conflict in the objective set within both infinite and finite planning horizons. We also formulate dynamic versions of membership functions for interdependent objectives in crisp and fuzzy multiobjective programming problems. The new concepts are used to describe and model temporal goal conflicts in numerical illustrations.

An Integer Linear Programming Model for the Cargo Airline Parts Inventory Problem

Abstract The advent of the overnight delivery service has made significant changes in the operation of manufacturing and service companies. The parts inventory problem of cargo airlines serving overnight delivery companies is an important managerial decision problem, requiring efficient allocation of resources. An integer programming formulation is presented to determine the parts inventory requirement of each airport outstation. The model incorporates transportation costs and penalty costs for flight delays due to unavailability of needed parts. A solution approach exploiting the special structure of the model is developed. We apply die problem formulation and the solution technique to an actual data set and report the results.

Note—On Choosing Between Rev. Bayes and Prof. Von Neumann

In a recent issue of Management Science, Kadane and Larkey [10], [11] debated with Harsanyi [8], [9] on the relative merits of strategic policies derived from game theoretic vs. Bayesian decision-theoretic orientations. While the fact that the two orientations are virtually first cousins gives a Middle Eastern flavor to the discussion, just as the problems of that unfortunate spot on the globe, the two orientations have substantive differences that should be attended to by people faced with managerial decision problems modelled as games.

Decision Analysis for Small Business

Decision analysis is a relatively recent subject to enter the field of managerial decision-making. The application of decision analysis to managerial decision problems is useful especially in situations where the problem is complex, outcomes are risky, and intuitive judgments are rather difficult. This paper discusses the fundamental concepts of decision analysis and illustrates its utility to small business executives in analyzing and resolving their problems more effectively. It is shown that the decision analysis approach is an extension of the executive's natural problem solving style—that of analyzing contingencies—and can increase the information base useful in making better intuitive decisions.

Intuitive versus optimal solutions to some problems in distribution

This paper is concerned with the issue of assessing the relative performance of unaided decision-makers and model-based optimal solutions to managerial decision problems. This has important implications for project selection, research direction and management training. Some possible approaches designed to achieve such comparisons are examined and examples given. Some experimental studies are reported, set in the context of distribution management, which make use of one of the research strategies discussed.

Relative contribution of decision-maker attributes to decision processes

The individual and joint contributions to decision processes of psychological and demographic attributes of decision-makers were empirically investigated for a sample of 79 industrial managers. Performance in decision-making was determined by the Personnel Decision Simulation, a simulated managerial decision problem which permits observation and measurement, in a standardized situation, of eight decision processes. It was found the cognitive attributes contributed heavily to the evaluative aspects of decision-making, i.e., judging information diagnosticity and integrating it into a high quality solution, particularly to predecision and decision point behavior. Motivational and personality attributes influenced stylistic or idiosyncratic behaviors leading to a choice (e.g., amount of information sought and processing rate) and was especially influential on post-decisional behaviors (e.g., decision confidence and decision flexibility).