Soil carbon and its associate resilience using big data analytics: For food Security and environmental management

Hinge, Gilbert; Surampalli, Rao Y.; Goyal, Manish Kumar; Gupta, Brij B.; Chang, Xiaojun

doi:10.1016/j.techfore.2021.120823

Cited by 21 publications

(10 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Canada, Big Data consists of several data layers (Hinge et al , 2021). The first step toward realizing the full potential of Big Data is to integrate different data sets and make them simply and rapidly accessible.…”

Section: Literature Reviewmentioning

confidence: 99%

Big Data analytics and financial reporting quality: qualitative evidence from Canada

Saleh

Marei

Ayoush

et al. 2022

JFRA

View full text Add to dashboard Cite

Purpose Big Data analytics (BDA) and its implications for the accounting profession continue to be a key issue that requires more research and evaluation. As a result, the purpose of this study is to evaluate the impact of BDA on financial reporting quality, as well as to assess the accounting challenges associated with Big Data. It provides qualitative evidence from Canada. Design/methodology/approach This study used a qualitative approach to ascertain the thoughts and perceptions of auditors, financial analysts and accountants at Canadian audit and accounting firms in BDA and its impact on financial reporting quality, using semi-structured interviews. To obtain their consent to participate in the interview, 127 auditors, financial analysts and accountants from Canadian audit and accounting firms were initially approached. The final number of respondents was 41, representing a response rate of 32%. Findings The authors’ findings underscored the relevance of Big Data and BDA in affecting financial report quality and revealed that BDA had a significant effect on improving financial reporting quality. Big Data improves accounting reporting and expert judgment by providing professional. In summary, participants agreed that when analytical methods in Big Data are implemented effectively, businesses may possibly achieve a variety of benefits, including customized goods, simplified processes, improved risk assessment process and, finally, increased risk management. Practical implications The authors’ findings indicate that BDA may help predict investment returns and risks, estimate future investment opportunities, forecast revenues, detect fraud and susceptibility early and identify economic growth opportunities. As a result, auditors, financial analysts, accountants, investors and other strategic decision-makers should be aware of these findings to make informed choices. Originality/value Big Data has become the norm in recent years; accountants and other decision-makers have struggled to analyze massive amounts of data. This limits their capacity to profit from such data even more. Therefore, this study is motivated by the lack of research on Big Data’s influence on financial report quality.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Big Data analytics and financial reporting quality: qualitative evidence from Canada

Saleh

Marei

Ayoush

et al. 2022

JFRA

View full text Add to dashboard Cite

show abstract

“…The literature points out that there are many digital solutions that allow data to be assimilated, that is, artificial intelligent (He et al , 2010; Dubey et al , 2020), the IoT (Côrte-Real et al , 2020), big data analytics (Berger et al , 2015; Edwards et al , 2017; Grover et al , 2018; He et al , 2017; Hinge et al , 2021; Janssen et al , 2017; Lehrer et al , 2018; Martinez and Walton, 2014; Matthias et al , 2017; O’Connor and Kelly, 2017; Opresnik and Taisch, 2015; Wang and Byrd, 2017; Nguyen Dang Tuan et al , 2019; Shamim et al , 2019; Côrte-Real et al , 2020; Dong and Yang, 2020; Hallikainen et al , 2020; Hung et al , 2020; Sivarajah et al , 2020; Gupta et al , 2020; Ghasemaghaei and Calic, 2019; Ghasemaghaei and Calic, 2020; Yasmin et al , 2020; Wamba et al , 2020; Dubey et al , 2020), cloud solutions (Marston et al , 2011), machine learning (Beque and Lessmann, 2017; Salminen et al , 2019) and wearable technology (Chaffin et al , 2017). Most of the studies show the key role of big data analytics solutions in explaining the assimilation of data.…”

Section: Resultsmentioning

confidence: 99%

Industry 4.0 transition: a systematic literature review combining the absorptive capacity theory and the data–information–knowledge hierarchy

Ardito

Cerchione

Mazzola

et al. 2021

JKM

View full text Add to dashboard Cite

Purpose The effect of the transition toward digital technologies on today’s businesses (i.e. Industry 4.0 transition) is becoming increasingly relevant, and the number of studies that have examined this phenomenon has grown rapidly. However, systematizing the existing findings is still a challenge, from both a theoretical and a managerial point of view. In such a setting, the knowledge management (KM) discipline can provide guidance to address such a gap. Indeed, the implementation of fundamental digital technologies is reshaping how firms manage knowledge. Thus, this study aims to critically review the existing literature on Industry 4.0 from a KM perspective. Design/methodology/approach First, the authors defined a structuring framework to highlight the role of Industry 4.0 transition along with absorptive capacity (ACAP) processes (acquisition, assimilation, transformation and exploitation), while specifying what is being managed, that is data, information and/or (actual) knowledge, according to the data-information-knowledge (DIK) hierarchy. The authors then followed the systematic literature review methodology, which involves the use of explicit criteria to select publications to review and outline the stages a process has to follow to provide a transparent and replicable review and to analyze the existing literature according to the theoretical framework. This procedure yielded a final list of 150 papers. Findings By providing a clear picture of what scholars have studied so far on Industry 4.0 transition, in terms of KM, this literature review highlights that among all the studied digital technologies, the big data analytics technology is the one that has been explored the most in each phase of the ACAP process. A constructive body of research has also emerged in recent years around the role played by the internet of things, especially to explain the acquisition of data. On the other hand, some digital technologies, such as cyber security and smart manufacturing, have largely remained unaddressed. An explanation of the role of these technologies has been provided, from a KM perspective, together with the business implications. Originality/value This study is one of the first attempts to revise the literature on Industry 4.0 transition from a KM perspective, and it proposes a novel framework to read existing studies and on which to base new ones. Furthermore, the synthesis makes two main contributions. First, it provides a clear picture of the different digital technologies that support the four ACAP phases in relation to the DIK hierarchy. Accordingly, these results can emphasize what the literature has looked at so far, as well as which digital technologies have gained the most attention and their impacts in terms of KM. Second, the synthesis provides prescriptive considerations on the development of future research avenues, according to the proposed research framework.

show abstract

“…, 2023), the low-carbon production decision of cold chain of fresh products has increasingly become a research hotspot. Unlike other industries, fresh cold chain low-carbon carbon (Hinge et al. , 2021) has fewer means of carbon sequestration, mainly through carbon emission reduction to reduce carbon emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With the development of low-carbon economy, while taking into account the health of food (Nahar et al, 2023), the low-carbon production decision of cold chain of fresh products has increasingly become a research hotspot. Unlike other industries, fresh cold chain low-carbon carbon (Hinge et al, 2021) has fewer means of carbon sequestration, mainly through carbon emission reduction to reduce carbon emissions. Table 1 summarizes the relevant papers on low-carbon decision-making in the cold chain of fresh products.…”

Section: Literature Reviewmentioning

confidence: 99%

An optimal decision for fresh products' cold chain considering freshness and carbon emission reduction

Liu,

Huang,

Han

et al. 2024

BFJ

Self Cite

View full text Add to dashboard Cite

PurposeThe aim of this study was to analyze the effects of carbon reduction efforts and preservation efforts on system benefits in the cold chain industry of fresh products.Design/methodology/approachThis study develops an optimal decision game model for the fresh products in the cold chain, incorporating the retailer's preservation effort and the supplier's carbon emission reduction effort. It quantifies the relationship between carbon emission reduction effort, preservation effort and system profit. The model considers parameters like carbon trading price, consumer low-carbon preference and consumer freshness preference, reflecting real-world conditions and market trends. Numerical simulations are conducted by varying these parameters to observe their impact on system profit.FindingsUnder the carbon cap-and-trade policy, the profit of the fresh cold chain system is higher than that of the fresh cold chain system without carbon constraints, and the profit of the supplier under decentralized decision-making is increased by nine times in the simulation results. The increase in carbon trading prices can effectively improve the freshness level of fresh products cold chain, carbon emission reduction level and system profit.Originality/valueThis study comprehensively considers the factors of freshness and carbon emission reduction, provides the optimal low-carbon production decision-making reference for the fresh food cold chain and promotes the sustainable development of the fresh food cold chain.

show abstract

Soil carbon and its associate resilience using big data analytics: For food Security and environmental management

Cited by 21 publications

References 60 publications

Big Data analytics and financial reporting quality: qualitative evidence from Canada

Big Data analytics and financial reporting quality: qualitative evidence from Canada

Industry 4.0 transition: a systematic literature review combining the absorptive capacity theory and the data–information–knowledge hierarchy

An optimal decision for fresh products' cold chain considering freshness and carbon emission reduction

Contact Info

Product

Resources

About