Data as a Factor of Production Promoting the Deep Integration of the Digital Economy and the Real Economy:Theoretical Logic and Analysis Framework

Data is the primary factor of production in the digital economy,playing a role in promoting the deep integration of the digital economy and the real economy and smoothing the national economic cycle.After entering the circulation system of the real economy,data is rapidly integrated into production,circulation,consumption,distribution,and other links.It optimizes resource allocation,unblocks circulation channels,promotes accurate matching of supply and demand,stimulates emerging demand,and forms a virtuous circle of digital technology application,traditional physical enterprise transformation,and technological innovation.Integrated development is an important feature of the digital economy.Data promotes the integration of factors of production,products,enterprises,industries,and markets,which fosters a circular system with deep integration of the digital economy and the real economy.To promote the deep integration of the digital economy and the real economy,the government and business entities should take measures to improve the circular efficiency of the digital economy and the real economy.These measures include attaching importance to the role of data-driven development,improving data capacity,data development,and utilization in enterprises,exploring diverse circulation models of enterprise data,and creating typical application scenarios and industrial data spaces.

The Coupled Operational Systems:A Linear Optimisation Review

The purpose of this review is to summarise the existing literature on the operational systems as to explain the current state of understanding on the coupled operational systems.The review only considers the linear optimisation of the operational systems.Traditionally,the operational systems are classified as decoupled,tightly coupled,and loosely coupled.Lately,the coupled operational systems were classified as systems of time-sensitive and time-insensitive operational cycle,systems employing one mix and different mixes of factors of production,and systems of single-linear,single-linear-fractional,and multi-linear objective.These new classifications extend the knowledge about the linear optimisation of the coupled operational systems and reveal new objective-improving models and new state-of-the-art methodologies never discussed before.Business areas affected by these extensions include product assembly lines,cooperative farming,gas/oil reservoir development,maintenance service throughout multiple facilities,construction via different locations,flights traffic control in aviation,game reserves,and tramp shipping in maritime cargo transport.

Toward a research framework to conceptualize data as a factor of production:The data marketplace perspective

The widespread use of machine learning techniques and artificial intelligence algorithms has highlighted the strategic role of data.To acquire data for training algorithms and eventually empowering the digital transformation,data marketplaces are often required to support and coordinate cross-organizational data transactions.However,the prior industry practices have suggested that the transaction costs in the data marketplaces are severely high,and the supporting infrastructure is far from mature.This paper proposes a data attributes-affected data exchange(DADE)conceptual model to understand the challenges and directions for developing data marketplaces.Specifically,our model framework is built upon two dimensions,data lifecycle maturity and data asset specificity.Based on the DADE model,we propose four approaches for developing data marketplaces and discuss future research directions with an overview of computational methods as potential technical solutions.

What Implications Does COVID-19 Have on Sustainable Economic Development in the Medium and Long Terms?

Given the enormous impact that the COVID-19 pandemic had on China's economy,helping companies to revitalize post-pandemic economic activities promptly is a priority for the whole society.This necessitates the smooth circulation of production-factors among different economic entities,departments,and regions.The pandemic's huge impact on the economy is evident in the severely hampered flow of these factors,including labor,materials,and capital.Therefore,using data and digital technology,combined with a contact-free allocation of labor,capital,and materials,to accelerate the flow of production-factors is critical to the post-pandemic economy's restoration.Such a policy can not only provide a short-term stimulus but also a momentum for China's mid-and long-term sustainable economic development.