Armin Mahmoodi, Leila Hashemi, Amin Mahmoodi, Benyamin Mahmoodi and Milad Jasemi
The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese…
Abstract
Purpose
The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).
Design/methodology/approach
In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.
Findings
Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.
Research limitations/implications
In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.
Originality/value
In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.
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Armin Mahmoodi and Leila Hashemi
This paper presents a novel multi-objective optimization model aimed at enhancing the success rate of resource planning (RP) implementation. The model optimization is developed…
Abstract
Purpose
This paper presents a novel multi-objective optimization model aimed at enhancing the success rate of resource planning (RP) implementation. The model optimization is developed based on the organizational structure types, fit-gap contingency analysis reports, uncertainty optimization problems on implementation schedule time and relative time and budget constraints.
Design/methodology/approach
Two pivotal strategies are employed: RP tools redesign through customization and organizational redesign. The synergistic integration of these strategies is essential, recognizing that RP tools implementation success hinges not only on technical aspects but also on aligning the system with organizational structure, culture and practices. In the analysis phase, a committee of experts identifies the initial gaps, which are evaluated through three conflicting objective functions: cost, time and penalty and running by the e-constraint method. In case of uncertainty nature time of RP tools implementation, the Activity-on-Arrow (A-O-A) method has been utilized.
Findings
The e-constraint method is utilized to derive the Pareto-optimal front, representing solutions effectively addressing identified gaps. A compromised solution is then proposed using the LP-metric method to strike a balance between conflicting objectives, ultimately improving RP tool implementation by reducing misfits.
Originality/value
To demonstrate and validate the model, a controlled case study is initially presented, illustrating its effectiveness. Subsequently, a real industry case study is provided, further validating the model’s applicability and practical relevance. This comprehensive approach offers valuable insights to optimize RP tool implementation outcomes, a critical concern for organizations undergoing technological transitions.
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Amin Bahador and Mahnaz Mahmudi Zarandi
The emergence of Covid-19 and its epidemic features have affected many people around the world. Regardless of the physical and psychological problems caused by it, people must…
Abstract
Purpose
The emergence of Covid-19 and its epidemic features have affected many people around the world. Regardless of the physical and psychological problems caused by it, people must isolate themselves from their surroundings. This problem is more intense in urban areas where people live in crowded apartments and high-rise buildings. During the lockdown, residents of such buildings suffered from disconnection from nature, in addition to the lack of communication with others. As most multi-story apartments and residential complexes do not have separate green spaces and do not provide a safe connection to nature for occupants, it is very tough for the residents of these buildings to endure the disease, and occupants are more vulnerable to disease. Accordingly, this study proposes the biophilic design as an effective approach to provide a secure connection with nature in residential complexes and high-rise apartments.
Design/methodology/approach
The questionnaire method was used in this study to analyze the raised hypotheses. Two types of residential zones were selected for the survey and comparing the results. One is apartment units without dedicated green space, and the other is villa houses with private green space. Size of the sample population include 300 people (150 residents of an apartment block and 150 residents of villa homes).
Findings
Strict restrictions during the pandemic have prevented people from connecting with nature, especially in urban areas, owing to the lack of separated and dedicated green spaces, whereas connection with nature can be healing and lead to relieving anxiety and stress in this era based on the approved research. Accordingly, applying a biophilic approach to the design process would be helpful.
Research limitations/implications
The lack of a biophilic project to observe was one of the limitations of this study. Being an available biophilic project in the surroundings could be very helpful to observe and acquire comprehensive knowledge and experiences from the handlers and users of biophilic buildings.
Practical implications
This study can be beneficial for patients, individuals and occupants of apartments and residential complexes in urban areas who suffer from distance from nature and green spaces during the restrictions of pandemics such as Covid-19.
Originality/value
This study proposes the use of biophilic architecture in the design process of residential complexes and high-rise apartments to provide isolated and dedicated green spaces for occupants, especially during the lockdown when people have been deprived of parks and public green spaces.
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Wenjing Wang, Moting Wang and Yizhi Dong
The paper's purpose is to investigate the effects of digital finance on the risk of stock price crashes and the underlying transmission mechanisms, and to provide suggestions to…
Abstract
Purpose
The paper's purpose is to investigate the effects of digital finance on the risk of stock price crashes and the underlying transmission mechanisms, and to provide suggestions to inhibit the stock crash risk (CR).
Design/methodology/approach
This paper selects all companies that were listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2011 to 2020. It then uses the two-way fixed effect model and the intermediary effect model to verify such effects.
Findings
The overall outcomes demonstrate such a result that the CR of listed companies in China can be significantly reduced by the development of digital finance, and the overall transparency of business financial information and the equity pledge of controlling shareholders are the two underlying transmission mechanisms that digital finance can cause effects on the CR of stocks.
Research limitations/implications
The main limitations are that there may exist some problems in the method for evaluating the CR of stocks. And there may be a problem of endogeneity caused by the empirical model cannot control all correlation variables.
Practical implications
This paper would provide policy implications, for different roles, to inhibit the stock CR and to make the development of the economy more stabilize.
Social implications
Digital finance can promote economic development while restraining financial risks at the same time. Therefore, although this study is based on the relevant data from China, it can also provide a reference for other economies with different basic conditions from China, to promote the overall development of the world economy.
Originality/value
The current academic research on digital finance or stock price CR has been relatively sufficient, but there are few papers that combined both. By combining digital finance with stock CR, this paper researches the influence of digital finance on the CR of stocks through empirical analysis. So, this paper would provide new research ideas and evidence for potential influence factors of the CR of stocks, fill the gap in this research field and provide certain help for subsequent scholars to conduct relevant research.
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Rohit Sood, Ajay Sidana and Neeru Sidana
Introduction: The government has taken many initiatives for the overall growth of India after liberalisation and remarkably performed to make India an emerging economy. Due to…
Abstract
Introduction: The government has taken many initiatives for the overall growth of India after liberalisation and remarkably performed to make India an emerging economy. Due to changes in macroeconomic conditions, investment in companys’ shares includes the possibility of bearing high risk, which cannot be eliminated but, to some extent, minimised. The persistence of risks motivates investors to invest in different available options of investment. Gearing measures, a company’s financial leverage, represent the risk afforded within the company’s capital structure.
Purpose: The research aims to identify the risk-return analysis of financial geared stocks of Nifty 50 companies in India, which have debt equity ratios of more than 1.
Methodology: Convenience and cluster sampling techniques were used to identify companies with debt equity ratios of more than 1. The considered time period is 2010–2019.
Findings: This research found capital structure ratios, debt equity ratio, and total debt ratio. The total equity ratio does not have any visible effect on any of the dependent variables, i.e., Return on equity (ROE), Return on Assets (ROA), Earnings per share (EPS), Return on capital employed (ROCE). It explains the impact of high-levered firms’ performance on profitability and functioning. The study highlights that highly geared companies do not significantly impact the ROA, proving Modigliani and Miller’s (1958) irrelevant theory.
Ramesh Krishnan, Rohit G and P N Ram Kumar
Considering sustainability and resilience together is crucial in food supply chain (FSC) management, as it ensures a balanced approach that meets environmental, economic and…
Abstract
Considering sustainability and resilience together is crucial in food supply chain (FSC) management, as it ensures a balanced approach that meets environmental, economic and social needs while maintaining the system's capacity to withstand disruptions. Towards this, a multi-objective optimisation model is proposed in this study to create an integrated sustainable and resilient FSC. The proposed model employs four objective functions – each representing a dimension of sustainability and one for resilience and utilises an augmented ϵ-constraint method for solving. The findings highlight the interplay between sustainability aspects and resilience, illustrating that overemphasis on any single dimension can adversely affect others. Further, the proposed model is applied to the case of Indian mango pulp supply chain and several inferences are derived. The proposed model would assist decision-makers in making a well-balanced choice based on sustainability and resilience considerations.
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Leila Hashemi, Armin Mahmoodi, Milad Jasemi, Richard C. Millar and Jeremy Laliberté
This study aims to investigate a locating-routing-allocating problems and the supply chain, including factories distributor candidate locations and retailers. The purpose of this…
Abstract
Purpose
This study aims to investigate a locating-routing-allocating problems and the supply chain, including factories distributor candidate locations and retailers. The purpose of this paper is to minimize system costs and delivery time to retailers so that routing is done and the location of the distributors is located.
Design/methodology/approach
The problem gets closer to reality by adding some special conditions and constraints. Retail service start times have hard and soft time windows, and each customer has a demand for simultaneous delivery and pickups. System costs include the cost of transportation, non-compliance with the soft time window, construction of a distributor, purchase or rental of a vehicle and production costs. The conceptual model of the problem is first defined and modeled and then solved in small dimensions by general algebraic modeling system (GAMS) software and non-dominated sorting genetic algorithm II (NSGAII) and multiple objective particle swarm optimization (MOPSO) algorithms.
Findings
According to the solution of the mathematical model, the average error of the two proposed algorithms in comparison with the exact solution is less than 0.7%. Also, the algorithms’ performance in terms of deviation from the GAMS exact solution, is quite acceptable and for the largest problem (N = 100) is 0.4%. Accordingly, it is concluded that NSGAII is superior to MOSPSO.
Research limitations/implications
In this study, since the model is bi-objective, the priorities of decision makers in choosing the optimal solution have not been considered and each of the objective functions has been given equal importance according to the weighting methods. Also, the model has not been compared and analyzed in deterministic and robust modes. This is because all variables, except the one that represents the uncertainty of traffic modes, are deterministic and the random nature of the demand in each graph is not considered.
Practical implications
The results of the proposed model are valuable for any group of decision makers who care optimizing the production pattern at any level. The use of a heterogeneous fleet of delivery vehicles and application of stochastic optimization methods in defining the time windows, show how effective the distribution networks are in reducing operating costs.
Originality/value
This study fills the gaps in the relationship between location and routing decisions in a practical way, considering the real constraints of a distribution network, based on a multi-objective model in a three-echelon supply chain. The model is able to optimize the uncertainty in the performance of vehicles to select the refueling strategy or different traffic situations and bring it closer to the state of certainty. Moreover, two modified algorithms of NSGA-II and multiple objective particle swarm optimization (MOPSO) are provided to solve the model while the results are compared with the exact general algebraic modeling system (GAMS) method for the small- and medium-sized problems.
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Leila Hashemi, Armin Mahmoodi, Milad Jasemi, Richard C. Millar and Jeremy Laliberté
In the present research, location and routing problems, as well as the supply chain, which includes manufacturers, distributor candidate sites and retailers, are explored. The…
Abstract
Purpose
In the present research, location and routing problems, as well as the supply chain, which includes manufacturers, distributor candidate sites and retailers, are explored. The goal of addressing the issue is to reduce delivery times and system costs for retailers so that routing and distributor location may be determined.
Design/methodology/approach
By adding certain unique criteria and limits, the issue becomes more realistic. Customers expect simultaneous deliveries and pickups, and retail service start times have soft and hard time windows. Transportation expenses, noncompliance with the soft time window, distributor construction, vehicle purchase or leasing, and manufacturing costs are all part of the system costs. The problem's conceptual model is developed and modeled first, and then General Algebraic Modeling System software (GAMS) and Multiple Objective Particle Swarm Optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGAII) algorithms are used to solve it in small dimensions.
Findings
According to the mathematical model's solution, the average error of the two suggested methods, in contrast to the exact answer, is less than 0.7%. In addition, the performance of algorithms in terms of deviation from the GAMS exact solution is pretty satisfactory, with a divergence of 0.4% for the biggest problem (N = 100). As a result, NSGAII is shown to be superior to MOSPSO.
Research limitations/implications
Since this paper deals with two bi-objective models, the priorities of decision-makers in selecting the best solution were not taken into account, and each of the objective functions was given an equal weight based on the weighting procedures. The model has not been compared or studied in both robust and deterministic modes. This is because, with the exception of the variable that indicates traffic mode uncertainty, all variables are deterministic, and the uncertainty character of demand in each level of the supply chain is ignored.
Practical implications
The suggested model's conclusions are useful for any group of decision-makers concerned with optimizing production patterns at any level. The employment of a diverse fleet of delivery vehicles, as well as the use of stochastic optimization techniques to define the time windows, demonstrates how successful distribution networks are in lowering operational costs.
Originality/value
According to a multi-objective model in a three-echelon supply chain, this research fills in the gaps in the link between routing and location choices in a realistic manner, taking into account the actual restrictions of a distribution network. The model may reduce the uncertainty in vehicle performance while choosing a refueling strategy or dealing with diverse traffic scenarios, bringing it closer to certainty. In addition, two modified MOPSO and NSGA-II algorithms are presented for solving the model, with the results compared to the exact GAMS approach for medium- and small-sized problems.
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Ifeyinwa Juliet Orji and Sun Wei
Globally, supply chains compete in a complex and rapidly changing environment. Hence, sustainable supplier selection has become a decisive variable in the firm’s financial…
Abstract
Purpose
Globally, supply chains compete in a complex and rapidly changing environment. Hence, sustainable supplier selection has become a decisive variable in the firm’s financial success. This requires reliable tools and techniques to enhance understanding on how supplier behavior evolves with time and to select the best sustainable supplier. System dynamics (SD) is an approach to investigate the dynamic behavior in which the system alterations correspond to the system variable changes. Fuzzy logic usually solves the challenges of imprecise data and ambiguous human judgment. The paper aims to discuss these issues.
Design/methodology/approach
This work presents a novel modeling approach for integrating information on supplier behavior in fuzzy environment with SD simulation modeling technique. This results in a more reliable and responsible decision-support system. Supplier behavior with respect to relevant sustainability criteria were sourced through expert interviews and simulated in Vensim to select the best possible sustainable supplier. The simulation runs were carried out in four scenarios, namely, past, current, future and average time horizon for four different suppliers. A multi-criteria decision-making model was presented to compare results from the systems dynamics model.
Findings
An increase in the rate of investment in sustainability by the different suppliers causes an exponential increase in total sustainability performance of the suppliers. The growth rate of the total performance of suppliers outruns their rate of investment in sustainability after about 12 months.
Originality/value
While a significant work exists regarding supplier selection, little work has been found that investigates how to insure sustainable suppliers maintain their status for a long period of time.