Mathematics

Research

18 pages, 248 KiB

Open AccessArticle

The Impact of the Disclosed R & D Expenditure on the Value Relevance of the Accounting Information: Evidence from Greek Listed Firms

by Petros Kalantonis, Sotiria Schoina, Spyros Missiakoulis and Constantin Zopounidis

Mathematics 2020, 8(5), 730; https://doi.org/10.3390/math8050730 - 6 May 2020

Cited by 13 | Viewed by 3001

Abstract

Although many empirical studies have focused on R & D performance models for markets globally, the available financial information for R & D expenditure is limited. In other words, can we assume that the reported accounting information for R & D investment is [...] Read more.

Although many empirical studies have focused on R & D performance models for markets globally, the available financial information for R & D expenditure is limited. In other words, can we assume that the reported accounting information for R & D investment is adequate and valuable? This study empirically investigates the effect of R & D reported information on the value relevance of the accounting information of firms’ financial statements. Specifically, using Ohlson’s equation, it is examined whether changes in stock prices are explained better when R & D factors are included in models, in conjunction with changes in book value and abnormal earnings. We focus on listed firms on the Athens Stock Exchange in order to explore whether R & D expenses are value relevant, in a market which has been affected for a long period by the global economic crisis of 2007. In our findings, we observe that the reported R & D expenses do not have any significant influence on the investors’ choices, in contrast to expectations based on the prior literature. Moreover, the panel data analysis employed in the paper overcomes common methodological problems (such as autocorrelation, multicollinearity, and heteroscedasticity) and allows the estimation of unbiased and efficient estimators. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

15 pages, 1777 KiB

Open AccessArticle

A Bradley-Terry Model-Based Approach to Prioritize the Balance Scorecard Driving Factors: The Case Study of a Financial Software Factory

by Vicente Rodríguez Montequín, Joaquín Manuel Villanueva Balsera, Marina Díaz Piloñeta and César Álvarez Pérez

Mathematics 2020, 8(2), 276; https://doi.org/10.3390/math8020276 - 19 Feb 2020

Cited by 6 | Viewed by 5272

Abstract

The prioritization of factors has been widely studied applying different methods from the domain of the multiple-criteria decision-making, such as for example the Analytic Hierarchy Process method (AHP) based on decision-makers’ pairwise comparisons. Most of these methods are subjected to a complex analysis. [...] Read more.

The prioritization of factors has been widely studied applying different methods from the domain of the multiple-criteria decision-making, such as for example the Analytic Hierarchy Process method (AHP) based on decision-makers’ pairwise comparisons. Most of these methods are subjected to a complex analysis. The Bradley-Terry model is a probability model for paired evaluations. Although this model is usually known for its application to calculating probabilities, it can be also extended for ranking factors based on pairwise comparison. This application is much less used; however, this work shows that it can provide advantages, such as greater simplicity than traditional multiple-criteria decision methods in some contexts. This work presents a method for ranking the perspectives and indicators of a balance scorecard when the opinion of several decision-makers needs to be combined. The data come from an elicitation process, accounting for the number of times a factor is preferred to others by the decision-makers in a pairwise comparisons. No preference scale is used; the process just indicates the winner of the comparison. Then, the priority weights are derived from the Bradley-Terry model. The method is applied in a Financial Software Factory for demonstration and validation. The results are compared against the application of the AHP method for the same data, concluding that despite the simplifications made with the new approach, the results are very similar. The study contributes to the multiple-criteria decision-making domain by building an integrated framework, which can be used as a tool for scorecard prioritization. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

12 pages, 800 KiB

Open AccessArticle

Robust Optimization Model with Shared Uncertain Parameters in Multi-Stage Logistics Production and Inventory Process

by Lijun Xu, Yijia Zhou and Bo Yu

Mathematics 2020, 8(2), 211; https://doi.org/10.3390/math8020211 - 7 Feb 2020

Cited by 1 | Viewed by 3052

Abstract

In this paper, we focus on a class of robust optimization problems whose objectives and constraints share the same uncertain parameters. The existing approaches separately address the worst cases of each objective and each constraint, and then reformulate the model by their respective [...] Read more.

In this paper, we focus on a class of robust optimization problems whose objectives and constraints share the same uncertain parameters. The existing approaches separately address the worst cases of each objective and each constraint, and then reformulate the model by their respective dual forms in their worst cases. These approaches may result in that the value of uncertain parameters in the optimal solution may not be the same one as in the worst case of each constraint, since it is highly improbable to reach their worst cases simultaneously. In terms of being too conservative for this kind of robust model, we propose a new robust optimization model with shared uncertain parameters involving only the worst case of objectives. The proposed model is evaluated for the multi-stage logistics production and inventory process problem. The numerical experiment shows that the proposed robust optimization model can give a valid and reasonable decision in practice. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

18 pages, 1672 KiB

Open AccessArticle

Integrated Production and Distribution Problem of Perishable Products with a Minimum Total Order Weighted Delivery Time

by Ling Liu and Sen Liu

Mathematics 2020, 8(2), 146; https://doi.org/10.3390/math8020146 - 21 Jan 2020

Cited by 57 | Viewed by 4696

Abstract

In this paper, an integrated production and distribution problem for perishable products is presented, which is an NP hard problem where a single machine, multi-customers, and homogenous vehicles with capacity constraints are considered. The objective is to minimize the total order weighted delivery [...] Read more.

In this paper, an integrated production and distribution problem for perishable products is presented, which is an NP hard problem where a single machine, multi-customers, and homogenous vehicles with capacity constraints are considered. The objective is to minimize the total order weighted delivery time to measure the customer service level, by making two interacted decisions, production scheduling and vehicle routing, simultaneously. An integrated mathematical model is built, and the validity is measured by the linear programming software CPLEX by solving the small-size instances. An improved large neighborhood search algorithm is designed to address the problem. Firstly, a two-stage algorithm is constructed to generate the initial solution, which determines the order production sequence according to the given vehicle routing. Secondly, several removal/insertion heuristics are applied to enlarge the search space of neighbor solutions. Then, a local search algorithm is designed to improve the neighbor solutions, which further generates more chances to find the optimal solution. For comparison purposes, a genetic algorithm developed in a related problem is employed to solve this problem. The computational results show that the proposed improved large neighborhood search algorithm can provide higher quality solutions than the genetic algorithm. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

19 pages, 2828 KiB

Open AccessArticle

Impacts of Online and Offline Channel Structures on Two-Period Supply Chains with Strategic Consumers

by Qian Lei, Juan He and Fuling Huang

Mathematics 2020, 8(1), 34; https://doi.org/10.3390/math8010034 - 27 Dec 2019

Cited by 5 | Viewed by 3457

Abstract

In this paper, the effects of strategic consumer behaviors have been investigated and analyzed with regard to online retailers and offline retailers in a dual-channel supply chain. Four channel structures (i.e., no-promotion, a direct online channel, a retail offline channel, and dual channels [...] Read more.

In this paper, the effects of strategic consumer behaviors have been investigated and analyzed with regard to online retailers and offline retailers in a dual-channel supply chain. Four channel structures (i.e., no-promotion, a direct online channel, a retail offline channel, and dual channels introduced in the promotion sales period) are considered. At the beginning of the paper, the original demand functions of a dual-channel supply chain incorporating the consumers’ utility has been introduced. The results indicate that despite improved consumer patience, all promotional prices do not fall as expected. When sales channels are provided by online retailers rather than offline retailers during the promotion period, offline retailers can achieve higher profits. We also find that in most cases, a dual-channel model in a single-period is more beneficial to both online and offline retailers than a dual-channel model in two periods, which is, to a certain extent, contrary to the existing literature of single sales channel. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

25 pages, 2522 KiB

Open AccessArticle

Digital Supply Chain through Dynamic Inventory and Smart Contracts

by Pietro De Giovanni

Mathematics 2019, 7(12), 1235; https://doi.org/10.3390/math7121235 - 13 Dec 2019

Cited by 25 | Viewed by 5077

Abstract

This paper develops a digital supply chain game, modeling marketing and operation interactions between members. The main novelty of the paper concerns a comparison between static and dynamic solutions of the supply chain game achieved when moving from traditional to digital platforms. Therefore, [...] Read more.

This paper develops a digital supply chain game, modeling marketing and operation interactions between members. The main novelty of the paper concerns a comparison between static and dynamic solutions of the supply chain game achieved when moving from traditional to digital platforms. Therefore, this study proposes centralized and decentralized versions of the game, comparing their solutions under static and dynamic settings. Moreover, it investigates the decentralized supply chain by evaluating two smart contracts: Revenue sharing and wholesale price contracts. In both cases, the firms use an artificial intelligence system to determine the optimal contract parameters. Numerical and qualitative analyses are used for comparing configurations (centralized, decentralized), settings (static, dynamic), and contract schemes (revenue sharing contract, wholesale price contract). The findings identify the conditions under which smart revenue sharing mechanisms are worth applying. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Graphical abstract

7 pages, 370 KiB

Open AccessArticle

Customer Exposure to Sellers, Probabilistic Optimization and Profit Research

by Miltiadis Chalikias, Panagiota Lalou and Michalis Skordoulis

Mathematics 2019, 7(7), 621; https://doi.org/10.3390/math7070621 - 12 Jul 2019

Cited by 4 | Viewed by 2577

Abstract

This paper deals with a probabilistic problem in which there is a specific probability for a customer to meet a seller in a specified area. It is assumed that the area in which a seller acts follows an exponential distribution and affects the [...] Read more.

This paper deals with a probabilistic problem in which there is a specific probability for a customer to meet a seller in a specified area. It is assumed that the area in which a seller acts follows an exponential distribution and affects the probability of meeting with a customer. Furthermore, the range in which a customer can meet a seller is another parameter which affects the probability of a successful meeting. The solution to the problem is based on a bomb fragmentation model using Lagrange equations. More specifically, using Lagrange equations, the abovementioned dimensions will be calculated in order to optimize the probability of a customer meeting a seller. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

17 pages, 647 KiB

Open AccessArticle

A Novel Coordinated TOPSIS Based on Coefficient of Variation

by Pengyu Chen

Mathematics 2019, 7(7), 614; https://doi.org/10.3390/math7070614 - 11 Jul 2019

Cited by 39 | Viewed by 3077

Abstract

Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS [...] Read more.

Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS has some limitations and problems, which are listed as follows. (1) It is based on modified TOPSIS, not the original TOPSIS. (2) It is inapplicable when using vector normalization. (3) The calculation formulas of the coordination degree are incorrect. (4) The coordination level of attributes is interrelated with the weights. In this paper, the problems of the existing coordinated TOPSIS are explained and revised, and a novel coordinated TOPSIS based on coefficient of variation is proposed to avoid the limitations. Comparisons of the existing, revised, and proposed coordinated TOPSIS are carried out based on two case studies. The comparison results validate the feasibility of the proposed coordinated TOPSIS. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

20 pages, 328 KiB

Open AccessArticle

Satisfying Bank Capital Requirements: A Robustness Approach in a Modified Roy Safety-First Framework

by Ebenezer Fiifi Emire Atta Mills, Bo Yu and Kailin Zeng

Mathematics 2019, 7(7), 593; https://doi.org/10.3390/math7070593 - 1 Jul 2019

Cited by 4 | Viewed by 3787

Abstract

This study considers an asset-liability optimization model based on constraint robustness with the chance constraint of capital to risk assets ratio in a safety-first framework under the condition that only moment information is known. This paper aims to extend the proposed single-objective capital [...] Read more.

This study considers an asset-liability optimization model based on constraint robustness with the chance constraint of capital to risk assets ratio in a safety-first framework under the condition that only moment information is known. This paper aims to extend the proposed single-objective capital to risk assets ratio chance constrained optimization model in the literature by considering the multi-objective constraint robustness approach in a modified safety-first framework. To solve the optimization model, we develop a deterministic convex counterpart of the capital to risk assets ratio robust probability constraint. In a consolidated risk measure of variance and safety-first framework, the proposed distributionally-robust capital to risk asset ratio chance-constrained optimization model guarantees banks will meet the capital requirements of Basel III with a likelihood of 95% irrespective of changes in the future market value of assets. Even under the worst-case scenario, i.e., when loans default, our proposed capital to risk asset ratio chance-constrained optimization model meets the minimum total requirements of Basel III. The practical implications of the findings of this study are that the model, when applied, will provide safety against extreme losses while maximizing returns and minimizing risk, which is prudent in this post-financial crisis regime. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

14 pages, 1093 KiB

Open AccessArticle

Intelligence in Tourism Management: A Hybrid FOA-BP Method on Daily Tourism Demand Forecasting with Web Search Data

by Keqing Li, Wenxing Lu, Changyong Liang and Binyou Wang

Mathematics 2019, 7(6), 531; https://doi.org/10.3390/math7060531 - 11 Jun 2019

Cited by 24 | Viewed by 4330

Abstract

The Chinese tourism industry has been developing rapidly for the past several years, and the number of people traveling has been increasing year by year. However, many problems still beset current tourism management. Lack of effective management has caused numerous problems, such as [...] Read more.

The Chinese tourism industry has been developing rapidly for the past several years, and the number of people traveling has been increasing year by year. However, many problems still beset current tourism management. Lack of effective management has caused numerous problems, such as tourists stranded during tourist season and the declining service quality of scenic spots, which have become the focus of tourists’ attention. Network search data can intuitively reflect the attention of most users through the combination of the network search index and the back propagation (BP) neural network model. This study predicts the daily tourism demand in the Huangshan scenic spot in China. The filtered keyword in the Baidu index is added to the hybrid neural network, and a BP neural network model optimized by a fruit fly optimization algorithm (FOA) based on the web search data is established in this study. Different forecasting methods are compared in this paper; the results prove that compared with other prediction models, higher accuracy can be obtained when it comes to the peak season using the FOA-BP method that includes web search data, which is a sustainable means of practically solving the tourism management problem by a more accurate prediction of tourism demand of scenic spots. Full article

(This article belongs to the Special Issue Applications of Operational Research and Mathematical Models in Management)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Applications of Operational Research and Mathematical Models in Management

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (10 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI