Evaluation of E-commerce Performance in SMEs based on Vector Auto Regression Model

Zhou, Li; Chen, Qing-yi

doi:10.14257/ijunesst.2014.7.5.14

Cited by 9 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some of the widely used methodologies to assess e-businesses' performance or related firms are summarized in Table 1. Typical key system measurements that are ranked or evaluated are financial performance [38], supply chain integration [39], website performance [40][41][42][43], cost efficiency [44,45], productivity effects [46][47][48], technical and technological efficiency [49][50][51][52][53][54][55], security [56], and success factors [57], to name just a few. In terms of methodologies, the potential and strengths of DEA in e-commerce performance evaluation are highlighted in many studies.…”

Section: Methodology Motivationmentioning

confidence: 99%

“…The DEA Malmquist model is an extension of the original DEA model that divides total productivity change into technical efficiency change and technological efficiency change, as proposed in [46,50,53]. Some other methodologies that are widely used for the evaluation of e-commerce impact on business efficiency include the model of cost efficiency [45,47,62,63], the regression model [39,44,48,49,51,52], the analytical hierarchy process (AHP), and the technique for order of preference by similarity to ideal solution (TOPSIS) and/or under fuzzy conditions [41][42][43]. From our literature review, a hybrid approach that combines the forecasting model GM (1, 1) and DEA Malmquist to predict and evaluate the performance of e-commerce companies has never been reported.…”

Section: Methodology Motivationmentioning

confidence: 99%

See 1 more Smart Citation

Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

et al. 2020

View full text Add to dashboard Cite

E-commerce has become an integral part of businesses for decades in the modern world, and this has been exceptionally speeded up during the coronavirus era. To help businesses understand their current and future performance, which can help them survive and thrive in the world of e-commerce, this paper proposes a hybrid approach that conducts performance prediction and evaluation of the e-commerce industry by combining the Grey model, i.e., GM (1, 1) and data envelopment analysis, i.e., the Malmquist-I-C model. For each e-commerce company, GM (1, 1) is applied to predict future values for the period 2020–2022 and Malmquist-I-C is applied to calculate the efficiency score based on output variables such as revenue and gross profit and input variables such as assets, liabilities, and equity. The top 10 e-commerce companies in the US market are used to demonstrate model effectiveness. For the entire research period of 2016–2022, the most productive e-commerce marketplace on average was eBay, followed by Best Buy and Lowe’s; meanwhile, Groupon was the worst-performing e-commerce business during the studied period. Moreover, as most e-commerce companies have progressed in technological development, the results show that the determinants for productivity growth are the technical efficiency change indexes. That means, although focusing on technology development is the key to e-commerce success, companies should make better efforts to maximize their resources such as labor, material and equipment supplies, and capital. This paper offers decision-makers significant material for evaluating and improving their business performance.

show abstract

Section: Methodology Motivationmentioning

confidence: 99%

Section: Methodology Motivationmentioning

confidence: 99%

Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

et al. 2020

View full text Add to dashboard Cite

show abstract

“…(5) This is the basic model of VAR, as the formula only has lagged endogenous variables, so that these lagged endogenous variables are asymptotic unrelated with t  . Then we can use OLS method to estimate each VAR formula, and the parameter estimators that we gat will be consistent [18].…”

Section: Vector Auto Regression Modelmentioning

confidence: 99%

The Research on the Relationship of Financial Expenditure, Real Estate Development and Economic Growth?An Empirical Study of Fujian Province

Zhang¹,

Wang

Li³

et al. 2015

IJUNESST

View full text Add to dashboard Cite

With Fujian Province as object of study, panel data from 1980 to 2013 is selected in this paper. Besides, VAR model is established. Co-integration test, Granger causality, impulse response function and variance decomposition are used for quantitative analysis on correlation between real estate development, financial expenditure and economic growth in Fujian Province. The research results show that long-term stable balance among real estate development, financial expenditure and economic growth in Fujian Province. Real estate development and financial expenditure are the Granger factors driving the growth of economic growth. Financial expenditure is the Granger reason for real estate development's development. On this basis, the author proposes some policies and recommendations for macroeconomic regulation and control in Fujian Province.

show abstract

“…In recent years, the shortage of water resources, the deterioration of water environment, water emergency has been profoundly endanger the safety of water supply China city (Chen and Zhou, 2014). In order to ensure sufficient supply of water resources, reduce water pollution, China has established a lot of water area and these areas are usually also is an important ecological barrier area and relatively poor regional economic (Luz et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Ecological Compensation Mechanism of Agricultural Water Resources: An Empirical Study in Zhejiang, China

Hu¹

2015

AJFST

View full text Add to dashboard Cite

Ecological compensation is a new area in the field of resources environment. In this study, we set an empirical analysis model about ecological compensation mechanism and analyze influential factors based on agricultural perspective. The result shows that: first, loss of development opportunities is the most important factor that will affect ecological compensation, the regression coefficient is 0.071; sec, environmental protection cost is the most significant variable in ecological compensation, the sig value is 0.007 and the regression coefficient is positive; third, public awareness has high coefficient value as 0.048, means that public awareness plays a positive effect. Overall, the regression model of the empirical results with the above assumptions, under the 10% significant level, the loss of development opportunities; environmental protection cost; the compensation standard; public awareness of the value of ecological environment variable are significantly variables that affecting ecological compensation and the effects of other variables are not obvious. On this basis, we put forward relevant suggestions.

show abstract

Evaluation of E-commerce Performance in SMEs based on Vector Auto Regression Model

Abstract: Abstract

Cited by 9 publications

References 4 publications

Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

The Research on the Relationship of Financial Expenditure, Real Estate Development and Economic Growth?An Empirical Study of Fujian Province

Ecological Compensation Mechanism of Agricultural Water Resources: An Empirical Study in Zhejiang, China

Contact Info

Product

Resources

About