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As global supply chains continue to develop, uncertainty grows and supply chains are frequently threatened with disruption. Although big data technology is being used to improve supply chain resilience, big data technology's role in human–machine collaboration is shifting between “supporters” and “substitutes.” However, big data technology's applicability in supply chain management is unclear. Choosing appropriate big data technology based on the enterprise's internal and external environments is important.

This study built a three-factor structural model of the factors “management support,” “big data technology adoption” and “supply chain resilience”. Big data technology adoption was divided into big data-assisted decision-making technology (ADT) and big data intelligent decision-making technology (IDT). A survey was conducted on more than 260 employees from supply chain departments in Chinese companies. The data were analyzed through structural equation modeling using Analyze of Moment Structures (AMOS) software.

The study's empirical results revealed that adopting both ADT and IDT improved supply chain resilience. The effects of both types of big data were significant in low-dynamic environments, but the effect of IDT on supply chain resilience was insignificant under high-dynamic environments. The authors also found that government support had an insignificantly effect on IDT adoption but significantly boosted ADT adoption, whereas management support factors promoted both ADT and IDT adoption.

By introducing two types of big data technology from the perspectives of the roles in human–machine collaborative decision-making, the research results provide a theoretical basis and management implications for enterprises to reduce the supply chain risk of enterprises.

The purpose of this paper is to examine the relationship between school climate and teacher stress. Specifically, the authors construct two parsimonious models to test two main hypotheses. First, whether preschool collegial leadership predicts teachers’ job stress through the mediating role of teacher self-efficacy; second, whether teacher professionalism influences teachers’ perceptions of occupational stress through the mediating role of teacher self-efficacy.

The authors conceptualized the mediating role of teacher efficacy as an important mechanism that can help to explain the effect of school climate on teacher stress. School climate consisted of two dimensions: principal collegial leadership and professionalism. Therefore, the authors constructed and examined two mediation models by using Bootstrapping mediation modeling: first, preschool teacher self-efficacy as a mediator between preschool collegial leadership and teacher stress; second, preschool teacher self-efficacy as a mediator between preschool teacher professionalism and teacher stress.

Results from two mediation analyses showed that principal collegial leadership exerts a significant negative effect on preschool teachers’ stress through the mediating role of teacher self-efficacy. Moreover, professionalism was also a significant predictor of preschool teachers’ stress through the mediating role of teacher self-efficacy.

This study contributes to the literature in terms of understanding the mechanism of how school climate helps to reduce teacher stress. First, the authors found that teachers’ individual well-being can be efficiently enhanced through a more collegial leadership. Second, the preschool leadership teams can create a supportive climate to reduce teachers’ stress by improving teachers’ professionalism.

This study offers a new perspective about understanding the internal and external mechanism of teacher stress. The authors discussed the results in light of the recent push by the Chinese Government to teacher quality improvement in early childhood education. The authors argued for prioritizing support for building a supportive school climate for teachers.

The ancient town of Lijiang is a representative place of ethnic minorities in China’s southwest border area jointly built by many ethnic groups. Its rich and diversified history, culture and architecture as well as its artistic and spiritual values need to be better retained and explored.

The protection and inheritance of Lijiang’s cultural heritage will be improved through the construction of digital memory resources. To guide Lijiang’s digital memory construction, this study explores strategies of digital memory construction by analyzing four case studies of well-known memory projects from China and America.

From the case studies analysis, factors of digital memory construction were identified and compared. Factors led to the discussion of strategies for constructing the digital memory of Lijiang within its design, construction and service phases.

The ancient town of Lijiang is a famous historical and cultural city in China, and it is also a representative place of ethnic minorities in the border area jointly built by many ethnic groups. The rich culture should be preserved and digitalized to offer better use for the whole nation.

The purpose of this paper is to investigate three issues: how does an innovative search (local search and boundary-spanning search) impact firm innovation performance of latecomers; how does capability reconfiguration (capability evolution and capability substitution) mediates the relationship between innovative search and firm innovation performance; and how does the technological leapfrogging process (initial stage, following stage, synchronization stage and leading stage) moderate the relationship between capability reconfiguration and firm innovation performance.

A “resource-capability-performance” theoretical framework was developed to explore the relationships between local/boundary-spanning search, capability reconfiguration and firm innovation performance. The data were collected by sending out surveys to managers and employees in various industries in mainland China. These hypotheses were tested using structural equation models and hierarchical regressions.

The results showed that: innovative search has a direct causal relationship to capability reconfiguration; local search and boundary-spanning search are conducive to improve the innovation performance of latecomers; the impact of local search and boundary-spanning search on innovation performance is realized through the completion of mediating role of capability reconfiguration; there are differences in the path of local search and boundary-spanning search affecting the capability reconfiguration of enterprise innovation performance; and the relationship between innovative search, capability reconfiguration and enterprise innovation performance evolves with the enterprise in different stages of technological leapfrogging.

This study explores the relationship and the path of innovative search to firm innovation performance and analyzes the path difference between local search and boundary-spinning search, which enriches the research of organizational search and enterprise innovation. This paper reveals the whole path of innovative search affecting innovation performance, discusses the important role of capability reconfiguration and makes incremental contributions to dynamic capability theory. It studies the evolution of innovative search on innovation performance under the background of technological leapfrogging, which provides a new perspective for the study of organizational search and capability-based theory.

This paper describes the results of non-linear elasto-plastic implicit dynamic finite element analyses that are used to predict the collapse behaviour of cold-formed steel portal frames at elevated temperatures. The collapse behaviour of a simple rigid-jointed beam idealisation and a more accurate semi-rigid jointed shell element idealisation are compared for two different fire scenarios. For the case of the shell element idealisation, the semi-rigidity of the cold-formed steel joints is explicitly taken into account through modelling of the bolt-hole elongation stiffness. In addition, the shell element idealisation is able to capture buckling of the cold-formed steel sections in the vicinity of the joints. The shell element idealisation is validated at ambient temperature against the results of full-scale tests reported in the literature. The behaviour at elevated temperatures is then considered for both the semi-rigid jointed shell and rigid-jointed beam idealisations. The inclusion of accurate joint rigidity and geometric non-linearity (second order analysis) are shown to affect the collapse behaviour at elevated temperatures. For each fire scenario considered, the importance of base fixity in preventing an undesirable outwards collapse mechanism is demonstrated. The results demonstrate that joint rigidity and varying fire scenarios should be considered in order to allow for conservative design.

Reconfigurability of the assembly fixtures, which enables a set of sheet metal automotive parts to be produced on a single production line, is becoming crucial to maintaining competitiveness in the rapidly changing market. One of the key issues in reconfigurable fixture design is to identify the fixture configuration and make sure there is enough workspace for a family of parts. The purpose of this paper is to address this issue, through the design and analysis of two novel reconfigurable fixturing robots.

Following an introduction, the application of the reconfigurable fixturing robot addressed in this paper is described; it is characterized by using parallel manipulator as programmable fixture elements. Kinematic design and reconfigurable design of the fixturing robot is presented based on screw theory and modularized design, respectively.

The proposed reconfigurable fixturing robots can transform their configurations with 4 DoF (degrees‐of‐freedom), and have a continuous workspace for their application.

Reconfigurability of the assembly fixtures is an important issue for automotive manufacturing, due to the highly competitive nature of this industry. The proposed reconfigurable fixturing robots can greatly facilitate the development of new models of vehicles.

The purpose of this study is to assess the impact of land rights and tenure types on farmers' investment behavior in Chinese collective forests, using household survey data from Fujian Province.

In this study, the authors conducted a household survey in Fujian province of 520 randomly selected forest farmers. The authors used a random‐effects Tobit model to estimate the impact of land rights and other components on, for example, tenure security and harvest quota, and the impact of tenure types on farmers' investment incentives.

This study produced three main findings: perceived tenure security in the context of frequent agricultural land redistribution negatively affects input intensity; farmers still perceive some tenure arrangements to be more uncertain than others, which discourages them from undertaking investments on such plots; and the harvest quota regulation, introduced to conserve forest stock, has in fact acted as a disincentive in forestry management.

Almost all previous studies are based on national or regional data, which have primarily focused on the links between tenure types and investment incentives. In this study, based on the plot‐level data, the authors are able to assess not only the impacts of tenure types but also how specific land rights and their components affect farmers' investment behavior.

The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India.

Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location.

Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region.

Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model.

The findings provide valuable results to be considered for controlling air pollution in the region.

Sustainable development requires businesses to improve their positive and reduce their negative impacts. This chapter discusses how the impact of business on sustainable development can be measured and managed using the sustainable development goals (SDGs). First, it introduces two complementary approaches for measuring impact: a top-down approach that departs from the economic activities that companies undertake; and a bottom-up approach that defines the impacts of individual companies. Second, it argues that companies can manage their impacts on the SDGs through a nexus approach. Instead of treating SDGs as isolated silos, a nexus approach aims to advance multiple SDGs simultaneously (creating co-benefits) while reducing the risk that contributions to one SDG undermine progress on another (avoiding trade-offs).