arXiv subjects

Hengameh Fakhravar

Publications and source records attributed to Hengameh Fakhravar.

5 recordsLinked to original sources

arXiv2022

International Co-Branding and Firms Finance Performance

Co-branding has become a widely used marketing strategy, yet little attention has been paid to its impact on a firm's stock value. Prior literature has shown that using a co-branding strategy properly helps firms leverage the brand value and equity. We discussed the theoretical foundations and main accomplishments of prior studies. We developed a conceptual framework and hypothesis to close the existing research gap in the topic of interest. We argued that co-branding event announcement generates positive abnormal returns in the stock market. Furthermore, we investigated the moderating impact of co-branding structure on the relation between co-branding event announcements and abnormal returns. We claimed that higher co-branding integration, greater co-branding exclusivity, and longer co-branding duration generate a greater positive abnormal return for the partnering firms.

q-fin.TR↗

arXiv2022

Combining heuristics and Exact Algorithms: A Review

Several different ways exist for approaching hard optimization problems. Mathematical programming techniques, including (integer) linear programming-based methods and metaheuristic approaches, are two highly successful streams for combinatorial problems. These two have been established by different communities more or less in isolation from each other. Only over several years ago, a larger number of researchers recognized the advantages and huge potentials of building hybrids of mathematical programming methods and metaheuristics.

math.OC↗

arXiv2021

Application of Failure Modes and Effects Analysis in the Engineering Design Process

Failure modes and effects analysis (FMEA) is one of the most practical design tools implemented in the product design to analyze the possible failures and to improve the design. The use of FMEA is diversified, and different approaches are proposed by various organizations and researchers from one application to another. The question is how to use the features of FMEA along with the design process. This research focuses on different types of FMEA in the design process, which is considered as the mapping between customer requirements, design components, and product functions. These three elements of design are the foundation of the integration model proposed in this research. The objective of this research is to understand an integrated approach of FMEA in the design process. Significantly, an integration framework is developed to integrate the design process and FMEA. Then, a step-by-step FMEA-facilitated design process is proposed to apply FMEA along with the design process.

cs.SE↗

arXiv2020

Quantifying Uncertainty in Risk Assessment using Fuzzy Theory

Risk specialists are trying to understand risk better and use complex models for risk assessment, while many risks are not yet well understood. The lack of empirical data and complex causal and outcome relationships make it difficult to estimate the degree to which certain risk types are exposed. Traditional risk models are based on classical set theory. In comparison, fuzzy logic models are built on fuzzy set theory and are useful for analyzing risks with insufficient knowledge or inaccurate data. Fuzzy logic systems help to make large-scale risk management frameworks more simple. For risks that do not have an appropriate probability model, a fuzzy logic system can help model the cause and effect relationships, assess the level of risk exposure, rank key risks in a consistent way, and consider available data and experts'opinions. Besides, in fuzzy logic systems, some rules explicitly explain the connection, dependence, and relationships between model factors. This can help identify risk mitigation solutions. Resources can be used to mitigate risks with very high levels of exposure and relatively low hedging costs. Fuzzy set and fuzzy logic models can be used with Bayesian and other types of method recognition and decision models, including artificial neural networks and decision tree models. These developed models have the potential to solve difficult risk assessment problems. This research paper explores areas in which fuzzy logic models can be used to improve risk assessment and risk decision making. We will discuss the methodology, framework, and process of using fuzzy logic systems in risk assessment.

cs.AI↗

arXiv2020

A fuzzy inventory model considering imperfect quality items with receiving reparative batch and order overlapping

This paper presents an inventory model for imperfect quality items with receiving a reparative batch and order overlapping in a fuzzy environment by employing triangular fuzzy numbers. It is assumed that the imperfect items identified by screening are divided into either scrap or reworkable items. The reworkable items are kept in store until the next items are received. Afterward, the items are returned to the supplier to be reworked. Also, a discount on the purchasing cost is employed as an offer of cooperation from a supplier to a buyer to compensate for all additional holding costs incurred to the buyer. The rework process is error-free. An order overlapping scheme is employed so that the vendor is allowed to use the previous shipment to meet the demand by the inspection period. In the fuzzy model, the graded mean integration method is taken to defuzzify the model and determine its approximation of a profit function and optimal policy. In doing so, numerical examples are rendered to represent the model behavior and, eventually, the sensitivity analysis is presented.

math.OC↗