Evaluation of Chinese Cloth Suppliers using Dynamic Grey Relational Analysis

Ouali, Mohamed

doi:10.52812/ijgs.62

Cited by 5 publications

(3 citation statements)

References 46 publications

(61 reference statements)

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“…In 2022, Javed et al (2022) overcame these shortcomings by proposing the Dynamic GRA model. Later, Ouali (2022) confirmed the model's validity while studying the supplier selection problem, whereas Mahmoudi and Javed (2023) used it to validate another MCDM model. The key components of the model are discussed below.…”

Section: Dynamic Grey Relational Analysismentioning

confidence: 94%

Evaluation of Barriers to E-commerce in Malawi using Grey Relational Analysis

Matambo

2023

IJGS

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E-commerce (electronic commerce) provides a convenient way of buying or selling products online and is a popular choice in certain segments of societies worldwide. The significance of e-commerce has been observed during the COVID-19 crisis, where customer preferences shifted from physical stores to online stores due to lockdowns and social distancing. E-commerce has been observed to be more effective in developed countries than in developing countries such as Malawi due to the difference in the resources required for the sustainability and growth of e-commerce. The current study evaluated the barriers to e-commerce in Malawi and ranked them using the Dynamic Grey Relational Analysis model. Using the primary data collected from the customers in Malawi, the study found that lack of trust in online systems and limited access to cell phones and computers and online payment methods are the most significant barriers. The study found that both human and technical (infrastructure) factors are hindering the growth of e-commerce in Malawi.

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Section: Dynamic Grey Relational Analysismentioning

confidence: 94%

Evaluation of Barriers to E-commerce in Malawi using Grey Relational Analysis

Matambo

2023

IJGS

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“…Today, it has seen widespread applications in various fields. Among its core parts include the theories of Grey Numbers (Shajedul, 2021; Candra, 2022), Grey Decision-Making (Javed et al ., 2022; Mahmoudi et al ., 2021), Grey Linear Programming (Mahmoudi et al ., 2018), Grey Relational Analysis (Oyedeji et al , 2022; Abifarin and Ofodu, 2022; Ouali, 2022) and Grey Forecasting (Wu et al ., 2022; Tian et al ., 2021). Grey forecasting models are data-driven intelligent time-series forecasting systems that can predict future patterns of a variable with minimal data (Javed and Cudjoe, 2022; Zineb et al ., 2022).…”

Section: Methodsmentioning

confidence: 99%

Grey forecast of electricity production from coal and renewable sources in the USA, Japan and China

Tulkinov

2023

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PurposeElectricity plays an essential role in nations' economic development. However, coal and renewables currently play an important part in electricity production in major world economies. The current study aims to forecast the electricity production from coal and renewables in the USA, China and Japan.Design/methodology/approachTwo intelligent grey forecasting models – optimized discrete grey forecasting model DGM (1,1,α), and optimized even grey forecasting model EGM (1,1,α,θ) – are used to forecast electricity production. Also, the accuracy of the forecasts is measured through the mean absolute percentage error (MAPE).FindingsCoal-powered electricity production is decreasing, while renewable energy production is increasing in the major economies (MEs). China's coal-fired electricity production continues to grow. The forecasts generated by the two grey models are more accurate than that by the classical models EGM (1,1) and DGM (1,1) and the exponential triple smoothing (ETS).Originality/valueThe study confirms the reliability and validity of grey forecasting models to predict electricity production in the MEs.

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“…In 2022, Javed et al (2022) proposed an improved version of Deng's GRA model called the DGRA that overwhelmed the issue in the original model. Later studies have confirmed the validity of the improved model (Ouali, 2022;Ervural, 2023;Matambo, 2023). The steps involved in the execution of the DGRA model are given below: STEP 1.…”

Section: Dynamic Grey Relational Analysis Modelmentioning

confidence: 99%

Investigating the Barriers to Electric Vehicle Adoption among Older Adults using Grey Relational Analysis: A Cross-country Survey

Darbinian,

Osibo,

Septime

et al. 2023

MSBD

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The adoption of electric vehicles (EVs) is a critical step towards the achievement of sustainable transportation, mitigated environmental challenges, and reduction in dependence on fossil fuels. In recent years, the popularity of EVs has grown, yet their adoption among seniors (older adults aged 50 and above) remains a challenge. This paper presents a comparative analysis of the barriers to EV adoption among seniors in two major economies, China and Russia. These two major economies have vast territories and significant transportation demands and as such they play crucial roles in the global shift towards EV adoption. We collected data from Russian and Chinese senior citizens using a comprehensive drafted questionnaire (252 respondents). Also, the Dynamic Grey Relational Analysis (DGRA) is used to analyze the quantitative data and rank the barriers to EV adoption. Our results suggest the inability of seniors to smartly locate available charging stations as the barrier to adopting EVs in China, while the lack of charging infrastructure at home is identified as the main barrier for seniors in Russia. Our findings provide valuable insights for manufacturers, technology firms, and policymakers, in the ongoing promotion of electric mobility.

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Evaluation of Chinese Cloth Suppliers using Dynamic Grey Relational Analysis

Cited by 5 publications

References 46 publications

Evaluation of Barriers to E-commerce in Malawi using Grey Relational Analysis

Evaluation of Barriers to E-commerce in Malawi using Grey Relational Analysis

Grey forecast of electricity production from coal and renewable sources in the USA, Japan and China

Investigating the Barriers to Electric Vehicle Adoption among Older Adults using Grey Relational Analysis: A Cross-country Survey

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