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Showing 2 results for Etebari
Etebari, Aaghaie, Khoshalhan,
Volume 3, Issue 1 (4-2012)
Abstract
In recent years, enriching traditional revenue management models by considering the customer choice behavior has been a main challenge for researchers. The terminology for the airline application is used as representative of the problem. A popular and an efficient model considering these behaviors is choice-based deterministic linear programming (CDLP). This model assumes that each customer belongs to a segment, which is characterized by a consideration set, which is a subset of the products provided by the firm that a customer views as options. Initial models consider a market segmentation, in which each customer belongs to one specific segment. In this case, the segments are defined by disjoint consideration sets of products. Recent models consider the extension of the CDLP to the general case of overlapping segments. The main difficulty, from a computational standpoint, in this approach is solving the CDLP efficiently by column generation. Indeed, it turns out that the column generation subproblem is difficult on its own. It has been shown that for the case of nonoverlapping segments, this can be done in polynomial time. For the more general case of overlapping segments, the column generation sub-problem is NP-hard for which greedy heuristics are proposed for computing approximate solutions. Here, we present a new approach to solve this problem by using a genetic algorithm and compare it with the column generation method. We comparatively investigate the effect of using the new approach for firm’s revenue
Dr Mahdi Bahrami , Dr Akbar Etebarian Khorasgani, Dr Reza Ebrahimzadeh Dastjerdi,
Volume 13, Issue 1 (6-2022)
Abstract
This research was carried out with the aim of providing a comprehensive model for redesigning the organizational structure that fulfills the requirements of activity in the era of the fourth industrial revolution with the approach of developing smart business. The research was of a sequential mixed type of quantitative and qualitative type. In the quantitative part, which was conducted using a descriptive survey method, in the first stage, organization pathology and organizational design models were examined and identified through a systematic review of the research literature, and Burton's multi-contingency model, which simultaneously includes pathology and organization design, was selected. In the second stage, the researcher developed a questionnaire based on different editions of Burton's multi-contingency model, and the validity and reliability of the questionnaire (content validity using the Laushe method, face validity and construct validity using the confirmatory factor analysis method with Smart PLS software and reliability It was evaluated by the methods of Cronbach's alpha, composite reliability and divergent and convergent reliability of Fornell and Lockerre), the results of which indicate the high internal validity of the research and the validity of the tool designed in the society. Finally, a 90-item questionnaire was developed to measure 14 dimensions and 28 components, which was arranged in the form of a Likert scale and distributed among 263 managers and experts of Esfahan Steel Company, who were selected by stratified random method. After data collection and analysis, it was found that the different dimensions of the organizational structure of Esfahan Steel Company based on Burton's multi-contingency model are not located in one area and are scattered in four different areas of the diagram, and the dimensions of the structure are not proportional and aligned. In the future, in order to redesign the appropriate structure, the research was continued using the qualitative method. In this section, with the purposeful sampling technique dependent on the criterion among 30 academic and steel industry experts related to the subject, the most important dimensions of the organizational structure (using the fuzzy Delphi method and in two rounds) and the components of business intelligence (using the fuzzy Delphi method) and during three rounds) were determined. Then, by using the fuzzy Delphi technique during four rounds, which stopped at the Schmidt agreement criterion, a comprehensive model of organizational structure redesign with the approach of developing smart business was obtained. The findings showed that the most effective components of business intelligence include commercial intelligence, artificial intelligence, strategic intelligence, and competitive intelligence, which can provide suitable platforms and facilitators to achieve a suitable and intelligent organizational structure. The results show that the use of business intelligence factors consisting of strategic, competitive, commercial and artificial intelligence models are effective platforms for making appropriate decisions in order to make changes and redesign the organizational structure (organization plan) and create appropriateness and alignment. It is between dimensions with the aim of developing smart business.
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