Journal of Modelling in Management

Zakaria, Firano; Salawa, Doughmi

2023 Journal of Modelling in Management

doi: 10.1108/jm2-12-2019-0287

There is a wealth of literature on the financing structure of a company. For this reason, the authors considered it useful to present a theoretical and empirical literature review of classical and new theories of the financial structure. The purpose of this study is to realize on a panel of 15 nonfinancial Moroccan companies listed on the Casablanca Stock Exchange, over a period of 11 years.Design/methodology/approachThe results obtained indicate that only a few variables from financial theory have an important role in the financing policy of Moroccan companies. The authors have presented the positive role of size and self-financing on the debt ratio. The analysis of the effects of profitability shows in this study that it is negative related on the debt ratio which asserts the predictions of the pecking order theory. Also, the age of the company and the growth opportunities explain the level of indebtedness.FindingsEconometric analysis is used to ascertain the nature of the financial structure of listed companies. For this purpose, a large number of companies listed on the Casablanca stock exchange were used.Originality/valueThe authors have presented the positive role of size and self-financing on the debt ratio. Regarding the influence of profitability, this analysis shows that it is negative related on the debt ratio which asserts the predictions of the pecking order theory. Also, the age of the company and the growth opportunities explain the level of indebtedness.

Khan, Aima; Qureshi, Muhammad Azeem

2023 Journal of Modelling in Management

doi: 10.1108/jm2-10-2020-0272

The purpose of this study is firm value management through corporate finance policy design and scenario analysis to maximize the firm value.Design/methodology/approachThe study develops a system dynamics model for an oil firm and incorporates the financial and physical processes to perform the firm valuation. The model is simulated under the current and alternative investment, capital structure and dividend policies of the case firm, assuming different oil and gas price and tax rate scenarios to identify which combination of policies maximizes the firm value.FindingsThe simulation results suggest that lowering the volume of investments, increasing the debt ratio and reducing the dividend payments from the current level increases the share price, given increased oil and gas price expectations and lower tax rates. However, the total firm value outperforms with increased investments toward the end of the simulation period. In case of decreased oil and gas price expectations, lower volume of investments, lower debt ratio and lower dividend payments increase the share prices, given lower taxes.Originality/valueThis study entails significance as it provides a comprehensive financial planning model for an oil firm, which incorporates the complex interactions of key financial and physical processes of the firm. The study contributes to debates on corporate finance policies by integrating multiple theories, accounting for accumulation processes and feedback loops and their non-linear interactions. The study proposes the consideration of combined impact of policies for firm value management.

Yazdani, Fatemeh; Khashei, Mehdi; Hejazi, Seyed Reza

2023 Journal of Modelling in Management

doi: 10.1108/jm2-08-2021-0182

This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs.Design/methodology/approachThe objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible.FindingsEmpirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs.Originality/valueThe proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.

Asgari Sooran, Mahnaz; Tayebi, Hamed; Ebrahimnejad, Sadoullah

2023 Journal of Modelling in Management

doi: 10.1108/jm2-08-2021-0184

The purpose of this study is to investigate a joint economic lot-size model with the possibility of cofinancing between members of a three-echelon supply chain (SC) including one supplier, one manufacture and one retailer. Given the differences in credit as well as differences in access to capital markets, SC members will be able to create a financial alliance to maximize the profits of each member. This study proposed a model to maximize the annuity stream of the SC by considering the financial interaction between SC members.Design/methodology/approachThis joint economic lot-sizing problem was described and modeled mathematically. To evaluate the mathematical model, different scenarios were considered with (and without) the possibility of financial interaction.FindingsIt is suggested that, in addition to the goods and information flow among SC members, proper financial flow can also have an impact on the improvement of SC performance.Originality/valueWhile previous studies consider cofinancing between members of a two-echelon SC, this paper considers a three-echelon SC including one supplier, one manufacturer and one retailer where financial cooperation between different levels of the SC in both upstream and reverse directions will be possible.

Khajeh, Fatemeh; Shahbandarzadeh, Hamid

2023 Journal of Modelling in Management

doi: 10.1108/jm2-10-2021-0242

Because container terminals (CTs) are broker organizations, their interest has complex, various internal and external factors, the purpose of this study is to scrutiny and structure the factors affecting the interests of the CT.Design/methodology/approachIn terms of purpose, this study is a developmental study that, are identified the factors related to the interests of the CT through studying the library and interviewing experts and then the degree of influence of each factor on each other by using the interview with experts of CT in Bushehr province are determined. Then, the fuzzy DEMATEL method is used to calculate the feedback loop of the indicators, and then the matrix obtained Fcmapper software and the fuzzy cognitive map (FCM) is drawn.FindingsAccording to the FCM analysis, three important factors are centrality identified in terms of attracting capital, quality of service and efficiency. In addition, there are three factors, attracting capital, operator performance and law have high outdegree.Originality/valueThis research has identified 34 effective indicators of CT interests and evaluated their relationship with FCM. In the available researches, all these indicators measurement has not been evaluated together. Furthermore, fuzzy DEMATEL has been used to evaluate self-loops. Another contribution of this research is the introduction of a strategic route as a roadmap for CT managers in Bushehr province to decide on the interests of a CT.

Lu, Qingqing; Yang, Weizhe; Zhou, Chuiri; Wang, Ningning

2023 Journal of Modelling in Management

doi: 10.1108/jm2-11-2021-0266

This study aims to investigate whether the contract manufacturer (CM) should take the first-mover advantage in the end-product without supplying core components to the original equipment manufacturer (OEM) immediately, or should fully squeeze the benefit of the learning effect through an amplified production quantity by letting the OEM enter the end-product market early.Design/methodology/approachThe authors propose a two-period model for a supply chain consisting of a CM and an OEM where the CM has four alternative entry strategies concerning it competition to the OEM in the end-product market. For each strategy, the authors derive the equilibrium solutions of the two firms using a backward approach. Comparison leads to the CM’s final choices among the four strategies.FindingsFor both CM and OEM, the monopoly and the first-entry strategies will be dominated by either the post-entry or the simultaneous-entry strategy, and thus, their preferred strategy is chosen from the latter two. Regarding the two firms choices between the post- and simultaneous-entry strategy, the CM prefers the post-entry strategy when the OEMs brand premium is at a moderate level, whereas the OEM prefers the post-entry strategy when its brand premium is low, and the learning effect can amplify the interval for the CMs adopting the post-entry strategy as well as changes the interval for the OEMs preference related to the two strategies.Originality/valueThis paper is the first one to explore the optimal strategy for a CM to maximize its profit in a co-opetitive supply chain situation with a CM and an OEM. The authors believe that our paper contributes to both literature and the market.

Yang, Feng; Wu, Xiang; Shan, Feifei

2023 Journal of Modelling in Management

doi: 10.1108/jm2-01-2022-0003

This paper aims to study the impact of manufacturer’s upgrading strategy of durable products on the retailer’s decision on trade-in program and her decision on the secondary market.Design/methodology/approachThis paper develops a channel that consists of a manufacturer and a retailer, where the manufacturer releases an upgraded product, and the retailer introduces a trade-in program for consumers, simultaneously, decides whether to enter the secondary market. These approaches are modeled through Stackelberg game.FindingsThis paper reveals that the optimal conditions for manufacturer to release upgraded products and retailer to resell used products in the secondary market, and it reveals that under what conditions it is profitable for retailer to enter the secondary market under product upgrade levels.Practical implicationsIf the manufacturer’s upgrade level is low, it is profitable for the retailer to enter the secondary market. However, if the manufacturer’s upgrade level is high, it is unprofitable for the retailer to enter the secondary market.Originality/valueIn this paper, the active secondary market, upgrading of new products, consumer market segmentation and especially, the upgrade degree of new products as a function of consumer demand are considered simultaneously.

Mahmoodi, Armin; Hashemi, Leila; Tahan, Mohammad Mehdi; Jasemi, Milad; Millar, Richard C.

2023 Journal of Modelling in Management

doi: 10.1108/jm2-12-2021-0306

This study aims to investigate the impact of new technologies on parameters of organizational behavior and evaluate their determining role of technology maturity and readiness of staff in the digital readiness.Design/methodology/approachThis study has obtained an integrated model of technology’s effect on staff’s organizational behavior considering digital readiness level by using system dynamics is developed. In this model, the effects of new technologies entry on organizational behavior variables are analyzed in different layers, and the result of this impact on the consequent of a bank organizational behavior and each indicator is examined separately in different scenarios. In determining the indicators and their significant coefficients, the viewpoints of banking experts and professionals in organizational behavior have been considered.FindingsAs a result of our surveys, five technology effects, without intermediaries, were obtained, which are automation, learning, streamlining repetitive jobs, addiction to technology and reducing face-to-face contact. Each of these factors would make a chain of side effects. In a way that, ultimately, their positive or negative effects on productivity and consequently on organization profits appear. The result indicates technology has effects on important behavioral factors such as stress, motivation, organization values and personal satisfaction. Indicators, which are formed by positive or negative factors, are being upgraded or downgraded. Therefore, managing negative cycles and developing positive cycles can be considered as one of the major banking concerns for controlling IT effects on its organizational behavior of human resources.Originality/valueThere is little academic remarkable literature on clarifying the effects of digitalization on employee's behavior in an organization, this research offers managers and organizations a model of influential factors that need to be taken into account by managers when they encounter new technologies. This study’s proposed analysis is useful to improve the efficiency and productivity of the organization, and alongside this, it is effective for the digital transformation process. This study fills previous research gaps in the academic context related to the practical studies that relied on digital maturity.

Singh, Rubee; Khan, Shahbaz; Dsilva, Jacinta

2023 Journal of Modelling in Management

doi: 10.1108/jm2-06-2021-0145

Consumers, governments and regulatory agencies are concerned about the social and environmental aspect that pushes firms to move towards the circular economy. The transformation of the existing linear model into a circular model depends on several circular economy practices. Therefore, the purpose of this study is to identify and analyse the critical factors that are responsible for the adoption of circular practices.Design/methodology/approachIn total, 15 critical factors are identified through the literature review and 12 are finalised with the grey Delphi method. Further, these critical factors are prioritised using the weighted aggregated sum/product assessment (WASPAS) method. A sensitivity analysis is also conducted to test the robustness of the ranking of critical factors obtained from WASPAS.FindingsThe finding of this study show that “top management participation,” “market for recovered products” and “circular economy oriented R&D activities promotion” are the most significant factors for circular practice adoption. These factors need to address on the highest priority by the stakeholders.Research limitations/implicationsThis study is beneficial for the managers to formulate their strategies for the adoption of circular practices. The prioritisation of critical factors supports the managers and professionals to optimise their effort and resources to adopt the circular practice.Originality/valueThis study explores and analyses the critical factor for circular economy practice adoption in the supply chain in the context of emerging economies.

Zakaria, Firano; Benbachir, Anass

2023 Journal of Modelling in Management

doi: 10.1108/jm2-04-2021-0099

One of the crucial issues in the contemporary finance is the prediction of the volatility of financial assets. In this paper, the authors are interested in modelling the stochastic volatility of the MAD/EURO and MAD/USD exchange rates.Design/methodology/approachFor this purpose, the authors have adopted Bayesian approach based on the MCMC (Monte Carlo Markov Chain) algorithm which permits to reproduce the main stylized empirical facts of the assets studied. The data used in this study are the daily historical series of MAD/EURO and MAD/USD exchange rates covering the period from February 2, 2000, to March 3, 2017, which represent 4,456 observations.FindingsBy the aid of this approach, the authors were able to estimate all the random parameters of the stochastic volatility model which permit the prediction of the future exchange rates. The authors also have simulated the histograms, the posterior densities as well as the cumulative averages of the model parameters. The predictive efficiency of the stochastic volatility model for Morocco is capable to facilitate the management of the exchange rate in more flexible exchange regime to ensure better targeting of monetary and exchange policies.Originality/valueTo the best of the authors’ knowledge, the novelty of the paper lies in the production of a tool for predicting the evolution of the Moroccan exchange rate and also the design of a tool for the monetary authorities who are today in a proactive conception of management of the rate of exchange. Cyclical policies such as monetary policy and exchange rate policy will introduce this type of modelling into the decision-making process to achieve a better stabilization of the macroeconomic and financial framework.

Liu, Zhiyuan; Chen, Yuwen; Qin, Jin

2023 Journal of Modelling in Management

doi: 10.1108/jm2-12-2021-0290

This paper aims to address a pollution-routing problem with one general period of congestion (PRP-1GPC), where the start and finish times of this period can be set freely.Design/methodology/approachIn this paper, three sets of decision variables are optimized, namely, travel speeds before and after congestion and departure times on given routes, aiming to minimize total cost including green-house gas emissions, fuel consumption and driver wages. A two-phase algorithm is introduced to solve this problem. First, an adaptive large neighborhood search heuristic is used where new removal and insertion operators are developed. Second, an analysis of optimal speed before congestion is presented, and a tailored speed-and-departure-time optimization algorithm considering congestion is proposed by obtaining the best node to be served first over the congested period.FindingsThe results show that the newly developed operator of congested service-time insertion with noise is generally used more than other insertion operators. Besides, compared to the baseline methods, the proposed algorithm equipped with the new operators provides better solutions in a short time both in PRP-1GPC instances and time-dependent pollution-routing problem instances.Originality/valueThis paper considers a more general situation of the pollution-routing problem that allows drivers to depart before the congestion. The PRP-1GPC is better solved by the proposed algorithm, which adds operators specifically designed from the new perspective of the traveling distance, traveling time and service time during the congestion period.

Mousa, Mohamed El-Sayed; Kamel, Mahmoud Abdelrahman

2023 Journal of Modelling in Management

doi: 10.1108/jm2-11-2021-0272

This study aims to examine performance assessment of organizational units through psychological empowerment (PE) and employee engagement (EE) approach and whether this relationship differs among efficient and inefficient organization units.Design/methodology/approachThis study drew on merging the principal component analysis (PCA), data envelopment analysis (DEA) and partial least square-multigroup analysis (PLS-MGA) to benchmark the performance of organizational units affiliated with Zagazig University in Egypt using PE dimensions as inputs and EE as output. Besides investigating whether PE inputs have the same effect among efficient and inefficient units.FindingsPerformance assessment based on independent data showed that all the investigated organizational units are not at the same efficiency level. The results revealed that there are eight efficient units versus seven inefficient ones. Moreover, PLS-MGA results demonstrated that no significant differences concerning the impact of PE inputs on EE between efficient and inefficient units groups. Nevertheless, the effect of these inputs was slightly higher in the former.Originality/valueStudies on EE performance in the service sector are scarce in the literature, this study is a novel contribution of exploring EE efficiency in Egypt as a developing economy. Specifically, using the PCA-DEA-structural equation modeling approach.

Arık, Oğuzhan Ahmet

2023 Journal of Modelling in Management

doi: 10.1108/jm2-01-2022-0014

This paper aims to provide a promising memetic algorithm (MA) for an unrelated parallel machine scheduling problem with grey processing times by using a simple dispatching rule in the local search phase of the proposed MA.Design/methodology/approachThis paper proposes a MA for an unrelated parallel machine scheduling problem where the objective is to minimize the sum of weighted completion times of jobs with uncertain processing times. In the optimal schedule of the problem’s single machine version with deterministic processing time, the machine has a sequence where jobs are ordered in their increasing order of weighted processing times. The author adapts this property to some of their local search mechanisms that are required to assure the local optimality of the solution generated by the proposed MA. To show the efficiency of the proposed algorithm, this study uses other local search methods in the MA within this experiment. The uncertainty of processing times is expressed with grey numbers.FindingsExperimental study shows that the MA with the swap-based local search and the weighted shortest processing time (WSPT) dispatching rule outperforms other MA alternatives with swap-based and insertion-based local searches without that dispatching rule.Originality/valueA promising and effective MA with the WSPT dispatching rule is designed and applied to unrelated parallel machine scheduling problems where the objective is to minimize the sum of the weighted completion times of jobs with grey processing time.

Jaramillo, Juan R.

2023 Journal of Modelling in Management

doi: 10.1108/jm2-02-2022-0034

This paper aims to present two different methods to speed up a test used in the sanitary ware industry that requires to count the number of granules that remains in the commodity after flushing. The test requires that 2,500 granules are added to the lavatory and less than 125 remain.Design/methodology/approachThe problem is approached using two deep learning computer vision (CV) models. The first model is a Vision Transformers (ViT) classification approach and the second one is a U-Net paired with a connected components algorithm. Both models are trained and evaluated using a proprietary data set of 3,518 labeled images, and performance is compared.FindingsIt was found that both algorithms are able to produce competitive solutions. The U-Net algorithm achieves accuracy levels above 94% and the ViT model reach accuracy levels above 97%. At this time, the U-Net algorithm is being piloted and the ViT pilot is at the planning stage.Originality/valueTo the best of the authors’ knowledge, this is the first approach using CV to solve the granules problem applying ViT. In addition, this work updates the U-Net-Connected components algorithm and compares the results of both algorithms.

Ahmadi, Mehrnaz; Khashei, Mehdi

2023 Journal of Modelling in Management

doi: 10.1108/jm2-04-2021-0092

The purpose of this paper is to propose a new linear-nonlinear data preprocessing-based hybrid model to achieve a more accurate result at a lower cost for wind power forecasting. For this purpose, a decomposed based series-parallel hybrid model (PKF-ARIMA-FMLP) is proposed which can model linear/nonlinear and certain/uncertain patterns in underlying data simultaneously.Design/methodology/approachTo design the proposed model at first, underlying data are divided into two categories of linear and nonlinear patterns by the proposed Kalman filter (PKF) technique. Then, the linear patterns are modeled by the linear-fuzzy nonlinear series (LLFN) hybrid models to detect linearity/nonlinearity and certainty/uncertainty in underlying data simultaneously. This step is also repeated for nonlinear decomposed patterns. Therefore, the nonlinear patterns are modeled by the linear-fuzzy nonlinear series (NLFN) hybrid models. Finally, the weight of each component (e.g. KF, LLFN and NLFN) is calculated by the least square algorithm, and then the results are combined in a parallel structure. Then the linear and nonlinear patterns are modeled with the lowest cost and the highest accuracy.FindingsThe effectiveness and predictive capability of the proposed model are examined and compared with its components, based models, single models, series component combination based hybrid models, parallel component combination based hybrid models and decomposed-based single model. Numerical results show that the proposed linear-nonlinear data preprocessing-based hybrid models have been able to improve the performance of single, hybrid and single decomposed based prediction methods by approximately 66.29%, 52.10% and 38.13% for predicting wind power time series in the test data, respectively.Originality/valueThe combination of single linear and nonlinear models has expanded due to the theory of the existence of linear and nonlinear patterns simultaneously in real-world data. The main idea of the linear and nonlinear hybridization method is to combine the benefits of these models to identify the linear and nonlinear patterns in the data in series, parallel or series-parallel based models by reducing the limitations of the single model that leads to higher accuracy, more comprehensiveness and less risky predictions. Although the literature shows that the combination of linear and nonlinear models can improve the prediction results by detecting most of the linear and nonlinear patterns in underlying data, the investigation of linear and nonlinear patterns before entering linear and nonlinear models can improve the performance, which in no paper this separation of patterns into two classes of linear and nonlinear is considered. So by this new data preprocessing based method, the modeling error can be reduced and higher accuracy can be achieved at a lower cost.

Richard, Abigail; Ahrens, Fred; George, Benjamin

2023 Journal of Modelling in Management

doi: 10.1108/jm2-01-2022-0007

This study aims to introduce a new prescriptive model to aid both managers and researchers in partner selection for innovation-orientated collaboration. This framework demonstrates how prospective partner firms’ complementing bodies of knowledge and goal alignment interact to affect the success of a collaboration.Design/methodology/approachThe authors use geometric modeling to represent the interrelationships among knowledge similarity/dissimilarity, goal congruence, knowledge complementarity (KC) and innovation in alliance formation. Using this model as a framework, the authors derive relationships among predictors of innovation success and determine how they affect the nature of partnerships under varying conditions of KC.FindingsThis research shows how innovation success is strongly determined by partner selection. Specifically, the authors examine the influence of KC and partner goals on three aspects of a potential research and development (R&D) alliance – the potential level of innovation outcome for the alliance, the boundaries of knowledge sharing and limitations arising from knowledge and goal incongruence and the nature of cooperation.Originality/valueAlthough there is broad empirical support that innovation success is influenced by the similarity of R&D partners’ knowledge, further research is still needed to model the relationship more precisely between partner KC and goal alignment. The authors address this gap by developing a model that is both prescriptive and predictive of how innovation success can be achieved in the context of disparate but complementing knowledge and goal sets. The authors conclude with practical implications for practice and future research directions.

Ozkan-Canbolat, Ela; Ozkan, Gulberk; Beraha, Aydin

2023 Journal of Modelling in Management

doi: 10.1108/jm2-02-2022-0039

This paper aims to show that evolutionary game theory not only provides a general and unified theory of political philosophy and strategic management theories but also a positive theory of interactive behavior.Design/methodology/approachThis study suggests a way of the evolutionary game-theoretical model.FindingsThe model presented in this paper demonstrates coopetition is derived from balance points in multi-actor games. As the political–philosophical address of those strategic games will of all becomes convention in this balance point at which common knowledge occurs global optimum.Research limitations/implicationsThis study explores the connections between several streams in philosophy and strategic management. What does a particular philosophy contribute to strategic management with respect to game theory? When addressing this question in historical or exploratory terms, or in a combination of both, the end result is similar: particular philosophical issues, properly explained, are discussed in relation to important questions in strategic management.Practical implicationsWhat are the psychological and behavioral underpinnings of strategic decisions of this kind? What type of cognitive frames and managerial mental models, such as the game-theoretical model, might enable or hinder the integration of real-world problems in strategic decision-making?Social implicationsWhat explains the evolution of such mental models, as well as the development of philosophical ideas, in informing the origins? How does the evolution of social and political contexts influence change in the cognitive and behavioral underpinnings of strategic decision-making?Originality/valueThis study highlights the overt power of strategic management ideas – competition, cooperation and coopetition – which have historically been built on the foundations of organizational theory, while also underlying the potential of philosophies, collective wisdom and Condorcet’s jury theorem and Rousseau’s (1998) correctness theory in games of evaluation. This study investigates whether the many produce better decisions than the wise few.