Analysis of the application of information technology in the management of rural population return based on the era of big data

Based on rural population return management, governance theory, and information technology theory, this paper analyzes the specific performance of rural areas in managing population return, and describes the overview, quantity, life status, and demographic characteristics of rural population return, as well as the current situation of rural population return management. A method of managing rural population return based on a rural population return management model constructed by a machine learning algorithm is designed. The empirical results show that the method designed in this paper is low-cost, fast, and highly accurate, and is well suited for improving and expanding the system for managing rural return flows. The research in this paper provides a reference for further promoting the transformation strategy of rural governance in the context of new urbanization.

Digital Innovation Risk Management Model of Discrete Manufacturing Enterprise Based on Big Data Analysis

At present, most risk management work mainly relies on manpower, and manpower relies on the professional knowledge of relevant skilled workers to discover hidden safety risks in production activities. This article combines relevant big data theories and 4V characteristics to analyze and investigate safety production and big data, study data structure, data source and data type. Using 5W1H scientific big data and applications, this analysis method analyzes the theoretical basis, applications and beneficiaries of big data related to safety production, some of which are application links and important theoretical issues. Secondly, it studies the security risk management model based on big data, proposes a risk management model based on big data, the technical basis of big data and the idea of a three-dimensional model, and applies the systematic space method, which is reflected in three aspects of risk management. In the end, a risk identification model based on big data, a risk assessment classification model, and a risk early warning and pre-control model are defined.

Construction and Optimization of Green Supply Chain Management Mode of Agricultural Enterprises in the Digital Economy

Digital economy is a rapidly developing economic form under the background of the information age. This article introduces the construction and optimization of the green supply chain management model of agricultural enterprises under the digital economy, and intends to provide some ideas and directions for the development of green supply chain management of agricultural enterprises based on digital economy. This paper proposes the construction and optimization research methods of the green supply chain management model of agricultural enterprises under the digital economy, including the overview of green supply chain management, the construction of the optimization management model of the green supply chain of agricultural enterprises, and the digital economy under the construction of a green supply chain management practice index system for agricultural enterprises. Experimental results show that average Cronbachα value of each scale factor of the optimized management model in this paper is 0.876, and optimized decision-making coordination mechanism has high internal consistency.

Understanding crisis resilience in manufacturing firms in the DACH region during the COVID-19 pandemic

PurposeThis paper describes the impact of COVID-19 on manufacturing firms in the DACH region of Europe (DACH is an acronym used to describe Germany, Austria and Switzerland). The purpose of the study was threefold: first to describe crisis resilience empirically through the actions taken by the firms using the elements of resilience; the paper then goes on to compare the DACH region with Northern Italy; finally, based on the findings, an existing crisis management model is expanded.Design/methodology/approachA mixed method of quantitative research based on survey data and qualitative interviews was applied for data collection. The findings are based on 57 survey results and 13 interviews from December 2020 to March 2021. The findings are presented based on the resilience elements and are discussed based on processes, technologies and people. The findings are compared with those from an Italian study made 6–9 months before this study. The comparison provides the basis for the adaptations to the crisis management model.FindingsThe findings describe the actions taken by firms in the DACH region to overcome the challenges posed by COVID-19. The findings were, in most cases, very similar to those from the Italian study. The most resilient firms had well-defined processes in place, adaptable employees who were well-led, and had (digital) technologies that could be quickly implemented.Originality/valueThe timing for the crisis was later in the DACH region and firms were able to learn from Italy. The crisis management model based on the Italian study was refined; the resulting model will support managers to face future crises. This model needs testing and extending to link to past and future events.

Coordinated Development of Population, Resources, Environment, Economy, and Society under Engineering Management Combined with Bilevel Optimization Model

The in-depth analysis of the strategies for the coordinated and continuous development of population, resources, environment, economy, and society based on the engineering management model is highly important for the sustainable development of the regional economy and society. In this article, a population-economy-resources-environment bilevel optimization model is established based on the economic and social development in a provincial region. The method of bilevel optimization is adopted to introduce the specific bilevel optimization model. The concept and objectives of the bilevel optimization are explained, and its corresponding technical applications are described. In this article, the development in coordinated economic and social development of population, resources, and environment is analyzed and compared based on the bilevel optimization model. In particular, the evolution and changes before and after the implementation of engineering management are studied. Through the results, it can be observed that after the implementation of project management, the coefficient of industry location has presented a downward trend, and the coordinated development of population, resources, environment, economy, and society has become more coordinated.

Knowledge Management Model for Smart Campus in Indonesia

The application of smart campuses (SC), especially at higher education institutions (HEI) in Indonesia, is very diverse, and does not yet have standards. As a result, SC practice is spread across various areas in an unstructured and uneven manner. KM is one of the critical components of SC. However, the use of KM to support SC is less clearly discussed. Most implementations and assumptions still consider the latest IT application as the SC component. As such, this study aims to identify the components of the KM model for SC. This study used a systematic literature review (SLR) technique with PRISMA procedures, an analytical hierarchy process, and expert interviews. SLR is used to identify the components of the conceptual model, and AHP is used for model priority component analysis. Interviews were used for validation and model development. The results show that KM, IoT, and big data have the highest trends. Governance, people, and smart education have the highest trends. IT is the highest priority component. The KM model for SC has five main layers grouped in phases of the system cycle. This cycle describes the organization’s intellectual ability to adapt in achieving SC indicators. The knowledge cycle at HEIs focuses on education, research, and community service.

Flood Control and Aquifer Recharge Effects of Sponge City: A Case Study in North China

Sponge City is an integrated urban stormwater management approach and practice to tackle waterlogging, flooding, water scarcity, and their related problems. Despite many positive effects of Sponge City on flood control that have been investigated and revealed, the effect on aquifer recharge is still less known. Considering maximizing the function of natural elements such as surface water bodies and subsurface storage space, to minimize the use of a gray drainage system, a Sponge City design was proposed to substitute the planning development scheme in the study area. The stormwater management model of SWMM (storm water management model) and the groundwater flow model of MODFlow (Modular Three-dimensional Finite-difference Groundwater Flow Model) were adopted to evaluate the flood-control effect and aquifer-recharge effect, respectively. Compared with the traditional planning scenario, the peak runoff is approximately 92% less than that under the traditional planning scenario under the condition of a 5-year return period. Due to the increase in impervious areas of urban construction, the total aquifer recharge from precipitation and surface water bodies was decreased both in the present planning scenario and the Sponge City design scenario. However, the Sponge City design has a positive impact on maintaining groundwater level stabilization and even raises the groundwater level in some specific areas where stormwater seepage infrastructure is located.