Search results

In order to encourage the high-water-consumption (HWC) manufacturers to carry out water-saving transformation relying on self-strength or outsourcing to a water-saving service company (WSSC) during production processes, government subsidies are provided according to water-saving efforts (WSE) or investment cost. In this context, the authors derive the participant's equilibrium decisions and the manufacturer's water-saving strategy. Additionally, the effects of subsidies on WSE and stakeholders' profits are discussed.

Mathematical models including optimization model and Stackelberg game model are constructed under different subsidy schemes.

The study finds that (1) there exists a threshold related to the subsidy coefficient for the HWC manufacturer when choosing between self-saving and outsourcing-saving. (2) When the technological competitive advantage between WSSC and manufacturer is within a certain range, government's subsidy promotes HWC enterprises to choose outsourcing-saving. (3) Given a water-saving mode, subsidy on investment cost is more effective for the government to achieve more environmental performance.

First, subsidy endogeneity can be considered to explore the optimal interval for government subsidies to maximize social welfare. Second, in outsourcing-saving, other types of contract can be discussed. Another extension is about model uncertainties. Finally, other policies on improving water efficiency can be also examined.

The paper includes implication for HWC manufacturers to select the best water-saving mode under subsidy, and it allows policymakers to understand the efficiency of proposed subsidies.

Decisions on water-saving efforts, selection of water-saving modes and operational planning are also regarded as business strategies in the paper. Particularly, the influences of different government subsidies are also considered and compared.

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19. Furthermore, test the mediation effect of team climate and individual resilience in this relationship.

A survey of 347 expatriates in international construction projects was conducted. A cross-level chain mediation model was employed to test the moderating effect of social support and repatriation intention. Then, statistical analysis with a bootstrap sample was used to test the mediation effect of the model.

The empirical results support that team climate, individual resilience and the chain mediating effect of team climate to individual resilience is significant among the influences of social support on repatriation intention. Social support can enhance the team climate of construction expatriates, promoting their resilience to reduce the repatriation intention further.

This study provides guidelines for international construction enterprises and managers to decide when and which expatriates should return home and formulate a series of policies to support expatriates and maintain a good team climate.

This study contributes to expatriate management literature by establishing the relationship between social support and repatriation intention. It provides a better understanding of how team-level factors impact individual thought. It takes team climate as one of the protective factors affecting individual psychological resilience. Also it takes social support as the antecedents of team atmosphere in case of emergencies.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

This study aims to investigate NiTi alloys’ characterization and corrosion behaviour produced by two different powder metallurgy (PM) methods.

It was pre-formed under a protective atmosphere at 900 °C under a force of 45 MPa and sintered for 1 h under 10–6 Mbar in an atmosphere-controlled heat treatment furnace at 1,100 °C. The relationship between microstructural properties, SEM, XRD, density, microhardness and corrosion behaviour of pre-alloyed NiTi alloys produced by two different methods with the production method was investigated.

As a result of the studies, TiO, NiTi, NiTi2 and Ni3Ti intermetallics were determined in XRD examinations. The best surface roughness was observed in the mechanically milled (MM’ed) pre-alloyed NiTi alloy compared to the pre-alloyed NiTi alloy mixed with turbula. The corrosion tests performed in 3.5% NaCl solution determined that the MM’ed pre-alloyed NiTi alloy had better corrosion resistance than the pre-alloyed NiTi alloy mixed with turbula. Pitting corrosion was visualized in the SEM images taken from the corrosion surfaces.

Two different PM methods produced pre-alloyed NiTi powders, and the effects of these methods on the mechanical and corrosion resistance of NiTi alloys were systematically investigated for the first time.