International Journal of Applied Operational Research

A bibliometric analysis by using VOSviewer for FinTech research

S.C. Chen

The field of Financial Technology, or "FinTech," emerged in 2008 and has since garnered notable attention from academics due to advancements in technology. This research analyzes 1,855 scholarly articles published between 2014 and 2023, with a focus on FinTech. We utilized the Scopus database to gather these articles and conducted a bibliometric analysis using VOSviewer software. Our analysis delves into publication patterns, global distribution, author affiliations, prolific authors, and keyword correlations within the research body. We identify significant interrelationships between FinTech and three prominent domains: Finance, Blockchain, and Artificial Intelligence. These fields have significantly influenced the development of FinTech discourse over the last decade. Our study presents significant findings on the current research status in FinTech, providing guidance and motivation for future research in this rapidly-evolving sector. Ultimately, our objective is to clarify the intricate relationship between FinTech and its related domains, offering insight for future research endeavors.

A multi-objective mathematical model for planning, scheduling and increasing projects productivity

M. A. Mousavi

We aimed to develop a mathematical method for planning, scheduling and increasing the productivity of projects with multiple goals, including reducing project time, resources, and negative cash flows, increasing floatiness of activities, and responding to the project's needs by considering various stakeholders and objectives. As such problems are NP-hard, particle swarm optimization was used to solve the multi-objective mathematical model. Then, the algorithm function was evaluated by changing the value of the parameters. We are looking for the use of multi-objective models for planning projects, which allow for planning each activity in different modes and functions using multiple objectives, enables project managers to implement their projects by considering various priorities. Based on previous studies on project schedules, it seems that most of them focus on reducing time and cost; nevertheless, this study intended to investigate issues like various operational modes of each activity, optimal and in-time allocation of resources, and to increase floatiness of activities.

A review of the methods of recognition multimodal emotions in sound, image and text

M. R. Yamaghani

The study of recognizing multifaceted emotions through auditory, visual, and textual cues is a rapidly growing interdisciplinary field, encompassing the domains of psychology, computer science, and artificial intelligence. This paper investigates the spectrum of methodologies utilized to isolate and identify complex emotional states across these modalities, with the objective of delineating advancements and identifying areas for future investigation. Within the realm of sound, we explore progress in signal processing and machine learning techniques that facilitate the extraction of nuanced emotional indicators from vocal inflections and musical arrangements. Visual emotion recognition is evaluated through the effectiveness of facial recognition algorithms, analysis of body language, and integration of contextual environmental information. Text-based emotion recognition is examined using natural language processing techniques to perceive sentiment and emotional connotations from written language. Moreover, the paper considers the amalgamation of these distinct sources of emotional data, contemplating the challenges in constructing coherent models capable of interpreting multimodal inputs. Our methodology encompasses a meta-analysis of recent studies, evaluating the effectiveness and precision of diverse approaches and identifying commonly employed metrics for their assessment. The results suggest a preference towards deep learning and hybrid models that harness the strengths of multiple analytical techniques to enhance recognition rates. However, challenges such as the subjective nature of emotion, cultural disparities in expression, and the necessity for extensive, annotated datasets persist as significant hurdles. In conclusion, this review advocates for more nuanced datasets, enhanced interdisciplinary cooperation, and an ethical framework to govern the implementation of emotion recognition technologies. The potential applications for these technologies are expansive, ranging from healthcare to entertainment, and necessitate a concerted endeavor to refine and ethically integrate emotion recognition into our digital interactions.

Sustainability evaluation of supply chain by inverse data envelopment analysis model: a case study of the power industry

M. Pouralizadeh

The Pollutant emissions control and management of greenhouse gas play a fundamental role in wasted energy mitigation in the energy and power plant sectors and transmission and distribution networks. The majority of the energy consumption mostly derived from Fossil fuels. This results in extensive pollution, which endangers human health and other organisms while also reduces the economic return on industrial activities. The purpose of this study is to evaluate the sustainability of the electricity supply chain by the inverse output-oriented data envelopment analysis (DEA) model. The inverse output-oriented (DEA) model provides optimal amount of economic return order to desirable products and undesirable outputs while other factors are kept unchanged. An empirical conclusion yielded on the model’s performance in the electrical supply chains and their divisions. According to the results of the inverse output-oriented DEA model, a supply chain’ first power plan and first transmission line require an influential investment in flare gas inhibition and economic return enhancement. Also, the distribution lines confront fluctuations of power loss hence; it is recommended that specialized workforce employed to avoid power loss.

Sensitivity Analysis of Costs in Grey Transportation Problems

F. Pourofoghi

The parameters of the transportation problem in the real world can be presented mostly as grey numbers. Therefore, after solving the grey transportation problem and reaching the optimal answer, sensitivity analysis of cost coefficients of a grey transportation problem is discussed. In this paper, using the definitions of center and width of interval grey numbers, a new method for the sensitivity analysis of cost coefficients of a grey transportation problem is presented. In this way, it can be determined the ranges of costs in the grey transportation problem such that its optimal basis is invariant. The proposed method is also explained with an example.

Providing a model for the impact of performance on the relationship between corporate governance mechanisms and the probability of firing the CEO

E. E. Gorjian Mehlabani

According to the agency theory and the separation of ownership from management, including the most important measures of a company is management changes. On the other hand, the cause of changing the executive’s managers because of their effectiveness should be a special place in accounting research. In that light, this study investigates the effect of performance on the relationship between corporate governance mechanisms and the probability of firing the CEO. In this research, the studied population included companies listed on the Tehran Stock Exchange from March 21^st, 2008 to March 21^st, 2017. The systematic elimination method was used to narrow down the sample down to 65 companies that were examined in a nine-year period. The Eviews package was used to investigate the validity of the hypotheses relying on the logistic regression method. The results of the hypothesis test showed that firm performance has a significant negative effect on the relationship of institutional ownership, independent directors, and entrenching with CEO replacement. And performance also has a significant positive impact on the relationship between major ownership and CEO change. In addition, the results show that performance has a significant negative impact on the relationship between ownership (private and public) with CEO change. The impact of private ownership is less severe than state ownership.