تبیین کاهندگی اثر شلاقی زنجیره تأمین با استفاده از فناوری‌های نوین داده‌های کلان، هوش تجاری و نگاشت شناختی فازی

ABSTRACT

This study aimed to investigate the effective factors that reduce the supply chain bullwhip effect using of new technologies of big data and business intelligence and utilizing fuzzy cognitive mapping methodology. In this regard, based on the research literature, 11 effective variables were identified and a questionnaire was designed. The importance of each of these variables in explaining the role of new technologies of big data and business intelligence in reducing the bullwhip effect was asked to petrochemical industry experts in a survey conducted in the second half of 1403. The collected data were analyzed using the fuzzy cognitive mapping method and with the help of FCMapper software to examine the relationship between the factors. The results of the analysis showed that the main factors affecting the use of big data and business intelligence technologies to reduce the bullwhip effect in the supply chain are these eleven variables: Flexibility in the supply chain, Trust in the supply chain, Information quality in the supply chain, Agility capability of the supply chain, Customer relationship management, Lead time in the supply chain, Integration and transparency in the supply chain, Coordination and cooperation in the supply chain, Order volume in the supply chain, Information sharing capability, and visibility capability. Next, the relationship and mutual effects of these factors were mapped and explained using the fuzzy cognitive mapping methodology. The findings emphasize the importance of these key factors and the complex relationships between them as a basis for developing operational strategies to reduce the bullwhip effect in supply chains, using the analytical capabilities of modern technologies.

Introduction

A growing number of companies are relying on a variety of and ever-evolving methods to extract valuable information from big data and business intelligence to make better decisions. The terms “big data” and “business intelligence” refer to large volumes of information or data at a specific point in time and within a specific scope. However, these new technologies have a short life cycle and their effective value is rapidly decreasing.

But big data and business intelligence are actually more than what we have just read. Big data is not only about the vast amounts of data or how it is consumed, but also about the structure of this data with the aim of providing added value to the organization. And business intelligence is “a set of methods, processes, architectures, and technologies that transform raw data into meaningful and useful information to benefit from tactical and operational insights and more effective decision-making.”

However, the impact of big data and business intelligence in reducing the bullwhip effect has not yet been analyzed. Since there can be various reasons for the bullwhip effect, the first goal of this research is to understand what actually causes the bullwhip effect in the supply chain. After that, it is investigated how to precisely apply big data and business intelligence in the supply chain.

Methodology

The aim of this section is to identify the relationship between the factors affecting the development of new technologies of big data and business intelligence in reducing the bullwhip effect in the supply chain. In this regard, a questionnaire was designed in which the degree of importance of each of the 38 research variables (in the form of 11 main dimensions) obtained from the Fuzzy Delphi stage was asked from petrochemical industry experts in explaining the development of new technologies of big data and business intelligence in reducing the bullwhip effect in the supply chain. The results were analyzed using the fuzzy cognitive mapping methodology and Fc mapper software, and the relationship between the research factors was examined.

Discussion and Results

One of the most important and dynamic issues in the supply chain is a phenomenon known as the bullwhip effect. This means that small changes in product demand from consumers downstream in the supply chain translate into larger and larger fluctuations in demand upstream. In this study, first, through a comprehensive review of the literature on the subject, factors affecting the reduction of bullwhip effect in the supply chain have been identified. Then, by combining the categories available in the literature, a new classification for these factors has been proposed. In the remainder of this study, pilot products have been selected to study the bullwhip effect. By reviewing the literature on the subject, using the opinions of experts and specialists, and the results of statistical analysis, it was shown that the main factors affecting the reduction of the bullwhip effect include eleven variables as follows:

• Flexibility in the supply chain

• Trust in the supply chain

• Information quality in the supply chain

• Agility capability of the supply chain

• Customer relationship management

• Lead time in the supply chain

• Integration and transparency in the supply chain

• Coordination and cooperation in the supply chain

• Order volume in the supply chain

• Information sharing capability

• Visibility capability

Conclusion

Using the fuzzy cognitive mapping methodology, the relationship between these factors was explained in accordance with Figure 2. Based on the resulting model, a comprehensive understanding of how the variables interact to reduce the bullwhip effect can be found; in addition, the possibility of adopting and designing bullwhip effect reduction strategies in organizations based on the resulting model will be facilitated because organizational strategists have a complete picture of the impact and effects of bullwhip effect reduction factors in the petrochemical industry and can predict the impact of changing each of the aforementioned variables under a new strategy. However, the issue of the bullwhip effect in Iranian industry is one of the issues that requires more attention from researchers and managers, because, according to research, studying big data and business intelligence and the bullwhip effect of the supply chain is necessary, especially in developing countries, and existing research plays an important role in the supply chain, and these technologies and their application are one of the main competitive advantages of organizations.

Keywords: Bullwhip effect, Supply chain, Big data, Fuzzy cognitive mapping, Business intelligence.