Developing a fuzzy inference system to devise proper business strategies: a study on carpet industry

Hemayatkar, Nasrin; Khalili‐Damghani, Kaveh; Didehkhani, Hosein; Samiee, Roohalla

doi:10.1007/s40092-018-0279-1

Cited by 5 publications

(2 citation statements)

References 26 publications

(23 reference statements)

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“…The dynamic strategic management is a process through which the members of a future organization are visualized and the process creates the procedures and actions required to achieve them (Hemayatkar et al 2018). The dynamic strategic management is a decision-making process which can relate the environment within the organization to the opportunities and threats coming from the outside of the organization in such a way that the value of each factor will be completely obvious (Cosenz and Noto 2017).…”

Section: Dynamic Strategic Managementmentioning

confidence: 99%

Evaluation of trade and production policy in Iranian SME (a system dynamics model)

2019

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It is undeniable that SMEs face many management-related problems. These problems are often deeply rooted in the strategic decision making by managers. One of these decisions is associated with the production section. Many of these companies provide production infrastructure at high costs; however, they are unsuccessful in acquiring their market share. In these circumstances, providing a solution to the decision-making problem of managers in these companies can prevent the loss of capital. In this research, the system dynamics approach is used to test the hypothesis of a company's participation in the production field after securing a success in business activities of the market. In the present study, the SME performance model, proposed by Schmid's, is considered as the base model. After analyzing its construction steps according to managers' viewpoints, the model has been developed based on the conditions in Iran. Then, the research scenario is presented as follows. If an entrepreneur, before entering the production sector, tries to establish a customer network by conducting business activities, the organization's chance for success will increase. By defining a variable called "production switch" and adding it as a function of a loyal customer network, the model has been tested. After simulating the model for a 5-year period, it is concluded that the rate of return on investment of an organization that has conducted the commercial activities at the outset of production is four times higher than that at the outset of production without the commercial activity.

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Section: Dynamic Strategic Managementmentioning

confidence: 99%

Evaluation of trade and production policy in Iranian SME (a system dynamics model)

2019

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“…Forecasting has the objective of estimating prospects for economic progress as well as business activities and the environmental impact on these prospects [4,5]. So that forecasting for every company or business organization enters the most important part in every management decision making and forecasting itself can be the basis for management to plan activities and decisions in the short, medium and long term [6,7]. In conducting the forecasting process, a method is needed in its application, namely the K-nearest neighbor method [8,9].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor

Al-Khowarizmi

Syah

Nasution

et al. 2021

IJECE

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Forecasting involves all areas in predicting future events. Many problems can be solved by using a forecasting approach to become a study in the field of data science. Forecasting that learns through data in the light age is able to solve problems with large-scale data or big data. With the big data, the performance of the k-Nearest Neighbor (k-NN) method can be tested with several accuracy measurements. Generally, accuracy measurement uses MAPE so it is necessary to conduct sensitivity on MAPE by combining it with the detection rate which is the difference technique. In addition, the k-NN process has been developed for the sake of running sensitivity by performing normalized distance using normalized Euclidean distance so that in this paper using the crude palm oil (CPO) price dataset, it is able to forecast and become a future model and apply it to Business Intelligence and analysis. In the final stage of this paper, the accuracy value in doing big data forecasting on CPO prices with MAPE is 0.013526% and MAPE sensitivity combined with a detection rate of 0.000361% so that future processes using different methods need to involve detection rates.

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An intelligent approach based on hybrid of principal component analysis-fuzzy inference system-adaptive neuro-fuzzy inference system for the simultaneous spectrophotometric determination of sofosbuvir and velpatasvir as antiviral drugs in pharmaceutical formulation and urine sample

Keyvan

Sohrabi

Motiee

2022

Chemometrics and Intelligent Laboratory Systems

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Developing a fuzzy inference system to devise proper business strategies: a study on carpet industry

Cited by 5 publications

References 26 publications

Evaluation of trade and production policy in Iranian SME (a system dynamics model)

Evaluation of trade and production policy in Iranian SME (a system dynamics model)

Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor

An intelligent approach based on hybrid of principal component analysis-fuzzy inference system-adaptive neuro-fuzzy inference system for the simultaneous spectrophotometric determination of sofosbuvir and velpatasvir as antiviral drugs in pharmaceutical formulation and urine sample

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