Evaluation of food security based on DEA method: a case study of Heihe River Basin

Zhan, Jinyan; Zhang, Fan; Li, Zhihui; Zhang, Yue; Qi, Wei

doi:10.1007/s10479-018-2889-9

Cited by 15 publications

(4 citation statements)

References 34 publications

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“…Productivity also heavily depends on the climate conditions, and thus a change in climate to higher temperatures or frequent extreme weather conditions can have a major impact on productivity. There is a need to investigate the impact of possible climate change scenarios on food production and food security (Zhan et al., 2020). We next focus on emerging themes and opportunities for future research.…”

Section: Operational Efficiency In Farmingmentioning

confidence: 99%

Opportunities in farming research from an operations management perspective

Gupta

Berenji

Shukla

et al. 2023

Production and Operations Management

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We review and analyze the farming (upstream agribusiness supply chain) research literature since 1965 to identify farming research opportunities for operations management (OM) researchers. A majority of reviewed papers in our corpus, until the turn of the 21st century, primarily focus on improving operational efficiency and effectiveness of farming using optimization techniques. However, during the last two decades, farmers’ welfare and the interests of other stakeholders have drawn OM researchers’ attention. This expanded focus on farming research has become possible due to the proliferation of mobile communication devices and the Internet as well as advancements in information technology platforms and social media. Our review also shows that there is a paucity of OM literature that leverages increased data availability from the emergence of precision agriculture and blockchain to address major challenges for the farming sector emanating from climate change, natural disasters, food security, and sustainable and equitable agriculture, among others. Big data, in conjunction with opportunities for field‐based experimentation, artificial intelligence and machine learning, and integration of predictive and prescriptive analytics, can be leveraged by OM scholars engaged in farming research. We zero in on specific questions, issues, and opportunities for research in farming.

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Section: Operational Efficiency In Farmingmentioning

confidence: 99%

Opportunities in farming research from an operations management perspective

Gupta

Berenji

Shukla

et al. 2023

Production and Operations Management

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“…Given that, the particular approach has been widely adopted in related studies of TFP. Most scholars employing the DEA-Malmquist productivity index to study TFP in China's agriculture concluded that agricultural TFP was mainly driven by TC and that the decrease of EC was in sync with that of TC for most parts of China [13,14]. e paper, therefore, attempts to employ the DEA-Malmquist indexbased approach to decompose agricultural TFP of Hubei into TC and EC.…”

Section: Literature Reviewmentioning

confidence: 99%

Research of Total Factor Productivity and Agricultural Management Based on Malmquist-DEA Modeling

Wan

Zhou

2021

Mathematical Problems in Engineering

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Based on the Malmquist-DEA Modeling and drawing on the data from 12 cities in Hubei, a central province of China, this paper measures the total factor productivity (TFP) of agricultural management as well as technological change (TC) and technical efficiency change (EC). The Cobb–Douglas (C-D) production function is adopted to empirically estimate the impacts of TFP and its constituent elements on the agricultural management and economic growth comprehensively and further study the effects on different regions in Hubei. The results demonstrate that TC grows at an annual average rate of 6.7% and drives agricultural TFP growth in Hubei. The decline in scale efficiency accounts for the drop of 1.1% of EC. The agricultural TFP growth rates among different regions vary remarkably but overall have a positive and significant effect on agricultural output. The research sheds light on the analysis of agricultural development of Hubei according to the findings based on Malmquist-DEA Modeling and provides practical implications for the future management.

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“…Among others, the study contributes by employing a big data sample that closely represents the population. Taking the Heihe River Basin (HRB) as a case study area and using DEA and the Malmquist index, Zhan et al (2020) analysed the agricultural production efficiency in the HRB and further aimed to identify what was the role played by big data in the assessment of food security. developed a new methodology for rural transportation management which takes into consideration both the equity and cost factors under multiple objectives.…”

Section: Herranz Et Al (2017) Used Principal Component Analysis Dea and Artificialmentioning

confidence: 99%

Data Envelopment Analysis and Big Data: A Systematic Literature Review with Bibliometric Analysis

Charles

Gherman

Zhu

2021

International Series in Operations Research &Amp; Management Science

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Data envelopment analysis (DEA) is a powerful data-enabled, big data science tool for performance measurement and management, which over time has been applied across a myriad of domains. Over the past years, various advancements in big data have captured the attention of DEA scholars, which in turn, has translated into the emergence of new research strands. In the present work, we perform a systematic literature review with bibliometric analysis of studies integrating DEA with big data, in an attempt to answer the question: what are the current avenues of research for such studies? The results obtained are further complemented with a thematic analysis. Among others, findings indicate that big data is still a new entrant within the DEA literature, that most of the studies have focused on developing faster and more accurate computational techniques to handle problems with a large number of decision-making units (DMUs), and that most of the studies have been carried out in the area of environmental efficiency evaluation. This work should contribute to the construction of an overview of the existing literature on DEA-big data studies, as well as stimulate the interest in the topic.

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Evaluation of food security based on DEA method: a case study of Heihe River Basin

Cited by 15 publications

References 34 publications

Opportunities in farming research from an operations management perspective

Opportunities in farming research from an operations management perspective

Research of Total Factor Productivity and Agricultural Management Based on Malmquist-DEA Modeling

Data Envelopment Analysis and Big Data: A Systematic Literature Review with Bibliometric Analysis

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