Search results

Previous studies have proposed that correctly managing stakeholders with certain attributes can benefit project management; however, robust theoretical elaborations and empirical investigations of this topic have been lacking. The purpose of this study is to empirically test the effects of two stakeholder attributes – contractor-perceived contractor salience and contractor project position – on the criticality of five typical contractor-related risks: risk of (1) injuries and accidents, (2) quality defects, (3) work delays, (4) cost overruns and (5) breaches of contract.

Questionnaire data were collected from 118 Chinese contractor managers. Regression models were run in Mplus 7.11 to test the hypotheses.

The data show that higher contractor-perceived contractor salience and a more supportive contractor project position were both related to lower criticality of contractor-related risks, including risk of (1) injuries and accidents, (2) quality defects, (3) work delays, (4) cost overruns and (5) breaches of contract. Contractor salience also mediated the negative relationship between a supportive contractor project position and the criticality of contractor-related risks.

The authors’ research design is cross-sectional and thus cannot establish causation in the relationships among the studied variables. The single item measure of contractor project position was used for the first time in the present study; thus, its reliability and validity still await more empirical examinations.

The findings advance the understanding of the value of stakeholder management in projects by specifying that prioritizing stakeholders' claims and securing their support for the project reduce the criticality of stakeholder-related risks. By providing empirical evidence from the construction context, the findings also add to knowledge on the instrumental power of stakeholder management in enhancing project risk management performance.

The 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.

This 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.

Under 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.

This 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.

The purpose of this paper is to examine the influence of human resource management (HRM) reforms on job-related well-being of academics in Chinese universities. It also tests the mediating effect of work intensification (WI) and affective commitment (AC), and the moderating effect of perceived organizational justice (OJ) on the HRM‒well-being relationship to understand the influence mechanisms and boundary conditions.

A questionnaire survey was conducted in 25 Chinese universities, obtaining 638 usable questionnaires. Structural equation modeling (SEM) was used as the analytical technique to examine the model fit and test hypotheses.

The findings reveal that the relationship of HRM and well-being is neither direct nor unconditional, and a win‒win scenario for both management and employee well-being is possible when organizations pursue HRM innovations.

The limitations of this study are that data were collected at once and at a defined time, with no time lag being involved. In addition, all variables were self-reported.

Commitment-oriented HRM practices can create a win‒win scenario; when control-oriented HRM practices are necessary, managers should ensure OJ to offset their negative influence on employees.

This study is among the first to examine the impact of HRM on employee well-being in the context of Chinese higher education, contributing to the limited studies on HRM in Chinese public sector and the on-going debate on the nature of HRM in China.

The purpose of this paper is to present some dynamic hesitant fuzzy aggregation operators to tackle with the multi-period decision-making problems where all decision information is provided by decision makers in hesitant fuzzy information from different periods.

First, the notions and operational laws of the hesitant fuzzy variable are defined. Then, some dynamic hesitant fuzzy aggregation operators involve the dynamic hesitant fuzzy weighted averaging (DHFWA) operator, the dynamic hesitant fuzzy weighted geometric (DHFWG) operator, and their generalized versions are presented. Some desirable properties of these proposed operators are established. Furthermore, two linguistic quantifier-based methods are introduced to determine the weights of periods. Next, the paper extends the results to the interval-valued hesitant fuzzy situation. Furthermore, the authors develop an approach to solve the multi-period multiple criteria decision making (MPMCDM) problems. Finally, an illustrative example is given.

The presented hesitant fuzzy aggregation operators are very suitable for aggregating the hesitant fuzzy information collected at different periods. The developed approach can solve the MPMCDM problems where all decision information takes the form of hesitant fuzzy information collected at different periods.

The presented hesitant fuzzy aggregation operators and decision-making approach can widely apply to dynamic decision analysis, multi-stage decision analysis in real life.

The paper presents the useful way to aggregate the hesitant fuzzy information collected at different periods in MPMCDM situations.

Mobile technologies have recently come to serve as the primary reservation option for the hospitality industry. This study examines the role of online experience in determining potential consumers' perceived hotel brand image, through a three-stage model based on the stimulus–organism–response (SOR) framework.

A dual-stage analytical procedure, including structural equation modeling (SEM) and an artificial neural network (ANN) approach, was adopted to test the hypotheses.

Online experience of mobile applications (apps) can be influenced by perceived usefulness. As the indivisible component of consumers' cognitive beliefs, perceived ease of use exerts a positive impact on online experience. The online experience of mobile apps positively influenced brand awareness and satisfaction, further contributing to potential consumers' brand image formation.

This study empirically verified the relationships among potential hotel consumers' perceptions of official hotel mobile app quality, online experience and brand image.

This study reiterates the importance of official hotel apps in implementing online marketing strategies, suggesting that hoteliers should pay attention to enhancing the quality of their official apps.

This study is one of the first to combine machine learning techniques with the traditional SEM approach to assess linear and nonlinear relationships in consumers' perceptual models. Additionally, the findings provide theoretical insights into the online experience of mobile apps and reveal the perceived brand image formation process of potential consumers.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.

This paper aims to report on the experiments with the Contour Crafting Automated Construction process using sulfur concrete as the choice of construction material.

Several experiments have been performed at centimeter and meter scales. A finite element analysis simulation model for the behavior of sulfur concrete-based structures has been developed. Experimental results were compared with the results of simulation.

Sulfur concrete has numerous terrestrial applications and is potentially an ideal construction material for planetary construction.

Experimental samples of sulfur concrete were fabricated using a novel mixer/extrusion system. The mechanism was proven to be durable and stable after more than 500 h of work.

In this paper the aim is that Aramid/alginate blended nonwoven fabrics were prepared, and the flame retardancy of the blended nonwoven fabrics was studied by thermogravimetric analysis, vertical flame test, limiting oxygen index (LOI) and cone calorimeter test.

The advantages of different fibers can be combined by blending, and the defects may be remedied. The study investigates whether incorporating alginate fibers into aramid fibers can enhance the flame retardancy and reduce the smoke production of prepared aramid/alginate blended nonwoven fabrics.

Thermogravimetric analysis indicated that alginate fibers could effectively inhibit the combustion performance of aramid fibers at a higher temperature zone, leaving more residual chars for heat isolation. And vertical flame test, LOI and cone calorimeter test testified that the incorporation of alginate fibers improved the flame retardancy and fire behaviors. When the ratio of alginate fibers for aramid/alginate blended nonwoven fabrics reached 80%, the incorporation of alginate fibers could notably decreased peak-heat release rate (54%), total heat release (THR) (29%), peak-smoke production rate (93%) and total smoke production (86%). What is more, the lower smoke production rate and lower THR of the blends vastly reduced the risk of secondary injury in fires.

This study proposes to inhibit the flue gas release of aramid fiber and enhance the flame retardant by mixing with alginate fiber, and proposes that alginate fiber can be used as a biological smoke inhibitor, as well as a flame retardant for aramid fiber.