Marketing strategies evaluation based on big data analysis: a CLUSTERING-MCDM approach

Mahdiraji, Hannan Amoozad; Zavadskas, Edmundas Kazimieras; Kazeminia, Aliakbar; Kamardi, Ali Asghar Abbasi

doi:10.1080/1331677x.2019.1658534

Cited by 58 publications

(40 citation statements)

References 35 publications

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“…, y is a class label, and x is a vector with n attributes [15]. ere is a general form of linear discriminant function in two-dimensional linear space:…”

Section: Hdfs Reads Filesmentioning

confidence: 99%

Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

Cheng

Song

2021

Mathematical Problems in Engineering

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The service information system is constantly transforming to a networked information model, and domestic hardware equipment is constantly updated. Independent controllability has also become the basic requirement of the new information age. With the development of the information age and the new era of independent control, more and more services and applications will also be deployed on autonomous and controllable cloud platforms. With the rapid development of Internet technology in the information age and the resulting changes in productivity, people can record, store, and transmit more and more information. When information becomes recordable, storage, and easy to transmit, information becomes modern meaning nowadays, an era of information explosion characterized by massive, volatile, timely transmission, and diverse forms has truly come, forming what is now called the “big data era”. This article mainly introduces the analysis of sports big data based on the cloud platform and the research on the impact on the sports economy and intends to provide ideas and directions for the analysis of sports big data and the research on the impact on the sports economy. This paper proposes a cloud platform-based sports big data analysis and research methods for its impact on the sports economy, including the use of Hadoop cloud platform big data processing systems and support vector regression algorithms for cloud platform-based sports big data analysis and sports economy. The experimental results of this paper show that the average correlation between sports big data analysis and sports economic development is 0.5155, and appropriate cloud platform-based sports big data analysis plays a positive role in promoting sports economic development.

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“…, y is a class label, and x is a vector with n attributes [15]. ere is a general form of linear discriminant function in two-dimensional linear space:…”

Section: Hdfs Reads Filesmentioning

confidence: 99%

Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

Cheng

Song

2021

Mathematical Problems in Engineering

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“…Among all possible criteria evaluation methods (e.g. 'Shannon's entropy, Best Worst Method (BWM), Factor relationship evaluation (FARE)), SWARA is one of the most popular methods that have been used for many assessment problems (Beheshti et al, 2016;Mahdiraji et al, 2019). This method is different from other similar methods and makes the decision-maker capable to select their priority based on the current situation of the environment and economy.…”

Section: Methodsmentioning

confidence: 99%

Classification of inter-organizational knowledge mechanisms and their effects on networking capability: a multi-layer decision making approach

Mokhtarzadeh

Mahdiraji

Jafarpanah

et al. 2021

JKM

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Purpose The role of inter-organizational knowledge mechanisms (IOKMs) in learning networks is increasing so that the competition of business networks in providing innovations is highly dependent on the effective selection and application of these mechanisms. This study aims to argue that recognizing the classification of IOKMs and understanding their impact on networking capability (NC) makes the selection of mechanisms more effective. Design/methodology/approach With a systematic review of literature, a comprehensive list of IOKMs, their main characteristics and NCs have been extracted. The authors have used a focus group for data gathering and a hybrid multi-layer decision-making approach for data analysis. Finally, the impact of IOKMs on NC was determined. Findings By implementing a multi-layer decision-making approach, four categories of IOKMs including person-to-person, co-creation, team-oriented and informational are illustrated and their effects of NC are determined. Therefore, the findings of this research provide latecomer firms (LCFs) managers with a clear framework for selecting IOKMs. Originality/value The literature review shows that the number of knowledge mechanisms, especially their inter-organizational types, is increasing. It has made it difficult for LCFs managers to select effective and efficient mechanisms. Most of these mechanisms are listed, and few studies have classified them. Besides, research shows that fewer studies have investigated how IOKMs relate to NC. Furthermore, most studies on IOKMs have been conducted in the context of leading firms and LCFs have been neglected.

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“…By employing a linear and non-linear mathematical model, the optimal values of each criterion are calculated (Rezaei, 2015). This method is used in a variety of contexts such as humanitarian supply chain (Sahebi et al, 2017), medical tourism management (Abadi et al, 2018), education management (Nafari et al, 2017), technology selection (Mokhtarzadeh et al, 2018), marketing (Mahdiraji et al, 2019) and facility location (Kheybari et al, 2019). The well-known non-linear version of this model is described as follows (Rezaei, 2015):…”

Section: The Best-worst Methodsmentioning

confidence: 99%

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of BWM and interval valued intuitionistic fuzzy TODIM

Mahdiraji

Zavadskas

Škare

et al. 2020

Economic Research-Ekonomska Istraživanja

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Developing and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts' opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of 'Technology', 'Quality', and 'Operation' have respectively the highest importance. Furthermore, the strategies for "new business models development', 'Improving information systems' and 'Human resource management' received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information.

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Marketing strategies evaluation based on big data analysis: a CLUSTERING-MCDM approach

Cited by 58 publications

References 35 publications

Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

Classification of inter-organizational knowledge mechanisms and their effects on networking capability: a multi-layer decision making approach

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of BWM and interval valued intuitionistic fuzzy TODIM

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